A EPA
EPA/635/R-23/148a
External Review Draft
www.epa.gov/iris
IRIS Toxicological Review of Perfluorohexanesulfonic Acid
(PFHxS, CASRN 335-46-4) and Related Salts
July 2023
Integrated Risk Information System
Center for Public Health and Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
DISCLAIMER
This document is a preliminary draft for review purposes only. This information is
distributed solely for the purpose of pre-dissemination peer review under applicable information
quality guidelines. It has not been formally disseminated by EPA. It does not represent and should
not be construed to represent any Agency determination or policy. Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.
This document is a draft for review purposes only and does not constitute Agency policy.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
CONTENTS
CONTENTS iii
AUTHORS | CONTRIBUTORS | REVIEWERS xi
EXECUTIVE SUMMARY xiii
ES.l Lifetime and Subchronic Oral Reference Dose (RfD) for Noncancer Effects xvi
ES.2 Confidence in the Oral Reference Dose (RfD) and subchronic RfD xvi
ES.3 Noncancer Effects Following Inhalation Exposure xvi
ES.4 Evidence for Carcinogenicity xvii
1. OVERVIEW OF BACKGROUND INFORMATION AND ASSESSMENT METHODS 1-1
1.1. BACKGROUND INFORMATION ON PERFLUOROHEXANESULFONIC ACID (PFHXS) 1-1
1.1.1. Physical and Chemical Properties 1-1
1.1.2. Sources, Production, and Use 1-3
1.1.3. Environmental Fate and Transport 1-4
1.1.4. Potential for Human Exposure and Populations with Potentially Greater Exposure 1-5
1.2. SUMMARY OF ASSESSMENT METHODS 1-8
1.2.1. Literature Search and Screening 1-8
1.2.2. Evaluation of Individual Studies 1-11
1.2.3. Data Extraction 1-13
1.2.4. Evidence Synthesis and Integration 1-14
1.2.5. Dose-Response Analysis 1-15
2. LITERATURE SEARCH AND STUDY EVALUATION RESULTS 2-1
2.1. LITERATURE SEARCH AND SCREENING RESULTS 2-1
2.2. STUDY EVALUATION RESULTS 2-2
3. PHARMACOKINETICS, EVIDENCE SYNTHESIS, AND INTEGRATION 3-1
3.1. PHARMACOKINETICS 3-1
3.1.1. Absorption 3-4
3.1.2. Distribution 3-6
3.1.3. Metabolism 3-20
3.1.4. Excretion 3-20
3.1.5. Evaluation of PBPK and PK Modeling 3-34
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
3.1.6. Empirical Pharmacokinetic Analysis 3-39
3.1.7. Model Evaluation Conclusion and Extrapolation Approach 3-44
3.2. NONCANCER HEALTH EFFECTS 3-47
3.2.1. Thyroid Effects 3-48
3.2.2. Immune Effects 3-74
3.2.3. Developmental Effects 3-105
3.2.4. Hepatic Effects 3-196
3.2.5. Neurodevelopmental Effects 3-224
3.2.6. Cardiometabolic Effects 3-248
3.2.7. Hematopoietic Effects 3-289
3.2.8. Female Reproductive Effects 3-296
3.2.9. Male Reproductive Effects 3-318
3.2.10.Renal Effects 3-332
3.2.11.Other Noncancer Health Effects 3-342
3.3. CARCINOGENICITY 3-342
3.3.1. Cancer 3-342
4. SUMMARY OF HAZARD IDENTIFICATION CONCLUSIONS 4-1
4.1. SUMMARY OF CONCLUSIONS FOR NONCANCER HEALTH EFFECTS 4-1
4.2. SUMMARY OF CONCLUSIONS FOR CARCINOGENICITY 4-5
4.3. CONCLUSIONS REGARDING SUSCEPTIBLE POPULATIONS AND LIFESTAGES 4-5
5. DERIVATION OF TOXICITY VALUES 5-1
5.1. NONCANCER AND CANCER HEALTH EFFECT CATEGORIES CONSIDERED 5-1
5.2. NONCANCER TOXICITY VALUES 5-2
5.2.1. Oral Reference Dose (RfD) Derivation 5-2
5.2.2. Subchronic Toxicity Values for Oral Exposure (Subchronic Oral Reference Dose
[RfD]) Derivation 5-21
5.2.3. Inhalation Reference Concentration (RfC) Derivation 5-23
5.3. CANCER TOXICITY VALUES 5-23
REFERENCES R-l
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
TABLES
Table 1-1. Physical-chemical properties of PFHxS and related salts3 1-3
Table 1-2. Serum PFHxS concentrations based on NHANES 2013-2014 data (ng/L) 1-5
Table 1-3. PFHxS levels at 10 military installations 1-6
Table 1-4. Populations, exposures, comparators, and outcomes (PECO) criteria 1-9
Table 3-1. Estimated Volume of distribution (Vd) values in rats, mice, and monkeys 3-10
Table 3-2. Measured cord serum: maternal serum ratios 3-15
Table 3-3. Summary of estimated clearance values in animals 3-23
Table 3-4. Summary of clearance values estimated for humans 3-31
Table 3-5. Summary clearance values for humans 3-34
Table 3-6. Pharmacokinetic parameters for rats, mice, monkeys, and humans 3-41
Table 3-7. Data-derived extrapolation factor (DDEF) calculations 3-46
Table 3-8. Associations between PFHxS exposure and thyroid hormone levels in medium
confidence studies of adults 3-53
Table 3-9. Associations between PFHxS exposure and thyroid hormone levels in medium
confidence studies of infants 3-56
Table 3-10. Evidence profile table for PFHxS thyroid effects 3-72
Table 3-11. Summary of PFHxS and data on antibody response to vaccines in children 3-78
Table 3-12. Summary of PFHxS and data on antibody response to vaccines in adults 3-81
Table 3-13. Summary of PFHxS and selected data on infectious disease in humans 3-84
Table 3-14. Summary of PFHxS and data on hypersensitivity in humans 3-91
Table 3-15. Animal study details 3-98
Table 3-16. Evidence profile table for PFHxS immune effects 3-102
Table 3-17. Summary of 34 epidemiologic studies of PFHxS exposure and growth restriction
measures 3-116
Table 3-18. Summary of 11 epidemiologic studies of PFHxS exposure and post-natal growth
measured 3-161
Table 3-19. Associations between PFHxS and anogenital distance in medium confidence
epidemiology studies 3-165
Table 3-20. Summary of 19 epidemiological studies of PFHxS exposure and gestational duration
measures 3-175
Table 3-21. Evidence profile table for PFHxS related developmental effects 3-187
Table 3-22. Associations between PFHxS and liver enzymes in medium confidence epidemiology
studies 3-199
Table 3-23. Evidence profile table for oral PFHxS exposure and liver effects 3-219
Table 3-24. Summary of results for medium confidence epidemiology studies of PFHxS exposure
and cognitive effects 3-231
Table 3-25. Summary of results for medium confidence epidemiology studies of PFHxS exposure
and attention deficit hyperactivity disorder (ADHD) 3-236
Table 3-26. Summary of results for medium confidence epidemiology studies of PFHxS exposure
and behavior 3-238
Table 3-27. Evidence profile table for PFHxS neurotoxicological effects 3-246
Table 3-28. Associations between PFHxS exposure and blood lipids in medium confidence
epidemiology studies 3-253
Table 3-29. Associations between PFHxS exposure and hypertension in medium confidence
epidemiology studies in adolescents and young adults 3-260
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Table 3-30. Associations between PFHxS exposure and gestational hypertension and
preeclampsia in medium confidence epidemiology studies 3-260
Table 3-31. Associations between PFHxS exposure and type 2 diabetes in epidemiology studies 3-264
Table 3-32. Associations between PFHxS exposure and gestational diabetes in epidemiology
studies 3-266
Table 3-33. Associations between PFHxS exposure and insulin resistance or blood glucose in
epidemiology studies 3-269
Table 3-34. Associations between maternal exposure to PFHxS and adiposity in children 3-277
Table 3-35. Associations between maternal exposure to PFHxS and overweight status in children
in medium confidence epidemiology studies 3-280
Table 3-36. Evidence profile table for PFHxS exposure and cardiometabolic effects 3-286
Table 3-37. Evidence profile table for PFHxS hematopoietic effects 3-295
Table 3-38. Summary of results for epidemiology studies of fecundity 3-298
Table 3-39. Evidence profile table for PFHxS exposure and female reproductive effects 3-314
Table 3-40. Associations between PFHxS and semen sperm parameters in medium confidence
epidemiology studies 3-320
Table 3-41. Evidence profile table for PFHxS exposure and male reproductive effects 3-329
Table 3-42. Associations between PFHxS exposure and renal function 3-335
Table 3-43. Evidence profile table for PFHxS urinary system effects 3-341
Table 4-1. Hazard conclusions across published EPA PFAS human health assessments 4-3
Table 5-1. Endpoints considered for dose-response modeling and derivation of points of
departure for thyroid effects in animals 5-4
Table 5-2. Endpoints considered for dose-response modeling and derivation of points of
departure for immune (decreased serum antibody) effects in humans 5-6
Table 5-3. Mean birth weight deficit studies considered for dose-response modeling and
derivation of points of departure for developmental effects in humans 5-8
Table 5-4. Benchmark response levels selected for BMD modeling of PFHxS outcomes 5-10
Table 5-5. Points of Departure (PODs) considered for the derivation of PFHxS candidate toxicity
values 5-11
Table 5-6. Uncertainty factors for the development of the lifetime RfD for PFHxS 5-14
Table 5-7. Lifetime candidate values for PFHxS 5-18
Table 5-8. Confidence in the organ-/system-specific RfDs for PFHxS 5-19
Table 5-9. RfD and organ-/system-specific RfDs for PFHxS 5-20
Table 5-10. Subchronic RfD organ-/system-specific RfD values for PFHxS 5-22
FIGURES
Figure 1-1. Chemical structure of PFHxS and related salts 1-2
Figure 2-1. Literature search for perfluorohexanesulfonic acid and related salts 2-2
Figure 3-1. Observed end-of-study of PFHxS in female and male rats in the NTP bioassay 3-3
Figure 3-2. Ratio of extracellular water (% of body weight) in children versus adults 3-17
Figure 3-3. Comparison of PFHxS PBPK model predictions to IV dosimetry data 3-36
Figure 3-4. Comparison of Female (left) and Male (right) CL values for IV and gavage exposure of
equivalent dose levels 3-40
Figure 3-5. Study evaluation results for epidemiology studies of PFHxS and thyroid effects 3-51
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Figure 3-6. Study evaluation results for measures of thyroid hormone levels in PFHxS animal
toxicity studies 3-59
Figure 3-7. Summary of thyroid hormone measures in animal studies 3-61
Figure 3-8. Percent change in thyroid hormone levels following PFHxS exposure in the available
animal toxicology studies 3-62
Figure 3-9. Study evaluation results for endocrine histopathology outcomes in PFHxS animal
toxicity studies 3-64
Figure 3-10. Study evaluation results for endocrine organ weights in PFHxS animal toxicity
studies 3-65
Figure 3-11. Summary of endocrine organ weight effects in animal studies 3-66
Figure 3-12. EDSP21 results of PFHxS active assays 3-69
Figure 3-13. Summary of evaluation of epidemiology studies of PFHxS and antibody response
immunosuppression effects 3-76
Figure 3-14. Summary of evaluation of epidemiology studies of PFHxS and infectious disease
immunosuppression effects 3-83
Figure 3-15. Summary of evaluation of epidemiology studies of PFHxS and hypersensitivity
effects 3-89
Figure 3-16. Study evaluation results of PFHxS animal toxicity studies with immune-related
endpoints 3-97
Figure 3-17. Summary of PFHxS immune hematology results 3-99
Figure 3-18. Study evaluation results for 39 epidemiological studies of birth weight and PFHxS 3-110
Figure 3-19. Perinatal studies of birth weight measures and subsets included in different
evaluations 3-111
Figure 3-20. Overall population birth weight results for 11 high confidence PFHxS
epidemiological studies 3-120
Figure 3-21. Overall population birth weight results for 17 medium and low confidence
epidemiological studies 3-121
Figure 3-22. Forest plot of 27 studies included for the EPA meta-analysis on changes in mean
birth weight per each In-unit PFHxS increase 3-122
Figure 3-23. Sex-specific male infants only mean birth weight results for 14 PFHxS
epidemiological studies 3-125
Figure 3-24. Sex-specific female infants only mean birth weight results for 14 PFHxS
epidemiological studies 3-126
Figure 3-25. Overall population standardized birth weight results for 12 epidemiologic studies 3-129
Figure 3-26. Sex stratified standardized birth weight results for 5 epidemiologic studies 3-130
Figure 3-27. Study evaluation results for 19 epidemiological studies of birth length and PFHxS 3-134
Figure 3-28. Overall population mean birth length results for 16 PFHxS epidemiological studies 3-135
Figure 3-29. Sex stratified birth length results for 11 epidemiologic studies 3-136
Figure 3-30. Study evaluation results for 14 epidemiological studies of head circumference and
PFHxS 3-138
Figure 3-31. Overall population head circumference results for 12 epidemiologic studies 3-140
Figure 3-32. Sex stratified head circumference results for 8 epidemiologic studies 3-141
Figure 3-33. Study evaluation results for 7 epidemiological studies of small for gestational age
and low birth weight and PFHxS 3-143
Figure 3-34. Small for gestational age and low birth weight results for 7 epidemiologic studies 3-144
Figure 3-35. Study evaluation results for 13 epidemiological studies of postnatal growth and
PFHxS 3-147
Figure 3-36. Standardized postnatal weight results for PFHxS epidemiological studies 3-149
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Figure 3-37. Mean postnatal weight results for PFHxS epidemiological studies 3-150
Figure 3-38. Standardized postnatal height results for PFHxS epidemiological studies 3-152
Figure 3-39. Mean postnatal height results for PFHxS epidemiological studies 3-153
Figure 3-40. Postnatal rapid growth (weight-for-age and weight-for-length z-score) results for
PFHxS epidemiological studies 3-156
Figure 3-41. Postnatal rapid growth (length-for-age and head circumference z-score) results for
PFHxS epidemiological studies 3-157
Figure 3-42. Postnatal head circumference results for PFHxS epidemiological studies 3-158
Figure 3-43. Postnatal body mass index, adiposity, and ponderal index and weight status results
for PFHxS epidemiological studies 3-160
Figure 3-44. Summary of study evaluation for epidemiology studies of anogenital distance 3-163
Figure 3-45. Summary of study evaluation for 10 epidemiology studies of preterm birth 3-168
Figure 3-46. Preterm birth results for 10 PFHxS epidemiological studies 3-169
Figure 3-47. Study evaluation results for 19 epidemiological studies of gestational age and
PFHxS 3-171
Figure 3-48. Overall population gestational age results for 17 PFHxS epidemiological studies 3-172
Figure 3-49. Sex stratified gestational age results for 8 PFHxS epidemiological studies 3-174
Figure 3-50. Study evaluation results for nine epidemiological studies of fetal loss and PFHxS 3-177
Figure 3-51. Summary of study evaluation for 2 epidemiology studies of birth defects 3-179
Figure 3-52. Developmental animal study evaluation heatmap 3-180
Figure 3-53. PFHxS-induced developmental effects 3-183
Figure 3-54. Hepatic effects human study evaluation heatmap 3-197
Figure 3-55. PFHxS liver weight animal study evaluation heatmap 3-203
Figure 3-56. Liver weight responses from animal studies 3-204
Figure 3-57. Liver histopathology animal study evaluation heatmap 3-206
Figure 3-58. Histopathology observations from short-term studies 3-207
Figure 3-59. Histopathology observations from developmental toxicity studies 3-208
Figure 3-60. Histopathology observations from developmental toxicity studies (F1 generation
animals) 3-209
Figure 3-61. PFHxS liver serum biomarkers animal study evaluation heatmap 3-211
Figure 3-62. PFHxS liver/hepatobiliary serum biomarkers 3-212
Figure 3-63. Summary of study evaluation for epidemiology studies of neurodevelopment 3-226
Figure 3-64. Confidence scores of neurodevelopmental system effects from repeated PFHxS
dose animal toxicity studies 3-242
Figure 3-65. Study evaluation results for epidemiology studies of PFHxS and blood lipids 3-250
Figure 3-66. Study evaluation results for epidemiology studies of PFHxS and cardiovascular
disease risk factors 3-259
Figure 3-67. Study evaluation results for epidemiology studies of PFHxS and cardiovascular
disease 3-261
Figure 3-68. Summary of study evaluation for PFHxS and type 2 diabetes in epidemiology
studies 3-263
Figure 3-69. Heatmap of study evaluations for PFHxS and gestational diabetes 3-265
Figure 3-70. Heatmap of study evaluations for insulin resistance and blood glucose 3-268
Figure 3-71. Summary of study evaluations for epidemiology studies of PFHxS and metabolic
syndrome 3-273
Figure 3-72. Summary of study evaluations for epidemiology studies of adiposity 3-275
Figure 3-73. Cardiometabolic effects, heart weight/histopathology - animal study evaluation
heatmap. For additional details see HAWC link 3-282
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Figure 3-74. Cardiometabolic effects, serum lipids - animal study evaluation heatmap 3-283
Figure 3-75. Hematological animal study confidence scores from repeated PFHxS dose animal
toxicity studies 3-290
Figure 3-76. Hematopoietic effects of PFHxS exposure in animals 3-293
Figure 3-77. Summary of study evaluation for epidemiology studies of fecundity 3-297
Figure 3-78. Summary of study evaluations for epidemiology studies of female reproductive
hormones 3-300
Figure 3-79. Summary of study evaluation for epidemiology studies of other female reproductive
effects 3-303
Figure 3-80. PFHxS mating and fertility animal study evaluation heatmap 3-307
Figure 3-81. PFHxS estrous cycle animal study evaluation heatmap 3-308
Figure 3-82. PFHxS hormone levels animal study evaluation heatmap 3-309
Figure 3-83. PFHxS female reproductive histopathology animal study evaluation heatmap 3-310
Figure 3-84. PFHxS female reproductive organ weight animal study evaluation heatmap 3-311
Figure 3-85. PFHxS female reproductive sexual differentiation and maturation animal study
evaluation heatmap 3-312
Figure 3-86. Semen parameters epidemiology study evaluation heatmap 3-319
Figure 3-87. Summary of study evaluation for epidemiology studies of male reproductive
hormones 3-321
Figure 3-88. Male reproductive animal study evaluation heatmap - sperm measures 3-324
Figure 3-89. Male reproductive histopathology animal study evaluation heatmap 3-325
Figure 3-90. Male reproductive animal study evaluation heatmap - reproductive hormones 3-326
Figure 3-91. Male reproductive animal study evaluation heatmap - reproductive organ weights 3-327
Figure 3-92. Male reproductive animal study evaluation heatmap - developmental effects and
functional measures 3-328
Figure 3-93. Renal effects human study evaluation heatmap 3-333
Figure 3-94. Renal effects - animal study evaluation heatmap 3-338
Figure 3-95. Study evaluation results for epidemiology studies of PFHxS and cancer 3-343
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
ABBREVIATIONS AND ACRONYMS
ADHD
attention deficit hyperactivity disorder
MNPCE
micronucleated polychromatic
AIC
Akaike's information criterion
erythrocyte
ALT
alanine aminotransferase
MOA
mode of action
AST
aspartate aminotransferase
MTD
maximum tolerated dose
atm
atmosphere
ATSDR
Agency for Toxic Substances and
NCI
National Cancer Institute
Disease Registry
NOAEL
no-observed-adverse-effect level
BMD
benchmark dose
NTP
National Toxicology Program
BMDL
benchmark dose lower confidence limit
NZW
New Zealand White (rabbit breed)
BMDS
Benchmark Dose Software
ORD
Office of Research and Development
BMR
benchmark response
osRfD
organ-specific reference dose
BUN
blood urea nitrogen
PBPK
physiologically based pharmacokinetic
BW
body weight
PFHxS
perfluorohexanesulfonic acid
CA
chromosomal aberration
PND
postnatal day
CASRN
Chemical Abstracts Service registry
POD
point of departure
number
POD [AD J]
duration-adjusted POD
CHO
Chinese hamster ovary (cell line cells)
QSAR
quantitative structure-activity
CPHEA
Center for Public Health and
relationship
Environmental Assessment
RD
relative deviation
CL
confidence limit
RfC
inhalation reference concentration
CNS
central nervous system
RfD
oral reference dose
CYP450
cytochrome P450
RGDR
regional gas dose ratio
DAF
dosimetric adjustment factor
RNA
ribonucleic acid
DDEF
data-derived extrapolation factor
SAR
structure activity relationship
DMSO
dimethylsulfoxide
SCE
sister chromatid exchange
DNA
deoxyribonucleic acid
SD
standard deviation
EPA
Environmental Protection Agency
SDH
sorbitol dehydrogenase
ER
extra risk
SE
standard error
FDA
Food and Drug Administration
SEM
Systematic Evidence Map
FEVi
forced expiratory volume of 1 second
SGOT
glutamic oxaloacetic transaminase, also
GD
gestation day
known as AST
GDH
glutamate dehydrogenase
SGPT
glutamic pyruvic transaminase, also
GGT
y-glutamyl transferase
known as ALT
GLP
good laboratory practices
TSCATS
Toxic Substances Control Act Test
GSH
glutathione
Submissions
GST
glutathione-S-transferase
TWA
time-weighted average
HBCD
hexabromocyclododecane
UF
uncertainty factor
Hb/g-A
animal blood:gas partition coefficient
UFa
animal-to-human uncertainty factor
Hb/g-H
human blood:gas partition coefficient
UFd
database deficiencies uncertainty factor
HEC
human equivalent concentration
UFh
human variation uncertainty factor
HED
human equivalent dose
UFl
LOAEL-to-NOAEL uncertainty factor
HERO
Health and Environmental Research
UFs
subchronic-to-chronic uncertainty
Online
factor
i.p.
intraperitoneal
WOS
Web of Science
IRIS
Integrated Risk Information System
i.v.
intravenous
LC50
median lethal concentration
LD50
median lethal dose
LOAEL
lowest-observed-adverse-effect level
MN
micronuclei
This document is a draft for review purposes only and does not constitute Agency policy.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
AUTHORS | CONTRIBUTORS | REVIEWERS
Assessment Managers (Lead Authors)
Xabier Arzuaga. Ph.D. U.S. EPA/ORD/CPHEA
Ingrid L. Druwe. Ph.D.
Authors
Thomas F. Bateson. Sc.D., M.P.H. U.S. EPA/ORD/CPHEA
I. Allen Davis. M.S.P.H.
Michael Dzierlenga. Ph.D.
Andrew Kraft. Ph.D.
Alexandra Larsen. Ph.D.
Elizabeth Radke. Ph.D.
Hongvu Ru. Ph.D.
Paul Schlosser. Ph.D.
Shana White. Ph.D.
lohn Michael Wright. Sc.D.
lay Zhao. Ph.D.
lason C. Lambert. Ph.D. U.S. EPA/ORD/CCTE
Contributors
Laura Dishaw. Ph.D. U.S. EPA/ORD/CPHEA
Mary Gilbert. Ph.D.
Barbara Glenn, Ph.D. (retired)
Christopher Lau. Ph.D.
Geniece Lehmann. Ph.D.
Andrew Hotchkiss. Ph.D.
Anuradha Mudipalli. Ph.D.
Kathleen Newhouse. Ph.D.
Pamela Noves. Ph.D.
Katherine O'Shaughnessv. Ph.D.
Kristen Rappazzo. Ph.D.
Susan Makris. Ph.D. (retired)
Tammv Stoker. Ph.D.
Andre Weaver. Ph.D.
Erin Yost. Ph.D.
Chris Corton. Ph.D.
Stephanie Kim. Ph.D.
Andrew Roonev. Ph.D.
Kvla Taylor. Ph.D.
Dori Germolec. Ph.D.
U.S. EPA/ORD/CCTE
U.S. EPA/Region 2
NIH/NTP/NIEHS
Alexis Agbai Oak Ridge Associated Universities (ORAU) Contractor
Timothy Decoff
Angela Scafidi (former)
This document is a draft for review purposes only and does not constitute Agency policy.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Robvn B. Blain. Ph.D.
Alexandra E. Goldstone. M.P.H. ICF
Alexander I. Lindahl. M.P.H.
Christopher A. Sibrizzi. M.P.H.
Production Team
Maureen Johnson U.S. EPA/ORD/CPHEA
Ryan Jones
Dahnish Shams
Jessica Soto Hernandez
Vicki Soto
Samuel Thacker
Garland Waleko
Grace Kaupas Oak Ridge Associated Universities (ORAU) Contractor (former)
Rebecca Schaefer Oak Ridge Associated Universities (ORAU) Contractor
Jacqueline Weinberger Oak Ridge Associated Universities (ORAU) Contractor (former)
Executive Direction
Wayne Cascio
V. Kay Holt
Samantha Jones
Kristina Thayer
Andrew Kraft
Paul White
Ravi Subramaniam
Janice Lee
Glenn Rice
Viktor Morozov
CPHEA Center Director
CPHEA Deputy Center Director
CPHEA Associate Director
CPAD Division Director
CPAD Associate Division Director, IRIS PFAS Team Lead
CPAD Senior Science Advisor
CPHEA/CPAD/Toxic Effects Assessment (DC) Branch Chief
CPHEA/CPAD/Toxic Effects Assessment (RTP) Branch Chief
CPHEA/CPAD/Science Assessment Methods Branch Chief
CPHEA/CPAD/Quantitative Assessment Branch Chief
Review
CPAD Executive Review Committee
Kristina Thayer
Paul White
Janice Lee
Glenn Rice
Ravi Subramaniam
Karen Hogan
Alan Stern
CPAD Division Director
CPHEA/CPAD/Senior Science Advisor
CPHEA/CPAD/Toxic Effects Assessment (RTP) Branch Chief
CPHEA/CPAD/Science Assessment Methods Branch Chief
CPHEA/CPAD/Toxic Effects Assessment (DC) Branch Chief
CPHEA/CPAD/Emeritus
NJDEP (retired), Contractor
Agency Review
This assessment was provided for review to scientists in EPA's program and regional offices. Comments were
submitted by: Office of Air and Radiation (OAR), Office of Air Quality and Standards (OAQPS), Office of Land
and Emergency Management (OLEM), Office of Children's Health Protection (OCHP), Office of Water, Region
1, Region 3, Region 4, and Region 8.
Interagency Review
This assessment was provided for review to other federal agencies and the Executive Office of the President
(EOP). Comments were submitted by: The National Institute for Occupational Safety and Health (NIOSH),
Department of Defense (DoD), National Institute of Environmental Health Sciences (NIEHS), Council on
Environmental Quality (CEQ), Department of Health and Human Services (HHS), National Institute of Health
(NIH), and the Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substance and Disease
Registry (ATSDR).
This document is a draft for review purposes only and does not constitute Agency policy.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
EXECUTIVE SUMMARY
Perfluorohexanesulfonic acid (PFHxS, CASRN 355-46-4)1, and its related salts (such as
potassium perfluorohexanesulfonate [PFHxS-K, CASRN 3871-99-6], ammonium
perfluorohexanesulfonate [PFHXS-NH4, CASRN 68259-08-5], and sodium perfluorohexanesulfonate
[PFHxS-Na, CASRN 82382-12-5]), are members of the group per- and polyfluoroalkyl substances
(PFAS). This assessment applies to PFHxS as well as nonmetal and alkali metal salts of PFHxS that
would be expected to fully dissociate in aqueous solutions of pH ranging from 4 to 9 (e.g., in the
human body) and not release other moieties that would cause toxicity independent of PFHxS. The
synthesis of evidence and toxicity value derivation presented in this assessment focuses on the free
acid of PFHxS and its potassium, sodium, and ammonium salts given the currently available toxicity
data.
Concerns about PFHxS and other PFAS stem from the resistance of these compounds to
hydrolysis, photolysis, and biodegradation, which leads to their persistence in the environment.
PFAS are not naturally occurring; they are man-made compounds that have been used widely over
the past several decades in industrial applications and consumer products as many PFAS are
resistant to heat and are used to confer resistance of products (e.g., textiles) to stains by repelling
oil, grease, and water. PFAS are also used in a wide range of other applications, including as
electrical insulation and to confer frictionless coatings onto surfaces. PFAS in the environment are
found at industrial sites, military fire training areas, wastewater treatment plants, and found in
commercial products (see Appendix A, Section 2.1.2).
The Integrated Risk Information System (IRIS) Program is developing a series of five PFAS
assessments (i.e., perfluorohexane sulfonate [PFHxS], perfluorobutanoic acid [PFBA],
perfluorohexanoic acid [PFHxA], perfluorononanoic acid [PFNA], perfluorodecanoic acid [PFDA],
and their associated salts) (see December 2018 IRIS Program Outlook) at the request of EPA
national programs and regions. Specifically, the development of human health toxicity assessments
for exposure to these individual PFAS represents only one component of the broader PFAS strategic
roadmap at the EPA f https://www.epa.gov/pfas/pfas-strategic-roadmap-epas-commitments-
action-2021-20241. The systematic review protocol (see Appendix A) for these five PFAS
assessments outlines the related scoping and problem-formulation efforts, including a summary of
other federal and state assessments of PFHxS. The protocol also describes the systematic review
1 The CASRN given here is for linear PFHxS; the source of PFHxS used in toxicity studies was reported to be
98% pure and reagent grade, generally giving this CASRN. None of the studies referenced in this assessment
explicitly state that only the linear form was used. Therefore, there is the possibility that a minor proportion
of the PFHxS used in the studies were branched isomers and thus observed health effects may apply to the
total linear and branched isomers in a given exposure source.
This document is a draft for review purposes only and does not constitute Agency policy.
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and dose-response methods used to conduct this review (see also Section 1.2). In addition to these
ongoing IRIS PFAS toxicity assessments, EPA's Office of Research and Development is carrying out
several other activities related to PFAS, including the creation of PFAS systematic evidence maps
(SEMs) fCarlsonetal.. 2022: Radke etal.. 20221and consolidating and updating PFAS data on
chemical and physical properties, human health toxicity, and pharmacokinetics, as well as
ecotoxicity.
Human epidemiological studies have examined possible associations between PFHxS
exposure and health outcomes including immune responses, birth weight, hematopoietic effects,
thyroid hormone effects, liver enzyme effects, serum lipids effects, cardiovascular disease,
hematological effects, reproductive effects, neurodevelopmental effects, and cancer. The ability to
draw conclusions from the epidemiological evidence for the assessed health outcomes is limited
(apart from immune effects) by the overall quality and lack of consistency in the available studies.
Animal studies of PFHxS exposure exclusively examined the oral exposure route; therefore,
no inhalation assessment was conducted nor was an inhalation reference concentration (RfC)
derived (see Section 5.2.3). The available animal studies of oral PFHxS exposure examined a variety
of noncancer endpoints, including those relevant to the thyroid, immune system, developmental
effects, hematopoietic system, hepatic effects, cardiometabolic effects, reproductive (male and
female) system, nervous system, and renal effects. Some limitations in the animal database include
the types of studies identified (e.g., few subchronic studies and no chronic exposure studies were
available), and few studies per health outcome.
Overall, the available evidence indicates that PFHxS exposure is likely to cause thyroid and
developmental immune effects in humans, given sufficient exposure conditions. For thyroid effects,
the primary supporting evidence for this hazard conclusion included evidence of decreased thyroid
hormone levels, abnormal histopathology results, and changes in organ weight in experimental
animals. For immune effects, the primary supporting evidence included decreased antibody
responses to vaccination against tetanus or diphtheria in children. Selected quantitative data from
these identified hazards were used to derive toxicity values (see Table ES-1; see Sections 3.2.1 and
3.2.2 for evidence synthesis and integration analyses).
Evidence primarily from epidemiological studies suggests but is insufficient to infer that
PFHxS exposure might affect fetal development, specifically resulting in decreased birth weight (see
Section 3.2.3). However, due to limitations and uncertainties in the currently available studies, a
hazard could not be clearly identified, and these data were not considered for use in deriving
toxicity values. While no reference dose (RfD) was derived for developmental effects, a point of
departure (POD) was derived and presented for comparison purposes (see Section 5.2.1).
In addition, evidence from human and animal studies suggests but is insufficient to infer
that PFHxS exposure may cause hepatic, neurodevelopmental, and cardiometabolic effects in
humans.
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1 Lastly, although evidence from humans and or animals was also identified for
2 hematopoietic, reproductive, renal, and carcinogenic effects, the currently available evidence is
3 inadequate to assess whether PFHxS exposure may be capable of causing these health effects in
4 humans, and these outcomes were not considered for use in deriving toxicity values.
Table ES-1. Health effects with evidence available to synthesize and draw
summary judgments and derived toxicity values
Organ/
System
Evidence
Integration
judgment
Toxicity
value
Value
(mg/kg-d)
Confidence
UFA
UFH
UFS
UFL
UF
D
UFC
Basis
Immune (i.e.,
developmental
immune)
Evidence
indicates
(likely)
Lifetime
osRfD
2 X 1010
(RfD)
Medium
1
10
1
1
3
30
Decreased serum
anti-tetanus antibody
concentration in
children at age 7 yrs
(Budtz-J0rgensen
and Grandiean,
2018: Grandiean et
al., 2012)
Subchronic
osRfD
2 x 10"10
Medium
1
10
1
1
3
30
Decreased serum
anti-tetanus antibody
concentration in
children at age 7 yrs
(Budtz-J0rgensen
and Grandiean,
2018: Grandiean et
al., 2012)
Thyroid
Evidence
indicates
(likely)
Lifetime
osRfD
1 x 10"7
Medium
3
10
1
1
3
100
Decreased serum
total T4 levels in F1
Wistar rats (Ramh0i
et al., 2018)
Subchronic
osRfD
1 x 10"7
Medium
3
10
1
1
3
100
Decreased serum
total T4 levels in
Wistar rats (Ramh0i
et al., 2018)
RfD = reference dose (in mg/kg-d) for lifetime exposure; subchronic RfD = reference dose (in mg/kg-d) for less-
than-lifetime exposure; osRfD = organ-/system-specific reference dose (in mg/kg-d); UFA = animal to human
uncertainty factor; UFC = composite uncertainty factor; UFD = evidence base deficiencies uncertainty factor;
UFH = human variation uncertainty factor; UFL = LOAEL to NOAEL uncertainty factor; UFS = subchronic to chronic
uncertainty factor.
This document is a draft for review purposes only and does not constitute Agency policy.
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ES.1 LIFETIME AND SUBCHRONIC ORAL REFERENCE DOSE (RfD) FOR NONCANCER EFFECTS
From the identified hazards with sufficient qualitative and quantitative information to
support the derivation of candidate lifetime values (i.e., immune and thyroid), decreased serum
anti-tetanus antibody concentrations in children (male and female) fBudtz-largensen and
Grandiean. 2018: Grandiean etal.. 20121 was selected as the basis for the oral RfD of 4 x 10-10
mg/kg-day. A BMDLy2sD of 2.82 x 10~4 mg/L in serum was identified for this endpoint and was used
as the PODintemai- The human equivalent dose POD (PODhed) of 1.16 x 10"8 mg/kg-day was derived
by multiplying the PODintemai by the human clearance of 4.1 x 10"5 L/kg-day to estimate human
equivalent doses from an internal dose. The overall RfD for PFHxS was calculated by dividing the
PODhed by a composite uncertainty factor of 30 to account for inter individual differences in human
susceptibility (UFh = 10) and deficiencies in the toxicity evidence base (UFd = 3). The immune
organ-/system-specific osRfD is based on the lowest overall PODhed and UFc; therefore, the selected
RfD based on decreased serum anti-tetanus antibody concentration in children (a susceptible
lifestage for this effect) is considered protective of the observed health effects associated with
lifetime PFHxS exposure. The selection considered both available osRfDs as well as the overall
confidence and composite uncertainty for those osRfDs. The thyroid osRfD was based on
application of a composite uncertainty threefold greater than that applied in deriving the immune
osRfD (UFc = 100 for thyroid versus UFC = 30 for developmental immune effects). Further, when
comparing the sensitivity of thyroid and immune osRfDs, the thyroid value is 500-fold higher than
the developmental immune endpoint. Selection of the RfD on the basis of developmental immune
effects is presumed to be protective of possible thyroid and other potential adverse health effects
(including potential effects on birth weight) in humans. Finally, since the developmental immune
osRfD is based on effects observed in males and females, the overall RfD would be protective for
both sexes. The same study fBudtz-largensen and Grandiean. 2018: Grandiean etal.. 20121
endpoint (decreased serum anti-tetanus antibody concentration in children) and value were
selected as the basis for the subchronic RfD of 4 x 10"10 mg/kg-day.
ES.2 CONFIDENCE IN THE ORAL REFERENCE DOSE (RFD) AND SUBCHRONIC RFD
The overall confidence in the RfD and subchronic RfD is medium and is driven by medium
confidence in the overall evidence base for immune effects, medium confidence in the Budtz-
Targensen and Grandiean f20181: Grandiean etal. f20121 study fHAWC linkl. and medium
confidence in quantitation of the POD (see Section 5.2. and Table 5-8).
ES.3 NONCANCER EFFECTS FOLLOWING INHALATION EXPOSURE
No studies that examine toxicity in humans or experimental animals following inhalation
exposure are available and no acceptable physiologically based pharmacokinetic (PBPK) models
are available to support route-to-route extrapolation; therefore, no RfC was derived.
This document is a draft for review purposes only and does not constitute Agency policy.
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1 ES.4 EVIDENCE FOR CARCINOGENICITY
2 Under EPA's Guidelines for Carcinogen Risk Assessment fU.S. EPA. 20051. EPA concluded
3 there is inadequate information to assess carcinogenic potential for PFHxS by either the oral or
4 inhalation routes of exposure. This conclusion is based on the lack of adequate data to inform the
5 potential carcinogenicity of PFHxS in the database. This precludes the derivation of quantitative
6 estimates for either oral (oral slope factor [OSF]) or inhalation (inhalation unit risk [IUR])
7 exposure.
This document is a draft for review purposes only and does not constitute Agency policy.
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1. OVERVIEW OF BACKGROUND INFORMATION
AND ASSESSMENT METHODS
A series of five PFAS assessments (Perfluorohexanesulfonic acid [PFHxS],
perfluorohexanoic acid [PFHxA], perfluorobutanoic acid [PFBA], perfluorononanoic acid [PFNA],
perfluorodecanoic acid [PFDA], and their associated salts; see December 2018 IRIS Outlook) is
being developed by the Integrated Risk Information System (IRIS) Program at the request of the
U.S. Environmental Protection Agency (EPA) national programs and regions. Appendix A is the
systematic review protocol for these five PFAS assessments. The protocol outlines the scoping and
problem-formulation efforts relating to these assessments, including a summary of other federal
and state reference values for PFHxS. The protocol also lays out the systematic review and dose-
response methods used to conduct this review (see also Section 1.2). This systematic review
protocol was released for public comment in November 2019 and was subsequently updated based
on those public comments. Appendix A includes a link to the updated protocol, including a
summary of the updates in the protocol history section (see Section 12). In addition to these
ongoing IRIS PFAS toxicity assessments, EPA's Office of Research and Development is carrying out
several other activities related to PFAS, including creation of PFAS systematic evidence maps
(SEMs) and consolidating and updating PFAS data on chemical and physical properties, human
health toxicity, and pharmacokinetics, as well as ecotoxicity.
1.1. BACKGROUND INFORMATION ON PERFLUOROHEXANESULFONIC
ACID (PFHxS)
Section 1.1 provides a brief overview of aspects of the physicochemical properties, human
exposure, and environmental fate characteristics of perfluorohexanesulfonic acid (PFHxS; CASRN
335-46-4), and its related salts that might provide useful context for this assessment This overview
is not intended to provide a comprehensive description of the available information on these topics.
The reader is encouraged to refer to the source materials cited below, more recent publications on
these topics, and authoritative reviews or assessments focused on these topics.
1.1.1. Physical and Chemical Properties
PFHxS and its related salts such as potasium, sodium, and ammonium PFHxS salts covered
in this assessment are members of the group per- and polyfluoroalkyl substances (PFAS). Buck et
al. f20111 defines PFAS as fluorinated substances that "contain 1 or more C atoms on which all the
H substituents (present in the nonfluorinated analogues from which they are notionally derived)
have been replaced by F atoms, in such a manner that they contain the perfluoroalkyl moiety
This document is a draft for review purposes only and does not constitute Agency policy.
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1 C„F2n+i-)." More specifically, PFHxS is classified as a perfluoroalkane sulfonic acid [PFSA; fOECD.
2 20151]. PFSAs containing six or more perfluorinated carbons are considered long-chain PFASs
3 fATSDR. 2018b: OECD. 2015: Buck etal.. 20111. Thus, PFHxS is a long-chain PFAS. The chemical
4 structures of PFHxS2 and its related salts are presented in Figure 1-1. The physical-chemical
5 properties of PFHxS and related salts are provided in Table 1-1.
F
D=S OH
II
o
PFHxS
355-46-4
r 1
:
¦
: 1
: 1
PFHxS
related salts
Figure 1-1. Chemical structure of PFHxS and related salts (see
https://comptox.epa.goV/dashboard /l. X represents the cations for potassium
(CASRN 3871-99-6), sodium (CASRN 82382-12-5), and ammonium (CASRN
68259-08-5).
2 While this figure shows the linear chemical structures, the assessment may also apply to other non-linear
isomers of PFHxS and related salts as described in the Executive Summary
This document is a draft for review purposes only and does not constitute Agency policy,
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Table 1-1. Physical-chemical properties of PFHxS and related salts3
Property (unit)
Value
PFHxS
355-46-4b
PFHxS
Potassium salt
3871-99-6c
PFHxS
Ammonium salt
68259-08-5c
PFHxS
Sodium salt
82382-12-5c
Molecular weight (g/mol)
400
438
417c*
422*
Melting point (°C)
190
273
111*
217*
Boiling point (°C)
246
303*
228*
238*
Density (g/cm3)
1.84*
1.84*
1.84*
1.84*
Vapor pressure (mm Hg)
8.10 x 10"9
8.19 x 10"9*
8.19 x 10"9*
8.19 x 10"9*
Henry's law constant
(atm-m3/mol)
1.94 x 10"10*
1.94 x 10"10*
1.94 x 10"10*
1.94 x 10"10*
Water solubility (mol/L)
6.08 x 10"4d
3.52 x 10"2*
6.10 x 10"4*
7.03 x 10"2*
pKa
0.14*
ND
ND
ND
LogP
2.20d
2.71*
3.48*
2.91*
Soil adsorption coefficient (L/kg)
2,300*
2,300*
2,300*
2,300*
Bioconcentration factor (BCF)
175*
271*
271*
5.94*
aThis information is provided as part of a general overview providing background context only and should not be
used for decision purposes. Up-to-date primary references should be consulted.
bCompTox Chemicals Dashboard (U.S. EPA, 2018a) for all values except pKa. The value of pKa was obtained from
ECHA: https://echa.europa.eu/documents/10162/lf48372e-97dd-db9f-4335-8cec7ae55eee. Questions and
corrections to the CompTox Chemicals Dashboard can be submitted at: https://comptox.epa.aov/dashboard/.
c (U.S. EPA, 2018a). Questions and corrections to the CompTox Chemicals Dashboard can be submitted at:
https://comptox.epa.gov/dashboard/.
dAs of April 2023 these values are indicated as 'experimental' in the CompTox Chemicals Dashboard (U.S. EPA,
2018a): however, they appear to be predicted values based on the citations provided, and therefore may be more
uncertain. Note that these values are not used for dosimetric extrapolation in this assessment, which was based
on available empirical pharmacokinetic data (see Section 3.1.7).
* Average predicted value. These values are more uncertain and, in general, less reliable than experimental values.
ND= No data
1.1.2. Sources, Production, and Use
1 PFAS are not naturally occurring in the environment (ATSDR. 2018a). They are man-made
2 compounds that have been used widely over the past several decades in consumer products and
3 industrial applications because of their resistance to heat, oil, stains, grease, and water. PFHxS has
4 been used as a surfactant to make fluoropolymers, and in water- and stain-protective coatings for
5 carpets, paper, packaging, and textiles (Norwegian Environment Agency. 2018: NTP. 2018c). It may
6 also be present in certain industrial and consumer products, such as electronics, industrial fluids,
7 "food-contact papers, water-proofing agents, cleaning and polishing products either for intentional
8 uses (as surfactants or surface protection agents) or as unintentional impurities from industrial
This document is a draft for review purposes only and does not constitute Agency policy.
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production processes" (Norwegian Environment Agency. 20181. It has also been used in aqueous
film-forming foam (AFFF) for fire suppression (Laitinen etal.. 20141.
EPA has been working with companies in the fluorochemical industry since the early 2000s
to phase out the production and use of long-chain PFAS such as PFHxS
fhttps://www.epa.gov/assessing-and-managing-chemicals-under-tsca/risk-management-and-
polyfluoroalkvl-substances-pfassl. However, in addition to the environmental persistence of PFHxS
(see below), products containing PFHxS are still in use and may be imported into the United States;
thus, there may continue to be a source of environmental contamination due to disposal or
breakdown in the environment (Kim and Kannan. 20071.
No chemical reporting data on production volume are available in EPA's ChemView fU.S.
EPA. 2019al for PFHxS or its salts. As part of the National Defense Authorization Act for Fiscal Year
2020 (see Section 7321), 172 per- and polyfluoroalkyl substances including PFHxS were added to
the EPA's Toxic Release Inventory (TRI) list (https: //www.epa.gov/toxics-release-inventory-tri-
program/tri-listed-chemicalsl. The reporting requirements apply to a de minimus limit of 1% and a
manufacture, process, or otherwise use threshold of 100 lbs. Currently, there is incomplete
quantitative information available in EPA's Toxic Release Inventory or other informational
repositories regarding PFHxS releases to the environment from facilities that manufacture, process,
use imported/previously manufactured products that contain, or dispose of imported/previously
manufactured products containing PFHxS.
1.1.3. Environmental Fate and Transport
PFAS, including PFHxS, are very stable and persistent in the environment (ATSDR. 2018a:
Harbison etal.. 20151. and many are found worldwide in the environment, wildlife, and humans
f https://www.epa.gov/assessing-and-managing-chemicals-under-tsca/risk-management-and-
polyfluoroalkyl-substances-pfassl. Long-chain PFAS have been found at sites, including private and
federal facilities, and have been associated with various sources, including AFFF for fire
suppression, and PFAS manufacturers and industries that use PFAS (e.g., textiles) (ATSDR. 2018a).
Various long chain PFAS have estimated half-lives of 2 to 9 years in humans (ATSDR. 2018a).
However, using an average volume of distribution of 255 mL/kg estimated from nonhuman primate
data (see Table 3-1) and weighted geometric mean clearance of 0.031 mL/kg-day in humans (see
Table 3-4), the half-life of PFHxS in humans is estimated by the EPA to be 15.6 years.
PFAS that are released to air exist in the vapor phase in the atmosphere and resist
photolysis, but particle-bound concentrations have also been measured fKim and Kannan. 20071.
In soil, the mobility of PFHxS depends on the soil adsorption coefficients (see Table 1-1).
Volatilization of PFHxS from moist soil is not expected to be an important transport process (NLM.
2017. 2016. 2013). Furthermore, PFHxS is expected to adsorb to suspended solids and sediments in
water fNLM. 2017. 2016. 20131.
This document is a draft for review purposes only and does not constitute Agency policy.
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1.1.4. Potential for Human Exposure and Populations with Potentially Greater Exposure
The general population may be exposed to PFAS via inhalation of indoor or outdoor air,
ingestion of drinking water and food, and dermal contact with PFAS-containing products fATSDR.
2018a: NLM. 2017. 20131. Exposure may also occur via hand-to-mouth transfer of materials
containing these compounds fATSDR. 2018al. However, the oral route of exposure has been
considered the most important route of exposure among the general population. This conclusion is
based on several studies that have investigated the various routes of PFAS exposure (Sunderland et
al.. 20191.
The presence of PFHxS in human blood provides evidence of exposure among the general
population. PFHxS has been monitored in the human population as part of the National Health and
Nutrition Examination Survey (NHANES). PFHxS was measured in serum samples collected in
2013-2014 from more than 2,000 survey participants fCDC. 20221. The results of these analyses
are presented in Table 1-2.
Table 1-2. Serum PFHxS concentrations based on NHANES 2013-2014
data (pg/L)
Population group3
Value
Total Population (N = 2,168)
geometric mean
1.35
50th percentile
1.40
95th percentile
5.60
3 to 5 yrs (N = 181)
geometric mean
0.715
50th percentile
0.740
95th percentile
1.62
6 to 11 yrs (N = 458)
Geometric mean
0.913
50th percentile
0.850
95th percentile
4.14
12 to 19 yrs (N = 402)
Geometric mean
1.27
50th percentile
1.10
95th percentile
6.30
20 yrs and older (N = 1,766)
Geometric mean
1.36
50th percentile
1.40
95th percentile
5.50
aThis table provides only general context on serum PFHxS levels from a single study and within a narrow time-
period (environmental PFHxS levels are changing over time). Note that PFHxS is expected to bioaccumulate over a
lifetime (see Sections 1.1.3 and 3.1). Up-to-date information from authoritative bodies should be used in any
decisional context.
Source: CDC (2022). Fourth National Report on Human Exposure to Environmental Chemicals.
This document is a draft for review purposes only and does not constitute Agency policy.
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Air and Dust
PFHxS has not been evaluated under the Air Toxics Screening Assessment
(https://www.epa.gov/AirToxScreenl. However, PFHxS was measured at concentrations ranging
from less than the limit of detection to 1.56 pg/m3 in the vapor and particle phases of air samples
collected from an urban area of Albany, New York, in 2006 (Kim and Kannan. 20071.
PFAS, including PFHxS, have also been measured in indoor air and dust and may be
associated with the indoor use of consumer products such as PFAS-treated carpets or other textiles
fATSDR. 2018al. For example, Kato etal. f20091 analyzed dust samples collected from 39 homes in
the United States, United Kingdom, Germany, and Australia for PFAS, including PFHxS, which was
detected in 79.5% of the samples. Furthermore, indoor air samples (N = 4) from a town in Norway
had PFHxS mean concentrations of <4.1 pg/m3 for PFHxS fBarber etal.. 20071.
Water
EPA conducted monitoring for several PFAS in drinking water as part of the third
Unregulated Contaminant Monitoring Rule (UCMR) fU.S. EPA. 2016cl. Under the UCMR3, all public
water systems (PWSs) serving more than 10,000 people and a representative sample of 800 PWSs
serving 10,000 or fewer people were monitored for 30 unregulated contaminants between January
2013 and December 2015. PFHxS was among the 30 contaminants monitored and was detected
above the minimum reporting level (MRL) of 0.03 ng/L in 55 of the 4,920 PWSs tested and in 207 of
the 36,971 samples collected. Kim and Kannan (20071 analyzed lake water, rainwater, snow, and
surface water from Albany, New York, and reported concentrations of PFHxS ranging from less than
the LOD to 0.0135 ng/L. PFAS were detected at higher concentrations in groundwater samples from
an industrial site (3M Cottage Grove) in Minnesota. PFHxS was detected in all seven wells that were
sampled at concentrations ranging from 6.47 to 40 ng/L fWS. 20071 as cited in ATSDR f2018bl.
Aqueous Film-Forming Foam (AFFF) Training and Military Sites
The levels of PFHxS in soil and sediment surrounding perfluorochemical industrial facilities
has been measured at concentrations ranging from less than the LOD to 3,470 ng/g (ATSDR.
2018b). PFHxS was also detected at an Australian training ground where AFFFs had been used
fBaduel etal.. 20151. PFHxS was detected at 10 U.S. military sites in 76.9% of the surface soil
samples and 72.7% of sediment samples fATSDR. 2018bl. Table 1-3 shows the concentration of
PFHxS in soil and sediment at these military sites.
Table 1-3. PFHxS levels at 10 military installations
Media
Value
Surface Soil
Frequency of detection (%)
Median (ng/kg)
Maximum (ng/kg)
76.92
5.70
1,300
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Media
Value
Subsurface Soil
Frequency of detection (%)
59.62
Median (ng/kg)
4.40
Maximum (ng/kg)
520
Sediment
Frequency of detection (%)
72.73
Median (ng/kg)
9.10
Maximum (ng/kg)
2,700
Surface Water
Frequency of detection (%)
88.00
Median (ng/kg)
0.710
Maximum (ng/kg)
815
Groundwater
Frequency of detection (%)
94.93
Median (ng/kg)
0.870
Maximum (ng/kg)
290
Source: Anderson et al. (2016); ATSDR (2018a).
Other Exposures
Schecter et al. f20121 collected 10 samples of 31 food items from five grocery stores in
Texas and analyzed them for persistent organic pollutants, including PFHxS, which was detected in
cod fish at a concentration of 0.07 ng/g wet weight. Stahl etal. f20141 characterized PFAS in
freshwater fish from 164 U.S. urban river sites and 157 Great Lakes sites. PFHxS was detected in
45% of the samples at maximum concentrations of 3.5 ng/g and method detection limit of 0.12
ng/g (Stahl etal.. 20141. PFHxS was not detected in U.S. grocery store finfish and shellfish samples
(Ruffle etal.. 20201. Apart from fish, overall dietary data for the United States are limited. Data from
other countries (e.g., South Korea, Brazil, Saudi Arabia) suggest that long-chain PFAS such as PFHxS
can sometimes be detected in samples of food products including shellfish, dairy products, meats,
vegetables, food packaging materials, and water (both tap and bottled) fChen etal.. 2018b: Surma
etal.. 2017: Heo etal.. 2014: Moreta and Tena. 2014: Perez etal.. 20141. The relevance of these
detects (and the associated PFHxS levels) to U.S. products is unknown.
Populations with Potentially Greater Exposures
Populations that may experience exposures greater than those of the general population
may include individuals in occupations that require frequent contact with PFHxS-containing
products, such as individuals who install and treat carpets or firefighters fATSDR. 2018al. Rotander
etal. (2015a) analyzed serum samples from 149 Australian firefighters at an AFFF training facility.
Mean and median PFHxS concentrations were 10 to 15 times higher than those of the general
population of Australia and Canada. Laitinen et al. (2014) evaluated eight firefighters exposure to
PFHxS after three training sessions in Finland in which AFFF had been used. The authors found that
the firefighters "serum PFHxS concentrations seemed to increase during the three training sessions
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although it was not the main PFAS used in AFFF." Populations living near fluorochemical facilities
where environmental contamination has occurred may also be more highly exposed (ATSDR.
2018b).
Populations that rely primarily on seafood for most of their diet, possibly including some
native American tribes fBvrne etal.. 20171. may also be disproportionately exposed to PFHxS.
Christensen etal. f20171 and Haugetal. f20101 used data on serum PFAS levels and 30-day self-
reported fish and shellfish ingestion rates from NHANES 2007-2014 to explore potential
relationships between PFAS exposures and fish consumption. PFHxS was detected in the serum of
at least 30% of the NHANES participants, and after adjusting for demographic characteristics
shellfish consumption was associated with elevated levels of PFHxS f Christensen etal.. 20171.
1.2. SUMMARY OF ASSESSMENT METHODS
The methods used to conduct this systematic review and dose-response analysis are
summarized in the remainder of this section. A more detailed description of the methods for each
step of the assessment development process is provided in the systematic review protocol released
in 2019 (see Appendix A); the literature inventory for PFHxS in the protocol was not updated after
its release (see Section 2.1). The protocol includes additional problem-formulation details,
including the specific aims and key science issues identified for this assessment
1.2.1. Literature Search and Screening
The detailed search approach, including the query strings and populations, exposures,
comparators, and outcomes (PECO) criteria (see Table 1-4), are provided in Appendix B. The results
of the literature search and screening efforts are documented in Section 2.1. Briefly, a literature
search was first conducted in 2017 and regular yearly updates are performed. The most recent
literate search update that was fully incorporated into the assessment is from April 2022. The
literature from the past year (through March 2023) is in the process of being screened while the
document is undergoing public comment. The results of this literature update and any additional
unscreened studies identified during public comment will be screened against the PECO criteria
and presented in a table that will be included as an Appendix to the assessment. The table will
provide the identified studies that met PECO criteria or certain supplemental evidence categories
(i.e., in vivo mechanistic or MOA studies, including non-PECO routes of exposure and populations;
in vitro and in silico models; and ADME and pharmacokinetic studies) and EPA's judgment on
whether the studies would have a material impact on the assessment conclusions (i.e., identified
hazards or toxicity values) presented in the public comment draft The external peer reviewers are
asked to consider EPA's disposition of these newly identified studies and make recommendations,
as appropriate (see Charge Question 1).
The literature search queried the following databases (no date or language restrictions
were applied):
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1 • PubMed fNational Library of Medicine 1
2 • Web of Science (Thomson Reuters)
3 • Toxline (National Library of Medicine)
4 • TSCATS fToxic Substances Control Act Test Submissions!
5 In addition, relevant literature not found through database searching was identified by:
6 • Review of citations in studies meeting the PFHxS PECO criteria or published reviews of
7 PFHxS; finalized or publicly available U.S. federal and international assessments (e.g., the
8 2021 Agency for Toxic Substances and Disease Registry [ATSDR] PFAS toxicity profile).
9 • Searches of published PFAS Systematic Evidence Maps (SEMs) (Carlson et al.. 2022: Pelch et
10 al.. 20221 starting in 2021.
11 • Review of studies submitted to federal regulatory agencies and brought to the attention of
12 EPA. For example, studies submitted to EPA by the manufacturers in support of
13 requirements under the Toxic Substances Control Act (TSCA).
14 • Identification of studies during literature screening for other EPA PFAS assessments. For
15 example, epidemiology studies relevant to PFHxS were sometimes identified by searches
16 focused on one of the other four PFAS currently being assessed by the Integrated Risk
17 Information System (IRIS) Program.
18 • Other gray literature (e.g., primary studies not indexed in typical databases, such as
19 technical reports from government agencies or scientific research groups; unpublished
20 laboratory studies conducted by industry; or working reports/white papers from research
21 groups or committees) brought to the attention of EPA.
22 All literature is tracked in the U.S. EPA Health and Environmental Research Online (HERO)
23 database (https://heronetepa.gov/heronet/index.cfm/proiect/page/proiect id/2630). The PECO
24 criteria (see Table 1-4) identify the evidence that addresses the specific aims of the assessment and
25 to focus the literature screening, including study inclusion/exclusion.
Table 1-4. Populations, exposures, comparators, and outcomes (PECO) criteria
PECO
element
Evidence
Populations
Human: Any population and lifestage (occupational or general population, including children and
other sensitive populations). The following study designs will be included: controlled exposure,
cohort, case control, and cross-sectional. (Note: Case reports and case series will be tracked as
potential supplemental material.)
Animal: Nonhuman mammalian animal species (whole organism) of any lifestage (including
preconception, in utero, lactation, peripubertal, and adult stages).
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PECO
element
Evidence
Other: In vitro, in silico, or nonmammalian models of genotoxicity. (Note: Other in vitro, in silico,
or nonmammalian models will be tracked as potential supplemental material.)
Exposures
Human: Studies providing quantitative estimates of PFHxS exposure based on administered dose
or concentration, biomonitoring data (e.g., urine, blood, or other specimens), environmental or
occupational-setting measures (e.g., water levels or air concentrations, residential location
and/or duration, job title, or work title). (Note: Studies that provide qualitative, but not
quantitative, estimates of exposure will be tracked as supplemental material.)
Animal: Oral or inhalation studies including quantified exposure to PFHxS based on administered
dose, dietary level, or concentration. (Note: Nonoral and noninhalation studies will be tracked as
potential supplemental material.) PFHxS mixture studies are included if they employ an
experimental arm that involves exposure to a single PFHxS. (Note: Other PFHxS mixture studies
are tracked as potential supplemental material.)
Studies must address exposure to following: PFHxS (CASRN 355-46-4), PFHxS potassium salt
(CASRN 3871-99-6) or PFHxS ammonium salt (CASRN 68259-08-5).
Comparators
Human: A comparison or reference population exposed to lower levels (or no
exposure/exposure below detection levels) or for shorter periods of time.
Animal: Includes comparisons to historical controls or a concurrent control group that is
unexposed, exposed to vehicle-only or air-only exposures. (Note: Experiments including
exposure to PFHxS across different durations or exposure levels without including one of these
control groups will be tracked as potential supplemental material [e.g., for evaluating key
science issues; Section 2.4 of the protocol].)
Outcomes
All cancer and noncancer health outcomes. (Note: Other than genotoxicity studies, studies
including only molecular endpoints [e.g., gene or protein changes; receptor binding or
activation] or other nonphenotypic endpoints addressing the potential biological or chemical
progression of events contributing toward toxic effects will be tracked as potential supplemental
material [e.g., for evaluating key science issues; Section 2.4 of the protocol].)
1 In addition to those studies meeting the PECO criteria and studies excluded as not relevant
2 to the assessment, studies containing supplemental material potentially relevant to the specific
3 aims of the assessment were inventoried during the literature screening process. Although these
4 studies did not meet PECO criteria, they were not excluded. Rather, they were considered for use in
5 addressing the identified key science issues (see Appendix A, Section 2.4) and other potential
6 scientific uncertainties identified during assessment development but unanticipated at the time of
7 protocol posting. Studies categorized as "potentially relevant supplemental material" included the
8 following:
9 • In vivo mechanistic or mode of action studies, including nonPECO routes of exposure
10 (e.g., intraperitoneal injection) and populations (e.g., nonmammalian models)
11 • In vitro and in silico models
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• Absorption, distribution, metabolism, and excretion (ADME) and pharmacokinetic studies
(excluding models)3
• Exposure assessment or characterization (no health outcome) studies
• Human case reports or case series studies
The literature was screened by two independent reviewers with a process for conflict
resolution, first at the title and abstract level and subsequently the full-text level, using structured
forms in DistillerSR (Evidence Partners; https://distillercer.com/products/distillersr-systematic-
review-software/). Literature inventories for PECO-relevant studies and studies tagged as
"potentially relevant supplemental material" during screening were created to facilitate subsequent
review of individual studies or sets of studies by topic-specific experts.
1.2.2. Evaluation of Individual Studies
The detailed approaches used for the evaluation of epidemiologic and animal toxicological
studies used in the PFHxS assessment are provided in the systematic review protocol (Appendix A,
see Section 6). The general approach for evaluating PECO-relevant health effect studies is the same
for epidemiology and animal toxicological studies, although the specifics of applying the approach
differ; thus, they are described in detail in Appendix A (see Sections 6.2 and 6.3, respectively).
Approaches for study evaluation for mechanistic studies is described in detail in Appendix A (see
Section 6.5).
The key concerns for the review of epidemiology and animal toxicological studies are
potential bias (systematic errors or deviations from the truth related to internal validity that affect
the magnitude or direction of an effect in either direction) and insensitivity (factors that limit the
ability of a study to detect a true effect and can lead to a false negative). For example, any types of
random measurement error that may lead to attenuation of study results (i.e., bias toward the null).
In evaluating individual studies, two or more reviewers independently arrived at judgments
regarding the reliability of the study results (reflected as study confidence determinations; see
below) with regard to each outcome or outcome grouping of interest; thus, different judgments
were possible for different outcomes within the same study. The results of these reviews were
tracked within EPA's version of the Health Assessment Workplace Collaboration (HAWC). To
develop these judgments, each reviewer assigned a category of good, adequate, deficient (or not
reported, which generally carried the same functional interpretation as deficient), or critically
deficient (listed from best to worst methodological conduct; see Appendix A, Section 6 for
definitions) related to each evaluation domain representing the different characteristics of the
study methods that were evaluated based on the criteria outlined in HAWC.
3Given the known importance of ADME data, this supplemental tagging was used as the starting point for a
separate screening and review of pharmacokinetics data (see Appendix A, Section 9.2 for details).
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Once all evaluation domains were evaluated, the reviewers collectively considered the
identified strengths and limitations to reach a final study confidence classification:
• High confidence: No notable deficiencies or concerns were identified; the potential for bias
is unlikely or minimal, and the study used sensitive methodology.
• Medium confidence: Possible deficiencies or concerns were noted, but the limitations are
unlikely to be of a notable degree or to have a notable impact on the results.
• Low confidence: Deficiencies or concerns were noted, and the potential for bias or
inadequate sensitivity could have a significant impact on the study results or their
interpretation. Low confidence results were given less weight than high or medium
confidence results during evidence synthesis and integration (see Sections 1.2.4 and 1.2.5).
• Uninformative: Serious flaw(s) were identified that make the study results unusable.
Uninformative studies were not considered further, except to highlight possible research
gaps.
Using the HAWC platform (and conflict resolution by an additional reviewer, as needed), the
reviewers reached a consensus judgment regarding each evaluation domain and overall
(confidence) determination. The specific limitations identified during study evaluation were carried
forward to inform the synthesis (see Section 1.2.4) within each body of evidence for a given health
effect (i.e., study confidence determinations were not used to inform judgments in isolation).
Additional Epidemiology Considerations
While the detailed methods for epidemiology study evaluation are described in the
systematic review protocol (see Appendix A, Section 6.2.1), a few considerations have been
developed further; these are described here.
As noted above, study sensitivity is an important consideration given that it could lead to
false negative (i.e., null) results (Type II error) if a study is underpowered or not designed with
adequate sensitivity to detect an association that may exist A key element for study sensitivity,
along with others described in the systematic review protocol, is whether exposure
contrasts/gradients are sufficient across populations to detect differences in risk. For example, if
measurement error results in inaccurate exposure estimates, this can lead to exposure
misclassification and also influence the ability to detect an association as well as an exposure-
response relationship that may be evident of a biologic gradient
Confounding across PFAS is a potential source of uncertainty when interpreting the results
of epidemiology studies of individual PFAS (e.g., quantifying the effect of an individual PFAS can
potentially be confounded by other PFAS). For confounding to occur, co-pollutants would have to
be associated with PFAS of interest, associated with the endpoint, and not act as an intermediate in
the causal pathway. One way to begin to assess whether co-exposure is occurring is through
examination of correlations. While some PFAS pairs have correlation coefficients consistently above
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0.6 (e.g., PFNA and PFDA), the correlations for most PFAS, including PFHxS, vary from 0.1 to 0.6
depending on the study (see Appendix A, Section 6). For this reason, it was not considered
appropriate to assume that co-exposure to other PFAS was necessarily an important confounder in
all studies. The potential for confounding across PFAS is incorporated in individual study
evaluations and assessed across studies in evidence synthesis. In most studies, it is difficult to
determine the likelihood of confounding without considering additional information not typically
included in individual study evaluation (e.g., associations of other PFAS with the outcome of
interest and correlation profiles of PFAS within and across studies). In addition, even when this
information is considered or the study authors perform analyses to adjust for other PFAS, it is often
not possible to fully disentangle the associations due to high correlations. This challenge stems
from the potential for amplification bias in which bias can occur following adjustment of highly
correlated PFAS fWeisskopf etal.. 20181. Thus, in most studies, there may be some residual
uncertainty about the risk of confounding by other PFAS. A "Good" rating for the confounding
domain is reserved for situations in which there is minimal concern for substantial confounding
across PFAS as well as for other sources of confounding. Examples that would obtain this rating
include results for a PFAS that predominates in a population (such as a contamination event) or
studies that demonstrate robust results following multi-PFAS adjustment (i.e., similar results to
single-PFAS models), which would also indicate minimal concern for amplification bias. Because of
the challenge in evaluating individual studies for confounding across PFAS, this issue is also
assessed across studies during the evidence synthesis phase, as described in the systematic review
protocol (see link in Appendix A, Section 6.2), primarily when there is support for an association
with adverse health effects in the epidemiology evidence (i.e., moderate, or robust evidence in
humans, as described below). Analyses used include comparing results across studies in
populations with different PFAS exposure mixture profiles, considering results of multipollutant
models when available, and examining strength of associations for other correlated PFAS. In
situations for which there is considerable uncertainty regarding the impact of residual confounding
across PFAS, a factor is captured that decreases the overall strength of evidence (see link in
Appendix A, Section 10).
1.2.3. Data Extraction
The detailed data extraction approach is provided in Appendix A, Section 8. Briefly, data
extraction and content management were carried out using HAWC for all health effects for animal
studies and some health effects for epidemiological studies. Data extraction elements collected from
epidemiological, controlled human exposure, animal toxicological, and in vitro studies are
described in HAWC (https://hawcprd.epa. gov/about/). For epidemiological studies not extracted
in HAWC, extraction was performed into Word tables and the extraction elements depended on
information needed for presentation. Not all studies that meet the PECO criteria went through data
extraction: studies evaluated as being uninformative were not considered further and therefore did
not undergo data extraction, and outcomes determined to be less relevant during PECO refinement
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did not go through data extraction. The same was true for low confidence studies when medium and
high confidence studies (e.g., on an outcome) were available. All findings are considered for
extraction, regardless of the statistical significance of their findings. The level of extraction for
specific outcomes within a study may differ (i.e., ranging from a narrative to full extraction of
dose-response effect size information). For quality control, data extraction was performed by one
member of the evaluation team and independently verified by at least one other member.
Discrepancies in data extraction were resolved by discussion or consultation within the evaluation
team.
1.2.4. Evidence Synthesis and Integration
For the purposes of this assessment, evidence synthesis and integration are considered
distinct but related processes (see Appendix A, Sections 9 and 10 for full details). For each assessed
health effect, the evidence syntheses provide a summary discussion of each body of evidence
considered in the review that directly informs the integration across evidence to draw an overall
judgment for each health effect The available human and animal evidence pertaining to the
potential health effects are synthesized separately, with each synthesis providing a summary
discussion of the available evidence that addresses considerations regarding causation that are
adapted from Hill fl9651. Mechanistic evidence is also synthesized as necessary to help inform key
decisions regarding the human and animal evidence; processes for synthesizing mechanistic
information are covered in detail in Appendix A, Section 9.2.
The syntheses of the human and animal health effects evidence focus on describing aspects
of the evidence that best inform causal interpretations, including the exposure context examined in
the sets of studies. The evidence synthesis is based primarily on studies of high and medium
confidence. Low confidence studies could be used if few or no studies with higher confidence are
available to help evaluate consistency, or if the study designs of the low confidence studies address
notable uncertainties in the set of high or medium confidence studies on a given health effect. If low
confidence studies are used, a careful examination of the study evaluation and sensitivity with
potential effects on the evidence synthesis conclusions will be included in the narrative. When
possible, results across studies are compared using graphs and charts or other data visualization
strategies. The synthesis of mechanistic information informs the integration of health effects
evidence for both hazard identification (e.g., biological plausibility or coherence of the available
human or animal evidence; inferences regarding human relevance, or the identification of
susceptible populations and lifestages across the human and animal evidence) and dose-response
evaluation (e.g., selection of benchmark response levels, selection of uncertainty factors).
Evaluations of mechanistic information typically differ from evaluations of phenotypic evidence
(e.g., from routine toxicological studies) primarily because mechanistic data evaluations consider
the support for and involvement of specific events or sets of events within the context of a broader
research question (e.g., support for a hypothesized mode of action; consistency with known
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biological processes), rather than evaluations of individual apical endpoints considered in relative
isolation.
Following the synthesis of human and animal health effects data and mechanistic data,
integrated judgments are drawn across all lines of evidence for each assessed health effect. During
evidence integration, a structured and documented two-step process is used, as follows:
Building from the separate syntheses of the human and animal evidence, the strength of the
evidence from the available human and animal health effect studies are summarized in parallel, but
separately, using a structured evaluation of an adapted set of considerations first introduced by Sir
Bradford Hill (Hill. 19651. This process is similar to that used by the Grading of Recommendations
Assessment, Development, and Evaluation (GRADE) fMorgan etal.. 2016: Guvattetal.. 2011:
Schiinemann et al.. 20111. which arrives at an overall integration conclusion based on consideration
of the body of evidence. These summaries incorporate the relevant mechanistic evidence (or mode
of action [MOA] understanding) that informs the biological plausibility and coherence within the
available human or animal health effect studies. The terms associated with the different strength of
evidence judgments within evidence streams are robust, moderate, slight, indeterminate, and
compelling evidence of no effect.
The animal, human, and mechanistic evidence judgments are then combined to draw an
overall judgment that incorporates inferences across evidence streams. Specifically, the inferences
considered during this integration include the human relevance of the animal and mechanistic
evidence, coherence across the separate bodies of evidence, and other important information
(e.g., judgments regarding susceptibility). Note that without evidence to the contrary, the human
relevance of animal findings is assumed. The final output is a summary judgment of the evidence
base for each potential human health effect across evidence streams. The terms associated with
these summary judgments are evidence demonstrates, evidence indicates (likely), evidence suggests,
evidence inadequate, and strong evidence of no effect. The decision points within the structured
evidence integration process are summarized in an evidence profile table for each considered
health effect.
As discussed in the protocol (see Appendix A), the methods for evaluating the potential
carcinogenicity of PFAS follow processes laid out in the EPA cancer guidelines (U.S. EPA. 2005):
however, for PFHxS, data relevant to cancer were sparse and did not allow for such an evaluation
(see Appendix A, Section 3.3).
1.2.5. Dose-Response Analysis
The details for the dose-response employed in this assessment can be found in Appendix A,
Section 11. Briefly, a dose response assessment was performed for noncancer health hazards,
following exposure to PFHxS via the oral route, as supported by existing data. For oral noncancer
hazards, oral reference doses (RfDs) are derived when possible. An RfD is an estimate, with
uncertainty spanning perhaps an order of magnitude, of an exposure to the human population
(including susceptible subgroups) that is likely to be without an appreciable risk of deleterious
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health effects over a lifetime fU.S. EPA. 20021. The derivation of reference value like the RfD
depends on the nature of the health hazard conclusions drawn during evidence integration. For
noncancer outcomes, a dose response assessment was conducted for evidence integration
conclusions of evidence demonstrates or evidence indicates (likely). In general, toxicity values
are not developed for noncancer hazards with evidence suggests conclusions (see Appendix A,
Section 10.2 for exceptions). Consistent with EPA practice, the PFHxS assessment applied atwostep
approach for dose response assessment that distinguishes analysis of the dose response data in the
range of observation from any inferences about responses at lower environmentally relevant
exposure levels fU.S. EPA. 2012. 20051:
• Within the observed dose range, the preferred approach was to use dose-response
modeling to incorporate as much of the dataset as possible into the analysis. This modeling
to derive a point of departure (POD) ideally includes an exposure level near the lower end
of the range of observation, without significant extrapolation to lower exposure levels.
• As derivation of cancer risk estimates and reference values nearly always involves
extrapolation to exposures lower than the POD; the approaches to be applied in these
assessments are described in more detail in Appendix A, Section 11.2.
When sufficient and appropriate human and laboratory animal data are available for the
same outcome, human data are generally preferred for the dose-response assessment because use
of human data eliminates the need to perform interspecies extrapolations. For reference values,
this assessment will derive a candidate value from each suitable dataset Evaluation of these
candidate values will yield a single organ/system-specific value for each organ/system under
consideration from which a single overall reference value will be selected to cover all health
outcomes across all organs/systems. While this overall reference value represents the focus of
these dose-response assessments, the organ/system-specific values can be useful for subsequent
cumulative risk assessments that consider the combined effect of multiple PFAS (or other agents)
acting at a common organ/system. For noncancer toxicity values, uncertainties in these estimates
are characterized and discussed.
For dose-response purposes, EPA has developed a standard set of models
fhttp://www.epa.gov/bmdsl that can be applied to typical datasets, including those that are
nonlinear. In situations for which there are alternative models with significant biological support
(e.g., pharmacodynamic models), those models are included as alternatives in the assessment(s)
along with a discussion of the models strengths and uncertainties. EPA has developed guidance on
modeling dose-response data, assessing model fit, selecting suitable models, and reporting
modeling results [see the EPA Benchmark Dose Technical Guidance fU.S. EPA. 20121], For each
modeled response, a POD from the observed data was estimated to mark the beginning of
extrapolation to lower doses. The POD is an estimated dose (expressed in human-equivalent terms)
near the lower end of the observed range without significant extrapolation to lower doses. The POD
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is used as the starting point for subsequent extrapolations and analyses. For noncancer effects, the
POD is used in calculating the RfD.
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2. LITERATURE SEARCH AND STUDY EVALUATION
RESULTS
2.1. LITERATURE SEARCH AND SCREENING RESULTS
The database searches yielded 4,432 records, of these records 162 were identified from
additional sources, such as posted National Toxicology Program (NTP) study tables and during
review of reference lists from other authoritative sources fATSDR. 2018bl (see Figure 2-1). No
studies were submitted to EPA. After deduplication, 1,935 unique records were identified, 862 were
excluded during title and abstract screening, and 806 were reviewed at the full text level. Of the 806
screened at the full text level, 446 were considered to meet the populations, exposures,
comparators, and outcomes (PECO) eligibility criteria (see Table 1-4). The studies meeting PECO at
the full text level included 415 epidemiologic studies and 20 animal studies. High throughput
screening data on perfluorohexane sulfonate (PFHxS) are currently available from the EPA's
Chemicals Dashboard fU.S. EPA. 2019bl and relevant information is presented and analyzed in
Appendix D (see Section 3).
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PFHxS
Literature Searches (through April 2022),
PubMed
(n = 1002)
WOS
(n =1064 )
ToxLine
(n = 566)
TSCATS
(n = 10)
Other
Pelch database (n=582)
SCOPUS (n = 1208)
Additional search
strategies (n=162)
TITLE AND ABSTRACT
Figure 2-1. Literature search for perfluorohexanesulfonic acid and related
salts.
2.2. STUDY EVALUATION RESULTS
1 One hundred seventeen epidemiologic studies were identified that met the PECO criteria
2 and report on the potential association between PFHxS and human health effects. The database of
3 animal toxicity studies for PFHxS consists of two short-term oral exposure studies using rats fNTP.
4 2018a: 3M. 2000a), one subchronic study using mice fBiiland etal.. 20111. and three
5 multigenerational studies using rats or mice fRamh0i etal.. 2020: Chang et al.. 2018: Ramhai etal..
6 2018: ButenhoffetaL 2009: 3M. 20031.
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1 Graphical representations of outcome-specific study evaluations are presented and
2 discussed within the hazard sections (see Sections 3.2.1-3.3.1). In cases for which a study was rated
3 medium or low confidence for one or more of the evaluated outcomes, the specific limitations are
4 explained in the synthesis section(s). Detailed rationales for each domain and overall confidence
5 rating are available in Health Assessment Workspace Collaborative (HAWC).
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3. PHARMACOKINETICS, EVIDENCE SYNTHESIS,
AND INTEGRATION
3.1. PHARMACOKINETICS
The following sections review the scientific evidence for the absorption, distribution,
metabolism, and excretion (ADME) of perfluorohexane sulfuric acid (PFHxS). In general, the
evidence described below demonstrates that PFHxS has ADME characteristics of comparable with
other perfluoroalkyl acids (PFAA) that are readily absorbed in the gastrointestinal tract following
oral exposure irrespective of sex or species.
Multiple PFHxS isomers have been identified. Benskinetal. (20091 found evidence of three
PFHxS isomers as minor fractions in a PFOS standard generated using electrochemical fluorination.
They identified the most prevalent of these as the linear isomer (n-PFHxS), and the two others as
branched isomers. The branched isomers were present as a small fraction relative to the linear
isomer4 but were a majority of the PFHxS found in urine 3 days after dosing, as branched isomers
are eliminated more quickly than n-PFHxS. By day 38 the branched isomers, but not n-PFHxS, were
essentially absent in blood (Benskin etal.. 20091. Some pharmacokinetic studies specifically
identified the isomer used (e.g., Sundstrom etal. (20121 used the linear isomer), but others did not
Results from other studies based on measured PFHxS concentrations in blood were therefore
assumed to represent n-PFHxS unless otherwise specified. The current evidence is too sparse to
draw separate judgments for branched and linear isomers, although this review of PFHxS ADME is
interpreted as primarily focused on evidence for n-PFHxS. While branched PFHxS isomers are likely
to have many similar pharmacokinetic (and pharmacodynamic) properties as n-PFHxS, their
contribution to the summary information below (and the toxicity data in Section 3.2) cannot
currently be specified.
Both animal and human data suggest that PFHxS has a high affinity for protein binding.
Bischel etal. f20111 measured 99% bound in a solution of bovine serum albumin and Kim et al.
f2018bl estimated less than 0.08% free in rat plasma and 0.03% free in human plasma. Significant
sex differences in urinary excretion have been reported, suggesting hormonal regulation of
transporters involved in renal reuptake fYang etal.. 20091. The PFHxS serum concentrations
reported at the end of the 28-day NTP bioassay (NTP. 20191 were in fact strongly suggestive both of
sex differences and of saturable resorption in the elimination of PFHxS by rats (see Figure 3-1).
While the dose range was greater for female rats (0-50 mg/kg-day) than male rats (0-10 mg/kg-
4 Based on peak height in a representative chromatogram shown in Figure 1 of Benskin et al. f20091.
quantified by digitization of the published plot, the two branched isomers had concentrations of about 8%
and 15% of the linear isomer in the dosing solution.
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day), it is still clear that plasma levels in the males at 10 mg/kg-day (198 mg/L) were three times
higher than the plasma concentration in females given 12 mg/kg-day (64 mg/L) at the end of the
28-day study. This sex difference was clearly reflected by the differences in clearance and half-life
for male and female rats seen in multiple studies, discussed subsequently. The NTP T20191 data also
clearly indicated strong pharmacokinetic nonlinearity (see Figure 3-1). If absorption and clearance
were independent of concentration the plasma concentrations in Figure 3-1 would be
approximately linear with dose. The PK data discussed below also indicated nonlinearity in either
or both the absorption and clearance. In particular, Huang etal. (2019a) estimated clearance levels
1.5 to 2 times higher after a 32 mg/kg dose than after 4 and 16 mg/kg and a decrease in
bioavailability of about 50% between 4 and 32 mg/kg in both male and female rats. However,
because those PK experiments only used a single dose, they may not have achieved plasma
concentrations high enough to demonstrate the extent of the difference in clearance that might be
needed to explain the NTP data.
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i r
4 6
Dose (mg/kg/d)
10
Figure 3-1. Observed end-of-study of PFHxS in female and male rats in the NTP
bioassay (NTP. 2019) as a function of dose. The plasma concentrations were
measured one day after the final dose, i.e., day 29. While the two data sets look
similar as shown with their respective dose scales, note that significant saturation
occurs in male rats by a dose of 5 mg/kg-day, where the plasma concentration is
80% of that observed at the highest administered dose, while a dose of about 20
mg/kg-day is needed to achieve the same degree of saturation in females, while the
highest concentration in males is twice that in females. The similarity in shape may
occur because binding of PFHxS to the same transporter determines the
nonlinearity in both sexes.
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Serum binding also appears to limit distribution of PFHxS into other tissues, with the
tissue:blood or plasma ratio reported as less than 0.2 for liver and much lower for all other tissues
fKim etal.. 2016b: Benskin et al.. 20091. After the liver, the next highest tissue levels were observed
in kidney, lung, heart, and spleen. Similar to other PFAAs, PFHxS has been presumed to be
metabolically inert, but Sundstrom et al. f20121 only recovered 45%-55% of material between
serum, liver, urine, and feces 96 hours after dosing to Sprague Dawley (SD). The majority (—90%)
of PFHxS was excreted in the urine rather than the feces fKim etal.. 2018b).
A pharmacokinetic (PK) approach was used to extrapolate toxicity points of departure from
animal PFHxS doses and human blood PFHxS levels to a human equivalent (external oral) dose. A
review of the ADME information for rats and humans directly informed the PK approach. Although
no endpoints in mice or monkeys were advanced for dose-response modeling, evaluation of ADME
in those species provided a broader context for interpreting the results in rats and humans. For
example, to what extent might significant differences between PK in male and female rats be
predictive of possible sex differences in humans? Differences or similarities between rats and
monkeys can likewise be indicative of the comparison between rats and humans.
Two key parameters determined were clearance (CL; L/kg-day) and volume of distribution
(Vd; L/kg). For convenience, the following analysis of published data used units of mL/kg-day.
Options for PBPK, and PK modeling were evaluated (see Section 3.1.5). That evaluation informed
the specific choice for dose extrapolation, described in Approach for Animal Human Extrapolation
of PFHxS Dosimetry in Section 3.1.7), while the literature used to support the selection of the PK
parameters and rationale for the approach used are discussed in the relevant Pharmacokinetics
sections below.
3.1.1. Absorption
For the most part, PFHxS data showed near complete absorption after oral dosing. Kim et al.
f2016bl estimated total AUC in blood (AUCo-oo) that was greater after oral compared with IV doses
(4 mg/kg PFHxS) in both male and female rats. This result is counter to general pharmacokinetic
understanding, which assumes that the oral AUC will be lower than the IV AUC due to incomplete
absorption in the gastrointestinal tract. These results may have been an artifact of experimental
variability and the PK analysis used but they indicated complete absorption. Kim etal. (2018b) then
estimated ~90% absorption in female SD rats (92% and 88% absorption at 1 and 4 mg/kg doses,
respectively) and 96% in male SD rats (10 mg/kg dose) based on observations to 14 days
postexposure. While Sundstrom etal. f20121 showed results indicating only 50% oral uptake in SD
rats, this was based on only two animals for the oral PK and observations only to 24-hour post dose,
so are more uncertain. Huang etal. (2019a) estimated a decline in the fraction of PFHxS absorbed
with increasing dose in rats: 98%, 82%, and 52% absorbed in males and apparent values of 142%,
112%, and 71% in females at respective doses of 4,16, and 32 mg/kg. As noted above, reduced
absorption at higher doses would explain in part the observed dose-dependence seen in Figure 3-1.
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While the results discussed above indicate a decrease in bioavailability at higher doses,
pharmacokinetic extrapolation from animals to humans is focused on low doses for which most of
the available data indicated complete absorption, if not greater bioavailability after oral exposure
than IV dosing. A more comprehensive computational analysis of the PK data was conducted (see
Section 3.1.6), including consideration of less than 100% bioavailability; however, that analysis was
unable to resolve the uncertainty in bioavailability. Therefore, 100% bioavailability was assumed
for the purpose of low-dose extrapolation from rats to humans.
The rate of absorption appeared to be more rapid in female rats than in males. Kim et al.
(2016b) reported a Tmax- of 1.4-1.5 hours (0.06 days) in female rats, but 3 days in male rats and Kim
etal. f2018bl likewise reported 1.4 hours in females and 3.1 days in males. However, this difference
in timing may also be confounded by the much slower clearance in male versus female rats (see
below). Huang etal. f2019al obtained a Tmax- of 2-3 hours in female rats and 5-7 hours in male rats,
with a decreasing trend as dose increased. Transporter-mediated processes and protein binding
may have caused dose-dependence of Tmaxfor PFHxS, but the differences in Tmax between dose
groups was not reported as statistically significant by Huang etal. (2019a) and the range of values
for each sex was not large enough to be of consequence for dose extrapolation.
While these results indicated somewhat slower absorption in male than female rats, it is
only by a factor of 2 or 3 fHuang etal.. 2019al. Sundstrom etal. f20121 observed a Tmax of only 0.5
hours in female SD rats and could not estimate a value for male rats due to the short 24-hour
window of observation. The cause for the discrepancy from other studies discussed just above was
unclear. Plotted data indicated very rapid initial absorption in both males and females (Kim etal..
2018b: Kim etal.. 2016b) and by definition peak concentration occurs when the rate of clearance
equals the rate of absorption (which decreases as the remaining dose in the gastrointestinal tract
declines). So, it may simply be that it took longer for the absorption rate to fall below the slow
clearance rate of PFHxS in male rats than female rats.
In male CD-I mice Sundstrom etal. T20121 the observed Tmax was 8 hours at a dose of 1
mg/kg and 4 hours at a dose of 20 mg/kg, while Tmax was 2 days in females at 1 mg/kg, but only 4
hours in female mice at 20 mg/kg. Thus, the predominant results indicated that the majority of
absorption occurs in less than 8 hours in mice, consistent with uptake being in the range of 90% or
higher. It was unclear why Tmax was lower at the higher doses in both males and females. No specific
methodological flaws were identified, but the exact value ofTmax from an experiment depends on
the timing of blood samples (experimental design) and can be affected by experimental variability.
Serum concentrations were measured starting at 2 hours and it is possible that the value of "2" for
female mice dosed with 1 mg/kg PFHxS was actually 2 hours, rather than 2 days. While
bioavailability was not measured in primates, it is reasonable to assume that uptake in monkeys
and humans is likewise fairly efficient
A study on the toxicological response upon dermal exposure to a technical mixture
containing PFHxS showed the presence of PFHxS in serum during the 28-day dosing period and
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after a 14-day recovery period (3M. 20041. Male and female rats were exposed to the product as a
liquid on cotton gauze or as a solid dried onto cotton gauze. PFHxS from both the liquid and dried
product entered systemic circulation through the skin as determined by measurements of serum
PFHxS levels. Male rats showed higher PFHxS serum levels compared with female rats, which was
likely an effect of differential excretion, rather than differential absorption. Male rats showed a
clear accumulation of PFHxS in serum over the duration of the 28-day dosing period and levels
appeared to decrease during the recovery period in the group exposed to the dried formulation.
Male rats exposed to the liquid formulation had peak levels observed after the recovery period. In
female rats, peak concentrations were seen after 14 days of exposure and lower levels were seen
after 28 days of exposure. Levels were lower still after the recovery period. These data suggested a
concern for dermal exposure to PFHxS in both liquid and dried formulations, but further research is
needed to quantify rates of absorption, the resulting relationship between external and internal
dose, and the extrapolation of this information to human exposure.
No data on absorption of PFHxS through the respiratory tract has been found.
There is no direct quantification of oral absorption of PFHxS in humans. However, an
epidemiological study by Stubleski etal. (20161 identified a qualitative association between PFHxS
concentrations in human serum and concentrations in drinking water. Specifically, a 54% increase
in serum levels was observed during the observation period after a large contamination event, but
serum levels only declined 20% after an intervention that decreased drinking water levels by 60%.
The lack of exact correlation may have been due to the timing of sampling versus the contamination
event, as well as to the long half-life of PFHxS in humans.
Given the generally high absorption reported in rats (e.g., 90% for female rats and 96% for
male rats) by Kim etal. (2018b). humans will be assumed to absorb 100% of ingested PFHxS, which
is slightly more health protective compared with assuming 90%-96%.
3.1.2. Distribution
While PFHxS was found at some level in all tissues evaluated, the largest amounts have been
in the liver, followed by the kidneys and lung, with much lower levels in other tissues. For example,
Benskin et al. (20091 reported tissue:blood ratios in male rats on day 3 of dosing at 0.03 mg/kg as
being 17% for liver, 10% for lungs, 5% for heart and kidney, with other tissues being 4% or lower.
Kim etal. f2016bl measured ratios after 72 days in male and 14 days in female rats from 4 mg/kg
doses and obtained ratios of 17% and 11% for male and female liver, respectively; 13% and 8% for
kidney; 5% and 4% for heart; 4% and 3% for lung (each for males and females, respectively); and
2% for spleen in both sexes. This distribution appears to be fairly rapid compared with the overall
time-course in blood: Huang etal. (2019a) showed essentially constanttissue:plasma ratios in
female rat liver and kidney from day 0 to day 8 and in the male rat kidney from 0 to 50 days after a
16 mg/kg dose. Interestingly, the ratio in the male rat liver quickly rose to 5 0%-60% but then
gradually increased to over 80% on day 50 fHuang et al.. 2019al. This time-dependence may have
been due to slower clearance from the male rat liver than the blood and other tissues which may
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confound interpretation of PK data. If the percent distribution to the liver (relative to plasma)
increased over time, then the observed decline in plasma concentrations was not proportional to
whole-body elimination.
The order of tissue concentrations was observed to be the same in mice as in rats, but with
the mouse liver having 25%-40% of serum levels and the kidney ~10% fSundstrom etal.. 20121.
However, measurements of PFAS levels in human cadavers indicated a different ordering of
concentration, with highest levels in kidney (median 18 ng/g), followed by lung (median 5.7 ng/g),
then brain, liver, and bone (2.3,1.8, and 1.2 ng/g, respectively) (Perez etal.. 2013). These human
results should be interpreted with some caution since they do not provide ratios from matched
samples and the specific method of collecting tissues likely differed to some extent (details on the
human tissue collection are not available). But the difference between kidney and liver may be large
enough to suggest a difference between human and rodent PFHxS distribution for these tissues.
Karrman etal. (2010) also examined postmortem liver concentrations in 12 human samples
and compared those to serum concentrations previously observed in the region. This comparison is
severely limited as the serum and liver samples were sourced from different individuals.
Yeung etal. (2013) evaluated PFHxS concentrations in liver versus serum of humans with
hepatocellular carcinoma (HCC) or cirrhosis due to chronic hepatitis C virus (HCV). In these
patients, the liver concentration was 15% of the serum in HCC patients (n = 11) and 9% of the
serum in HCV patients (n = 32). These results need to be interpreted with caution because of the
disease status, but they indicated somewhat lower distribution into the human liver than observed
in rodents. The authors did not have paired liver and serum from healthy individuals for
comparison. In addition to the evidence of distribution to the brain in cadavers, PFHxS has been
observed in the cerebrospinal fluid of neonates, with a median cerebrospinal fluid: blood serum
ratio of 0.0290 from 2 paired samples fLiu etal.. 2022bl. Based on evidence from other PFAS in
humans and rats that the authors reviewed, this ratio is expected to be higher in neonates
compared to adults due to ongoing development of the blood-cerebrospinal fluid barrier.
Intracellular concentrations of PFHxS in the brain are expected to be much higher than the
concentration in the cerebrospinal fluid due to interactions between PFHxS and cytoplasmic
proteins.
A recent study evaluated levels of several PFAS, including PFHxS, in human serum as a
function of various measures of body composition as well as localized measurements of adipose
content throughout the body generated by dual-energy X-ray absorptiometry (DXA) and whole-
body magnetic resonance imaging (WB-MRI) fLind etal.. 20221. There was not an association with
traditional measures of body composition, such as body-mass index (BMI). PFHxS was however
inversely related to total lean mass, leg lean mass, subcutaneous adipose tissue in the arms, trunk
and thigh, and skeletal muscle volume in the arms and legs in men but not in women. Given the
minimal distribution of PFHxS to adipose and muscle tissues described above, one might expect
essentially no effect of the volume of these tissues on serum levels. However, one would predict a
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negative correlation between Vd and body fat, the results in men may be consistent with that
prediction if glomerular filtration increases with body mass or surface area. It is also possible that
the correlation was due to variation in exposure related to body fat or muscle volume that occurs
particularly in males. Matched estimates of exposure from dietary surveys or samples, or matched
measures of urinary clearance (PFAS concentrations in urine) are ultimately needed to determine
whether or not the correlations actually reflect PK variation.
Kang etal. (20201 measured the levels of PFAS in the follicular fluid of women undergoing
oocyte retrieval for in vitro fertilization in relation to their serum levels and observed a median
ratio of 0.84, which is much higher than seen for other various tissues described above. This result
suggested that PFHxS can pass readily through the follicular walls (theca and granulosa cells), and
that binding to proteins in the follicular fluid is similar to that in serum.
Zhao etal. f20151 and Zhao etal. f20171 investigated the role of renal transporters known
to be involved in enterohepatic recirculation of bile acids. Zhao etal. (2015) showed that PFHxS is a
substrate for the human and rat Na+/taurocholate co-transporting polypeptide (NTCP) expressed in
vitro and Zhao etal. (2017) showed that multiple human and rat organic anion transporting
polypeptides (OATPs) likewise transported PFHxS. These active transport processes may
contribute to the relatively high distribution of PFHxS observed in the liver and its long half-life in
rats and humans by limiting biliary excretion. Excretion is also limited by protein binding in the
liver, for example observed in interactions with human liver fatty acid-binding protein (hL-FABP)
(Yang etal.. 2020a: Sheng etal.. 2016). and in serum, discussed subsequently in the Distribution in
Blood/Proteins section. The impact of serum protein binding on renal clearance is also discussed in
the Excretion section (Section 3.1.4) under the Clearance Versus Glomerular Filtration Rate and
Free Fraction in Serum subsection.
Volume of Distribution
Vd is a pharmacokinetic parameter that quantifies the extent to which a chemical
distributes between the blood and the body as a whole and is effectively an average of tissue-
specific distribution ratios. Vd is key in evaluating internal dose because it quantifies the blood
concentration for a given total amount in the body. See Section 3.1.6, Empirical Pharmacokinetic
Analysis, for details of EPA's computational analysis. In rats, mean Vd ranged from 123 to 327
mL/kg among studies, doses, and routes of administration, without a clear sex difference fHuang et
al.. 2019a: Kim etal.. 2018b: Kim etal.. 2016b: Sundstrom etal.. 20121. Only Sundstrom etal.
f20121 evaluated the Vd in mice at two oral doses, and while the values were approximately 25%
lower in females than in males at a given dose, the value for female mice given 20 mg/kg was
between the values for male mice given 1 versus 20 mg/kg. The overall range of Vd in mice (96-195
mL/kg) strongly overlapped the observed range in rats. The Vd in monkeys was also evaluated by
Sundstrom etal. (2012). though only at a single IV dose (10 mg/kg) and was likewise in the range
reported for rats: 213 mL/kg in female monkeys and 287 mL/kg in male monkeys.
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The fact that reported values ofVd were generally below 300 mL/kg and that most tissue-
specific levels were low compared with blood (see previous section) indicated that PFHxS primarily
distributes with extracellular fluid, with the exception of the liver.
Reported values of Vd are listed in Table 3-1, grouped by species and sex. No data to
determine Vd in humans were found.
The biochemical and physiological factors that determine tissue distribution have been
generally presumed to be evolutionarily conserved among mammalian species, an assumption
which was supported by the overall similarity of values across species seen in Table 3-1. However,
species differences in Vd can occur, especially given that the tissue fraction in the body varies
among species, and as shown by Kim etal. f2018bl the distribution to different tissues varies
several-fold. Since nonhuman primates were expected to be closer to humans in body composition
than rats or mice, the Vd values in human males and females was assumed equal to the values
estimated by Sundstrom et al. (20121 for male and female monkeys, respectively. There is
uncertainty in this assumption, that would be reduced by measurements of the PFHxS Vd in
humans.
A Bayesian PK analysis was conducted that combines data from across studies and doses
listed in Table 3-1 for male and female rats and mice (summary in Section 3.1.6, details provided in
Appendix E). This analysis provided both an overall mean and a credible interval for the Vd for each
of these species and sexes. The analysis for rats was restricted to oral dosimetry data because the
reported PK parameters indicated some discrepancy between the results for IV and oral dosimetry
that were unlikely to be resolved by the empirical modeling approach used here, and the bioassay
results that will be extrapolated using the PK parameters are from oral exposures. Because only IV
route data were available for monkeys, those data were used for that species.
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Table 3-1. Estimated Volume of distribution (Vd) values in rats, mice, and
monkeys
Study
Vd (mL/kg)
Notes
Male rats
Sundstrom et al. (2012)
275 ± 5a
10 mg/kg IV, n = 4,10 w time-course
Kim et al. (2016b)
269 ± 52b
4 mg/kg IV, n = 5, 72 d
278 ± 4b
264.4 (255.6-272.6)
4 mg/kg oral, n = 5, 72 d
Kim et al. (2018b)
315 ± 23b
10 mg/kg IV, n = 5,14 d
327 ±10b
293.4(262.9-323.9)
10 mg/kg oral, n = 5,14 d
Huang et al. (2019a)
224 ± 32c
4 mg/kg IV, n = 3/time point, 50 d
123 ± lld
137.8(116.2-159.6)
4 mg/kg oral, n = 3/time point, 50 d
137 ± 9d
144.2 (121.1-166.5)
16 mg/kg oral, n = 3/time point, 50 d
192 ± 17d
210.7(176.9-243.2)
32 mg/kg oral, n = 3/time point, 50 d
Population mean
216.5 (149.2-281.4)
Female rats
Sundstrom et al. (2012)
278 ± 66a
10 mg/kg IV, n = 3, 24 h
126 ± 14a
10 mg/kg IV, n = 4.10 w
Kim et al. (2016b)
289 ± 24b
4 mg/kg IV, n = 5,14 d
256 ±18b
286.9 (264.5-309.6)
4 mg/kg oral, n = 5,14 d
Kim et al. (2018b)
176 ±llb
0.5 mg/kg IV, n = 5,14 d
191 ± 7.5b
1 mg/kg IV, n = 5,14 d
130 ± 5.5b
4 mg/kg IV, n = 5,14 d
154 ± 20b
10 mg/kg IV, n = 5,14 d
187 ± 3.5b
196.0 (117.2-213.6)
1 mg/kg oral, n = 5,14 d
159 ± 7.8b
236.3 (215.5-257.6)
4 mg/kg oral, n = 5,14 d
Huang et al. (2019a)
144 ± 18c
4 mg/kg IV, n = 3/time point, 22 d
155 ± 9d
162.8(142.9-183.2)
4 mg/kg oral, n = 3/time point, 22 d
186 ± 14d
187.9 (166.5-208.5)
16 mg/kg oral, n = 3/time point, 22 d
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Study
Vd (mL/kg)
Notes
264 ± 20d
261.9 (231.9-290.2)
32 mg/kg/ oral, n = 3/time point, 22 d
Population mean
224.2(182.7-266.4)
Male mice
Sundstrom et al. (2012)
129b
1 mg/kg oral, n = 4/time point, 23 w
195b
20 mg/kg oral, n = 4/time point, 23 w
Population mean
154.6(122.6-185.5)
Female mice
Sundstrom et al. (2012)
96b
1 mg/kg oral, n = 4/time point, 23 w
147b
20 mg/kg oral, n = 4/time point, 23 w
Population mean
123.0 (104.5-140.6)
Male monkeys
Sundstrom et al. (2012)
287 ± 52b
282.4 (251.9-314.9)
10 mg/kg IV, n = 3,171 d
Female monkeys
Sundstrom et al. (2012)
213 ± 28b
228.5 (204.4-252.5)
10 mg/kg IV, n = 3,171 d
Values in italics are the mean (90% credible interval) from the Bayesian analysis described in Appendix E (oral
exposure data).
aVdSS from two-compartment PK model.
bVd from noncompartmental PK analysis.
cSum of central and peripheral compartment volumes obtained with a 2-compartment PK model.
dVd from one-compartment PK model.
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While Vd in rodents for a number of PFAS have generally been found to be less than 1,000
mL/kg (1 L/kg), reported values do vary considerably. For example, Huang etal. (2019a) reported
respective male and female rat values for total Vd of:
• 170-340 and 170-420 mL/kg for PFBS;
• 300-680 and 220-420 mL/kg for PFOS given doses of 2 mg/kg; but
• 79 and 56 mL/kg for PFOS given a dose of 20 mg/kg
fDzierlenga et al.. 20191 reported respective male and female rat values for total Vd of:
• 300-620 and 223-560 mL/kg for PFHxA;
• 150-200 and 79-340 mL/kg for PFOA; and
• 410-630 and 270-410 mL/kg for PFDA.
In part, these ranges, and differences in reported Vd values between laboratories reflected
both experimental variability and differences in the pharmacokinetic analyses used, which may
have been more or less sensitive to variability in the data. Experimental design, such as the
timepoints selected for measurement and duration of a PK study also impact Vd estimates. But
some of the variability demonstrated here between different PFAS almost certainly represents true
differences in their chemical properties. A comprehensive review of such factors is beyond the
scope of this assessment, but these data indicated that the reported Vd values for PFHxS were well
within the overall range observed for several other PFAS.
The only study to evaluate Vd in humans directly from human data for PFHxS (vs. using a
value obtained for other PFAS or in other species) was that of Chiu etal. f20221. who applied a one-
compartment PK model in a Bayesian analysis of human serum concentrations matched with
drinking water (DW) concentrations of several PFAS, including PFHxS, from multiple community
studies. The analysis only included adults who were determined unlikely to have occupational
exposure (i.e., for whom DW was likely to be the primary exposure) with corresponding DW
concentrations measured prior to measurement of their serum concentration. The overall approach
and parameter estimation method were considered sound. The value of Vd obtained for PFHxS
(95% CI) was 0.25 (0.15, 0.42) L/kg, which is almost identical to the average of the Vd values
estimated for male and female monkeys (Table 3-1).
Distribution in Blood/Proteins
The low estimated volume of distribution of PFHxS reflects the relatively high amount of the
chemical found in plasma. A major factor in this distribution was attributed to the interaction
between PFHxS and proteins in plasma, including albumin and transthyretin (Alesio etal.. 2022:
Forsthuber etal.. 2020: Bischel etal.. 2011: Weiss etal.. 20091. An investigation of protein binding
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showed that in human plasma PFHxS was 99.98% bound to protein with no sex-specific difference
(Kim etal.. 2018b). The same study reported 99.92% binding to protein in male rat plasma and
99.93% binding to protein in female rat plasma fKim etal.. 2018bl. Binding to plasma proteins may
also drive the partitioning of PFHxS within blood components for which greater levels of PFHxS
were measured in serum and plasma compared with whole blood. Poothong etal. f 20171 found
median ratios of 1.06 between serum and plasma, 1.88 between serum and whole blood, and 1.75
between plasma and whole blood in adult men and women. Hanssen et al. (20131 found a median
ratio of 1.58 between plasma and whole blood in women just after the delivery of a child. Tin etal.
(20161 determined a mass fraction in plasma of 0.87 in adult men and women. Liu etal. (20231
obtained a similar mean fraction in plasma of 0.84 specifically for n-PFHxS, but higher fractions of
0.9 and 0.93 for two branched isomers.
Fetal Blood and Placenta
Studies of the associations between maternal serum levels and umbilical cord blood levels
of PFHxS demonstrated transfer through the placenta (Kang etal.. 2021: Li etal.. 2020a: Chen et al..
2017: Hanssen et al.. 2013: Lee etal.. 2013: Zhang etal.. 2013a: Fromme etal.. 2010: Monrov etal..
20081. Lee etal. f20131. Chen etal. f20171. Kang etal. f20211. Li etal. f2020al and Zhang et al.
f2013al showed greater concentrations of PFHxS in maternal serum relative to cord serum, a
phenomenon that also has been observed for other PFAS such as PFOA and PFOS (e.g., Li et al.
(2020all. Lee etal. (20131 analyzed pairwise data to determine a cord serum: maternal serum ratio
of 0.57 ± 0.29 (mean ± SD). Chen etal. (20171 similarly found a geometric mean cord
serum:maternal serum ratio of 0.54. Kang etal. (20211 calculated an arithmetic mean cord
serum:maternal serum ratio of 0.365. Hanssen etal. (20131 observed a median cord:maternal ratio
of 0.53 in plasma and a median cord:maternal ratio of 0.43 in whole blood from pairwise data.
Zhang etal. f2013al also examined the ratio in whole blood and found a cord:maternal blood ratio
of 0.294. Li etal. f2020al compared cord: maternal serum ratios from preterm versus full-term
deliveries and reported a median ratio of 0.40 for preterm versus 0.72 for full-term, with the
difference being statistically significant The authors suggest that this increase in distribution may
be due to placental aging, resulting in a reduced capacity to limit transfer of xenobiotics, though
they also consider simple accumulation with time as a mechanism (Li etal.. 2020a). Li etal. (2020a)
also evaluated the role of nine placental transporters, testing for correlation between their
expression and the cord:maternal serum ratio. However, the only significant correlation was with
folate receptor alpha (FRa) in preterm deliveries (i.e., not full term), with a positive correlation
coefficient, indicating that FRa facilitates transfer to the fetus.
In contrast, Monrov etal. (20081 observed cord serum concentrations that were
significantly higher than maternal serum concentrations based on a paired t-test and linear
regression analysis. However, these data were highly censored, with the prevalence of samples
above the level of detection in umbilical cord serum (20%) lower than in maternal serum (45.5%).
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The observed relationship between maternal serum and umbilical cord serum could be an artifact
due to the higher prevalence of umbilical cord samples below the level of detection.
To quantitatively compare the distribution between tissues and maternal blood matrices
among different studies, adjustment were made to correct for the distribution among blood
components. As described above, Poothong etal. f20171 measured a median ratio of 1.88 for
serum: whole blood, 1.75 for plasma: whole blood, and 1.06 for serum: plasma concentrations of
PFHxS. These values were used to adjust subsequent tissue:blood matrix ratios to tissue:serum,
when reported for whole blood or plasma.
Serum and plasma are components of whole blood, with the main other component (by
volume) being red blood cells. Assuming that PFHxS partitions completely into the plasma and not
the red blood cells, a theoretical maximum ratio between the plasma and whole blood was
calculated, that is, as if whole blood is a dilution of plasma with red blood cells. The small additional
volume contribution from other components of whole blood not present in plasma or serum were
assumed to not substantially affect this theoretical ratio. The most common metric for the
composition of whole blood is the hematocrit (Hct), which is the ratio of the volumes of red blood
cells and whole blood. In terms of Hct, the theoretical maximum ratio of plasma:whole blood was
calculated as 1/(1-Hct). The normal range of hematocrit for men is 42-52 % and for women is 37-
48 % flordan et al.. 19921. Inputting a typical human male Hct of 45% gave a plasma:whole blood
ratio of 1.82. In females, Hct is typically lower, which resulted in a lower estimated maximum
plasma:whole blood ratio. Using the reported plasma:whole blood ratio of 1.7 and a Hct of 45% the
fraction of PFHxS in plasma (Fp) was calculated to be 1.7 x (1-Hct) = 93.5%, which is very high but
consistent with the high level of plasma protein binding described above. The median ratio of 1.88
serum:whole blood reported by Poothong etal. (20171 is greater than the theoretical maximum and
implies a Hct of >46.8%, which is in the normal range for men, but slightly higher than the normal
range for women. The population of Poothong etal. (2 0171 was approximately 75% women, which
may indicate a deviation from the ideal behavior assumed for the calculation, variation in Hct, or an
experimental error in the measurement of concentrations or in the separation. Partitioning of
PFHxS and other PFAAs between human plasma and blood cells was also investigated by Tin etal.
(20161. who obtained a mean Fp = 91% and report a mean serum:whole blood ratio of 1.6. The
average of serum: blood ratio of 1.6 from Tin etal. (20161 and 1.88 from Poothong et al. (20171 is
1.7. Given Hct = 0.45, this value implies 95.7% of PFHxS is in serum, which is still reasonable.
Therefore, a serum:blood ratio of 1.7 was used to convert tissue partitioning data relative to whole-
blood concentrations to serum-based concentrations below.
The empirical data of Hanssenetal. (20131. although limited by a modest number of
subjects with data over the limit of detection, indicated generally higher serum:whole blood ratios
in cord serum and blood than maternal serum and blood, with ratios for multiple samples
(subjects) reported as 2.2 or higher. This difference can be explained in part by a higher hematocrit
in later gestation and newborns than in adults (mean hematocrit ~51% for gestation week 42 and
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full-term newborns) flopling etal.. 20091. One study included in Table 3-2 below (Zhang etal..
2013a) reported concentrations of PFHxS for whole maternal and cord blood, rather than serum
levels. Therefore, the resulting ratios for matched samples (obtained from the supplemental data of
Zhang etal. f2013all were adjusted by the ratio 0.55;0.49, that is, (1-Hctaduit)/(1-Hctfetus) to account
for the expectation that serum:whole blood concentrations will be higher in the fetal cord blood
than in the adult
With the adjustment noted above, median (mean) values of cord serum:maternal serum
ratios in humans atchildbirth were 0.53 on average (see Table 3-2). Thatthe value is roughly 50%
indicated that the placenta may limit transfer of PFHxS from the mother to the fetus, but if
distribution to fetal tissues is increased in proportion to water content of tissue, as discussed
below, then an overall higher concentration in the fetus versus maternal tissue is predicted. There
was not an apparent trend in the ratio related to the maternal sample timing relative to childbirth
(i.e., whether taken before, at, or after childbirth) or the fraction of cord or maternal serum
measurement below the limit of detection, although as described above Li etal. (2020a) reported a
significant increase in the ratio from preterm to full-term deliveries. Examination of the standard
deviation of the mean of medians and mean of means shows that the two values are, on average,
similar, suggesting thatthe distribution of cord serum:maternal serum ratio is symmetric. However,
it is notable that the reported median value is lower than the mean value in almost every study.
Table 3-2. Measured cord serum: maternal serum ratios
Cord serum: maternal
serum ratio
% > LOD
Study
Median
Mean
Cord
Maternal
Maternal sample timing
Chen et al. (2017)
0.55
0.6
97%
97%
Within 3 d prior to delivery
Hanssen et al. (2013)
0.54
0.63
100%
100%
3-5 d after delivery
Kane et al. (2021)
0.315
0.365
97%
100%
At delivery, exact timing not clear
Kim et al. (2011b)
0.65
0.64
100%
100%
20-41st wk of pregnancy, mostly
in 3rd trimester
Lee et al. (2013)
0.5
0.57
100%
100%
At delivery, exact timing not clear
Liu etal. (2011)
0.73
0.95
96%
98%
Within 1 wk after delivery
Yang et al. (2016b)
0.35
0.43
100%
100%
1-2 d before delivery
Yang et al. (2016c)a
0.52
0.63
96%
100%
Within 1 wk after delivery
Zhang et al. (2013a)
0.332
0.387
100%
100%
Within 1 hr prior to delivery
Li et al. (2020a) preterm
0.40
NR
81%
81%
Within 1 wk before delivery
Li et al. (2020a) full-term
0.72
NR
94%
94%
Within 1 wk before delivery
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Cord serum: maternal
serum ratio
% > LOD
Study
Median
Mean
Cord
Maternal
Maternal sample timing
Overall meanb
0.50±0.14
0.58±0.17
NR = not reported.
aCord: maternal serum ratios for this study are the ratio of the reported median (mean) values for cord and
maternal serum.
bMean and standard deviation of the set of medians or means.
After correction for the serum:whole blood ratio as described above, comparisons between
maternal serum and placenta were reasonably consistent: Chen etal. (20171 observed median
(mean) placenta:maternal serum = 0.421 (0.429) and applying the serum:whole blood factor of 1.7
to the results of Zhang etal. f2013al the EPA obtained median (mean) = 0.266 (0.289). Chen et al.
f20171 suggested that the difference between their results and those of Zhang etal. f2013al was
due to variation in isomeric composition between the two study populations or the greater range in
concentration in the placentas in the study of Zhang etal. (2013a). but with the correction applied
here it appears to be modest The volume of distribution estimated for PFHxS in female monkeys
was Vd = 0.213 L/kg (Sundstrom etal.. 2012). which represents the average of distribution into all
tissues. While the placenta distribution measurements in humans of Chen et al. f2 0171 and Zhang et
al. f2013al were 1.5 to 2 times higher than this value for female monkeys, Kim etal. f2018bl
showed greater variability in PFHxS concentrations between specific tissues of rats. Hence, the
reported placenta: serum levels of Chen etal. f 20171 and Zhang etal. f2013al were not outside the
range one would expect for a specific tissue given an overall Vd of 0.213 L/kg, i.e., if distribution to
adipose and muscle was substantially less than internal organs, as was observed for rats by Kim et
al. C2018bl.
As umbilical cord blood followed the same trend as in adult blood, the results from Chen et
al. f20171 and Zhang etal. f2013al were consistent with a concentration trend of cord
serum > placenta > cord whole blood.
One study that distinguished between isomers of PFHxS found the greatest prevalence of
the linear relative to the branched isomer in cord serum (97% linear), followed by maternal serum
(86% linear) and placenta (77% linear) (Chen etal.. 2017).
Distribution in Fetal Tissues and Children
One study provides a relatively unique dataset of PFHxS concentrations in human fetal
tissues obtained from voluntary abortion (gestation week < 12) or after intrauterine fetal death in
the second and third trimester, and in maternal serum collected at these times (Mamsen etal..
2019). However, PFHxS was detected in only 6% of fetal tissues, making it difficult to interpret
these data quantitatively.
Pharmacokinetic modeling of PFOA dosimetry in humans by Goedenetal. (2019) suggested
a reason why observed tissue levels of PFAS in the fetus and young children may have been greater
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than in adults: the greater amount of extracellular water in the tissues of fetuses and children
fFriis-Hansen, 19611 led to a greater distribution of PFAS into these tissues. As noted above, the Vd
values estimated for adult rats, mice, and monkeys are consistent with the assumption of
distribution in body water. The amount of extracellular water in newborns was estimated to be 2.4
times higher than adults fFriis-Hansen. 19611 (see Figure 3-2).
Ratio of Extracellular Tissue Water in Children vs. Adults
2.6
Age (y)
Figure 3-2. Ratio of extracellular water (% of body weight) in children versus
adults. Values (points) were calculated from results in Friis-Hansen f!961) and
plotted at the mid-point for the corresponding age ranges evaluated.
Mamsenetal. f20191 (described briefly above) only detected PFHxS in 6% of fetal tissue
samples and did not report ratios of fetal tissue to maternal serum for PFHxS. So, while their data
may indicate that average fetal levels are much lower than maternal levels, they cannot be used to
quantify the fetal-maternal relationship. Since PFHxS is amphiphilic, with Vd < 1 in adults, it is not
expected to distribute with or in proportion to body fat and therefore fetal body fat content is not
considered an appropriate predictor of fetal PFHxS distribution. Given the overall lack of data on
fetal distribution of PFHxS, EPA considers any estimate of such distribution to be uncertain. In the
face of this uncertainty, EPA chose the simplest assumption for prediction of fetal body burdens:
that distribution between fetal serum and fetal tissues is the same as the distribution between
serum and tissues in the newborn. The alternative, which would be to assume that there is a
discontinuity (sudden increase or decrease) in the body burden of the offspring at the moment of
birth, would require a more specific assumption about the magnitude and direction of that
discontinuity. Likewise, assuming any other change in Vd over the time of fetal development and
birth would also have no supporting data and therefore involve equal or greater uncertainty. There
are no clear developmental PK data for PFHxS that could be used to guide a choice among these
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alternatives. Hence, EPA simply assumed that the ratio of body water in the newborn versus adults
(2.4) also applies to the fetus.
Since the Vd in a human woman (mother) is assumed to be the same as in monkeys, given
the assumption that Vd in a fetus is 2.4 times higher than an adult, the estimated Vd in a female
fetus relative to fetal serum is 2.4 x 0.213 L/kg = 0.511 L/kg and in a male fetus 2.4 x 0.287
L/kg = 0.689 L/kg. But as described above, the average ratio of PFHxS in cord serum, which is
assumed to be fetal serum, compared with maternal serum was rf:m = 0.52. Together, these values
and assumptions led to the prediction that relative to maternal serum, the Vd for the fetus as a
whole is 0.52 x 0.511 L/kg = 0.266 L/kg for females and likewise 0.358 L/kg for males, indicating
average fetal tissue concentrations is 25% higher than average maternal tissues for girls and 68%
higher for boys. Hence, the body burden in the newborn can be estimated using the following
equation:
amount of PFHxS in newborn = rf:m x Cmother x Vdnewborn x BWnewborn, (3-1)
where rf:m = 0.52 and Vdnewborn is 0.511 L/kg for girls and 0.689 L/kg for boys.
The average weight of a newborn is only 5% of maternal body weight (3.4 versus 68 kg), so
while distribution into the male fetus was estimated to be 68% higher than maternal tissues, the
effect on Vd of the mother and fetus together (i.e., total amount in the mother and fetus compared
with maternal serum concentration) was thereby estimated to be less than 3.4% (5% x 68%).
Therefore, the Vd for mother and fetus together during pregnancy was simply assumed equal to the
value for the adult woman (0.213 L/kg), although the amount in the newborn child was calculated
as described above. Because the maternal weight just after childbirth is reduced by more than the
weight of the newborn, reflecting the loss of amniotic fluid, placenta, etc., this choice effectively
assumed slightly less PFHxS mass is lost with those fluids than would be calculated if total maternal
and fetal Vd were increased. The interpolation function shown in Figure 3-2 can be multiplied by
the adult Vd (L/kg) to obtain the corresponding value for children under 10 years of age, as was
done by Goeden etal. (2019). However, an opposing factor is the approximately 20% larger blood
volume as a fraction of BW in young children compared with older children and adults (Darrowet
al.. 1928). given that a high fraction of PFHxS is bound to blood proteins. More specifically, the mass
of PFHxS bound to blood proteins would increase in proportion to the total mass of those proteins,
which one might expect to increase in proportion to blood volume. Hence, a 20% larger blood
volume could be expected to reduce the PFHxS available for distribution to tissues by 20%. So,
instead of an increase of 2.4-fold in Vd in newborns one might predict an increase of 1.9-fold (i.e.,
80% x 2.4).
Trend in Pregnancy
Four studies investigated how PFHxS levels tend to change during pregnancy and nursing.
Monrovetal. f20081 found that mean maternal serum PFHxS concentration did not change
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between sampling at 24-28 weeks and sampling at delivery. Likewise, Oh etal. (20221 observed
only a slight average decrease in maternal PFHxS over the course of pregnancy, not statistically
significant fVarsi etal.. 20221 observed PFHxS serum concentrations in pregnant women at 18, 28,
and 36 weeks. Total PFHxS concentrations were relatively constant during this time, but there were
differences observed between PFHxS isomers. Linear PFHxS decreased during pregnancy and was
lower than concentrations observed in women who had never been pregnant at all timepoints.
Branched PFHxS however was highest at the 36 week timepoint, compared to concentrations at 18
and 28 weeks and compared to the non-pregnant women. Glynn etal. (20121 presented data for
other PFAS on the relative serum concentrations during pregnancy and nursing but did not present
that information for PFHxS, although PFHxS was included in other analyses in that study.
Breast Milk
PFHxS has been observed in human breastmilk, indicating that nursing acts as a route of
excretion for the mother and a route of exposure for her infant (Kim etal.. 2011b: Karrman et al..
2010: Karrman et al.. 20071. Blomberg etal. (20231 evaluated longitudinal changes in breast milk
concentrations of PFHxS between delivery and up to 8 months postpartum; while milk
concentrations declined among the women with the highest levels at 0-2 months postpartum (i.e.,
over 500 pg/mL), they were more constant among those with early concentrations of 300 pg/mL or
lower. This decrease can be viewed as supporting this hypothesis, but some caution is needed in
interpreting these data as the drinking water source for the most highly exposed part of the cohort
was switched to a less contaminated source as soon as the contamination was identified, i.e.,
decreased exposure through drinking water could also drive decreased breast milk concentrations,
independent of excretion through breast milk. However, Oh etal. (20221 observed a significant
decline in maternal serum levels (average decline of 5.6%) during the first six months postpartum
in a population with typical PFHxS exposure (with no intervention to reduce exposure). This
provides some additional potential evidence of increased excretion of PFHxS after giving birth,
without an artificial change in PFHxS exposure.
In paired milk and maternal serum samples, the concentrations were highly correlated
(Pearson r2 = 0.8) (Karrman etal.. 20071. The concentration of PFHxS in breastmilk was reported to
be lower than the concentration in paired maternal serum, with ratios between milk and maternal
serum of 0.02 fKarrman etal.. 20071 and 0.008 fKim etal.. 2011bl. Karrman etal. f20101 reported
PFHxS concentrations in breast milk samples but did not have paired maternal blood levels, which
limits the ability to specify the distribution into breast milk compared with other body
compartments. Another study found that PFHxS was below the limit of detection in all breast milk
samples collected (Liu etal.. 20111. Mondaletal. (20141 investigated the association between
PFHxS concentration in maternal and infant serum and the length of breastfeeding and found that,
although there were associations consistent with breastfeeding acting as a route of excretion for the
mother and a route of exposure for the infant, none of the associations rose to the level of
significance. Significant associations were found for other PFAS studied and negative associations
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for maternal serum and length of breastfeeding and positive associations for infant serum and
length of breastfeeding were consistent across PFAS. Varsi etal. (20221 observed paired maternal
and infant serum concentrations, with one infant timepoint at 6 months of age, and six maternal
timepoints, three during pregnancy and four postpartum. At 6 months after delivery, the relative
concentrations of PFHxS in the infant and mother differed by isomer, with the infants having a
higher median linear PFHxS concentration and a lower median branched PFHxS compared to the
mothers. Similarly, the branched:linear isomeric ratio was lower in the infant compared to the
mother. This could indicate a preferential transfer of the linear isomer to the infant, either during
gestation or lactation. Potential evidence for gestational transfer is the increase in maternal
branched:linear isomeric ratio that the authors observed between the 28th and 36th week of
pregnancy. Evidence for lactational transfer is the association the authors observed between infant
linear PFHxS concentration and months of exclusive breastfeeding, a relationship that was not
present for the branched isomer.
3.1.3. Metabolism
Due to the high stability of the perfluoroalkyl bonds, PFHxS is thought to not be metabolized
in mammals, as was seen for similar PFAS fLau etal.. 20071. Studies have examined similar PFAS,
including perfluorooctanoic acid (PFOA) and perfluorodecanoic acid (PFDA) and identified only the
parent compound in excreta fVanden Heuvel et al.. 1991a. b). The sulfonate analog of PFOA,
perflurosulfonic acid (PFOS), is also not metabolized fLau etal.. 20071.
3.1.4. Excretion
Animals
Several studies examined the excretion of PFHxS from animals, particularly rats, after a
controlled exposure fHuang et al.. 2019a: Kim etal.. 2018b: Kim etal.. 2016b: Sundstrom etal..
2012: Benskin etal.. 20091. Excretion has been observed in urine and feces, with renal excretion
being the most prominent route. Other studies have only indirect observation of excretion through
the decreasing amounts of PFHxS in the serum over time. As PFHxS is not metabolized, decreases in
serum concentration after the distribution phase were attributed to excretion, assuming a constant
serum:tissue ratio. As noted above, the distribution phase may not be complete after a relatively
short time given the shifts in liver: serum ratio observed over 50 days fHuangetal.. 2019al. To
quantify the impact of such a shift on estimated excretion would require a PBPK model for PFHxS
that accounts for the time-dependence in specific tissue volumes and distribution, which is not in
the realm of available science. Since the extended time-dependent distribution appears to be
confined to the liver, the analysis based on empirical evaluation of excretion was still assumed to
provide a sufficient approximation for dosimetric extrapolation.
In animal studies, urinary excretion was greater than fecal excretion. There was a strong
sex-dependence in rats and mice in renal excretion with female rats excreting more of the total
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dose in urine. Specifically, Kim etal. (2018bl reported 15.9% of the initial IV dose was excreted in
urine and 1.3% of the dose was excreted in feces in male rats and 39.1% of the dose was excreted in
urine and 3.1% of the dose was excreted in feces in female rats after 14 days. Similarly, after an oral
dose, in male rats 18.5% of the dose was excreted in urine and 2.8% in feces, while in female rats
36.8% of the dose was excreted in urine and 3.3% in feces. In another study Kim etal. f2016bl.
reported that female rats excreted 28.02% of an IV dose in urine after 14 days while male rats
excreted 8.26% of the dose in urine after 72 days. Sundstrom etal. (20121 reported that twenty-
four hours after an IV dose, female rats excreted 13.28% of the dose, while male rats excreted
0.70% of the dose.
In mice, the total dose excreted in 24 hours was dose dependent, with 0.882% of a 1 mg/kg
dose and 1.654% of a 20 mg/kg dose excreted in males and 0.317% of a 1 mg/kg dose and 2.552%
of a 20 mg/kg dose excreted in females f Sundstrom etal.. 20121. The lower excretion in female
versus male mice for the 1 mg/kg dose was the only situation with a greater male rodent excretion
(Sundstrom etal.. 20121. Urinary excretion was slower in monkeys, with 0.102% of an IV dose
excreted in urine in 24 hours in male monkeys and 0.055% of the dose in female monkeys
(Sundstrom etal.. 20121. Unlike rodents, there was not a clear difference between monkey sexes in
the amount of urinary excretion.
In addition to observations in excreta, multiple studies also estimated the rate of decrease
in serum or plasma levels of PFHxS in the form of a half-life or clearance (CL) in rats fHuang etal..
2019a: Kim etal.. 2018b: Kim etal.. 2016b: Sundstrom etal.. 2012: Benskin etal.. 20091. While all of
these studies appear to have been conducted with appropriate quality, there is significant variation
in the results. For example, Kim etal. (2018b) estimated a CL of 228 mL/kg-day in female rats after
an intravenous (IV) dose of 4 mg/kg, while Huang etal. (2019a) estimated a CL of 46 mL/kg-day in
female rats after an oral dose of 4 mg/kg. Despite the significant variability in the results between
studies, routes of exposure, and to an extent, doses of PFHxS, a quite consistent result is that the CL
in male rats is about an order of magnitude lower than female rats, and so the subsequent analysis
evaluates parameters for male and female rats separately.
An issue found in the PK data is that for some studies that used both IV and oral doses, the
blood AUC was higher after the oral dose than after the same dose given IV, which contradicts
classical PK analysis. For example, given doses of 4 mg/kg Kim etal. (2016b) reported an AUC
almost twice as great after oral dosing than after IV dosing in female rats, and Huang etal. f2019al
reported an AUC 40% higher after oral dosing than after IV. By classical PK analysis one expects
that only a fraction of an oral dose will be absorbed but that the subsequent distribution and
elimination are otherwise identical to what is observed after IV dosing. In that case, the AUC after
oral dosing would be less than or equal to the AUC after IV dosing, to the extent that there is limited
oral bioavailability. A key assumption in this classical analysis is that distribution and elimination
are independent of the exposure route, and EPA interpreted these discordant empirical results as
suggestive that this assumption is incorrect. EPA's analysis of PK data supported this possibility,
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with a trend of greater clearance following IV exposure compared to gavage in female rats (see
3.1.6 Empirical Pharmacokinetic Analysis). The mechanistic explanation for this difference is not
obvious. Excretion could be greater after IV dosing if, immediately after dosing, a smaller
proportion of PFHxS is bound to tissue phospholipids and serum proteins compared with the oral
dosing scenario. This could occur if equilibration between bound and free PFHxS takes some time.
Absorption from the GI tract is slower and PFHxS first passes through the liver (where a significant
fraction is retained) before systemic distribution, which would allow for equilibration between free
and bound states as PFHxS enters the blood. Thus, a higher fraction of PFHxS could have been
bound when first reaching general circulation after oral dosing than after IV dosing, such that the
urinary excretion after oral dosing was slower. A similar mechanistic explanation for differences in
protein binding is that passage through the acidic environment of the stomach results in a greater
proportion of the PFHxS anion, which could facilitate binding and thus limit excretion compared to
IV exposure.
Because the toxicological bioassays that will be interpreted with the PK model used oral
administration, it was considered clearly preferable that the PK parameters used should reflect that
route of exposure. Given the oral-IV discrepancies noted above, only results from oral PK
experiments were evaluated for rats and mice. Key PK parameters from these oral PK experiments
are listed in Table 3-3.
A factor to be noted in Table 3-3 and discussed previously was thatthe data of Huang et al.
(2019a) indicate higher CL in male and female rats given a dose of 32 mg/kg compared with 4 and
16 mg/kg. While the difference was not indicated as statistically significant, it was consistent with a
mechanism of saturable renal resorption (Weaver etal.. 2010: Yang etal.. 2009) and with the end-
of-study serum concentration data shown in Figure 3-1 (NTP. 2019). Comparing results for the
lower two doses, the CL estimated by Huang etal. f2019al for 16 mg/kg in female rats was 25%
higher than that estimated at 4 mg/kg and the CL for 16 mg/kg in male rats was 19% higher than
that estimated at 4 mg/kg. Although not statistically significant, this was interpreted as likewise
consistent with some dose-dependence. On the other hand, the CL reported for female rats at 32
mg/kg by Huang etal. (2019a) was below that reported by Kim etal. (2016b) at 4 mg/kg and the CL
for male rats at 32 mg/kg by Huang etal. (2019a) was below that estimated from the results of
Benskin et al. (2009) presumably due to inter-study variability. Hence, subsequent PK analyses
included data for all dose levels from Huang etal. f2019al.
Overall mean CL values and confidence intervals for male and female rats, mice, and
monkeys were obtained by Bayesian PK analysis of all the oral PK data for each sex of rodents and
the IV PK data for each sex of monkeys (summary in in Section 3.1.6, analysis details provided in
Appendix E).
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Table 3-3. Summary of estimated clearance values in animals
Citation
Dose (mg/kg)
CLa(ml7kg-d)
n
Male rats
Benskin et al. (2009)
0.03
9.85b
7
Kim et al. (2016b)
4
7.15
5.71 (5.46-5.69)
5
Kim et al. (2018b)
10
6.65
6.58 (3.34-9.68)
5
Huang et al. (2019a)
4
4.82
5.37 (4.61-6.14)
3C
16
5.74
5.91 (5.09-6.75)
3C
32
9.02
9.74 (8.47-11.03)
3C
Population mean
7.15(3.73-10.26)
Female rats
Kim et al. (2016b)
4
124.8
117.8 (110.7-125.3)
5
Kim et al. (2018b)
1
81.1
83.02 (77.22-89.38)
5
4
65.3
106.3 (98.58-113.8)
5
Huang et al. (2019a)
4
46.1
50.14 (45.03-55.01)
3C
16
59.0
61.36 (55.58-67.17)
3C
32
92.2
94.54 (85.43-103.3)
3C
Population mean
84.10 (64.72-103.8)
Male Mice
Sundstrom et al. (2012)
1
4
20
4
Population mean
3.86(3.27-4.41)
Female mice
Sundstrom et al. (2012)
1
4
20
4
Population mean
3.18 (2.83-3.52)
Male monkeys
Sundstrom et al. (2012)
10
1.33 ±0.12
1.39 (0.94-1.83)
3
Female monkeys
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Citation
Dose (mg/kg)
CLa(miykg-d)
n
Sundstrom et al. (2012)
10
1.93 ±0.41
2.12 (1.81-2.44)
3
Only oral exposure results are shown for rats because there were discrepancies between oral and IV data that
could not be resolved and the oral route was used in the bioassays evaluated for toxicity. Only oral dosimetry
data were available for mice and only IV dosimetry data were available for monkeys (results shown; (Sundstrom
etal.. 2012)).
aValues in italics are mean (90% credible interval) from Bayesian analysis (details in Appendix E).
Calculated from reported half-life (To.s) for n-PFHxS as CL = ln(2)*Vd/To.s using the geometric mean of Vd values
for male rats listed in Table 3-1. Serum time-course data were not available from Benskin et al. (2009), so results
from this study were not used in the Bayesian analysis.
cNumber of rats per time point, but each rat had blood taken at no more than two time points, so the total number
of rats used per dose level where much higher (Huang et al., 2019a).
While the results summarized in Table 3-3 were obtained by empirical analysis for total
clearance, it is worth noting the fraction of PFHxS eliminated in feces reported by Kim etal. f2018bl
was used as a means of estimating fecal clearance in humans. These data were used to estimate
total clearance for studies where renal clearance was measured and were deemed most
appropriate as primate and human-specific data were unavailable. The ratio of average PFHxS
excretion in feces versus urine was 8.2% and 7.9% in male and female rats, respectively, after IV
dosing and 15.1% and 9.0%, respectively, after oral dosing fKim etal.. 2018bl. The higher fraction
eliminated in feces after oral dosing was attributed in part to incomplete absorption by that route.
Therefore, an average value of 8% from the IV data was used for extrapolation to humans.
The excretion of PFHxS has been observed in humans both directly through measurement
of PFHxS in urine and indirectly through the observation of changes in serum or plasma
concentrations over time. Changes in serum or plasma concentrations are informative of excretion
because PFHxS is not metabolized, thus any observations of decreasing concentrations in blood
after the distribution of the chemical were attributed to excretion. Most observations were within
populations with higher exposure than the general population, either workers in fluorochemical
production fFu etal.. 2016: Gao etal.. 2015: Olsen etal.. 20071. workers at a fishery where the
waters were contaminated with PFAS fZhou etal.. 20141. or with increased exposure via
contaminated drinking water fLi etal.. 2018: Worlev et al.. 20171. For measures of clearance and
half-life, geometric means were presented unless otherwise specified because geometric means are
less influenced by extreme values that are common in these skewed distributions.
Humans
Half-life estimates
Four studies reported half-life values for PFHxS based on observations of decreasing serum
levels in individual subjects at multiple time points after decreased exposure, either due to
retirement after occupational exposure fOlsen etal.. 20071. replacement of the foam used by
firefighters fNilsson et al.. 20221 or to the introduction of drinking water filtration at an
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occupational site (Li etal.. 2022b: Li et al.. 20181. Li etal. (2022b) is a follow-up analysis of the
population evaluated by Li etal. (20181. All four studies, the Nilsson et al. study and the Olsen et al.
study fit the data for each person separately. Several plots in Olsen etal. f20071 showed declines in
serum levels over time that were very close to log-linear (i.e., showed negligible positive curvature),
which is suggestive of little effect of ongoing exposure for those subjects. However, Li etal. f2022bl
obtained a shorter half-life using data collected between six months and one year after the end of
exposure (mean ti/2 = 3.85 years) compared to using data collected 1-2.5 years after the end of
exposure (mean ti/2 = 4.33 years) or 2.5-4.5 years after the end of exposure (mean ti/2 = 4.62
years). Positive curvature in a serum time-course plot after a decrease in exposure (for example
retirement), which is indicated by these results from Li etal. f2022bl. is evidence of background
exposure, as can be observed by examining Eq. 2 in fBartell. 20121. The differences among half-lives
values for the time periods of evaluation reported by Li etal. f2022bl. less than 20%, are not
statistically significant, however. Li etal. (20181 reported a mean half-life of 7.4 years in males
(n = 20) and 4.7 years in females (n = 30) aged 15-50 years old while Li etal. (2022b) reported a
median (5th, 95th percentile) half-life of 5.4 (2.34, 9.29) years (n = 114). Olsen etal. (20071 reported
a half-life of 8.5 years in their cohort, which consisted of 2 females and 24 males at retirement.
The population of Li etal. f2022bl included children and the mean half-life for those
participants 1-14 years of age was 3.01 years compared to 5.26 years for participants 15-50 years
of age and 6.41 years in participants over 50 years. The much lower apparent half-life in the 1-14
year old group is almost certainly the result of PFHxS dilution into the growing bodies of the youth.
The intermediate half-life for participants 15-50 years of age may be partly attributed to the
difference between males (mean 5.39 years) and females (mean 4.48 years) which correlates with
the expected higher clearance due to menstrual fluid loss for women in that age range. This
difference of 17% in half-life is in contrast to minimal differences of less than 2% between males
and females aged 1-14 and less than 3.7% between males and females over age 50.
Nilsson etal. f20221 analyzed PFHxS concentrations in firefighters after PFHxS was
removed from the formulation of the foam used for fire suppression. (97.5% of the recruited
population were male and the exact number of women in each sub-cohort was not reported, so the
results will be assumed to represent males.) The subjects had a range of serum concentrations at
the start of the study that overlapped with those found in the general population, which would
come from other exposure sources that are presumed to be shared by the study subjects. Since the
level of these other exposure sources is not precisely known and likely varies over time, the
contribution from them represents an uncertainty that would particularly impact half-life estimates
of subjects with initial concentrations in the general population range. Therefore, EPA chose to use
the results reported for only those subjects who's initial PFHxS concentration was greater than the
95th percentile of the general population, which ranged from just above that 95th percentile to over
20 times higher. Nilsson etal. f20221 reported a mean (95% CI) half-life of 7.7 (7.1, 8.3) years for
this group without background subtraction and a mean (95% CI) half-life of 6.7 (6.2, 7.2) years after
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subtracting age-specific average concentrations reported for the general Australian population. The
half-life calculation assumes a simple exponential decay, which would only be accurate with no
ongoing exposure or if background exposure is constant, allowing it to be addressed by simple
subtraction, and is reasonable estimated based on results from other study populations, albeit from
the same country. The modest difference in the mean half-lives obtained with and without
background subtraction for the highly exposed group indicates that background exposure had some
impact on the observed changes in serum levels for that group, but less than 15%. Hence, the value
obtained for the highly exposed group with subtraction is considered to be appropriate for
describing the elimination of the PFHxS from occupational exposure of this cohort with a minimal
level of uncertainty due to the assumptions involved.
Worlev etal. f20171 estimated a population half-life by fitting a PK model to population
mean serum concentrations at two timepoints with an estimated ingestion rate for that population.
Because Worlev etal. (20171 did not evaluate individual elimination, only measured serum levels at
two time points, and relied on an estimated exposure level, their study was considered to have
greater uncertainty than the other studies, with results that are more difficult to interpret in terms
of being a mean or geometric mean of individual values. In particular, it is possible that the drinking
water concentration was not constant as was assumed by Worlev etal. f20171 or that there were
other significant sources of ongoing exposure. Because of these methodological concerns, the
results of Worlev etal. f2 0171 were not used in estimating an overall average clearance for humans,
although it is noted that the corresponding clearance (0.031 mL/kg-day) is identical to the
estimated geometric mean across other studies (see Table 3-4).
As described in Volume of Distribution (in Section 3.1.21. Chiu etal. (20221 applied a one-
compartment PK model in a Bayesian analysis of human serum concentrations matched with
drinking water (DW) concentrations of several PFAS, including PFHxS, from multiple community
studies. Since the overall approach and parameter estimation method were considered sufficiently
sound, the resulting clearance was combined with other published human parameters in estimating
overall population clearance and volume of distribution (Table 3-4).
Clearance rates estimated from half-lives
The clearance rate for a single-compartment PK model is related to the half-life and volume
of distribution by the following equation:
CL = ln(2)-Vd/To.5
The approach for Bayesian analysis of PK data described in Appendix E was used to re-
analyze the monkey PK data from Sundstrom etal. (20121. resulting in mean volumes of
distribution of 278 mL/kg for males and 228 mL/kg for females, for which the average is 253
mL/kg. Using either the sex-specific Yd for corresponding segregated human studies, or the average
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Vd for results from mixed populations, values for total human clearance were estimated from the
half-life values:
• Li etal. (20181: 0.071 mL/kg-day in males and 0.092 mL/kg-day in females (same
participants as Li etal. (2022b)).
• Li etal. f2022bl: 0.098 mL/kg-day in male participants aged 15-50 years, 0.064 mL/kg-day
in females aged 15-50 years and 0.075 mL/kg-day in males and females aged > 50 years
(participants below age 15 not included due to impact of growth)
• Nilsson etal. T20221: 0.079 mL/kg-day in adults (age 22-82, 97%-98% males).
• Olsen etal. (2007): the clearance for each subject was calculated as described above for the
24 men and 2 women in the study.
o The geometric mean (arithmetic mean) of the resulting values is 0.072 (0.077) mL/kg-
day in males.
o Clearance in the two women ranked second and third lowest in the entire set
• Worlev etal. T20171: 0.031 mL/kg-day in men and women
These total clearance values also incorporate routes of clearance in addition to renal and menstrual
clearance, which could consist of fecal clearance, shedding of skin, and clearance due to childbirth
and lactation, to the extent that these occurred in the study populations.
Urinary clearance estimates
Four studies directly evaluated urinary clearance of PFHxS in humans from matched serum
and urine concentrations fYao etal.. 2023: Fu etal.. 2016: Gao etal.. 2015: Zhang etal.. 2013bl. Of
these studies, the ones with occupational cohorts Gao etal. T20151 and Fu etal. T20161 had much
greater exposure than the general population fYao etal.. 2023: Zhang etal.. 2013bl. Yao et al.
f20231 estimated clearance in infants, while all other studies were in adults. Their results are as
follows:
Fu etal. (2016) measured serum and urine PFHxS concentrations in matched samples from
occupationally exposed workers, and while they converted the results to half-lives for reporting,
the paper states that Vd = 230 mL/kg was used for the estimate. Given a reported geometric mean
(GM) half-life of 19.9 years in men, the corresponding clearance is 0.022 mL/kg-day. The GM
urinary clearance for women in the study (reported in the text) was 0.024 mL/kg-day. That the
overall population GM was reported to be 0.023 mL/kg-day increases confidence in the CL in men
back-calculated here (0.022 mL/kg-day).
Gao etal. (2015) did not distinguish between sexes but did distinguish between isomers of
PFHxS and found much greater clearance for the branched isomer, GM = 0.18 mL/kg-day, compared
with the linear (n-) isomer, GM = 0.04 mL/kg-day, with an overall clearance GM of 0.05 mL/kg-day
for total PFHxS, in a mixed population of men and women. The values for n- and total are between
those estimated from the half-lives of Li etal. f 20181 and Olsen etal. f20071 fO. 06-0.07 mL/kg-day)
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and the urinary clearance values estimated by Fu etal. (20161 and Zhang etal. (2013b) (0.02-0.03
mL/kg-day).
Zhang etal. f2013bl obtained GM values of 0.018 for men and older women and 0.028 for
younger women, which is in the range of total clearance estimated from Worlev etal. f20171. That
the GM values of Zhang etal. f2013bl are within an order of magnitude of the overall population
GM provides confidence that the true value is within an order of magnitude of those reported.
These route-specific clearance estimates do not include fecal elimination. After IV dosing
Kim etal. (2018b) measured fecal/urinary excretion rates of 8.2% and 7.9% in male and female
rats, respectively. Therefore, total excretion for Fu etal. (20161. Gao etal. (20151. and Zhang et al.
f2013bl was estimated as 1.08 times) the estimated urinary excretion rates (i.e., 100% of urinary
excretion plus 8% of urinary excretion for fecal clearance) for the purpose of determining an
overall total clearance in humans. The value estimated from a rat study was deemed appropriate as
there is no human or primate data on the relative amount of fecal and urinary excretion. There is
uncertainty in assuming that relative amount of fecal and urinary excretion in human is similar to
rats, that could be reduced by additional relevant human or primate data.
Yao etal. (20231 estimated urinary clearance of PFHxS and other PFAS in infants, based on
the ratio of the estimated urinary excretion rate to estimated cord serum concentration. Cord blood
was collected at delivery and the concentration multiplied by two to account for the serum-to-
whole-blood ratio. Urine was collected in disposable diapers collected over the first postnatal week
and later extracted for measurements. The methods do not specify how a daily average urine
concentration was then determined from the set of samples for each infant, but it is presumed that
the extracted urine from all diapers collected during the week was mixed prior to analysis, resulting
in a "mixing cup" average concentration for the week. The resulting concentration was then
multiplied by a reported average urine elimination rate in infants of 48 mL/kg-day, rather than
using the actual urine volume collected. Since the serum concentrations and resulting urinary
elimination of breast-fed infants are expected to increase significantly after child-birth based on
reported breast milk: maternal serum distribution and breast milk ingestion rates, while the cord
blood concentration might only match the infant blood concentration at the moment of birth, the
resulting estimate of infant clearance is likely to be an over-prediction of the true clearance rate.
From a population of 20 infants the median (15th, 75th percentile) urinary clearance was 0.270
(0.108, 0.781) mL/kg-day, with a mean value 0.956 mL/kg-day, i.e., an order of magnitude higher
than the rate estimated in adults. The sample distribution is clearly skewed, with a maximum
estimated value of 11.7 mL/kg-day perhaps due to the urine sample timing issue discussed here.
While glomerular filtration is still developing in neonates, the expression of renal 0AT1 and 0AT3 is
also below adult levels (Bueters etal.. 20201. and urinary excretion of PFNA will depend on both of
these opposing factors in a manner that cannot be quantitatively predicted. Given these
uncertainties, the results of this study will not be used quantitatively, though they indicate that
neonates will have lower serum levels of PFNA per unit exposure than adults.
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Sex differences in human PFHxS PK
Zhang etal. f2013bl shows a small quantitative difference in urinary clearance between
men and older women and younger women (i.e., 0.01 mL/kg-day). It is possible that this difference
derives from differences in renal expression of renal transporters between men and women
fMurray. 20171. but it could also be due to random inter-subject variability, given the overall range
of clearance observed across studies, and based on the overall range of clearance in each group, the
difference is not statistically significant. Hence, there does not appear to be a systematic difference
between men and women in the urinary clearance of PFHxS, except to the extent that menstrual
blood loss accounts for the difference reported by Li etal. f20181 and in participants between 15
and 50 years of age reported by Li etal. f2022bl. However, a menstrual loss term of 0.033 mL/kg-
day was used for EPA's analysis for women of reproductive age, based on the analysis of Verner and
Longnecker f20151 of corresponding blood and fluid loss reported by Hallberg et al. f!9661.
Applying the Vd values estimated from male and female monkeys f Sundstrom et al.. 20121 to men
and women respectively also led to some difference in the corresponding half-life estimates.
Zhang etal. (2013b) calculated a rate for menstrual clearance based on a study of PFOA and
PFOS that estimated menstrual blood loss using measurements of the blood quantity excreted
fHarada etal.. 20051. This estimate of menstrual blood loss was not specific to PFOA or PFOS and is
also applicable to PFHxS. However, Harada et al. f20051 cite Hallberg et al. f!9661 as the source for
a menstrual blood loss of 70 mL per cycle, but according to Hallberg, "The mean value of the
menstrual blood loss was 43.4 ± 2.3 mL in the entire series" [of experimental groups] and "the
upper normal limit of the menstrual blood loss is situated between 60-80 mL." Thus, 70 mL/cycle
appears to be closer to an upper bound for healthy women. More recently Verner and Longnecker
f20151 reviewed Hallberg etal. f!9661. evaluated both blood loss and total fluid loss from
menstruation and concluded that the fluid lost in addition to blood was likely to be serum, with the
corresponding serum binding proteins and associated PFAS. Including this serum loss and
assuming 12.5 menstrual cycles per year, Verner and Longnecker (20151 estimated an average
yearly total serum loss of 868 mL (69.4 mL/cycle or 72.3 mL/month). Assuming an average human
female body weight of 72 kg (mean value for women 21-30 years of age from Table 8-5 of (U.S. EPA.
2011a)), the corresponding average rate of clearance is 868 mL/(365 day)/(72 kg) = 0.033 mL/kg-
day.
Lorber etal. f20151 examined the effects of ongoing blood loss through menstruation or
through frequent blood withdrawal as a medical treatment. Male patients with frequent blood
withdrawal had serum concentrations 40%-50% less than males from the general population for
the chemicals observed in the study (PFOA, PFNA, PFDA, PFHxS, and PFOS). Female patients also
had a lower serum concentration than females from the general public. The trend in relation to the
number of recent blood draws or in the recency of the last blood draw was not examined for PFHxS.
It was examined for PFOA and PFOS, and significant associations were observed in PFOS only. This
study's analysis of the impact of menstrual blood loss was purely a modeling exercise, which was
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performed for PFOA and PFOS. The authors estimated a monthly blood loss of 35 mL (which is close
to the median loss of 43.4 mL reported by Hallberg et al. (196611. 50% of which was serum,
resulting in a clearance of 17.5 mL/month, or 0.0081 mL/kg-day in a 72 kg woman. This value is
also chemical-independent and could be applied to PFHxS instead of the menstrual clearance
estimated by Verner and Longnecker f20151.
Tain and Ducatman f20221 compared serum levels of PFHxS and other PFAS in US females
and males as a function of age. While serum PFHxS concentrations were similar at age 12-13 and
after age 55, they declined in females compared to males between these ages until the
concentrations in females were approximately one half of those in males between ages 30 and 45.
Qualitatively similar results, though with a smaller magnitude, were seen for PFOA, PFOS and PFNA
flain and Ducatman. 20221. Similarly, Li etal. f2022bl estimated a shorter half-life (corresponding
to more rapid clearance) for females than males 15-50 years of age, but not for 1-14 years of age or
over 50 years of age, although the difference between males and females aged 5-50 is only about
15%. These results are strongly suggestive that menstrual clearance is a significant factor in the
clearance of these PFAS. Further, the results of Tain and Ducatman (20221 that for the US population
(rather than a highly exposed Swedish cohort) menstrual clearance results in an approximate
doubling of total clearance, supporting use of the menstrual clearance rate of 0.033 mL/kg-day
estimated from the results of Verner and Longnecker f20151 above.
As mentioned in the distribution section (see Section 3.1.2), PFHxS has been observed in
breast milk, so lactation can act as an excretion route for a nursing mother. One study that
examined the association between maternal serum concentrations and the length of breastfeeding
and found a weak, nonsignificant inverse association. There were stronger inverse associations for
the other PFAS studied, PFOA, PFOS and PFNA, suggesting that there may be less transfer of PFHxS
to breast milk than other PFAS, or that the variation between people in serum level is large
compared with the impact of breastfeeding.
Dosimetry of linear versus branched isomers
Gao etal. (20151 is the only PK study to provide separate estimates of elimination for linear
versus branched isomers in humans. With the clearance of the branched isomer being so much
higher than the linear, the body burden is expected to be much higher for the linear than the
branched isomer, given equal exposures. Using the clearance for the sum of PFHxS accounts for the
relative prevalence of the different isomers in the serum of the participants. Therefore, the result
for mixed or total PFHxS from Gao etal. f20151 will be used in combination with the results of the
other PK studies. The result is interpreted as reasonably health-protective across all forms.
Summary of human PFHxS excretion
A summary of the clearance values reported or estimated from each of the adult human
elimination studies is provided in Table 3-4.
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Table 3-4. Summary of clearance values estimated for humans
Study
(basis)
Clearance
(mL/kg-d)
N
Notes
Chiu et al. (2022) (serum levels vs. drinking
water exposure
0.068
41
Geometric mean; 37 individuals and 4 population
mean results
Fu et al. (2016) (urinarv clearance with fecal
estimatea)
0.025
207
Geometric mean; 136 men, 71 women
Gao et al. (2015) (urinarv clearance with fecal
estimate3)
0.054
36
Geometric mean for total linear and branched
PFHxS; result based on 57 paired samples from 22
men, 14 women
Li et al. (2018) (empirical half-life)
0.071
20
Men aged 15-50; CL calculated from mean half-life
using Vd = 278 mL/kg
Li et al. (2018) (empirical half-life)
0.059
30
Women aged 15-50; CL calculated from mean half-
life using Vd = 228 mL/kg and subtracting 0.033
mL/kg-d for menstrual clearance (Verner and
Longnecker. 2015)
Olsen et al. (2007) (empirical half-life)
0.072
26
Geometric mean of individual clearance values,
calculated from reported half-lives as described
above; 24 men, 2 women (all >59 yrs)
Li et al. (2022b) (empirical half-life)
0.098
22
Males, ages 15-50; CL calculated from mean half-
life using Vd = 278 mL/kg
Li et al. (2022b) (empirical half-life)
0.064
30
Females, ages 15-50; CL calculated from mean
half-life using Vd = 228 mL/kg and subtracting
0.033 mL/kg-d for menstrual clearance (Verner
and Longnecker. 2015)
Li et al. (2022b) (empirical half-life)
0.075
33
Age > 50; CL calculated from mean half-life using
Vd = 253 mL/kg
Nilsson et al. (2022) (empirical half-life)
0.079
99
Age 22-82, 97-98% males; CL calculated from
mean half-life using Vd = 278 mL/kg
Worlev et al. (2017) (half-life fitted for PK
modelb)
0.031
45
Clearance calculated using Vd = 230 mL/kg (value
used in the PK model); 22 men, 23 women
Zhang et al. (2013b) (urinarv clearance with
fecal estimate3)
0.030
19
Geometric mean; women <50 yrs
Zhang et al. (2013b) (urinarv clearance with
fecal estimate3)
0.019
64
Geometric mean; all men and women >50 yrs
Weighted geometric mean
0.041cd
447
Exp Z[log(CL;)-Ni] / Z[Ni]
aReported urinary clearance was multiplied by 1.08 based on observed fecal/urinary elimination in rats after IV
dosing (Kim et al., 2018b).
bHalf-life determined from fitting PK model to geometric mean of serum concentrations measured in 2010 and
2016, accounting for estimated ongoing exposure.
Calculated for all studies except Worlev et al. (2017) due to methodological issues identified for that study and U
et al. (2018) since data for that population are included in the data of Li et al. (2022b) (see "Half-life estimates").
dVariance around this value can be described by a weighted geometric standard deviation of 1.6, which is a
multiplicative factor, or a weighted geometric coefficient of variance of 22%.
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In Table 3-4, the subset of clearance values estimated from empirical half-lives (Li etal..
2022b: Li etal.. 2018: Olsen etal.. 20071 are fairly similar to each other after adjustment for
(subtraction of] menstrual blood loss, and similar to the results of Chiu etal. f20221. but are higher
than most of the urinary clearance values and the results ofWorlev etal. f20171. which were based
on exposure estimated from drinking water concentrations measured at one time point and may
not reflect higher exposure concentrations in preceding years. While Kim etal. f2018bl observed
fecal excretion of PFHxS in rats to be only 8% of urinary excretion after IV exposure, it is possible
that fecal excretion and other routes such as shedding of dead skin contribute enough to the overall
clearance to account for the two- to three-fold difference between those estimated from empirical
half-lives fLi etal.. 2022b: Li etal.. 2018: Olsen etal.. 20071 and the estimates of urinary clearance.
In this case, the weighted geometric mean clearance shown in Table 3-4 will underpredict overall
clearance to that extent However, it also possible that the empirical half-lives reflect urinary
clearance under conditions of saturated renal resorption, which is not representative of the general
population at lower exposure levels, but Chiu et al. (20221 attempted to exclude very highly
exposed individuals (i.e., with occupational exposure) and also obtained a relatively high clearance.
Data on how clearance may vary as a function of age (i.e., in rat pups or children compared
with adults) and during pregnancy are mostly lacking. Li etal. f2022bl did estimate the half-life in
individuals 1-14 years of age and found it to be about one half of that in older individuals (3 years
vs. 6 years), but this is an apparent half-life that likely includes the impact of growth. As discussed
above, Yao etal. (20231 estimated urinary clearance of PFHxS in infants to be almost an order of
magnitude higher than the estimated clearance rates in adults, 0.27 vs. 0.036 mL/kg-day, but the
approach used may have over-estimated the rate. Renal excretion varies in proportion to body
surface area with age over most of the lifetime but is still developing in newborns along with
expression of organic anion transporters (OATs) fBueters etal.. 20201 that are associated with
renal resorption of PFAS, and the volume of distribution may also vary with age. In the preceding
section, "Distribution in fetal tissues and children," the possible effect of changes in extracellular
water and blood volume as a fraction of BW in children was discussed. Finally, the absence of a
reliable pharmacokinetic model which can account for these factors and the likely differences in
accumulation of PFHxS in humans exposed chronically versus in experimental animals during
relatively short-term health effects studies creates uncertainty in simpler pharmacokinetic
extrapolation based on clearance. Nevertheless, the results of Tain and Ducatman f20221 indicate
strongly that menstrual fluid loss creates an approximately two-fold difference in clearance
between women of reproductive age and men, which is quite consistent with the weighted
geometric mean clearance of 0.041 mL/kg-day (in the absence of menstrual fluid clearance) and the
average menstrual fluid clearance of 0.033 mL/kg-day from Verner and Longnecker (20151 and the
limited data available for neonates and children indicate that their clearance is higher than adults.
While the range of values in Table 3-4 represent a range of uncertainty of five-fold, given
the number of estimates it seems unlikely that the true clearance in humans would be lower than
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the minimum value of 0.019 mL/kg-day from Zhang etal. (2013b). The weighted geometric mean
clearance of 0.041 mL/kg-day is 2.2 times higher than this minimum and based on the overall
evidence was considered sound for use in estimating human equivalent doses (HEDs) for points of
departure (PODs) estimated from animal toxicity studies or blood concentrations estimated from
epidemiological evaluations, with an additional 0.033 mL/kg-day for menstrual fluid loss in women
of reproductive age.
The clearance values shown in Table 3-4 were compared with species-specific glomerular
filtration rate (GFR), with and without adjustment for serum protein binding, to evaluate the
possible role of those mechanisms. Considering the time period ofDavies and Morris (19931. this
comparison used their value for average human BW, 70 kg, which results in an estimated GFR/BW
of 2.57 L/kg-day in humans, 83,000 times greater than the empirically estimated geometric mean
clearance for humans. Kim etal. f2018bl reported an average PFHxS free fractions (/free) of 0.00025
in humans, which led to GFRx/free = 0.64 mL/kg-day, which is still almost 16 times greater than the
geometric mean empirical clearance. Thus, it appears likely that there is significant renal resorption
of PFHxS in humans.
Comparing the human CL values to those predicted from allometric scaling of mouse and
rodent CL values shows that allometric scaling appears to overpredict human clearance rats. BW3/4
allometric scaling suggested that CL in an 80 kg human should be 4.2 times lower than in a 0.25 kg
rat and 7.2 times lower than in a 30 g mouse. Applying a factor of 4.2 to the population mean CL
values for male and female rats in Table 3-3, resulted in predictions of human male CL of 1.7
mL/kg-day and female CL of 20 mL/kg-day, one to three orders of magnitude higher than the
values estimated from human data in Table 3-4. Likewise using the CL in mice and the allometric
factor of 7.2 resulted in an estimated human male CL of 0.54 mL/kg-day and female CL of 0.44
mL/kg-day, roughly an order of magnitude higher than observed. Performing this analysis for a 6
kg male monkey or a 4 kg female monkey produces a similar overprediction, with extrapolated
clearance values of 0.73 and 1.0 mL/kg-day after applying scaling factors of 1.9 and 2.1. In
summary, this analysis indicated that use of BW3/4 scaling would have led to an overprediction of
HEDs (effectively an underprediction of risk) by one to three orders of magnitude, depending on
the animal species and sex in which a POD was identified. Hence, the use of BW3/4 scaling was
avoided for PFHxS, but comparisons of BW3/4 scaling to the selected approach (see Section 3.1.6)
was provided for context.
Excretion Summary
The estimated average clearance values for adult humans are listed in Table 3-5. Since
menstrual blood loss was subtracted as appropriate from the data in Table 3-4 when estimating the
general, nonspecific clearance in humans, a corresponding rate should be added for women of
childbearing age. In particular, the higher estimate of Verne r and Longnecker (2015) (0.033 mL/kg-
day) appears to be consistent with the empirical comparison of PFHxS serum concentrations in
men and women flain and Ducatman. 20221. This additional term is considered appropriate for
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deriving HEDs for reproductive effects in women. Since newly available data show that maternal
serum levels remain constant or decline during pregnancy and the early postpartum period, the
additional clearance term for menstrual loss is also considered appropriate for estimating HEDs for
effects occuring in-utero or otherwise correlated with maternal serum concentrations measured
during pregnancy and post-partum.
However, since the current analysis should protect younger children, men and older
women, it was considered appropriate not to include menstrual clearance when evaluating
dosimetry in humans for health effects that can occur at any point in life, even though they may
have been observed in laboratory animals of reproductive age. This choice follows the typical
approach when assessing susceptible sub-populations.
Table 3-5. Summary clearance values for humans
Population
Clearance (mL/kg-d)
References
Human geometric mean
(general population)
0.041a,b
(Chiu et al., 2022; Li et al., 2022b; Nilsson et al., 2022;
Fu et al., 2016; Gao et al., 2015; Zhang et al., 2013b;
Olsen et al., 2007)
With menstrual fluid loss
(women of reproductive age)
0.074
Includes average menstrual fluid loss of 0.033 mL/kg-
dav from Verner and Longnecker (2015)
aHuman clearance estimates also depend in part on volumes of distribution estimated for monkeys by Sundstrom
et al. (2012); does not include estimated clearance due to menstrual fluid loss.
bMeasurements of urinary clearance only were corrected for estimated fecal/urinary clearance ratio of 1.08 based
on observations in rats by Kim et al. (2018b).
3.1.5. Evaluation of PBPK and PK Modeling
The PFAS protocol (Supplemental Information document, Appendix A) recommends the use
of scientifically sound and validated physiologically based pharmacokinetic (PBPK) models as the
preferred approach for dosimetry extrapolation from animals to humans, while allowing for the use
of data-informed extrapolations (such as the ratio of serum clearance values) for PFAS that lack a
scientifically sound and sufficiently validated PBPK model. If chemical-specific information is not
available or too uncertain, the protocol then recommends that doses be scaled allometrically using
body weight (BW)3/4 methods. Selection from among this hierarchy of decisions considered both
the inherent and chemical-specific uncertainty (e.g., data availability) for each approach option.
This hierarchy of recommended approaches for cross-species dosimetry extrapolation is consistent
with EPA's recommendations on using allometric scaling for the derivation of oral reference doses
fU.S. EPA. 2011bl This hierarchy preferentially prioritizes adjustments that result in reduced
uncertainty in the dosimetric extrapolation.
A PBPK model was identified for PFHxS in rats and humans (Kim etal.. 2018b). The
computational code for this model was obtained from the model authors and evaluated for
consistency with the written description in the published paper, the PK data for PFHxS, known
physiology, and the accepted practices of PBPK modeling. Unfortunately, several flaws were found
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in the model. One flaw, an error in the balance of blood flow through the liver, had only a moderate
impact on model predictions. A much larger issue identified is that the model had only been
calibrated to fit the oral PK data for rats and the set of model parameters selected by the model
authors to match those data included an oral bioavailability (BA) lower than is otherwise supported
by the empirical PK data. For example, the fraction absorbed by the male rat was effectively set to
39% in the model when the empirical PK analysis showed 88%-92% bioavailability. Further, when
the model was used to simulate the intravenous PK data, data to which a PK model should be
calibrated, the parameters were found to be completely inconsistent with these data. Figure 3-3
compares results obtained with a replication of the PBPK model, which exactly matches the
published PBPK model results for oral dosimetry, to the data and empirical PK fit for a 10 mg/kg IV
dose to male rats.
The overprediction (approximately three to four times higher than the data for male rats) of
the IV data by the Kim etal. f2018bl model indicated that distribution into the body is significantly
underpredicted by the model, which was offset in the simulations of oral dosimetry data by use of
an unrealistically low oral bioavailability. Initial efforts to refit the model to the data did not
produce acceptable fits to both the IV and oral dose PK data and involved changing model
assumptions in a way that would require separate experimental validation before use. In particular,
to match the observed rate of decline in the blood as well as the observed accumulation in urine
and feces required an assumption of another route of excretion, for which there are no data. It was
therefore determined that the published model structure and underlying assumptions did not allow
a sufficiently sound calibration of the model to the PK data, given the currently available
understanding of PFAS pharmacokinetics.
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Plasma
CO
X
X
ll
Q_
O
O
Time (day)
Figure 3-3. Comparison of PFHxS PBPK model predictions to IV dosimetry data
(circles) of Kim et al. f2018bl for a 10 mg/kg dose. The red, solid line was the
result of an empirical PK analysis shown by Kim et al. f2018bl (digitized). EPA's
replication of the PBPK model (solid black line) exactly reproduced the PBPK model
results of Kim et al. (2018b) for oral dosimetry (results not shown - simulation
shown here was for IV dose) hence was considered an accurate reproduction of the
model. The blue dashed line shows model results after correction of the blood flow
rate exiting the liver. The discrepancy between the PBPK model prediction for a 10
mg/kg dose and the data demonstrated that the published model structure and
parameters are very inconsistent with the empirical data, hence that there was a
significant flaw in the model.
Fabrega etal. (2015) developed a PBPK model describing the dosimetry of multiple PFAS in
humans, including PFHxS. A concern with this model is that the tissue:blood partition coefficients
were estimated by comparing tissue concentrations measured in cadavers with blood
concentrations from different (living) subjects, albeit from the same geographic region. Also, the
brief description provided for the estimation of the parameters for saturable renal resorption was
considered not sufficient to allow for independent reproduction of that process and it was unclear
how the two constants can be independently identified from such data. Finally, model results for
PFHxS shown by the authors underpredict an epidemiological dataset (Rvlander etal.. 2009) by
about an order of magnitude. Therefore, the model was not considered further for use in this
review.
Verneretal. f20161 developed a coupled classical PK model, wherein single-compartment
models represented the mother and fetus or child, which incorporated growth of the fetus and
child, maternal body weight changes, and a time-varying rate of milk intake to account for the
decline in g/kg-day ingested with the child's age. With parameter samples selected from
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
distributions by Monte Carlo sampling, maternal exposure levels for individuals from two studies
were selected to match the observed maternal serum concentration at delivery (i.e., given the
sample set of parameter values) and the PFAS concentrations in the mother and child simulated for
the first three years of the child's life. Measured plasma levels in children at 6 months of age were
fairly well predicted, though the model tended to under-predict the plasma levels at age three, with
many observations more than two-fold higher than predicted. A version of the PK model was
implemented and its ability to predict rat PK data was evaluated as described in Appendix E.2.
Unfortunately, based on the under-prediction of PFHxS concentrations in three-year-old children
shown by Verner etal. (20161 and the poor performance of the model in predicting rat PK data
using parameter values estimated for that species (Appendix E.2), model predictions were not
considered sufficiently reliable for use in this assessment
It is also noted that EPA's high throughput toxicokinetics (httk) computational model
package (Pearce etal.. 20171 predicts dosimetry for PFHxS. However, this model currently does not
account for the activity of transporters, in particular those involved with renal resorption, so
clearance (in the absence of metabolism) is estimated as the free fraction in blood times the
glomerular filtration rate. The httk package estimates the half-life of PFHxS in humans to be 38 days
or 0.11 years, corresponding to CL = 3.9 mL/kg-day (using Vd for female monkeys), over two orders
of magnitude higher than that estimated from the empirical in vivo human data. Hence, the httk
model was also not considered further for use in this review.
Bil etal. (20221 used a classical two-compartment PK model structure to estimate internal
dose relative potency factors for liver toxicity observed in male rats for nine PFAS, including PFHxS.
Since the PK model parameter estimation was performed separately for each PFAS, only the results
for PFHxS need to be discussed here, but it is noted that the objective of the paper was to develop a
method for prediction of toxicity from exposure to PFAS mixtures. For, PFHxS, Bil etal. f20221 used
the PK data of Huang etal. f2019al. one of the studies included in EPA's analysis, and obtained
results for a single compartment (monophasic clearance) with a volume of distribution of 137
mL/kg and a half-life of 16.5 days using the data for the 16 mg/kg dose. These values are similar to
those reported by Huang etal. (2019a) for that dose (144 mL/kg and 16.9 days, respectively), but
somewhat lower than the results of EPA's analysis of multiple data sets including Huang et al.
(2019a) (mean values of 217 mL/kg and 21 days). Because EPA's clearance value is obtained from
analyzing data from all three dose levels used by Huang etal. f2019al and data from two other
studies fKim etal.. 2018b: Kim etal.. 2016bl. it is considered superior for use in pharmacokinetic
extrapolation from animal to human points of departure.
Sweeney (2022) developed a PBPK model for PFHxS in humans. Model simulations were
conducted for individuals from 0-70 years of age and results analyzed (compared with data) for
individuals from 12-70 years of age. The text indicates that an adjustment factor for ingestion in
children 0-10 years of age was employed, but gestational and lactational exposure are not
mentioned and pregnancy was not simulated. The model structure and assumptions and
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adjustments for physiological changes with age appear to be sound and the author has compared
model results to a comprehensive set of human PK data.
Unfortunately, the model code for Sweeney f20221 contains a mass-balance error in which
the unbound fraction in plasma (CAFREE) is calculated as the total amount in plasma (APLAS)
divided by the plasma volume, which effectively means that distribution to tissues and urinary
elimination are not restricted by the plasma protein binding. If instead one interprets APLAS as
only being the amount free in plasma, then the corresponding total amount in plasma
(APLAS/FREE) is not included in the mass balance check for the model code. EPA's review of the
model code suggested that the variable APLAS is consistent with the total amount in the plasma, not
the free amount. For example, the differential equation for APLAS sums all the PFHxS that
distributes out of the liver after absorption from the stomach (based on the amount free in the
liver), rather than being only assigned the fraction that is free in blood. However, if the total amount
in blood is AP LAS/FREE, making this correction would add an amount approximately 40 times
APLAS to the overall mass balance equation, which would then likely demonstrate an overall mass
balance error.
It is possible that the mass balance error in Sweeney (20221 is related to the inability of Kim
etal. f2018bl to correctly replicate the IV dosimetry in rats, noted above, in that both point to a
central assumption that appears to be incorrect. Kim etal. f2018bl correctly calculates the mass
balance in the plasma based on the assumption that only the free fraction in the plasma can
distribute to tissues, but then fails to predict that tissue distribution after IV dosing. The central
model code used by Sweeney (20221 was originally developed by Loccisano etal. (20111. who may
have inadvertently introduced the mass balance error in an attempt to correct for an inability of the
model to predict tissue distribution and urinary elimination. The resolution of this issue may
require relaxing the assumption that the free fraction and bound fraction in the serum are strictly at
equilibrium at all times, as opposed to being treated as a dynamic equilibrium with distinct rates of
association and dissociation. In the latter case, the rate of distribution to tissues and urinary
elimination would be limited by the rate of dissociation, which may be more rapid than the
equilibrium fraction free multiplied by the blood flow rate to the tissues (or glomeruli). A
mathematical model that incorporates the kinetics of plasma binding and release to describe
uptake of drugs by the brain has been previously described by Robinson and Rapoport (19861. but
adaptation of this model to the tissue distribution of PFHxS would require measurement of the
separate rates of association and dissociation, data which have not been reported. Hence,
appropriate revision of the PBPK models was not possible for use in this assessment.
Irrespective of the potential impact of the mass balance error, from Table 1 of Sweeney
(20221. the model predicts urine concentrations around 2.5 times higher than Fu etal. (20161 and
3.75 times higher than measured by Zhang etal. (2013b). indicating an overall predicted clearance
of 0.06-0.07 mL/kg-day, consistent with the results of Li etal. f20181. whose data were used for
calibration. However, the result means that application of the Sweeney f20221 would be less health-
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protective than use of the weighted geometric mean clearance, 0.041 mL/kg-day (Table 3-5) and
would not address some of the other uncertainties noted here. For both this reason and the mass
balance issue, the model was not further considered for use in the current analysis.
Most recently, Chiu etal. f20221 applied a one-compartment PK model in a Bayesian
analysis of human serum concentrations matched with drinking water (DW) concentrations of
several PFAS, including PFHxS, from multiple community studies. Since the one-compartment
model structure is essentially identical to that already evaluated by the EPA and only addresses
exposure of adults, for whom body weight is presumed fixed, it was not considered further for use
as a PK model, but the overall approach and parameter estimation method were considered
sufficiently sound that the resulting parameters were combined with other published human
parameters in estimating overall population clearance and volume of distribution (Table 3-4).
Yao etal. T20231 used a one-compartment PK model to estimate the time-course of multiple
PFAS, including PFHxS, in human children from birth to one year of age. However, the model used a
constant level of intake by the child, based on the breast milk concentration measured just after
birth and the volume of breast milk ingested per day for infants < 1 month of age, and did not
account for the dilution due to growth of the child over that time. Breast milk intake is expected to
peak between 3 and 6 months of age and the intake per kg BW of the infant to decline from the first
month of age through the first year (https://www.epa.gov/expobox/exposure-factors-handbook-
chapter-15), while concentrations of PFHxS in maternal serum declined on average in the first
month after birth (Oh etal.. 2022). Hence, the simulations of Yao etal. (2023) likely over-predict
the actual PFHxS time-course in children after the first month of life.
3.1.6. Empirical Pharmacokinetic Analysis
To estimate sex-specific PK parameters with measures of uncertainty for male and female
rats based on all of the published studies, including Kim etal. f2018bl. a hierarchical Bayesian
analysis was conducted using either a one- or a two-compartment empirical PK model. Details of
the analysis are provided in Appendix E. Results for a one-compartment model are described here
for mice and rats and results for a two-compartment model for monkeys.
Estimation of Pharmacokinetic Parameters
In classical PK theory, it is expected that once a chemical is absorbed or distributed to the
blood, its excretion (clearance) is then independent of the route of administration. With IV
administration, 100% of the dose is delivered directly to the blood, while only a fraction of an oral
dose may be absorbed. Therefore, the area-under-the-curve (AUC) for blood or serum
concentration after an oral dose should be less than or at most equal to the AUC after the same dose
administered IV, and the fraction absorbed, or bioavailability, is estimated as AUCorai/AUCiv.
However, when both the IV and oral PFHxS exposure data for rats (at identical doses) were
analyzed from Kim etal. f2016bl. Kim etal. f2018bl and Huang etal. f2019al by EPA, the estimated
serum concentration AUC was consistently lower for the IV-dose data than the oral dose data for a
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
number of the datasets, with the result that the corresponding CL values were quite different, in
some cases with non-overlapping data-set-level credible intervals (see Figure 3-4). This difference
was especially evident in the female, where CL after IV dosing was higher in all cases examined.
This outcome does not match general pharmacokinetic theory, which depends on a number of
assumptions, including that distribution into body tissues is independent of dose route.
Female rat
Male rat
Kim, 2016. 4 mg/kg (tv)
Kim, 2016, 4 mg/kg (gavage)
Kim. 2016. 4 mg/kg 0v)
Kim. 2018.1 mg/kg (lv) 201<>' 4 m3/*g Ravage)
Kim, 2018,1 mg/kg (gavage) ^ ^ 2018( 10 mg/kg (,vj
Kim, 2018, 4 mg/kg —-»¦—
Kim, 2018, 4 mg/kg (gavage) ——
Huang, 2019, 4 mg/kg (lv)
Huang, 2019, 4 mg/kg (gavage) -o- Huan5' 2019' * m«/k9
Kim, 2018. 10 mg/kg (gavage)
Huang, 2019, 4 mg/kg (iv)
50 100 150 200 250 2 4 6 8
Clearance (ml/kg/d) Clearance (ml/kg/d)
Figure 3-4. Comparison of Female (left) and Male (right) CL values for IV and
gavage exposure of equivalent dose levels from Kim et al. (2016b). Kim etal.
f2018bl and Huang et al. f2019al. The central point, a triangle for IV and a circle
for gavage, denotes the mean CL, the thicker portion of the lines are the quartiles,
and the thinner extent of the lines denote the 95th confidence interval. Note that
these clearance values are slightly different than presented in Table 3-6, because
those values were based on an analysis of only the gavage datasets, whereas the
values in the figure above are based on analysis of the gavage and IV data together
in a hierarchical Bayesian framework.
Since data of Kim etal. f2018bl show nearly identical urinary and fecal excretion after IV
versus oral dosing it is possible that distribution into body tissues was much greater after IV
dosing, perhaps because more of the IV-infused PFHxS could distribute to various tissues before it
became bound to serum proteins, while the slower absorption from oral dosing led to lower tissue
distribution. Tissue dosimetry data after both IV and oral doses, which could be used to evaluate
this hypothesis, were not available and resolution of the apparent discrepancy was considered
beyond the scope of this analysis. Because the objective was to extrapolate dosimetry from oral
exposures in animal toxicity studies to humans, given the unusual quantitative results from
classical PK analysis for IV versus oral dosimetry, only the oral dosimetry data were included in the
final analysis for rats and mice. Only IV dosimetry data were available for monkeys, so those data
were analyzed recognizing that it may not exactly represent oral kinetics. Because the empirical
data indicted the blood AUC after IV exposure was less than after oral exposure to the same dose for
most of the experimen ts, it was assumed that oral bioavailability was 100% and that was assumed
in subsequent analyses.
A single study reported PK data that could be used for parameter estimation for mice and
monkeys fSundstrom etal.. 20121. While Sundstrom et al. f20121 did collect PK data after both IV
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
and oral administration in mice, they did not estimate a bioavailability for male mice and the
estimate of 50% availability in female mice was based on only two animals for oral dosimetry.
Therefore, the more complete datasets for 1 and 20 mg/kg oral doses provided separately were
analyzed similarly to the analysis for rats described above, assuming 100% bioavailability. The
resulting PK model fits (see Appendix E, Figure E-5) were quite good, showing that the oral PK data
for mice were consistent with this assumption; the model did not over-predict the serum
concentration time-course.
Only IV data were available for monkeys (Sundstrom etal.. 20121. so those data were
analyzed for that species, recognizing the resulting uncertainty in bioavailability and that there may
be differences in distribution and clearance between the two routes of administration. While the
mouse and rat PK data were adequately fit with a one-compartment model (see Appendix E, Figures
E-l to E-5), the monkey PK clearly showed biphasic clearance from the serum, requiring a two-
compartment model, that is, one including both central and a deep tissue compartment (see
Appendix E, Figure E-6). No critical dose-response endpoints were identified in monkey, so no
determination needed to be made considering the best approach for pharmacokinetic extrapolation
from monkeys.
Values for the volume of distribution (Vd, mL/kg) and clearance (CL, mL/kg-day) were also
estimated from the Bayesian analysis for each study and dose, as well as overall population mean
values (Appendix E). An average half-life (T1/2) was calculated from these results using the formula,
T1/2 = ln(2) x Vd/CL. Interestingly, while the analysis showed a clear, large sex difference in
clearance and the corresponding half-life between male and female rats, almost no difference
appeared between male and female mice. The monkey results should be interpreted with some
caution, as they were based on only three animals per sex, but they suggest an intermediate case
between rats and mice, with clearance in male monkeys being 73% of female monkeys. The much
slower clearance in male rats compared with female rats is assumed to result from higher
expression of renal transporters that resorb PFHxS. The data for mice and monkeys suggest that
expression of the transporters is much less sex-dependent in those species.
Table 3-6. Pharmacokinetic parameters for rats, mice, monkeys, and humans
Study
Dose
(mg/kg)
n
Clearance (mL/kg-
d)a
Volume of
distribution
(mL/kg)a
Tl/2b
(d)
Male rats
Kim et al. (2016b)
4
5
5.71 (5.46-5.69)
264.4 (255.6-272.6)
32.1
Kim et al. (2018b)
4
5
6.58 (3.34-9.68)
293.4 (262.9-323.9)
30.9
Huang et al. (2019a)
4
3C
5.37 (4.61-6.14)
137.8 (116.2-159.6)
17.8
16
3C
5.91 (5.09-6.75)
144.2 (121.1-166.5)
16.9
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Study
Dose
(mg/kg)
n
Clearance (mL/kg-
d)a
Volume of
distribution
(mL/kg)a
Tl/2b
(d)
32
3C
9.74 (8.47-11.03)
210.7 (176.9-243.2)
15.0
Population mean
-
-
7.15 (3.73-10.26)
216.5 (149.2-281.4)
21.0f
Female rats
Kim et al. (2016b)
4
5
117.8(110.7-125.3)
286.9 (264.5-309.6)
1.7
Kim et al. (2018b)
1
5
83.02 (77.22-89.38)
196.0 (117.2-213.6)
1.6
4
5
106.3 (98.58-113.8)
236.3 (215.5-257.6)
1.5
Huang et al. (2019a)
4
3C
50.14 (45.03-55.01)
162.8 (142.9-183.2)
2.3
16
3C
61.36 (55.58-67.17)
187.9 (166.5-208.5)
2.1
32
3C
94.54 (85.43-103.3)
261.9 (231.9-290.2)
1.9
Population mean
-
-
84.10(64.72-103.8)
224.2 (182.7-266.4)
1.8?
Male mice
Sundstrom et al. (2012) (all data)
1 & 20
4C
3.86 (3.27-4.41)
154.6 (122.6-185.5)
27.8
Female mice
Sundstrom et al. (2012) (all data)
1 & 20
4C
3.18 (2.83-3.52)
123.0 (104.5-140.6)
26.8d
Male monkeys
Sundstrom et al. (2012)
10
3
1.39 (0.94-1.83)
282.4 (251.9-314.9)e
141
Female monkeys
Sundstrom et al. (2012)
10
3
2.12 (1.81-2.44)
228.5 (204.4-252.5)e
75
Human
All males and females below age 12.4 y and
above age 50 y
-
577
0.041
228 (women)'
278 (men)'
3,855
(10.6 y)
4,700
(12.6 y)
Women 12.4-50 years of age
0.074
228 (women)'
2,136
(5.9)
aValues are mean (study-level 90% credible interval) or population mean (90% credible interval).
bTi/2 = ([mean] volume of distribution [mL/kg]) x In (2) / ([mean] clearance [mL/kg-d]).
cNumber of animals per time point.
dRats displayed a large difference in half-life between sexes that mice did not. This sex-dependence was seen in
rats for many PFAS and has been linked to sex-hormone dependent changes in renal transporters (Kudo et al.,
2002). It is not fully understood why this phenomenon is different between species.
eSum of central and peripheral compartment volumes from a 2-compartment PK model.
fVd in women assumed equal to the value for female monkeys, Vd in men assumed equal to male monkeys.
1 While the results for rats showed a fair degree of variability in CL between studies (see
2 Table 3-6), the range in mean values is 1.8-fold for males and 2.3-fold for females is modest and the
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overall population means were obtained via a Bayesian analysis that addressed the variability both
within and among the datasets (see details in Appendix E, Section 1). Hence, these values provided
an estimate of the relationship between dose and mean serum concentration levels in rats that
appeared to be accurate to within a factor of two, which was set as an acceptable degree of
discrepancy between PK model simulations and data in EPA's Umbrella Quality Assurance Project
Plan (QAPP) for Dosimetry and Mechanism-Based Models fU.S. EPA. 2018bl. and so were
considered sufficiently sound for use in cross-species extrapolation.
The assumption that the Vd derived from monkeys is a suitable surrogate for the human Vd
introduces some uncertainty to the calculated human half-life. However, Chiu etal. (20221 obtained
a mean (95% CI) Vd of 0.25 (0.15, 0.42) L/kg from their analysis of human data, which is essentially
the average of the values from male and female monkeys, 0.287 and 0.213 L/kg, respectively.
Hence, the extent of the uncertainty is judged to be minimal. Use of the value from Chiu etal. f20221
would only change some of the estimated clearance values in Table 3-5 by less than 20%, so would
have a minimal impact on the geometric mean clearance obtained.
Clearance Versus Glomerular Filtration Rate and Free Fraction in Serum
Some mechanistic insight could be gained by comparing the clearance values shown in
Table 3-6 with species-specific glomerular filtration rate (GFR), with and without adjustment for
serum protein binding. Davies and Morris f!9931 summarized GFR for multiple species. Using 0.25
kg as the species average BW for the rat, the GFR/BW for rats is 7.55 L/kg-day, which is
approximately 1,100 and 90 times higher than the population mean clearance estimated in male
and female rats, respectively.
Binding to serum proteins plays a likely role in these very large differences. As discussed
above in the context of distribution, PFHxS binds to albumin with high affinity and it is the major
carrier of PFHxS in blood fForsthuber etal.. 2020: Bischel etal.. 2010: Weiss etal.. 20091. This
binding may play a role in the limiting the rate of the renal excretion of PFHxS, in addition to the
role played by renal transporters. Kim etal. (2018b) measured reported PFHxS free fractions (/free)
of 0.00076 and 0.00069 in male and female rat plasma. Using these values, GFRx/free = 5.7 and 5.2
mL/kg-day in male and female rats. This alternative estimate of clearance for male rats is close to
the population mean in Table 3-6 (7.15 mL/kg-day), which could be interpreted as showing
minimal renal resorption in males. However, for female rats GFRx/free is more than order of
magnitude lower than the population mean clearance of 84.1 mL/kg-day. Section 3.1.5 provided
further discussion of the fact that the PBPK model of Kim etal. f2018bl. which assumed that tissue
distribution was similarly limited by the free fraction, underpredicted the observed short-term
distribution of PFHxS in rats. Hence, while it is expected that serum protein binding limits renal
excretion (and tissue distribution) to some extent, the reduction appears to be less than predicted
by assuming that clearance is strictly limited to the equilibrium free fraction. As noted above,
Robinson and Rapoport T19861 used a mathematical model that incorporates the kinetics of plasma
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binding and release in order to describe uptake of drugs by the brain, supporting this conclusion.
Alternately, there could be an error in the measured free fraction.
More qualitatively, the fact that the measured free fraction is similar in male versus female
rats indicates that it cannot explain the large sex difference in empirical clearance, and hence that
sex differences in renal resorption are likely to be a factor.
3.1.7. Model Evaluation Conclusion and Extrapolation Approach
The clearance in rats is sufficiently slow that PFHxS is expected to accumulate throughout
the course of the 28-day NTP bioassay (NTP. 20191 in male rats and for about 10 days in female
rats, as illustrated in Appendix E, Section 2. For this reason, the preferred approach would be to
perform an interspecies dose extrapolation that accounts for the time-dependence of the internal
dose (i.e., bioaccumulation). Further, given the slow clearance of PFHxS in male rats, the growth of
rats during these toxicity studies could be a significant factor as increases in BW are expected dilute
the body burden from earlier exposures. Therefore, a computational model for a single-
compartment PK model was developed to describe the accumulation and elimination of PFHxS
during these experiments, with time-dependence in BW based on the empirical data for BW. Details
of the model and its evaluation against serum concentration data from NTP f20191 were provided
in Appendix E, Section 2. While the period of accumulation was much longer for male rats, female
rats were modeled in the same way as males for consistency. However, application of the single-
compartment PK model revealed that this simple approach was not suitable for PFHxS due to an
observed nonlinear relationship between dose and plasma concentration, which the single-
compartment model was not able to replicate.
As noted in the Summary of Human PFHxS Excretion section, uncertainties also exist in the
potential extrapolation of such a model to developmental or other early-lifestage effects. Even
though the results for the one-compartment PK model indicated that the model may be adequate
for low-dose extrapolation of dosimetry in adult animals, the failure of this model (see Appendix E,
Section 2) and the issues identified with the published PBPK models (see Section 3.1.5)
demonstrated an incomplete understanding of PFHxS pharmacokinetics. Additional research, which
may be extensive, is needed to resolve the existing inconsistencies between the various models and
the data. Thus, a reliable PK model for PFHxS is not considered to be in the realm of available
science. Further, use of the empirical one-compartment PK model for some endpoints and a of data-
derived extrapolation factor (DDEF) for others would create inconsistency in the extrapolation
approach. This inconsistency would hinder the comparison between different candidate points of
departure and the failure of the model in some instances lowers the confidence in model
predictions, even for dose ranges where the model appears to be performing well. Therefore, a PK
model was not used for dosimetric extrapolation.
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Approach for Animal-Human Extrapolation of PFHxS Dosimetry
After evaluation of three published PBPK models and a one-compartment PK model for
PFHxS, it was determined that none of these options could reliably predict PFHxS dosimetry. An
alternative to use of PK (or PBPK) models for dosimetric extrapolation is use of data-derived
extrapolation factors (DDEFs). As stated in EPA's guidance for DDEFs fU.S. EPA. 20141. use of these
factors "maximize the use of available data and improve the scientific support for a risk
assessment" As discussed above in the Evaluation of Pharmacokinetic Modeling and Summary of
Human PFHxS Excretion sections, the estimated population average values of total CL for male and
female rats and for humans were considered sufficiently sound for use in such extrapolation, while
use of BW3/4 scaling (the least preferred option; see U.S. EPA f2011bll could lead to over-prediction
of HEDs by as much as three orders of magnitude. Therefore, DDEFs calculated from the clearance
values listed in Table 3-5 and Table 3-6, were used as the next preferred option. Specifically, the
ratio of human clearance to clearance in the animal species and sex in which a given POD was
identified was used to estimate the HED for that POD. For example, to extrapolate from a POD from
the NTP bioassay for an endpoint in male rats to humans,
HED = POD X CLH/CLrat,m,
where CLhIs the clearance in humans for the appropriate population, CLrat,m is the clearance in male
rats and CLH/CLrat,m is the DDEF. This calculation assumed the same fraction absorbed or
bioavailability in human and rats, which is taken to be 100% as described in Section 3.1. In
particular, the computational PK analysis summarized in Section 3.1.6 found that the published PK
data showed serum AUC after oral exposures were higher than serum AUCs after matching IV
exposures for several key studies rather than results consistent with less than 100% oral
bioavailability.
For gestational effects, the clearance in the female animal (dam) was assumed to determine
dosimetry to the fetus. However, for effects observed in rat pups at PND 22, the clearance for the
same sex adult rat was used.
While menstruation does not occur during pregnancy and may not resume until after
weaning of the child, as described in the subsections Trend in Pregnancy and Breast Milk in 3.1.2
Distribution, studies of longitudinal changes in during and after pregnancy show maternal serum
levels remaining fairly constant or constant or declining through this lifestage. This likely occurs
because the long half-life of PFHxS results in slow accumulation as well as elimination, while the
increase in total body mass during pregnancy (including the fetus and placenta) is expected to
result in a dilution of the body burden as the PFHxS distributes into those growing tissues.
Therefore, the serum levels in the pregnant and postpartum woman are expected to be consistent
with her serum levels at the start of pregnancy, which are determined by her total clearance prior
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
to pregnancy, including menstrual fluid loss. Thus, HEDs for developmental endpoints that occur in-
utero such as reduced birthweight or are based on measures of maternal serum concentration will
be calculated using the higher clearance estimated for women of childbearing age (12.4-50 years)
in Table 3-6.
However, this additional clearance clearly does not occur in young children, and as
described in Summary of Human PFHxS Elimination in Section 3.1.4, there may be differences in PK
among human lifestages that cannot be quantified because of a lack of empirical PK data during
childhood. While effects in adults do not involve extrapolation across lifestages, the degree of
accumulation of PFHxS in rats during a 28-day bioassay could be less than the accumulation during
a comparable portion (4%) of the human life span. Therefore, HEDs for effects observed in
experimental animals more than a few days after birth, where dosimetry in the pups or human
child may be a significant factor, and immune effects correlated with serum concentrations
measured 5 years after birth, for which the exposure and clearance of the offspring are significant
factors, have been calculated using the population-average CLh from Table 3-6.
The key assumption made in calculating a DDEF for a given endpoint evaluated was that for
effects observed in adult male and female rats, the CL and Fabs for the corresponding rat sex from
Table 3-6 were used to calculate the DDEF. Table 3-7 shows the resulting DDEFs.
Table 3-7. Data-derived extrapolation factor (DDEF) calculations
Sex and species of observation (lifestage)
CLA (mL/kg-d)
DDEF3
Male rats (adult and male pups > PND 7)
7.15
5.73 x 10"3
Female rats (adult and female pups > PND 7),
non-reproductive/developmental effects
84.1
4.88 x 10"4
Female rats (adult), reproductive effects and effects in
pups < PND 7
84.1
8.80 x 10"4
aDDEF = (CLh/CLa) with CLh = 0.041 mL/kg-d for effects in all males and females outside of reproductive age, except
for those occurring in-utero or correlated with maternal serum levels during or after pregnancy. For reproductive
effects in females and developmental effects associated with maternal serum levels, CLh = 0.074 mL/kg-d was
used. These DDEF values assume equal oral bioavailability in rats and humans. Rat CL values from Table 3-6. No
data exist showing that CL in juveniles is different from adults.
When an internal dose POD, specifically a serum concentration, is obtained from human
epidemiological studies, the HED will likewise be calculated as:
HED = PODint x CLh,
using the geometric mean estimate for human clearance from Table 3-5, CLh = 0.041 mL/kg/d = 4.1
x 10"5 L/kg-day for effects associated with serum levels in children (e.g., immune effects associated
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
with serum levels measured at age 5) and 0.074 mL/kg-day = 7.4 x 10"5 L/kg-day for
developmental effects associated with maternal serum levels.
Uncertainty in HED Calculations
The ranges in population mean parameter Table 3-6 can be used as a measure of
uncertainty in the CL for male and female rats. The upper end of the 90% credible intervals is only
43% higher than the mean for male rats and 23% higher than the mean for female rats, indicating
that concentrations during the bioassays were unlikely to be much lower than effectively estimated
using the DDEF, hence that the corresponding HEDs were also judged unlikely to be more than 1.5-
fold lower. Applying the DDEF, however, effectively assumed the rats were at steady state, when
this was not likely the case, especially for male rats used in the NTP bioassay fNTP. 2018al. which
could lead to an over-prediction of the HEDpod- The non-menstrual clearance value used for humans
was approximately two-fold higher the lowest from among those reported by or estimated from
multiple studies of PFHxS dosimetry in humans. Only a modest correction for fecal absorption
(using the ratio of fecal/urinary elimination observed in rats after IV dosing) was applied. Hence,
the average human clearance is unlikely to be more than two-fold lower than the value used for
HED calculation. The relative values of non-menstrual and menstrual clearance correlate strongly
with differences between PFHxS serum levels found in the U.S. population (NHANES data) flain and
Ducatman. 20221. reducing the qualitative uncertainty. While uncertainties in the extrapolation to
developmental exposure and dosimetry in children remain, there are currently no data to indicate
that these are greater than is accounted for by application of the standard human interindividual
uncertainty factor (UFh), of which a factor of 3 is typically attributed to pharmacokinetic differences
across individuals.
3.2. NONCANCER HEALTH EFFECTS
For each potential health effect discussed below, the synthesis describes the evidence base
of available studies. Arrays or tables summarizing endpoint results across studies within each
evidence stream are also provided. The effect levels presented in these arrays and tables are based
on statistical significance5 or biological significance, or both. Examples relevant to interpretations of
biological significance include consideration of the directionality of effect (e.g., statistically
significantly decreased cholesterol/triglycerides is of unclear toxicological relevance), tissue-
specific magnitude of effect (e.g., statistically nonsignificant increase of >10% in liver weight may
be considered biologically significant), and dose-dependence (e.g., a significant finding at a single,
lower dose level but not at multiple, higher dose levels may be interpreted as potentially spurious).
For this section, evidence to inform organ-/system-specific effects of PFHxS in animals following
throughout the assessment, the phrase "statistical significance" indicates a p-value < 0.05, unless otherwise
noted.
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developmental exposure are discussed in the individual organ-/system-specific sections (e.g., liver
effects after developmental exposure are discussed in the hepatic effects section and so on,
although they are generally cross-referenced to the Developmental Effects section; Section 3.2.3).
Evidence on other developmental effects (e.g., fetal growth) is only discussed in the Developmental
Effects section. Lastly, overt toxicity was not observed at any of the highest doses tested in any of
the available studies (in contrast to data available for some of the other PFAS being assessed by the
IRIS Program), and thus the potential for overt toxicity to complicate interpretation of the health
effect-specific PFHxS evidence is not a factor discussed in any of the following sections.
3.2.1. Thyroid Effects
Under normal physiologic conditions, neurons in the hypothalamus release thyroid
releasing hormone (TRH) to stimulate epithelial cells of the anterior pituitary gland to release
thyroid stimulating hormone (TSH) flrizarrv. 20141. TSH plays a number of important metabolic
functions including stimulation of the thyroid gland to release thyroxine (T4), which is converted to
triiodothyronine (T3). When increased T3 and T4 serum levels exceed a blood concentration
threshold, secretion of TRH from the hypothalamus is inhibited via a negative feedback loop
flrizarrv. 2014: Pilo etal.. 19901. In adults, T3 and T4 play important metabolic functions; for
example, decreases in T3 and T4 serum levels, a condition known as hypothyroidism, result in
increased weight gain, fatigue, and dry skin, as well as effects on the memory and a difficulty to
concentrate. Conversely, increased levels of T3 and T4, otherwise known as hyperthyroidism, result
in increased rate of metabolism, weight loss and increased heart rate (Mullur etal.. 20141. During
fetal development and throughout early childhood, thyroid hormones play an important role in
somatic growth and development. Thyroid hormones have been shown to play a critical role in
neurogenesis, neuronal migration, and synaptogenesis, as well as shifting neuronal cells from a
proliferative state to a differentiation state and myelination fGilbert et al.. 20161. In humans,
alterations of prenatal maternal T4 have been linked to declines in cognitive function in children
(Korevaar etal.. 2016: Haddowetal.. 19991. Importantly, changes in prenatal and maternal T4 have
been shown to be biologically important in the absence of changes in TSH reviewed in (Vansell.
2022: Moog etal.. 2017: Stagnaro-Green and Rovet. 2016: Dong etal.. 2015: Navarro etal.. 2014:
Rovet. 2014: Patel etal.. 2011: Berbel etal.. 2010: Morreale de Escobar et al.. 2008: Cuevas etal..
2005: Rovet. 2005: Zoeller and Rovet. 2004: Hood and Klaassen. 2000: Hood etal.. 1999a: Hood et
al.. 1999bl.
Human Studies
Thirty-nine studies (reported in 44 publications) have investigated the relationship
between PFHxS exposure and thyroid hormones and/or thyroid disease in humans. All of the
available human studies examined the association between PFHxS exposure measured in blood and
thyroid hormones (see Figure 3-5).
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There were multiple outcome-specific considerations that were influential on the study
evaluations. First, for outcome ascertainment, collection of blood during a fasting state and at the
same time of day for all participants (or adjustment for time of collection) is preferred for
measurement of thyroid hormones to avoid misclassification due to diurnal variation fvan Kerkhof
et al.. 20151. Studies that did not consider these factors (e.g., by study design or adjustment) were
not excluded but were considered deficient for the outcome ascertainment domain. This is expected
to result in nondifferential outcome misclassification, and thus, bias toward the null on average. For
participant selection, it was considered important to account for current thyroid disease and/or use
of thyroid medications; studies that did not consider these factors by exclusion or another method
were considered deficient for the participant selection domain. Concurrent measurement of
exposure with the outcome was considered acceptable for this outcome since thyroid hormones
can be up- or downregulated relatively quickly in relation to the long half-life of PFHxS (half-life of
T3 and T4 are in the order of hours/days, respectively (Leboffetal.. 1982) versus years for PFHxS
(Li etal.. 2018): see Section 3.1.3); thus, exposure measurement ratings were not downgraded for
timing of measurement All of the available studies analyzed PFHxS in serum or plasma using
appropriate methods as described in the systematic review protocol (see Appendix A). Thyroid
hormones were analyzed using standard methods (e.g., immunoassays, HPLC-MS/MS) in all studies.
The medium confidence studies generally were not downgraded for participant selection, but most
did not account for time of day of blood collection and fasting, which is considered likely to result in
nondifferential outcome misclassification (expected to be toward the null on average) for thyroid
hormone measures. The low confidence studies were generally downgraded for both the
participant selection issues and outcome ascertainment issues described above, though Liu et al.
(2018) did not account for thyroid medication use but was unique in the set of available studies in
that data were collected prospectively, and the analysis was based on change in outcome, so there
was less concern for the lack of adjustment impacting the results.
In summary, 26 studies were medium confidence fCakmak etal.. 2022: Gallo etal.. 2022: Li
etal.. 2021b: Sarzo etal.. 2021: Aimuzi etal.. 2020: Kim etal.. 2020a: Lebeaux etal.. 2020: Liang et
al.. 2020: Aimuzi etal.. 2019: Caron-Beaudoin etal.. 2019: Inoue etal.. 2019: Reardon etal.. 2019:
Blake etal.. 2018: Dufour etal.. 2018: Kang etal.. 2018: Liu etal.. 2018: Preston etal.. 2018: Berg et
al.. 2017: Crawford etal.. 2017: Shah-Kulkarni etal.. 2016: Yang etal.. 2016a: Wang etal.. 2014:
Webster etal.. 2014: Wang etal.. 2013: Wen etal.. 20131 and ten were low confidence fLiu etal..
2021b: Itoh etal.. 2019: Heffernan etal.. 2018: Khalil etal.. 2018: Zhang etal.. 2018b: Li etal..
2017c: Lewis et al.. 2015: Ti etal.. 2012: Chan etal.. 2011: Bloom etal.. 20101. Three studies were
uninformative in study evaluation (Seo etal.. 2018: Kim etal.. 2016a: Kim etal.. 2011a). Sensitivity
was a concern across studies due to narrow exposure contrasts in several studies (see sensitivity
domain in Figure 3-4), combined with the expected bias toward the null due to outcome
misclassification. Thus, null results are difficult to interpret. The medium confidence studies were
the focus of evidence synthesis; low confidence studies did not undergo data extraction but were
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still considered for consistency in the direction of association. The domain ratings, populations, and
thyroid measures for each study are presented in Figure 3-5.
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Aintuzi, 2019,5387078-
Aimuzi, 2020, 6512125-
Berg V, 2016, 3350759-
Blake, 2018, 5080657-
Bloom. 2010, 757875-
Cakmak, 2022. 10273369-1
Caron-Beaudoin, 2019, 5097914-
Chan. 2011, 1402500-
Crawford, 2017, 3859813-
Dufour, 2018, 4354164 J *
Gallo, 2022, 9962235-
Guo, 2021,7410165- I
Heffernan, 2018,5079713-
lnoue,2019, 5918599 -
Koh, 2019, 5315990-
Ji. 2012, 2919189-
Kang, 2018, 4937567-
Khalil, 2018, 4238547-
Kim, 2011, 1424975-
Kim, 2016, 3351917-1
Kim, 2020, 6833758-1
Lebeaux, 2020, 6356361 -
Lewis, 2015, 3749030-
Li, 2017, 3856460 -
Li, 2021, 7277672-
Liang, 2020,7161554 -
Liu. 2018, 4238396-
Uu. 2021 10176563-
Preston, 2018, 4241056-
Reardon, 201S, 5412435-
Safzo, 2021, 9959596-!
Seo, 2018, 4238334-
lah-Kulkarni. 2016, 3859821 -
Wang. 2013, 4241230- I
Wang, 2014, 2850394-
Webstar, 2014, 2850208-
Wen, 2013,2850943-1
Yang, 2016, 3858535-
Zhang, 2018,5079665-
~ Adequate (metric) or Medium confidence (overall)
- Deficient (metric) or Low confidence (overall)
B Critically deficient (metric) or Uninformative (overall)
~ Multiple judgments exist
Figure 3-5. Study evaluation results for epidemiology studies of PFHxS and thyroid effects. Full
details available by clicking H AWC link. Multiple publications of the same study: Preston et al.
(20181 also includes Preston et al. f20201.
G: good; A: adequate; D: deficient; CD: critically deficient; Un: uninformative.
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The results for the association between PFHxS exposure and thyroid effects in medium
confidence studies are presented in Tables 3-8 and 3-9. Twenty-eight studies examined
associations with thyroid hormones in adults, including 13 focused on pregnant women (see Table
3-8). For T4, out of 27 studies, the results are mixed. In the 15 medium confidence studies, a few
statistically significant associations were reported (positive associations in both sexes in Cakmak et
al. f20221. positive association in women but inverse in men in Wen etal. f20131. positive
association in men >50 years of age in Li etal. (2021b). positive association in pregnant women in
Aimuzi etal. (2020). and inverse association in pregnant women in Reardon et al. (2019). Other
non-significant results were also in both directions or showed no association. The low confidence
studies were also inconsistent in direction of association for T4. Many of the inverse associations
had small magnitudes of effect and some estimates, particularly for total T4, were imprecise, both
of which decrease certainty in the evidence. There is no clear pattern by exposure level or
population. Nineteen studies examined associations with T3. In the 12 medium confidence studies,
most reported no association with the exception of three studies (Aimuzi etal.. 2020: Crawford et
al.. 2017: Wen etal.. 2013) in women that reported higher levels of T3 with higher exposure to
PFHxS (statistically significant in latter two studies). Twenty-seven studies reported on TSH, and of
the 16 medium confidence studies, one reported statistically significant higher TSH with higher
exposure fReardon etal.. 20191 and one study reported a statistically significant inverse
association f Aimuzi etal.. 20201. both in pregnant women, but the remaining studies reported no
clear association.
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Table 3-8. Associations between PFHxS exposure and thyroid hormone levels
in medium confidence studies of adults.
Reference
Population
Median
exposure
(IQR) or as
specified
(ng/mL)
Effect
estimate
T4
T3
TSH
General population, adults
Cakmak et al.
CHMS cross-sectional
1.5 (GM)
Percent
Total T4
NR
-1.1 (-4.9, 2.9)
(2022)
study (2007-2011),
Canada, 6,045
participants (all ages)
change for
GM
equivalent
increase
0.9 (0.1,1.8)*
Crawford et
al. (2017)
Time to Conceive
cross-sectional study
(2008-2009), U.S., 99
women
1.6 (GM)
P (p-value)
for log-
unit
increase
Total T4
-0.15 (0.5)
Free T4
0.01 (0.8)
Total T3
2.8 (0.2)
-0.03 (0.7)
Wen et al.
(2013)
NHANES cross-
sectional study (2007-
2010), U.S., 1,181
adults (672 men, 509
women)
2.0 (GM)
P (95% CI)
for In-unit
increase
Total T4
Women
0.26 (0.11, 0.41)*
Men
-0.03 (-0.18, 0.11)
Free T4
Women
0.003 (-0.02, 0.03)
Men
-0.02 (-0.03, -0.003)*
Total T3
Women
4.07 (2.23, 5.92)*
Men
-0.08 (-1.70, 1.54)
Free T3
Women
0.003 (-0.02, 0.03)
Men
0.005 (-0.003, 0.01)
Women
-0.02 (-0.13, 0.09)
Men
0.02 (-0.06, 0.52)
Blake et al.
(2018)
Fernald Community
Cohort (1990-2008),
U.S., 210 adults (81
men, 129 women)
2.7 (1.7-4.1)
Percent
change for
IQR
increase
Total T4
1.74 (-1.73, 5.33)
NR
1.97 (-7.73, 12.7)
Liu et al.
(2018)
POUNDS Lost trial of
weight loss treatment
(2004-2007) 621
adults (237 men, 384
women)
3.1 (2.3-4.4)
Spearman
correlatio
n
coefficient
s for
change in
hormone
0-6 months
0.04
6-24 months
-0.02
0-6 months
0.01
6-24 months
-0.05
NR
Gallo et al.
(2022)
Veneto cross-sectional
study in high exposure
area (2017), Italy,
14,888 adults
6.5 (3-12)
Percent
change for
IQR
increase
NR
NR
Women
1.1 (-1.8, 4)
Men
-5.5 (-11, 0.3)
Li et al.
(2021b)
Ronneby cross-
sectional study in high
exposure area (2014-
2015), Sweden, 2,687
participants (all ages)
93 in women
age 20-50
yrs
Percent
change
Free T4
Women 20-50 yrs
0.43 (-0.08, 0.94)
Women >50 yrs
0.01 (-0.57, 0.6)
Men 20-50 yrs
0.51 (-0.14, 1.16)
Men >50 yrs
0.73 (0.02,1.45)*
Free T3
Women 20-50 yrs
0.08 (-0.41, 0.57)
Women >50 yrs
0.05 (-0.47, 0.57)
Men 20-50 yrs
0.29 (-0.29, 0.88)
Men >50 yrs
0.26 (-0.36, 0.89)
Women 20-50 yrs
-0.47 (-2.52, 1.62)
Women >50 yrs
0.63 (-1.88, 3.2)
Men 20-50 yrs
-0.37 (-2.7, 2.01)
Men >50 yrs
-0.14 (-2.79, 2.58)
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Reference
Population
Median
exposure
(IQR) or as
specified
(ng/mL)
Effect
estimate
T4
T3
TSH
Pregnant women
Yang et al.
(2016b)
Beijing Prenatal
Exposure cross-
sectional study (2013)
157 mother-infant
pairs
0.5
Spearman
correlatio
n
coefficient
s
Total T4: 0.08
Free T4: 0.04
Total T3: 0.08
Free T3:0.12
-0.15
Wang et al.
(2013)
Cross-sectional
analysis within
Norwegian Mother
and Child Cohort Study
(2003-2004), Norway,
903 pregnant women
0.6 (0.4-0.8)
P (95% CI)
for In-unit
increase
NR
NR
0.01 (-0.04, 0.07)
Aimuzi et al.
Cross-sectional
0.6 (0.4-0.7)
P (95% CI)
Free T4
Free T3
-0.12 (-0.22, -0.01)*
(2020)
analysis within
Shanghai Birth Cohort
(2013-2016), China,
1,885 pregnant
women
for In-unit
increase
0.12 (0.02, 0.22)*
0.2 (0.05, 0.34)*
Sarzo et al.
(2021)
Cross-sectional
analysis within INMA
(2003-2008), Spain,
919 pregnant women
0.6 (0.4-0.9)
Percent
change for
doubling
(95% CI)
Free T4
-1.6 (-7.56, 4.75)
Total T3
0.52 (-6.05, 7.54)
6.09 (-0.71, 13.4)
Wang et al.
(2014)
Taiwan Maternal and
Infant Cohort Study
(2000-2001), Taiwan,
285 pregnant women
and 116 neonates
0.8 (0.3-1.4)
P (95% CI)
for unit
increase
Total T4
-0.13 (-0.32, 0.06)
Free T4
-0.01 (-0.02, 0.003)
Total T3
-0.002 (-0.01,
0.001)
0.11 (-0.002, 0.21)
Webster et
al. (2014)
CHirP cohort (2007-
2008), Canada, 152
women
1.0 (0.7-1.7)
P (95% CI)
for IQR
increase
Free T4
-0.02 (-0.1, 0.07)
NR
0.01 (-0.05, 0.07)
Reardon et
al. (2019)
Alberta Pregnancy
Outcomes and
Nutrition cohort
(2009-2012), 494
women
1.0
P (95%
CI) for
unit
increase
Free T4
-0.01 (-0.01, -
0.001)*
Free T3
Not significant
0.14 (0.04, 0.25)*
Inoue et al.
(2019)
Cross-sectional
analysis within Danish
National Birth Cohort
(1996-2002),
Denmark, 1,366
pregnant women
1.1 (0.8-1.4)
Absolute
Percent
difference
(95% CI)
per IQR
increase
Free T4
-0.3 (-1.6,1)
NR
1.7 (-4.4, 8.1)
Lebeaux et
al. (2020)
Health Outcome and
Measures of the
Environment cohort
(2003-2006), 355
mother-infant pairs
1.6(1.5)
P (95% CI)
for
doubling
Total T4
-0.01 (-0.04, 0.02)
Free T4
0.02 (-0.01, 0.05)
Total T3
-0.01 (-0.04, 0.02)
Free T3
-0.02 (-0.04, 0)
-0.06 (-0.23, 0.11)
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Reference
Population
Median
exposure
(IQR) or as
specified
(ng/mL)
Effect
estimate
T4
T3
TSH
Preston et al.
Project Viva cohort
(1999-2002), U.S., 732
pregnant women and
480 neonates
2.4 (1.6-3.8)
(3 (95% CI)
for IQR
increase
Total T4
-0.05 (-0.14, 0.04)
Free T4
-0.60 (-1.39, 0.19)
NR
2.89 (-2.12, 8.17)
(2018)
*p <0.05.
GM: geometric mean.
One medium confidence study (Berg et al., 2017) is not included because quantitative results were only reported
for significant associations.
Six studies examined associations with thyroid hormones in children and/or adolescents, in
addition to studies of adults that included adolescents or all ages without stratifying results, which
were described above. All six studies (five medium confidence and one low confidence) reported
null associations between PFHxS exposure and thyroid hormones (Gallo etal.. 2022: Li etal.. 2021b:
Kim etal.. 2020a: Caron-Beaudoin et al.. 2019: Kangetal.. 2018: Khalil etal.. 20181
Eleven studies (9 medium confidence) examined associations with thyroid hormones in
infants. For T4,10 studies were available, including 9 of medium confidence. One study with the
highest exposure levels fPreston etal.. 20181 reported statistically significant lower levels of total
T4, driven by the association in boys, with an exposure-response gradient across quartiles. The
remaining studies reported no association. Nine studies examined associations with T3. One low
confidence study fShah-Kulkarni etal.. 20161 reported statistically significant higher levels of T3
with higher PFHxS exposure in girls and no association in boys, while Aimuzietal. (20191 reported
statistically significant inverse associations, strongest in boys. The remaining studies reported no
association. Ten studies examined the association between TSH and PFHxS exposure. There were
lower levels of TSH with higher PFHxS exposure in one low confidence study fShah-Kulkarni et al..
20161. and higher levels of TSH in one study fWang etal.. 20141 though neither was statistically
significant, and the confidence intervals were wide. The remaining studies reported no association.
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Table 3-9. Associations between PFHxS exposure and thyroid hormone levels
in medium confidence studies of infants.
Reference
Population
Median
exposure
(IQR) or
as
specified
(ng/mL)
Effect
estimate
T4
T3
TSH
Guo et al.
(2021)
Sheyang Mini Birth
Cohort Study (2009-
2010), China, 490
infants
0.1 (0.1-0.1)
(3 (95% CI)
for In-unit
increase
Total T4
0.04 (-0.006, 0.09)
Free T4
0.02 (-0.007, 0.05)
Total T3
0.04 (-0.003, 0.09)
Free T3
0.02 (-0.02, 0.05)
-0.10 (-0.23, 0.03)
Dufour et al.
(2018)
University Hospital of
Liege cohort (2013-
2016) 214 mother-
infant pairs
0.2
(3 (p-value)
for
detected vs
not
detected
NR
NR
(0.9)
Girls
0.09(0.5)
Boys
-0.06 (0.5)
Aimuzi et al.
(2019)
Cross-sectional analysis
from Shanghai Obesity
and Allergy Cohort
Study (2012-2013), 568
infants
0.2 (0.1-0.3)
(3 (95% CI)
for In-unit
increase
Free T4
0.06 (-0.06, 0.18)
Girls
0.03 (-0.14, 0.2)
Boys
0.1 (-0.07, 0.26)
Free T3
-0.04 (-0.09, -
0.001)*
Girls
-0.08 (-0.14, -0.02)*
Boys
-0.02 (-0.16, -0.03)*
-0.03 (-0.06, 0.004)
Girls
-0.02 (-0.07, 0.02)
Boys
-0.04 (-0.08, 0.01)
Yang et al.
(2016b)
Beijing Prenatal
Exposure cross-
sectional study (2013)
157 mother-infant pairs
0.5
Spearman
correlation
coefficients
Total T4: -0.005
Free T4: 0.01
Total T3: -0.07
Free T3: -0.03
0.08
Wang et al.
(2014)
Taiwan Maternal and
Infant Cohort Study
(2000-2001), Taiwan,
116 infants
0.8 (0.3-1.4)
(3 (95% CI)
for unit
increase
Total T4
0.002 (-0.50, 0.50)
Free T4
-0.03 (-0.10, 0.04)
Total T3
-0.001 (-0.007,
0.004)
0.49 (-1.45, 2.43)
Lebeaux et
al. (2020)
Health Outcome and
Measures of the
Environment cohort
(2003-2006), 355
mother-infant pairs
1.6(1.5)
(3 (95% CI)
for
doubling
Total T4
0.02 (-0.01, 0.06)
Free T4
-0.01 (-0.04, 0.02)
Total T3
-0.02 (-0.08, 0.03)
Free T3
-0.02 (-0.05, 0.02)
0.05 (-0.05, 0.16)
Preston et
al. (2018)
Project Viva cohort
(1999-2002), U.S., 480
infants
2.4 (1.6-3.8)
(3 (95% CI)
for IQR
increase
-0.15 (-0.38, 0.08)
Girls
0.07 (-0.23, 0.37)
Boys
-0.46 (-0.83, -0.1)*
NR
NR
Liang et al.
(2020)
Cross-sectional analysis
within Shanghai-
Minhang cohort (2012),
China, 300 infants
2.7 (2.0-3.4)
(3 (95% CI)
for In-unit
increase
Total T4
-0.59 (-7.94, 6.76)
Free T4
-0.32 (-0.87, 0.22)
Total T3
0 (-0.05, 0.04)
Free T3
0.02 (-0.08, 0.13)
0.43 (-1.02, 1.88)
*p <0.05.
One medium confidence study (Berg et al., 2017) is not included because quantitative results were only reported
for significant associations.
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In addition, five studies (four medium confidence) (Gallo etal.. 2022: Kim etal.. 2020a:
Dufour etal.. 2018: Wen etal.. 2013: Chan etal.. 20111 reported on the association between PFHxS
and dichotomous hyper- and hypothyroidism outcomes defined by the authors using set cutpoints.
In Wen etal. f20131. a medium confidence study, there were greater odds of subclinical
hypothyroidism in men (OR 1.57, 95% CI 0.76, 3.25) and women (OR 3.10, 95% CI 1.22, 7.86), and
subclinical hyperthyroidism in women (OR 2.27, 95% CI 1.07, 4.80) and lower odds of subclinical
hyperthyroidism in men (OR 0.56, 95% CI 0.24,1.2). Subclinical hypothyroidism was defined as
TSH >5.43 mlU/L, and subclinical hyperthyroidism was defined as TSH < 0.24 mlU/L (both limited
to those without diagnosed thyroid disease). Also in adults, Dufour et al. (2018) reported higher
odds (though not statistically significant) of hypothyroidism in pregnant women and Gallo et al.
f20221 did not report increases in thyroid disease or medication use. In the low confidence study
fChan etal.. 20111. hypothyroxinemia in pregnant women was defined as normal TSH
concentrations with no evidence of hyperthyroidism (0.15-<4 mU/L) and free T4 in the lowest
10th percentile (<8.8 pmol/L) of the study sample). They found higher odds of hypothyroxinemia
with higher PFHxS exposure (OR 1.12, 95% CI 0.89,1.41). In children and adolescents, Kim et al.
(2020a) reported lower odds of subclinical hypothyroidism with higher exposure and Gallo et al.
f20221 reported no association.
Thyroid effects summary
Overall, the evidence for the association between PFHxS exposure and thyroid effects is
inconsistent. Some studies do indicate an association between thyroid hormones or subclinical
thyroid disease and PFHxS exposure, but this direction is not consistent across studies and the
associations with PFHxS exposure in most studies were null. There is also not clear coherence
across outcomes, with indications of associations with both hyper- and hypothyroidism and unclear
coherence of the direction of association between TSH and the other hormones. However, almost all
of the available studies were deficient in outcome ascertainment due to lack of consideration of
timing of sample collection. As discussed above, this is likely to result in nondifferential outcome
misclassification, which also is expected to bias results toward the null on average, although the
studies without this issue also reported null findings. Given these concerns, the findings across this
set of studies are difficult to interpret.
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Animal Studies
The toxicity evidence base for PFHxS-induced endocrine outcomes consists of three
multigenerational publications (two studies) in SD or Wistar rats fRamhai etal.. 2020: Chang etal.. 2018:
Ramhai etal.. 20181. one developmental study in ICR mice f Chang etal.. 20181. and one short-term (28
day) study in SD rats fNTP. 2018al. All studies treated the animals orally to PFHxS via gavage. Endocrine-
related outcomes evaluated by these studies included: thyroid hormones, histopathology, and endocrine
organ weights including thyroid, parathyroid, and adrenal gland weight. Potential PFHxS effects on male
and female reproductive organs (e.g., testes and ovaries) and reproductive hormones (e.g., testosterone
and estradiol) that also encompass part of the endocrine system are discussed in Male Reproductive Effects
and Female reproductive Effects sections.
Evaluation of the available animal studies showed that these were generally well conducted for
most endocrine-related endpoints. The available studies examined PFHxS endocrine toxicity effects using
doses that ranged between 0 and 10 mg/kg-day in mice (Chang etal.. 20181: 0 and 25 mg/kg-day in rats
with the exception of NTP (2018a). for which a range of 0-50 mg/kg-day in female rats and 0-10 mg/kg-
day in male rats was used. These ranges account for the pharmacokinetic (PK) sex differences that have
been observed in rats, for which PFHxS appears to have a lower mean half-life in female rats versus their
male counterparts (1.72 and 26.9 days, respectively, after oral dosing fKim etal.. 2016bll. No overt toxicity
was observed at any of the highest doses tested in any of the available studies. Two high confidence studies,
Chang etal. (2018) and NTP (2018a). examined PFHxS effects on histopathology endpoints; three high
confidence studies (Chang etal.. 2018: NTP. 2018a: Butenhoff et al.. 2009) examined PFHxS effects on
thyroid gland weight Lastly, two high confidence studies (NTP. 2018a: Butenhoff etal.. 2009) also
measured adrenal gland weights. A summary of the study evaluations for each endpoint are presented in
Figures 3-6, 3-12, and 3-13; additional details can be obtained from HAWC.
Thyroid hormones
Four studies (three high and one low confidence; see Figure 3-6, below) examined the effects of
PFHxS on levels of thyroid hormones, T3, T4, and/or TSH. One high confidence study, NTP (2018a)
examined effects on serum concentrations of TSH, T3, and total and free T4 in adult animals. The other two
high confidence studies examined effects of PFHxS on serum T4 (Ramh0i etal.. 2018). T3 and TSH (Ramh0i
etal.. 20201 in exposed dams and their offspring (exposed via lactation) through PND 22. Lastly, the fourth
study was low confidence in which Chang etal. T20181 reported using a developmental study design that
followed established guidelines for such studies (OECD 422 Testing guidelines). However, the reported
study design ignored essential components of the OECD 422 developmental toxicity screening guidelines. A
necessary requirement of the OECD guidelines is that serum T4 be measured as part of developmental
toxicity studies. The study authors did not measure T4 serum levels, under the rationale that T4 is an
"inactive hormone" and elected to measure TSH serum levels instead. It has been established that serum
TSH measures are not good indicators of potential endocrine disruption fOECD. 2016: Stoker etal.. 2006:
Crofton. 20041.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Reporting quality -
Allocation -
¦*
1
NR
Observational bias/blinding -
NR
] NR
NR
Confounding/variable control
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Results presentation
Endpoint sensitivity and specificity
Overall confidence -
Legend
j Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Not reported
Figure 3-6. Study evaluation results for measures of thyroid hormone levels in PFHxS
animal toxicity studies. Full details available by clicking HAWC link.
NTP f 201 Sal measured free and total T4 serum levels in Sprague Dawley and Ramh0i etal. f20181
measured total T4 serum levels in Wistar rats (see Figures 3-7 and 3-8). NTP observed a statistically
significant, dose-dependent decrease (p < 0.01) of free and total T4 levels starting at the lowest
experimental dose (0,625 mg/kg-day) in male rats (up to 60% and 78% decrease in free and total T4
respectively); free T4 and total T4 were significantly decreased beginning at 12.5 mg/kg-day and 6.25
mg/kg-day respectively, in female rats (p < 0.01, up to 32% and 38 % decrease in free and total T4
respectively). However, serum total T4 levels are a more sensitive and reliable measure of T4 due to
sensitivity limitations in the available assays used to measure free T4. Ramhai etal. f20181 reported
similar findings in Wistar rat dams, with statistically significant, dose-dependent decreases in serum total
T4 at 5 mg/kg-day and above in dams atPND 22 after exposure from gestational day 7 (GND 7) through
postnatal day 16/17 fRamhdi etal.. 20181 (-26% decrease at 5 mg/kg-day dose and up to -71% decrease
at 25 mg/kg-day dose). Comparable observations were made in the pups born to the PFHxS-exposed dams
in Ramhai etal. f20181. with statistically significant decreases in total T4 levels in serum collected from
PND22 pups at >5 mg/kg-day (p < 0,001, up to a 71% decrease in total T4 at 25 mg/kg-day dose and 38%
decrease in total T4 at 5 mg/kg-day dose). No overt toxicity was observed at any of the highest doses tested
in any of the available studies. Effects occurred at lower concentrations of PFHxS in male rats than their
female counterparts indicating that males could be more susceptible to PFHxS effects than females (see
Figure 3-7). However, a more likely explanation is that these observations, at least in part, can be explained
by the differences in PFHxS pharmacokinetics that exist between male and female rats. Sex differences in
plasma half-life and tissue distribution have been observed for PFHxS, wherein PFHxS-exposed male rats
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have a longer plasma half-life (20.7-26.9 days) versus their female counterparts (0.9-1.7 days) (Kim etal..
2016b").
Two studies, NTP f2018al and Ramhai etal. f20201. measured T3 in serum. NTP f2018al observed
a statistically significant and dose-dependent decrease (p < 0.05) in serum T3 levels in male, but not female,
SD rats at >0.625 mg/kg-day (p < 0.01); Ramhai etal. f20201 in a similar study design as Ramhai etal.
f20181. reported a significant decrease in serum T3 in Wistar rat dams at the highest tested dose: 25
mg/kg-day at PND 22 after exposure from gestational day 7 (GND 7) through postnatal day 16/17
(p < 0.001,19% decrease). Comparable observations were also made in the pups born from the exposed
dams at PD16/17 in which a significant decrease in serum T3 was observed in pups of both sexes at the
highest dose: 25 mg/kg-day (p < 0.001,16% decrease).
Lastly, three studies, NTP f2018al. Chang etal. T20181 and Ramhai etal. f20201 investigated PFHxS
effects on TSH levels. None of these studies observed changes in TSH serum levels in male or female CD1
mice, Sprague Dawley rats or Wistar rats in response to PFHxS exposure.
Taken together, and as noted in the study results reported by NTP and the combined Ramh0j
studies (Ramh0i etal.. 2020: Ramh0i etal.. 2018). these results support that PFHxS exposure in rats has the
ability to adversely decrease the endocrine hormones, T4 and T3, in the absence of observed effects on
TSH.
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Endpoint Name
Study Name
Experiment Name
Species Strain
Generation
Sex
Lifestage Exposed
PFHxS Effects on Animal Thyroid Hormones
Thyroid Stimulating Hormone (TSH)
NTP, 2018. 4309363
28 Day Oral
Rat Sprague-Dawley
Female
7-8 week old
-• 1
Male
7-8 week old
1
Ramh0j. 2020, 6320959
Multigenerational Oral
Rat Wistar
P0
Female
Adult (gestation)
•
•
-•
F1
Male
Developmental
•
•
•
Thyroxine (T4), Free
NTP, 2018, 4309363
28 Day Oral
Rat Sprague-Dawley
Female
7-8 week old
Male
7-8 week old
•
~ 1
Thyroxine (T4), Total
Ramh0j, 2018, 4442260
Multi-Generational Oral (range-finding)
Rat Wistar
P0
Female
adult
•--T
F1
Male
fetal and juvenile
• ~
Thyroxine (T4), Free
Ramhcj, 2018, 4442260
Multi-Generational Oral (range-finding)
Rat Wistar
F1
Combined
fetal and juvenile
Thyroxine (T4), Total
Ramhej, 2018, 4442260
Multi-Generational Oral
Rat Wistar
P0
Female
Adult (gestation)
•
~
V
•
*
V
F1
Combined
Fetal and Juvenile
•
*
V
•
*
V
NTP, 2018, 4309363
28 Day Oral
Rat Sprague-Dawley
Female
7-8 week old
Male
7-8 week old
H Doses
•
~ ~ ~ i
Triiodothyronine (T3)
NTP, 2018, 4309363
28 Day Oral
Rat Sprague-Dawley
Female
7-8 week old
A Significant Increase
1
V Significant Decrease
#-
www ¦
Ramh0j, 2020, 6320959
Multigenerational Oral
Rat Wistar
P0
Female
Adult (gestation)
•
•
V
F1
Combined
Developmental
•
•
V
0.(
)1 0.1
1 10
1(
)0
Dose {mg/kg)
Figure 3-7. Summary of thyroid hormone measures in animal studies. Figure displays the three high confidence studies
included in the analysis; the sole low confidence study, Chang et al. f20181 was omitted from the analysis. Full details available by
clicking HAWC link. Details on study confidence may be found in Figure 3-6.
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Figure 3-8. Percent change in thyroid hormone levels following PFHxS
exposure in the available animal toxicology studies. For details see HAWC link.
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Histopathology
Three high confidence studies evaluated nonneoplastic histopathologic lesions in endocrine
tissues in response to PFHxS exposure fRamhai etal.. 2020: NTP. 2018a: Butenhoff etal.. 20091
(see Figure 3-9). NTP f2018al evaluated various organs in the endocrine system including the
adrenal cortex, adrenal medulla, parathyroid gland, pituitary gland, and the thyroid gland in adult
male and female rats exposed to PFHxS for 28 days. NTP (2018a) observed no histological lesions in
any of the endocrine tissues they evaluated and made no observations of hyperplasia or
hypertrophy in the thyroids at doses up to 10 mg/kg-day in male rats or 50 mg/kg-day in female
rats. However, a 44-day study by Butenhoff et al. f20091 observed increased incidences of
hypertrophy and hyperplasia (characterized as "minimal") of thyroid follicular epithelial cells in
adult male rats that were exposed to 3.0 mg/kg-day PFHxS (40% incidence) and an increase in
"moderate" hypertrophy and hyperplasia at 10 mg/kg-day PFHxS (70% incidence) for up to 44
days (minimal hypertrophy/hyperplasia (20% incidence) was observed in control animals). The
study authors attributed the pathological changes in the thyroid to changes in enzyme induction in
the liver (see Serum Biomarkers of Liver Function in Section 3.2.5) that have been shown by others
f Sanders etal.. 19881 to result in a compensatory increase in T4 clearance that may elicit increases
in TSH hormone levels or no compensatory TSH responses. The role of TSH in the progression of
thyroid hyperplasia and hypertrophy were highlighted in Noves etal. f20191. In the proposed
Adverse Outcome Pathway (AOP) by Noves etal. (20191. the authors illustrate that increased serum
TSH may lead to thyroid hyperplasia and hypertrophy. However, Butenhoff et al. (20091 did not
measure thyroid hormone levels as part of their experimental analysis, so this hypothesis was not
tested. Lastly, Ramh0i etal. (20201 reported that in Wistar rat dams exposed to PFHxS at doses
ranging from 0.05 to 25 m/kg-day from gestational day 7 (GND 7) through postnatal day 16/17, no
PFHxS effects on thyroid histopathology were observed. The authors reported that the thyroid
glands corresponding to the high dose (25 mg/kg-day) male pups showed "small histological
changes;" however, these changes were within the normal range and were no longer evident on PD
22. The authors did not observe hypertrophy or hyperplasia at any time point in either the exposed
dams or their offspring (Ramh0i etal.. 20201.
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Reporting quality^
Allocation -
NR
Observational bias/blinding -
NR
ff
NR
Confounding/variable control -j
44-
H-
~4
Selective reporting and attrition -
44
44
4-*
Chemical administration and characterization -
44
44-
4-4
Exposure timing, frequency and duration -
44
H
4-f
Results presentation -
44
~+
-•-4
Endpoint sensitivity and specificity -
44
4-4-
+4-
Overall confidence -
4+
4-f
+¦+
Legend
| Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Not reported
Figure 3-9. Study evaluation results for endocrine histopathology outcomes in
PFHxS animal toxicity studies. Full details available by clicking HAWC link.
Organ weights
Three studies evaluated the effect of PFHxS exposure on thyroid gland weights fRamhfli et
al.. 2020: Chang et al.. 2018: NTP. 2018al (see Figure 3-10; Figure 3-1:1). Chang etal. (20181 and
NTP f2018al observed no significant effects in adult CD1 male or female mice or in adult male or
female Sprague Dawley rats at the PFHxS doses administered in these studies (see Figure 3-11).
However, Ramhai etal. (20201 observed a statistically significant (p < 0.05) decrease in absolute
thyroid weights (relative weights were not reported) starting at 5 mg/kg bw-day that continued
into the highest dose tested (25 mg/kg bw-day) in PD 22 female Wistar pups exposed to PFHxS
starting at GD7 (5 mg/kg bw-day p < 0.05,17% decrease; 25 mg/kg bw-day p < 0.01; 23%
decrease) (see Figure 3-11). The differences in experimental designs across these studies make it
difficult to compare the results and thus the importance of the findings reported by Ramh0i et al.
(20201 is unclear.
T wo studies, Bute nhoff etal. f2009 and Chang etal. f2018) evaluated the effects of PFHxS
on adrenal gland weights in SD rats. Bute nhoff et al. f20091 reported no effect on absolute or
relative adrenal weight resulting from 0, 0.3,1.3, or 10 PFHxS mg/kg-day for 44 days. NTP observed
statistically significant increase in absolute adrenal weights in female rats (at >12.5 mg/kg-day;
15% increase) and an increase in relative adrenal gland weight at 50 mg/kg-day (9% increase
p < 0.01) in female rats. NTP also reported decreases in both absolute (at >5 mg/kg-day; -13%;
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1 p < 0.05} and relative adrenal weights (at >2.5 mg/kg-day; -17%; p < 0.05) in male rats. It is unclear
2 why there were opposing responses across sexes in the NTP study that were not observed in the
3 Butenhoffetal. (20091 (see Figure 3-11); however, these observations could be due to the
4 pharmacokinetic differences between male and female animals coupled with differences in study
5 design between the two studies.
6 Overall, the organ weight changes are mixed and cannot be readily interpreted.
Allocation -
Observational bias/blinding -
«~
-•*
NR
NR
NR
L .
NR
Confounding/variable control -
+4
~ 4 ++ ++
p
Selective reporting and attrition -
44
~~ *4- +4
Chemical administration and characterization -
44
~+ ++
Exposure timing, frequency and duration -
++
++ ++ +~
Results presentation -
++
++ ++ -HI-
Endpoint sensitivity and specificity -
++
Overall confidence -
44
um
4-4
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Not reported
Figure 3-10. Study evaluation results for endocrine organ weights in PFHxS
animal toxicity studies. Full details available by clicking HAWC link.
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Endpoint Name Study Name Effect Subtype Experiment Name Animal Description
Thyroid Weight, Absolute NTP, 2018,4309363 Absolute 28 Day Oral Rat, Sprague-Dawley (Q)
Rat, Sprague-Dawley (;")
Ramhoj, 2020, 6320959 Absolute Multigenerational Oral F1 Rat, Wistar (y)
F1 Rat. Wistar (5)
Thyroid Weight, Relative NTP, 2018,4309363 Relative 28 Day Oral Rat, Sprague-Dawley ( V)
Rat, Sprague-Dawley (_ )
Adrenal Gland Weight, Absolute NTP, 2018, 4309363 Absolute 28 Day Oral Rat, Sprague-Dawley (£)
Rat, Sprague-Dawley (
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Mechanistic Evidence and Supplemental Information
The available thyroid hormones data in rodents showed strong effects on T4 and T3 after
short-term exposure, although no effects were observed on TSH; however, a pattern of decreased
T4 without pronounced (or detectable) changes in TSH is consistent with hypothyroxinemia and
has been observed in some analyses of other PFAS, including several long-chain fKim etal.. 2018al
and short-chain (U.S. EPA. 2022. 2021a. b) PFAS. During pregnancy and early development,
perturbations in thyroid function can have impacts on normal growth and neurodevelopment in the
offspring (Stagnaro-Green and Rovet. 2016: Zoeller and Rovet. 20041. Low thyroid hormone status
is also likely associated with effects in numerous other organ systems, including the heart, bone,
lung, and intestine fBassettet al.. 2007: Mochizuki etal.. 2007: Wexler and Sharretts. 2007:
Bizzarro and Gross. 20041.
Mechanistic studies on the endocrine effects of PFHxS are scarce, with only one study
conducted in a mammalian test system. Long etal. (20131 explored the effects of PFHxS along with
other PFAS on thyroid hormone signaling and the aryl hydrocarbon receptor (AhR) using the T3-
dependent rat pituitary cell line, GH3. The authors found that PFHxS inhibited GH3 cell
proliferation in a dose-dependent manner. Additionally, the authors found that PFHxS—along with
three other PFAS (PFOS, PFNA, and PFUnA)—antagonized GH3 cell proliferation in response to
exogenous T3 treatment The authors speculated that PFHxS may compete with T3 for binding to
thyroid hormone receptor (TR) or other cofactors to inhibit cell proliferation; however, specific
experiments testing this hypothesis were not conducted.
Other studies in nonmammalian systems (e.g., avian neuronal cells and chicken embryos)
have shown that PFHxS alters mRNA levels of thyroid hormone-responsive genes, including
transthyretin (TTR) fCassone etal.. 2012: Vongphachan etal.. 20111. TTR is a transport protein that
is secreted into the blood by the liver and by the choroid plexus into the cerebrospinal fluid. TTR
binds to thyroid hormones such as T4 and T3 in the serum and in the cerebrospinal fluid. Due to its
low affinity for thyroid hormones TTR readily disassociates from these and is therefore responsible
for the immediate delivery of T3 and T4 to various extrahepatic tissues and potentially into the
brain (Palha. 20021. Decreases in TTR may lead to decreases in T4 transport (Refetoff. 20151.
Additionally, TTR plays a key role in thyroid hormone storage and transport during fetal
development PFHxS-induced decreases in TTR mRNA have been shown in nonmammalian
systems, and the above mechanism would in part assist in elucidating the mechanisms underlying
the in vivo observations pertaining to PFHxS-induced decreases T3 and T4. However, TTR binds
only a small portion of the circulating thyroid hormones (15%-20%) (Refetoff. 20151. and
confirmatory studies in model systems more relevant to humans would be needed to understand
the potential role of PFHxS-induced alterations to thyroid hormone-responsive genes in humans.
Data from the ToxCast Dashboards Endocrine Disruptor Screening Program (EDSP21)
(https://comptox.epa.gov/dashboard/chemical-lists/EDSPUOC) reveal that K+PFHxS was active in
a total of only 2 out of 57 endocrine-related assays (with both positive hits at PFHxS levels nearing
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the cytotoxicity limit). A summary of the assay results from the EDSP21 project may be found in
Appendix C, Section 3. Briefly, out of 27 estrogen receptor assays, K+PFHxS was active in one, the
ATG_ERE_CIS_up induction assay with an AC50 at 96.96 |a,M (see Figure 3-12). K+PFHxS was not
active in any of the 16 androgen receptor assays. K+PFHxS was active in one out of 13 assays
associated with perturbation of thyroid hormone signaling, synthesis, or metabolism, namely the
NIS-RAIU_inhibition assay with an AC50 of 18.68 |iM. It should be noted that the current panel of
bioactivity assays interrogating thyroid hormone dynamics is predominately targeted at receptor-
dependent agonism/antagonism, which is only one of several pathways by which the mammalian
HPT-axis may be perturbed by PFAS (Noves etal.. 2019). K+PFHxS was not active in any of the
three steroidogenesis assays in the database. Overall, although not conclusive, PFHxS exhibited
little in vitro endocrine activity in these assays (>96% of assays were inactive).
Overall, the mechanistic information is scarce and inconclusive, and therefore does not
provide clear support for or against endocrine (thyroid)-modulating activity of PFHxS.
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B
s
1
ts
1
ATG.ERE_CtS.UD
HfTCAll ACTIVE
Potassum p*rtk>0anasu»fonate (3871-99-6,i
OTXS>D3037709
TP0001679E08
•
J /
/
A i
]/
o
1 C
Si
1 1 1 1
1
40 »
©'
u • »
< I
1—1 1 i
Consian: MotW
Ga»n-iaw Mow
loo Concanfra&on (uM)
I hii Modal
Winning Model
Modal
ak:
RMSE
To©
AC 50
Siop«
Constant
182 22
3911
-
Gam-loss
126 97
634
104 62
1868
091
H«ll
122 97
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104 62
18 68
091
Figure 3-12. EDSP21 results of PFHxS active assays: A: ATG_ERE_CIS_up induction assay performed in HepG2 cells; B:
NIS_RAIU_inhibition assay performed in HEK293T cells. Assay details available in Appendix C, Section 3.
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Evidence Integration
Human studies provide conflicting evidence as to the potential effects of PFHxS on thyroid
outcomes (e.g., thyroid hormone levels). Although a few studies did suggest an association between
increasing PFHxS exposure levels and decreased circulating thyroid hormones (i.e., T4) or
subclinical thyroid disease, the associations were not consistent across studies (most studies were
null); the inconsistent findings could not be explained by differences in study design, confidence, or
other factors such as population, and there was no clear coherence across outcomes. The available
human evidence on PFHxS effects on the thyroid is indeterminate.
Evidence of thyroid toxicity resulting from PFHxS exposure in animal models exposed in
short-term and multigenerational studies showed dose-dependent effects on thyroid hormone (TH)
levels, most notably consistent decreases in serum T4 levels in rats (untested in mice) fNTP. 2018a:
Ramhai etal.. 20181. Coherent and consistent decreases in T3 in rats were also observed across
studies, whereas TSH was unchanged. Thyroid organ weights and thyroid histopathology were
inconsistently or only weakly affected across studies (e.g., increased incidence of thyroid
hypertrophy and mild hyperplasia in one study and decreased thyroid weight in another, with
otherwise null results), suggesting that the TH decreases are probably not attributable to effects of
PFHxS on thyroid gland function. However, the available evidence from exposed rodents shows a
consistent, dose-dependent disruption of thyroid hormone homeostasis, characterized by
decreased T4 and T3 serum levels concurrent with unaffected, normal levels of TSH is consistent
with hypothyroxinemia and also consistent with what has been observed in other PFAS including
PFBS, PFHxA, PFBA and PFOA. The observed TH decreases occurring in exposed adult animals and
indirectly (through the dams) exposed offspring were of a large magnitude of effect and occurred
even at PFHxS exposure levels as low as 0.625 mg/kg-day in male rats. This finding is consistent
with the published proposed thyroid disruption Adverse Outcome Pathway (AOP) by Noves etal.
f20191 and publication by Zoeller and Crofton f20051. in which the authors illustrated that
endocrine disruption in humans and rodents possess analogous key events and adverse outcomes
perhaps due to conserved biology across species (see additional discussion below). Decreased
thyroid hormone levels are judged relevant to human health, given the many similarities in the
production, regulation, and functioning of thyroid hormones between rodents and humans (Vansell.
2022: Stagnaro-Green and Rovet. 2016: Dong etal.. 2015: Navarro etal.. 2014: Rovet. 2014: Berbel
etal.. 2010: Morreale de Escobar et al.. 2008: Cuevas etal.. 2005: Rovet. 2005: Zoeller and Rovet.
2004: Hood and Klaassen. 2000: Hood etal.. 1999a: Hood etal.. 1999bl. Taken together, the
available animal evidence on endocrine effects, which is primarily based on the observed
supporting decreases in thyroid hormone levels after PFHxS exposure, is considered moderate.
Mechanistic studies examining the endocrine disrupting effects of PFHxS are scarce. In the
single mammalian study, Long etal. (2013). PFHxS, similar to other tested PFAS, inhibited cell
growth but not proliferation in the T3-dependent rat pituitary cell line, GH3. However, while this
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study suggests the possibility that PFHxS might compete with THs, these data alone are insufficient
to provide support for biological plausibility.
The currently available evidence indicates that PFHxS exposure likely causes thyroid
effects in humans given sufficient exposure conditions6 (see Table 3-10). This conclusion is based
primarily on consistent and coherent decreases in thyroid hormone levels across short-term and
multigenerational studies in rats exposed to PFHxS levels >2.5 mg/kg-day (with males being more
sensitive). The pattern of available evidence in rats indicates that PFHxS, like other PFAS (U.S. EPA.
2021a: Coperchini etal.. 2017) leads to a disruption of thyroid hormone homeostasis in a pattern
similar to hypothyroxinemia. Noves etal. (2019) along with Zoeller and Crofton (2005) illustrated
that endocrine disruption in humans and rodents possess analogous key events and adverse
outcomes perhaps due to conserved biology across species, and thus these effects are considered
adverse and relevant to humans. These TH decreases could have detrimental effects on susceptible
populations as T3 and T4 are critical in brain development and bone growth during early childhood
and adolescence (Crofton. 2004). However, at present, few epidemiological studies and
toxicological studies have addressed PFHxS-induced effects in these populations, highlighting an
important data gap.
6 The "sufficient exposure conditions" are more fully evaluated and defined for the identified health effects
through dose-response analysis in Section 5.
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Table 3-10. Evidence profile table for PFHxS thyroid effects
Evidence Stream Summary and Interpretation
Evidence Integration
Summary Judgement
Evidence from studies of exposed humans (see Human Thvroid Section)
Studies and confidence
Factors that increase
certainty
Factors that decrease
certainty
Summary and key findings
Evidence stream judgment
®©o
Evidence Indicates (likely)
Primary basis:
Moderate animal evidence for
decreased T4 and T3 in adult
and juvenile rats
Human relevance:
Effects in rats are considered
relevant to humans due to
conserved biology across
species (see Evidence
Integration section.)
Cross-stream coherence:
NA; human evidence
indeterminate
Susceptible Populations and
lifestages:
Young individuals exposed to
PFHxS during gestation and
early childhood may be
susceptible populations.
Thyroid Measures &
Disease
Twenty-six medium
confidence studies
Ten low confidence
• No factors noted
• Unexplained
inconsistency
Some human studies report an
inverse association between
thyroid hormones and PFHxS
exposure, but most studies
reported null findings.
ooo
Indeterminate
Evidence from in vivo animal studies (see Animal Thvroid Section)
Studies and confidence
Factors that increase
certainty
Factors that decrease
certainty
Summary and key findings
Evidence stream judgment
Thyroid Hormones
Three high confidence
studies in rats
• 28-d
• Multigenerational
• Consistent and
coherent decreases of
T4 and T3 in adult and
juvenile rats in the
absence of effects on
TSH
• Large Magnitude of
effect (up to 70%)
• Dose response in
studies
• No factors noted
Studies in rats (2 for T3 and 3
forT4) reported significant
decreases in TH levels in both
male and female rats (for T4),
or just male rats (for T3),
generally after PFHxS exposure
at >2.5 mg/kg-d.
©0©
Moderate
Based on decreased T4 and
T3
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' and Related Salts
Evidence Stream Summary and Interpretation
Evidence Integration
Summary Judgement
Histopathology
Three high confidence
studies in rats
• 28- and 42-d
• Multigenerational
• No factors noted
• No factors noted
Increased incidence of thyroid
hypertrophy and hyperplasia in
male rats in one study.
Organ Weights
Three high confidence
studies in rats and one
medium confidence
study in mice
• Concerning magnitude
of effect (up to 23%
decrease) in female
pups in one study
• Unexplained
inconsistency
(across studies for
thyroid weights
and across sexes
for adrenal
weights)
Decreased absolute thyroid
weight in female F1 pups at
PD22 (one study); Increased
absolute adrenal gland weight
in female rats and decreased
absolute adrenal gland weight
in male rats (one study);
Increased relative adrenal
gland weight in female rats
(highest dose only) and
decreased a relative adrenal
gland weight in male rats (one
study).
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3.2.2. Immune Effects
Human Studies
Epidemiology studies examining immune effects of PFHxS exposure include studies on
antibody response, infectious diseases, and hypersensitivity-related outcomes, which includes
asthma, allergies, and atopic dermatitis. The health effects results were grouped across studies to
develop conclusions on the same or related outcomes for the main categories of immune response
according to immunotoxicity guidance from the World Health Organization/ International
Programme on Chemical Safety flPCS. 20121: (1) immunosuppression, (2) sensitization or allergic
response, and (3) autoimmunity. Evidence for potential immune effects was considered within
these three categories because of common and related mechanisms within each category. Within
each category, health effects data were considered in the order of most to least informative for
immunotoxicity risk assessment (IPCS. 20121. Specifically, clinical studies on disease or immune
function assays are considered most informative, then general/observational immune assays
(lymphocyte phenotyping or cytokines), and finally endpoints such as hematology (i.e., blood
leukocyte counts) are least informative. Outcomes related to immunosuppression were considered
within two subcategories: antibody response and infectious disease. Several different outcomes,
such as asthma and food allergies, were included in the sensitization and allergic response category.
No studies were identified that evaluated outcomes related to autoimmunity.
Immunosuppression
Antibody response outcomes
The production of antigen-specific antibodies in response to an immune challenge (e.g.,
vaccination in humans or injection with sheep red blood cells in rodents) is a well-accepted
measure of immune function included in risk assessment guidelines and animal testing
requirements for immunotoxicity (IPCS. 2012: ICH Expert Working Group. 2005: U.S. EPA. 1998:
IPCS. 19961. The production, release, and increase in circulating levels of antigen-specific
antibodies are important for protection against infectious agents and preventing or reducing
severity of influenza, respiratory infection, colds, and other diseases as part of the humoral immune
response. Reduced antibody production is an indication of immunosuppression and may result in
increased susceptibility to infectious disease.
Evaluations for studies of antibody responses following vaccination as reported in ten
epidemiological studies (reported in 11 publications) are summarized in Figure 3-13. Among these
studies, there were analyses of several vaccinations: diphtheria (six studies), tetanus (seven
studies), measles (three studies), rubella (two studies), mumps (one study), Haemophilus
influenzae Type B (two studies), hepatitis (one study), and FluMist (one study). There were four
prospective birth cohorts, including three in the Faroe Islands and one in Norway fGranum etal..
20131. and one cohort of children beginning in their first year of life in Guinea-Bissau
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fTimmermann etal.. 20201. The three Faroe Islands studies included non-overlapping populations
enrolled at separate times, all medium confidence, one with enrollment in 1997-2000 and
subsequent follow-up to age 7 fGrandiean etal.. 20121 and age 13 fGrandiean etal.. 2017al. one
with enrollment in 2007-2009 and follow-up to age 5 fGrandiean etal.. 2017bl. and one with
enrollment in 1986-1987 and follow-up to age 28 fShih etal.. 20211. These cohorts are thus
considered independent of each other. Some analyses in Grandiean et al. f2017bl combined new
data from the cohort born in 2007-2009 with new follow-up data from the cohort born in 1997-
2000 fGrandiean etal.. 20121: these are labeled in the results table. Given that the etiologic window
for immune effects of PFAS exposure is not known, these studies in the Faroe Islands have the
benefit of assessing multiple windows of exposure (maternal, multiple points in childhood) as well
as following outcomes over time. For example, exposures measured during infancy could have
reflected residual maternal antibodies, but the half-life of maternal antibodies is short and residual
antibodies would not be expected to exist beyond infancy and would not exist in the children at age
five years. Similarly, vaccine boosters likely changed these children's antibody concentrations over
time, but such changes were not expected to be related to PFHxS concentration. Having multiple
windows of exposure in this study allowed for comparisons of effects. In children, there were also
two medium confidence cross-sectional studies in the U.S. and Greenland fTimmermann etal.. 2021:
Stein etal.. 2016bl and one low confidence (due to expected residual confounding) cross-sectional
study in Germany fAbraham etal.. 20201. In adults, there were two additional low confidence
studies, a short-term cohort (with exposure measured at vaccination and follow-up 30 days later)
in the United States (Stein etal.. 2016a) and a cross-sectional study in Denmark (Kielsen etal..
2016). These studies were low confidence due to concerns for potential selection bias and
confounding.
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Abraham, 2020, 6506041
Grandjean, 2017a, 3858518
Grandjean, 2017b, 4239492
Granum, 2013, 1937228
Kielsen, 2016, 4241223
Shih, 2021,9959487-1
Stein, 2016, 3108691
Stein, 2016, 3860111
Timmermann, 2020, 6833710
Timmermann, 2021, 9416315 ~
Legend
I Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-13. Summary of evaluation of epidemiology studies of PFHxS and
antibody response immunosuppression effects. For additional details see HAWC
link.
There are outcome-specific ratings for these domains. Multiple publications of the same data are presented on the
heat map as one study. Grandjean et al. (2017a) also includes Grandjean et al. (2012).
The results for this set of studies are shown in Tables 3-11 (children) and 3-12 (adults).
Although results were mostly not statistically significant, a general inverse trend was apparent,
particularly among studies of children. Of the six medium confidence studies in children, three
(Grandjean etal.. 2017a: Stein etal.. 2016b: Granum etal.. 2013) observed a statistically significant
inverse association for at least one vaccine type while the other three also reported inverse
associations in some analyses fTimmermann etal.. 2021: Timmermann et al.. 2020: Grandiean et
al.. 2017bl Antibody levels were measured in the blood of individuals of several age groups (and
therefore different lengths of time since their initial vaccination or booster vaccination) and
compared with serum PFHxS concentrations also measured at different ages. All the studies in
children reported an association between higher concentrations of PFHxS and lower anti-vaccine
antibody levels in at least some exposure-outcome analysis pairs. These associations were
statistically significant for tetanus vaccination in children at ages 5 and 7 with childhood exposure
measurement Grandiean etal. f20121 and for rubella vaccination in Granum etal. ("20131 and Stein
etal. f2016bl There are some results in the opposite direction for sub-analyses of the Faroe Island
cohorts and in Timmermann etal. (20211 In Timmermann etal. f2020I an inverse association was
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observed in children who had received only one measles vaccination, but a positive association was
observed in children who had received two vaccinations. Neither of these results were statistically
significant, but the exposure contrast in this study was limited, which may have influenced their
ability to detect a statistically significant effect. No biological rationale has been identified as to
whether one exposure time period is more predictive of an overall immune response which might
explain the few inconsistent results. Only one study fTimmermann etal.. 20211 examined the odds
ratio for not being protected against diphtheria (antibody concentrations < 0.1 IU/mL), which has
clearer clinical significance than continuous changes in antibody levels, and they reported an OR of
6.44 (95% 1.51, 27.36) among children with known vaccination records (adjusted for area of
residence, consistent with continuous antibody results).
In adults, the birth cohort with follow-up to young adulthood fShih etal.. 20211 reported
inconsistent results across exposure measurement timing windows. Results were similarly
inconsistent for antibodies to Hepatitis A and B (not shown). One low confidence study reported an
inverse association for diphtheria and tetanus vaccination (Kielsen etal.. 20161. The single study of
FluMistreported no immunosuppression (Stein etal.. 2016a).
It is plausible that the observed associations with PFHxS exposure could be explained by
confounding across PFAS. Exposure levels to other PFAS in the Faroe Islands populations were
considerably higher (blood concentrations of PFOS 17 ng/mL, PFOA 4 ng/mL, PFHxS 0.6 ng/mL) at
age 5 years in Grandiean etal. f20121. and there was a moderately-high correlation between PFHxS
with PFOS and PFOA (r = 0.57 and 0.53, respectively). The authors assessed the possibility of
confounding in a follow-up paper (Budtz-l0rgensen and Grandiean. 2018) in which PFHxS effect
estimates from a piecewise-linear model were adjusted for PFOS and PFOA and there was only
limited attenuation of the observed effects of PFHxS indicating that there was still an independent
effect of PFHxS(see Appendix D, Table D-l). These two PFAS were the most important to control for
given that they were the most highly correlated with PFHxS and present at the highest
concentrations in the population. The other available studies did not perform multipollutant
modeling. In Stein etal. (2016b). correlations between PFHxS and PFOS and PFOA were moderate-
high (r = 0.6 and 0.45, respectively), while in the other studies of antibody response, specific
correlations for each pair of PFAS were not provided, so it is difficult to determine the potential for
highly correlated PFAS to confound the effect estimates. Still, seeing PFHxS associated with the
outcome in multiple studies, each of which have different exposure conditions and thus different
inter-PFAS correlations, reduces the likelihood that confounding is the explanation. Overall, while it
is not possible to rule out confounding across PFAS, the available evidence supports that it is
unlikely to completely explain the observed effects, based primarily on the multipollutant modeling
results of the Faroe Islands studies (Budtz-l0rgensen and Grandiean. 2018). Other sources of
potential confounding, including possible co-exposures such as PCBs, were controlled
appropriately.
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Despite the imprecision of many of the individual exposure-outcome analysis pairs, the
findings are generally consistent with an association between PFHxS exposure and
immunosuppression. Of the 37 antibody-to-PFHxS-exposure analyses provided in Table 3-11, 26
support a finding of decrease in antibodies with higher PFHxS concentration. While some were less
than a 1% decrease in antibody concentration per doubling of PFHxS concentration, the majority
were greater than 5% and several were greater than 10%. While there is not clear clinical adversity
for these fairly small changes in antibody levels for a healthy individual, by lowering the immune
response of the entire population, it is likely that a subset of people will be shifted into clinically
relevant immune suppression and that people with pre-existing immunosuppression will be more
severely affected. This combined with the elevated odds for lack of protection from diphtheria in
Timmermann etal. f20211 support that this is a relevant health effect resulting from PFHxS
exposure. The variability in the results, including a few null and positive associations, could be
related to differences in sample sizes, individual variation, vaccine type, and differences in timing of
the boosters, as well as differences in timing of antibody measurements in relation to the last
booster. However, these factors cannot be explored further with currently available evidence. The
inverse associations were observed despite limited sensitivity resulting from narrow exposure
contrast in some studies. While multiple of the available studies are in a fairly specific population
(i.e., Faroe Islands), this is the highest quality evidence available and the results are directly
relevant to humans in general, particularly given the similar exposure levels to the general U.S.
population. There is not evidence that differences in dietary habits (e.g., marine diet) or social
determinants of health in this population can explain the results. In summary, some uncertainty
remains resulting from variability in the response by age of exposure and outcome measures as
well as from vaccination (initial and boosters), and also due to the potential for confounding across
PFAS discussed above; but overall, the available evidence provides support for an association
between increased serum levels of PFHxS and decreased antibody production following routine
vaccinations in children and adults.
Table 3-11. Summary of PFHxS and data on antibody response to vaccines in
children
Reference, N,
confidence
PFHxS Exposure
timing and
concentration in
serum
Outcome measure timing
Effect estimate as
specified
Effect estimate as
specified a
Diphtheria vaccine
(% change in antibodies
with increase in PFHxS)
Tetanus vaccine
(% change in
antibodies with
increase in PFHxS)3
Grandiean et al.
(2012). N = 380-
537, medium
Maternal; mean
(IQR): 4.4 (2.2-8.4)
ng/mL
Children (age 5), prebooster
-6.4 (-16.0 to 4.3)
-6.3 (-15.1 to 3.4)
Children (age 5), postbooster
-3.7 (-14.1 to 7.9)
6.3 (-8.4 to 23.2)
Children (age 7)
-0.5 (-13.1 to 14.0)
4.5 (-9.6 to 20.6)
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Reference, N,
confidence
PFHxS Exposure
timing and
concentration in
serum
Outcome measure timing
Effect estimate as
specified
Effect estimate as
specified a
Grandiean et al.
Children (age 5);
mean (IQR): 0.6
(0.5-0.9) ng/mL
Children (age 5), prebooster
5.0 (-8.9 to 21.0)
-6.3 (-17.6 to 6.5)
Children (age 5), postbooster
-9.1 (-18.7 to 1.7)
-19.0 (-29.8 to -6.6)
Children (age 7)
-9.8 (-22.3 to 4.9)
-19.7 (-31.6 to -5.7)
(2017a)
1997-2000 cohort
Children (age 7);
mean (IQR): 0.5
(0.4-0.7) ng/mL
Children (age 13)
-10.2 (-25.7 to 8.5)
14.8 (-13.3 to 52.2)
Children (age 13);
mean (IQR): 0.4
(0.3-0.5) ng/mL
Children (age 13)
-5.5 (-22.9 to 15.8)
8.7 (-18.5 to 45.0)
Grandiean et al.
(2017b)b. N = 349.
medium
2007-2009 cohort
(unless specified)
At birth, not
reported
Children (age 5), prebooster
-3.33 (-15.28 to 10.30)
-11.31 (-21.72 to 0.49)
Infant (18 m);
median (IQR): 0.2
(0.1-0.4) ng/mL
Children (age 5), prebooster
2007-2009 cohort
7.85 (-0.38 to 16.76)
1997-2000 cohort
-12.42 (-55.25 to 71.43)
2007-2009 cohort
-2.616 (-10.08 to 5.47)
1997-2000 cohort
-5.18 (-51.71 to 86.19)
Children (age 5);
median (IQR):0.3
(0.2-0.4) ng/mL
Children (age 5), prebooster
4.26 (-15.12 to 28.08)
-4.432 (-21.26 to
15.99)
Granum et al.
(2013). N =49.
medium
Maternal 0-3 d
post-delivery;
median: 0.3 ng/mL
Children (age 3)
n/a
0.07 (-0.03 to 0.18)
Granum et al.
(2013). N = 50.
medium
Maternal 0-3 d
post-delivery;
median: 0.3 ng/mL
Children (age 3)
-0.48 (-4.64 to 3.67)
n/a
Timmermann et
al. (2021). N = 314.
medium
Children (age 7-12)
Children (age 7-12)
Adjusted for time since
vaccine booster,
breastfeeding duration
48 (1,115)
Additionally adjusted for
area of residence
-40 (-64,1)
Adjusted for time since
vaccine booster,
breastfeeding duration
28 (-6, 73)
Additionally adjusted
for area of residence
-28 (-53,10)
Maternal
-53 (-87, 73)
-1 (-72, 245)
Measles vaccine
P (95%)a
Rubella vaccine
P (95%)a
Timmermann et
al. (2020). N = 237.
medium
Children (<1 yr)
0.1 (0.1-0.1)
Children (<1 yr)
-5 (-23, 18)
NR
Children (2 yrs)
After 1 vaccine (control
group)
-11 (-34,19)
After 2 vaccines
(intervention group)
10 (-18, 48)
NR
Granum et al.
(2013). N = 50.
medium
Maternal 0-3 d
post-delivery;
median: 0.3 ng/mL
Children (age 3)
-0.04 (-0.30 to 0.22)
-0.38 (-0.66 to -0.11)
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Reference, N,
confidence
PFHxS Exposure
timing and
concentration in
serum
Outcome measure timing
Effect estimate as
specified
Effect estimate as
specified a
Stein et al.
(2016b). N = 1.101-
1,190,
medium
Children (age 12-
19); mean: 2.5
ng/mL
Children (age 12-19)
-2.8 (-10.1 to 5.21)
(seropositive)
-6.0 (-9.6 to -2.2)
(seropositive)
Hib vaccine
P (95%)a
Mumps vaccine
P (95%)a
Granum et al.
(2013). N = 50.
medium
Maternal 0-3 d
post-delivery;
median: 0.7ng/mL
Children (age 3)
-0.48 (-4.64 to 3.67
n/a
Stein et al.
(2016b). N = 1.101-
1,190,
medium
Children (age 12-
19); mean: 2.5
ng/mL
Children (age 12-19)
n/a
-2.3 (-5.5 to 0.9)
aLinear regression (
5 or % change in antibody per twofold increase of PFHxS). Numbers in parentheses are 95%
confidence intervals.
bResults for Faroe Islands Cohort 5 (2007-2009) unless otherwise stated.
Bold font indicates p < 0.05.
One study did not report quantitative results. Abraham et al. (2020) stated in text that there were no significant
correlations of levels of PFHxS with levels of the vaccine antibodies for Hib, tetanus, or diphtheria.
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Table 3-12. Summary of PFHxS and data on antibody response to vaccines in
adults
Reference, N,
confidence
Exposure timing
and
concentration
Outcome
measu re
timing
Diphtheria vaccine
P (95 %f
Tetanus vaccine
P (95%)a
FluMist (A H1N1)
vaccine
Seroconversion RR
(95% CI)
Shih et al.
(2021), Faroe
Islands, N =
281, medium
Cord blood; median
(IQR) 0.2 (0.2)
Adults (age
28)
Total: 13.57 (-2.4,
32.15))
Women: 12.94 (-6.42,
36.32)
Men: 14.72 (-10.98,
47.82)
Total: 0.63 (-10.86, 13.6)
Women: 0.58 (-13.47,
16.91)
Men: 0.74 (-17.78, 23.43)
n/a
Children (age 7); 0.9
(0.4)
Total: 1.96 (-18.98,
28.31)
Women: -18.74 (-
43.42, 16.68)
Men: 17.48 (-11.86,
56.59)
Total: 3.23 (-13.22,
22.79)
Women: -8.27 (-30.54,
21.15)
Men: 11.01 (-10.78,
38.13)
Children (age 14);
0.6(0.4)
Total: -7.62 (-37.93,
37.48)
Women: -8.03 (-47.08,
59.84)
Men: -7.20 (-47.17,
62.98)
Total: -10.24 (-35.99,
25.87)
Women: -17.92 (-48.63,
31.14)
Men:-1.37 (-39.02,
59.53)
Adults (age 22); 0.5
(0.4)
Total: -8.44 (-27.27,
15.27)
Women:-15.68 (-
36.26, 11.55)
Men: 8.32 (-27.37,
61.54)
Total: -3.47 (-19.88, 16.3)
Women: -10.25 (-28.45,
12.57)
Men: 11.85 (-18.98, 54.4)
Kielsen et al.
(2016). N = 12.
low
Adult (10 d post
vaccination);
median (IQR): 0.4
(0.3-0.7) ng/mL
Adult-
change from
4 d to 10 d
postvaccinati
on
-13.31 (-25.07, 0.29)
-4.35 (-13.72 to 6.04)
n/a
Stein et al.
(2016a).
N = 75,
low
Adult (18-49 yrs
old), d of
vaccination; mean:
1.1 ng/mL
Adult (18-49
yrs old), 30 d
postvaccinati
on
n/a
n/a
by hemaglutinin
inhibition:
T2: 1.2 (0.2, 6.5)
T3: 3.1 (0.8, 12.7)
by immuno-
histochemistry:
T2: 1.1 (0.4, 2.9)
T3: 1.7(0.6, 4.8)
aLinear regression (P or % change in antibody per two-fold increase of PFHxS). Numbers in parentheses are 95%
confidence intervals.
Bold font indicates p < 0.05.
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Infectious disease
Direct measures of infectious disease incidence or severity such as respiratory tract
infections, pneumonia or otitis media are useful for evaluating potential immunotoxicity in humans.
Increases in incidence or severity of infectious disease can be a direct consequence of impaired
immune function whether the specific functional deficit has been identified or not. Given the clear
adversity of most infectious diseases, they are generally considered good measures for how
immunosuppression can affect individuals and communities. Physician diagnosis is the most
specific way to assess infectious diseases, but these are usually only available for severe diseases
and are less likely for diseases where treatment is not sought Self-reported incidence or severity of
disease may be less reliable but may be the only way to assess diseases such as the common cold or
gastroenteritis which while less adverse, are more common and can thus provide information about
immunosuppression and susceptibility to more severe infections. In general, symptoms of infection
alone are not considered reliable measures of disease because of their lack of specificity. Antibody
levels in response to infection are also included in this section (differentiated from antibody levels
in response to vaccination, described above); the utility of these measures depends on the study
design and population due to various factors such as potential confounding and prevalence of
infection.
Ten studies examined infectious disease occurrence in children, including eight prospective
birth cohorts one cohort with exposure measurement in childhood, and one cohort examining
antibody response to Hand, Foot, and Mouth Disease (HFMD) infection in the first three months of
life. In addition, two studies examined infectious disease occurrence in adults, including a cross-
sectional study of COVID-19 illness severity (Grandiean etal.. 20201 and a cross-sectional study of
antibody levels in response to several persistent infections fBulka etal.. 20211.
Study evaluations are summarized in Figure 3-14. Of the studies in children, four studies in
Japan fGoudarzi etal.. 20171. Spain fManzano-Salgado etal.. 20191. Denmark fDalsager etal..
2021a), and China (Wang etal.. 20221 were medium confidence, and the remaining studies were
low confidence (Kvalem et al.. 2 0 2 0: Impinen etal.. 2019: Zeng etal.. 2019b: Impinen etal.. 2018:
Dalsager etal.. 2016: Granum etal.. 20131. The low confidence birth cohorts were rated as
"deficient" in outcome ascertainment due to relying on parental self-report of incidence of common
infections or symptoms, with no validation of the measures. However, because the parents are
unlikely to know their child's exposure level, this misclassification is likely to be nondifferential
with respect to exposure. In contrast, the medium confidence studies assessed physician-diagnosed
conditions and were limited to more severe illnesses (otitis media, pneumonia, varicella, and
respiratory syncytial viral infection), which likely have better parental recall. Zeng etal. (2019b)
was low confidence because the outcome is difficult to interpret in infants and there are concerns
for confounding by timing of HFMD infection as well as other limitations. The two studies in adults
were both considered medium confidence. Grandiean etal. f20201 used biobank samples and
national registry data in Denmark to examine severity of COVID-19 illness severity. There was some
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1 concern for selection bias in this study due to the expectation that biobank samples were more
2 likely to be available for individuals with chronic health concerns. In addition, severity of COVID-19
3 is not a direct measure of immune suppression as other factors may contribute to illness severity.
Bulka, 2021, 7410156-
Dalsager, 2016, 3858505 -
Dalsager, 2021, 7405343 -
Goudarzi, 2016, 3859523-
Grandjean, 2020, 7403067-
Granum. 2013. 1937228-
Impinen, 2018, 4238440-
Impinen, 2019, 5080609-
Kvalem, 2020,6316210-
Manzano-Salgado, 2019, 5412076-
Wang, 2022, 10176501 -
Zeng, 2019, 5081554-
•
+
~
+
+
+
_
+
-
*
•
+
•f
-
*
*
1
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
+
J
D
+
+
-
*»-
~
D
+
+
+
f
4-
BO
¦4*
+
-
+ I +
+
~
-
-
++ -H-
-
++
*
-
~
~
-f
~ |
*
-
+
++
|
+ j
1
-
j-
*
+
¦V
+
-
4-
*
•
"
4
*
-
Figure 3-14. Summary of evaluation of epidemiology studies of PFHxS and
infectious disease immunosuppression effects. For additional details see
HAWC link.
Two studies (Impineri et al., 2018; Granum et al., 2013) were sub-samples of the Norwegian Mother and Child
(MoBa) cohort, The cohort sub-sampies for these publications were different, so their study evaluations and
results are reported independently, but it is possible that there is some overlap in the participants. Two studies
(Dalsager et al,, 2021a; Dalsager et al., 2016) were both analyses of the Odense Child Cohort. They were
evaluated separately due to their different samples and outcome measurement methods but were not
considered fully independent samples.
4 In children, higher odds of infectious disease with higher PFHxS levels were reported in two
5 of the four medium confidence studies fWang et al.. 2022: Goudarzi etal.. 20171 and three of the six
6 low confidence studies flmpinen et al.. 2019: Dalsager etal.. 2016: Granum et al.. 20131 (see Table
7 3-11). Wang etal. T20221 reported higher odds (though not statistically significant] of upper and
8 lower respiratory infection and diarrhea with higher exposure, fGoudarzi et al.. 20171 reported
9 higher odds of total infectious disease from birth to age 4, but only in girls, and a significant trend
10 was observed, but the association was nonmonotonic across quartiles. No clear explanation for why
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
these results might vary by sex is available, and none of the other studies of immunosuppression
analyzed the results stratified by sex. Impinenetal. (20191 also reported higher odds of
gastroenteritis (statistically significant from birth to age 3), but not common cold or otitis media.
Dalsager etal. f20161 reported higher odds of diarrhea and fever (p > 0.05), but not cough or nasal
discharge. Another medium confidence study fManzano-Salgado etal.. 20191 reported an
association in the same direction, but the effect estimate was small and imprecise. Two other low
confidence studies did not observe an association between maternal PFHxS concentrations and
infections. In adults and adolescents, one study found higher persistent pathogen burden with
higher exposure (Bulka etal.. 20211. In contrast, there an inverse association between PFHxS
exposure and COVID-19 illness severity. Overall, many of the studies had limited sensitivity due to
narrow exposure contrast, but there was no apparent relationship between higher study exposure
levels and observed associations. Given the inconsistency across studies, there is considerable
uncertainty in this outcome. The associations observed in some studies provide some limited
support for (and coherence with) the evidence of immunosuppression observed in the antibody
response studies.
Table 3-13. Summary of PFHxS and selected data on infectious disease in
humans
Disease
Reference,
confidence
Exposure
measu rement
timing and
concentration
Disease
assessment
timing
PFHxS results
Total infectious
disease3
Dalsager et al.
(2021a), medium
Maternal; median:
0.4
From birth to age 4
HR (95% CI)
1.02 (0.90, 1.16)
Goudarzi et al.
(2017)
medium
Maternal; median
(IQR): 0.3 (0.2-0.4)
ng/mL
From birth to age 4
Adj OR (95% CI) Total:
Q2 1.03 (0.764, 1.41)
Q3 1.23 (0.905, 1.69)
Q4 0.957 (0.703, 1.30)
Trend p = 0.928
Male:
Q2 0.780 (0.508, 1.19)
Q3 0.947 (0.614, 1.45)
Q4 0.708 (0.461, 1.08)
Trend p = 0.223
Female:
Q2 1.46(0.938, 2.29)
Q3 1.81 (1.14, 2.88)
Q4 1.55 (0.976, 2.45)
Trend p = 0.045
Lower respiratory
tract infection15
Impinen et al.
(2018)
low
Cord blood
From birth to age
10
Adj (3 (95% CI)
0.04 (-0.01, 0.09)
Dalsager et al.
(2021a), medium
Maternal; median:
0.4
From birth to age 4
HR (95% CI)
1.01 (0.78, 1.32)
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Disease
Reference,
confidence
Exposure
measu rement
timing and
concentration
Disease
assessment
timing
PFHxS results
Wang et al.
(2022), medium
Maternal; median
(IQR): 0.6(0.4-0.8)
Through Age 1
OR (95% CI)
10.62 (0.65, 173.7)
IRR (95% CI)
1.81 (0.27, 12.19)
Manzano-
Salgado et al.
(2019) medium
Maternal (1st
trimester), median
(IQR): 0.6 (0.4-0.8)
ng/mL
Age 1.5-7
1.07(0.96, 1.18)
Impinen et al.
(2019)
low
Maternal mid-
pregnancy; median
(IQR): 0.7 (0.5-0.9)
ng/mL
From birth to age 3
Adj RR (95% CI):
1.15(1.06, 1.24)
Age 6-7
0.92 (0.70, 1.21)
Kvalem et al.
(2020) low
Child age 10;
median (IQR): 1.3
(0.9)
Age 10-16
Adj RR (95% CI)
0.98(0.95, 1.02)
Age 16 (last 12 m)
0.93 (0.74, 1.18)
Gastroenteritis
(No. episodes/
frequency)
Granum et al.
(2013).
low
Maternal
0-3 d post-delivery;
median: 0.3 ng/mL
From birth to age 3
Adj P (95% CI)
3rd yr: 0.33 (-0.05, 0.71)
All 3 yrs: 0.35 (0.10, 0.61)
Dalsager et al.
(2021a), medium
Maternal; median:
0.4
From birth to age 4
HR (95% CI)
0.85 (0.50, 1.43)
Impinen et al.
(2019).
low
Maternal mid-
pregnancy; median
(IQR): 0.7 (0.5-0.9)
ng/mL
From birth to age 3
Adj (RR):
0.98(0.96, 1.02)
Age 6-7
1.27(1.18, 1.38)
Diarrhea
Dalsager et al.
(2016) low
Maternal; median
(range): 0.3 (0.02-
1.0) ng/mL
Age 1-3
OR for proportion of d with symptoms
(under/above median)
Low exposure: Ref
Medium: 1.16(0.66, 2.02)
High: 1.39 (0.77,2.51)
IRR for number of d with symptoms
Low exposure: Ref
Medium: 1.18(0.64, 2.19)
High: 1.71 (0.92, 3.16)
Wang et al.
(2022), medium
Maternal; median
(IQR): 0.6(0.4-0.8)
Through age 1
OR (95% CI)
1.17(0.20, 6.83)
IRR (95% CI)
1.27(0.50, 3.20)
Common cold
(No. episodes/
frequency)
Impinen et al.
(2018).
low
Cord blood; median
(IQR): 0.2 (0.2-0.3)
ng/mL
From birth to age 2
Adj P (95% CI)
-0.01 (-0.04, 0.02)
Granum et al.
(2013). low
Maternal
0-3 d post-delivery;
median: 0.3 ng/mL
From birth to age 3
Adj P (95% CI) c
3rd year: 0.24 (-0.03, 0.51)
All 3 yrs: 0.15 (-0.02, 0.32)
Dalsager et al.
(2021a), medium
Maternal; median:
0.4
From birth to age 4
HR (95% CI) for upper respiratory infections
1.01 (0.83,1.21)
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Disease
Reference,
confidence
Exposure
measu rement
timing and
concentration
Disease
assessment
timing
PFHxS results
Wang et al.
(2022), medium
Maternal; median
(IQR): 0.6(0.4-0.8)
Through Age 1
OR (95% CI)
1.49(0.28, 7.97)
IRR (95% CI)
1.16(0.60, 2.26)
Impinen et al.
(2019). low
Maternal mid-
pregnancy; median
(IQR): 0.7 (0.5-0.9)
ng/mL
From birth to age 3
Adj RR (95% CI):
1.01 (1.00, 1.03)
Kvalem et al.
(2020) medium
Child age 10;
median (IQR): 1.3
(0.9)
Age 10-16
Adj OR (95% CI):
Reference 1-2 colds
3-5 colds: 0.99 (0.93, 1.04)
>5:0.97(0.93, 1.03)
Age 16 (last 12 m)
Adj OR (95% CI)
Reference 0 colds
1-2 colds:0.98 (0.96, 1.00)
>3: 0.97 (0.94, 1.00)
Cough
Dalsager et al.
(2016) low
Maternal; median
(range): 0.3 (0.02-
1.0) ng/mL
Age 1-3
OR for proportion of d with symptoms
(under/above median)
Low exposure: Ref
Medium: 1.04(0.60,1.79)
High: 0.97 (0.54,1.73)
IRR for number of d with symptoms
Low exposure: Ref
Medium: 1.14(0.87,1.48)
High: 1.00 (0.76, 1.31)
Ear infection
Granum et al.
(2013). low
Maternal
0-3 d post-delivery;
median: 0.3 ng/mL
From birth to age 3
No significant association with otitis media
(data not shown)
Impinen et al.
(2019). low
Maternal mid-
pregnancy; median
From birth to age 3
Adj RR (95% CI):
1.09(1.04, 1.14)
(IQR): 0.7 (0.5-0.9)
ng/mL
Age 6-7
1.08(0.93, 1.25)
Throat infection
Impinen et al.
(2019). low
Maternal mid-
pregnancy; median
(IQR): 0.7 (0.5-0.9)
ng/mL
From birth to age 3
Adj RR (95% CI):
1.10(1.02, 1.18)
(no association with streptococcus throat
infection)
Pseudocroup
Impinen et al.
(2019). low
Maternal mid-
pregnancy; median
(IQR): 0.7 (0.5-0.9)
ng/mL
From birth to age 3
Adj RR (95% CI):
1.20(1.11, 1.30)
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Disease
Reference,
confidence
Exposure
measu rement
timing and
concentration
Disease
assessment
timing
PFHxS results
Fever
Dalsager et al.
(2016) low
Maternal; median
(range): 0.3 (0.02-
1.0) ng/mL
Age 1-3
OR for proportion of d with symptoms
(under/above median)
Low exposure: Ref
Medium: 0.99 (0.58,1.71)
High: 1.29 (0.72,2.28)
IRR for number of d with symptoms
Low exposure: Ref
Medium: 1.07(0.80,1.42)
High: 1.20 (0.89, 1.62)
Hand Foot and
Mouth Disease
Virus Antibodies
Zeng et al.
(2019b). low
Cord; median (IQR):
4.0(2.3-5.4)
Birth and age 3 mo
OR (95% CI) for HFMD antibody concentration
below clinically protective level
Cord blood:
1.08 (0.74,1.60)
3 mo: 1.00(0.71,1.43)
COVID-19 illness
severity
Grandiean et al.
(2020), medium
Biobank prior to
illness; median
(IQR):
0.5 (0.3-0.7)
Adulthood
OR (95% CI) for 1 unit increase
Increased severity based on hospitalization,
admission to intensive care and/or death
0.52 (0.29, 0.93)*
Pathogen burden
of persistent
infections based
on antibodies
Bulka et al.
(2021)
Mean: 1.5
Ages 12-49 yrs
Relative difference (95% CI) per doubling
12-19 yrs: 1.11(1.06,1.15)*
20-49 yrs: 1.02(1.00,1.05)*
For individual pathogens, only Toxocara spp
had positive association
Bolded values are statistically significant,
includes Otitis media, pneumonia, RS virus, Varicella.
bLower respiratory tract infections include bronchitis, bronchiolitis, and pneumonia.
cBivariate model was statistically significant (p = 0.036) for all 3 years.
Sensitization or allergic response
Another major category of immune response is the evaluation of sensitization-related or
allergic responses resulting from exaggerated immune reactions (e.g., allergies or allergic asthma)
to foreign agents flPCS. 20121. A chemical may be either a direct sensitizer (i.e., promote a specific
IgE-mediated immune response to the chemical itself] or may promote or exacerbate a
hypersensitivity-related outcome without evoking a direct response. For example, chemical
exposure could promote a physiological response resulting in a propensity for sensitization to other
allergens (pet fur, dust, pollen, etc.). Hypersensitivity responses occur in two phases. The first
phase, sensitization, is without symptoms, and it is during this step that a specific interaction is
developed with the sensitizing agent so that the immune system is prepared to react to the next
exposure. Once an individual or animal has been sensitized, contact with that same (or, in some
cases, a similar) agent leads to the second phase, elicitation, and symptoms of allergic disease.
While these responses are mediated by circulating factors such as T-cells, IgE, and inflammatory
cytokines, there are many health effects associated with hypersensitivity and allergic response.
Functional measures of sensitivity and allergic response consist of measurements of the health
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effects such as allergies or asthma and skin prick tests. Observational tests such as measures of
total IgE levels measure indicators of sensitivity and allergic responses but are not a direct
measurement of the response. The section is organized by the different types of measurements,
starting with functional measures as the most informative.
Thirteen studies (reported in 19 publications) examined hypersensitivity outcomes in
children. The study evaluations are summarized in Figure 3-15. Two of the included studies were
subsamples of the Norwegian Mother and Child (MoBa) cohort that were analyzed independently
flmpinen et al.. 2019: Granum etal.. 20131. In addition, three publications of NHANES data are
grouped together as one study because there is significant overlap in the NHANES years included in
the analysis samples fBuser and Scinicariello. 2016: Stein etal.. 2016b: Humbletetal.. 20141:
another publication examined a different year range of NHANES data and was considered
separately flackson-Browne etal.. 20201. Ten studies were prospective birth cohorts, with
exposure measured during gestation or in cord blood. These studies were performed in China
(Chen etal.. 2018al. Japan f Goudarzi et al.. 2 016: Okada etal.. 20141. Norway flmpinen et al.. 2019:
Impinen et al.. 2018: Granum etal.. 20131. Greenland and Ukraine fSmit etal.. 20151. Spain
(Manzano-Salgado etal.. 20191. Denmark (Beck etal.. 20191. and the Faroe Islands (Timmermann
etal.. 20171. In addition to the cohort studies, there was a case-control study of asthma in Taiwan
reported in multiple publications fZhou etal.. 2017b: Zhu etal.. 2016: Dong etal.. 20131. a cohort of
children with exposure measured at age 10 fKvalem etal.. 20201. and the analyses of NHANES data,
which is cross-sectional. All the studies were considered medium confidence.,
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¦pT
¦JO
GO° 5©^
Beck, 2019, 5922599
Chen, 2018. 4238372-
Dong, 2013, 1937230-
Goudarzi, 2016. 3859523
Granum, 2013,1937228
Impinen, 2018. 4238440
Impinen, 2019, 5080609
Jackson-Browne MS et al. 2020
Kvalem, 2020,6316210
Manzano-Salgado, 2019, 5412076
Smit, 2015,2823268
Stein. 2016. 3108691
Timmermann, 2017, 3858497
0 Legend
Good (metric) or High confidence (overall)
+ Adequate (metric) or Medium confidence (overall)
- Deficient (metric) or Low confidence (overall)
H Critically deficient (metric) or Uninformative (overall)
Figure 3-15. Summary of evaluation of epidemiology studies of PFHxS and
hypersensitivity effects (e.g., asthma, allergies, and atopic dermatitis). For
additional details see HAWC link.
Multiple publications of the same data are presented on the heat map as one study. Goudarzi et al. (20161 also
includes Okada et al. (2014). Stein et al. (2016b) also includes Buser and Scinicariello (2016) and Humblet et al.
(2014).
Asthma
Twelve studies evaluated different measures related to asthma diagnosis and symptoms in
relation to PFHxS exposure (see Table 3-12. All studies were medium confidence. One study
examined asthma incidence (i.e., diagnosis within the past year, with cases identified from two
hospitals), which is the most specific measure available across studies, but which may result in
under-ascertainment because only severe cases are identified. The remaining studies examined
asthma prevalence using validated questionnaires, either "current" asthma (generally experiencing
symptoms in the pastyear with asthma diagnosis) or "ever" asthma (asthma diagnosis at any time
during their life). These measures are less specific than asthma incidence and the relevant etiologic
period is less clear.
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Four studies examined "current" asthma and 11 studies examined "ever" asthma. Looking at
current asthma, one study (Impinen et al.. 20191 out of four reported higher odds, although this was
not statistically significant. Three studies also reported a positive association with "ever" asthma,
but with inconsistency within each study. Zeng etal. f2019al reported a strong positive, but very
imprecise, association in boys, and an imprecise inverse association in girls, while in Beck et al.
f20191. a strong positive association (p < 0.05) was observed in girls for doctor-diagnosed asthma,
but there was no sex-interaction with self-reported asthma. InTimmermannetal. (20171. a positive
association was observed only in a small subgroup (4%, 22 children) of the study population that
did not receive MMR vaccination and may be due to chance. The remaining studies showed no
association with ever asthma.
The single study (reported in multiple publications) of asthma incidence (the most specific
outcome measurement available) reported higher odds of asthma in children 10-15 years of age
with higher PFHxS exposure with an exposure-response gradient observed across quartiles in the
overall population (Dong etal.. 20131. The association was stronger in girls than in boys (Zhu et al..
20161. although there was no significant interaction with sex hormone levels (Zhou etal.. 2017b).
The association was strong (OR >3 in highest quartile of exposure), and the outcome measurement
is likely to suffer from less outcome misclassification than would measures of asthma prevalence in
the other available studies. This medium confidence study in Taiwan also had PFHxS exposure
levels that were among the highest of the available studies, while several studies with null results
had exposure levels with narrow exposure contrast across participants, which may have reduced
sensitivity. While there is considerable uncertainty due to inconsistency in the results across
studies, the null results are not interpreted as contradictory to the positive findings given the better
sensitivity and specificity (and relatively higher exposure levels) in Dong etal. (2013).
Allergies/Allergic sensitization
Five studies, all medium confidence, evaluated allergies and allergic sensitization outcomes
(see Table 3-12). Two studies examined food allergies. Buser and Scinicariello (2016). an NHANES
analysis, reported higher odds of allergy in the second and fourth quartiles, with statistical
significance in the fourth quartile. Impinen et al. (2019) observed slightly higher, but not
statistically significant odds of current food allergies with higher exposure. Impinen etal. (2019)
also found higher, but not significant, odds of inhaled allergies. Four studies examined allergic
sensitization, and one study observed higher odds of elevated IgE with higher exposure, although
this was not monotonic as the highest odds were in the third quartile fBuser and Scinicariello.
2016). The other NHANES analysis (Stein etal.. 2016b) and three other studies did not report
higher odds of sensitization with higher exposure.
Dermal allergic measures - eczema
Nine studies evaluated eczema (see Table 3-12). While the studies used different
terminology including eczema, atopic eczema, and atopic dermatitis, most assessed presence of an
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itchy rash that was coming and going for at least 6 months using the International Study of Asthma
and Allergies in Childhood questionnaire. Three studies examined physician-diagnosed atopic
eczema, also collected using a questionnaire flmpinen etal.. 2019: Impinen etal.. 2018: Granum et
al.. 20131. and Kvalem etal. f20201 used a different questionnaire for self-reported eczema. These
dermal response conditions can represent hypersensitivity to an antigen exposure from any route.
Two medium confidence studies reported higher odds of eczema with higher PFHxS exposure (Chen
etal.. 2018a: Timmermann etal.. 20171. both statistically significant (in girls only for Chen et al.
(2018all. while two studies (Kvalem etal.. 2020: Okada etal.. 20141 reported an inverse
association. The remaining five studies reported no association. Exposure levels were highest in
Timmermann etal. f20171. but levels in Chen etal. f2018al were similar to the null studies, and
Okada etal. f20141. There is no apparent explanation for the inconsistency across studies on the
basis of study design, population, bias, or other factors.
Table 3-14. Summary of PFHxS and data on hypersensitivity in humans.
Reference
Exposure
measurement timing
and concentration
Hypersensitivity
measu rement
timing
PFHxS OR (95% Cl)a or as
specified
Asthma Incidence
GBCA
Dong et al. (2013)
Children, current;
median (IQR): 1.3 (0.6—
2.8) (without asthma)
Children (age 10-15)
Asthma diagnosed in past year
Q2: 1.54 (0.85, 2.77)
Q3: 2.94 (1.65, 5.25)
Q4: 3.83 (2.11, 6.93)
Trend p< 0.001
Zhou et al. (2017b)
Children (age 10-15)
By Sex Hormone Levels
Low Testosterone
M: 2.12 (1.34, 3.35)
F: 1.62 (1.08, 2.45)
High Testosterone
M: 1.43 (0.99, 2.07)
F: 2.27 (1.29, 3.99)
Low Estradiol
M: 1.47(1.00,2.15)
F: 2.39(1.39, 4.12)
High Estradiol
M: 1.62 (1.01, 2.60)
F: 1.65 (1.07, 2.55)
No significant interaction
between PFHxS and sex hormone
category
Zhu etal. (2016)
Children (age 10-15)
By Sex
Q4 vs Q1
M: 2.97 (1.33, 6.64)
F: 5.02 (2.05, 12.30)
Current Asthma
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Reference
Exposure
measurement timing
and concentration
Hypersensitivity
measu rement
timing
PFHxS OR (95% Cl)a or as
specified
Impinen et al. (2019)
Maternal mid-
pregnancy; median
(IQR): 0.7(0.5-0.9)
ng/mL
From birth to age 7
1.21 (0.87, 1.67)
Impinen et al. (2018)
Cord blood; median
(IQR): 0.2 (0.2-0.3)
ng/mL
From birth to age 10
0.99(0.82, 1.21)
Kvalem et al. (2020)
Child (age 10); median
(IQR): 1.3 (0.9) ng/mL
Child (age 16)
Last 12 months
RR: 1.00(0.98, 1.02)
NHANES
Stein et al. (2016b)
Children, current; mean:
2.5 ng/mL
Children (age 12-19)
IQR increase:
0.98(0.51, 1.87)
Ever Asthma
Zeng et al. (2019a)
Cord blood median
(IQR): 0.2 (0.1-0.2)
Child (age 5)
Ever asthma
2.02 (0.24, 17.24)
Girls: 0.48 (0.00, 85.33)
Boys: 3.40(0.18, 65.11)
MoBa
Granum et al. (2013)
Maternal
0-3 day post-delivery;
median: 0.3 ng/mL
From birth to age 3
No significant association (data
not shown)
Impinen et al. (2019)
Maternal mid-
pregnancy; median
(IQR): 0.7(0.5-0.9)
ng/mL
From birth to age 7
0.96(0.79,1.18)
Beck et al. (2019)
Maternal, gest week 8-
16; median (IQR): 0.4
(0.2-0.5) ng/mL
Child (age 5)
Ever doctor-diagnosed asthma
1.16(0.78,1.71)
Boys: 0.89 (0.59, 1.34)
Girls: 2.96 (1.26, 6.96)
Ever self-reported asthma (>
episodes of wheezing lasting
more than a day in past 12
months)
1.18(0.73,1.90)
Boys: 1.33 (0.66, 2.71)
Girls: 1.04(0.55, 1.98)
Manzano-Salgado et al. (2019)
medium
Maternal (1st trimester),
median (IQR): 0.6 (0.4-
0.8) ng/mL
Age 1.5-7
Ever asthma
RR: 0.96 (0.74, 1.24)
Jackson-Browne et al. (2020)
Child (age 3-11); mean
(IQR): 0.8 (0.5-1.3)
Child (age 3-11)
Ever asthma
OR: 1.1(0.9,1.3)
Kvalem et al. (2020)
Child (age 10); median
(IQR): 1.3 (0.9) ng/mL
Child (age 10)
Ever asthma
RR: 0.99 (0.97, 1.01)
Child (age 10-16)
Asthma between 10 and 16
years
RR: 1.00(0.99, 1.02)
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Reference
Exposure
measurement timing
and concentration
Hypersensitivity
measu rement
timing
PFHxS OR (95% Cl)a or as
specified
Smit et al. (2015)
Maternal, mean
gestational week 24 or
25; mean (5th-95th):
Ukraine: 1.5 (0.5-4.1),
Greenland: 2.1 (1.0-5.1)
Children (age 5-9)
0.91 (0.69, 1.18)
Impinen et al. (2018)
Cord blood; median
(IQR): 0.2 (0.2-0.3)
ng/mL
From birth to age 10
0.94(0.72, 1.21)
Timmermann et al. (2017)
Maternal, gestational
week 34-36; median
(IQR): 4.5 (2.2-8.3)
Child (age 5)
0.99(0.80, 1.22)
Child (age 13)
0.98(0.79, 1.20)
Child (age 5); median
(IQR): 0.6(0.4-0.9)
Child (age 5)
No MMR: 3.57(0.95, 13.43)b
Yes MMR: 0.81 (0.58, 1.14)
Interaction p = 0.03
Child (age 13)
No MMR: 2.52 (0.77, 8.16)b
Yes MMR: 0.90 (0.63, 1.27)
Interaction p = 0.10
Child (age 13); median
(IQR): 0.4(0.3-0.5)
Child (age 13)
0.63 (0.41, 0.97)
NHANES
Humblet et al. (2014)
Children, current;
median (IQR): 2.0 (1.0,
4.1)
Children (age 12-19)
Continuous: 0.98 (0.88-1.08)
T2: 1.07(0.89, 1.30)
T3: 0.92 (0.74, 1.14)
Allergies (Food)
Impinen et al. (2019)
Maternal mid-
pregnancy; median
(IQR): 0.7(0.5-0.9)
ng/mL
From birth to age 7
Ever: 1.03 (0.82,1.30)
Current: 1.10 (0.86,1.41)
NHANES
Buser and Scinicariello (2016)
Children, current; mean:
2.2 ng/mL
Children (age 12-19)
Q2 1.43 (0.40, 5.14)
Q3 0.99 (0.37, 2.65)
Q4 3.06 (1.35, 6.93)
Trend p = 0.11
Allergies (Inhaled)
Impinen et al. (2019)
Maternal mid-
pregnancy; median
(IQR): 0.7(0.5-0.9)
ng/mL
From birth to age 7
Ever: 1.18(0.93,1.50)
Current: 1.21 (0.81,1.81)
Allergies (Sensitization)
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Reference
Exposure
measurement timing
and concentration
Hypersensitivity
measu rement
timing
PFHxS OR (95% Cl)a or as
specified
Impinen et al. (2018)
Cord blood; median
(IQR): 0.2 (0.2-0.3)
ng/mL
From birth to age 10
Positive SPT or slgE > 0.35 kU/L
1.01 (0.84, 1.21)
Kvalem et al. (2020)
Child (age 10); median
(IQR): 1.3 (0.9) ng/mL
Child (age 10)
Positive skin prick test
RR: 1.01 (1.00, 1.02)
Child (age 16)
Positive skin prick test
RR: 1.00(1.00, 1.01)
Timmermann et al. (2017)
Maternal, gestational
week 34-36; median
(IQR): 4.5 (2.2-8.3)
Children (age 13)
Positive skin prick test
0.94(0.79,1.12)
Positive skin prick test
0.95 (0.75,1.20)
Positive skin prick test
0.88(0.64,1.21)
Children (age 5)
Children (age 13)
Child (age 5); median
(IQR): 0.6(0.4-0.9)
Children (age 13)
NHANES
Buser and Scinicariello
(2016)
Children, current; mean:
2.2 ng/mL
Children (age 12-19)
Sensitization (any slgE >0.35
kU/L)
Q2 1.11 (0.66, 1.88)
Q3 1.46 (0.79, 2.69)
Q4 1.17 (0.56, 2.44)
Trend p = 0.72
Stein et al. (2016b)
Children, current; mean:
2.5 ng/mL
Children (age 12-19)
Sensitization (any slgE >0.35
kU/L)
IQR increase: 0.92 (0.66,1.28)
Eczema
MoBa
Granum et al. (2013)
Maternal
0-3 day post-delivery;
median: 0.3 ng/mL
From birth to age 3
Eczema and itchiness or doctor-
diagnosed atopic eczema:
No significant association (data
not shown)
Impinen et al. (2019)
Maternal mid-
pregnancy; median
(IQR): 0.7(0.5-0.9)
ng/mL
From birth to age 7
Ever: 1.09(0.90,1.31)
Current: 1.06 (0.83,1.36)
Hokkaido
Goudarzi et al. (2016)
Maternal, gestational
week 28-32; median
(IQR): 0.3 (0.2-0.4)
Children (age 4)
Ever:
Q2: 0.953 (0.658, 1.38)
Q3: 0.910 (0.623, 1.32)
Q4: 0.917 (0.626, 1.34)
Trend p = 0.618
Okada et al. (2014)
Children (age 1 or 2)
Ever:
Q2 0.82 (0.60, 1.13)
Q3 0.69 (0.50, 0.95)
Q4 0.79 (0.57, 1.08)
Trend p = 0.08
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Reference
Exposure
measurement timing
and concentration
Hypersensitivity
measu rement
timing
PFHxS OR (95% Cl)a or as
specified
Smit et al. (2015)
Maternal, gestational
week 24
Children (age 5-9)
Ever: 1.03 (0.86,1.24)
Current: 0.93 (0.73,1.20)
Chen et al. (2018a)
Cord blood; median
(IQR): 0.2 (0.2-0.2)
ng/mL
Children (age 2)
Ever:
1.08 (0.62,1.85) per log unit
increase
Q2 1.25 (0.74, 2.12)
Q3 1.15 (0.68, 1.94)
Q4 1.14 (0.67, 1.94)
Trend p = 0.73
Females only
Q2 1.43 (0.62, 3.30)
Q3 1.29(0.55, 2.99)
Q4 2.30 (1.03, 5.15)
Trend p = 0.06
Impinen et al. (2018)
Cord blood; median
(IQR): 0.2 (0.2-0.3)
ng/mL
From birth to age 10
0-2 years of age
1.06(0.89, 1.26)
Ever in 10 years
1.00 (0.67,1.49)
Manzano-Salgado et al. (2019)
Maternal (1st trimester),
median (IQR): 0.6 (0.4-
0.8) ng/mL
Age 1.5-7
Ever eczema
RR: 0.95 (0.86, 1.05)
Kvalem et al. (2020)
Child (age 10); median
(IQR): 1.3 (0.9) ng/mL
Child (age 10)
Ever doctor diagnosed:
RR: 1.00(0.98, 1.01)
Child (age 10-16)
Ever between 10 and 16 years
RR: 0.79 (0.34, 0.99)
Child (age 16)
Current (last 12 months)
RR: 0.78 (0.60, 1.02)
Timmermann et al. (2017)
Maternal, gestational
week 34-36; median
(IQR): 4.5 (2.2-8.3)
Children (age 13)
1.32 (1.08,1.62)
Children (age 5)
Children (age 13)
0.92 (0.70-1.22)
Child (age 5); median
(IQR): 0.6(0.4-0.9)
Children (age 13)
No MMR: 1.27(0.16, 10.15)c
Yes MMR: 0.80 (0.53, 1.20)
Interaction p = 0.66
aAII estimates are presented as OR (95% CI) for the odds of the outcome per two-fold increase in PFHxS
concentration unless otherwise stated.
bResults provided broken down by MMR vaccination status; yes (n = 537) or no (n = 22) when provided; some
results were not split by MMR vaccination status.
Bold font indicates p < 0.05.
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Animal Studies
Animal toxicity studies examining the effects of PFHxS on the immune system include two
[high confidence) short-term oral exposure studies performed in Sprague Dawley rats, fNTP.
2018a: 3M. 2000b] and one (medium confidence due to lack of results presentation) subchronic
oral exposure study performed in Crl:CDl mice fChang etal.. 20181: the study details are provided
in Table 3-15. It should be noted that none of the studies in the database were immunotoxicity
specific studies, but rather short-term or subchronic studies that focused on reproductive
endpoints but also measured general immune-related endpoints. IPCS guidance states that a 28-day
exposure period, such as those in the three studies in the evidence base, are adequate to elicit an
immune response flPCS. 20121. The immune-relevant endpoints evaluated in these studies include
immune hematology (i.e., blood leukocyte counts), histopathology, and organ weights (i.e., bone
marrow, lymph nodes, spleen), which may inform sensitization and allergic response and
autoimmunity, categories of immunotoxicity described in guidance from the International
Programme on Chemical Safety (IPCS. 20121.7 Studies were separately evaluated for each of these
endpoints; however, the overall confidence rating was the same regardless of endpoint (see Figure
3-16; for study details please see Table 3-15 and HAWC).
7IPCS guidance notes that "the dataset[s] for most chemicals is unlikely to contain all the data on all the
described endpoints" (IPCS. 20121.
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Reporting quality
Allocation
Observational bias/blinding
Confounding/variable control
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Results presentation
Endpoint sensitivity and specificity
Overall confidence
Legend
Good (metric) or High confidence (overall)
+ j Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
NRj Not reported
Figure 3-16, Study evaluation results of PFHxS animal toxicity studies with
immune-related endpoints. For additional details see HAWC link.
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Table 3-15. Animal study details
Study
Experimental
model
Exposure route
Exposure doses
Duration
Immune endpoint(s)
3M (2000b)
Male and Female
SD rats
Oral Gavage
0, or 10 mg/kg-d
28 d
Total immune cell counts3
Histopathology, Organ Weights
Chang et al. (2018)
Male and Female
CD-I Mice
Oral Gavage
0, 0.3,1, or 3
mg/kg-d
F0: Males: dosing started 14 d prior to
cohabitation for a total of 42 d until
scheduled to be euthanized.
Females: dosing started 14 d prior to
cohabitation and continuing through
mating, gestation, and lactation. F0 dams
were euthanized on lactation d 22 (LD22)
which was 1 d post-last dose.
Fl: Mice were exposed in utero and via
lactation. After weaning at postnatal d 22,
pups were directly dosed with PFHxS for an
additional 14 d at the same respective
maternal doses.
Total Leukocyte counts'5
Histopathologyc
Organ Weights
NTP (2018a)
Male and Female
SD rats
Oral Gavage
Males: 0, 0.625,
1.25, 2.5, 5 or 10
mg/kg-d
Females: 0, 3.12,
6.25, 12.5, 25 or 50
mg/kg-d
28 d
Total immune cell counts
Histopathology
Organ Weights
aTotal immune cell count included detailed counts of immune cells, e.g., basophil, eosinophil counts.
bTotal leukocyte count does not include detailed counts of immune cells.
cData not shown.
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Immune hematology
A summary of the immune hematology outcomes can be found in Figure 3-17. Briefly, of the
three studies that examined immune outcomes, two 3M r2000bl and NTP f2018al performed a
complete detailed analysis of blood leukocyte counts including basophils, eosinophils, leukocytes,
lymphocytes, monocytes, and neutrophils, while Chang etal. f20181 reported only total blood
leukocyte counts. 3M f2000bl and Chang etal. f20181 reported no statistically significant changes
in white blood cell counts in response to PFHxS exposure while NTP observed a statistically
significant decrease (p < 0.05] in eosinophil counts at the 10 mg/kg-day dose in male but not in
female SD rats. However, there were no other statistically significant changes in immune
hematology parameters, and the inconsistency in findings across the two rat studies is not
explained by dose or duration of exposure, or rat strain.
Endpoint Name
Study Name
Study Design
Animal Description
Trend Test Result
Basophil Count (BASO)
3111,2000,3931194
28 Day Oral
Rat. Crl:CdBr(+)
not reported
Rat, Crl:Cd Br(X)
not reported
NTP, 2018,4309363
28 Day Oral
Rat, Sprague-Dawley ( )
not significant
Rat. Sprague-Dawley (5)
not significant
Eosinophil Count (EO)
3M.2000, 3981194
28 Day Oral
Rat, Crl:Cd Br (J)
not reported
Rat, Crl:Cd Br (J)
not reported
NTP, 2018,4309363
28 Day Oral
Rat. Sprague-Dawley (-)
not significant
Rat, Sprague-Dawley (j)
significant
Leukocytes, Total
3M, 2000, 3981194
28 Day Oral
Rat, Crl:Cd Br (J)
not reported
Rat. Crl:CdBr(;)
not reported
NTP, 2018,4309363
28 Day Oral
Rat, Sprague-Dawley (2)
not significant
Rat, Sprague-Dawley (;?)
not significant
Lymphocyte Count (LYMPH)
3M, 2000, 3981194
28 Day Oral
Rat. Crl:Cd Br (r)
not reported
Rat, Crl:Cd Br(")
not reported
NTP. 2018,4309363
28 Day Oral
Rat, Sprague-Dawley (I)
not significant
Rat. Sprague-Dawley (_')
not significant
Monocyte Count (MONO)
3M.2000, 3981194
28 Day Oral
Rat, Crl:Cd Br ( J)
not reported
Rat, Crl:Cd Br (-')
not reported
NTP, 2018,4309363
28 Day Oral
Rat. Sprague-Dawley ( )
not significant
Rat, Sprague-Dawley (!j
not significant
Neutrophils
3M, 2000,3981194
28 Day Oral
Rat, CrlrCd Br (})
not reported
Rat, Crl:Cd Br (-5)
not reported
NTP. 2018.4309363
28 Day Oral
Rat. Sprague-Dawley (-¦)
not significant
Rat, Sprague-Dawley (-")
not significant
9 Dose
A Significant Increase
V Significant Decrease
0,1
•—•—•—• w
T
10
100
Dose (mgfkg-day)
Figure 3-17. Summary of PFHxS immune hematology results. Figure displays
the high and medium confidence studies included in the analysis. For additional
details see HAWC link
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Histopathologv
All three studies, 3M f2000bl. NTP f2018al. and Chang etal. f20181. performed histological
analyses of immune organs and tissues, including bone marrow, lymph nodes, spleen, and thymus.
All three studies reported that they found no PFHxS-related histological abnormalities in the
immune organs and tissues that they examined although specific results were not reported.
Organ weights
All three studies, 3M (2000b). NTP (2018a). and Chang etal. (20181. measured thymus and
spleen weights of control and exposed animals, and no PFHxS-related effects were observed.
Mechanistic Evidence and Supplemental Information
Most of the mechanistic evidence available relates most closely to potential sensitization or
allergic response outcomes. Specifically, five studies examined mechanistic endpoints related to
hypersensitization in the human studies. None of the five studies reported significant associations
between PFHxS and IgE (Timmermann etal.. 2017: Stein etal.. 2016b: Zhu etal.. 2016: Ashley-
Martin etal.. 2015: Dong etal.. 20131. Among asthmatics in the Taiwan population where an
association was observed with asthma, increases in eosinophilic cationic protein concentration
were significantly associated (p = 0.004) with increasing PFHxS concentration fDong etal.. 20131.
In addition, one study examined cord blood gene expression in relation to PFHxS levels and found
that gene changes associated with PFHxS tracked very well with a set of 27 gene changes associated
with common cold episodes (Pennings etal.. 20161: however, changes with PFHxS tracked very
poorly with a second set of 26 gene changes associated with rubella titers, and the relevance of
these gene changes to immune function in general, or antibody responses in particular, remains
unknown. No mechanistic evidence from animal, in vitro, in silico, or other evidence streams was
identified.
Evidence Integration
Human studies provide moderate evidence for immune system effects following exposure to
PFHxS (see Table 3-16). Specifically, increased serum levels of PFHxS correlated with decreased
antibody responses were observed in most exposure-outcome timing combinations in multiple
medium confidence studies, although most results were imprecise (i.e., not statistically significant).
While variability in response by age of exposure and outcome measure (vaccine type) as well as
timing of vaccinations (initial and boosters) resulted in some uncertainty, decreases (generally
between 5% and 10%) in antibody concentration per doubling of PFHxS concentration were
observed with reasonable consistency across multiple well-conducted studies. In addition, higher
odds of infectious disease or symptoms with higher PFHxS concentrations were observed in four of
seven available studies, which is coherent with the immunosuppression observed in antibody
response studies. There are remaining sources of uncertainty in the immunosuppression evidence,
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including potential confounding by other PFAS and imprecision of some effect estimates. The
evidence for sensitization or allergic response was generally inconsistent, but there was some
evidence of an association with asthma incidence. A strong positive association with doctor-
diagnosed asthma within the last year was observed in one medium confidence study, and this was
considered the most specific outcome measure available across the set of studies. However, unlike
the evidence on infectious disease, it is unclear how this finding might relate to the evidence
supporting immunosuppression, and without additional support or mechanistic understanding
(mechanistic information was predominantly null apart from a biomarker coherent with the
development of asthma observed in this same study) it does not support a stronger strength of
evidence determination. Other studies of sensitization and allergic response were inconsistent.
Studies of autoimmunity were not available.
Animal studies provide indeterminate evidence for immune system effects following
exposure to PFHxS (see Table 3-16). There were no immunotoxicity-specific animal studies in the
database, but rather general toxicity or developmental toxicity studies that included immune-
related endpoints. As a result, the immune endpoints evaluated in the animal studies were less
sensitive and less informative for hazard identification than the endpoints evaluated in the human
studies available in the database. No reliable findings of PFHxS-related immune effects were
observed in high and medium confidence studies in animals exposed to PFHxS.
Taken together, the currently available evidence indicates that PFHxS likely causes
immune toxicity in humans given sufficient exposure conditions8. This conclusion is based on
epidemiology evidence of an association between PFHxS exposure and immune effects—
specifically, immunosuppression, driven primarily by studies of antibody response following
vaccination, with median PFHxS blood concentrations in children of 0.3-2.5 ng/mL. Despite
imprecision in the results, the antibody results present a generally consistent pattern of findings
that higher prenatal and childhood concentrations of PFHxS were associated with suppression of at
least one measure of the anti-vaccine antibody response to common vaccines, and coherent findings
from more limited evidence of associations between PFHxS exposure and higher odds of infectious
disease. These associations were observed despite poor study sensitivity. While clinical adversity of
fairly small changes in antibody concentrations is not established, one study reported higher odds
for lack of protection from diphtheria, and there is potential for a subset of people to be more
severely affected. Some uncertainty remains resulting from variability in the response by age of
exposure and outcome measures as well as from timing of vaccination (initial and boosters) and the
potential for confounding by other PFAS.
8 The "sufficient exposure conditions" are more fully evaluated and defined for the identified health effects
through dose-response analysis in Section 5.
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Table 3-16. Evidence profile table for PFHxS immune effects
Evidence Stream Summary and Interpretation
Evidence Integration
Summary Judgment
Evidence from studies of exposed humans (see Immune Human Studies Section)
Studies and
interpretation
Factors that increase
certainty
Factors that decrease
certainty
Summary and key findings
Evidence stream
judgment
®©o
Evidence indicates (likely)
Based on generally
consistent evidence of
reduced antibody response
to vaccination at median
blood concentrations of
0.2-0.6 ng/mL
Human relevance:
Evidence comes from
epidemiological studies
(see Immune Human
Studies Section)
Cross-stream coherence:
NA: animal evidence is
indeterminate
Antibody Response to
Vaccine
• 7 medium
confidence studies
• 3 low confidence
studies
• Consistency -
Evidence is generally
consistent in the
direction of
association across
vaccine type, timing
of vaccination, and
age at antibody
response
measurement
• Low risk of bias in
studies in children
• Magnitude of effect -
Large effect size
observed in most
studies despite
limited sensitivity
• Potential for
residual
confounding across
PFAS
• Imprecision of
most findings
Studies in children
observed inverse
associations between
PFHxS exposure and
antibody levels following
vaccination in at least
some analyses. While not
all results were statistically
significant, the direction of
association was generally
consistent across studies
and timing of exposure
and outcome measures.
®©o
Moderate
Generally consistent
evidence for
immunosuppression with
PFHxS exposure based on
lower antibody response
in multiple medium
confidence studies,
supported by coherent
but limited results for
infectious diseases [Note:
the evidence of
hypersensitivity, based a
single well-conducted
study of asthma with
inconsistent findings
across other studies with
less robust outcome
measures, did not
contribute to this
judgment].
Infectious Disease
• 6 medium
confidence study
• 6 low confidence
studies
• Despite potential
limited sensitivity, six
studies observed a
significant positive
association for at
least one outcome
• Unexplained
inconsistency
• High risk of bias
from potential
outcome
misclassification in
low confidence
studies
2 medium and 3 low
confidence studies
reported higher odds of
infectious disease or
symptoms with higher
PFHxS exposure, including
total infectious disease,
lower respiratory infection,
throat infection,
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Evidence Stream Summary and Interpretation
Sensitization or allergic
response
• 13 medium
confidence studies
• Magnitude of effect -
Large effect size in
the only study of
asthma incidence
• Exposure-response
gradient observed for
asthma incidence in 1
study with the most
reliable outcome
measure
• Biological plausibility
- mechanistic change
coherent with
asthma in the only
study of asthma
incidence
Potential for
residual
confounding across
PFAS
Unexplained
inconsistency-
Inconsistent
direction of
associations across
studies for all
hypersensitivity
outcomes (with
predominantly null
findings)
pseudocroup, and
gastroenteritis
1 well-conducted study
reported a clear positive
association with asthma
incidence and eosinophilic
cationic protein. Of 11
other studies of asthma,
only four reported higher
odds of asthma in at least
one subpopulation but
were based on "current"
or "ever" asthma
definitions, which are less
specific. Results for
allergies/allergic
sensitization, and dermal
allergic measures had
inconsistent findings.
Evidence from In vivo Animal Studies (see Immune Animal Studies Section)
Hematology
• 2 high confidence
studies
• One medium
confidence study
Histopathology
• 2 high confidence
studies
• Low risk of bias
• Low risk of bias
Endpoints
considered
nonspecific and
insensitive
indicators of
immune function
Decreased eosinophil
counts in 1 study (NTP,
2018a); however, there
were no other statistically
significant changes in
immune hematology
parameters and this
finding alone is not
considered adverse.
No PFHxS-induced effects
observed for
histopathology.
Evidence stream
judgment
ooo
Indeterminate
[noting that the immune
endpoints evaluated in
the available animal
studies are considered
insensitive or nonspecific
indicators of immune
function.!
Evidence Integration
Summary Judgment
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Evidence Stream Summary and Interpretation
Evidence Integration
Summary Judgment
• 1 medium
confidence study
Organ weights
• 2 high confidence
studies
• 1 medium
confidence study
• Low risk of bias
No PFHxS-induced effects
observed for organ
weights.
ated Salts
C: cohort, CC: case control, CS: cross sectional.
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3.2.3. Developmental Effects
This section describes studies of PFHxS exposure and potential in utero and perinatal
effects or developmental delays, as well as effects attributable to developmental exposure. The
latter includes all studies for which exposure is limited to gestation and/or early life. Given that
some endpoints examined here, such as spontaneous abortion and preterm birth, could be driven
by either female reproductive or developmental toxicity, these endpoints are also discussed in the
context of coherence in Section 3.2.7 on Female reproductive effects. As such, this section has some
overlap with evidence synthesis and integration summaries for other health systems for which
studies evaluated the effects of developmental exposure (see Sections 3.2.5, 3.2.2, 3.2.7, 3.2.8, and
on potential Hepatic, Endocrine, and Female and Male Reproductive Effects, respectively).
Human Studies
The epidemiologic studies of possible developmental effects of PFHxS evaluate the
following endpoints: fetal and childhood growth restriction, spontaneous abortion, and gestational
duration (i.e., preterm birth and gestational age). Given that many of these endpoints could be
driven by either female reproductive or developmental toxicity, some are also discussed in the
context of coherence in the female reproductive effects section (see Section 3.2.7). The evidence
informing specific endpoints is discussed and synthesized below; however, the hazard conclusion
was determined at the level of developmental effects for the group of endpoints.
Study evaluation considerations
As detailed in the PFAS Systematic Review Protocol (see Appendix A), multiple outcome-
specific considerations informed domain-specific ratings and overall study confidence. For the
Confounding domain, downgrading of studies occurred when key confounders of the fetal growth
and PFAS relationship, such as parity, were not considered. Some pregnancy hemodynamic factors
related to physiological changes during pregnancy were also considered in this domain as potential
confounders (e.g., glomerular filtration rate and blood volume changes over the course of
pregnancy) because these factors may be related to both PFHxS levels and the developmental
effects examined here. Irrespective of study design, more confidence was placed in the
epidemiologic studies that adjusted for glomerular filtration rate in their regression models or if
they limited this potential source of confounding by sampling PFAS levels earlier in pregnancy. An
additional source of uncertainty was the potential for confounding by other PFAS (and other co-
occurring contaminants). Although scientific consensus on how best to address PFAS co-exposures
remains elusive, it was considered in the study quality evaluations and as part of the overall weight
of evidence determination (see Appendix C for additional discussion of these issues).
For the Exposure domain, all the available studies analyzed PFAS in serum or plasma using
standard methods. Given the estimated long half-life of PFHxS in humans (range: 4.7 to 8.5 years;
see Section 3.1.4.), samples collected during all three trimesters (and shortly after birth) were
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considered adequately representative of the most critical in utero exposures for fetal growth and
gestational duration measures. Many of the cross-sectional studies relied on umbilical cord
measures collected shortly after birth. Exposure measures collected close to or concurrently with
outcome ascertainment were considered etiologically relevant and acceptable for these
developmental endpoints; thus, exposure measurement ratings were not downgraded for timing of
measurement The postnatal anthropometric studies were evaluated with consideration of fetal
programming mechanisms (i.e., Barker hypothesis) where in utero perturbations, such as poor
nutrition, can lead to developmental effects such as fetal growth restriction and ultimately adult-
onset metabolic-related disorders and related complications (see more on this topic in De Boo and
Harding f20061 and Perngetal. f20161 and other PFAS syntheses for potential cardiometabolic
disorders in Section 3.2.6). There is some evidence that birth weight deficits can be followed by
increased weight gain that may occur especially among those with rapid growth catch-up periods
during childhood (Perng etal.. 2016). Therefore, the primary critical exposure window for
measures of postnatal (and early childhood) weight and height change is assumed to be in utero for
study evaluation purposes, and studies of this outcome were downgraded in the exposure domain if
exposure data were collected later during childhood or concurrently with outcome assessment (i.e.,
cross-sectional analyses).
Studies were also downgraded for study sensitivity, for example, if they had limited
exposure contrasts or small sample sizes, since this can impact the ability of studies to detect
statistically significant associations that may be present (e.g., for sex-stratified results). In the
outcome domain, specific considerations address validation and accuracy of specific endpoints and
adequacy of case ascertainment for some dichotomous (i.e., binary) outcomes. For example,
birthweight measures have been shown to be quite accurate and precise, while other fetal and early
childhood anthropometric measures may result in more uncertainty. Mismeasurement and
incomplete case ascertainment can affect the accuracy of effect estimates by impacting both
precision and validity. For example, some spontaneous abortion studies were downgraded for
participant selection due to incomplete case ascertainment given that some pregnancy losses go
unrecognized early in pregnancy including before participants would be enrolled. This incomplete
ascertainment, referred to as left truncation, can result in bias toward the null if ascertainment of
fetal loss is not associated with PFHxS exposures (i.e., nondifferential). In some situations where
there is a true association with PFHxS, differential loss is possible, possibly causing a bias away
from the null, and can manifest as an apparent protective effect Fetal and childhood growth
restriction were examined using several endpoints including low birth weight, small for gestational
age (SGA), ponderal index [i.e., birth weight grams)/birth length (cm3) x 100], abdominal and head
circumference, as well as upper arm/thigh length, mean height/length, and mean weight either at
birth or later during childhood. When sufficient high and medium confidence evidence is available
for a set of related endpoints, the developmental effects synthesis is largely focused on the higher
quality endpoints (i.e., classified as good in the outcome domain).
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Overall, mean birth weight and birth weight-related measures are considered very accurate
and were collected predominately from medical records; therefore, more confidence was placed in
these developmental endpoints in the outcome domain judgments. Some of the adverse birth
weight endpoints of interest examined here included fetal growth restriction endpoints based on
birth weight such as mean birth weight (or variations of this endpoint such as standardized
birth weight z-scores), as well as binary measures such as SGA (e.g., lowest decile of birth weight
stratified by gestational age and other covariates) and low birth weight (i.e., typically <2,500 grams;
5 pounds, 8 ounces) births. Sufficient details on the SGA percentile definitions and stratification
factors as well as sources of standardization for z-scores were necessary to be classified as good for
these endpoints in this domain. In contrast, other measures of fetal growth that are subject to
greater measurement error (e.g., head circumference and body length measures such as ponderal
index) were given a rating of adequate fShinwell and Shlomo. 20031. These sources of
measurement error are expected to be nondifferential with respect to PFHxS exposure status and,
therefore, would not typically be a major concern for risk of bias but could impact study sensitivity.
Gestational duration measures were presented as either continuous (i.e., per each
gestational week) or binary endpoints such as preterm birth (typically defined as gestational age
<37 weeks). The potential for measurement error can complicate accurate estimates of gestational
age and may decrease study sensitivity related to some of these endpoints especially when based
on recall of last menstrual period alone. However, many of the studies were based on ultrasound
measures early in pregnancy, which should increase the accuracy of estimated gestational age and
the ability to detect associations that may be present Studies were downgraded if based solely on
last menstrual period and more certainty was anticipated for studies using a combination of
measures with comparisons of any differences. Any sources of error in the classification of these
endpoints should be nondifferential with respect to PFHxS exposure and, therefore, would not be
considered a major concern for risk of bias, but could impact precision and study sensitivity.
Anogenital distance (AGD) is an externally visible marker that has been shown in animal
studies to be a sensitive indicator of prenatal androgen exposure (lower androgen levels associated
with decreased AGD, and the reverse). It is associated with other reproductive tract abnormalities,
including hypospadias and cryptorchidism in human and animal males (Liu etal.. 2014:
Sathvanaravana et al.. 2010: Salazar-Martinez etal.. 2004): the potential adverse consequences in
females are less well defined. In boys, measures can be taken from the center of the anus to the
posterior base of the scrotum (ASD) or from the center of the anus to the cephalad insertion of the
penile (APD). In girls, there are two possible measures, the anoclitoris distance (ACD) and the
anofourchette distance (AFD). The primary outcome-specific criteria for this outcome are the use of
clearly defined protocols for measurement, ideally multiple measures of each distance (averaged),
and minimal variability in the age of participants at measurement
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Growth restriction - fetal growth
Developmental Epidemiologic Studies
Sixty-one epidemiological publications (across 58 different studies) examining PFHxS
exposures in relation to developmental endpoints were identified in the literature search. Several
studies examined multiple endpoints that are captured in separate sub-sections below. This
included the following: 12 studies on postnatal growth, 19 studies on gestational duration, 5 on
fetal loss, 4 on anogenital distance, 2 studies on birth defects, and 42 publications (across 39
different studies) that examined fetal growth restriction.
Fetal Growth Restriction - Study Background
The heat map of 39 fetal growth restriction studies below does not include three
overlapping publications, such as the Woods etal. (2017) publication from the same study
population (Health Outcomes and Measures of the Environment cohort) as Shoaffetal. (2018) (see
Figures 3-18 and 3-19). For consistency, birth outcomes measures reported in (Manzano-Salgado
etal.. 2017al were preferred to in utero growth estimates in the Costa etal. f20191 study from the
same Environment and Childhood - Infancia y Medio Ambiente (INMA) birth cohort. The smaller
population subset from the Bierregaard-Olesen etal. f20191 study is from the same Aarhus birth
cohort as Bach etal. f20161. Given disparate results shown below in this subset versus the whole
cohort for head circumference and birth length, results from the full study population in Bach etal.
(2016) are given precedent However, the Bierregaard-Olesen etal. (2019) provide additional sex-
specific data not examined in Bach etal. (2016). Difference in results for these endpoints are
highlighted in the syntheses below but only one study is plotted for each endpointto aid the
evaluation of consistency across studies. Five of the remaining 39 fetal growth studies fMaekawa et
al.. 2017: Alkhalawi etal.. 2016: Lee etal.. 2016: Lee etal.. 2013: Monrovetal.. 20081 are not
included in the synthesis further as they were classified as uninformative largely due to critical
study deficiencies in some risk of bias domains (e.g., confounding) or multiple domain deficiencies.
Birth Weight - Background of Studies
As shown in Figure 3-18 and Table 3-17, there were 34 informative studies that examined
birth weight measures in relation to PFHxS exposures. This included 13 studies that examined
PFHxS in relation to continuous standardized birth weight scores. Ten of these 13 reported
standardized measures along with mean birth weight differences in relation to PFHxS. Three
(Gardener etal.. 2021: Gross etal.. 2020: Xiao etal.. 2019) of the 13 studies reported only
standardized birthweight measures, with Gardener et al. (2021) not plotted below with the others
given an atypical, dichotomized effect estimate with different scaling.
Of the 31 epidemiological studies with mean birth weight data, four f Marks etal.. 2019a:
Ashlev-Martin etal.. 2017: Lind etal.. 2017: Maisonet etal.. 20121 only reported sex-specific
findings, including a study in boys f Marks etal.. 2019al and girls fMaisonetetal.. 20121 from the
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1 ALSPAC study (see Figure 3-19). Fifteen different studies examined mean birth weight differences
2 across the sexes 14 each in boy and girls. Among the 27 studies with results in the overall
3 population, three studies fEick etal.. 2020: Gao etal.. 2019: Cao etal.. 20181 reported results based
4 only on categorical data.
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Alkhalawi et al., 2016, 3859818
Ashley-Martin, 2017. 3981371
Bach at al., 2016, 3981534
Buck Louis. 2018, 5016992
Callan. 2016. 3858524
Cao et al-, 2018, 508O197
Chang el al., 2022. 9959688
Chen. 2021. 7263985
Eick at al., 2020, 7102797
Gao et al., 2019. 5387135
Gardener. 2021, 7021199
Gross et al., 202O, 7014743
Gyllenhammar et al., 2018. 4238300 -
Hamm, 2010; 1290814
Hj«trnits»|av, 2020, 5880849
Kashino. 2020. 6311832
Kwon, 2016. 3858531
Lee. 2013. 3859850 -
Lee. 2016. 3981528
Lenters, 2016, 5617146
Li, 2017. 3981358
Lind. 2017. 3858512
Luo et al., 2021, 9959610
Maekawa, 2017. 4238291
Maisonot ct al., 2012, 1332465
Manzano-Saigado at al., 2017, -4238465
Marks, 2019. 5081319
Meng Gt al., 2018; 4829851
Monroy, 2008, 2349575
Sagiv, 2018. 4238410
Shi, 2017. 3827535
ShoalT et al., 2018. 4619944
Starling. 2017. 3858473 -J
Valvi et al., 2017, 3983872 H
Wikstrom. 2020. 6311677 -]
Workman at al., 2019, 5387046
Xiao et al.. 2020. 5918609
Xu, 2019. 5381338 -
Yao et al.. 2021, 9960202
s (overall)
•» 'I Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
^9 Critically deficient (metric) or Uninformative (overall
Figure 3-18. Study evaluation results for 39 epidemiological studies of birth
weight and PFHxS. For additional details see H.AWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
39 Perinatal Studies of Mean Birth Weight included in study quality evaluation
/ \
\
3 Overlapping Study Mean
Birth Weight Studies
31 Included Mean
Birth Weight Studies
5 Uninformative Mean
Birth Weight Studies
27 Studies with Overall
Population Results
14 Studies with Sex-Specific
Results (4 studies examined
either only boys and/or girls)
27 Studies included in
Meta-Analysis that had
Overall Population Results
(boys and girls combined)
11 High Confidence Studies
10 Medium Confidence Studies
6 Low Confidence Studies
Confidence
6 High Confidence Studies
6 Medium Confidence Studies
3 Low Confidence Studies
Confidence
based on continuous
exposure measures
Figure 3-19. Perinatal studies of birth weight measures and subsets included
in different evaluations.
Birth weight - Mean Differences - Background
Twenty-five of the included 31 mean birth weight studies were prospective birth cohorts,
and six were cross-sectional studies fXu et al.. 2019: Gvllenhammar et al.. 2018: Li et al.. 2017b: Shi
etal.. 2017: Callan etal.. 2016: Kwon etal.. 20161 (see Figures 3-20 and 3-21). Five of these six
studies relied on umbilical cord blood measures fXu etal.. 2019: Cao etal.. 2018: Li etal.. 2017b: Shi
etal., 2017: Kwon etal., 20161. and one collected PFHxS blood samples in infants 3 weeks following
delivery f Gvllenhammar etal.. 20181. Twenty-four studies had maternal blood measures that were
sampled during trimesters one (Buck Louis et al.. 2018: Ashley-Martin etal.. 2017: LindetaL 2017:
Manzano-Salgado etal.. 2017al. two fHamm etal.. 20101. three fLuo etal.. 2021: Yao etal.. 2021:
Kashino etal.. 2020: Gao etal.. 2019: Valvi et al.. 2017: Callan etal.. 20161. or across multiple
trimesters fChang etal.. 2022: Chen etal.. 2021: Eick etal.. 2020: Hiermitslevetal.. 2020: Wikstrom
etal.. 2020: Marks etal.. 2019a: Workman etal.. 2019: Sagiv etal.. 2018: Shoaffetal.. 2018: Starling
etal.. 2017: Bach etal.. 2016: Lenters et al.. 2016: Maisonetetal.. 20121. The study by Meng et al.
(2018' pooled exposure data from two study populations, one that measured PFHxS in umbilical
cord blood and one that measured PFHxS in maternal blood samples collected in trimesters 1 and 2.
For comparability with other studies of mean birth weight, EPA only examined data from one
measure, such as umbilical cord or maternal serum concentrations, and when necessary, relied on
other related publications (e.g., Gvllenhammar I ("201711 or additional information or data provided
by study authors. When possible, EPA converted effect estimates that were based on continuous
PFHxS measures to a 1 ln-unit increase to enhance comparability across studies (see Figures 3-22,
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3-23, 3-24). These results employing a common unit of measurement were also used for the birth
weight meta-analysis conducted by EPA (see Appendix C for details on the methods employed).
Thirteen of the 31 mean birth weight studies were rated high in overall study confidence
fLuo etal.. 2021: Yao etal.. 2021: Eick etal.. 2020: Wikstrom etal.. 2020: Buck Louis etal.. 2018:
Sagivetal.. 2018: Shoaff etal.. 2018: Ashlev-Martin etal.. 2017: Lind etal.. 2017: Manzano-Salgado
etal.. 2017a: Starling et al.. 2017: Valvi etal.. 2017: Bach etal.. 20161. while 11 were rated medium
(Chang etal.. 2022: Chen etal.. 2021: Hiermitslev etal.. 2020: Kashino etal.. 2020: Gvllenhammar et
al.. 2018: Meng etal.. 2018: Li etal.. 2017b: Kwon etal.. 2016: Lenters etal.. 2016: Maisonetetal..
2012: Hamm etal.. 2010). and 7 were classified as low (Gao etal.. 2019: Marks etal.. 2019a:
Workman et al.. 2019: Xu etal.. 2019: Cao etal.. 2018: Shi etal.. 2017: Callan etal.. 20161 (see
Figure 3-18).
Of the 31 mean birth weight studies detailed in this synthesis, 13 studies fLuo etal.. 2021:
Wikstrom etal.. 2020: Marks etal.. 2019a: Gvllenhammar etal.. 2018: Meng etal.. 2018: Sagivetal..
2018: Shoaff etal.. 2018: Ashlev-Martin etal.. 2017: Li etal.. 2017b: Starling etal.. 2017: Valvi etal..
2017: Lenters etal.. 2016: Maisonet etal.. 2012) were considered to have good study sensitivity.
Ten studies (Chang etal.. 2022: Chen etal.. 2021: Eick etal.. 2020: Hiermitslev etal.. 2020: Buck
Louis etal.. 2018: Lind etal.. 2017: Manzano-Salgado etal.. 2017a: Bach etal.. 2016: Kwon etal..
2016: Hamm etal.. 20101 were classified as adequate and eight were deficient fYao etal.. 2021:
Kashino etal.. 2020: Gao etal.. 2019: Workman etal.. 2019: Xu etal.. 2019: Cao etal.. 2018: Shi et
al.. 2017: Callan et al.. 2016).
Birth weight - Mean Difference Results (in Grams) in Overall Population
Overall, 14 of the 27 different epidemiological studies that examined associations in the
overall population (i.e., both male and female neonates combined) detected some deficits in relation
to PFHxS exposures (see Figures 3-20, 3-21, 3-22, and Table 3-17). This included five fBuck Louis et
al.. 2018: Shoaff etal.. 2018: Manzano-Salgado etal.. 2017a: Starling etal.. 2017: Bach etal.. 20161
out of 11 high confidence studies, five (Chang etal.. 2022: Hiermitslev etal.. 2020: Gvllenhammar et
al.. 2018: Li etal.. 2017b: Kwon etal.. 2016) out of 10 medium and four (Gao etal.. 2019: Xu etal..
2019: Cao etal.. 2018: Callan et al.. 2016) out of six low confidence studies. In contrast, four studies
reported increased birth weight with PFHxS exposures while eight other studies were null. For
example, the high confidence study by Eick etal. f20201 reported non-significant increased birth
weight across PFHxS tertiles ((3 range: 75.7 to 82.2 g) relative to tertile 1. The medium confidence
study by Chen etal. f20211 reported a small increased mean birth weight based on continuous
exposures ((3 = 27.6 g; 95%CI: -64.7,119.9 per ln-unit increase) along with mixed results based on
categorical PFHxS exposures ((3 range: -46 to 26 g). The high confidence Manzano-Salgado etal.
(2017a) study showed consistent but non-monotonic birth weight decreases across all three upper
quartiles ((3 range: -30 to -65 g), but a relatively small deficit per each unit increase ((3= - 12.4 g;
95%CI: -46.2, 21.4). The latter results were indicative of deficits seen in the five high confidence
studies ((3 range: -12 to -22 gper each ln-unit increase).
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Birth weight deficits detected in the five medium confidence studies were larger ((3 range: -
30 to -93 g per each ln-unit increase). For example, the medium confidence study by Hiermitslev et
al. f20201 reported a large birth weight deficit ((3= -93 g; 95%CI: -230, 44 per each ln-unit
increase). Two other medium confidence studies fGvllenhammar etal.. 2018: Kwon etal.. 20161
reported birth weight decreases consistent in magnitude ((3 range: -53 to -60 g per each ln-unit
increase). The medium confidence study by Chang etal. f20221 reported a non-significant deficit
per each ln-unit increase ((3= -20 g; 95%CI: -84, 45) but larger results for PFHxS quartiles 2 ((3= -
36 g; 95%CI: -154, 83) and 4 ((3= -54 g; 95%CI: -173, 66). The medium confidence study by
Kashino etal. (2020) reported a null association with PFHxS and mean birth weight ((3= -1.3 g;
95%CI: -26.3, 23.6 per each ln-unit increase). They did show large differences in multiparous
participants ((3= -81.2 g; -122.3, -40.1 per each ln-unit increase) but not for primiparous
participants ((3= -2.2 g; -46.2, 41.7 per each ln-unit increase).
Birth weight deficits detected in the two low confidence studies were consistent in
magnitude ((3 range: -72 to -76 g per each ln-unit increase). The low confidence study by Gao et al.
(2019) reported larger decreased birth weight in a non-monotonic fashion across PFHxS tertiles 2
((3= -154.1 g; 95%CI: -332.2, 24.0) and 3 ((3= -101.2 g; 95%CI: -275.5, 73.1). Across all confidence
levels, only one fCao etal.. 20181 of 11 studies with categorical data in the overall population
showed some evidence of exposure-response relationships ((3 range: -14 to -25 g across tertiles).
Birth Weight- Mean Difference- Overall Population Summary
In the overall population, there were consistent results of deficits across all study
confidence levels (5 of 11 high, 5 of 10 medium, and 4 of 6 low confidence studies). However, the
five high confidence studies showed consistently smaller deficits ((3 range: -12 to -22 g per each
unit increase) compared to the five medium ((3 range: -20 to -93 g) and two low ((3 range: -72 to -
76 g) confidence studies. Although the majority of low confidence studies observed larger birth
weights in association with PFHxS exposure, the estimates were consistently imprecise, and the
identified methodological limitations preclude further interpretation in that subset. There was
limited evidence of exposure-response relationships based on categorical data, but the magnitude
of changes in those studies showing deficits ranged from -25 to -101 grams for the highest quantile
(compared to the lowest quantile) were comparable to those results ((3 range: -12 to -93 grams per
each ln-unit increase) based on the continuous exposure expressions shown above.
Limited patterns were evident as study sensitivity, exposure levels and contrasts and other
study design elements were not explanatory for null or inverse associations detected across the
birth weight studies. The birth weight deficits in the overall population may be influenced by
hemodynamic changes during pregnancy related to exposure assessment timing, as only four of the
fourteen were based on early biomarker sampling.
M eta-Analysis of Mean Birth Weight Differences
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Twenty-eight studies were identified for possible inclusion into a meta-analysis of overall
population estimates (see Figure C-l and more details on the Methods in Appendix C) if they
provided results in the overall population or in both sexes which allowed combination to estimate
an overall population result. Three studies with PFHxS categorical data only fEick etal.. 2020: Gao
etal.. 2019: Cao etal.. 20181 were not included in the meta-analysis due to the lack of results on a
per continuous exposure increase. The remaining 27 studies (from 28 publications) include the
other 24 studies identified in the overall population section noted above as well as three additional
studies, which reported sex-specific data only on boys and girls individually (Ashley-Martin et al..
2017: Lind etal.. 20171. Another cohort (ALSPAC) reported results in girls (Maisonet et al.. 20121 in
one publication and boys f Marks etal.. 2019al in another and were combined for the meta-analysis.
Following scale conversions and re-expressions (to ln-unit) for some studies by U.S. EPA,
the meta-analysis of 27 studies showed negligible between-study heterogeneity (I2 = 0%), and a
small but statistically significant decrease in birthweight ((3=-7.7 g; 95% CI: -14.8, -0.5) per each
ln-unit PFHxS increase (see Figure 3-20). Statistically significant results comparable in magnitude
were also detected when restricted to just medium and high confidence studies ((3=-8.0 g; 95% CI:
-15.2, -0.7) and also to 23 studies that provided results based on some logarithmic transformation
((3= -6.5 g; 95% CI: -14.8, -0.5).
Mean birth weight deficits were detected only among the 12 high ((3= -6.8 g; 95% CI: -16.3,
2.8) and 11 medium ((3=-9.6 g; 95% CI: -20.8,1.6) confidence studies. The pooled effect in the low
confidence studies was null ((3=—1.5 g; 95% CI: -51.6, 48.7) and based upon far fewer studies (n =
4). Stratified mean birth weight deficits were also different based on studies with later sample
timing. The five studies that used umbilical cord samples or maternal samples after birth or
pregnancy samples had considerably larger deficits ((3= -28.3 g; 95% CI: -69.3,12.7) compared
with the 12 studies with sampling from early pregnancy ((3= -7.3 g; 95% CI: -16.0,1.4) or the ten
studies with sampling from mid- to late pregnancy ((3= -3.9 g; 95% CI: -17.7, 9.9).
Overall, the meta-analytical data showing a small change in mean birth weight per each ln-
unit change (i.e., a 2.7-fold increase in exposure in ng/mL within the range of observed exposures in
the study populations) support the main epidemiologic findings detailed above and provide some
limited evidence of an adverse effect on birthweight from maternal exposure to PFHxS (see
Appendix C for more detail and additional stratified analyses). The median exposure ranged from
0.16 to 10.36 ng/mL across the 27 studies with birth weight data in the meta-analysis. The pooled
birth weight estimates expressed here per each unit change are relatively small in magnitude are
expressed here per each unit change and could be larger depending on the range of exposures
within a particular study population or the range to which it is being extrapolated to. Although a
gradient across sample timing was not evident across all time periods, the pooled estimate in the
five studies with post-partum sample was much larger. In contrast to the late maternal sampled
studies, the associations in the early sampled studies were consistent in magnitude to the pooled
estimate across all studies as well as the combined medium and high confidence studies. Thus, while
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
133 some uncertainty remains on the potential impact due to pregnancy hemodynamics especially in
134 the later sampled studies, the overall combined results, the early sample timing studies as well as
135 the higher confidence (medium and high combined) studies do show a small association between
136 mean birthweight and PFHxS.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Table 3-17. Summary of 34 epidemiologic studies of PFHxS exposure and growth restriction measures
Author
Study location,
years
Sample
size3
Median
exposu re
(range)
in
ng/mL
Birth
weight
Birth
length
HC
SGA/
LBW
High Confidence Studies
Ashlev-Martin et al.
(2017)
Canada,
2008-2011
1,509
1.0
(0.3,
25.0)
0 Overall
+ Boys
-Girls
Bach et al. (2016):
Bierregaard-Olesen et al.
(2019)
Denmark,
2008-2013
1,507
0.5
(
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Author
Study location,
years
Sample
size3
Median
exposu re
(range)
in
ng/mL
Birth
weight
Birth
length
HC
SGA/
LBW
Shoaff et al. (2018)
USA,
2003-2006
345
1.5
(0.1-32.5)
- Overall
Starling et al. (2017)
CO, USA,
2009-2014
598
0.8
(0.1, 10.9)
- Overall
Valvi et al. (2017)
Denmark,
1997-2000
604
4.54
(N/A)
+ Overall/
Boys/Girls
- Overall/ Boys
0 Girls
+
OveralT/Boys*
0 Girls
Wikstrom et al. (2020)
Sweden,
2007-2010
1533
1.23
(N/A)
0 Overall/Boys
/Girls
0 SGA
Overall/Boys
¦f SGA Girls
Xiao et al. (2019)
Faroe Islands,
1994-1995
172
0.55
(0.1, 2.8)
Overall/Boys/
Girls
Overall/Boys/Girls*
Overall/Boys/
Girls*
Yao et al. (2021)
China, 2010-
2013
369
0.32
0 Overall
Medium Confidence Studies
Chang et al. (2022)
USA, 2014-2018
370
1.10
(
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Author
Study location,
years
Sample
size3
Median
exposu re
(range)
in
ng/mL
Birth
weight
Birth
length
HC
SGA/
LBW
Hiermitslev et al. (2020)
Greenland,
2010-2011;
2013-2015
266
1.15
(0.21,
7.87)
- Overall/Girls
+ Boys
0 Overall
+ Boys
-Girls
-Overall/Girls
0 Boys
0 Overall SGA
0 Overall LBW
Kashino et al. (2020)
Japan, 2003-
2009
1,591
0.3 (N/A)
0 Overall/Boys
/Girls
0
Overall/Boys/Girls
0
Overall/Girls-
Boys
Kwon et al. (2016)
S. Korea,
2006-2010
268
0.38
(0.11,
1.20)
- Overall
Lenters et al. (2016)
Ukraine/Poland/
Greenland,
2002-2004
1,321
1.56, 2.28
(0.45,
5.95)d
0 Overall
Li et al. (2017b)
China,
2013
321
3.87
(ND,
20.15)
- Overall/Boys
0 Girls
Maisonet et al. (2012)
United Kingdom,
1991-1992
422
1.6
(0.2-54.8)
- Girls*a
- Girls*a
Meng et al. (2018)
Denmark,
1996-2002
2,120
~1(N/A)
0
Overall/Girls
+ Boys
¦f LBW
^VLBW
Low Confidence Studies
Callan et al. (2016)
W. Australia,
2003-2004
98
0.33
(0.06,
3.3)
- Overall
- Overall
- Overall
Cao et al. (2018)
China,
2013-2015
337
0.09
0.03-0.31f
Overalla/Boysa
+ Girls
- Overall/
Boys
0 Girls
Gao et al. (2019)
China, 2015-
2016
132
0.24
(N/A)
- Overall
- Overall
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Author
Study location,
years
Sample
size3
Median
exposu re
(range)
in
ng/mL
Birth
weight
Birth
length
HC
SGA/
LBW
Gross et al. (2020)
USA, 2014
98
0.108
(N/A)s
- Overall/
Boys/Girls
Marks et al. (2019a)
England,
1991-1992
447
1.9
(0.5,
74.2)
-Boys
- Boysb
0 Boys
Shi et al. (2017)
China,
2012
170
0.16
(
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Study
Population
Overall Study
Design
Exposure
Regression
Exposure
Confidence
Window
Coefficient
Comparison
Regression coefficient
§ 6 [change in mean BWT (g)j
Buck L&jjs;
5016992
MCHD Fetal Gmwlh SIncjlHH
(2009-2013), United States, 2106
mothe'-infant pairs
(High
Cptiorl
(Prospective)
Trimester 1
-22,1
ln-unil (rig/ml)
increase
!
i—•—w
© 3 [change in mean BWT (g)> p<0.05
t-i 95% confidence interval
Manzano-Salgado INMA conot (2003-2008) 1202
et at.. 2017 mofie'-irrant pairs
4238465
IHigh
Cohort
(Prospective)
Trimester 1
-30.2
Quartile 2
I
- i ¦
-64.!
Quartil&3
A
0 1
-40,3
Quartile 4
• • r—<
-12.4
Iri-unit (ng/mL)
increase
—.J-.
i
Bach et al„ 2015
3981534
Aarhu$ Birth Cohort (2005-20131,
OfinrTfHrk, 15D7 rmllwr-infant pairs
IHigh
Cohort
(Prospective)
Trimester 1-2
¦41
-34
Quartile 2
Quartite3
• l—H
1
i •—i—1
49
Quartile 4
-19.35
In-unit (ng/mL)
increase
Sagiv, 2018.
4238410
Project Viva (1999*2002) 1645
moiheHnfant pairs
IHigh
Cohort
(Prospective)
Trimester 1-2
-37.5
Quartile 2
> -•
f
44,9
Quartile 3
-10, a
QuarliM
m 1
-3.28
In-unit (ng/mL)
¦he/ease
I
H|H
Wikstra-Ti. 2020.
SELMA (2007-2010). Sweden, 1533
IHigh
Cohort
Trimester 1-2
4
Quartile 2
1
"
6311677
mothe'-infant pairs
(Prospective)
-15
Quartile 3
. 1
-6
Quartile 4
M
-A1
Iri-unll (ng/«nl)
meeast
I « !
Eicketal.,2020.
7102797
Chemicals In Our Bodies (CIOB"i
(2014-2018), US, 497 female
participants
|High
Cross-sectional
Trimester 1-3
32,2
fertile 2
. 1
1
75.71
Tertile 3
Starling. 2017,
Healthy Starr cohort (2009-2014) 628
IHigh
Cohort
Trimester 2-3
32.9
Tenile 2
1
3858473
moitiG'-infant pairs
(Prospective)
-311
-13.5
Tertile 3
In-unit (ng/mL)
increase
r •
i- • 1 i
1
» *~T i
Shoaffetal..
2018,4019544
HOME (2003-2006), United State.
345 mother-infant pairs
IHigh
Cohort
(Prospective)
Trimester 2-3. at
delivery
-20.88
In-unit (ng/mL)
increase
1
Lunelsi ym,
9959610
Zhup.ng HosTiital Cdtioh, Ctixs
(2017-2019)224 mother-infant paiis
IHigh
Cotiorl
(Prospective)
Trimeter 3
-11.343
-7.761
-2.985
-12,5
Quartile?
Quartile 3
Quartile 4
In-unit (nq/mLi
i
-
t—••—i
i 4
i
increase
Valvietal.,2017.
Faroe Islands (1997-2000),
IHigh
Cohort
Trimeter 3
21.6
In-unit (ng/mL)
i
3$S38?2
DHnrriarK. t'KM molheHnfart pairs
(Prospective)
Tir/ease
•
Vaoet al, 2021.
9960202
Laizhou Wan Birth Cohort (LWBC)
(2010-2013) China, 369 parent-infant
pairs
(High
Cohort
(Prospective)
Trimestoi 3
-10.13
In-unit (ngtoiL)
increase
I
i
200
-150
-100 -50 0 50
100 150 200
Figure 3-20. Overall population birth weight results for 11 high confidence
PFHxS epidemiological studies.ab For additional details see HAWC link.
Abbreviation: BWT = Birth Weight
aStudies are sorted first by overall study confidence level, then by exposure window(s) examined.
bFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
This document is a draft for review purposes only and does not constitute Agency policy,
3-120 DRAFT-DO NOT CITE OR QUOTE
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Study
Population
Overall Study
Design
Exposure
Regression
Exposure
Confidence
Window
Coefficient
Comparison
ReflreiiiCrt ee-srreiant
A |i rchfKioo In tcHiai* 0WT101)
GySfcrfurrtrtw,
POPUP < 1OT6-30111 381
5M«#utn|
C(i»±--sccUDB f. msan DWT igj; p«Q05
201ft. <1215300
motfwr-Wsnl pairs
• 1 \
H-! 95% conRdarm nlwvBl
Kwon, 2016.
E0GRC (2006-2010; 208
CmwKll en«l
At birth
-00 1
ln-unlt (n^Vrl)
motTMr-irifanl pairs
ircri»ns«
"l
L. 2017 39BI353
GBC-3 r2013J Chhi»( 321
(Me4um|
CrosMKUona)
Al birth
.M3
hvuNt (ngfnlj
¦#. ' t
Chunet ul.
206E. KttWtKS
mMwr-Wanl pairs
fcmoiT LVllve'slty Alricuri Amwicnn
vagina1, Ural arnr gui Mic!oo«w»
jMetftuml
Cohort
l)'rt>19#CUV*l
T rlrtwstor 1»2
-36
Quarllte 2
1
P#&giiaccy Study <2014 ?01fl|,
P*iU siDW»h>
1
a
-64
uuartim
In wfMl injVnLi
¦ I
wmh
PmsflOrtiv" Uihivt [triiVr*" trnnt
ShwiijM Bltll. Cohort 12015-2017k
2I4 m-atnw-mfiini pnf*
Medium!
Cohort
(Prwpocllrwl
TrimMtoi 1 2
SI
Ounrtilii 2.
1
!•
-455
Quuirltttf %
I
25, B
Qunrlihi4
i •
27 e
li*-unli |n|jiVr4.)
Mang et al 2018
DNDC OWC-JO02I Q*rv-n*r. 3335
A'etfiumi
Cohort
T rtmsatv 1-3
37 3
inOiMwa
Ouartlhi 2
i
1 •
•WSflfii
moffww Infcinl poim
iPtoMMcllv*)
«
8«
OiMiliW! 4
)•
AG
lnprt 12005 2006) 252
Weifluml
Cohort
TrfffltSW 2
4^
Twnb 2
1290814
ma!H«r4nianl pairs
fProwKUvB)
26
21 9
ToitM3
Itvumr 4hf>W4)
10rt!ow4)
i
—i
(
2017,
4183 Mil
HOME I2003-20GGK U.S , $84
MwIUjinI
Cohort
rPi©w«c»»vB»
Trin wt«r 23
¦7J»
h» unM IfnjInL)
i
>
KiwMno, 2020,
6311032
H*>JiX4iliki Sludy on Eriyiwvn#tV| u«nJ
CfllliMsn's Health ii0C3-20C*Ji.
Japan, IMS rmJHien-chiW p*r»
fMwftimv)
Cohorl
iProwccttvoi
TtirtWWir 3
¦i21
Pn»iiy f ¦ 1)
I
> • 1
»
-81 j!
Pnmy (»«2i
20«5i
sontiis/
City LonOWiJMuM Bi> il<
Crtw»M2i»3-anr>| c:iiir«i anz
tr>othe*-*t»lanl pair*
li»*l
Cahwt
(Pl<*1MJCllV1ft
Al (jliih
•1,3
13J
li».ynli (ngAnt,)
mira
"inn* 2
-t-
i
•2*1
SIM. 2017,
HmiJ.ii! HiMpiial 12012) 170
Hw)
CmMeciiMMl
At lilltli
-17 3
liwinli ifift.'«4.)
war'jX,
if>oftiw»if4wil pin
(l«f» BASIC
Xu 2019,
Ctoto-wsl>ei>irt» Mntly <2016-2017|,
,Lmv|
CXHMMUOftlll
AJSillll.
•7S.6
liwinii' (ng*i4.j
H3BI33H
Otiltt MB niiUhwl-mliWit [ih'i'i
H«:»rMi Aualrataii. 98
|Ufw|
CrajS'Sectanai
Tnnsjater3
•72
livunlt
* ,
3650524
rr>s9w-lr^an| pairs
Irauae
i
Gao el al 201'J
5357135
ABAalitd hospital of Capital Medical
Unlyerifty (2015-2016). CNn», 132
pi r-gfinfit vwMMfi
ftMl
Cohort
lPr«#cctlvfi>)
Tnnieitor 3
-154 1
T«We2
i
i
-101.2
TaitHe 3
i
2M
-ISO
-100
-SO 0 3d
100 150 200
Figure 3-21, Overall population birth weight results for 17 medium and low
confidence epidemiological studies. For additional details see HAWC link.
Abbreviation: BWT= Birth Weight
aStudies are sorted first by overall study confidence level, then by exposure window(s) examined.
b(Meng et a!., 2018) pooled samples from umbilical cord blood and maternal plasma during the first and second
trimesters. The remaining studies were all based on either one umbilical or maternal sample.
c(Gvllenhammar et al.. 2018) results are displayed here for mean birth weight among 587 overall population
participants in the POPUP Cohort compared to a smaller sample size of 381 in their 2018 publication.
dFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectionai analyses.
eSome confidence intervals (CIs) truncated, e.g. the entire 95%Cls for these studies are: (Hiermitslev et al., 2020): -
230, 44.1; (Xu etal.. 2019): -272,7,121.6; (Gao etal., 2019): Tertile 2: -332.2, 24; Tertile 3: -275.5, 73.1
This document is a draft for review purposes only and does not constitute Agency policy,
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Author(s) and Year
Confidence
Timing
N
Luo, 2021
High
T3
224
Shoaff. 2018
High
T2-T3
299
Yao. 2021
High
T3
369
Starting, 2017
High
T2-T3
598
Valvi, 2017
High
T3
604
Lind. 2017
High
T1
636
Manzano-Salgado, 2017
High
T1-T3
1202
Bach, 2016
High
T1-T2
1507
Ashley-Martin, 2017
High
T1
1509
WikstrOm, 2020
High
T1-T2
1533
Sagiv, 2018
High
T1-T2
1645
Buck Louis, 2018
High
T1
2106
Kwon. 2016
Medium
B
268
Li, 2017
Medium
B
321
Gyllenhammar, 2018
Medium
PB
587
Hamm. 2010
Medium
T2
252
Lenters. 2016
Medium
T2-T3
1321
Kashino. 2020
Medium
T3
1591
Chen.2021
Medium
T1-T2
214
Hjermilslev. 2020
Medium
T1-T3
266
Chang. 2022
Medium
T1-T2
370
Maisonet, 2012
Medium
T1-T3
895
Meng. 2018
Medium
T1-T2
2120
Xu, 2019
Low
B
98 -
Shi. 2017
Low
B
170
Callan, 2016
Low
T3
98
Workman, 2019
Low
T2-T3
414
Estimate [95% CI]
-12,5 [-106.8. 818]
-20.9 [-55.9, 14.1]
-10,2 [-130.1, 109.7]
-13 5 [-50.7. 23.7]
21.6 [-25 2. 60.5]
3.5 [-46 7. 53.8]
-12.4 [ -46.2. 214]
-19.4 [-55.4, 16.7]
7.5 [-26 6, 41.6]
-0.1 [-38 1, 37.9]
-3.3 [-18.8, 12 2]
-22.1 [-52.5, 8 4]
-60.0 [-136.4, 16.3]
-30.0 [-83.5, 23.5]
-53.3 [-104.5. -2.1]
21.9 [-23.4, 67 2]
-5.1 1-44 5, 34.3]
-13[-26 3. 23 6]
27.6 [-64.7. 119.9]
-93 0 [-230 0, 44 0]
-20.2 [ -84 4 , 44.0]
-11.2 [-28.5, 6 2]
4.5 [-36 0, 44.9]
-75,5 [-272.7,121.7]
47.3 [-23 4,117.9]
-72.0 [-194 0. 50.0]
-6.6 [-66.9. 53.7]
RE Model for All Studies
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Birth Weight - Mean Differences - Sex-specific Results
Eight of the 14 studies with results showed some birth weight deficits in relation to PFHxS
exposures in either or both sexes (see Figures 3-23 and 3-24). In contrast, five studies in boys ((3
range: 17 to 70 g per ln-unit increase) and three studies in girls ((3 range: 20 to 70 gper ln-unit
increase) showed non-significant increased birth weight. Seven studies in girls were null (Kashino
etal.. 2020: Wikstrom etal.. 2020: Meng etal.. 2018: Ashley-Martin etal.. 2017: Li etal.. 2017b:
Lind etal.. 2017: Manzano-Salgado etal.. 2017a). while three were null in boys (Kashino etal..
2020: Wikstrom etal.. 2020: Manzano-Salgado etal.. 2017a).
Among the eight different studies that showed some evidence of inverse associations, six
were in boys and four were in girls. Two fGyllenhammar etal.. 2018: Bach etal.. 20161 of the eight
different studies reported decrements in both sexes. For example, birth weight deficits ranging
from -21 to -34 grams for quartiles 3 and 4 were seen in girls from the high confidence Bach etal.
(2016) study, but results were null for continuous exposure (per each ln-unit increase). In contrast,
results in boys for each ln-unit were -25 g but smaller ((3 range: -16 to -21 g) based on the upper
three quartiles (compared to quartile 1). In the medium confidence Gvllenhammar et al. (2018)
study, results were stronger in males ((3= -71 g; 95%CI: -150, 8 per each ln-unit PFHxS increase)
than females ((3= -45 g; 95%CI: -139, -47 per each ln-unit PFHxS increase).
Four of the studies noted above showed deficits only in boys f Marks et al.. 2 019 a: Cao etal..
2018: Li etal.. 2017b: Lind etal.. 2017). Two of the four studies noted above detected deficits in
girls only (Hi ermitslev et al.. 2 0 2 0: Maisonet etal.. 2012). The largest association in girls was seen
in the medium confidence study by Hiermitslev et al. (2020) ([3= -145; 95%CI: -306,14.7 per each
ln-unit increase). The medium confidence Maisonet et al. (2012) study showed some evidence of an
exposure-response relationship ((3 range: -9 to -108 grams across PFHxS tertiles). Two fMarks et
al.. 2019a: Lind etal.. 20171 of the seven studies that reported decrements in boys showed
incongruent results based on continuous and categorical exposures. For example, they both showed
null results for each ln-unit increase but large deficits were seen for exposure categories ((3 range: -
54 to -104 grams across PFHxS quantiles). A large deficit was also seen in the low confidence Li et
al. (2017b) study ((3= -53 g; 95%CI: -127, 20 per each ln-unit increase). The low confidence Cao et
al. (2018) study showed some evidence of an exposure-response relationship in boys ((3 range: -30
to -109 g across tertiles). The study by Hiermitslev etal. f20201 was null for their continuous
exposure measure and quartile 4, did show some elevated non-significant results for quartiles 2
and 3 ((3 range: -39 to -51 g).
This document is a draft for review purposes only and does not constitute Agency policy.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Birth Weight - Mean Difference - Sex-Specific Summary
Eight different studies showed some birth weight deficits in relation to PFHxS exposures in
either or both sexes. Although the magnitude of deficits was larger among girls ((3 range: -45 to
-145 g) per each ln-unit PFHxS increase than boys ((3 range: -25 to -71 g), more studies showed
deficits among boys. Four of these studies showed deficits in girls, while six showed deficits in
boys. There were no patterns seen for results across confidence levels among boys, but the deficits
seen in girls were limited to medium and high confidence studies only. Two of the three low
confidence studies in boys showed adverse results including one with evidence of an exposure-
response relationship based on categorical data. Among the five studies with categorical data, one
study each in boys and girls had exposure-response relationships that were comparable in
magnitude (-108 and -109 g in tertile 3). Those results were coherent with linear birth weight
relationships detected in several studies with continuous exposure metrics data as noted above
(ranging from -25 to -145 grams per each unit change in PFHxS).
Among these eight sex-specific studies, five had early biomarker samples indicative that
pregnancy hemodynamics was not likely an explanatory factor here. No other patterns by other
study characteristics were evident in the sex-specific findings including study sensitivity among the
null studies. Although the evidence may be somewhat stronger among males, the lack of consistent
patterns within and across studies and insufficiently sensitive studies to detect statistically
significant sex-specific associations preclude more definitive conclusions from being drawn.
This document is a draft for review purposes only and does not constitute Agency policy.
3-124 DRAFT-DO NOT CITE OR QUOTE
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Study
Population
Study Sensitivity
Design
Exposure Window
Regression Exposure Comparison
Coefficient
Regression coefficient
0 2 (change in mean BWT (g)]
Ashley-Martin,
WIREC study (2008-2011)1509
Good
Cohort
Trimester 1
23.3
liHjnif (ng/mL) increaa
HIGH CONFIDENCE
I
O 3 (change in mean BWT (g)| p<0 05
2017,39B1371
iwther-lnte lit pairs
(Prospective)
H-p#—<
M SS't confidence interval
Lmd.2017,
Odense Child Cohort (2010-2012)
Adequate
Cohort
Trimester t
-28
QuartUe 2
I
3858512
638 mother-infant pairs
l Prospective |
I
-104
Quartiie 3
•-
I' 1
-66
auarDle4
-f 1 .
9
ln-unrt (ng/mLj increase
1 W
Mania no-Sal gado
iNMAcohon (2003-2008) 1202
Adequate
Cohort
Trimester 1
•6.4
Irv-unit (ng/mLI increase
at al . 2017.
mother-intent pairs
(Prospective)
k—4—»
4238485
I
Bach etai.. 2016,
Aarfius Birth Cohort (2008-2013),
Adequate
Cohort
Trimester 1-2
•21
Quartiie 2
3961534
Denmark. 1507 mother-infani pairs
(Prospective)
i
-19
Quartiie 3
t-i
-16
Quartiie 4
1>
-24.63
Irvunit I ng/mL) increase
t-i—~
WiXslfom, 2020,
SELMA (2007-20101, Sweden. '533
Good
Cohort
Trimester 1-2
-39
Ouarliie 2
1
6311677
mother-Infant pairs
'Prospective!
•51
Quartiie 3
—•—'—t
A
Quartiie 4
-13
hvunit (ng/ml.) increase
~—•¦J—i
vawielal.,2017,
Faroe Elands (1997-2000),
Good
Cohort
Trimester 3
17.3
tn-unit ihg/wiL) increase
39B3872
OenrrtBrt 6M mother-infaiil oaire
(Prospective)
Gyllenhammaret
POPUP (1986-2011) 381
Good
Cross-sectional
3 weeks post-birth
•71
IrvutiH (n^mL) increase
al, 2018,4238300 mother-infant pairs
MEDIUM CONFIDENCE
U, 2017.3981358
G8CS (2013). China. 321
Good
Cross-eeclonal
At birth
-53.2
In-unit (rnftnL) Increase
I
mother-Infant pairs
w
Meng et al,. 2010,
ONBC |1996-2002), Denmark. 3535
Good
Cohort
Tnmester 1-2
20.2
Irv-unit IngAnL) increase
1
4829851
mother-Infant pairs
I Prospective I
Hjermdstev, 2020.
ACCEPT birth cohort (2010-2011,
Adequate
Cohort
Tnmester t-3
70.4
In-unit (ng/mL) increase
I
5880849
2013-2015). Greenland 482
(Prospective)
1 •"
mother-infant pairs
Kashino, 2020.
Hokkaido Study on Environment and
Deficient
Cohort
Trimester 3
-13.2
Irvunit (ng/ril) increase
6311632
Children's Health (2003-2009),
(Prospective!
Japan. 1985 mothei-child pairs
1
Cao e! al.. 2018.
Zhoukou City Longitudinal Birth
Befidani
Cohort
AtWIh
-29.7
Tertiie 2
1
5080197
Cohort (2013-2015). China. 282
(Prospective)
§—1
mother-Infant pairs
LOW CONFIDENCE
-109.3
Tertile 3
1"
1
Shi, 2017,
Haidan Hospital (2012) 170
Deficient
Cross-sedional
Al birth
67,7
hvunit (n^rriL) Increase
3827535
mother-Intent pairs
Marks, 2019.
ALSPAC (1991-1992), England, 457
Good
Cohort
Trimester 1-3
-72.9
Tertile 2
5081319
mother-Infant pairs
(Prospective)
-53.9
Tertile 3
t ' 1
-5.2
In-unit (ngr'mL) increase
350 -300 -350 -?00
-150 -100
-50 0 50
100 150 200 250 300 350
Figure 3-23. Sex-specific male infants only mean birth weight results for 14
PFHxS epidemiological studies.a'bcd For additional details see HAWC link.
Abbreviations: BWT = Birth Weight
aStudies are sorted first by sex, overall study confidence level, then by exposure window(s) examined.
b(Meng et al., 2018) pooled samples from umbilical cord blood and maternal plasma during first and second
trimesters. The remaining studies were all based on either one umbilical or maternal sample.
c(Gvllenhammar et al., 2018) results are displayed here for mean birth weight among 587 overall population
participants in the POPUP Cohort compared to a smaller sample size of 381 in their 2018 publication.
dFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
This document is a draft for review purposes only and does not constitute Agency policy,
3-125 DRAFT-DO NOT CITE OR QUOTE
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Study
Population a
udy Sensitivity
Design
Exposure Wii>dow
Regression
Coefficient
Exposure Comparison
Regmssion
• i icnanqa main BW* U3II
Ailtiny-MamA,
2017. JSBiaJl
MIRSC «r>Kly sn|.bii
-45,4
In-urit inanne
MtntUM CONMDtNCt
u.aov.
C8CS 125131. Ct»w, 331
fKilhSf-ttfafii pa'm
QwS
t'i^i»-«TClWrHW
Atiwa»
-2,3
?0Ul>Cl IftWBPte
« f 1
Miniumjl x>-a
4ltffl8dl
DKfiC 11938 2002) Dvrat. 35i5
mcmar-mliirt palm
Good
Cohort
((*«mnmetnw)
T'liliosWr 1-2
64
bi.tnl (ligiivLt IH04IMSU
' ^
M,BnrW»» 20J0
5080849
ACCSPf l*ih Bohon (SHO *011
2U'>201S|, GiavMnd Ala
n*iliiw'n(iw
6311632
Hohka.la Siuay on Emtnyvnnm and
ChidiBVn HmIUi (2003.2MS),
•Vnpnn 15«3 rrwltw jiiilis
DnfcMm
Cchait
Trfcmwtnf 3
IQJil
(n-urtj (noW. t Innrmsn
i
C«o Hoi. 3018.
WW157
«9«ww>u City UWltidMl Birth
Cohen (SOI3-20151. Ct*w. 262
inuliin mriMf put*
0«*«iinl
C«hwl
«»«rwv
-5.1
latin 2
!
LOW CONr IDfchCt
i
Sm.2017.
Hutllwi (2012) 110
43
Iimi.hi ()nymL> miiso*
1
iazrail
rnnUHff HltiM pnri
350 300 250 3W 150 190 50 0 50 IOO IB0 200 250 MO 380
Figure 3-24. Sex-specific female infants only mean birth weight results for 14
PFHxS epidemiological studies. For additional details see HAWC link.
Abbreviations: BWT= Birth Weight
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
bMeng et al. (2018 pooled samples from umbilical cord blood and maternal plasma during first and second
trimesters. The remaining studies were all based on either one umbilical or maternal sample.
cGvllenhammar et al. (2018) results are displayed here for mean birth weight among 587 overall population
participants in the POPUP Cohort compared to a smaller sample size of 381 in their 2018 publication.
dFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
This document is a draft for review purposes only and does not constitute Agency policy,
3-126 DRAFT-DO NOT CITE OR QUOTE
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8
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12
13
14
15
16
17
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25
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Birth Weight - Standardized - Background
Twelve of thirteen studies in the overall population that reported a continuous
standardized birth weight scores in relation to different PFHxS measures (see Figures 3-25 and 3-
26), while the Gardener etal. f20211 study not included on the forest plot examined odds of being
in the lowest standardized birthweight category (vs. the top 3 birth weight z-score quartiles). Four
of the 13 studies also reported sex-specific results fEick etal.. 2020: Gross etal.. 2020: Wikstrom et
al.. 2020: Xiao etal.. 20191. while Gardener et al. (20211 only examined interactions across sex for
associations between PFHxS and standardized birth weight measures.
Among the 13 studies that examined PFHxS exposure in relation to standardized birth
weight scores in the overall population, eight were high f Gardener etal.. 2021: Eick etal.. 2020:
Wikstrom etal.. 2020: Xiao etal.. 2019: Sagiv etal.. 2018: Shoaff etal.. 2018: Ashlev-Martin et al..
2017: Bach etal.. 20161. three were medium fGvllenhammar etal.. 2018: Meng etal.. 2018: Hamm
etal.. 20101 and two were low (Gross etal.. 2020: Workman etal.. 20191 confidence. Six studies
had good (Wikstrom etal.. 2020: Gvllenhammar etal.. 2018: Meng etal.. 2018: Sagiv etal.. 2018:
Shoaff etal.. 2018: Ashlev-Martin et al.. 20171 study sensitivity ratings, while five were adequate
(Gardener etal.. 2021: Eick etal.. 2020: Xiao etal.. 2019: Bach etal.. 2016: Hamm etal.. 20101 and
two were deficient fGross etal.. 2020: Workman etal.. 20191.
Birth Weight - Standardized - Study Results
Null associations between PFHxS exposure and standardized birth weight scores were
reported in six studies (Wikstrom etal.. 2020: Workman etal.. 2019: Gvllenhammar etal.. 2018:
Sagiv etal.. 2018: Ashlev-Martin etal.. 2017: Hamm etal.. 20101 (see Figures 3-25 and 3-26).
Similar to results from categorical and continuous exposures in Wikstrom etal. (20201 and Sagiv et
al. (20181. birth weight z-score results were largely null in relation to PFHxS tertiles in the high
confidence Eick etal. f20201 study in the overall population and across the sexes. They did report
larger birth weight z-scores in the overall population for tertile 3 ((3= 0.15; 95% CI: -0.12, 0.42
compared to tertile 1) that appeared to be driven primarily by results in females ((3= 0.22; 95%CI:
-0.18, 0.63). The high confidence study by Gardener etal. (20211 detected non-significant increased
odds for their lowest standardized birthweight category (vs. the top three birth weight z-score
quartiles) across PFHxS quartiles (Q3: OR= 1.70; 95%CI: 0.81, 3.74); Q4: OR= 1.20; 95%CI: 0.55,
2.62). They also found no statistically significant interactions for their birth weight z-score
measures by sex.
Although their continuous exposure results were null per each ln-unit PFHxS increase, the
high confidence study by Bach etal. f 20161 reported a small decrease in standardized birth weight
scores ((3= -0.11; 95%CI: -0.25, 0.03) in PFHxS quartile 4 compared to quartile 1. Similar results
were seen for both tertiles 2 and 3 only ((3 range: -0.12 to -0.13) in the high confidence Shoaff et al.
(20181 study. Statistically significant results similar in magnitude were detected in the medium
confidence Meng etal. T20181 study ((3= -0.14; 95%CI: -0.22, -0.07 per each ln-unit PFHxS
increase). Larger statistically significant lower birth weight z-scores results were reported in the
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
1 low confidence study by Gross etal. (20201 for the overall population ((3= -0.65; 95%CI: -0.99,
2 -0.39), males ((3= -0.60; 95%CI: -1.14, -0.06) and females ((3= -0.77; 95%CI: -1.25, -0.29) for
3 PFHxS levels greater than the mean level of dried-blood spot samples. Associations large in
4 magnitude per each ln-unit increase were also detected in the high confidence study by Xiao et al.
5 £2019} for the overall population ((3= -0.74; 95% CI: -1.23, -0.26), male neonates ((3= -0.62; 95%
6 CI: -1.28, 0.06), and female neonates ((3= -0.87; 95% CI: -1.50, -0.22).
This document is a draft for review purposes only and does not constitute Agency policy.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Study
Population
Study Sensitivity
Design
Exposure
Regression
Exposure
Window
Coefficient
Comparison
Ashley-Martin,
MIREC study (2008-2011) 1509
Gooa
Cohort
Trimester t
0.04
•n-unit (ng'niLj
2017.3981371
mother-infant oairs
(Prospective)
increase
Bach etai,. 2016,
Aarhus Birth Cohort (2003-2013).
Adequate
Cohort
Trimester 1-2
0.01
Quartile 2
3981534
Denmark. 1507 mother-infant pairs
(Prospective)
-0.03
Quartile 3
-0,11
Quartile 4
0.05
tn-unit (ngfmL)
Sagiv. 2018,
Project Viva (1999 2002) 1645
Gooc
Cohort
Tnmester 1-2
01'
Quartile 2:
4236410
mother-infant pairs
(Prospective)
0.04
Quartile 3
0
Quartile 4
0
'n-unit (ng'rnL)
Wikstrom, 2020.
SELMA (2007-2010), Sweden, '533
Goad
Cohort
Tnmester 1-2
-0.004
Quartile 2
6311677
rnglher-infant pairs
(Prospective)
-0.016
Quartile 3
-0.008
Quartile 4
0.007
in-unit (ng/mL)
Ei<* el al.. "2020.
Ctlefflirtals In Qui Bodies (CIQB'l
Adequate
Cioas-eiHcJIonal
Trimastef 1-3
0.08
Taitlte?
7102797
(2014-2016). US, 497 female
participants
fl:1«
Tertile 3
Shoaff et al..
HOME (2003-2006). Unitec States.
Good
Cohort
Trimester 2-3, at
-OAZ
Tertile 2
2018.4619944
345 mother-infant pairs
(Prospective!
delivery
-0 13
Tertile 3
-0.09
tn-unit (ng'mL)
Xiao ei al. 2019.
Faroe Islands (1994 1995), 172
Adequate
Cohort
Trimester 3
074
m-unit (ng'mL)
5918609
mothor-infant pa.rs
(Prospective)
increase
Gyllenhammar.
POPUP (1996-2011) 381
Good
Cross-sectional
3 weeks post-birth
-0.003
tn-unit (ng'mL)
2018,4238300
mother-infar.t pairs
Mcnqctal,. 2018
~NBC (1996-2002), Denmark, 3535
Good
Cohort
Trimester 1-2
-0.14
in-unit (ng'mL)
4B29H51
mothf-M-infam pans
(Prospective)
Inciease
Hamm, 2010,
Alberta coiioit <2005-2006) 252
Adequate
Cohort
Trimester 2
-0.013
Tertile 2
1290814
mother-infant pairs
(Prospective)
0.013
Tertile 3
0.035
•n-unit (ng'mL)
Gross el H\ . 20W.
StHiiing Eaily Program (SlEP)
Deficient
Nested
Alfcnflh
-0,05
high (>rnean) vs.
7014743
Cohort, United S tates, 98
case-control
low
mother-infant pairs
Workman et al..
Canadian Healthy Infant Longitudinal
deficient
Cohort
l nmester 2-3
-0.D16
In-unit(ngzmL)
2019, 5387046
Development (CHILD) Stud"
(Prospective)
increase
Regression coefficient
t (3 [change in 6WT Z-Soore]
) (3 [change In SWT Z-Score| p^O.05
¦4 95% confidence interval
I I
\
0.4 -0.2 0 (J.2
Figure 3-25. Overall population standardized birth weight results for 12
epidemiologic studies. For additional details see HAWC link.
Abbreviations: BWT= Birth Weight
'Studies are sorted first by overall study confidence level then by Exposure Window examined.
b(Xiao et al.. 2019) results are truncated: the complete 95% CI ranges from -1.23 to -0.26 grams.
cFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
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Study
Population
Study Sensitivity
Design
Exposure Window
Regression
Exposure Comparison
Coefficient
Regression coefficient
0 P [change in BWT Z-Score]
Wikstrom, 2020,
6311677
SELMA (2007-2010), Sweden. 1533
mother-infant pairs
Good
Cohort
(Prospective)
Trimester 1-2
-0.061
-0.083
Quartile 2
Quartile 3
»—•—.
O P [change in BWT Z-Score] p<0.0£
f-H 95% confidence interval
0.016
Quartile 4
1 • 1
Sagiv. 2018,
4238410
Project Viva (1999-2002) 1645
mother-infant pairs
Good
Cohort
(Prospective)
Trimester 1-2
-0.017
-0.01
In-unit (ng/mL) increase
In-umt (ng/mL) increase
4-h
Eick et al., 2020,
7102797
Chemicals In Our Bodies (CIOB)
(2014-2018), US. 497 female
participants
Adequate
Cross-sectional
Trimester 1-3
0.14
Tertile 2
i m
1
i
Xiao etal,, 2019,
Faroe Islands (1994-1995), 172
Adequate
Cohort
Trimester 3
-0 62
In-unit (ng/mL) increase
i
5918609
mother-infant pairs
(Prospective)
Gross et al , 2020,
7014743
Starting Early Program (StEP)
Cohort, United States, 98
mother-infant pairs
Deficient
Nested
case-control
At birth
-0.6
high (>mean) vs. low
i i
i
Wikstrom, 2020,
6311677
SELMA (2007-2010). Sweden, 1533
mothBr-infant pairs
Good
Cohort
(Prospective)
Trimester 1-2
0.071
0.062
-0.043
0.031
Quartile 2
Quartile 3
Quartile 4
In-unll (ng/mL) increase
h-L.
i—<-m—i
i—•>—i
»-W-.
Sagiv. 2018,
4238410
Project Viva (1999-2002) 1645
mother-infant pairs
Good
Cohort
(Prospective)
Trimester 1-2
0.04
In-unit (ng/mL) increase
Eick etal : 2020.
7102797
Chemicals In Our Bodies (CIOB)
(2014-2018), US, 497 female
participants
Adequate
Cross-sectional
Trimester 1-3
0.06
Tertile 2
l
0,22
Tertile 3
1
Xiao etal,, 2019,
Faroe Islands (1994-1995), 172
Adequate
Cohort
Trimester 3
-0.87
In-unit (ng/mL) increase
I
5918609
mother-infant pairs
(Prospective)
1
Gross et al., 2020,
7014743
Starting Early Program (StEP)
Cohort, United States. 98
mother-infant pairs
Deficient
Nested
case-control
At birth
-0.77
high (>mean) vs. low
1
I
1.4 -1.2 -1 -0.8 -0.6
-0.4 -0.2 0 0.2 0.4
0.6 0.8 1 1.2 1.4
Figure 3-26. Sex stratified standardized birth weight results for 5 epidemiologic studies (boys above reference
line, girls below). For additional details see HAWC link.
Abbreviations: BWT= Birth Weight
aStudies are sorted first by overall study confidence level, then by Exposure Window(s) examined.
b(Xiao et al., 2019) results are truncated: the complete 95% CI ranges from -1.5 to -0.22.
cFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or after birth to be cross-sectional analyses.
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Birth Weight - Summary of Different Measures and Analyses
Six of 13 studies showed some evidence of inverse associations between PFHxS and
standardized birth weight measures in the overall population. Among the 12 studies examining
continuous birth weight measures in the overall population, 3 showed some associations of at least
-0.1 in relation to either categorical or continuous PFHxS exposures. Two other studies (1 high and
1 low confidence) showed stronger associations in excess of -0.74 as well as comparable results in
both sexes. The high confidence study by Gardener et al. (20211 also reported non-significant odds
of being in the lowest standardized birth weight category (vs. the top 3 BWT z-score quartiles)
based on PFHxS quartiles 3 (OR range: 1.20 to 1.74). There was limited evidence of exposure-
response relationships in support of the continuous study results expressed per a unit change. Few
patterns and minimal differences were seen across sexes. Among the six studies in the overall
population that showed some suggestion of inverse associations, two studies (1 high and 1 low
confidence) reported large associations consistent in magnitude for both male and female
neonates. Study sensitivity did also not seem to explain null study findings as four of these six
studies had good ratings in this domain. There was a slight preponderance of inverse associations
with four of the six studies using later biomarker samples.
Overall, 17 of the 31 epidemiological studies with mean birth weight in either/both sex or
the overall population detected some deficits in relation to PFHxS exposures (see Table 3-17),
although these deficits were at times limited to sex-specific findings (Marks etal.. 2019a: Lind etal..
2017: Maisonetet al.. 2012) and often were not statistically significant (see Figures 3-20, 3-21, 3-
23, and 3-24). This included 14 (4 low and 5 each medium and high confidence) of the 27 studies in
the overall population. Two different studies (out of 14) with categorical data in the overall
population or either sex showed some evidence of exposure-response relationships. Overall, the
magnitude of changes in those studies showing deficits ranged from -25 to-109 grams for the
highest quantile (compared to the lowest quantile). Those results were consistent in magnitude
with 12 studies with continuous exposure metrics data showing birth weight-related deficits with
increasing exposures in the overall population ((3 ranging from -12 to -93 grams per each unit
change in PFHxS). Seven of these ranged from -12 to -30 grams, and the remaining five ranged
from -53 to -93 grams. These data were supported by an EPA meta-analysis that showed also
showed a small birth weight deficit ((3= -7.7 g; 95% CI: -14.8, -0.5) per each ln-unit PFHxS among
all 27 studies and were consistent in magnitude ((3 range: -7 to -10 g) across 12 high confidence
studies, 11 medium confidence studies, and the combined high and medium studies. Although
deficits were largest among post-partum samples, the results among the 12 early samples studies
were comparable ((3= -7.3 g; 95% CI: -16.0,1.4) to that seen in the overall population of all studies.
Although deficits were largest among post-partum samples, the results among the 12 early sampled
studies were comparable ((3= -7.3 g; 95% CI: -16.0,1.4) to that seen in the overall population of all
27 studies.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Limited patterns were evident in the mean birth weight findings as overall confidence,
study sensitivity, exposure levels and other study design elements were not explanatory for the null
or inverse associations. The mean birth weight differences in the overall population may be
influenced by hemodynamic changes during pregnancy, as only ten of the fourteen were based on
late biomarker sampling. Similar to that seen for standardized birth measures, the sex-specific data
were more mixed in relation to sample timing as four of six studies showing birth weight deficits
were based on late biomarker collection.
Birth Length - Background of Studies
Nineteen studies examined the relationship between PFHxS exposures and birth length in
the overall population or across sexes; one study fAlkhalawi et al.. 20161 was classified as
uninformative and is not discussed here (see Figure 3-27). Two of the 10 studies reporting sex-
specific findings did not report overall population results; both studies were from the ALSPAC
population, including a study in boys (Marks etal.. 2019a) and girls (Maisonetetal.. 20121. Two
studies (Xiao etal.. 2019: Gvllenhammar etal.. 20181 reported standardized birth length measures,
while the remaining studies examined mean birth length differences in relation to PFHxS. As noted
above, two studies fBierregaard-Olesen etal.. 2019: Bach etal.. 20161 from the Aarhus birth cohort
are discussed when discrepancies arise or in isolation as for some sex-specific findings. They are
both listed together below in the background materials just below, but only counted as one study
when evaluating consistency and between-study heterogeneity patterns.
Six of the 18 included PFHxS studies examining birth length studies were classified as high
(Luo etal.. 2021: Bierregaard-Olesen etal.. 2019: Xiao etal.. 2019: Buck Louis etal.. 2018: Manzano-
Salgado etal.. 2017a: Valvi etal.. 2017: Bach etal.. 20161. and five were medium (Chen et al.. 2021:
Hiermitslev etal.. 2020: Kashino etal.. 2020: Gvllenhammar etal.. 2018: Maisonetetal.. 20121
confidence. Seven of birth length studies were classified as low confidence fGao etal.. 2019: Marks
etal.. 2019a: Workman etal.. 2019: Xu etal.. 2019: Cao etal.. 2018: Shi etal.. 2017: Callan etal..
20161 largely due to concerns with participant, selection, confounding, and study sensitivity. For
example, seven of those studies were considered deficient for study sensitivity (Kashino etal..
2020: Gao etal.. 2019: Workman etal.. 2019: Xu etal.. 2019: Cao etal.. 2018: Shi etal.. 2017: Callan
etal.. 20161. Five studies were rated good (Luo etal.. 2021: Marks etal.. 2019a: Gvllenhammar et
al.. 2018: Valvi etal.. 2017: Maisonet etal.. 20121 and six were adequate fChen etal.. 2021:
Hiermitslev etal.. 2020: Bierregaard-Olesen etal.. 2019: Xiao etal.. 2019: Buck Louis et al.. 2 018:
Manzano-Salgado etal.. 2017a: Bach etal.. 20161.
Birth length-Overall Population Results
Nine of the 16 studies in the overall population reported shorter birth length in relation to
PFHxS exposure (see Figure 3-28; Table 3-17). Five of the six high confidence studies observed that
PFHxS exposure was associated with shorter birth length in at least one comparison set, including
statistically significant changes in three high confidence studies examining mean fBuck Louis etal..
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
2018: Manzano-Salgado etal.. 2017a) or standardized birth length measures (Xiao etal.. 20191. For
example, Xiao etal. (20191 reported smaller birth length z-scores in overall population ((3= -0.52;
95% CI: -1.04, -0.13 each ln-unitincrease!. The Manzano-Salgado etal. f2017al study reported
birth length reductions consistent in magnitude across all three PFHxS quartiles ((3 range: -0.31 to
-0.33 cm), although results were largely null for each ln-unit increase ((3= -0.09; 95%CI: -0.25,
0.09). The study by Valvi etal. f20171 reported small deficits in mean birth length in the overall
population ((3= -0.14 cm; 95% CI: -0.35, 0.04). Based on a ln-unit PFHxS increase, null results were
reported in the Bach etal. (2016) study, and their smaller subset analysis (n = 671 participants)
reported in Bierregaard-Olesen etal. (2019) (the latter data are not plotted given from same
cohort). The Bach etal. f 20161 study based on 1,507 participants did report decreased birth length
in the third ((3= -0.1 cm; 95% CI: -0.5, 0.3) and fourth ((3= -0.2 cm; 95% CI: -0.5, 0.2) quartiles
compared with the lowest quartile (not included on Figure Y given overlapping population). The
study by Buck Louis et al. (2018) reported that PFHxS was associated with reductions in birth
length (and upper thigh length; the latter data not shown) in the overall population ((3= -0.22 cm;
95% CI: -0.39, -0.05 per each ln-unit increase), as well as Black ((3= -0.43 cm; 95% CI: -0.71,
-0.14) and Hispanic neonates ((3= -0.34 cm; 95% CI: -0.70, 0.03).
Three out of four medium confidence studies in the overall population were null for birth
length deficits in relation to PFHxS exposures. The Chen etal. f20211 study reported a small deficit
((3= -0.15 cm; 95% CI: -0.42, 0.11) per each ln-unit increase and non-monotonic consistent deficits
across quartiles ((3 range: -0.33 to -0.46 cm). Three out of five low confidence studies reported
some suggestion of birth length deficits in relation to PFHxS. Although results were null for tertile 3
relative to tertile 1, the low confidence study by Cao etal. (2018) reported a statistically significant
result ((3= -0.33 cm; 95% CI: -0.68, -0.01) for tertile 2. Compared to tertile 1, the low confidence
study by Gao et al. f20191 reported a statistically significant result ((3= -0.43 cm; 95% CI: -0.78,
-0.07) for tertile 2 but a smaller deficit in tertile 3 ((3= -0.20 cm; 95% CI: -0.64, 0.25). Callan et al.
f20161 reported an imprecise deficit of -0.20 cm (95% CI: -0.78, 0.38) per each ln-unit increase. In
contrast, Xu etal. (2019) reported a large increased birth ((3= 0.66 cm; 95% CI: -0.01,1.26 per each
ln-unit increase).
Overall, 9 (5 high, 1 medium, and 3 low confidence) out of 16 studies in the overall
population provided some evidence of birth length deficits with increasing PFHxS exposure. Some
of these results were not always internally consistent across different exposure expressions
(continuous vs. categorical). The five studies with categorical data in the overall population did not
provide any evidence of any exposure-response relationships. Although mean birth length results
for continuous PFHxS exposures were smaller, two of the three studies with PFHxS quartiles
showed deficits similar in magnitude ((3= -0.31 to -0.46 cm). There was a consistent pattern by
sample timing among those studies demonstrating birth length deficits in the overall population, as
six of the nine studies were based on late biomarker sampling. No other patterns by study
characteristics were evident
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
I 1 I I I I ' ' ! I I I I I I I
^,0^"
$&oV>
_J !
Participant selection
Exposure measurement
Outcome ascertainment
Legend
J Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-27. Study evaluation results for 19 epidemiological studies of birth
length and PFHxS. For additional details see HAWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Study
Population
Study Sensitivity
Design
Exposure
Window
Regression
Coefficient
Exposure
Comparison
Regression coefficient
• p [change in mean BL (cm)]
M-i'iiV) no-SnlyrfiJi)
Hi al., 2017,
4238465
INMA cohort (2003-200011202
Adequate
Cohen
(Prospective)
THiriBsiar 1
-0,33
Quartile 2
HIGH CONFIDENCE
H 95% confidence interval
-0,32
-0.31
-0.09
Quartile 3
Quartile 4
Ir-unit (ng/mL)
1
1
Buck Louis. 2018.
5016992
NICHD Fetal Growth Studios
(2009-2013), United States. 2106
mother-infant pairs
Adequate
(Prospective)
Trimester 1
-0.22
ln-unit (ng/mL)
I
1— • ¦ 1
Bach et al.. 2016.
3981534
Aarhus Birth Cohort (2008-2013).
Denmark, 1507 mother-infant pairs
Adequate
Cohort
(Prospective)
Triniostor 1-2
0
ln-unit (ng/mL)
0.1
Quartilo 2
-0;1
Quartile 3
1 •-! <
-0.2
Quartile 4
lunetal., 2021
9959610
Zhujiang Hospital Cohoit, China
(2017-2019) 224 mother-infant pairs
Good
Cohort
(Prospective)
Trimester 3
-0.001
0.04
Quartile 2
Quartile 3
Quartile 4
ln-unit (ng/rnL)
1 1—4
1
1
Valvietal., 2077.
3983872
Faroe Islands (1997-2000),
Denmark, 604 mother-infant pairs
Good
Cohort
(Prospective)
Trimester 3
-0.J4
Ip-unit (ng/mL)
1
« •—H
Xiao etal. 2019,
5918609
Faroe islands (19S4-1995), 172
mothor.mfant pairs
Adequate
Cohort
(Prospective)
Trimester 3
-059
imunii fTQ/mL)
9 ' I
Gyllenhammar,
2013. 4238300
POPUP (1996 2011) 381
mother-infant pairs
Boo"
Cross-sectional
3 weens post-birth
0
in unit fngrtnL)
MEDIUM CONFIDENCE
•
Chen. 2021,
7263965
Prosoective cohort analysis from
Shanghai Birth Cohort (2015-2017).
214 mother-infant pairs
Adequate
Cohort
(Prospective)
Trimester 1-2
-0-4
-0.46
-0,33
-0.15
Quartile 2
Quartile 3
Quartile 4
ln-unit (og/mL)
• M
I
• H
% 1 |
1
i • r~*
Hjermitslev, 2020,
5880849
ACCEPT birth cohort (2010-2011,
2013-2016). Greenland. 482
mother-infant pairs
Adequate
Cohort
(Prospective)
Trimester 1-3
-a.ia
li»-unit (ng/fnL)
i
Kashino. 2020,
6311632
Hokkaido Study on Environment and
Children's Health (2003-2009),
Japan. 1985 mother-child pairs
Deficient
Cohort
(Prospective)
Trimester 3
0.01
ln-unit (ny/rnL)
i-4-i
1
Cao el al., 2018.
5080197
Zhoukou City Longitudinal Birth
Cohort (2013-2015), China. 282
mother-infant pairs
Deficient
Cohort
(Prospective)
At birth
-0.33
-0.07
TerUle 2
Tertile 3
LOW CONFIDENCE
• 1
1
' -•-]
Shi. 2017.
Harden Hospital {2012} 170
Deficient
CiOKK-sectional
At birth
ffi17
lr>-unit (ngtoll)
,1 f ,
3827535
mother-infant pairs
increase
Xu, 2019,
Cross-sectional study (2016-2017).
Deficient
Cioss-sectional
At birth
0,66
lr)-unit (rig/ml)
5381336
Chma, 98 mother-infant pairs
Workman si al.,
2019, 5387046
Canadian Heallhy Infant Longitudinal
Develapmenl (CHILD) Study
Deficient
Cohort
(Prospective)
Trimester 2-3
-0,012
ln-unit(ng/nil.)
(2010-2012), Canada (414
mother-infant pairs)
I
Callan. 2016.
AMETS (2008-2011). Australia, 98
Deficient
Cros5-seclional
Trimester 3
-0.2
In-unii (ng,'mL)
3858524
mother-infant pairs
increase
#
1
Gao al al., 2019,
5387135
Affiliated Hospital of Capital Medical
University (2015-2016). China. 132
pregnant women
Deficient
(Prospective)
Trimester 3
-0.43
-0.2
Tertile 2
Terlile 3
1.4 -1.2 -1 -0.8
-0.6 -0.4 -0.2 0 0.2
4 0.6 0-8 1 1.2 1.4
Figure 3-28. Overall population mean birth length results for 16 PFHxS
epidemiological studies. For additional details see HAWC link.
Abbreviations: BL= Birth Length
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
b(Xiao et al., 2019) and (Gvllenhammar et al„ 2018) in blue text report birth length z-score data.
cFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
Birth Length-Sex-Specific Results
Among these 11 studies with results in either boys, girls or both, some birth length deficits
were detected in 7 different studies (see Figure 3-29). The high confidence study by Xiao et al
(20191 reported deficits in both sexes including larger and statistically significant birth length z-
scores among girls (p= -0.72; 95% CI: -1.33, -0.12 each ln-unit increase). Sex-specific results were
null based in both sexes based on continuous (per each ln-unit increase) data in the Manzano-
Salgado etal. f2017al and Kashino etal. f202CQ studies. Four of the remaining six studies in females
were null fChen etal.. 2021: Bierregaard-Olesen et al.. 2019: Cao et al.. 2018: Shi etal.. 20171. The
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medium confidence Maisonet et al. T20121 study of girls only reported dose-dependent statistically
significant associations across exposure tertiles ((3 range: -0.52 to -0.82). The medium confidence
Hiermitslev et al. f20201 study reported deficits among female neonates only (P= -0.42 cm; 95% CI:
-1.07, 0.22 per each ln-unit increase).
The medium confidence Chen etal. f2021) study reported a small birth length deficit ((3=
-0.15 cm; 95% CI: -0.61, 0.31) per each ln-unit increase in boys only. The high confidence study by
Valvi etal. (2017) reported deficits among male neonates only (p= -0.22 cm; 95% CI: -0.49, 0.04
per each ln-unit increase). The low confidence study by Cao etal. f20181 detected non-monotonic
reductions in birth length across tertiles (P range: -0.18 to -0.44) in boys, while another low
confidence study of boys only fMarks et al.. 2019al detected evidence of an exposure-response
relationship across PFHxS tertiles ((3 range: -0.25 to -0.39). In contrast, increased birth length (p
range: 0.20 to 0.40 cm per ln-unit PFHxS increase) was detected in males in three studies
fHiermitslev et al.. 2020: Bierregaard-Olesen et al.. 2019: Shi etal, 2017).
Figure 3-29. Sex stratified birth length results for 11 epidemiologic studies
(boys above reference line, girls below). For additional details see HAWC link.
Abbreviations: BL= Birth Length,
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
bXiao et al. (2019) in blue text reports birth length z-score data.
cFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
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Summary-Birth Length-Sex-Specific
Stronger evidence of birth length deficits was observed in males (5 of 10 studies) compared
to females (3 of 10 studies); however, these deficits were generally smaller in magnitude among
males ((3 range: -0.15 to -0.39 cm) than females ((3 range: -0.42 to -0.82 cm). In addition to the two
null studies in males, three other studies reported increased birth length in relation to PFHxS
exposures. Two of the three studies with categorical data provided evidence of an inverse
exposure-response relationships, albeit only in males (Marks etal.. 2019a) and females (Maisonet
etal.. 2012) derived from the same ALP SAC study population.
Exposure levels were higher in the studies reporting birth length deficits in males, including
the top four and five of the top six highest exposure measures of centrality reported. Besides this
and the slightly more consistent results in males in general, no other patterns across study
characteristics explained the between-study heterogeneity including the null results. For example,
there was no definitive pattern of results by study confidence across the seven different studies
(two high, three medium, and two low confidence) nor sample timing (four had early biomarker
samples compared to three with late).
Summary-Birth Length
Overall, 12 out of 18 included studies provided some evidence of birth length deficits with
increasing PFHxS exposure in either the overall population or either sex. Some of these results were
not always internally consistent across different exposure expressions (continuous vs. categorical).
Two of the seven studies with categorical data provided some evidence of any exposure-response
relationships, both of these were from sex-specific studies in the same cohort. There was no pattern
among the null studies based on study sensitivity or other study characteristics. Mean and median
exposure levels were higher among the male studies showing deficits, but this did not appear to
explain results in females or the overall population. There was not a consistent pattern by sample
timing among the studies showing inverse associations in either/both sex (four of seven had early
sampling) or the overall population (three of nine had early sampling). Among the 11 different
studies demonstrating birth length deficits, six of them relied on early sampling suggesting limited
overall potential impact of pregnancy hemodynamics.
Head Circumference at Birth - Study Background
Fourteen studies examined PFHxS in relation to head circumference measured at birth
including two studies fXiao etal.. 2019: Gvllenhammar etal.. 20181 reporting standardized head
circumference measures (see Figure 3-30). Among the other 12 studies, 10 fChen etal.. 2021:
Hiermitslev etal.. 2020: Kashino etal.. 2020: Bierregaard-Olesen etal.. 2019: Workman etal.. 2019:
Xu etal.. 2019: Buck Louis et al.. 2018: Manzano-Salgado etal.. 2017a: Valvi etal.. 2017): Bach et al.
(2016): (Callan etal.. 2016) of these studies reported data in the overall population. Eight studies
analyzed sex-specific results include two studies (Marks etal.. 2019a: Lind etal.. 2017) that only
reported these data.
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Four studies were classified as low confidence fMarks etal.. 2019a: Workman etai, 2019:
Xu eta).,, 2019: Callan et al.. 20161 and five each were medium (Chen et al., 2021: Hiermitslev etal..
2020: Kashino etal.. 2020: Gvllenhammar etal.. 2018: Lind et al.. 20171 and high fBierregaard-
Olesenetal.. 2019: Xiao etal.. 2019: Buck Louis etal.. 2018: Manzano-Salgado etal.. 2017a: Valvi et
al.. 20171: Bach et al. f20161. Seven of the 14 PFHxS studies on head circumference had adequate
study sensitivity fChen etal.. 2021: Hiermitslev et al.. 2020: Bierregaard-Olesen etal.. 2019: Xiao et
al.. 2019: Buck Louis et al.. 2018: Lind etal.. 2017: Manzano-Salgado etal.. 2017al. while four were
deficient fKashino et al.. 2020: Workman et al.. 2019: Xu etal. 2019: Callan etal.. 20161 and three
had good study sensitivity (Marks etal.. 2019a: Gvllenhammar etal.. 2018: Valvi etal.. 20171.
Participant selection
Exposure measurement
Outcome ascertainment
Confounding -
Analysis -
Sensitivity -
Selective Reporting -
Overall confidence-
B Legend
Good (metric) or High confidence (overall)
+ Adequate (metric) or Medium confidence (overall)
- Deficient (metric) or Low confidence (overall)
| Critically deficient (metric) or Uninformative (overall)
Figure 3-30. Study evaluation results for 14 epidemiological studies of head
circumference and PFHxS. For additional details see HAWC link.
Head Circumference at Birth - Overall Population Results
Seven out of the 12 studies in the overall population reported some evidence of reduced
mean or standardized head circumference at birth with increasing PFHxS exposures including four
Hdjajy
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of five high confidence studies, two of four medium and one of three low confidence studies (see
Figure 3-31). Three studies detected null associations (Kashino etal.. 2020: Xu etal.. 2019:
Gvllenhammar et al.. 20181. Two studies reported small increases in head circumference per each
ln-unit increase including the high confidence Valvi etal. f20171 study ((3= 0.16 cm; 95% CI: 0.01,
0.29) and the low confidence Workman etal. f20191 study ((3= 0.12 cm; 95% CI: -0.18, 0.42).
The high confidence Xiao etal. f20191 study reported lower head circumference z-scores in
the overall population ((3= -0.52; 95% CI: -1.04, 0.00 per each PFHxS ln-unit increase). The high
confidence study by Bach etal. (2016) detected consistent deficits across quartiles two through
four (all (Betas were -0.2 cm), but they reported null findings based on the continuous PFHxS
measure as well as in their smaller subset in a separate publication fBierregaard-Olesen et al..
20191 (the latter data are not plotted given from same cohort). Similarly, the high confidence study
by Manzano-Salgado etal. f2017al showed some evidence of an exposure-response relationship
across the PFHxS quartiles ((3 range: -0.08 to -0.16) but not among the continuous exposure results
((3= -0.01 cm; 95% CI: -0.13, 0.10). The high confidence study by Buck Louis etal. (2018) reported
a precise but small deficit in the overall population ((3= -0.09 cm; 95%CI: -0.19, 0) and saw a
statistically significant reduction in head circumference for Black ((3= -0.25 cm; 95% CI: -0.41,
-0.08) neonates per each ln-unit increase in PFHxS. Two medium confidence studies detected an
imprecise head circumference difference of -0.14 cm per each ln-unit PFHxS increase including
Hiermitslev etal. C20201 (95%CI: -0.52, 0.25) and Chen etal. C20211 C95%CT: -0.46, 0.19). A larger
difference was detected in the low confidence Call an etal. (2016) study ((3= -0.31 cm; 95% CI:
-0.74, 0.12 per each ln-unit PFHxS increase).
Overall, 7 of 12 studies showed some evidence of associations between PFHxS and different
head circumference measures in the overall population. Some of these results were not always
internally consistent across different exposure expressions (continuous vs. categorical). One of two
studies with categorical data showed some evidence of an exposure-response relationship across
quartiles. There was no clear pattern in study characteristics among the null studies, although two
of the four had deficient study sensitivity. Five of the seven studies were based on early biomarker
samples, so pregnancy hemodynamics did not appear to explain the study findings.
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Manzano-Salgado INMA conort (2003-200811202
el al„ 2017, mother-Infant pairs
4238465
Exposure
Window
Regression Exposure
Coefficient Comparison
-0.Q8 Quartile 2
-0-14 Quartils 3
-0.16 Guartile 4
-0,01 In-unit (ng/mL)
Regression coefficient
9 p [change in "neap HC (cm)]
0 P [change in mean HC (cm)] fKO.OS
1 -I 35% confidant® interval
Buck Louis. 2018, NICHD Fetal Growth Studies
5016992 <2009-2013), United States. 2106
mother-infant pairs
ln-unit (ng/mL)
In-unil (ng/ml.)
-•—I
Prospective cohort analysis from
Shanghai Birth Cohort (2015-2017),
214 mother-infant pairs
ACCEPT birth cohort (2010-2011.
2013-2015). Greenland. 482
mother-infant pairs
Hokkaido Study on Environment and
Children's Health (2003-2009).
Japan, 1985 mother-child pairs
Canadian Healthy Infant Longitudinal
Development (CHIL D) Sluciy
(2010-2012), Canada (414
molher-infanl pairs)
Medium I
| Medium |
|Low|
|Low|
T rimester 3
Cohort
(Prospective)
Goh&n Tliriiestara
(Proso&ctlva)
Cross-sectional 3 weeks ooBl-blrth
Cohort Tn master 1-2
Cross-sectional
At birth
Tnwiester 2-3
Cross-sectional Trimester 3
Quartile 2
Quartile 3
Quartile 4
In-unit (ng/mL)
increase
lli-Ui>it (IW'mLj
increasa
In-upli (ng/mL )
In-unit (ng.'inL)
-0.07 In-unit (ng/mL)
0.05 In-unit (ng/mL)
0-12 ln-uriii(ng/mL)
Figure 3-31, Overall population head circumference results for 12
epidemiologic studies. For additional details see HAWC link.
Abbreviations: HC= Head Circumference
3Studies are sorted first by overall study confidence level, then by Exposure Window(s) examined.
bXiao et al. (2019 and Gvllenhammar et al. (2018; in blue text report head circumference z-score data,
cXiao et al. (2019i results are truncated: the complete 95% CI ranges from -1.04 to 0.
dFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
Head circumference at birth - Sex arid Race-specific Results
Eight studies examined PFHxS and head circumference differences among sexes (see Figure
3-32}. Two high confidence studies were null in both sexes fBierregaard-Olesen et al.. 2019:
Manzano-Salgado etal.. 2017al and only one study fXiao etal.. 20191 showed inverse associations
in both sexes. Four of eight studies were null in boys, and one showed larger head circumference
differences with increasing PFHxS exposures. Five studies were null in girls and two studies
showed inverse associations between head circumference differences and PFHxS exposures.
Three of eight studies in boys and two of seven studies in girls reported associations with
PFHxS. The high confidence study by Xiao et al. f20191 reported smaller head circumference z-
scores with larger results in female ((3= -0.76; 95% CI: -0.19, 0.23 per each In-unit increase)
compared to male ((3= -0.26; 95% CI: -0.46, 0.07 per each In-unit increase) neonates. All of the
other studies examined mean head circumference differences in relation to PFHxS. For example,
the medium confidence study by Hiermitslev et al. (20201 showed head circumference differences
among females only ((3= -0.26; 95% CI: -0.73, 0.20 per each ln-unit increase). Among boys, the
medium confidence study by Kashino etal. f2 0 2 01 reported head circumference differences smaller
in magnitude relation to PFHxS (P= -0.14 cm; 95%CI: -0.29, 0.02 per each ln-unit PFHxS increase),
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1 as did the medium confidence study by Lind etal. T2017 ((3= -0.1 cm; 95%CI: -0.4, 0.2 per each ln-
2 unit PFHxS increase). The Lind etal. (20171 study showed non-monotonic head circumference
3 deficits across exposure categories (p range: -0.1 to -0.7 cm), including one that was statistically
4 significant for PFHxS quartile 3 ((3= -0.7 cm; 95% CI: -1.2, -0.2).
5 Overall, four (1 high; 3 medium confidence) of eight studies showed some evidence of
6 associations between PFHxS and different head circumference measures among either or both
7 sexes (including three of eight studies in boys and two of seven studies in girls). No study
8 characteristics (i.e. study design features or study quality domains) appeared to explain between-
9 study heterogeneity of results including sample timing, as half of the studies reporting inverse
10 association were based on early biomarker samples.
Study
Mar'-ii'.ru-Salyado
el al.. 201',
Bjisn'egaaid-Ola&cii
si al.. 2013.
50B36W
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Xiao etal 2013,
is Birth Cohort (2008-2013) 'i
Overall Study Study Sensitivity Design Exposure Window Regression Exposure Comparison
Aduq-iiile
AdcquatG
! iHisM
'Highl
IHlgfi'
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Adequate
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Kashma, 2020.
ACCEPT birth cohort (2010-2011.
2013-201 SI, Greenland, 482
mother-infant paits
ALSPAC (1331-1992), England, IS
Bja'raqaard-Olas
ef al.. 2019,
S0S364S
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Fume IslarKfc (1334-1933), I
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H1gh| Adequate
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Medium) Adequate
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CWrart 1
Figure 3-32. Sex stratified head circumference results for 8 epidemiologic
studies (boys above reference line, girls below). For additional details see
HAWC link.
Abbreviations: HC= Head Circumference
aStudies are sorted first by overall study confidence level, then by Exposure Window(s) examined.
bXiao et al. (2019) in blue text report head circumference z-score data.
cFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
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Head Circumference Summary
Overall, 8 of 14 total studies showed some head circumference deficits in either sex or in the
overall population in relation to PFHxS exposures. There was fairly consistent evidence of
associations in the overall population as 6 out of 12 studies (including five of the nine high and
medium confidence studies) reported some evidence of deficits for at least one exposure
comparison. Overall, one of the three studies with categorical data showed evidence of an
exposure-response relationship in either sex or in the overall population. There was no pattern
among the null studies based on study sensitivity and exposure levels/contrasts. There was not a
consistent pattern by sample timing among those studies demonstrating head circumference
deficits, as half other studies in both the overall population and sex-specific analyses that were
based on late biomarker sampling.
Small for Gestational Age and Low Birth Weight
Seven epidemiological studies included here examined associations between PFHxS
exposure and different dichotomous fetal growth restriction endpoints, such as SGA (or related
intrauterine growth retardation endpoints) fChangetal.. 2022: Wikstrom etal.. 2020: Xu etal..
2019: Hamm etal.. 20101 or low birth weight (LBW) fHiermitslev etal.. 2020: Meng etal.. 2018:
Manzano-Salgado etal.. 2017al (see Figure 3-33). Two studies were high confidence fWikstrom et
al.. 2020: Manzano-Salgado etal.. 2017al. three were medium confidence fHiermitslev etal.. 20201:
Mengetal. (20181: (Hamm etal.. 20101 and two were low confidence (Chang etal.. 2022: Xu etal..
20191. Two of these studies had good study sensitivity fWikstrom etal.. 2020: Manzano-Salgado et
al.. 2017a). four had adequate study sensitivity (Chang etal.. 2022: Hiermitslev etal.. 2020:
Wikstrom etal.. 2020: Manzano-Salgado etal.. 2017al while one was deficient fXu etal.. 20191. All
seven studies reported results in the overall population, while two fWikstrom etal.. 2020:
Manzano-Salgado etal.. 2017al provided results in both the overall population and across sexes.
Three fWikstrom etal.. 2020: Xu etal.. 2019: Hamm etal.. 2010) of four SGA studies showed
some adverse associations (see Figure 3-34) in relation to PFHxS. The medium confidence study by
Hamm etal. (2010) showed increased odds (OR=2.35; 95%CI: 0.63, 8.72) in the overall population
among fertile 3 compared to fertile 1. The low confidence by Xu etal. (2019) reported showed an
even larger statistically significant odds of SGA (OR=9.14; 95%CI: 1.15, 72.8 per each ln-unit
increase). Although their overall population results were null, some of the quartile results were
elevated (OR=1.76; 95%CI: 0.79, 3.90) but in a non-monotonic fashion. Their results based on a ln-
unit increase were largely null for both sexes. In addition to the Wikstrom etal. (2020) study, two
other studies in the overall population were null (Chang etal.. 2022: Hiermitslev etal.. 2020). The
Manzano-Salgado etal. (2017a) study was null for the overall population, girls, and boys.
Two studies reported largely null results between PFHxS and LBW in the overall population
fHiermitslev etal.. 2020: Manzano-Salgado etal.. 2017al as did the medium confidence study by
Mengetal. f20181 based on their quartile comparisons. Based on the continuous exposure
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1 expressions, Meng etal. f2018) reported a larger risk (0R=1.5; 95%CI: 0.7, 2.9 per each ln-unit
2 increase) for a very LBW (i.e., <2,260 grams) measure compared to the typical LBW definition of
3 <2,500 grams (0R=1.3; 95%C1: 0.8, 2.1). Although term LBW results were null in girls in the
4 Manzano-Salgado etal. f2017al study, non-significant increases were seen amongst boys (OR=l,33;
5 95%CI: 0.47, 3.82 per ln-unit increases).
VI.
Participant selection ¦
Exposure measurement -
Outcome ascertainment
Confounding -
Analysis -J
Sensitivity -
Selective Reporting -
Overall confidence -
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-33. Study evaluation results for 7 epidemiological studies of small for
gestational age and low birth weight and PFHxS. For additional details see
HAWC link.
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Msnzano Sa'gatlo INMAcohort (2003 2C08) '202
e; al.. 2017 mother Infant oairs
4235480
g el al. 2018. DNBC <1996-2002). Oennsik. 25
Nsmoitis (n=3T)
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# 3 [SGA'LBW Relative "ilsk J
© 8 (SGA/IBW Relative Risk < RR)] p-
KH 95% nonfidenoa interval
Newborns (n—37)
is (n»182>
Manzanp-SaJgado INMA cohort (2003 2M&: '202
ct ai„ 201? fnothei-lntantjMilis
4233486
Trimester t 1,33
07-211101 Sweden. 1533
QiJSitlbti
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Newborns (n-42S>
Nev/Ooins (n=42o)
Newnoms (rf4?0>
Newborn boys ;n=o2;
Newborn boys (r\-80! j
Que nils 3 Newborn boys (n=8Qt)
Quarcile 4 Newborn boys (iv-901 j
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Fetal Growth Restriction Summary
Among the most accurate fetal growth restriction endpoints examined, there was
reasonably consistent evidence for birth weight deficits across different measures and types of
PFHxS exposure metrics considered. Some mean or standardized birth weight deficits were
detected in 20 of the 34 included studies, including 14 out of 16 medium and high confidence
studies. Inverse associations were also noted in 17 of 31 studies that examined mean birth weight
associations in the overall population (5 high; 5 medium and 4 low confidence). Although smaller
birth weight deficits were seen in the five high confidence studies ((3= -11 to -22 g), the remaining
studies reporting reductions ranged from -30 to -93 grams per each ln-unit PFHxS increase.
Similarly, 9 out of 12 sex-specific analyses, including 5 out of 9 medium and high confidence studies,
showed deficits in either or both male and female neonates. Results were larger based on
categorical comparisons in two low confidence studies ((3 range: -108 and -109 g for highest
tertiles), but also consistent among these sex-specific studies expressing results per each ln-unit
increase in both medium ((3 range: -45 to -71 g) and high confidence studies ((3 range: -11 to -14
g)-
The findings in the overall population were supported by meta-analysis results of a larger
study subset (n = 27) presented above (and detailed in Appendix C) that showed a small deficit ((3=
-7.7 g; 95% CI: -14.8, -0.5 per each ln-unit increase) in analyses of the overall populations. This
overall meta-analysis birth weight result ((3= -7.7 g) was comparable to analyses restricted to just
the high ((3= -6.8 g) and medium ((3= -9.6 g) confidence studies. The analysis restricted to only
studies with some early pregnancy ((3= -7.3 g) biomarkers was also comparable in magnitude to
these results. This early pregnancy data subset would be less prone to any potential impact of bias
related to pregnancy hemodynamics. As noted above, many of the individual study results lacked
precision and were not statistically significant, especially the sex-stratified results. Two of the 16
medium and high confidence studies examining categorical data for the overall population or
different sexes, showed evidence of exposure-response relationships, which was supported by the
findings based on continuous PFHxS exposure data.
The evidence for birth length deficits was also consistent, with all four of the high
confidence studies showing deficits with increasing PFHxS exposures. However, among the high
confidence studies based on the overall populations, the birth length results were often imprecise
and fairly small in magnitude (-0.14 to -0.43 cm). In contrast, the results for PFHxS studies of head
circumference and ponderal index were largely null. Across these different endpoints there is some
evidence of an association between fetal growth restriction and PFHxS exposure, but important
uncertainties remain. For example, there was a pattern suggestive of potential bias in studies with
biomarker samples collected after pregnancy (i.e., postpartum), given these studies showed larger
deficits in birthweight. Some additional uncertainty also remains regarding whether any other
PFAS co-exposures are likely to be confounders in these studies; as such, this could potentially
affect study findings.
This document is a draft for review purposes only and does not constitute Agency policy.
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Growth restriction - postnatal growth finfancv and early childhood up to 2 years of age!
Postnatal Weight, Height, and Head Circumference - Background
Thirteen studies were identified that assessed postnatal growth in relation to PFHxS (see
Figure 3-35) with each examining some measures of infant weight and/or height. Two
uninformative studies (Tin etal.. 2020a: Alkhalawi etal.. 20161 are not further considered here
mainly due to deficiencies or critical deficiencies in participant selection, confounding, analysis, and
study sensitivity. As shown in Figure 3-37 and Table 3-18, 5 of the 11 included studies were
considered high confidence fGao etal.. 2022: Zhang etal.. 2022: Starling etal.. 2019: Shoaffetal..
2018: Manzano-Salgado etal.. 2017bl. while three each were medium flensen etal.. 2020a:
Gvllenhammar et al.. 2018: Maisonetetal.. 20121 and low confidence f Gross etal.. 2020: Cao etal..
2018: Lee etal.. 20181. Of the 11 postnatal growth studies, study sensitivity in three were
considered adequate (Gao etal.. 2022: Starling etal.. 2019: Manzano-Salgado etal.. 2017b). while
four each were good (Gvllenhammar et al.. 2018: Lee etal.. 2018: Shoaff etal.. 2018: Maisonetetal..
20121 and deficient (Zhang etal.. 2022: Gross etal.. 2020: Tensen etal.. 2020a: Cao etal.. 20181
largely owing to small exposure contrasts.
Although there was some overlap across studies, limited serial measures during infancy as
well as inconsistent age at examinations and analyses may limit some comparisons here. For
example, Zhang etal. T20221 examined growth up to 12 months and Starling et al. T20191 took
measurements at 5 months only. Manzano-Salgado etal. (2017b) examined growth from birth until
6 months of age. Lee etal. (20181 examined postnatal growth at 2 years, while the Cao etal. (20181
analyses were based on a mean of 19 months in participants. Gvllenhammar et al. (20181 had serial
postnatal growth measures for most endpoints at 3, 6,12 and 18 months but was limited to 36
months and beyond for BMI SDS measures. Gross etal. f20201 completed examinations at 18
months, while Maisonetetal. T20121 did so at 20 months. Tensen et al. f2020al examined different
adiposity measures at 3 and 18 months, while Gao etal. (20221 examined growth trajectory based
on serial measurements at five time periods within the first 2 years (at birth, 42 days, 6 months, 12
months, and 24 months). Shoaff etal. (20181 examined postnatal growth with repeated measures at
age 4 weeks to 2 years.
This document is a draft for review purposes only and does not constitute Agency policy.
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Participant selection
Exposure measurement
Outcome ascertainment -
Confounding -
Analysis -
Sensitivity
Selective Reporting -
Overall confidence
1 ii 1 — 1 ¦ 1 1 i 1 i
Legend
| Good (metric) or High confidence (overall)
Adoquato (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Ql Critically deficient (metric) or Uninformative (overall)
* M u Iti pi e judg merits exist
Figure 3-35. Study evaluation results for 13 epidemiological studies of
postnatal growth and PFHxS. For additional details see HAWC link.
Postnatal Weight Standardized Results
In the overall population, eight postnatal studies (four high, two medium, and two low
confidence) examined PFHxS in relation to either standardized fZhang et al.. 2022: Starling etai.
2019: Gvllenhammar etal.. 2018: Shoaff etal.. 2018: Manzano-Salgado etal.. 2017bl or mean
weight measures fCao etal.. 2018: Lee etal.. 2018: Maisonet et al.. 20121 (see Figure 3-36). Three of
five studies with standardized postnatal weight measures reported some inverse associations with
PFHxS exposures, while the medium confidence Gvllenhammar et al. f2018" study of standard
deviation scores (SDS) for weight measured at 3 to 18 months was null. Results in the high
confidence study by Zhang etal. f20221 were largely null for standardized weight measures in the
overall population and both sexes, with the only association seen for increased weight among
tertile 2 exposures among girls examined up to 12 months ((3= 0.15; 95% CI: 0.05, 0.25).
The results in the high confidence study by Starling et al. (20191 for the overall population
and both sexes were largely null for both weight-for-age and weight-for-length z-scores, although
they reported a statistically significant lower weight-for-age z-score at 5 months of age (|3 = -0.17;
95%CI: -0.33, -0.01 per each ln-unit increase) among girls. The authors did show an exposure-
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response relationship for weight-for-age z-scores among girls across PFHxS tertiles (T2: (3 = -0.24;
95%CI: -0.54, 0.05; T3 (3 = -0.38; 95%CI: -0.69, -0.08), butthe opposite was seen for boys (T2: (3 =
0.31; 95%CI: -0.01, 0.62; T3: p = 0.26; 95%CI: -0.09, 0.61). Results were smaller in magnitude but
fairly comparable for weight-for-length z-scores albeit in a non-monotonic fashion for girls ((3
range: -0.20 to -0.23).
Compared with tertile 1, the high confidence study by Shoaffetal. T20181 detected small
nonstatistically significant deficits in z-scores for several outcomes including weight-for-age and
weight-for-length for PFHxS tertile 3 ((3 range: -0.15 to -0.16). They also reported non-significant
results per each ln-unit increase for both weight-for-age ((3 = -0.12; 95%CI: -0.29. 0.06) and
weight-for-length ((3 = -0.12; 95%CI: -0.26. 0.01) z-scores. Although they were also not statistically
significant, small weight z-score changes from birth to 6 months of age were also reported in the
Infancia y Medio Ambiente (INMA) birth cohort ((3 = -0.09; 95% CI: -0.22, 0.03 per each ln-unit
increase) from the other high confidence Manzano-Salgado etal. f2017b) study. These data seemed
largely driven by the findings in girls ((3 = -0.13; 95% CI: -0.29, 0.03).
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Shanghai Birln Cohort (SBC)
(2013-2016), China, 2395
mother-infant pairs
Healthy Start Stutiy (2009-2014), |Hkjh
United States. 1410 mother-infant
pairs
Trlmestei 2-3
0.017
-0.05
-a 16
-0,12
Exposure
Comparison
ln-unil(ng;'rriL)
increase
Teitile 2
Tertile 3
tn-unit (ng/mL)
Tertile 2
Tertile 3
Tertile 2
Tertile 3
In-unit (ngftnL)
# B [change in PNG z-score]
Q Q [change in PNG z-score] p-
hH 95% confidence interval
Regression coefficient
Weight-for-Age Z-Score
OVERALL POPULATION
Shanghai Biftti Cohort (SBC)
(2013-2016), China, 2395
mother infant pairs
Adequate Cohort Trimester 2-3
In-unil(ngjmL)
Tertilo 2
Tertile 3
In-unit (ng/mL)
increase
Tertile 2
Tertile 3
Shanghai Birth Cohort (SBC)
(2013-2016). China, 2395
mother-infant pairs
-0.24
-0,38
In-unit(ngjmL)
increase
Tertile 2
Terlile 3
In-unlt (rig/ml.)
Tertile 2
Tertile 3
-0.02
-D.12
-0.03
-0.15
In-unit (ng/mL)
Tertile 2
Tertile 3
in-unit (ng/mL)
Tertile 2
Tertile 3
Weight-for-Length Z-Score
OVERALL POPULATION
l-unii (ngmiL)
Tertile 2
Tertile 3
-0 08
-0.23
In-unit (ng/mL)
Tertile 2
Tertile3
m-unil (ng.'mL)
In-unit (ng/mL)
increase
in-unil (ng/mL)
ln-un>( (ng.'mL)
In-unit (ng/mL)
In-unit (ng/mL)
In-unit (ng/mL)
Weight Gain_ OVERALL POPULATION
-0.04
-0,13
. BOYS
GIRLS
-0.0 -0.5 -0.4 -0.3
0.2 0.3 0.4 0.5 0.6 0 7
Figure 3-36, Standardized postnatal weight results for PFHxS epidemiological
studies. For additional details see HAWC link.
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
bAge at Outcome Measurement: (Gvllenhammar et al., 2018) at 3 months, 6 months, 12 months, and 18 months
(ordered top to bottom); (Starling et al., 2019) at 5 months; (Zhang et al., 2022) between 42 days and 12 months;
(Shoaff et al., 2018) at 4 weeks, 1 year, and 2 years; (Manzano-Salgado et al., 2017b) at 6 months.
cSolid black lines divide the figure into four categories. Listed from top to bottom they are as follows: Weight-for-
Age Z-Score, Weight-for-Length Z-Score, Weight Z-Score, and Weight Gain Z-Score
dWithin each category, overall population is located above the first blue dashed lines, boys are between the two
blue dashed lines, and girls are below the second blue dashed line.
eFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
This document is a draft for review purposes only and does not constitute Agency policy,
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Postnatal Weight_Mean - Results
Three studies examined associations between PFHxS exposures and mean postnatal weight
measures fCao et al.. 2018: Lee etal.. 2018: Maisonetetal.. 20121 (see Figures 3-37). The low
confidence study by Lee et al. T20181 detected associations infant weight at age 2 ((3= -200 g; 95%
CI: -420, 20} per each In-unit increase and monotonically across PFHxS quartiles (P range: -160 to -
360 grams). For example, a large difference was detected for quartile 4 (>1.81 ng/mL) (P= -360 g;
95% CI: -740, 20) compared with quartile 1 (<0.77 ng/mL). They detected weight change
associations from birth to age 2 per each ln-unit increase (|3= -170 g; 95% CI: -330,160) but was
considerably smaller among quartile 4 exposures (f>= -60 g; 95%CI: -400, 270). The Cao et al.
f20181 study was null for all comparisons, but they did report an imprecise postnatal (mean = 19
months) weight difference for tertile 2 (P= -145 g; 95% CI: -584, 294) in the overall population.
Tertile 2 results were imprecise and in opposite directions for boys ((3= -387 g; 95% CI: -916,143)
and girls ((3= 155 g; 95% CI: -605, 915), while there was some suggestion of reduced weight in
tertile 3 among girls ((3= -101 g; 95% CI: -811, 608). The medium confidence study of girls from
the ALSPAC study (Maisonet et al.. 2012) were largely null and inconsistent across tertile (p range: -
32 to 63 g) over the first 20 months of life.
Overall Study Study Sensitivity
Confidence
Exposure Regression Exposure
Window Coefficient Comparison
Environment and Development of
Children (EPC) Cohort, South Korea,
645 mother-child pays
62.86
-360
Tertile 3
Quartile 4
Regression coefficient
0 (5 {change in mean growct weight {g)J
£ p [change in mean grcruvtn weight
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Postnatal Weight Summary
Five of eight studies in total showed some evidence of associations in the overall population
or other sex for either mean or standardized infant weight measures. This included one high
confidence study fShoaffet al.. 20181 showing associations for both weight for age and weight for
length measures in the overall population and both low confidence studies. There was a
preponderance of inverse associations between PFHxS and infant weight among girls only (based
on three of four, including two of three weight standardized studies and one mean weight study).
No patterns across the few studies with associations were evident
Postnatal Height Standardized Results
In the overall population, five postnatal studies (two high, one medium, and two low
confidence) examined PFHxS in relation to either standardized fZhang etal.. 2022: Gvllenhammar
etal.. 2018: Shoaff etal.. 2018) or mean height measures (Cao etal.. 2018: Lee etal.. 2018) (see
Figures 3-38). Five studies in total examined postnatal height measures in relation to PFHxS
including three that examined standardized postnatal height (Zhang etal.. 2022: Gvllenhammar et
al.. 2018: Shoaff etal.. 20181. None of these studies showed any evidence of an association between
PHFxS in relation to standardized infant height measures. The medium confidence by
Gvllenhammar et al. f20181 was null for standardized height measures in the overall
population. The high confidence study by Zhang etal. T20221 were null for standardized height
measures in the overall population and both sexes. The high confidence study by Shoaff et al.
(2018) was largely null for length-for-age z-score for continuous ((3= -0.07; 95% CI: -0.27, 0.14) for
each ln-unit increase and categorical PFHxS exposures (T3 ((3 = -0.13; 95%CI: -0.52, 0.27)).
This document is a draft for review purposes only and does not constitute Agency policy.
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POPUP (1096-5011) .V
Snongnal Birth Cohort (SBC)
[2013-20161. Oima. 2395
moUwsr-lntenl pairs
-0,0?
-0,05
OVERALL POPULATION
Tartile 2
Tertlle 3
In-unil (n^mD
Irvuiili ('ig/int)
In-ooh (og/ml i
increase
In-unii (naftnL)
increase
Teolle 1
Tertile 3
ln-um!(ng/mL)
0.092
-0.023
# 3 [change in height Z Scare]
0 a [change In heigh! Z-Scorel p<0.Cl5
_^L& JLa -1U JL2 JLL
Figure 3-38. Standardized postnatal height results for PFHxS epidemiological
studies. For additional details see HAWC link.
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
bAge at Outcome Measurement: Gvllenhammar et al. (2018) at 3 months, 6 months, 12 months, and 18 months
(ordered top to bottom); Zhang et al. (2022) between 42 days and 12 months; Shoaff et al. (2018) between 4
weeks and 2 years.
cZhang et al. (20221 and Shoaff et al. (2018) examined length-for-age z-score.
dOverall, population is above the solid black line, while sex-stratified data is below. Within sex-stratified data, boys
are above the dashed line, girls below.
eFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
Postnatal Height Mean Results
Two studies fCao etal.. 2018: Lee etal.. 20181 examined associations between PFHxS
exposures and mean postnatal height measures (see Figures 3-39). The low confidence study by
Lee et al. f20181 reported statistically significant decreased mean height ((3= -0.84 cm; 95% CI:
-1.26, -0.42 per each ln-unit increase) at age 2 as well as reductions in height ((3= -0.89 cm; 95%
CI: -1.45, -0.33 per each ln-unit increase) from birth to age 2. They also detected exposure-
response relationships and statistically significant infant height reductions in quartiles 3 and 4 for
both weight at 2 years (Q4 j3= -1.34 cm; 95% CI: -2.09, -0.60; Q3 |3= -0.82 cm; 95% CI: -1.57,
-0.07) and weight change from birth to 2 year (Q4 (3= -1.63 cm; 95% CI: -2.62, -0.64; Q3 (3= -1.20
cm; 95% CI: -2.10, -0.30). The low confidence study bv Cao et al. f20181 reported non-monotonic
increased postnatal length in the overall population ((3 range: 0.95 to 1.42 cm across
tertiles). Similar results were seen for girls (P range: 1.32 to 2.01 cm across tertiles) but were null
for boys ((3 range: 0.30 to 0.32 cm across tertiles).
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Zhoukou City Longitudinal Birth
Cohort (2013-2015), China. 282
mother-intent pairs
Overall Study Study Sensitivity Design Exposure Regression Exposure
Confidence Window Coefficient Comparison
ILowi Deficient Cohort At birth 1,42 Tertile 2
Regression coefficient
OVERALL POPULATION
I fi [change in Height]
) P |change in height] p«0.05
-4 95% confidence interval
Environment and Development of
Children (EDC) Cohort, South Korea,
645 mother-child pairs
Cohort 0-2 years -0,27
-0,82 Quartite 3
-1,34 Quarlite4
-0.84 Iri-unit {ng/niL)
-0.76
Ouartiia 2
Quartite 3
Quartite 4
BIRTH TO 2 YRS"
Zhoukou City Longitudinal Birth
Cohort (2013-2015), China. 282
rtiothei-irifsnt pairs
Tertile 3
Tertile Z
Tertile 3
-3 -2
Figure 3-39. Mean postnatal height results for PFHxS epidemiological studies.
For additional details see HAWC link.
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
bAbove the solid black line is overall population data, while below is sex-stratified. Within the sex-stratified data,
above the dashed blue line is boys, below is girls.
cFor Lee et al. (2018) data, above the black dashed line is data referring to at two years, below the line is data
referring to change from birth to 2 years.
dFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
This document is a draft for review purposes only and does not constitute Agency policy,
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Rapid Weight Gain
Four high confidence studies fGao etal.. 2022: Starling etal.. 2019: Shoaff etal.. 20181:
Manzano-Salgado etal. f2017bl examined different rapid weight gain measures in relation to
PFHxS (see Figures 3-40 and 3-41). In the Health Outcomes and Measures of the Environment
(HOME) study, Shoaff etal. T20181 examined rapid growth based on weight z-scores in relation to
PFHxS in the overall population. In the Healthy Start study, Starling etal. (2019) examined different
rapid weight gain measures in relation to PFHxS for the overall population and both sexes. In the
Shanghai Birth Cohort, Gao etal. (2022) examined various measures of growth trajectories in the
overall population and across sex for various postnatal growth measures. In the INMA Birth Cohort
Study, Manzano-Salgado etal. f2017bl examined rapid growth from birth to six months.
Two of the four studies showed some increased odds of rapid growth measures with
increasing PFHxS exposures, although results were not always internally consistent Shoaff et al.
(2018) reported null associations for odds of weight z-score differences across tertiles (e.g., tertile
3 OR=0.95, 95%CI: 0.65,1.40). The study by Manzano-Salgado etal. (2017b) was also null for rapid
growth (OR=0.87; 95%CI: 0.72,1.04). The study by Starling et al. (2019) reported an OR of 1.49
(95%CI: 1.02, 2.18) for rapid weight gain per each ln-unit increase based on the weight-for-age z-
score data but was null for weight-for-length z-score (OR=0.95; 95%CI: 0.63,1.44).
In the Gao etal. T20221 study, most relative risks were null based on standardized weight
for age and weight for length measures in the overall population and both sexes. Compared to the
moderate-stable referent, Gao etal. (2022) reported elevated odds for the low-rising weight-for-age
z-score (WAZ) trajectory (OR=1.92; 95% CI: 1.19, 3.08 per each ln-unit PFHxS increase) in the
overall population. This seemed driven by results in males (OR=2.96; 95%CI: 1.51, 5.82 per each ln-
unit PFHxS increase) given that females showed null associations. Using a weighted quantile sum
mixture approach, they reported a statistically significant inverse association (OR=1.53; 95%CI:
1.13, 2.06 per each ln-unit PFAS Sum increase) for WAZ among low-rising participants (vs.
moderate-stable) with PFHxS having the highest weight among the PFAS mixture constituents.
Among males only, Gao etal. (2022) reported increased odds for weight-for-length z-score
(WLZ) trajectory in low-rising (OR=2.43; 95% CI: 1.00, 5.87 per each ln-unit PFHxS increase) and
low-stable participants (OR=2.04; 95% CI: 0.70, 6.02 per each ln-unit PFHxS increase). Compared to
the moderate-stable referent, Gao etal. f20221 reported elevated odds in females only for the
moderate-falling (OR=1.85; 95% CI: 0.97, 3.47 per each ln-unit PFHxS increase) and high-rising
length-for-age z-score (LAZ) trajectories (OR=1.61; 95% CI: 0.41, 6.38 per each ln-unit PFHxS
increase). The odds of LAZ for high-rising participants from the overall population was null in the
single pollutant model but was elevated for the PFAS mixture metric based on a weighted quantile
sum approach (OR=1.59; 95% CI: 0.90, 2.82 per each ln-unit PFHxS increase), with PFDA having the
highest weight among the PFAS mixtures.
Although most were not statistically significant, Gao etal. f20221 reported inverse
associations in the single PFAS models for head-circumference-for-age z-score for high-rising,
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moderate-rising, low-rising, and low-stable vs. moderate-stable participants (OR range: 0.46 to 0.71
per each ln-unitPFHxS increase). They also reported a statistically significant inverse association
(OR=0.37; 95%CI: 0.18, 0.72) for low-rising vs. moderate-stable groups based on a PFAS mixture
metric (per each ln-unit increase) using a weighted quantile sum approach.
Rapid Weight Gain Summary
Overall, two of four studies showed increased odds of rapid growth in relation to PFHxS
exposures. Although results were a bit mixed across different growth trajectory measures, there
was only evidence of inverse associations between PFHxS and rapid growth as measured by head
circumference z-scores in the Gao etal. f20221 study. In contrast, most of the associations they
detected using weight for age, weight for length and length for age z-scores showed increased risk
of rapid growth per each ln-unit PFHxS increase. These associations were most evident among the
weight and height measures among the participants with a low baseline growth trajectory followed
by a rapid increased trend afterward (i.e., low-rising group). These data were supported by another
study (Starling et al.. 2019) that reported a statistically significant OR (1.49; 95%CI: 1.02, 2.18 per
each ln-unit increase) for rapid weight gain based on weight-for-age z-score data only. Both of these
studies are consistent with a hypothesis that rapid weight growth in childhood that may have
followed intrauterine growth retardation from PFHxS exposures. These individuals may be at most
risk for metabolic syndrome, as evidenced by changes in obesity and other health effects later in
life.
This document is a draft for review purposes only and does not constitute Agency policy.
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HOME I
D So maCrowJi (fp
i io Temw 1 Rami O
0115 nm*l3 lineal 0»
Dwcrpllwi
Her cj:« Ocvfi m-JCi-
tr»ii~i«~<*! Fi«« u'rwr -ui
» R»i« jMiJkMHIIi
.1 IWI7VI
•>%** ;-Ot,L| R*t*2 Qwt o -37f| n ¦+_' *. C<9M!i
k '-vYriil i-H Pa-ij in Gi'ii
k- ;-^w* i -«v4«> i n*«B .«
»111 ««»aw <• ¦ -T> •«
O'-WX
1 onti pp;vF»-n»iii-T5 vtMcraau fUM in*J2«l
hn4»v!Ual SMr >3«n 2>HK
ah v. •.«'/«ju Imcmirum, iJiiifivie*r»'0'M
P*"
'm,,„J.X32. a-nl-Bk-liCvtw.iaJ-JKIC'i
» "ulitl •/! MseoiMinwinHfll
i* lM> v> Mwwuu 5kJi« ur2* I ¦
2«ii «¦-.«*
w ;i»vt| 'H "3 »< It*-£*21
r. .'-o'liii i- 'iff: ttMxmnfiUiM in*?5J:>
»i<»ll4| uwAMattrOI rtWowu^-SUukiiir^Ui
Figure 3-40. Postnatal rapid growth (weight-for-age and weight-for-length z-
score) results for PFHxS epidemiological studies. For additional details see
HAWC link.
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
bAge at Outcome Measurement: Starling et al. (2019' at 5 months, Gao et al. (2022 modeled data (collected at 42
days, 6 months, 12 months, and 24 months).
cWeight-for-Age Z-Score data above the black reference line; weight-for-length below.
dOverall population data above the blue line; Sex-stratified data below,
eSex-Stratified data: male infants above the blue dash-dotted line; females below,
fQuantile 2 in Starling et al. (2019) represents dichotomized exposure at median (quantile 1 referent: LQD-0.1
ng/mL; quantile 2: 0.2-3.5 ng/mL).
gThe following Gao et al. (2022) results have been truncated: 1.92 [1.19-3.08], 2.96 [1.51-5.82], 2.43 [1-5.87], and
2.04 [0.7-6.02],
hFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
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Study Population Overall Study Study Sensitivity Design
Exposure Regression
Exposure
Population description
Confidence
Window Coefficient
Comparison
Regression coefficient
Gaoem 2022, Shanghai Blrtr Cohort 12013-2016), Highi Adequate CofiSlt
Mmester 3 112
m-wiit
High-Rising vs. Moderate Stable
10412913 China 3*26 piaqnafil women (Pipspeclive]
meass
109
ln-iirit(ng'T\l!
Moderate-Falling vs Moderate Slafce
OVERALL
'
0.5
in-unit ing'TnLj
High-Rising vs. Moderate Stable
1
07
ln-unit (ng'mki
Mixtoats-Mling vb Moderate Stah-R
•
MALES
1
1,61
Irwjnit iiig*nU
Hfgh-Rlsing vs. Moderate Stable
1 +
1.85
In-ufllt jns"nL|
hdeass
Mixte'ato-Mling vs. Moderate Stat e
0.4&
lo-Ufiit (njj'BiLj
Ne.vDcrns (High-Rising vs Moderate Stabiei
increase
# [OckIs Ratio to Rap*] Giowth|
q.n
i
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
1 Postnatal Head Circumference
2 Three studies examined postnatal head circumference in relation to PFHxS fZhangetal..
3 2022: Cao etal.. 2018: Gvllenhammar etal.. 20181 (see Figure 3-42). Null results were detected in
4 the high confidence study by Zhang etal. f2022) for head circumference-for-age Z score per each ln-
5 unit PFHxS increase ((B = -0.08; 95%CI: -0.19, 0.02). The medium confidence study by
6 Gvllenhammar et al. T20181 showed monotonic head circumference-for-age Z increases as children
7 aged from 3 to 18 months (p range: 0.05 to 0.12). The low confidence study by Cao etal. (2018)
8 reported non-monotonic increased postnatal head circumference in the overall population (|3
9 range: 0.90 to 1.33 cm across tertiles). These results were comparable across boys ((3 range: 0.97 to
10 1.27 cm across tertiles) and girls ((3 range: 0.78 to 1.34 across tertiles). Overall, two of three studies
11 showed some evidence of increased postnatal head circumference in relation to PFHxS exposures.
«•*»{*» fl»iti e««*i «S8G> ptyn)
Okw ?3«
•AMmMldM |Wr*
£lK*fci*J Cay LMvludioii ""M
CfcHMeiai wf.«a m
pan
Tor Ma 1
q H mc| s-c m r
UVtKALl PWVLAIKM
Ootm
DrfUiHit Crfm
tninHua^riLi
Tr.Ur. 3
i«Kje«i cwon
Cry 9>ri
Cc»n. gwa-WHK Oww. JV
•milmi inCaii |nu
hurilifjittt)
Figure 3-42. Postnatal head circumference results for PFHxS epidemiological
studies. For additional details see HAWC link.
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
bAge at Outcome Measurement: Gvllenhammar et al. (2018) at 3 months, 6 months, 12 months, and 18 months
(ordered top to bottom); (Zhang et al., 2022) between 42 days and 12 months; Cao et al. (20181 at a mean of 19
months.
cZhang et al. (2022: reports head circumference-for-age Z-Score, Gvllenhammar et al, (2018) report head
circumference Z-Score, and Cao reported odds ratios.
dOverall population is above the solid black line, while sex-stratified data is below. Within sex-stratified data, boys
are above the dashed blue line, girls below,
eCao et al. (2018' upper and lower bounds have been truncated. For overall population, the Tertile 2 bounds are
[0.42, 2.26] and the Tertile 3 bounds are [0, 1.81]. For boys, the Tertile 2 bounds are [0.1, 2.43] and the Tertile 3
bounds are [-0.22, 2.16], For girls, the Tertile 2 bounds are [-0.16, 2.84] and the Tertile 3 bounds are [-0.62, 2.18].
fFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
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Postnatal Adiposity/Body Mass Index/Ponderal Index/Weight Status
Five studies fZhang et al.. 2022: Gross etal.. 2020: Tensen etal.. 2020a: Starling etal.. 2019:
Shoaff etal.. 20181 enabled examination of different measures of infant adiposity such as body mass
index (BMI), overweight status, and ponderal index (see Figure 3-43). Three of the five studies were
null f Zhang etal.. 2022: Tensen etal.. 2020a: Starling etal.. 20191 for associations in the overall
population, while the remaining two showed decreased measures of adiposity in relation to
PFHxS. For example, the low confidence study by Gross etal. (20201 showed an inverse but non-
significant association between overweight status at 18 months (OR=0.75 g; 95% CI: 0.30 to 1.85)
and dried blood spot PFHxS levels above the mean (compared to below the mean) with similar
relative risks among boys (OR=0.74; 95%CI: 0.17, 3.24) and girls (OR=0.68; 95%CI: 0.15. 3.12). The
high confidence study by Shoaff et al. f20181 exposure-response relationship detected for PFHxS
and BMI z score across tertile 2: ((3= -0.12; 95%CI: -0.37, 0.13) and tertile 3 ((3= -0.22; 95%CI:
-0.47, 0.03) and per each ln-unit increase ((3= -0.12; 95%CI: -0.26, 0.01).
The results were a bit more mixed when examined by sex, with two of three sex-specific
studies showing some suggestion of increased adiposity among boys only. For example, the medium
confidence by Tensen etal. f2020al reported null associations at age 3 and 18 months for
standardized (i.e., SDS) postnatal waist circumference, body mass index, and ponderal index
measures in their overall population. Although they did not detect statistically significant
interactions by sex for any endpoints evaluated, slight non-significant increases in boys BMI ((3=
0.13; 95%CI: -0.34, 0.60 per each ln-unit increase) and Ponderal Index ((3= 0.34; 95%CI: -0.14, 0.82
per each ln-unit increase) SDS scores were noted. The high confidence study by (Starling etal..
20191 was null for infant adiposity per each ln-unit PFHxS increase among the overall population
((3= 0.01 fat mass increase %; 95%CI: -0.67, 0.68). Results were divergent for males ((3= 0.54 fat
mass increase %; 95%CI: -0.51,1.58 per each ln-unit increase) versus females ((3= -0.42 fat mass
increase %; 95%CI: -1.31, 0.47 per each ln-unit increase). Similar results were seen in their tertile
analyses with more adiposity in males ((3 range: 0.89 to 1.90% fat mass increase) and females ((3=
-0.85 to -1.11% fat mass increase). The high confidence study by (Zhang etal.. 20221 reported null
associations for PFHxS and BMI-for-age z-scores ((3= -0.01; 95%CI -0.12, 0.09 per each ln-unit
increase) in the overall population, males ((3= -0.01; 95%CI -0.12, 0.09 per each ln-unit increase)
and females ((3= 0.10; 95%CI: -0.01, 0.20 per each ln-unit increase).
Postnatal Adiposity Summary
Overall, none of the five studies in the overall population reported increased adiposity with
increasing PFHxS exposures up to age 2 years. However, two of three studies in boys did show
some suggestion of increased adiposity in relation to PFHxS exposures. None of the three studies in
girls reported increased adiposity.
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Regression Exposure
Coefficient Comparison
0.13
0.03
lit (ng.'mL!
lit(ng'mL)
3Ml (overall population)
BMI (boys) I
. # (3 [change in adiposity measures]
O P (change in adiposity measures] p<0.05
H95% confidence interval
Shanghai Birth Cohort (SBC)
(2013-2016). China. 2395
mother-infant pairs
-0.12
-0.22
-0.01
Tertile 2
Tortile 3
fl-unit(ng.'mL)
0.02 Tertile 2
-0.09 Tertile 3
-0:01 ki-unit(ng/n»L)
0.02
-0.09
Tertile 2
Tertile 3
BMI Z-Score (overall pop)
BMI-for-Age Z-Score (overall pop)
BMI-for-Age Z-Score (boys)
Healthy Start Study (2009-2014),
United Stales. 1410 iruiUier-infanl
Tertile 2
Tertile 3
Tertile 2
Tertile 3
BMI-for-Age Z-Score (girls)
Adiposity (overall pop)
Tertile 2
Tertile 3
0.08
0.34
Tertile 2
Tertile 3
'n-unit (ng'mU)
in-unit (ng'mL)
Ponderal Index (overall pop). _
Ponderal Index (boys) .
. Starting Early Program (StEP)
Cohort, United States. 98
• •mother-tnlarrt'patrs
Ponderal Index (girls)
Weight Status (overall pop)
Weight Status (boys)
Weight Status (girls)
0J M
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
decreased postnatal head circumference in relation to PFHxS exposures. In contrast, two of them
showed increased postnatal head circumference. Similarly, none of the five studies in the overall
population reported increased adiposity in relation to PFHxS as two studies showed decreased
measures of adiposity. The results for rapid growth measures were a bit mixed but two of four
studies showed increased odds of rapid growth in relation to PFHxS.
Although few studies examined exposure-response relationships based on categorical data
in the overall population or across sexes, three different studies did show dose-dependence for
some measures such as infant weight (one of six studies), height (one of four studies) and adiposity
(one of three studies). No study characteristics were obvious explanatory factors for between-study
heterogeneity. Few patterns by sex were evident outside a preponderance of inverse associations
between PFHxS and infant weight among girls. There was also evidence in two of three studies in
boys of increased adiposity. However, limited exposure contrasts and statistical power may have
hampered the ability to detect associations small in magnitude especially among the sexes. In
summary, the evidence was mixed across various postnatal measures and different examination
windows, with only minimal evidence of exposure-response relationships to support the
continuous exposure scaled results. One challenge in evaluating consistency across heterogeneous
studies includes disparate periods of follow-up and assessment (e.g., childhood age at examination).
Table 3-18. Summary of 11 epidemiologic studies of PFHxS exposure and post-
natal growth measured
Author
Study
location,
years
Sample
size
Median
exposu re
(range)
in
ng/mL
Weight
Height
HC
Adiposity
Rapid
growth
High Confidence Studies
Gao et al. (2022)
China,
2013-2016
1,350
0.54
(0.21,
3.75)
'T Overall
Manzano-Salgado et
al. (2017b)
Spain,
2003-2008
1,154
0.58
(0.05,
11.01)
- Overall/
Girls
0 Boys
0
Overall
Shoaff et al. (2018)
OH, USA,
2003-2006
345
1.5
(0.1,
32.5)
- Overall
- Overall
- Overall3
0
Overall
Starling et al. (2019)
CO, USA,
2009-2014
415
0.7(0.2,
2.8)b
- Overall/Girls3
+ Boysa
0 Overall
+ Boys
-Girls
Overall
Zhang et al. (2022)
China,
2013-2016
2,395
0.53
(0, 25.4)
0 Overall/Boys
+ Girls
0 Overall/
Boys/Girls
Medium Confidence Studies
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Author
Study
location,
years
Sample
size
Median
exposu re
(range)
in
ng/mL
Weight
Height
HC
Adiposity
Rapid
growth
Gvllenhammar et al.
(2018)
Sweden,
1996-2001
381
2.4
(0.32,
26.0)
0 Overall
Maisonet et al.
(2012)
United
Kingdom,
1991—992
422
1.6
(0.2,
54.8)
-Girls
Low Confidence Studies
Cao et al. (2018)
China,
2013-2015
337
0.09
0.03,
0.31c
0 Overall/Boys
+ Girls
+
Overall/
Girls
0 Boys
+ Overall/
Girls/Boys
Gross et al. (2020)
USA, 2014
98
0.108
(N/A)d
4- Overall/
Girls/Boys
Jensen et al.
(2020a)
Denmark,
2010-2012
589
0.30
(0.08,
0.66)b
0
Overall/Girls
+ Boys
Lee et al. (2018)
S. Korea,
2012-2013
361
1.19
(0.22,
1.69)
- Overall
Overall*3
Abbreviations: N/A: not available
* Denotes statistical significance at p < 0.05; R. represents a null association; + represents a positive association; -
represents a negative association; - represents increased odds ratio;" represents decreased odds ratio
Note: "Adverse effects" are indicated by both increased ORs (-) for dichotomous outcomes and negative
associations (-) for the other outcomes.
/ Denotes multiple groups with the same direction of associations.
aExposure-response relationship detected based on categorical data.
bNo range provided but 5th-95th percentiles included.
cNo range provided but 10th-90th percentiles included.
dDried Blood spot PFHxS sample collected within 48 hours of birth.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Anoaenitctl distance
Four medium confidence studies examined the associations between PFHxS and AGD in
infants (see Figure 3-44). Reduced AGD is associated with clinically relevant outcomes in males,
including cryptorchidism, hypospadias, and lower semen quality and testosterone levels
fThankamonv etal.. 20161. but adversity of reduced AGD is less established in females. Three
studies examined boys and girls fChristensen etal.. 2021: Arbuckle et a!.: 2020: land etal.. 20171
while one included boys only (Tian etal.. 2019b). All four studies were birth cohorts in Denmark
(Lind etal.. 20171. Faroe Islands fChristensen et al.. 20211 (cross-sectional analysis within cohort
sample), Canada f Arbuckle etal.. 20201. and China fTian et al.. 2Q19bl. In Arbuckle etal. f2 0 2 01 and
Tian etal. f2019bl. AGD was measured shortly after birth (median 3.5 days). Christensenetal.
f20211 measured AGD at two weeks after the expected term date. Tian etal. f2019bl additionally
measured AGD at 6 and 12 months, and Lind etal. f20171 measured at 3 months. With greater
variability in timing of measurements, there is additional potential for misclassification with these
measures, but age at time of measurement was included in the statistical models in all studies.
Arbuckle, 2020, 6356900 -
Christensen, 2021, 9960218-
Unci 2017, 3858512-
Tian, 2019, 5390052-
S® 0s1
Legend
| Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-44. Summary of study evaluation for epidemiology studies of
anogenital distance. For additional details see HAWC link.
In Lind etal. (20171. there was a statistically significant inverse association (i.e., shorter
AGD with higher exposure) with ASD among boys. The other three studies did not report decreased
AGD, despite greater exposure contrasts (see Table 3-19). In girls, there was an inverse association
with PFHxS for ACD Lind etal. f20171. This was statistically significant with PFHxS analyzed as
continuous, although there was not a monotonic decrease across quartiles. A consistent but smaller
and non-significant association was also observed in the third and fourth quartiles for AFD. This
association is coherent with the decrease in testosterone observed in some studies (described
below in the Reproductive Effects section). However, in the other two studies fChristensen etal.,
20211: Arbuckle etal. f202 0). there was no decrease in either AGD measure with higher PFHxS
exposure.
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1 AGD is a marker of androgen exposure, and thus an inverse in AGD would be expected to
2 correspond with a decrease in testosterone. This was not observed in the two studies of
3 testosterone in male neonates, but an inverse association was observed in a study of female
4 neonates (see Male and Female Reproductive Effects). The lack of coherence for males does not
5 reduce confidence in the AGD findings due to low confidence in the reproductive hormone studies.
6 However, the inconsistency across studies results in considerable uncertainty for an association
7 with AGD.
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Table 3-19. Associations between PFHxS and anogenital distance in medium
confidence epidemiology studies
Boys
Median
Reference
Population
exposure
(IQR)
(ng/mL)
Effect
estimate
ASD
APD
Christensen et al.
(2021)
Cross-sectional
analysis within birth
cohort in the Faroe
Islands; 232 boys at 2
wks post term
Serum
0.2 (0.1-
0.3)
P (95% CI)
for In-unit
increase
0.2 (-0.3, 0.7)
NR
Lind et al. (2017)
Birth cohort in
Denmark; 299 boys at
3 months
Serum
0.3 (0.2-
0.4)
P (95% CI)
for In-unit
increase
-1.2 (-2.3, -0.2)
-0.6 (-1.8, 0.5)
Quartiles
vs. Q1
Q2: 0.6 (-1.3, 2.4)
Q3: -0.3 (-2.1, 1.6)
Q4: -0.8 (-2.7, 1.2)
Q2: 2.6 (0.5, 4.6)
Q3: 0.9 (-1.0, 2.9)
Q4: 0.1 (-2.0, 2.3)
(Arbuckle et al..
2020)
Birth cohort in
Canada; 198 boys at
birth
Plasma
1.1
(0.7-1.7)
P (95% CI)
for unit
increase
0.22 (-0.54, 0.98)
0.24 (-0.52, 1.01)
Quartiles
vs. Q1
Q2: -0.08 (-1.99, 1.83)
Q3: 0.13 (-1.80, 2.06)
Q4: 0.57 (-1.33, 2.46)
Q2:-0.91 (-2.74, 0.91)
Q3: 0.64 (-1.23, 2.51)
Q4: 0.57 (-1.30, 2.44)
Tian et al.
(2019b)
Birth cohort in China;
439 boys at birth
Plasma
2.8
(2.2-3.6)
P (95% CI)
for In- unit
increase
Birth:-0.19 (-0.97, 0.58)
6 mos: 0.69 (-1.86,3.23)
12 mos: 2.21 (-0.47,
4.89)
Birth: 0.35 (-0.55,1.26)
6 mos: 0.04 (-2.53,2.61)
12 mos: 0.60 (-2.62,
3.83)
Girls
Median
Reference
Population
exposure
(IQR)
(ng/mL)
Effect
estimate
ACD
AFD
Christensen et al.
(2021)
Cross-sectional
analysis within birth
cohort in the Faroe
Islands; 231 girls at 2
wks post term
Serum
0.2 (0.1-
0.3)
P (95% CI)
for In-unit
increase
NR
-0.1 (-0.4, 0.3)
Lind et al. (2017)
Birth cohort in
Denmark; 212 girls at
3 mos
Serum
0.3
(0.2-0.4)
P (95% CI)
for In-unit
increase
-0.9 (-1.9, 0.0)
-0.3 (-1.1, 0.4)
Quartiles
vs. Q1
Q2: -1.6 ( -3.4, 0.2)
Q3: -2.3 (-4.1, -0.5)
Q4: -1.6 (-3.4, 0.2)
Q2: 0.2 (-1.2, 1.6)
Q3: -0.8 (-2.2, 0.6)
Q4: -0.5 (-1.6, 0.9)
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Arbuckle et al.
Birth cohort in
Plasma
P (95% CI)
0.3 (-0.47,1.07)
0.14 (-0.79, 1.07)
(2020)
Canada; 205 girls at
1.1(0.7-
for unit
birth
1.7)
increase
Quartiles
Q2: 1.01 (-0.56, 2.59)
Q2: 1.23 (-0.66, 3.13)
vs. Q1
Q3: 0.31 (-1.40, 2.02)
Q3:-0.51 (-2.56, 1.54)
Q4: 0.92 (-0.94, 2.79)
Q4: 0.52 (-1.71, 2.75)
Abbreviations: ASD: AGD measured from anus to the posterior base of the scrotum; APD: AGD measured from the
center of the anus to the cephalad insertion of the penile; ACD: AGD measured from the from the center of the
anus to the top of the clitoris; AFD: AGD measured from the top of the center of the anus to the posterior
fourchette; mos: months
Gestation duration
As shown in Figure 3-47,19 informative epidemiological studies assessed PFHxS in relation
to changes in gestational duration measures. All 19 studies examined gestational age, with 10 of
these providing analyses of both preterm delivery and gestational age. Fourteen of the 19
gestational duration studies were nested case-control studies or prospective cohort studies (Yang
etal.. 2022a: Gardener etal.. 2021: Hiermitslev etal.. 2020: Huo etal.. 2020: Gao etal.. 2019:
Workman et al.. 2019: Buck Louis etal.. 2018: Meng etal.. 2018: Sagivetal.. 2018: Lind etal.. 2017:
Manzano-Salgado etal.. 2017a: Bach etal.. 2016: Maisonet etal.. 2012: Hamm etal.. 20101. and five
were cross-sectional (Bangma etal.. 2020: Eick etal.. 2020: Xu etal.. 2019: Gvllenhammar et al..
2018: Li etal.. 2017b). The 19 epidemiological studies examined here had maternal exposure
biomarkers collected either during trimesters one fBuck Louis etal.. 2018: Lind etal.. 2017:
Manzano-Salgado etal.. 2017al. two fHuo etal.. 2020: Hamm etal.. 20101. three f Gardener et al..
2021: Gao etal.. 20191 across multiple trimesters fEick etal.. 2020: Hiermitslev etal.. 2020:
Workman et al.. 2019: Meng etal.. 2018: Sagivetal.. 2018: Bach etal.. 2016: Maisonet etal.. 20121.
or had post-partum maternal or infant samples (Yang etal.. 2022a: Bangma etal.. 2020: Xu etal..
2019: Gvllenhammar etal.. 2018: Li etal.. 2017b).
Nine studies each were classified as having late (defined as trimester 2 exclusive onward)
and early sampling biomarker sampling (defined as having at least some trimester 1 maternal
sampling). Four of the five-cross-sectional studies/analyses had late biomarker sampling. Among
the 14 cohort or nested case-control studies, eight studies had early biomarker sampling
(Hiermitslev etal.. 2020: Buck Louis etal.. 2018: Meng etal.. 2018: Sagiv etal.. 2018: Lind etal..
2017: Manzano-Salgado etal.. 2017a: Bach etal.. 2016: Maisonet etal.. 20121. while six were
classified as late (Yang etal.. 2022a: Gardener etal.. 2021: Huo etal.. 2020: Gao etal.. 2019:
Workman et al.. 2019: Hamm etal.. 20101. For examination of consistency and between-study
heterogeneity, the type of statistical analyses in addition to the type of study design was evaluated.
As part of this evaluation, cross-sectional analyses are considered for any study that used maternal
serum/plasma, umbilical cord or placental post-partum PFHxS measures in relation to gestational
duration even if the data were derived from prospective cohort or nested case-control studies (e.g.,
(Yang et al.. 2022all.
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Preterm Birth
Two fHuo etal.. 2020: Manzano-Salgado etal.. 2017al of the ten preterm birth (typically
defined as <37 gestational weeks) studies reported sex-specific findings in addition to overall
population results (see Figure 3-45 and Table 3-20). Ten studies examined PFHxS and preterm
birth including six high fGardener etal.. 2021: Eick etal.. 2020: Huo etal.. 2020: Sagiv etal.. 2018:
Manzano-Salgado etal.. 2017a: Bach etal.. 2016) and four medium confidence (Yang etal.. 2022a:
Hiermitslev etal.. 2020: Meng etal.. 2018: Hamm etal.. 2010) studies. Two studies had good study
sensitivity (Meng etal.. 2018: Sagiv etal.. 2018). six had adequate study sensitivity (Gardener et al..
2021: Eick etal.. 2020: Hiermitslev etal.. 2020: Manzano-Salgado etal.. 2017a: Bach etal.. 2016:
Hamm etal.. 20101 and two were rated as deficient fYang etal.. 2022a: Huo etal.. 20201.
Six of the ten studies showed no increased odds for preterm birth in relation to PFHxS
fYang etal.. 2022a: Eick etal.. 2020: Hiermitslev etal.. 2020: Manzano-Salgado etal.. 2017a: Bach et
al.. 2016: Hamm etal.. 2010) with two reporting decreased risks (see Figure 3-46). The medium
confidence study by Hamm etal. (2010) found a statistically significant decreased exposure-
response relationship between preterm birth and the upper two PFHxS exposure tertiles (OR
range: 0.31 to 0.59). An inverse association (OR = 0.59; 95%CI: 0.33,1.06) was also detected in girls
in the largely null Manzano-Salgado etal. f2017al study.
Six studies were null for based on the overall population. The other four high and medium
confidence studies reported some increased ORs but were not always internally consistent in
direction of the effect estimates reported for different PFHxS exposure comparisons. The high
confidence Sagiv etal. (2018) study reported largely null results based on continuous PFHxS
exposures but showed some associations based on their categorical analysis that were not dose-
dependent. For example, they reported an increased OR of preterm birth for PFHxS quartile 3
(OR=1.8; 95%CI: 1.1, 3.1 for 2.5-3.7 ng/mL) and 4 (OR = 1.3; 95%CI: 0.7, 2.2 for 3.8-74.5 ng/mL)
compared with quartile one. Similarly, the medium confidence study by Meng et al. f20181 reported
no associations for the various definitions of preterm birth examined for PFHxS quartile 4 or per a
ln-unit increase. They did detect an increased OR of preterm birth for the second (OR=2.3; 95%CI:
1.1, 4.6) and third (OR=1.5; 95%CI: 0.7, 3.2) PFHxS quartiles compared with the first quartile.
However, small sample sizes limited the interpretation of these categorical data. The categorical
analysis in the high confidence Gardener etal. f20211 also found no dose-dependence but showed a
non-significant two-fold increased risk of preterm birth in quartile 2 (OR = 2.11; 95%CI: 0.76, 5.81)
relative to quartile 1.
In the high confidence study by Huo etal. (2020). associations between PFHxS and different
preterm birth measures (including overall and different sub-types) were just above the null value
based on continuous or categorical exposures for the overall population. However, an association
was seen for clinically indicated preterm births for each ln-unit increase (OR = 1.58; 95%CI: 0.82,
3.05) and for tertile 3 (OR=1.43; 95%CI: 0.66, 3.08). A small non-significant increased risk was also
seen for overall preterm birth (OR=1.33; 95%CI: 0.77, 2.27 per each ln-unit) in girls only, with
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
1 larger statistically significant associations noted among girls only for the clinically indicated
2 preterm birth subtype (OR = 2.56; 95%CI: 1.18, 5.53).
&
Participant selection
Exposure measurement
Outcome ascertainment -\
Confounding -
Analysis -1
Sensitivity -J +
Selective Reporting -
Overall confidence -
Legend
| Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-45. Summary of study evaluation for 10 epidemiology studies of
preterm birth. For additional details see HAWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
INMA. 42tO>iI pan.
4?9*-lraV>> p«»»
<338409
H J 'Ji. A a,5 i 5.5 li_
Figure 3-46. Preterm birth results for 10 PFHxS epidemiological studies. For
additional details see HAWC link.
Abbreviations: PTB= Preterm Birth
3Studies are sorted first by overall study confidence level then by Exposure Window examined.
bSex specific data below solid black line; newborn boys above dotted line, newborn girls below.
Tor evaluation of patterns of results, we considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses (e.g., Yang et al. (2022al).
dFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
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Gestational age-overall population results
Seventeen of the 19 epidemiological studies examined mean gestational age data in the
overall population, with the other two only reporting sex-specific findings fLind etal.. 2017:
Maisonet etal.. 20121 for PFHxS and gestational age relationships. Four studies reporting both sex-
specific and overall population results fHiermitslev et al.. 2020: Meng etal.. 2018: Li etal.. 2017b:
Manzano-Salgado etal.. 2017a). Among the 19 studies with gestational age measures, eight were
high confidence (Gardener etal.. 2021: Eick etal.. 2020: Huo etal.. 2020: Buck Louis et al.. 2 018:
Sagiv etal.. 2018: Lind etal.. 2017: Manzano-Salgado etal.. 2017a: Bach etal.. 20161. five were
medium fYang etal.. 2022a: Hiermitslev etal.. 2020: Gvllenhammar etal.. 2018: Meng etal.. 2018:
Maisonet etal.. 20121. and six were low confidence studies fBangma etal.. 2020: Gao etal.. 2019:
Workman et al.. 2019: Xu etal.. 2019: Li etal.. 2017b: Hamm etal.. 20101 (see Figure 3-47). Five
f Gvllenhammar et al.. 2018: Meng etal.. 2018: Sagiv etal.. 2018: Li etal.. 2017b: Maisonet etal..
20121 of the 19 studies received a good rating in the study sensitivity domain, while eight
(Gardener etal.. 2021: Eick etal.. 2020: Hiermitslev et al.. 2020: Buck Louis et al.. 2 018: Lind etal..
2017: Manzano-Salgado etal.. 2017a: Bach etal.. 2016: Hamm etal.. 20101 were considered
adequate and six were deficient fYang etal.. 2022a: Bangma etal.. 2020: Huo etal.. 2020: Gao etal..
2019: Workman etal.. 2019: Xu etal.. 20191.
Six fBangma etal.. 2020: Huo etal.. 2020: Workman etal.. 2019: Buck Louis et al.. 2 018:
Gvllenhammar et al.. 2018: Bach etal.. 20161 of the 17 studies in the overall population reported no
associations between gestational age and PFHxS exposures, while four reported an increased
gestational age with increasing PFHxS exposures (Eick etal.. 2020: Xu etal.. 2019: Li etal.. 2017b:
Hamm etal.. 20101 (see Table 3-20 or Figure 3-48). For example, the low confidence study by Xu et
al. f20191 reported a very large increase in gestational age ((3= 3.38 weeks; 95%CI: -0.80, 7.55) per
ln-unit increase in PFHxS. The Buck Louis etal. f20181 study was largely null in the overall
population and reported some small non-significant differences for black ((3= -0.14 weeks; 95%CI:
-0.34, 0.05 for each ln-unit increase) and Asian ((3= -0.09 weeks; 95%CI: -0.40, 0.21 for each ln-
unit increase) neonates.
Seven studies reported some gestational age reductions in relation to PFHxS in the overall
population. Although their continuous PFHxS exposure results were null, the high confidence study
by Sagiv etal. f20181 showed small non-significant decreases for quartiles 3 and 4 albeit not in a
non-monotonic fashion. Although their overall population results were null, based on each ln-unit
increase,.the high confidence study by Manzano-Salgado etal. f2017al did show a small decrease in
gestational age for quartile 4 ((3= -0.16 weeks; 95%CI: -0.43, 0.1). The medium confidence study by
Hiermitslev etal. (20201 reported a relatively large gestational age reduction ([3= -0.32 weeks;
95%CI: -0.72, 0.08 per each ln-unit increase). The medium confidence study by Yang et al. (2022a)
showed larger gestational age reductions among term births ((3= -0.64; 95%CI: -1.64, 0.36)
compared to preterm births ((3= -0.20 weeks; 95%CI: -3.32, 2.93) per each ln-unit increase in Total
PFHxS exposures. The medium confidence Meng etal. f20181 study reported a decrease based on
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
continuous exposure (j3= -0.29 weeks; 95%CI: —1..15, 0.58 per each ln-unit PFHxS increase) and
small non-monotonic decreases across quartiles ((3 range: -0.06 to -0.17 weeks). The low
confidence study by Gao etal. T20191 reported a non-monotonic decreased gestational age in
relation to PFHxS tertiles 2 (p= -0.37 weeks; 95%CI: -0.82, 0.09) and 3 (p= -0.22 weeks; 95%C1:
-0.71, 0.27). Although there was no evidence of an exposure-response relationship, the high
confidence study by Gardener etal. f20211 reported that participants in the three upper PFHxS
quartiles had smaller gestational ages ((3 range: -0.18 to -0.75) relative to quartile 1.
Although they were not always internally consistent across exposure metrics, seven (3 high,
3 medium, and 1 low confidence) of 17 studies in the overall population showed some gestational
age reductions in relation to PFHxS exposures. Few study characteristics appeared to be related to
patterns across the study results. For example, four of the seven studies showing inverse
associations were based on early biomarker sampling. Study sensitivity in the six (three high, one
medium, and one low confidence) may explain some of the null findings as half of the studies had
deficient ratings (one good, two adequate, and three deficient).
Participant selection
Exposure measurement
Outcome ascertainment
Confounding
Analysis
Sensitivity
Selective Reporting
Overall confidence
~Legend
Good (metric) or High confidence (overall)
+• Adequate (metric) or Medium confidence (overall)
- Deficient (metric) or Low confidence (overall)
Qj Critically deficient (metric) or Uninformative (overall)
Figure 3-47. Study evaluation results for 19 epidemiological studies of
gestational age and PFHxS. For additional details see HAWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Miuwanff-SaviKfe INMAcOhi<> (2CQ3-2Wfil H
•l«l,20>r 'W
4SMB
Overall Study Confidence Study Sunstitivity Oeiign
iHQl
BitfU'ttwrt, 2081 V*gai| P»M ShJiiy n» ww tvon?
?D2«IB8 CWd'on's Sudp (NCS) 5420
IfioOlfi v'Jrt {««»
Mwv«»l.,»i0, ONflC (»MC-JCCJi. I
rwo accept torn paio&i i
u, 20! I, 3M«39fl WCSWW PWKi M
Tccmr .Ware (am
*u, 2D1B. Cnnw-woonai ««janJ016-SO»T|i
M**1
SjiwiI
-tf.Ott
•043
Cctjolt Ittmlii '-2
COBm-jcdksr® 2
»2 ooe
¦Mr
-ft4B
u oq*Mist»i 4.U25
-0.IX
-ozn
JtX
Ou»ite i
Quarts*
'«("O-'fij mai
Wti»J
S»B«3
iw-iw <"awni,jwi
t^oninng'mL,! mi
•w»m ('Himu.3 iiipuw*
too ndh &AJ
• IKVX*
H us*.. e«»
WKUfcBWlyWJg
Mi'iiu- mlnival
+-
-1.4 -li -S3 rfl.6 -
1 -0.2 1 PJ M M "?.# 5 15 IA
Figure 3-48. Overall population gestational age results for 17 PFHxS
epidemiological studies. For additional details see HAWC link.
Abbreviations: GA= Gestational Age
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
bThe (Yang et al., 2022a) -0.64 per IQR Increase value is reported in the term birth population; the -0.2 per
IQR increase value is in the preterm birth population.
cGardener gestational age differences estimated from digitization of their Figure 4; 95%Cls were not estimable.
dFor evaluation of patterns of results, we considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses (e.g., Yang et al. (2022a)).
eYang et al. (2022ai preterm results are truncated: the complete 95% CI ranges from -3.32 to 2.93.
eYang et al. (2022b) term results are truncated; the complete 95% CI ranges from -1.64 to 0.36.
fXu et al. (2019 results are truncated: the complete 95% CI ranges from -0.8 to 7.55.
gUnlike other studies that relied on maternal or cord serum or plasma (in ng/'mL), Bangma et al. (2020) used
placental exposure measures (in ng/g).
hFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
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Gestational Age - Sex-specific Results
Eight (four high, three medium, and one low confidence) epidemiological studies examined
mean gestational age in relation to PFHxS in either or both sexes including one that evaluated data
in girls only fMaisonet etal.. 20121 (see Figure 3-49). None of the seven studies in boys showed
decreased gestational age with increasing PFHxS, with six studies showing null associations fEick et
al.. 2020: Hiermitslevetal.. 2020: Mengetal.. 2018: Sagivetal.. 2018: Lind etal.. 2017: Manzano-
Salgado etal.. 2017a). The low confidence study by Li etal. (2017b) reported a small increased
gestational age per each ln-unit PFHxS increase ((3= 0.20 weeks; 95%CI: -0.02, 0.42) among boys.
Five fEick etal.. 2020: Meng etal.. 2018: Sagivetal.. 2018: Li etal.. 2017b: Manzano-Salgado
etal.. 2017al of the eight studies in girls reported null associations between PFHxS and mean
gestational age, while another study fEick etal.. 20201 reported non-significant increased
gestational age across tertiles ((3 range: 0.18 to 0.33). Three studies in girls showed some
gestational age reductions including some that were moderately large in magnitude. The high
confidence study by Lind etal. (2017) showed some suggestion of an exposure-response
relationship for mean gestational age across the upper three PFHxS quartiles ((3 range: -0.33 to
-0.86 weeks) including a large association ((3= -0.86 weeks; 95%CI: -1.34, -0.29) in quartile 4
(0.4-7.3 ng/mL) versus quartile 1 (0.2-0.29 ng/mL). The medium confidence study by Hiermitslev
etal. f20201 also reported a large gestational age reduction ((3= -0.57 weeks; 95%CI: -1.04, -0.10
per each ln-unit increase). In their study population of female infants only, the medium confidence
study by Maisonet et al. (2012) reported nonstatistically significant decreases in gestational age
with some suggestion of an exposure-response relationship. They reported reduced gestational age
in the second ((3= -0.15 weeks; 95%CI: -0.52, 0.22 for 1.3-2.0 ng/mL) and third PFHxS tertiles ((3=
-0.24 weeks; 95% CI: -0.62, 0.14 for 2.0-54.8 ng/mL) compared with the lowest tertile (<1.3
ng/mL).
Overall, three (one high and two medium confidence) studies out of eight studies in girls
only showed reduced gestational age in relation to PFHxS exposures. Although they were not
always monotonic, both of the studies with categorical data showed some evidence of exposure-
response relationships which lends support to the findings based on continuous exposure
metrics. There was no evidence of inverse associations among boys, although half of the studies
had deficient study sensitivity. Few other study characteristics appeared to be related to patterns
across the study results; however, all three of the studies showing inverse associations in females
were based on early biomarker sampling.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Study
Population
Overall Study
Study Sensitivity
Design
Exposure Window
Regression
Exposure Comparison
Confidence
Coefficient
Regression coefficient
• [J Ias5ocia;ioi with GA|
LiirI.5017,
3&8&12
OdeiistJ Child Co-ion (2010-2012)
Mteitl
Adetjuate
(Prospaetlvo;
Til'nustol 1
0.07
OUii'tllo 2
- ,•
0 P [associaaon with GA] p<0.C!i
H 85% confidence Interval
§
Quartile4
•
0.04
lo-uinl (fry'lriL) btcreasis
, » .
Sagiv. 2D 18.
Proieat Viva (1993-2002) 1645
•ma"!
Good
Cohort
(Prospective)
Tnmeste' t-2
-0.01
In-un-t (nff'rnl.) increase
Man/ano-Salgado
INMA cohor. <2003-2008! 1202
Hiflhl
Adecuata
Cohort
TdrtiBBter 1
-0.BD
Irvuryt In&'mL) increase
f-«r*
Eick et al.. 2020.
710279?
Chemicals In Our Bodies (ClOBj
(2014-2018). US 497 female
pait clpants
Highl
Adequate
Cross-secttonai
Trimester 1-3
0 <8
Terl'le 2
Mcjmo eta)., 20 *8
4329851
DNBC (1396-2002), Denmark. 3535
iioth ur-u^ampairs
Mediuml
Good
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(Pmsji-jcilve;
Tnmeste* 1-2
-o.oe
b-linft (ng'mL) Increase
•-•n
Hjerm'tslev, 2-320
5530849
ACCEPT birth cohort <2010-2011.
2013-2015) Greenland, 482
molher-infam pairs
GBCS (20131, Chins. 321
mother-mfemi pairs
iMedliiml
|La«|
Adequate
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CraEs-seotionai
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Al birth
-0,08
0.2
l-1-iinit fno/ml.) increase
In-urol (ng.'rnL) Increase
i t ,
Lui'J, 201?.
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Odetrso Child Co'iurl (2010-21)12)
638 malhgr-l'i'anl pans
>Wifll.|
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-0.33
0,86
-6,17
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i • r—^
Sagiv. 2018.
473B-U.T
"reject Viva (1999-2002; 1645
'HIPI
Good
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(Prospective)
Trmester t-2
a
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*
fllal. 201 /
4238465
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Hlghl
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Tiimeatsrl
OM
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E'Ck et al. 2020,
7102797
Chemicals In Our Bodies (CIOB)
(2314-2018). US 467 female
participants
+ligfi|
Adcouatc
Cross sections
Trimester I -3
033
TertfcZ
Mens c-! al., 20'S
4829851
DNBC (1996-20021, Denmark. 3535
motheMnfaiit pairs
IMciiiuitti
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(Prospective)
Thtncster t-2
0.01
Irt-UWt Ing'niL) Increase
5330849
ACCEPT birth cohort (2010-2011,
2013-2015). Greenland. 482
mother-infant pairs
iMeOHim)
Adeawrte
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-0,5?
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I . ,1
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ALSRAC (1991-1992), U K., 447
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1., 2017 3DB135B
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MM
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Crass-sectlonai
Ai birth
0D7
-a -15 -1 -D.5 0 0.5 1 1.5 2
Figure 3-49. Sex stratified gestational age results for 8 PFHxS epidemiological
studies. For additional details see HAWC link.
Abbreviations: GA= Gestational Age
aStudies are sorted first by overall study confidence level then by Exposure Window examined.
bFor evaluation of patterns of results, we considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses (e.g., Yang et al. (2022a)i
°Lind et al. (20171 results are truncated: the complete 95% CI ranges from -3.1 to 0.7.
dFor evaluation of patterns of results, EPA considered studies that collected biomarker samples concurrently or
after birth to be cross-sectional analyses.
Gestational duration summary
There was mixed evidence within and between studies examining adverse associations
between PFHxS exposure with any gestational duration measures (preterm birth or gestational
age). Out of 19 total studies, 8 different ones showed gestational duration associations with
PFHxS. Four of 10 studies showed some increased odds preterm birth and PFHxS exposures in the
overall population or either/both of the sexes, although these were not always internally
consistent. Seven of 17 studies in the overall population reported mean gestational age deficits in
relation to PFHxS, while 3 of 8 studies with sex-specific data only reported inverse associations in
girls. In addition to the null studies, a few studies also reported increased gestational age related to
PFHxS exposures. Gestational age can be prone to some measurement error which may reduce the
ability of some studies to detect statistically significant resul ts for this endpoint. The preterm birth
binary endpoint may also be less impacted by this measurement error given the broad classification
of pre-term versus term births.
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Table 3-20. Summary of 19 epidemiological studies of PFHxS exposure and
gestational duration measures
Author
Study
location/
years
N
PFHxS
median
(ng/mL)
exposure
Overall
confidence
descriptor
Study
sensitivity
domain
PTB
GA
Bach etal. (2016)
Denmark
2008-2013
1,507
0.5
High
Adequate
0 All
0 All
Buck Louis et al. (2018)
USA,
2009-2013
2,106
0.71
High
Adequate
0 All
Eicketal. (2020)
USA,
2014-2018
506
0.33
High
Adequate
0 All
+ All
0 Boys/Girls
Gardener et al. (2021)
USA,
2009-2013
354
0.5
High
Adequate
t All
-All
Huo et al. (2020)
China,
2013-2016
2,849
0.54
High
Deficient
0
All/Boys T Girls
0 All
Lind et al. (2017)
Denmark,
2010-2012
636
0.3
High
Adequate
-Girls
0 Boys
Manzano-Salgado et al.
(2017a)
Spain,
2003-2008
1,202
0.58
High
Adequate
0
All/Boys -i- Girls
-All
0 Boys/Girls
Sagiv et al. (2018)
USA,
1999-2002
1,645
2.4
High
Good
t All
-All
0 Boys/Girls
Gvllenhammar et al.
(2018); 2017a
Sweden,
1996-2001
381
2.4
Medium
Good
0 All
Hiermitslev et al.
(2020)
Greenland,
2010-2015
266
0.51
Medium
Adequate
0 All
-All/Girls
0Boys
Maisonet et al. (2012)
United
Kingdom,
1991-1992
444
1.6
Medium
Good
— Girlsb
Meng et al. (2018)
Denmark
1996-2002
2,132
~1
Medium
Good
t All
0
All/Boys/Girls
Hamm et al. (2010)
Canada,
2005-2006
252
2.1
Medium/
Low
Adequate
i Allb
+ All
(Yang et al., 2022a)
China,
2018-2019
768
0.049-
0.058d
Medium
Deficient
0 All
-All"
Bangma et al. (2020)
USA, 2015-
2018
122
0.067=
Low
Deficient
0 All
Gao et al. (2019)
China,
2015-2016
132
0.24
Low
Deficient
-All
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Author
Study
location/
years
N
PFHxS
median
(ng/mL)
exposure
Overall
confidence
descriptor
Study
sensitivity
domain
PTB
GA
Li et al. (2017b)
China,
2013
321
3.87
Low
Good
+ All/Boys
0 Girls
Workman et al. (2019)
Canada,
2010-2011
414
0.44
Low
Deficient
0 All
Xu et al. (2019)
China,
2016-2017
98
0.61
(0.30-
1.94)f
Low
Deficient
+ Overall
Abbreviations: PTB = Preterm Birth; GA = Gestational Age.
* Denotes statistical significance at p < 0.05; 0 : represents a null association; + : represents a positive association;
- : represents a negative association; T: represents an increased odds ratio; -l: represents a decreased odds ratio;
/ implies that multiple groups shared the same classification.
Note: "Adverse effects" are indicated by both increased odds ratios () for dichotomous outcomes and negative
associations (-) for the other outcomes.
aGvllenhammar I (2017) and Gvllenhammar et al. (2018) results are included here (both analyzed the POPUP
cohort).
"Exposure-response relationship detected based on categorical data.
'Hamm et al. (2010) was medium confidence for PTB and low confidence for GA.
"Median range across cases and controls.
¦^Exposure measured in placenta (ng/g).
f5th-95th percentiles.
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Fetal Loss/Spontaneous Abortion
Five studies reported on the relationship between PFHxS exposure and spontaneous
abortion (see Figure 3-50). A cohort of pregnant women enrolled at 8-16 weeks gestation flensen
etal.. 20151 was considered low confidence primarily due to loss to follow-up and the high risk of
incomplete case ascertainment (i.e., not including women with losses that occurred prior to study
enrollment, which may bias the results towards or even past the null if there is a true association
between PFHxS exposure and spontaneous abortion (Radke et al.. 201911. Liew et al. f20201 is a
case-control study that identified cases via medical registry and also has the potential to miss early
losses. However, this study was not downgraded to low confidence as loss to follow-up was not a
concern. Three additional studies were considered medium confidence, two case-control studies of
first trimester miscarriage fMi etal.. 2022: Wikstrom et al.. 20211 and a cohort of women
undergoing their first in vitro fertilization-embryo transfer treatment cycle fWang etal.. 2021al.
Notably, Mi etal. f20221 measured sodium perfluoro-l-hexanesulfonate, a related salt, rather than
PFHxS.
Tensenetal. (20151 reported an increased OR (1.53; 95% CI: 0.99, 2.38] for spontaneous
abortion for each ln-unit increase in exposure despite study sensitivity limitations. While this study
is low confidence, the bias is unlikely to be away from the null (as described above], and thus the
limitations are unlikely to explain the observed positive association. However, the other four
studies, all medium confidence, reported no association between PFHxS exposure and early
spontaneous abortion. It is possible that there is only an association with second trimester
spontaneous abortion, but the evidence is currently not adequate to make this determination and
there is considerable uncertainty due to inconsistency across studies.
Jensen, 2015, 2850253 -
Liew, 2020, 6387285
Mi, 2022, 10413561 H
Wang, 2021, 10176703
Wikstrom. 2021, 7413606 -
,0^
&
a*
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-50. Study evaluation results for nine epidemiological studies of fetal
loss and PFHxS. For additional details see HAWC link.
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Birth Defects
Two studies examined birth defects in relation to PFHxS exposures (see Figure 3-51). The
medium confidence congenital heart defect study by Ou etal. f20211 reported null associations
risks for PFHxS >0.153 ng/mL (vs. <0.153 ng/mL) for septal defects (OR=1.07; 95%CI: 0.52, 2.22),
and total heart defects (OR=1.03; 95%CI: 0.65,1.64), although a non-significant inverse risk was
seen for conotruncal defects (OR=0.64; 95%CI: 0.28,1.49). Relative to tertile 1, the low confidence
Cao etal. (2018) study showed evidence of monotonic associations between all birth defects and
PFHxS tertiles 2 (OR=2.24; 95%CI: 1.05, 5.27) and 3 (OR=2.54; 95%CI: 1.06, 6.13). There is
considerable uncertainty in interpreting results for broad all birth defect groupings which
decreases study sensitivity given the etiological heterogeneity across different birth defects.
Overall, there was limited evidence of associations between PFHxS and birth defect based
on the two available epidemiological studies. Despite an exposure-response relationships in one
low confidence study based on an all (i.e., total) birth defect grouping, there is currently insufficient
data for any specific birth defects to draw further conclusions given the limitations noted above.
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Outcome ascertainment -
Confounding -
Analysis
Sensitivity -
Selective Reporting -
Overall confidence -
e^Vt ^
G®° 0°
++
¦
++
B
H
¦
¦
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-51. Summary of study evaluation for 2 epidemiology studies of birth
defects. For additional details see HAWC link.
Animal Studies
Five of the available toxicology studies evaluated PFHxS-induced effects in developing
animals. Three studies exposed Wistar rats fButenhoffetal.. 2009: 3M. 20031 or CD-I mice (Chang
etal.. 20181 to PFHxS for 14 days before mating, and during mating gestation, and lactation while
Marques etal. f20211 treated CD-I mice with PFHxS from GDI to PND20; one study exposed Wistar
rats from GD7 to PND22 fRamhai etal.. 20181: and a separate study using Wistar rats treated
animals from GD7 to GD22 and from PND1 to PND22. These studies administered PFHxS (doses
ranging from 0.03 to 45 mg/kg-day) via gavage and evaluated maternal toxicity and fetal survival,
growth, and morphological development The Butenhoff et al. (20091. 3M (20031 and Chang etal.
f 2 018) studies were evaluated as high confidence, while the Ramh0i etal. (20181. Marques et al.
f20211. and Tetzlaff etal. f20211 studies were evaluated as medium confidence (see Figure 3-52).
Concerns in the Ramhai etal. (20181. Tetzlaff etal. (20211. and Marques etal. f20211 studies were
noted for allocation, and the reporting of the number of animals per exposure group.
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Reporting quality
Allocation -4 ~
Observational bias/blinding - NR
Confounding/variable control
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Results presentation
Endpoint sensitivity and specificity
Overall confidence
Legend
Good (metric) or High confidence (overall)
+ I Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
NR| Not reported
Figure 3-52. Developmental animal study evaluation heatmap. For additional
details see HAWC link.
Maternal health
The health of the dams was assessed in all available studies except Tetzlaffetal. f20211 (see
Figure 3-53). Butenhoff etal. f20091: 3M f20031 reported that Sprague Dawley rats administered
PFHxS displayed decreased maternal body weight (6% to 8% relative to controls) during the
lactation period: on PNDs 4, 6-8, 11, and 13 at the lowest dose (0.3 mg/kg-day); on PNDs 7 and 8 at
3 mg/kg-day; and on PNDs 4, 6-9,11,13, and 14 at the highest dose (10 mg/kg-day). However,
these decrements are considered minimal, the animals recovered from these effects at weaning
(PND 22), and studies in CD-I mice (Marques etal.. 2021: Chang etal.. 20181 or Wistar rats
(Ramh0i etal.. 20181 did not report significantPFHxS-induced effects on maternal body weight
during gestation or lactation. Maternal food consumption was also not affected in exposed rats or
mice fChangetal.. 2018: Butenhoff etal.. 2009: 3M. 20031. Additional outcomes evaluated in F0
females included kidney and liver weights, reproductive organ weights and histopathology, and
maternal serum thyroxine levels, which are discussed in those respective sections (see Sections
3.2.3, 3.2.4, and 3.2.10). Briefly significant treatment-related increases were observed for mean
liver weight and the incidence of histopathological findings at 3 mg/kg-day in CD-I mice (Chang et
al.. 20181. and significant treatment- and dose-related decreases were observed in serum thyroxine
levels in Wistar rats fRamhai etal.. 20181: see hepatic and thyroid effect sections (see Sections 3.2.5
and 3.2.1, respectively) for more detail.
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Fetal viability
Endpoints related to fetal and postnatal viability were measured in the Butenhoff et al.
f20091. Chang etal. f20181. Marques etal. f20211. and Ramhai etal. f20181 studies. Post-
implantation loss, perinatal loss, number of live pups, litter size, and number of stillborn pups were
not affected by PFHxS exposure in Sprague Dawley or Wistar rats fRamhai etal.. 2018: Butenhoff et
al.. 2009: 3M. 20031. and Marques etal. (20211 reported no PFHxS-induced effects on live births per
litter in CD-I mice. However, a similar study in CD-I mice reported that exposure to PFHxS at 1 and
3 mg/kg-day decreased the related measures of live litter size (by 14% and 12%, respectively) and
the number of pups born per litter (by 12% and 11%, respectively) fChang etal.. 20181. An
explanation for the lack of dose-dependence of these observations is unavailable. Decreased litter
size is considered an indirect indication of pre-implantation loss and resorptions flPCS. 20061. but
the Chang etal. f20181 study did not measure either of these two outcomes. This mouse study also
evaluated the number of pups born-to-implant ratio and pup survival and reported no treatment-
related effects (Chang etal.. 20181. The finding of reduced litter size and live pups per litter in mice
but not in rats exposed to higher PFHxS levels is not explainable by differences in
pharmacokinetics, study design, or study evaluation considerations. Furthermore, the toxicological
significance of these effects observed in mice is not clear as these responses did not appear to be
dose dependent; other measured developmental outcomes were not altered in the Chang et al.
(20181 study.
Fetal growth
F1 animal growth was evaluated in all available animal developmental studies. PFHxS
exposure did not affect pup body weights in male or female Sprague Dawley and Wistar rats, or in
CD-I mice fMarques etal.. 2021: Tetzlaffetal.. 2021: Chang etal.. 2018: Ramhai etal.. 2018:
Butenhoff etal.. 2009: 3M. 20031. Furthermore, no significant treatment-related effects were
observed on sex ratio in Sprague Dawley and Wistar rats (Ramh0i etal.. 2018: Butenhoff etal..
2009: 3M. 20031. or in CD-I mice (Chang etal.. 20181 suggesting PFHxS exposure did not
specifically affect male or female animals.
Morphological development
Gross pathological examination of F1 pups revealed no significant exposure-related
developmental effects in exposed Sprague Dawley and Wistar rats, or CD-I mice fChang etal.. 2018:
Ramhai etal.. 2018: Butenhoff et al.. 2009: 3M. 20031.
Small but significant alterations in F1 AGD at birth were observed in CD-I mice and Wistar
rats (Chang etal.. 2018: Ramh0i etal.. 20181. Chang etal. (20181 reported that adjusted (i.e.,
relative to cube root body weight) PND1 AGD was increased by 3% to 5% in male CD-I mice at
doses ranging from 0.3 to 3 mg/kg-day; and in female PND1 mice, adjusted AGD was decreased by
5% only at the mid-dose (1 mg/kg-day). AGD is used as a phenotypical marker of androgen
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levels/production during the masculinization programming window (Foster and Gray. 201319.
Other phenotypical markers of androgen disruption were not altered in the available studies. On
PND13 male nipple retention (another marker indicative of hormonal alterations fFoster and Gray.
201311 was not altered by PFHxS treatment in CD-I mice, and puberty onset was not affected in
either CD-I mice or Wistar rats fChang etal.. 2018: Ramhai etal.. 20181. Additionally, male, and
female reproductive organ weights in F1 CD-I mice (at PND36] and Wistar rats (males at PND16,
females at PND17 or 22) were not affected by PFHxS treatment (Chang etal.. 2018: Ramh0i etal..
20181.
The biological significance of the small and directionally inconsistent changes in androgen
dependent AGD measures in animal and human studies is unclear. Taken together, the available
evidence does not support an effect on reproductive organ development by PFHxS exposure in
these animal studies.
9 In rodent models and in humans AGD is longer in males when compared to females (Dean and Sharpe.
20131. Decreases in AGD are associated with androgen disruption during the masculinization programming
window (Dean and Sharpe. 2013: Foster and Gray. 20131 whereas increased AGD in females could be
indicative or increased androgen levels or activation of the androgen receptor (Foster and Gray. 20131
Exposure to chemicals known to impair androgen synthesis or antagonize the androgen receptor have been
shown to result in decreased AGD as well as effects on other indicators of hormone disruption (e.g., increased
nipple retention] or adverse effects in the reproductive system (e.g., testicular atrophy, epididymal
malformations, testicular size, hypospadias, reduced size of the testis and accessory reproductive glands]
(Dent etal.. 20151
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Effect
Study Name
Endpoint Name
Animal Description
PFHxS Animal Developmental Effects
Maternal Body Weight
Butenhoff, 2009, 1405789
Maternal Body Weight Gain, GD 0-20
P0 Rat, Sprague-Dawley (- )
• No significant change
•
—•
—~
Maternal Body Weight, PND 4
P0 Rat, Sprague-Dawley (~)
A Significant increase
V
V
Maternal Body Weight, PND 6
P0 Rat, Sprague-Dawley (~)
V Significant decrease
V
—•
V
Maternal Body Weight, PND 8
P0 Rat, Sprague-Dawley (_)
V
V
V
Maternal Body Weight, PND 7
P0 Rat, Sprague-Dawley (^)
V
V
V
Maternal Body Weight, PND 11
P0 Rat, Sprague-Dawley (1)
V
V
Maternal Body Weight Change, PND 1-22
P0 Rat, Sprague-Dawley ( ")
«-
*
Chang, 2018, 4409324
Maternal Body Weight Change, GD 0-18
P0 Mouse, CD-1 ($)
»
-•
Maternal Body Weight Change, PND 1-21
P0 Mouse, CD-1 ($)
•
«
Ramhoj, 2018, 4442260
Maternal Body Weight Change, GD 7-21
P0 Rat, Wistar (:)
•—~
Maternal Body Weight Change, PND 1-14
P0 Rat, Wistar ( )
*—•
Marques, 2021, 9960182
Maternal Body Weight
P0 Mouse, CD-1 (y)
•
Pregnancy Outcomes
Chang, 2018, 4409324
Number of Pups Born to Implant Ratio
F1 Mouse, CD-1 (
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Evidence Integration
The currently available evidence suggests but is not sufficient to infer that PFHxS might
cause developmental effects in humans given sufficient exposure conditions10. This judgment is
based on slight human evidence, specifically the fairly consistent, but notably uncertain, evidence of
decreased birth weight and some coherent changes in other growth parameters from studies of
exposed humans in which PFHxS was measured pre-conception or either during or shortly after
pregnancy (see Table 3-2118). As discussed earlier (see Appendix C for more details), with the
exception of post-partum samples, fairly consistent small (but often statistically significant) birth
weight deficits were detected in EPA's meta-analysis of epidemiological studies including those
based on early sample timing. Overall, although there are data that suggest changes in fetal growth
are related to PFHxS exposures, additional evidence (e.g., more epidemiological study of PFHxS
exposure on birth weight with earlier biomarker sampling that helps to reduce uncertainties in the
current evidence base) would be needed to draw a stronger judgment
Although not entirely consistent, the epidemiological evidence includes a large fetal growth
restriction database with some of the most accurate endpoints available (e.g., birth weight is
generally measured with little error). The available epidemiologic studies showing birthweight-
related differences for continuous exposure data ((3 range: -12 to -145 grams per each ln-unit
increase) and categorical ((3 range: -25 to -101 grams for the highest quantile compared to the
lowest quantile) showed results comparable in magnitude and provided some support of a biologic
gradient, albeit the categorical data to a lesser degree given lack of monotonicity across quantiles.
For example, many studies based on continuous exposure data (per each increasing unit change in
PFHxS) showed fairly comparable birth weight-related deficits ranges in either boys or girls ((3
range: -25 to -145 g) or in the overall population ((3 range: -12 to -93 g). There also was some
evidence of exposure-response relationships based on categorical data in 3 of 16 epidemiological
studies, although these were predominately driven by sex-specific findings.
Taken together, some birth weight deficits of varying magnitude were detected in 17 of 31
studies included in the main developmental synthesis, including 14 of 27 (and 10 of 21
medium/high confidence) studies that examined associations in the overall population and 8 of 14
that reported mean birth weight deficits in either male or female neonates or both. Based on EPA's
meta-analysis, similar birth weight deficits per ln-unit PFHxS increase were seen across all 27
studies ((3= -7.7 g; 95%CI: -14.8, -0.5 per each ln-unit increase), 23 medium and high confidence
studies ((3= -8.0 g; 95% CI: -15.2, -0.7), or for the 12 high confidence studies ((3= -6.8 g; 95% CI:
-16.3, 2.8). No gradient was seen across confidence levels or by biomarker sample timing. Although
limited by a small sample size and considerable variation in results across studies, some deficits
were detected for five post-partum sampled studies ((3= -28.3 g; 95% CI: -69.3,12.7) using
umbilical cord samples or maternal samples after birth; this may be reflective of bias due to
10 The "sufficient exposure conditions" are more fully evaluated and defined for the identified health effects
through dose-response analysis in Section 5.
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pregnancy hemodynamic changes. In contrast, 12 studies based on earlier pregnancy sampling
periods (e.g., any first trimester sampling) showed deficits ((3= -7.3 g; 95% CI: -16.0,1.4) similar in
magnitude to the overall pooled estimate of all 27 studies and those restricted to medium and high
confidence. Given that these patterns are not consistent with what EPA has seen for other PFAS
such as PFNA fWright etal.. 20231 and what others have reported for PFOA and PFOS Dzierlenga et
al. f20201: Steenland etal. f20181. it remains unclear whether any differences noted between late
pregnancy and postpartum samples is unique to PFHxS.
Examining birth weight differences in human populations is challenging, and it can be
difficult to differentiate pathological deficits versus natural biological variation in distributions
within study populations. The magnitude of birth weight deficits across categorical and continuous
exposures in the individual studies, for example, ranged from -12 to -145 grams, depending on the
exposure contrasts being compared. The meta-analysis of the 27 studies that EPA conducted
showed a small but statistically significant decrease in mean birth weight ((3= -7.7 g; 95% CI: -14.8,
-0.5) per ln-unit increase in PFHxS. This overall result was similar when studies were restricted to
just the 12 high ((3= -6.8 g; 95% CI: -16.3, 2.8) confidence studies or the 19 combined medium and
high confidence studies ((3= -7.1 g; 95% CI: -15.2,1.0). The public health significance of small
changes in birth weight noted here in this meta-analysis may not be immediately evident On a
population level, even small changes, if causally related, can increase the number of infants at
higher risk for other co-morbidities and mortality especially during the first year of life. And,
therefore, small decrements may have a large public health impact if these shift the birth weight
distribution to include more infants in the low-birth-weight category. Additionally, decreased birth
weight has been associated with long-term adverse health outcomes such as cardiovascular disease
and diabetes (Osmond and Barker. 2000). Thus, this magnitude of decrease is considered to be of
concern.
Providing some evidence for changes coherent with the observed birth weight decreases,
decreases, 5 of 7 small for gestational age and low birth weight studies showed increased risk in
relation to PFHxS exposures. Additional evidence was seen in 12 of 18 (including 9 of 16 in the
overall population) birth length studies that showed associations of smaller birth length with
increasing PFHxS exposures, including 5 of 6 available high confidence studies. These results were
fairly small in magnitude. In addition, there was some support for these findings from coherent
effects related to postnatal weight measures (as 5 of 8 studies showed inverse associations), albeit
the other postnatal growth endpoints were null or mixed.
In addition to the uncertainty related to potential bias from pregnancy hemodynamics in
developmental epidemiological studies, a common area of concern when interpreting
epidemiological findings on individual PFAS is the potential for confounding by PFAS co-exposures.
As noted for other endpoints in general, despite extensive and advanced statistical modeling
attempts, it can be difficult at times to completely isolate an independent effect for each individual
PFAS when real-world exposures involve a myriad of sources. Although there were some moderate
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to strong positive correlations between PFHxS and some other PFAS, there were no consistent
patterns in magnitude of effects detected in models that adjusted for other PFAS (see detailed
write-up in Appendix C). Thus, while confounding by other PFAS remains a general source of
uncertainty in epidemiological studies, the lack of a consistent patterns across the available studies
here does not provide strong evidence of this possibility.
The available evidence on PFHxS-induced developmental effects in animal toxicity studies is
considered indeterminate. The available animal studies do not provide evidence coherent with the
epidemiological observations of effects on fetal growth (i.e., rodent offspring body weights were
generally unaffected). Similarly, PFHxS exposure during early developmental stages did not impact
the incidence of developmental malformations or alter reproductive organ development. One high
confidence study reported a significant decrease in litter size and numbers of pups per litter in CD-I
mice that was not dose-dependent fChang etal.. 20181 (note: a single, low confidence
epidemiological study evaluating an outcome related to fetal survival showed a marginally
statistically significant increased odds of fetal loss with increasing PFHxS exposure). However,
(Chang etal.. 2018) also reported that the number of pups born-to-implant ratio was unaffected,
and two separate high and medium confidence studies in rats reported no significant treatment-
related effects on fetal survival endpoints at the same or higher PFHxS levels fRamhai etal.. 2018:
Bute nhoff etal.. 2009: 3M. 20031. Chemical-induced reduction in litter size can provide an indirect
indication of pre-implantation loss flPCS. 20061: however, this was not evaluated in any of the
available gestational PFHxS exposure studies in animals, highlighting a significant data gap.
Several epidemiological and animal toxicity studies report alterations in AGD. However, the
biological significance of the small and directionally inconsistent changes as well as lack of
consistency with other markers of androgen-dependent phenotypical outcomes and developmental
measures adds uncertainty to the available evidence. Overall, the available studies do not support
an effect on reproductive organ development by PFHxS exposure.
Overall, the available evidence suggests but is not sufficient to infer that PFHxS exposure
may have the potential to cause developmental toxicity in humans given sufficient exposure
conditions11. A stronger evidence integration judgment was not drawn due to some important
sources of uncertainty in the epidemiological literature (most notably, uncertainty due to potential
bias by pregnancy hemodynamics) that appear to reflect complex patterns of biological influence
that are not completely understood. Nonetheless, the consistent and coherent epidemiological
findings on fetal growth restriction warrant further examination to disentangle these uncertainties
and improve understanding of whether and to what extent PFHxS exposure during these sensitive
lifestages might contribute to growth restriction in children.
11 Given the uncertainty in this judgement and the available evidence, this assessment does not derive a
toxicity value that might better define the "sufficient exposure conditions" for developing this outcome (see
Section 5 discussion).
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Table 3-21. Evidence profile table for PFHxS related developmental effects
Evidence stream summary and interpretation
Evidence integration
summary judgment
Evidence from studies of exposed humans (see Development Human Section)
©OO
Evidence suggests, but is not
sufficient to infer
Primary basis: Consistent human
evidence of decreased birth
weight and coherent findings
across multiple other fetal and
early-life measures of growth.
Median PFHxS values spanned
from 0.09 to 10.36 ng/mL across
the birth weight meta-analysis
studies.
Human relevance: N/A (based on
human evidence)
Cross-stream coherence: N/A
(animal evidence indeterminate)
Susceptible populations and
lifestages: Pregnancy and early
life
Evidence from human studies-fetal growth restriction
Studies and
confidence
Factors that increase
certainty
Factors that decrease
certainty
Summary and key
findings
Evidence stream
judgment
Fetal growth (Mean
birth weight
/z scores/small for
gestation age/low
birth weight)
9 high, 1 medium,
and 5 low confidence
studies
• Consistent
findings of some
inverse
associations in
20 of 34
(including 14 of
26 high or
medium
confidence)
studies
• Inverse
associations in
17 of 31 mean
birth weight
studies and 14 (5
high; 5 medium;
4 low) of 27 in
overall
population
across all study
confidence levels
• Although they
varied across
confidence
• Imprecision of
some birth
weight deficits
• Concern for
potential
confounding by
co-exposures to
highly correlated
PFAS
• Exposure-
dependence
limited, including
monotonic
relationships, in
only 3 of 14
different birth
weight studies
with categorical
data in overall
population or
either sex; lends
limited support
to studies based
• 20 of 34 overall
birth weight
studies
(including 14 of
26 medium or
high confidence)
studies showed
inverse
associations in
the overall
population, or
among boys or
girls
• Meta-analysis
conducted by US
EPA showed a
small but
statistically
significant birth
weight deficit
(7.7 g; 95% CI:
-14.8, -0.5) per
each In-unit
PFHxS increase;
results were
©oo
Slight
Based primarily on
consistent evidence
for birth weight
reductions and
coherent findings for
other fetal and
postnatal weight
endpoints, but
strength was reduced
due to concern for
confounding and
limited evidence of
dose-dependence
across most studies
with categorical
data.
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Evidence stream summary and interpretation
Evidence integration
summary judgment
levels, some
on continuous
comparable in
reported mean
exposure metrics
magnitude
birth weight
across early
deficits (up to
sampled studies
-145 g) and
and high and
relative risks
medium
were fairly large
confidence
in magnitude
studies
• Statistically
significant meta-
analysis results
for mean birth
weight from
continuous
exposure metrics
(-7.7 g; 95%CI: -
14.8, -0.5 per
each In-unit
increase); this
was comparable
to high (-6.8 g)
and medium (-
9.6 g) confidence
studies
• Overall meta-
analysis birth
weight results (-
7.7 g)
comparable to
early pregnancy
(-7.3 g) studies;
suggests results
not likely due to
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Evidence stream summary and interpretation
Evidence integration
summary judgment
pregnancy
hemodynamics
• Evidence among
6 of 13
standardized
birth weight
studies primarily
seen in high (4 of
8 high and
medium (1 of 3)
confidence
studies
• 5 of 7 studies
examining either
small for
gestational age,
low birth weight
or very low birth
weight showed
some increased
risks with
increasing PFHxS
exposures
among the
overall
population or
either girls or
boys (quite
variable in
magnitude, OR
range: 1.3-9.1)
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Evidence stream summary and interpretation
Evidence integration
summary judgment
Fetal growth
restriction (birth
length)
6 high, 5 medium,
and 7 low confidence
studies
Consistent
• None of the 5
• 9 of 16 studies
findings of some
studies with
reported
inverse
categorical data
adverse effects,
associations in 9
showed dose-
including all 5 of
of the 16 studies
dependent
6 high and 1 of 5
in the overall
associations in
medium
population (5
the overall
confidence
high, 1 medium,
population
studies
and 3 low
although 2 of 3
confidence)
sex-specific
analyses did
(both from same
birth cohort).
• Concern for
potential
confounding by
co-exposures to
highly correlated
PFAS
• Some concern
for potential bias
due to sample
timing
(pregnancy
hemodynamics)
as 6 of 9 studies
with inverse
associations
were based on
later biomarker
sampling;
although this did
not bear out in
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Evidence stream summary and interpretation
Evidence integration
summary judgment
the sex-specific
analyses.
Fetal growth
restriction (head
circumference)
5 high,
5 medium, and 4 low
confidence studies
• 8 of 14 studies in
total showed
inverse
associations,
including 7 of 12
studies in the
overall
population (4 of
5 high; 2 of 4
medium and 1 of
3 low
confidence)
• Exposure-
dependence in 1
of 2 studies with
categorical data
• Limited concern
over pregnancy
hemodynamics
as 5 of 7 studies
with inverse
associations in
the overall
population were
based on early
biomarker
sampling
• Concern for
potential
confounding by
co-exposures to
highly correlated
PFAS
• 8 of 14 studies (5
high; 2 medium
and 1 low
confidence)
reported
adverse
associations,
including 4 of 5
high confidence
studies
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Evidence integration
Evidence stream summary and interpretation
summary judgment
Anogenital distance
(AGD)
• No factors
• No factors
• Inverse
noted
noted
association
4 medium confidence
studies
between PFHxS
exposure and
AGD in 1 of 4
medium
confidence
studies in boys
and in 1 of 3
studies in girls
Evidence from human studies postnatal growth
Studies and
Factors that increase
Factors that decrease
Summary and key
Evidence stream
confidence
certainty
certainty
findings
judgment
Postnatal growth-
Weight measures:
5 high, 3 medium,
and 3 low confidence
studies
• Consistent
• Inconsistent
• 5 of 8 studies
findings of
inverse
associations
periods of
follow-up and
assessment (e.g.,
showed some
evidence of
postnatal weight
across 5 of the 8
studies of infant
weight with
more evidence
among girls
• Mixed results
were seen
among four
studies of rapid
growth (2 of 4
studies).
• Limited to no
evidence of
childhood age at
examination)
precludes more
direct
comparison
across studies.
• Concern for
potential
confounding by
co-exposures to
highly correlated
PFAS
reductions which
showed some
coherence with
birth weight
deficits.
• The other
endpoints were
mixed or
provided limited
or no evidence
of associations.
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Evidence stream summary and interpretation
Evidence integration
summary judgment
associations for
postnatal height
(1 of 5 studies),
head
circumference (0
of 3 studies) in
overall
population or
either sex.
• No evidence of
associations with
adiposity (0 of 5
studies) in the
overall
population, but 2
of 3 studies did
report this for
boys.
Evidence from human studies-gestational duration
Studies and
confidence
Factors that increase
certainty
Factors that
decrease certainty
Summary and key
findings
Evidence stream
judgment
Preterm birth
6 high and 4 medium
confidence studies
• All 10 published
studies were high
or medium
confidence
• Unexplained
inconsistency
• Concern for
potential
confounding by
co-exposures to
highly
correlated
PFAS
• 4 of 10 studies
showed some
evidence of
adverse
associations
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Evidence integration
Evidence stream summary and interpretation
summary judgment
Gestational age
8 high, 5 medium,
and 6 low confidence
studies
• 4 of the 7 studies
were based on
early biomarker
sampling;
suggesting that
pregnancy
• Unexplained
inconsistency
• One-half of the
studies in boys
were deficient
in study
sensitivity
• 8 of 19 studies in
total as well as 7
(3 high, 3
medium, and 1
low confidence)
of 17 studies in
hemodynamics
may have less of
the overall
population
an impact in this
• Concern for
showed some
subset.
potential
gestational age
• There was a
preponderance of
confounding by
co-exposures to
highly
correlated
PFAS
reductions
• 5 of the 8 sex-
associations
among girls with 2
specific studies
reported
of 3 of the studies
associations in
with categorical
girls, while none
data showing
of the studies in
some exposure-
the boys did.
response
relationship.
Spontaneous
abortion
4 medium and 1 low
confidence study
• No factors noted
• Low confidence
study reporting
an effect
• 1 low confidence
reported a
positive
association
despite bias
towards null, but
4 medium
confidence
studies reported
no associations.
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Evidence integration
Evidence stream summary and interpretation
summary judgment
Evidence from in vivo animal studies (see Developmental Animal Section)
Studies and
Factors that increase
Factors that
Summary and key
Evidence stream
confidence
certainty
decrease certainty
findings
judgment
Maternal health,
fetal viabilitv. fetal
growth,
morphological
development
• High confidence
studies
• Unclear
biological
significance of
small maternal
weight
changes
• Decreased litter
size in 1 of 3
studies
• No notable
ooo
Indeterminate
2 high confidence
studies:
PFHxS-induced
effects on
• GD0-PND22
• Lack of
maternal health,
expected dose-
fetal viability,
• GD7-PND22
dependence for
fetal growth, and
1 high confidence
study:
• GDO-
PND22
litter size
decrease in 1
study
gestation
duration.
• Studies did not
evaluate pre-
implantation
loss
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3.2.4. Hepatic Effects
Human Studies
Thirteen epidemiology studies (reported in 14 publications) report on the relationship
between PFHxS exposure and liver effects, primarily serum liver enzymes. Serum levels of alanine
aminotransferase (ALT) and aspartate aminotransferase (AST) are considered reliable markers of
hepatocellular function/injury, with ALT considered more specific and sensitive (Boone etal..
2005). Alkaline phosphatase (ALP), bilirubin, andy-glutamyltransferase (GGT) are also routinely
used to evaluate potential hepatobiliary toxicity fHall etal.. 2012: EMEA. 2008: Boone etal.. 20051.
Elevation of liver serum biomarkers is frequently an indication of liver injury, although they are not
as specific as functional tests, which are currently not available for PFHxS.
Of 13 available epidemiology studies, 10 were classified as medium confidence, 2 as low
confidence, and 1 was considered uninformative (see Figure 3-54). Tiangetal. (2014) was
considered uninformative due to critical deficiency in the confounding domain as well as a lack of
information on participant selection (deficient) and was excluded from further analysis. The
majority of the available studies were cross-sectional studies in adults, four of which fOmoike etal..
2020: Tain and Ducatman. 2019c: Gleason etal.. 2015: Lin etal.. 20101 were analyses of different
NHANES study populations (1999-2004, 2007-2010, 2011-2014, 2005-2012 respectively). The
inclusion criteria in these NHANES studies varied across analyses (e.g., Gleason et al. f20151
included adolescents as well as adults, fasting was required in Lin etal. (2010). individuals who
were carriers of hepatitis B or C virus were not excluded in Tain and Ducatman (2019cl). Because of
the overlapping population in Omoike etal. (2020) with the previous studies, this paper was not
considered a separate study. The other cross-sectional studies were in populations in Canada
fCakmak etal.. 20221. China fLiu etal.. 2022al. In addition, there was a cohort of elderly adults
fSalihovic etal.. 20181 and a birth cohort with follow-up into childhood fMora etal.. 20181. In
children and adolescents, in addition to the NHANES 2007-2010 analysis in Gleason etal. (2015)
that included adolescents but did not provide stratified estimates, Attanasio (2019b) examined
NHANES data from 2013 to 2016 in adolescents. A multicenter birth cohort examined liver
enzymes in childhood and was considered medium confidence (Stratakis et al.. 2020). There were
also two low confidence studies of children. Khalil etal. f 20181 was a pilot cross-sectional study of
48 obese children, and there was concern for potential for selection bias and confounding. Tin etal.
f2020bl was a cross-sectional study of children who had nonalcoholic fatty liver disease and
analyzed the odds of severe disease (non-alcoholic steatohepatitis) with PFHxS exposure. This was
the only study that did not examine liver function tests, but there were concerns for confounding
due to lack of adjustment for socioeconomic status and inclusion of BMI, which may lie on the
causal pathway. Across the studies of liver function, liver enzymes were analyzed appropriately in
serum. Analysis of PFHxS in serum or plasma samples was also appropriate in all studies.
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do0® .vr&
=,6^ 0^ 0.05)
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
in girls with elevated ALT, AST, and GGT (dichotomous based on upper reference limits). The other
medium confidence study in children (Stratakis et al.. 20201 did not report results for individual
liver enzymes but defined liver injury risk as having any liver enzyme concentration above the 90th
percentile for the study population. They found no association between liver injury risk and PFHxS
exposure. The low confidence study fKhalil etal.. 20181 also reported no association between
PFHxS and liver enzymes. In children with nonalcoholic fatty liver disease, higher PFHxS exposure
was associated with the presence of nonalcoholic steatohepatitis (OR [95% CI]: 4.18 [1.64,10.7] per
IQR increase). Positive associations were also observed with grade of steatosis (p > 0.05), lobular
inflammation, portal inflammation, ballooning (p > 0.05), and liver fibrosis (Tin etal.. 2020b).
Given the consistency of direction of association for ALT across most of the studies in
adults, there is some indication that PFHxS exposure may be associated with hepatic effects.
However, there is still some uncertainty due to the small or imprecise nature of some ALT increases
as well as the inconsistency of results for other liver enzymes. The single available low confidence
epidemiology study of liver histology (Tin etal.. 2020b) indicates an association between PFHxS
exposure and disease severity (i.e., nonalcoholic steatohepatitis), but these findings should be
interpreted with caution due to the potential for confounding and the nongeneralizable study
population. Additional studies of functional hepatic endpoints (e.g., liver disease) are not available,
so it is not possible to evaluate whether the small changes in liver enzymes observed in these
studies translate to clinical hepatic injury.
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Table 3-22. Associations between PFHxS and liver enzymes in medium confidence epidemiology studies
Reference
Population
Median exposure
(IQR) or as specified
Effect estimate
Ad
ALT
ults
AST
ALP
GGT
Total bilirubin
Nian et al.
(2019)
Cross-
sectional
(2015-2016);
China; 1,605
adults
0.7 (0.01-2.7)
% change (95% CI)
for In-unit change
0.2 (-0.8,1.2)
0.1 (-0.5,0.8)
-0.1
(-0.6,0.5)
0.4 (-0.6,1.4)
-0.3 (-1.0,0.5)
Liu et al. (2022a)
Cross-
sectional
(2018-2019);
China; 1,303
adults
0.9 (0.5-1.4)
% difference (95% CI)
vs. 25th percentile
50th: 7.69
(5.62, 9.80)*
75th: 12.15
(7.66, 16.83)*
95th: 16.90
(7.86, 26.70)*
50th: 3.43
(2.11, 4.78)*
75th: 6.16
(3.32, 9.07)*
95th: 9.66
(3.95, 15.68)*
50th: 0.90
(-0.22, 2.03)
75th: 0.88
(-1.46, 3.27)
95th: 0.44 (-
4.10, 5.19)
50th: 5.65
(3.22, 8.14)*
75th: 9.01
(3.81, 14.47)*
95th: 12.65
(2.30, 24.04)
50th: 3.05 (1.57,
4.55)*
75th: 6.44 (3.25,
9.72)*
95th: 11.40 (4.92,
18.28)*
Jain and
Ducatman
(2019c)
NHANES
cross-
sectional
(2011-2014),
U.S.; 2,883
adults
1.4
P (p-value) for log-
unit change
Nonobese
0.005 (0.8)
Obese
0.05 (<0.01)*
Nonobese
0.007 (0.6)
Obese
0.01 (0.4)
Nonobese
-0.005 (0.7)
Obese
0.006 (0.6)
Nonobese
0.008 (0.7)
Obese
0.03 (0.1)
Nonobese
0.002 (0.9)
Obese
0.04 (0.07)
Lin et al. (2010)
NHANES
cross-
sectional
(1999-2004),
U.S.; 2,216
adults
mean (SE)
1.7 (1.0) (women)
P (SE) for log-unit
increase
0.2 (0.5),
p = 0.7
NR
NR
0.0 (0.02),
p = 0.9
0.4 (0.2),
p = 0.06
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Reference
Population
Median exposure
(IQR) or as specified
Effect estimate
ALT
AST
ALP
GGT
Total bilirubin
Gleason et al.
(2015)
NHANES
cross-
sectional
(2007-2010),
U.S.; 4,333
adults
(12+ yrs)
1.8(1.0-3.1)
P (95% CI) for In-unit
increase
0.02
(0.01,0.03)*
0.02
(0.01,0.03)*
0.02
(0.01,0.04)*
0.01
(-0.01,0.03)
0.03 (0.01,0.05)*
Cakmak et al.
(2022)
Cross-
sectional
(2007-2017);
Canada;
4,952 adults
Cycle 1: 2.2;
Cycle 2: 1.7;
Cycle: 1.0
% change (95% CI)
for GM change
1.7 (0.2, 3.3)*
-0.3 (-1.6, 0.9)
-1.2 (-3.7,
1.3)
3.6 (-0.7, 8.0)
-0.8 (-4.8, 3.5)
Salihovic et al.
(2018)
Cohort
(2001-2014);
Sweden;
1,002 elderly
adults
2.1(1.6-3.4)
P (p-value) for In-unit
change
0.02
(0.0,0.03)*
NR
0.06
(0.02,0.09)*
0.03
(-0.01,0.07)
-1.0 (-1.3,-0.7)*
Children and adolescents
Mora et al.
(2018)
Project Viva
birth cohort
(1999-2002),
U.S.; 682
children (7-8
yrs)
prenatal
2.4(1.6-3.8)
P (95% CI) for IQR
increase
-0.1 (-0.4,0.2)
NR
NR
NR
NR
child
1.9 (1.2-3.4)
0.0 (-0.2,0.2)
NR
NR
NR
NR
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Median exposure
Reference
Population
(IQR) or as specified
Effect estimate
ALT
AST
ALP
GGT
Total bilirubin
Attanasio
NHANES
GM (SE)
P (95% CI) for
boys
boys
NR
boys
boys
(2019b)
cross-
male 1.3 (0.09)
quartiles vs. Q1
Q2: -0.07
Q2: -0.04
Q2: -0.09
Q2: 0.11
sectional
female 0.9 (0.06)
(-0.15, 0.01)
(-0.10, 0.03)
(-0.21, 0.03)
(0.03, 0.20)
(2013-2016);
Q3: -0.09
Q3: -0.03
Q3: -0.03
Q3: 0.07
354 males
(-0.20, 0.02)
(-0.09, 0.04)
(-0.15, 0.09)
(-0.01, 0.15)
and 305
Q4: -0.02
Q4: 0.00
Q4: 0.02
Q4: 0.16
females (12—
(-0.12, 0.08)
(-0.09, 0.09)
(-0.12, 0.15)
(0.07, 0.26)
19 yrs)
girls
girls
girls
p-trend: 0.01
Q2: -0.01
Q2: 0.00
Q2: 0.10
girls
(-0.14, 0.12)
(-0.10, 0.10)
(-0.01, 0.20)
Q2: 0.08
Q3: 0.05
Q3: 0.07
Q3: 0.10
(-0.02, 0.18)
(-0.05, 0.16)
(-0.01, 0.15)
(-0.01, 0.20)
Q3: 0.19
Q4: 0.03
Q4: 0.03
Q4: 0.08
(0.08, 0.30)
(-0.10, 0.16)
(-0.08, 0.14)
(-0.02, 0.18)
Q4: 0.25
(0.11, 0.40)
p-trend < 0.01*
*p < 0.05.
NR: not reported.
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Animal Studies
The toxicity database for PFHxS-induced liver effects in experimental animals consists of
two short-term exposure studies using SD rats fNTP. 2018a: 3M. 2000al: two subchronic exposure
study using AP0E*3-Leiden.CETP mice12 fBiiland etal.. 20111 or C57BL/6 mice fHe etal.. 20221:
one chronic exposure study using C57BL/6J mice fPfohl etal.. 20201 and four multigene ration
studies using Wistar (Ramh0i etal.. 20181 or Sprague Dawley rats (Butenhoff etal.. 2009: 3M.
20031. or CD-I mice (Marques etal.. 2021: Chang etal.. 20181. All studies exposed animals orally via
either gavage (Changetal.. 2018: NTP. 2018a: Ramh0i etal.. 2018: Butenhoffetal.. 2009: 3M. 2003.
2000a) or the diet fBiiland etal.. 20111. Outcomes evaluated and reported in these studies include
histopathological effects, serum biomarkers of liver damage and lipid metabolism, and changes in
absolute and relative liver weights.
Organ weight
Four high confidence studies five medium confidence studies evaluated PFHxS-induced
effects on liver weight (see Figure 3-55). In both rats and mice, short-term and subchronic exposure
led to increased absolute and relative liver weights13 fNTP. 2018a: Biiland etal.. 2011: 3M. 2000al
(see Figure 3-56). However, a chronic exposure study using male C57BL/6J mice reported no
significant effect on liver weight after exposure to 0.15 mg/kg-day for 29 weeks fPfohl etal.. 20201.
Two short-term (28-day) exposure studies using SD rats reported that exposure to PFHxS
increased liver weight by 8% to 54% at doses ranging from 1.25 to 10 mg/kg-day (NTP. 2018a: 3M.
2000a). Although NTP (2018a) observed increased relative and absolute liver weights in both male
and female animals, 3M (2000a) only observed exposure-related changes in male rats. A separate
subchronic exposure study using APOE*3-Leiden.CETP mice also observed increased absolute liver
weight (108%) in animals orally exposed to 6 mg/kg-day PFHxS for 42 days fBiiland etal.. 20111.
Four multigenerational toxicity studies evaluated PFHxS-induced effects on liver weights in
F0 and/or F1 animals (Chang etal.. 2018: Ramh0i etal.. 2018: Bute nhoff etal.. 2009: 3M. 2003). In
F0 generation male SD rats, exposure to 3 or 10 mg/kg-day PFHxS increased absolute and relative
liver weight by 20% to 67% when compared with controls, but no effects were observed in F0
females (Bute nhoff etal.. 2009: 3M. 2003). Two similar studies using CD-I mice also measured liver
weights, but reported different effects: fChang etal.. 20181 reported increased absolute and relative
liver weight (23% to 70%) in F0 generation (male and female) animals, but fMarques etal.. 20211
observed no exposure-related changes in F0 female liver weights. Both fChang etal.. 20181 and
fMarques etal.. 2021) exposed pregnant animals to similar doses of PFHxS, however fChang etal..
2018) treated animals for 42 days before mating, through gestation and lactation whereas
12 APOE*3-Leiden.CETP mice is a genetically modified animal model which emulates human lipoprotein
profiles and is used to investigate cholesterol metabolism and cardiovascular disease fVeseli et al„ 20171.
13 Alterations in liver weight are considered indicative of exposure-related responses such as enzyme
induction and hepatocellular hypertrophy (Thoolen et al.. 2010: Sellers et al„ 20071.
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1 (Marques etal.. 20211 exposed F0 female animals from GDI to PND20. In F1 generation animals,
2 significant PFHxS-induced increases in liver weight were observed in male CD-I mice (10%
3 increase in relative liver weight at 3 mg/kg-day) after exposure during gestation, lactation, and
4 post-weaning (until postnatal day 36) fChangetal.. 20181. However, in F1 male and female SD rats
5 sampled on PND22 and Wistar rats sampled on PNDs 16-17, there were no significant exposure-
6 related changes in relative or absolute liver weights fRamhai etal.. 2020: Ramhdi et al.. 2018:
7 Butenhoff et al., 2009: 3M. 20031. In F1 male and female CD-I mice exposure to a high fat diet plus
8 PFHxS resulted in decreased relative, but not absolute, liver weight on PND21. These effects were
9 not apparent on PND90. Overall, the majority of the available studies report fairly consistent
10 increases in liver weight across lifestages following PFHxS exposure.
lO%V JS. ^
Cof»/var»8blt> control
Salnctii/fl reporting nnd attrition
Chemical administration and cnsracterization
Fxpcsu«» timing, frequency and duration
Results presentation
bndpoint WKiOlvlty ana spocrtidty
Overall confidence
Figure 3-55. PFHxS liver weight animal study evaluation heatmap. For
additional details see HAWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Endpoint Name Study Name
Liver Weight, Absolute NTP, 2018.4309363
bwo« Weight, Relative NTP, 2018, 4309363
Live» Weight. Absolute 3M. 2000. 3981194
Liver Weight, Relative 3M. 2000. 3981194
Liver Weight. Absolute Buienhoff. 2009. 1405789
Liver Weighi, Relative Butennoff. 2009,1406789
Liver Weighi, Absolute Buienhoff 2009, 1405789
Liver Weight, Relative Bulenhoff. 2009,1405789
Livor Weighi. Absolute Ramhaj. 2018. 4442260
Animal Description
Rat. Sprague-Dawley ( ")
Rat. Sprague-Dawley {' •)
Ral, Sprague-Oawloy ( )
Rat, Sprague-Dawlay ( -)
Ral, Cil;Cd Bt (•)
Ral, Crl:Cd Br (i)
Rat. Crt;Cd Br (/)
Rat. Crl:CdBr< _)
P0 Rat. Spragu-e-Dawley (
P0 Rat. Sprague-Dawlcy (,
PO Rat, Sprague-Dawley {
P0 Rat. Spfaque-Dawley (.
F1 Ral, Sprague-Dawley (
F1 Rat, Sprague-Dawley <
F1 Rat, Sprague-Dawley <
F1 Rat, Sprague-Dawley (
P0 Rat. Wistar
F1 Rat, Wistar (,")
F1 Ral, Wistar < )
F1 Rat. Wistar (,')
F1 Rat, Wistar (;)
PO Mouse. CO-1 ( )
P0 Mouse. CO-1 (. J
PO Mouse, CD-1 (; )
P0 Mouse. CO-1 (.)
F1 Mouse, CD-I ( )
F1 Mouse. CD-1 (-)
Liver Weight, Relative Chang, 2018. 4409324 Multi-Generational Oral F1 Mouse. CD-1 ( .)
Experiment Name
28 Day Oral
28 Day Oral
28 Day Oral
26 Oay Oral
Multi-Generational Oral
Multi-Generational Oral
Multi-Generational Oral
Multi-Generational Oral
Mulli-Generational Oral
PFHxS Liver Weight
Liver Weight. Relative Ramhaj, 2018.4442260 Mulli-Gcncrational Oral
Livei Weighi, Absolute Chang, 201B. 4409321 Multi-Generational Oral
I tver Weight. Relative Chang, 2018 4409374 Multi-Generational Oral
Liver Weight, Absolute Chang, 2018.4409324 Multi-Generational Oral
Liver Weighi, Absolute Pfoht, 2020, 7021592 29-Week Oral
Liver Weigh I, Relative Pfohl, 2020, 7021592 29-Week Oral
L«vnr Waighl Absolute Marques. 2021 9960182 Multigenerntional Oral
Liver Weighi, Relative Marques. 2021, 9960182 Multigenerational Oral
Liver Woighl. Absolute Marques. 2021.9960182 Multigenerational Oral
Liver WeighL Relative Marques, 2021, 9960182 Multigenerational Oral
F1 Mouse. CD-1 (-)
Mouse. C57BL'6J( )
Mouse, C57BU6J (??)
P0 Mouse, CO 1 ()
F1 Mouse. CD-I < _)
F1 Mouse. CD-I ( >
F1 Mouse. CD-I ( .)
F1 Mouse, CD-I ( -)
i No significant change
A Significant Increase
~ Sign ificant doereaso
41 Dose 6
A A A A A
• A A A A
A A A A A
A
•
A
-•
-•
V
1
1
rng/kg-tlay
Figure 3-56. Liver weight responses from animal studies. Figure displays the
high and medium confidence studies included in the analysis (see Figure 3-55.
For additional details see HAWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Histopathologv
Histopathological lesions in the liver were reported in four high confidence studies using
Sprague Dawley rats fNTP. 2018a: Butenhoffetal.. 2009: 3M. 2003. 2000a) or mice fChang et al..
20181. two medium confidence study using Wistar rats fRamhai etal.. 20201 or CD-I mice, and one
low confidence study using C57BL/6 mice fHe etal.. 20221 (see Figure 3-57).
Two short-term studies evaluated histopathological responses male and female SD rats
after exposing animals to doses ranging from 2.5 to 10 mg/kg-day for 28 days, and one chronic
study evaluated effects in male C57BL/6 mice treated with 60 |a,g/kg-day PFHxS for 12 weeks.
Statistically significant increases in the incidence of hepatocellular hypertrophy14 (44% to 100%)
were observed in male SD rats exposed to PFHxS at doses >2.5 mg/kg-day (NTP. 2018a). or 10
mg/k-day f3M. 2000al (see Figure 3-58). 3M f2000al also evaluated other histological responses
(including hematopoietic cell foci, single cell necrosis, coagulative necrosis, hepatocellular
vacuolation, and inflammatory cell foci), but reported no significant exposure-related effects. Both
studies also report that female animals did not exhibit the histopathological effects observed in
male animals (NTP. 2018a: 3M. 2000a). In male C57BL/6 mice, exposure to 60 |a,g/kg-day for 12
weeks resulted in increased hepatocyte ballooning, inflammatory infiltration and fibrosis.
However, several deficiencies were identified in He etal. (2022) including lack of reporting of
histopathological effect incidences, observational bias, and chemical administration (see Figure 3-
57, and follow HAWC link for additional details).
PFHxS-induced histopathological effects were also evaluated in two multigenerational
toxicity studies. In F0 generation male SD rats or male and female CD-I mice, exposure to PFHxS
caused increased incidence of histopathological effects (see Figure 3-59), primarily hepatocellular
hypertrophy. In the rat study, F0 generation animals exposed to PFHxS for 42 days to 3 or 10
mg/kg-day increased the incidence of hepatocellular hypertrophy by 90% and 100%, but other
histological responses (including focal necrosis, lipidosis, vacuolation [midzonal or multifocal], and
chronic liver inflammation) were not significantly affected f Bute nhoff etal.. 2009: 3M. 20031.
Similar observations were made in male F0 generation CD-I mice for which exposure to 0.3,1, or 3
mg/kg-day PFHxS for 42 days increased hepatocellular hypertrophy and cytoplasmic alterations by
80%, 100%, and 100%, respectively when compared with controls fChang etal.. 20181.
Furthermore, the incidence of single cell necrosis and microvesicular fatty change were increased
(40% and 60% respectively) at the highest dose, but hepatocellular cell necrosis was not affected.
Female F0 generation rats or mice used in the Butenhoffetal. (2009) and Chang etal. (2018)
studies were exposed to PFHxS for 14 days before cohabitation and continued up to postnatal day
22. F0 generation female rats were nonresponsive to PFHxS exposure fBute nhoff etal.. 2009: 3M.
"Hepatocellular hypertrophy: a cellular response to chemical-induced stress that is considered indicative of
hepatomegaly fCattlev and Cullen. 2018: Thoolen et al.. 20101 and characterized by an increase of hepatocyte
size (Cestaetal.. 20141 It may be caused by increases in mitochondria, peroxisomes, endoplasmic reticulum,
or metabolic enzyme induction (Thoolen et al.. 20101
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20031. However, in F0 generation female CD-I mice cytoplasmic vacuolation was increased by 30%
at the highest dose (3 mg/kg-day) and hepatocellular hypertrophy and cytoplasmic alterations
(ground glass) were increased by 50 to 100% in all treated animals, but these effects were not
dose-dependent fChang etal.. 20181. F1 generation CD-I mice exposed to 3 mg/kg-day PFHxS
during gestation and lactation displayed statistically significant increases in cytoplasmic alterations
(63% incidence in males and 88% in females] and hepatocellular hypertrophy (83% incidence in
males and 88% in females) (see Figure 3-60), but the incidence of hepatocellular necrosis,
inflammation, and cytoplasmic vacuolation was not affected in F1 male or female CD-I mice (Chang
etal. 20181. A separate study using CD-I mice reported no effect on male or female F1 animals
exposed to 1 mg/kg-day PFHxS from GDI to PND20 (Marques etal.. 20211. These varying
responses in the two studies using CD-I mice fMarques etal.. 2021: Chang etal.. 20181 could have
been due to differences in experimental exposure durations: Chang, 2018, 4409324@@author-year
exposed animals before mating (14 days) and then during gestation and lactation, whereas
Marques et al. (20211 only exposed animals during gestation and lactation. Furthermore, a separate
study using Wistar rats reported no significant effects in F0 or F1 animals exposed to PFHxS (0.05
to 25 mg/kg-day) from GD7 to PND22 fRamhai etal.. 20201.
Reporting quality
Allocation
Observational bias/blinding
Confounding/variable control
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Results presentation
Endpoint sensitivity and specificity
Overall confidence
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
NR Not reported
Figure 3-57. Liver histopathology animal study evaluation heatmap. For
additional details see HAVVC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Endpoint Name Study Name Study Animal Description Dose observation time text
Design (mg/kg-day)
Hepatocellular Hypertrophy NTP, 2018,4309363 28 Day Oral Male Sprague Dawley (SD) Rat 0 Day 29
0-625 Day 29
1.25 Day 29
2.5 Day 29
5¦ Day 29
10 Day 29
Female Sprague Dawley (SD) Rat 0 Day 29
3.12 Day 29
6.25 Day 29
12.5 Day 29
25 Day 29
50 Day 29
Mldzonal'CentrilobularHypertrophy, 3M, 2000, 3981194 28 Day Oral Male Crl:Cd Br Rat 0 Study Day 28
Diffuse
10 Study Day 28
Female Crl:Cd Br Rat 10 Study Day 28
0 Study Day 28
Hepatocellular Vacuolatioh 3M. 2Q00, 3981194 28 Day Oral Male Crl:Cd Br Rat 0 Study Day 28
10 Study Day 28
Female CrhCd Br Rat 0 Study Day 28
10 Study Day 28
Hematopoietic Cell Foci 3M. 2000, 3981194 28 Day Oral Male CrfcCd Br Rat 0 Study Day 28
10 Study Day 28
Female Crl-Cd Br Rat 0 Study Day 28
10 Study Day 28
Single Cell Necrosis 3M. 2000, 3981194 28 Day Oral Mais Crl;Cd Br Rat 0 Study Day 28
10 Study Day 28
Single cell necrosis 3M. 2000, 3981194 28 Day Oral Female Crl:Cd Br Rat 0 Study Day 28
10 Study Day 28
Coagulative Necrosis, Focal 3M, 2000. 3981194 28 Day Oral Male Crl.'Cd Br Rat 0 Study Day 28
10 Study Day 28
Coagulative Necrosis, focal 3M, 2000, 3981194 28 Day Oral Female CH:Cd Br Ral 0 Study Day 28
10 Study Day 28
Inflammatory Cell Foci 3M, 2000, 3981194 28 Day Oral Male Crl:Cd Br Rat 0 Study Day 28
10 Study Day 28
Female Crl:Cd Br Rat 0 Study Day 28
10 Study Day 28
PFHxS Liver Histopathology
Statistically significant
l l incidence
1 1 1 1 1 1 1 1 1 1 1 1
0 2 4 6 8 10 12 14 16 18 20 22 24 26
incidence
Figure 3-58. Histopathology observations from short-term studies. Figure
displays the high and medium confidence studies included in the analysis. Details on
study confidence may be found in Figure 3-57. For additional details see HAWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Endpoint Name Study Name Animal Description Dose observation time text
(mgfkg-day)
t ioooroceiluar i fypertroony OutenhofT. 2009,14057159 F0 Mala CrlrCD (5D) Rot 0 Day 44
0-3 Day 44
^ Day 44
3 Day 44
IQ Day 44
F0 Female CmCD (5Dj Rat 0 Day 44
10 Day 44
Chang, 2018,4409324 F o Mala Cri:CD1 (ICR) Mouse 0 Day 42
0.3 Day 42
1 Day 42
3 Day 4?
PQ Fernsle Grl:C0l (ICR) Mouse 0 Day 42
0.3 Day 42
I Day 42
3. Day 42
Cylopliwrmc Atlawsbnn. Ground-Glass Chang, PlUti. 4409324 FD Mali* OilGDl ((CR) Mouse O Day 42
0.3 Day 42
1 Day 42
3 Day 42
f 0 t «mal* CrlCOl (ICR) Moire- 0 Day 42
03 Day 42
' Day 42
3- Day 42
Fa«y Change. Micovesicuiar Chang, 2018, 4409324 F0 Mala CrliCDI (ICR) Mouse 0 Day 42
03 Day 42
1 Day 42
3 Day 42
Fll Fetnale Cil.CDl (ICR) Muufn 0 Day 42
0 J Day 42
1 Day 42
3 Day 42
PaCMi NhcIoxis BulMri'tdN 3009, 14Q57&9 P0 MmIk C>l CD (SO) R*t O Day 44
0 3 Day 44
1 Day 44
3 Day 44
10 Day 44
F U F omnlc CrlrCD (SD) Rat 0 Day 44
10 Day 44
NiKtosk Cfiang. 2018,4409324 FQ Mali) CrlrCOl (ICR) Mouse 0 Day 42
0.3 Day 4?
i Day 42
3 Day 42
F0 Female Crl:CD1 (ICR) Mouse 0 Day 42
0.3 Day 42
i Day 42
3 Day 42
Lvor -Steatosis Marques, 2021,9S60182 3D P0 Fomoto CO 1 Mica 0 21 PNO
1 21 F*ND
MFD HO Fwtalo C3M Mice 0 21 PNO
1 21 PNO
PFHxS Liver Histopathology
¦¦Statistically stgnldnnl
;
I
I f I I l I i r t t 1 I
0 2 4 6 8 10 12 14 16 10 20 22 24 26
Figure 3-59. Histopathology observations from developmental toxicity studies
(F0 generation animals). Figure displays the high and medium confidence studies
included in the analysis. Details on study confidence may be found in Figure 3-57.
For additional details see HAWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Endpoinl Name Study Name Animal Description
Hepatocellular I lyp®rtrophy, Chwici, 201B. 4409324 r 1 Mole CrlrCDi < ICR) Mouse
Cenlrltobulor
F1 Fu»Mo CrliCUl (ICR) Mouau
Cytoplasmic AHwtillon Cheng, 2018, *4cfft3a Ft MenoCtlrCDi (ICR) Mouse
P1 FtimftlH Crl CD1 (ICR) Mourn
CyTopiasmtc Vflc*J03b
3
PND36
3
0
PND3G
3
PND36
0
PND36
3
PND36
PNQ36
PND36
J
0
3
HS'otntiqvXIy 3»gnt1i
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
using CD-I mice treated with 0, or 1 mg/kg-day PFHxS also reported no effects on serum ALT in F0
dams sampled on PND21 or male or female F1 animals sampled on PND5, 21, or 90 (Marques etal..
20211.
Two short-term studies using SD rats and one chronic exposure study using C57BL/6J mice
evaluated serum levels of AST, ALT, ALP, and bile salts/acids after exposure to doses ranging from
0.6 to 10 mg/kg-day PFHxS for 28 days fNTP. 2018a: 3M. 2000al. 3M f2000al reported that ALP
was statistically increased by 20% in male SD rats exposed to 10 mg/kg-day, but a similar study by
NTP observed no exposure-related effects fNTP. 2018al. Serum levels of ALT or AST were not
affected in male or female SD rats in either study fNTP. 2018a: 3M. 2000al. However, a chronic
exposure study using male C57BL/6J reported a 42% increase in ALT after exposure to 0.6 mg/kg-
day for 12 weeks. fNTP. 2018al also evaluated serum levels of albumin and total protein in male
and female SD rats and reported no significant exposure-related effects fNTP. 2018al. Serum
globulin levels were statistically decreased by 14% to 15% in male SD rats exposed to 10 mg/kg-
day PFHxS for 28 days fNTP. 2018a: 3M. 2000al. and bilirubin was significantly decreased by 12%
to 21% in male SD rats after 28 days of exposure to PFHxS at doses ranging from 2.5 to 10 mg/kg-
day fNTP. 2018al. The 3M and NTP studies also evaluated female animals and reported no
exposure-related effects.
One study using APOE*3-Leiden.CETP male mice, an animal model that better emulates
human lipoprotein profiles, evaluated PFHxS-induced changes in hepatic triglyceride, cholesterol
esters, and free cholesterol levels. Exposure to 6 mg/kg-day PFHxS for 42 days resulted in a 67%
increase in liver triglyceride levels, but free cholesterol levels were not affected (Biiland etal..
20111. These observations suggest PFHxS exposure may alter hepatic function in a manner relevant
to humans and they are supported by mechanistic studies evaluating PFHxS-induced alterations in
the liver of wild-type and genetically modified animals (see mechanisms section below).
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Endpoint sensitivity and specificity
Overall confidence
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
B Critically deficient (metric) or Uninformative (overall)
Not reported
Figure 3-61. PFHxS liver serum biomarkers animal study evaluation heatmap.
For additional details see HAWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Endpoint Name
Study Name
Animal Description
Duration of exposure
PFHxS Liver/Hepatobiliary Serum Biomarkers
Alanine Aminotransferase (ALT)
NTP, 2018, 4309363
Rat, Sprague-Dawley (J)
28 Days
# No significant change
3M, 2000,3981194
Rat, Crl:Cd Br(i')
28 Days
/\ Significant increase
•
Rat, Crl:Cd Br(r)
28 Days
~ Significant decrease
•
Butenhoff, 2009, 1405789
P0 Rat, Sprague-Dawley ( ')
44 Days
t • • •
P0 Rat, Sprague-Dawley (+)
PND 22
Marques, 2021,9960182
P0 Mouse, CD-1 (V)
GD1-19
•
He,2022, 10273379
Mouse, C57BL/6 (f)
84 days
A
Aspartate Aminotransferase (AST)
NTP, 2018, 4309363
Rat, Sprague-Dawley (; )
28 Days
Rat, Sprague-Dawley (-)
28 Days
3M, 2000, 3981194
Rat, Crl:Cd Br ( ')
28 Days
V
Rat, Crl:Cd Br (i)
28 Days
•
Butenhoff, 2009, 1405789
P0 Rat, Sprague-Dawley ( .")
44 Days
•—•—•—•
P0 Rat, Sprague-Dawley ('+)
PND 22
•—•—• •
Alkaline Phosphatase (ALP)
NTP, 2018, 4309363
Rat, Sprague-Dawley (-)
28 Days
Rat, Sprague-Dawley (>)
28 Days
3M, 2000, 3981194
Rat, Crl;Cd Br ( )
28 Days
A
Rat, Crl:Cd Br (-+)
28 Days
•
Butenhoff, 2009, 1405789
P0 Rat, Sprague-Dawley (;)
44 Days
• • •< A
P0 Rat, Sprague-Dawley (',')
PND 22
• • • •
Bile Salt/Acids
NTP, 2018, 4309363
Rat, Sprague-Dawley (,-')
28 Days
Rat, Sprague-Dawley (9)
28 Days
Direct Bilirubin
NTP, 2018, 4309363
Rat, Sprague-Dawley ( )
28 Days
Rat, Sprague-Dawley (L;)
28 Days
Total Bilirubin
NTP, 2018, 4309363
Rat, Sprague-Dawley (.-")
28 Days
• V V-V
Rat, Sprague-Dawley (v)
28 Days
3M, 2000, 3981194
Rat, CrlrCd Br (.')
28 Days
•
Rat, Crl:Cd Br (i)
28 Days
•
Butenhoff, 2009, 1405789
P0 Rat, Sprague-Dawley (•/)
44 Days
• • • •
P0 Rat, Sprague-Dawley (+)
PND 22
• • • •
Chang,2018, 4409324
P0 Mouse. CD-1 (.-?)
42 Days
• • ~
Triglyceride (TRIG)
Bijland, 2011. 1578502
Mouse. Apoe*3-Leiden.Cetp (-')
42 Days
A
Albumin
NTP, 2018, 4309363
Rat, Sprague-Dawley (_*)
28 Days
Rat, Sprague-Dawley (£)
28 Days
3M, 2000,3981194
Rat, Crl:Cd Br ( •?)
28 Days
•
Butenhoff, 2009. 1405789
P0 Rat, Sprague-Dawley (;?)
44 Days
• • • ~
Globulin
NTP, 2018, 4309363
Rat, Sprague-Dawley ( )
28 Days
Rat, Sprague-Dawley (v)
28 Days
3M, 2000, 3981194
Rat, Crl;Cd Br ( ;)
28 Days
V
Rat, Crl:Cd Br (V)
28 Days
•
Albumin/Globulin (A/G) Ratio
NTP, 2018, 4309363
Rat, Sprague-Dawley (.-')
28 Days
Rat, Sprague-Dawley (v)
28 Days
3M, 2000, 3981194
Rat, Crl:Cd Br (•')
28 Days
A
Butenhoff, 2009, 1405789
P0 Rat, Sprague-Dawley (;)
44 Days
• • A
Total Protein
NTP, 2018, 4309363
Rat, Sprague-Dawley (c )
28 Days
Rat, Sprague-Dawley (V)
28 Days
Liver Cholesteryl Esters
Bijland, 2011, 1578502
Mouse. Apoe*3-Leiden.Cetp
42 Days
•
Liver Free Cholesterol
Bijland, 2011,1578502
Mouse, Apoe*3-Leiden.Cetp (-")
42 Days
A
Liver Triglycerides
Bijland. 2011, 1578502
Mouse, Apoe*3-Leiden.Cetp ( )
42 Days
A
0.01
0.1
1 1 1
1 10 100
mg/kg-day
Figure 3-62. PFHxS liver/hepatobiliary serum biomarkers. Figure displays the
high and medium confidence studies included in the analysis (see Figure 3-61). For
additional details see HAVVC link.
Mechanistic Evidence and Supplemental Information
Mechanistic evidence relevant to PFHxS-induced effects was collected from the peer-
reviewed literature and from in vitro high-throughput screening (HTS) assays from the ToxCast and
Tox21 databases accessed via EPAs Chemicals Dashboard. The available in vitro and in vivo studies
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were evaluated based on a proposed mode of action (MOA) for liver injury for PFOS and PFOA, two
structural analogs of PFHxS and among the most well-studied PFAS (U.S. EPA. 2019c). Further, an
AOP-based approach was employed to organize and discuss the evidence according to the following
levels of biological organization: molecular events, cellular effects, organ effects, and organism
effects. Reponses informative of later two biological levels of organization are presented in the
preceding hazard sections. Refer to Appendix C for more details on the objective and methodology
of the mechanistic evaluation undertaken herein, and a description of the proposed MOA for PFAS-
induced hepatotoxicity (see Appendix C, Section 2). A detailed summary of the HTS data analysis
can be found in Appendix C, Section 3.
Molecular Initiating Events
The available studies have examined several nuclear receptor and cell signaling pathways
associated with chemical-induced liver toxicity. Many of the hepatic effects caused by exposure to
perfluorinated compounds such as PFHxS have been attributed to activation of the peroxisome
proliferator-activated receptor alpha (PPARa16) (Das etal.. 2017: Gleason. 2017: NTDWOI. 2017:
Rosen etal.. 2017: U.S. EPA. 2016a. b). In vivo studies using SD rats or several strains of mice report
that exposure to PFHxS results in activation of PPARa and increased expression of PPARa-
responsive genes f Chang etal.. 2018: NTP. 2018a: Das etal.. 2017: Rosen etal.. 2017: Biiland et al..
20111. Two cell culture studies using rat FaO hepatoma cells or primary mouse hepatocytes also
reported altered expression of PPARa-responsive genes (Biork etal.. 2021: Rosen etal.. 20131.
PFHxS also activates the human PPARa. PFHxS caused PPARa activation in human hepatoma cell
lines Rosenmai etal. (20181 and in primary human hepatocytes exposure was associated with
increased expression of PPARa-responsive genes (Rosen etal.. 20131. Overall, these studies suggest
that PFHxS exposure can activate PPARa in animal in vivo and in vitro studies, and in human liver
cell culture models.
Animal studies also provide evidence suggesting that additional nuclear receptor pathways
may be involved in PFHxS-induced liver effects. Two studies using genetically modified animals
reported increases in absolute and relative liver weight in both wild-type and PPARanull animals
(Das etal.. 2017: Rosen etal.. 20171. However, one study (Rosen etal.. 20171 also reported that
these effects were reduced in PPARa-null mice. Gene expression analyses in both wild-type and
PPARanull animals report that in addition to PPARa, other hepatocellular receptors that are known
to play a role in liver function can be affected by PFHxS exposure. These include: PPARa, the
constitutive androstane receptor (CAR), and the pregnane x receptor (PXR) f Chang etal.. 2018:
Rosen etal.. 2017: Biiland etal.. 2011: 3M. 20101. A 28-day study using SD rats also reported
increased mRNA levels of CAR/PXR-responsive genes (NTP. 2018a). suggesting these molecular
16PPARa is a member of the nuclear receptor superfamily that can be activated endogenously by free fatty
acid derivatives. PPARa plays a role in lipid homeostasis, but it is also associated with cell proliferation,
oxidative stress and inflammation (Li et al.. 2017a: Mellor etal.. 2016: Hall etal.. 20121.
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effects are conserved across rodent models. Furthermore, PFHxS was able to activate nuclear
receptors other than PPARa, in human cells (including PPARa, RXR, LXR, FOS, and NRF2; see
Appendix C). Activation of these hepatic nuclear receptors plays an important role in regulating
responses to xenobiotics, energy and nutrient homeostasis, and development of fatty liver disease17
fMackowiaket al.. 2018: Angrish etal.. 2016: Mellor etal.. 2016: di Masi etal.. 20091.
Cellular Effects
As discussed below, the available studies provide evidence for PFHxS-induced alterations in
reactive oxygen species production, cellular stress, and alterations in liver metabolic functions.
Excessive production of reactive oxygen species (ROS) is considered a mechanism
associated with PFAS-induced hepatocellular toxicity fLi etal.. 2017a: U.S. EPA. 2016a. b) and fatty
liver disease fWahlang etal.. 2019: Toshi-Barve etal.. 20151. One in-vivo study using C57BL/6J mice
reported increased mRNA levels of genes associated with oxidative stress, after exposure to 0.15
mg/kg-day for 25 weeks (Pfohl etal.. 20201. Two cell culture studies using HepG2 human
hepatocytes present conflicting evidence fOio etal.. 2021: Wiels0e etal.. 20151. While both studies
exposed cells for the same duration (24 hours) and similar concentrations (0, 0.02, 0.2, 2, 20, 200
|j.M in fWielsae etal.. 20151: and 0, 0.2, 2, 20 |a,M in fOio etal.. 202111 only fWielsae etal.. 20151
observed increased intracellular ROS production and neither study observed exposure-related
changes in cellular antioxidant levels.
PFHxS-induced alterations in hepatic lipid metabolism were evaluated in three in vivo
studies using mice and in one cell culture study using primary rat hepatocytes. In mice PPFhX
exposure is associated with increased mRNA levels of genes associated with lipid synthesis,
metabolism, and transport (Pfohl etal.. 20201. and liver cell lipid content and size (Das etal.. 20171.
Similar have been reported in genetically modified PPARa-null mice (Das etal.. 20171. However,
PPARa-null animals also had higher (sevenfold) baseline levels of cellular lipids when compared
with wild type SV129 control mice fDas etal.. 20171. The same study used WY-14643, a PPARa
activator, as a positive control and observed no significant effects in hepatic lipid accumulation in
WY-14643-exposed PPARa-null animals, suggesting that PFHxS-induced lipid accumulation in
genetically modified animals is mediated mostly (or entirely) via a PPARa-independent mechanism
(Das etal.. 20171. Das etal. (20171 also observed that PFHxS exposure did not have an impact on
fatty acid beta-oxidation in wild-type and PPARa-null animals, and a separate in vitro experiment
by the same group reported no significant exposure-related effects on rat hepatic mitochondria
17Fatty liver (steatosis) is a hepatic response to moderate alcohol consumption, xenobiotic exposure, or other
factors that may alter metabolic functions (Roth etal.. 2019: loshi-Barve et al.. 2015: Wahlang et al.. 20131. It
is characterized by excessive lipid accumulation in hepatocytes fAngrish et al.. 20161 and is considered a
reversible response when the stimulus is temporary fRoth etal.. 20191. However, steatosis increases
susceptibility to other insults and persistent steatosis is considered a precursor to other forms of liver disease
(Bessone et al.. 2019: Roth etal.. 20191. When combined with inflammation (steatohepatitis) fatty liver can
progress to fibrosis and cirrhosis (Roth etal.. 2019: Wahlang et al.. 20131.
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fatty acid beta-oxidation. Two studies evaluated hepatic triglyceride (TG) content and report that
PFHxS exposure led to increased liver TG levels in wild-type and AP0E*3-Leiden.CETP mice (Das et
al.. 2017: Biiland etal.. 20111. a genetically modified animal model used to investigate cholesterol
metabolism and cardiovascular disease. However, Das etal. f20171 also observed that PPARa-null
animals appeared to be less sensitive to this effect fDas etal.. 20171. Gene expression analysis
revealed that in both wild-type and PPARa-null animals PFHxS treatment resulted in altered
expression of genes associated with peroxisomal and mitochondrial fatty acid metabolism and
increased levels of genes associated with fatty acid and triglyceride transport and synthesis fDas et
al.. 20171. However, these responses were also attenuated in the PPARa-null mice fDas etal.. 20171.
The available studies suggest that PFHxS may alter hepatic lipid metabolism in animal models.
Experiments using genetically modified animals suggest that PPARa activation plays a role in the
metabolic responses described above, but other pathways are likely involved. Overall, the metabolic
effects reported in the Das etal. (20171 and Biiland etal. (20111 studies are considered to be
potential indicators of toxicant-induced alterations in hepatocyte function, which can result in
abnormal metabolism and accumulation of fatty acids leading to steatosis (Wahlang et al.. 2 019:
Angrish et al.. 20161. Biological understanding suggests that such changes can, in turn, increase
lipotoxicity susceptibility to other hepatic insults or independently progress to steatohepatitis
fRoth etal.. 2019: Mendez-Sanchez etal.. 2018: Yang etal.. 20141.
Cytotoxicity induced by PFHxS exposure was evaluated in two cell culture studies using
HepG2 humanhepatocytes (Oio etal.. 2021: Oio etal.. 20201. Ojo, 2020, 6333436 reported
increased cytotoxicity at an effective dose of 183 |a,M. (Oio etal.. 20211. did not report PFHxS-
induced changes in cytotoxicity. However, this was a mixture study designed to evaluate the
combined effects of PFHxS with other PFAS and (Oio etal.. 20211 selected concentrations below
their previously identified effective dose of 183 |a,M.
Conclusions from Mechanistic Evidence
Mechanistic evidence from in vivo and in vitro rodent cell models suggests that PFHxS
activates several hepatic xenobiotic-sensing nuclear receptors and other cell signaling pathways,
namely PPARa, PPARa, CAR, PXR, and LXR. PFHxS exposure was also associated with alterations in
hepatic ROS production, cellular stress, and abnormal liver function related to lipid metabolism in
animals (including genetically modified mouse models). The molecular and cellular mechanisms
induced by PFHxS exposure in these models have been implicated in chemical-induced liver
diseases such as steatosis, steatohepatitis, and fibrosis (Angrish etal.. 2016: Mellor etal.. 2016:
Toshi-Barve etal.. 2015: Wahlang etal.. 20131. and provide support for the biological plausibility of
the observed liver effects (i.e., histopathological responses, biomarkers of altered liver function and
lipid accumulation, and organ weight changes) in short-term oral studies on PFHxS.
Available mechanistic information in human models is limited to two in vitro studies in the
peer-reviewed literature and HTS assays from the ToxCast databases accessed via EPAs Chemicals
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Dashboard. As described in Appendix C-3, none of the 54 available assays in the ToxCast database
using the human hepatoma HepG2 cells were responsive to PFHxS treatment These HTS assay
findings are inconsistent with the observations from the other two in vitro studies Wielsae etal.
f20151 and Rosenmai etal. f20181. which also used HepG2 cells and reported that PFHxS exposure
promotes activation of the human PPARa and increased reactive oxygen species production.
Additional studies are needed to resolve these conflicting results.
Overall, the mechanistic evidence on pathways known to be associated with liver toxicity
(i.e., increased oxidative stress and altered lipid metabolism) provides biological plausibility for the
liver effects observed in animal bioassays. The available mechanistic evidence provides some
support for a possible role for both PPARa-dependent and PPARa -independent mechanisms in the
hepatic responses to PFHxS exposure, including hepatocellular hypertrophy, increased cellular lipid
content, and increased liver weight observed in animal studies. Limited evidence from in vitro
studies suggest that some responses may also be activated in human cellular models, including
nuclear receptor and transcription factor pathways that regulate liver functions (i.e., PPARa/y, CAR,
PXR, RXR, LXR, FOS, NRF2), and outcomes indicative of oxidative stress and altered metabolism. As
described above activation of these nuclear receptor and cell signaling pathways is associated with
changes in hepatic functions, lipid accumulation, and progression of fatty liver disease. However,
inconsistencies between the available peer-reviewed studies using human cell culture models and
HTS assays from the ToxCast database suggest that additional experiments are needed.
Considerations for potentially adaptive versus adverse responses
Increases in liver weight and hepatocyte hypertrophy were observed in rodents with PFHxS
administration in short-term oral studies. Enlargement of the liver and/or individual hepatocytes is
a common chemical-induced response that can involve lipid accumulation (e.g., micro- or macro-
vesicular steatosis), organellar growth and proliferation (e.g., peroxisomes, endoplasmic
reticulum), increased intracellular protein levels (e.g., Phase I and II enzymes), and altered
regulation of gene expression (e.g., stress response, nuclear receptors) (reviewed by Battand
Ferrari (1995)). Hepatocyte hypertrophy related to organelle growth and proliferation in response
to activation of xenobiotic-sensing receptors (primarily PPARa) is often considered an adaptive
response (Hall etal.. 2012). Histological and clinical effects considered adverse responses in the
liver (e.g., increased hepatic inflammation, and elevated serum markers of hepatocyte damage (Hall
etal.. 201211 were reported in the study by fHe etal.. 20221. However, the study by He etal. f20221
was considered low confidence due to issues related with evidence reporting and animal allocation
to exposure groups, and the other in vivo studies described above also evaluated hepatocellular
necrosis, inflammation and serum markers of liver disease and they report no PFHxS-induced
changes (see synthesis of histopathology and serum biomarkers of liver function above). In the
absence of concordant histopathological evidence of degenerative changes or other changes
indicative of adverse responses, the available evidence supports an interpretation that the
responses to PFHxS observed in the currently available animal studies are considered adaptive.
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Evidence Integration
The available evidence suggests but is not sufficient to infer that exposure to PFHxS might
cause hepatobiliary system effects in humans given sufficient exposure conditions18. This is due to
limitations in the available evidence that introduce significant uncertainty (see Table 3-23).
The available evidence on PFHxS-induced hepatic effects in humans is considered slight.
There is some evidence of an association between PFHxS exposure and hepatic effects in human
studies that is based on largely consistent associations with liver biomarkers (primarily small
increases in ALT, a specific biomarker of potential liver injury) in the blood in multiple studies of
adults. In addition, one study of liver disease found that in children with nonalcoholic fatty liver
disease, PFHxS exposure was associated with severe disease. However, there were no additional
studies of clinical liver effects available, and so it is not possible to evaluate whether the small
changes in liver enzymes observed in the biomarker studies translate into clinical hepatic injury.
There is also some unexplained inconsistency across studies and incoherence across liver enzymes
other than ALT that further reduces the strength of the evidence.
The available evidence on PFHxS-induced hepatic effects in animal toxicity studies is
considered slight. The evidence from short-term and multigenerational animal studies provides
evidence of PFHxS-induced effects on multiple endpoints relevant to the assessment of liver
responses to chemical exposure (including organ weight changes, histopathology [hepatocellular
hypertrophy], and lipid accumulation). Alterations in serum biomarkers of liver/hepatobiliary
function (ALT, ALP, bile salts/acids, and globulin) were observed in SD rats (NTP. 2018a: Butenhoff
etal.. 2009: 3M. 2003. 2000b). and C57BL/6J and CD-I mice (Chang etal.. 2018). However, as
described above, responses such as alterations in ALT, ALP and albumin were not consistently
observed in similar short-term fNTP. 2018a: 3M. 2000bl. sub-chronic and chronic fHe etal.. 2022:
Chang etal.. 2018: Butenhoff et al.. 20091. or multigenerational fMarques etal.. 2021: Chang etal..
2018: Butenhoff etal.. 2009: 3M. 20031 studies, and markers considered indicative of
hepatocellular toxicity (ALT and AST) (Hall etal.. 2012) were not affected in the available studies
C Chang etal.. 2018: NTP. 2018a: Butenhoff etal.. 2009: 3M. 2003. 2000b).
Increased liver weights were reported in SD rats after 28 to 44 days of exposure (NTP.
2018a: Butenhoff et al.. 2009: 3M. 2003. 2000b) and in APOE*3-Leiden.CETP and CD-I mice treated
with PFHxS for 42 to 44 days f Chang etal.. 2018: Biiland etal.. 20111. Alterations in histological
responses were also observed in the available studies and responses such as hepatocellular
hypertrophy were consistently observed after short-term exposure in male rats and mice fNTP.
2018a: Butenhoff et al.. 2009: 3M. 2000b) and F1 generation male and female mice (Chang etal..
2018). He etal. (2022) observed evidence of increased hepatic inflammation, but as described
above several issues were identified with this study which lowers our confidence to low, and other
outcomes indicative of hepatocellular degeneration (e.g., vacuolization) or injury (e.g., necrosis)
18 The "sufficient exposure conditions" are more fully evaluated and defined for the identified health effects
through dose-response analysis in Section 5.
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(Hall etal.. 20121 were unaffected in the available short-term and multigenerational studies (Chang
etal.. 2018: Bute nhoff etal.. 2009: 3M. 20031. Responses such as single cell necrosis might progress
to more severe effect after continued exposure fThoolen etal.. 20101. but the available information
from short-term studies is not sufficient to determine whether the observed histological effects can
evolve to clearly adverse hepatic injuries with continued exposure. Exposure to PFHxS also resulted
in increased hepatocyte lipid accumulation in exposed APOE*3-Leiden.CETP fBiiland etal.. 20111.
as well as wild-type and PPARa-null, mice (Das etal.. 20171 suggesting that PFHxS exposure may
have the potential to promote fatty liver development, including in the absence of PPARa. In
general, the responses observed in animals exhibited a dose-response gradient
Analysis of mechanistic data from in vivo and in vitro rodent models provide biological
plausibility for the apical effects reported in the short-term and multigenerational oral studies
summarized above. Exposure to PFHxS was associated with the activation of several molecular
signaling pathways and altered cellular functions thought to be involved in the MOA for liver
toxicity of well-studied PFAS such as PFOA and PFOS (see synthesis of Mechanistic evidence and
supplemental information above for more details). Additionally, the evidence for PFHxS-mediated
liver effects point to potential PPARa-dependent and -independent pathways, which is consistent
with the mechanisms of potential hepatotoxicity for related perfluorinated compounds fATSDR.
2018b: Li etal.. 2017a: U.S. EPA. 2016a. b).
Potential adverse liver effects caused by exposure to PFHxS and other PFAS have been
attributed, in part, to activation of PPARa (ATSDR. 2018b: Li etal.. 2017a: U.S. EPA. 2016a. b).
However, in addition to PPARa, PFHxS exposure appears to promote activation of other nuclear
receptor pathways (PPARy, CAR, PXR, LXR, and transcriptional factors, FOS, and NRF2) and
responses indicative of oxidative stress and cellular damage were observed in human liver cell
models (see synthesis of Mechanistic studies and supplemental information above for more
details). In addition, studies of PFHxS in PPARa-null mice indicate that many of the observed
responses are unaffected by loss of PPARa-signaling. Therefore, the available evidence supports the
interpretation that PPARa-dependent and -independent mechanisms mediate PFHxS-induced
effects in animals.
The available mechanistic evidence supports that PFHxS exposure may induce fatty liver
disease, but subchronic and chronic duration studies are not available to inform whether the
observed PFHxS-induced effects progress to adverse responses (e.g., steatosis and steatohepatitis)
in animal models.
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Table 3-23. Evidence profile table for oral PFHxS exposure and liver effects
Evidence stream summary and interpretation
Evidence integration
summary judgment
Evidence from studies of exposed humans (see Hepatic Human Studies Section)
Studies and
confidence
Serum Biomarkers
10 medium and 2 low
confidence studies
Factors that increase
certainty
Factors that decrease
certainty
Most medium
• Unexplained
confidence
inconsistency for
studies reported
biomarkers other
an effect
than ALT
Consistency
• Lack of
increased ALT in
coherence across
adults
biomarkers
Precision in three
• Unclear
studies
biological
significance of
small changes in
ALT
Summary and key
findings
Positive
associations
observed
between PFHxS
and ALT in
multiple studies.
Direction of
association with
other liver
biomarkers
varied within
and across
studies.
1 study of liver
disease reported
a positive
association (p >
0.05) with
severe disease.
Evidence stream
judgment
©oo
Slight
Based on largely
consistent, but
uncertain, increases
in ALT in adults
Evidence from in vivo animal studies (see Hepatic Animal Studies Section)
©OO
Evidence suggests, but is not
sufficient to infer
Based primarily on small
increases in ALT in men and
women, and consistent, but
possibly not adverse, hepatic
effects in rodents
Human relevance:
Limited studies in human in vitro
models suggest activation of
molecular and cellular responses
observed in rodent models are
relevant to human toxicity
Cross-stream coherence:
Alterations in serum biomarkers
of hepatobiliary injury were
reported in animals and in a few
epidemiological studies, although
the observations are uncertain,
and the markers affected
differed across species.
Susceptible populations and
lifestages:
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Evidence stream summary and interpretation
Evidence integration
summary judgment
Studies and
confidence
Factors that increase
certainty
Factors that decrease
certainty
Summary and key
findings
Evidence stream
judgment
None identified, although those
with pre-existing liver disease
could potentially be a greater risk
Organ Weight
5 high and 3 medium
and confidence
studies in rats and
mice
• 28-d (x2)
• 42-d
• 203-d
• Gestational (x4)
• Consistent
increases, across
studies
• Dose-response in
studies reporting
effects
• Coherence with
histopathology in
male rats and
mice
• All high or
medium
confidence
studies
• Unclear
biological
significance
(adversity) of the
combined
hepatic findings
in animals across
endpoints
• Dose-related
increases in liver
weights
reported at
doses ranging
from 1.25 to 50
mg/kg-d rat and
mouse studies,
and a gestational
exposure study
in mice
©oo
Slight
Based on consistent,
coherent, and dose-
dependent increases
in organ weight and
related
histopathology.
However, the current
evidence is
insufficient to
support the adversity
of the changes.
Histopathology
4 high, 1 medium,
and 1 low confidence
studies in rats and
mice:
• 28-d (x2)
• 84-d
• Gestational (x3)
• Consistent
cellular
hypertrophy
across studies
and species
• Coherence with
liver weight
effects
(especially at
high doses)
• Dose response
• Unclear
biological
significance
(adversity) of
histopathological
changes (e.g., no
necrosis
observed) as well
as the combined
hepatic findings
in animals across
endpoints
• Hepatocellular
lesions observed
in rats and mice
including
hepatocellular
hypertrophy in
mice exposed to
>0.3 mg/kg-d
and rats exposed
to 2.5 mg/kg-d.
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Evidence stream summary and interpretation
Evidence integration
summary judgment
• All high
confidence
studies
Serum Biomarkers
4 high confidence
studies in rats and
mice:
• 28-d (x2)
• 44-d
• 42-d
1 high and 2 medium
confidence studies in
mice
• 42-d
• 84-d
• Gestational (xl)
• Dose response
• Affected
biomarker (ALP)
not specific to
liver
• Inconsistent
evidence on ALT
levels
• No effects on
AST)
• Unclear
biological
significance
(adversity) of the
combined
hepatic findings
in animals across
endpoints
• Dose-related
increases in
biomarker (ALP)
in male mice and
rats exposed to
3 or 10 mg/kg-d
respectively
• Increased serum
ALT in 1 mouse
study
• Increased
marker of
altered function
(tissue
triglyceride
levels) in mice
exposed to 6
mg/kg-d
Mechanistic evidence and supplemental information (see Mechanistic Studies and Supplemental Information
Section)
Biological events or
pathways
Summary of key findings, interpretation, and limitations
Evidence stream
judgment
Molecular initiating
events — PPARa
Key findings and interpretation:
• Activation of hepatic PPARa in rat and mouse models. Some
evidence of PPARa activation in human in vitro models.
Evidence indicates a
role for PPARa-
dependent and -
independent
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Evidence stream summary and interpretation
Evidence integration
summary judgment
• In vivo PFHxS exposure increased expression of PPARa-
responsive genes in wild-type and hPPARa mice.
Limitations: No evidence in humanized in vivo models.
Inconsistencies in peer-reviewed and ToxCast/Tox21 studies using
human hepatoma HepG2 cells.
pathways in the MOA
for noncancer liver
effects of PFHxS.
Limited in vitro
studies suggest some
responses may be
activated in human
molecular/cellular
models.
Molecular initiating
events — PPARg
Key findings and interpretation:
• Activation of PPARy in mouse (in vivo) and human (in vitro)
models.
• Increased expression of PPARy-responsive genes in vivo; and
induction of PPARy transactivation in human hepatoma HepG2
cells.
Limitations: Few studies and no evidence in humanized in vivo
models.
Molecular initiating
events — CAR/PXR
Key findings and interpretation:
• Increased expression of CAR/PXR-responsive genes in mice.
Limitations: No evidence in humanized in vivo or in vitro models.
Molecular initiating
events — other
pathways
Key findings and interpretation:
• Limited in vivo evidence supports activation of cell signaling
pathways related to altered hepatic metabolism and
oxidative/cellular stress responses (RXR, LXR, FOS, and Nrf2).
Limitations: Few studies and no evidence in humanized in vivo or in
vitro models.
Cellular effects
Key findings and interpretation:
• Increased hepatic lipid content and altered expression of genes
associated with fatty acid and triglyceride metabolism.
• Increased ROS production and markers of cellular
stress/cytotoxicity in HepG2 cells.
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Evidence stream summary and interpretation
Evidence integration
summary judgment
Limitations: Few in vivo studies examining cellular toxicity,
functions, other cell signaling pathways, and no evidence in
humanized in vivo models. Inconsistencies in the in vivo and in vitro
results likely due to differences in experimental model and/or design
features.
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3.2.5. Neurodevelopmental Effects
The available database examining potential nervous system effects of PFHxS exposure was
composed of 17 epidemiological and 2 animal studies. All the studies in the evidence base examined
the effects of PFHxS in children or, in animal studies, exposed animals during early lifestages to
examine potential effects on neurodevelopment manifest in later lifestages (i.e., testing in newborn,
juvenile, or adult rats). Therefore, this section examines and discusses the evidence on PFHxS-
induced effects on the developing nervous system. For information on other developmental effects
please see Section 3.2.3.
Human Studies
Twenty-two studies (reported in in 31 publications) examined associations between PFHxS
exposure (measured in blood) and neurodevelopmental outcomes. Neurodevelopment is typically
assessed with a wide array of neurobehavioral or neuropsychological tests, which makes it difficult
to draw clear-cut divisions of neuropsychological categories. For example, a longer mean reaction
time (a measure of response time after a stimulus is introduced) on a continuous performance test
typically indicates inattention but may also be affected by slower information processing or motor
response. For the purposes of this review, and due partly to data availability, tests were organized
into the following categories: (1) cognition, (2) Attention Deficit Hyperactivity Disorder (ADHD) or
related behaviors, (3) social behavior or autism spectrum disorder, and (4) other outcomes. Nine
studies evaluated cognition, which comprised several endpoints including IQ, executive function,
language development, and intellectual disability. Seven studies evaluated ADHD or related
behaviors, which included ADHD diagnosis, inattention, impulsivity, hyperactivity, and
externalizing problems. Five studies evaluated social behavior and included autism spectrum
disorder (ASD) diagnosis, and two different autism screening scores, although there is overlap with
the behaviors assessed with ADHD. Given the heterogeneity in the tools and age ranges used in the
studies, it can be difficult to assess consistency within these categories. Other outcomes included
motor effects (three studies) and cerebral palsy (one study).
There were several considerations specific to the use of neuropsychological tests for
assessing children. For outcome ascertainment, tests used in a study should be appropriate for the
age range being studied and for the culture and language. Other relevant factors, such as time of day
of test administration or computer use, should have been considered, and some description of the
testing environment should have been provided. If there were multiple raters, this factor should
have been considered (e.g., statistical adjustment for rater, or analysis of interrater reliability).
While blinding to exposure is ideal, this information was not commonly reported, and it was
considered unlikely that participants or the outcome assessors would have knowledge of PFHxS
exposure levels during testing. Therefore, no blinding or lack of reporting on blinding was
determined to be unlikely to cause outcome misclassification. Evaluation of confounding was based
on the approach used by the study authors to identify potential confounders; confounders that
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
were considered potentially relevant across studies included child age and sex, maternal age,
socioeconomic status, quality of caregiving environment, prenatal tobacco exposure, and parental
mental health and IQ. It was considered preferable for analyses to use the outcome scales as
continuous variables to minimize misclassification into artificial categories and improve statistical
power fSagiv etal.. 20151. although this does not apply to clinical diagnosis of conditions such as
ASD and ADHD.
The majority of available studies were birth cohorts or case-control studies nested in birth
cohorts that evaluated maternal exposure to PFHxS during pregnancy (Yao etal.. 2022: Dalsager et
al.. 2021b: Oh etal.. 2021: Skogheim etal.. 2021: Luo etal.. 2020: Spratlen etal.. 2020a: Niu etal..
2019: Harris etal.. 2018: Liewetal.. 2018: Haver etal.. 2017: Teddy etal.. 2017: Oulhote etal.. 2016:
Vuong etal.. 2016: Wanget al.. 20151. Some of these studies were considered adequate rather than
good for exposure measurement due to variations in the timing during gestation of sample
collection across participants within each study. While the half-life of PFHxS is long and exposure
levels are unlikely to have changed drastically during pregnancy, changes in hemodynamics during
pregnancy may influence levels in the blood at different points during pregnancy. In some cohort
studies, childhood exposure was measured as well (Harris etal.. 2018: Vuong etal.. 2018a: Oulhote
etal.. 20161. There was one case-control study with measurements from banked maternal samples
fLvall etal.. 20181 and one case-control study with maternal samples taken concurrently with
outcome measurement fShin etal.. 20201. In addition, there were three cross-sectional studies,
based on data from NHANES (Hoffman etal.. 20101. the C8 Health Project (Stein and Savitz. 20111.
and a survey in the United States (Gump etal.. 20111. While the exposures measured in these
studies with concurrent exposure and outcome measurement may not represent an etiologically
relevant period, particularly for capturing any influence of exposure on the genetic component of
ADHD, these studies were considered adequate for exposure measurement due to the long half-life
of PFHxS and since exposure levels are generally expected to be fairly stable over time. Reverse
causation is not a concern for these outcomes because neuropsychological performance is unlikely
to influence PFHxS levels. The study evaluations are summarized in Figure 3-63.
For data extraction and synthesis, when multiple exposure measures from different time
points (ages) were available, cross-sectional results were not extracted unless the results were
different from results from the prospective measurement
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Dalsager. 2021. 9960591 -
Gump. 2011. 3858629
Harris. 2018, 4442261
Hoffman. 2010. 1291112
Heyer, 2017. 4184660
Jeddy. 2017. 3859807
Liew. 2014, 2852208
Liew. 2015, 2851010-
Liew. 2018. 5079744
Luo, 2020, 7175034-
Lyall. 2018. 4239287
Niu. 2019. 5381527-
Oh. 2021. 7404108
Oulhote. 2016. 3789517
Shin. 2020. 6507470
Skogheim. 2019. 5918847
Skogheim, 2021, 9959649
Spratlen. 2020. 6364693
Stein, 2011. 1424971
Vuong, 2016, 3352166
Wang. 2015. 3860120
Yao.2022. 10273386
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
~ Multiple judgments exist
Figure 3-63. Summary of study evaluation for epidemiology studies of
neurodevelopment. Multiple publications of the same study: HOME study: Vuong
etal. (2016) also includes Vuong etal. (2018b). Vuong et al. (2018a). Vuong et
al. f2019). Braun et al. (2014). Zhang et al. f2018al. Vuong et al. f2020). Vuong
etal. f2021a). and Vuong et al. (2021 bV Project Viva: Harris etal. (2018) also
includes Harris etal. f2021). Four publications with data from the Danish National
Birth Cohort were evaluated separately due to significantly different procedures but
should not be considered independent: Liew etal. (2014). Liew et al. (2015). Liew
et al. (2018). Luo et al. (2020). Two publications with data from the Norwegian
Mother Father and Child Cohort were evaluated separately due to significantly
different selection procedures but should not be considered independent:
Skogheim et al. (2020) and Skogheim et al. (2021) For additional detail see
HAWC link.
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Cognition
Ten studies (13 publications) reported on endpoints related to cognition and PFHxS
exposure, including 9 medium confidence studies and 1 low confidence study. The medium
confidence studies are presented in Table 3-24. Among the medium confidence studies, there was a
non-statistically significant inverse association with an exposure-response gradient across
quartiles in one study for nonverbal IQ when exposure was measured in mid-childhood (Harris et
al.. 20181. The same study also reports inverse associations between nonverbal IQ and maternal
exposure during pregnancy and between verbal IQ in mid-childhood and both exposure measures,
but these are nonmonotonic across the quartiles. Nonmonotonic associations with maternal
exposure during pregnancy were also observed for the Full-Scale Intelligence Quotient (FSIQ) at 5
years of age in Liewetal. f20181 and for intellectual disability in Lvall etal. f20181. Other studies
reported non-statistically significant inverse associations with in some analyses but positive
associations in others (Yao etal.. 2022: Skogheim etal.. 2020: Niu etal.. 20191: Vuong etal. (20191:
(Vuong etal.. 2016: Wang etal.. 20151. with no clear pattern by endpoints, timing of exposure
measurement, sex, or any other factor. The remaining medium confidence studies did not show
decreased cognition with PFHxS exposure. Lastly, the single low confidence study fleddv et al..
20171 reported associations in opposite directions for multiple measures of language and
communication development, and these varied by maternal age. This could be due to social factors
associated with age, but since only one low confidence study examined this interaction, it should be
interpreted with caution. Overall, while there are some inverse associations between cognitive
performance and PFHxS exposure, the nonmonotonicity, general imprecision, and inconsistency
across sub-analyses within studies make the findings difficult to interpret It is possible that there
are biological reasons for the inconsistencies, but given the heterogeneity in study designs, the data
currently do not provide clear support for associations between PFHxS exposure and cognition in
children.
Attention Deficit Hyperactivity Disorder fADHDl or Related Behaviors
Ten studies (13 publications) reported on associations between PFHxS exposure and ADHD
or behaviors potentially related to ADHD, including nine medium confidence studies and one low
confidence study. The medium confidence studies are presented in Tables 3-25 and 3-26. Six of the
ten studies (five of nine medium confidence) reported positive associations.
Two medium confidence studies examined ADHD diagnosis with PFHxS exposure measured
in children cross-sectionally and two studies were cohorts examining maternal exposure. Stein and
Savitz (20111 reported statistically significant associations between ADHD diagnosis and diagnosis
plus medication in children 5 to 18 years old and exposure-response gradients observed across
quartiles. Hoffman etal. (20101 also reported statistically significant positive associations for both
outcomes in children 12-15 years of age. Liew etal. f 20151 and Skogheim etal. f20211 examined
ADHD cases identified from national registries. In Liew etal. f20151. the registry was limited to
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hospital and psychiatric admissions, which likely represent only severe cases. Neither registry
study observed higher likelihood of ADHD with higher PFHxS exposure. All of the studies of ADHD
adjusted for sex but did not examine associations stratified by sex.
The remaining seven studies focused on behaviors. While these behaviors are not specific to
ADHD, many of them are elevated in individuals with ADHD and are used in its diagnosis.
Externalizing problems (consisting of hyperactivity and conduct subscales on the Strengths and
Difficulties Questionnaire [SDQ]) were examined in four studies (using the parent version of SDQ).
One medium confidence study (H0ver etal.. 20171 reported a statistically significant positive
association for 5- to 9-year-olds with maternal exposure measured during the second trimester of
pregnancy modeled as continuous (when exposure was modeled as tertiles, there was an exposure-
response gradient across exposure groups, but it was not statistically significant). Another medium
confidence study using the SDQ reported non-statistically significant positive associations for
externalizing, internalizing, and total scores (Luo etal.. 20201. The other two study using the SDQ,
also medium confidence, did not report greater problem behaviors with higher exposure (Harris et
al.. 2021: Oulhote etal.. 20161. The SDQ is a validated instrument, but its sensitivity for ADHD has
been inconsistent in different populations (Hall etal.. 2019: Pritchard. 2012: Ullebo etal.. 20111.
Looking at other neurobehavioral tests, most had only a single study available. One study
examined impulsivity and inattention using a different tool (the Conners Continuous Performance
Test-II) and also found a non-statistically significant positive association, for inattention but not
impulsivity in 8-year-olds with both maternal exposure and exposure measured in the children
(Vuong etal.. 2018a). In the same study population using a different tool (the Behavioral
Assessment System for Children 2 [BASC-2]), positive associations were reported with
externalizing problems, hyperactivity, internalizing problems, and attention (statistically significant
for all but the latter) when exposure was measured during gestation, but no associations were
observed when exposure was measured in children at 3 years. Another medium confidence study
found no association with behavior problems (measured using the Child Behavior Checklist) using
either maternal or childhood exposure measurement Finally, a low confidence cross-sectional
study examined inter-response time (IRT) at age 9-11 and found statistically significant decreases
in IRT, which indicates poor response inhibition (a primary deficit in children with ADHD) as the
test is designed to reward longer response times (Gump etal.. 20111.
Taken together, there is some evidence of an association between PFHxS exposure and
ADHD or potentially related behaviors. A positive association was observed in most studies (6 of
10) across a variety of populations and diagnostic tests, with an exposure-response gradient in
multiple studies. However, there is remaining uncertainty. Associations were inconsistent across
medium confidence studies. In addition, the only studies reporting an association with ADHD
diagnosis are cross-sectional, which may not represent exposure in an etiologically relevant period,
while the prospective study of ADHD diagnosis reported an inverse association, although the bias in
the cross-sectional studies would likely be toward the null due to nondifferential misclassification.
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A few studies examined the possibility of an interaction with sex. Vuongetal. (2018a)
reported better performance (lower errors of omission) in boys with higher PFHxS ((3 = -4.5, 95%
CI: -10.0,1.0), but worse in girls ((3 = 3.2, 95% CI: -1.1, 7.4). In sex-stratified analyses in Oulhote et
al. f20161. most associations were similar in boys and girls, but some had deficits in girls but not
boys (cross-sectional analyses at 7 years for externalizing problems and related subscales). Haver
etal. f20171 reported a lack of interaction with sex (p > 0.1). There is not adequate evidence to fully
assess differences in the association with ADHD or related behaviors by sex.
Social behavior or autism spectrum disorder
Nine studies (10 publications), all medium confidence, examined social behaviors or ASD
and PFHxS exposure. Five studies examined ASD diagnosis. Two studies fShin etal.. 20201: Liew et
al. f20151 reported positive associations. Liew etal. f 20151 found a higher risk ratio (RR 1.10, 95%
CI: 0.92,1.33) with PFHxS exposure and Shin et al. f20201 a higher odds ratio (OR 1.36, 95% CI:
0.96,1.93). The associations in both studies became statistically significant when adjusting for
other PFAS. The other three studies ASD diagnosis reported no increase in the odds of ASD
diagnosis (Oh etal.. 2021: Skogheim etal.. 2021: Lvall etal.. 2018).
Four medium confidence studies (five publications) examined questionnaires for social
behavior. Braun etal. f20141 used the Social Responsiveness Scale at 4 and 5 years and reported a
nonsignificant positive association (more problem behaviors) ((3: 0.4, 95% CI: -1.5, 2.3); in the
same study population, Vuongetal. (2021b) used the BASC-2 questionnaire and found similar
results with poor social skills. Niu etal. (2019) examined the Ages and Stages questionnaire at 4
years of age and also reported an elevated risk ratio (p > 0.05) for personal social skills problems
with higher exposure (RR 1.60, 95% CI: 0.92, 2.80 per ln-unit increase in exposure). However,
Oulhote etal. f 20161 calculated an autism screening score using the peer problems and prosocial
subscales on the SDQ at 7 years and reported an inverse association (mean difference: -0.1, 95% CI:
-0.3, 0.1). Yao etal. f20221 reported no association with the Social Development Quotient on the
Gesell Development Schedules at 1 year. Three of these studies measured PFHxS exposure in
maternal serum samples collected during pregnancy (most at 16 weeks gestation for Braun etal.
(2014). at 12-16 weeks gestation for Niu etal. (2019). and at 32 weeks gestation for Oulhote et al.
(2016)1: one study measured exposure in cord blood (Yao etal.. 2022). and one study measured
exposure in childhood at 3 and 8 years fVuong etal.. 2021bl.
Overall, there is some evidence of an association between PFHxS exposure and autism and
social behaviors, but there is inconsistency across studies and estimates are generally imprecise. It
is feasible that the inconsistency could be explained by timing of exposure measurement, autism
measurement tool, or some other factor, but is not possible to determine with the evidence
currently available.
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Other neurodevelopmental outcomes
Four medium confidence studies reported on motor-related behaviors and PFHxS exposure.
In fHarris etal.. 20181. there was a statistically significant decrease in the visual-motor score from
the Wide Range Assessment of Visual Motor Abilities (WRAVMA) test in mid-childhood with higher
exposures, when measured cross-sectionally (mean difference (95% CI) versus Ql: Q2: -5.1 (-8.9,
-1.3); Q3: -5.0 (-9.0, -0.9), Q4: -5.0 (-9.1, -0.8)). When using a maternal exposure measure during
pregnancy, the association was nonmonotonic across the quartiles. No association was observed
between the WRAVMA total score and early childhood and maternal exposure measures. In Yao et
al. f20221. a statistically significant inverse association was reported with the Gross Motor
Development Quotient on the Gesell Development Schedules at 1 year. Conversely, in Spratlen et al.
f2020al. positive associations (better motor function on Motor Development Index on Bayleys
Scales of Infant Development) were observed with PFHxS exposure at 1, 2, and 3 years of age
(p > 0.05). An association (p > 0.05) with better fine motor skills was also observed in Niu etal.
(20191. but no association was observed with gross motor skills using the Ages and Stages
Questionnaire. Given the lack of consistency across studies, there is not clear evidence of an
association between PFHxS exposure and motor-related behaviors.
One medium confidence study examined the association of PFHxS exposure measured
during the first or second trimester of gestation with rates of cerebral palsy fLiew etal.. 20141.
Cases of congenital cerebral palsy were identified from a population-based registry. There was a
nonstatistically significant positive association with congenital cerebral palsy in boys (RR 1.2, 95%
CI: 0.9,1.7, exposure-response gradient across quartiles). No association was observed in girls (RR
1.1, 95% CI: O.6., 1.9), and when limited to girls born at term, a nonsignificant inverse association
was observed (RR 0.7, 95% CI: 0.3,1.6). Given the lack of additional studies and imprecision in the
estimate (i.e., wide confidence intervals), there is not clear evidence of an association between
PFHxS exposure and cerebral palsy.
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Table 3-24. Summary of results for medium confidence epidemiology studies of PFHxS exposure and cognitive
effects
Study name,
country,
reference(s)
Measured
endpoint
(test used)
Exposure
measurement
timing
Estimate
type
(adverse
direction)3
Sub-
population
/N
Group or
unit change
Exposure
median (IQR)
or range
(quartiles)
Effect
estimate
CI LCL
CI UCL
Danish National
Birth Cohort,
Denmark
Liew et al. (2014)
FSIQ at 5 yrs
(WPPSI)
Maternal
(median 8.7, SD
2.5 wk
gestation)
Mean
Difference
VS. Q1 (vM
Boys
(n - 831)
Q1
=1.39
-2.0
-7.0
2.9
Mean
Difference
VS. Q1 (vM
Girls
(n -761)
Q1
=1.39
-0.7
-5.1
3.6
Health Outcomes
and Measures of
the Home
Environment
(HOME),
U.S.
Vuong et al.
(2016)
Vuong et al.
(2019)
FSIQ at 8 yrs
(WISC-IV)
3 yrs
Regression
Coefficient
w
221
Ln-unit
increase in
exposure
NR
-0.4
-2.5
1.6
Maternal
(16 ± 3 wks
gestation)
Regression
Coefficient
w
221
Ln-unit
increase in
exposure
GM 1.4
0.5
-1.8
2.9
Global
executive
function
score at 5/8
yrs (BRIEF)
Maternal
(16 ± 3 wks
gestation)
Mean
Difference
m
219
Ln-unit
increase in
exposure
1.5 (0.9-2.4)
1.36
-0.41
3.12
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Study name,
country,
reference(s)
Measured
endpoint
(test used)
Exposure
measurement
timing
Estimate
type
(adverse
direction)3
Sub-
population
/N
Group or
unit change
Exposure
median (IQR)
or range
(quartiles)
Effect
estimate
CI LCL
CI UCL
Vuong et al.
(2020)
Reading
composite
scores at 8 yrs
Maternal
Regression
Coefficient
w
161
Log 10-unit
increase in
exposure
1.7
4.5
-3.1
12.0
Project Viva,
U.S.
Harris et al. (2018)
Harris et al. (2021)
Word
knowledge
early
childhoodb
(PPVT)
Maternal
(5-21 wks
gestation)
Mean
Difference
VS. Q1 (vM
948
Q1
<0.1-1.6
Ref
Q2
1.7-2.4
0.7
-1.6
2.9
Q3
2.5-3.7
0.1
-2.1
2.4
Q4
3.8-43.2
0.4
-1.9
2.7
Verbal IQ
mid-
childhood15
(KBIT)
Maternal
(5-21 wks
gestation)
Mean
Difference
VS. Q1 (vM
851
Q1
<0.1-1.6
Ref
Q2
1.7-2.4
-2.8*
-5.1
-0.5
Q3
2.5-3.7
-1.2
-3.6
1.2
Q4
3.8-43.2
0.3
-2.2
2.8
Mid-childhood
(6-10 yrs)
Mean
Difference
VS. Q1 (vM
631
Q1
<0.1-1.1
Ref
Q2
1.2-1.9
-0.8
-3.6
2.1
Q3
2.0-3.4
-0.2
-3.3
2.8
Q4
3.5-56.8
-1.7
-4.8
1.5
Nonverbal IQ
mid-
childhood15
(KBIT)
Maternal
(5-21 wks
gestation)
Mean
Difference
VS. Q1 (vM
862
Q1
<0.1-1.6
Ref
Q2
1.7-2.4
-3.9*
-6.9
-0.5
Q3
2.5-3.7
-1.6
-4.7
1.5
Q4
3.8-43.2
-1.0
-4.2
2.2
640
Q1
<0.1-1.1
Ref
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Study name,
country,
reference(s)
Measured
endpoint
(test used)
Exposure
measurement
timing
Estimate
type
(adverse
direction)3
Sub-
population
/N
Group or
unit change
Exposure
median (IQR)
or range
(quartiles)
Effect
estimate
CI LCL
CI UCL
Mid-childhood
(6-10 yrs)
Mean
Difference
VS. Q1 (vM
Q2
<0.1-1.1
-0.9
-4.4
2.7
Q3
1.2-1.9
-2.3
-6.1
1.5
Q4
2.0-3.4
-2.7
-6.6
1.2
Global
executive
function
score at 6-10
yrs (BRIEF)
Maternal (5-21
wks gestation)
Mean
Difference
vs Q1 en
921
Q1
<0.1-1.6
Ref
Q2
1.7-2.4
-0.3
-1.9
1.3
Q3
2.5-3.7
0.2
-1.4
1.9
Q4
3.8-43
-1.1
-2.8
0.6
Taiwan maternal
and infant cohort
study,
Taiwan
Wang et al. (2015)
FSIQ at 5 yrs
(WPPSI)
Maternal
(3rd trimester)
Regression
Coefficient
w
120
Doubling of
exposure
0.7 (0.07-1.09)
0.4
-1.1
1.9
FSIQ at 8 yrs
(WISC)
Regression
Coefficient
w
120
Doubling of
exposure
0.7 (0.07-1.07)
-0.2
-1.8
1.4
WTC cohort, U.S.
Spratlen et al.
(2020a)
MDI at lyr
(BSID)
Cord blood/
maternal (1 d
post-delivery)
Regression
Coefficient
302
Log-unit
increase
GM 0.7 (range
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Study name,
country,
reference(s)
Measured
endpoint
(test used)
Exposure
measurement
timing
Estimate
type
(adverse
direction)3
Sub-
population
/N
Group or
unit change
Exposure
median (IQR)
or range
(quartiles)
Effect
estimate
CI LCL
CI UCL
FSIQ at 4 yr
(WPPSI)
302
0.04
-2.78
2.86
Girls 150
0.35
-3.20
3.90
Boys 152
-0.41
-4.84
4.02
FSIQ at 6 yr
(WPPSI)
302
-0.34
-3.71
3.03
Girls 150
0.57
-3.13
4.27
Boys 152
-1.64
-8.07
4.79
Norwegian
Mother, Father
and Child cohort,
Norway
Skogheim et al.
(2020)
Verbal
working
memory at 42
mo (CDI)
Maternal (17 wk
gestation)
Regression
coefficient
w
768
Q2
0.7 (0.5-0.9)
0.03
-0.20
0.26
Q3
0.10
-0.13
0.33
Q4
0.20
-0.03
0.44
Q5
0.21
-0.03
0.45
Nonverbal
working
memory at 42
mo (CDI)
934
Q2
-0.18
-0.38
0.03
Q3
-0.05
-0.26
0.16
Q4
-0.23
-0.44
-0.02
Q5
-0.18
-0.40
0.04
Shanghai-Minhang
cohort, China
Niuetal. (2019)
Communicati
on at 4 yrs
(ASQ-3)
Maternal (12—
16 wks
gestation)
Risk ratio
for
problems
m
533
Ln-unit
increase in
exposure
2.8 (2.1-0.5)
1.10
0.78
1.54
Girls 236
1.46
0.79
2.70
Boys 297
0.90
0.60
1.35
533
0.85
0.54
1.36
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Study name,
country,
reference(s)
Measured
endpoint
(test used)
Exposure
measurement
timing
Estimate
type
(adverse
direction)3
Sub-
population
/N
Group or
unit change
Exposure
median (IQR)
or range
(quartiles)
Effect
estimate
CI LCL
CI UCL
Problem
solving at 4
yrs (ASQ-3)
Girls 236
1.06
0.40
2.78
Boys 297
0.75
0.43
1.32
Early Markers for
Autism (EMA),
U.S.
Lvall et al. (2018)
Intellectual
disability at
4-9 yrs
(clinical
diagnosis)
Maternal (15—
19 wks
gestation)
Odds Ratio
(OR) m
622
Ln-unit
increase in
exposure
GM 1.33
1.11
0.86
1.42
Odds Ratio
(OR) vs. Q1
m
160
Q1
<0.8
1.0
171
Q2
0.8-<1.3
1.43
0.86
2.40
133
Q3
1.3-<2.0
1.03
0.58
1.85
157
Q4
> = 2.0
1.30
0.74
2.29
Laizhou Wan Birth
Cohort, China
Yao et al. (2022)
Adaptive
Development
Quotient at 1
yr
Cord serum
Regression
coefficient
274
Log 10-unit
increase in
exposure
0.3 (range 0.1-
1.1)
-1.40
-6.17
3.37
Girls 135
-2.02
-9.27
5.23
Boys 139
-1.22
-7.62
5.18
Language
Development
Quotient at 1
yr
274
3.00
-1.67
7.67
Girls 135
2.05
-4.82
8.93
Boys 139
4.02
-2.39
10.42
*p < 0.05.
aThe arrows indicate the direction the effect estimate will be if there is an association between PFHxS and reduced cognitive performance. For some tests, a
higher score means better performance, while for other tests, a higher score means more problems.
bEarly childhood median age 3.2 years, range 2.8-6.3; Mid-childhood median age 7.7 years, range 6.6-10.9.
FSIQ: Full-Scale Intelligence Quotient; WPPSI: Wechsler Primary and Preschool Scales of Intelligence, WISC: Wechsler Intelligence Scale for Children, BRIEF:
Behavior Rating Inventory of Executive Function, PPVT: Peabody Picture Vocabulary Test, KBIT: Kaufman Brief Intelligence Test, BSID: Bayley Scales of Infant
Development, MDI: mental development index.
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Table 3-25. Summary of results for medium confidence epidemiology studies of PFHxS exposure and attention
deficit hyperactivity disorder (ADHD)
Study name
Measured
endpoint
Exposure
measure-
ment
timing
Estimate
type
(adverse
direction)3
Subpopulation/
N
Group or unit
change
Exposure
median (IQR) or
range (quartiles)
Effect
Estimate
CI LCL
CI UCL
C8 Health
Project,
U.S.
(Stein and
ADHD
diagnosis at 5-
18 yrs (clinical)
Cross-
sectional
Odds Ratio
(OR) vs. Q1
m
1,0546
Q1
0.25-<2.9 ng/mL
1.0
02
2.9-<5.2
1.27*
1.06
1.52
03
5.2-<10.1
1.43*
1.21
1.70
Savitz, 2011)
04
10.1-276.4
1.53*
1.29
1.83
ADHD
diagnosis +
medication at
5-18 yrs
(clinical)
Cross-
sectional
Odds Ratio
(OR) vs. Q1
m
1,0546
Q1
0.25-<2.9 ng/mL
1.0
02
2.9-<5.2
1.44*
1.09
1.90
03
5.2-<10.1
1.55*
1.19
2.04
04
10.1-276.4
1.59*
1.21
2.08
NHANES
(1999-2000,
2003-2004),
U.S.
Hoffman et al.
(2010)
ADHD at 12-
15 yrs (clinical)
Cross-
sectional
Odds Ratio
(OR) m
571
One unit increase
in exposure
2.2 (2.9)
1.06*
1.02
1.11
ADHD+
medication at
12-15 yrs
(clinical)
2.2 (2.9)
1.07*
1.03
1.11
Danish
National Birth
Cohort,
Denmark
Liew et al.
(2015)
ADHD
diagnosis
(national
registry)
Maternal
(1st
trimester)
Risk ratio (1^)
770
In-unit increase
Controls 0.9 (0.7-1.2)
0.97
0.88
1.08
01
1.23
0.67*
0.54
0.83
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Study name
Measured
endpoint
Exposure
measure-
ment
timing
Estimate
type
(adverse
direction)3
Subpopulation/
N
Group or unit
change
Exposure
median (IQR) or
range (quartiles)
Effect
Estimate
CI LCL
CI UCL
Norwegian
Mother Father
Child Cohort,
Norway
Skogheim et al.
ADHD
diagnosis
(national
registry)
Maternal
(2nd
trimester,
18 wks
gestation)
Odds ratio
m
1801
Q1
0.1-0.5
1.0
Q2
0.5-0.6
1.08
0.82
1.42
Q3
0.6-0.9
1.12
0.85
1.49
(2021)
Q4
0.9-15
0.89
0.66
1.19
*p < 0.05.
aThe arrows indicate the direction the effect estimate will be if there is an association between PFHxS and reduced behavior. For all the tests included here,
higher scores indicate more ADHD diagnosis.
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Table 3-26. Summary of results for medium confidence epidemiology studies of PFHxS exposure and behavior
Study name
Measured
endpoint
Exposure
measure-
ment
timing
Estimate
type
(adverse
direction)3
Subpopulation/
N
Group or unit
change
Exposu re
median (IQR) or range
(quartiles)
Effect
Estimate
CI LCL
CI UCL
Faroe Island
cohort,
Denmark
Oulhote et al.
(2016)
Externalizing
problems at 7
yrs (SDQ)
5 yrs
Mean
Difference
m
508
Per doubling of
exposure
0.6 (0.5-0.9)
0
-0.36
0.37
Maternal
(32-wk
gestation)
539
4.5 (2.2-8.4)
-0.19
-0.48
0.11
Internalizing
problems at 7
yrs (SDQ)
5 yrs
Mean
Difference
m
508
Per doubling of
exposure
0.6 (0.5-0.9)
-0.1
-0.43
0.22
Maternal
(32-wk
gestation)
539
4.5 (2.2-8.4)
-0.1
-0.36
0.17
Total SDQ
score at 7 yrs
5 yrs
Mean
Difference
m
508
Per doubling of
exposure
0.6 (0.5-0.9)
-0.1
-0.66
0.46
Maternal
(32-wk
gestation)
539
4.5 (2.2-8.4)
-0.28
-0.75
0.18
INUENDO (Bio
persistent
organochlorines
in diet and
human fertility),
Greenland,
Ukraine, Poland
Hgver et al.
(2017)
Hyperactivity
score at 5-9 yrs
(SDQ)
Maternal
(median 2nd
trimester)
Regression
Coefficient
m
1,023
In-unit increase in
exposure
1.5 (10th-90th 0.7-3.4)
0.20*
0.00
0.40
Low exposure
0.2-1.2
Ref
Medium exposure
1.2-2.0
0.15
-0.30
0.60
High exposure
2.0-18.8
0.41
-0.03
0.86
Total SDQ
score at 5-9 yrs
Maternal
(median 2nd
trimester)
Regression
Coefficient
m
1,023
In-unit increase in
exposure
1.5 (10th-90th 0.7-3.4)
0.45
-0.03
0.92
Low exposure
0.2-1.2
Ref
Medium exposure
1.2-2.0
0.68
-0.04
1.38
High exposure
2.0-18.8
0.80*
0.06
1.54
Project Viva,
U.S.
Harris et al.
(2021)
Externalizing
problems at 6-
10 yrs (SDQ)
Maternal (5-
21 wks
gestation)
Mean
Difference vs
Ql(t)
921
Q1
<0.1-1.6
Ref
Q2
1.7-2.4
0.0
-0.5
0.5
Q3
2.5-3.7
0.6
0.0
1.1
Q4
3.8-43
0.0
-0.5
0.6
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Study name
Measured
endpoint
Exposure
measure-
ment
timing
Estimate
type
(adverse
direction)3
Subpopulation/
N
Group or unit
change
Exposu re
median (IQR) or range
(quartiles)
Effect
Estimate
CI LCL
CI UCL
Internalizing
problems at 6-
10 yrs (SDQ)
Q1
<0.1-1.6
Ref
Q2
1.7-2.4
0.2
-0.3
0.6
Q3
2.5-3.7
-0.1
-0.5
0.4
Q4
3.8-43
0.2
-0.3
0.7
Total SDQ
score at 6-10
yrs
Q1
<0.1-1.6
Ref
Q2
1.7-2.4
0.2
-0.6
1.0
Q3
2.5-3.7
0.5
-0.3
1.4
Q4
3.8-43
0.2
-0.7
1.1
Danish National
Birth Cohort,
Denmark
Luo et al.
(2020)
Externalizing
problems at 7
yrs
Maternal
(1st
trimester)
OR (1s) (odds
of elevated
score)
2421
Per doubling of
exposure
0.9(0.7-1.3)
1.11
0.86
1.43
Internalizing
problems at 7
yrs
1.18
0.88
1.58
Total SDQ
score at 7 yrs
1.15
0.94
1.42
Odense Child
Cohort,
Denmark
(Dalsager et
al.. 2021b)
Behavior
problems (CBC)
at 2-5 yrs
Maternal (8-
16 wks
gestation)
Incidence rate
ratio (1s)
1138
Doubling of
exposure
0.4
0.98
0.93
1.03
Odds ratio
m
0.95
0.79
1.16
18 mo
Incidence rate
ratio (1s)
817
0.3
0.95
0.88
1.04
Odds ratio
m
1.04
0.79
1.37
Health
Outcomes and
Measures of the
Home
Impulsivity-
Commissions at
8 yrs (CPT)
3 yrs
Regression
Coefficient
m
204
In-unit increase in
exposure
1.9 (1.0-3.3)
-0.6
-2.1
1.0
Maternal
(16 ± 3 wk-
gestation)
1.3 (0.8-2.3)
-0.5
-1.9
0.9
3 yrs
1.9 (1.0-3.3)
0.6
-2.3
3.5
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Exposure
Estimate
measure-
type
Exposu re
Measured
ment
(adverse
Subpopulation/
Group or unit
median (IQR) or range
Effect
Study name
endpoint
timing
direction)3
N
change
(quartiles)
Estimate
CI LCL
CI UCL
Environment
Inattention -
Maternal
1.3 (0.8-2.3)
2.5
-0.9
6.0
(HOME)
Omissions at 8
(16 ± 3 wk-
U.S.
yrs (CPT)
gestation)
Vuong et al.
Externalizing
Maternal
Odds ratio
241
In-unit increase in
1.5
1.9*
1.1
3.2
(2018a)
problems
(16 ± 3 wk-
m
exposure
Vuong et al.
(BASC-2) at 5
gestation)
(2021a)
and 8 yrs
Vuong et al.
(2021b)
Hyperactivity
(BASC-2)
2.5*
1.5
4.3
Attention
(BASC-2)
1.2
0.8
1.9
Internalizing
2.0*
1.1
3.4
problems
(BASC-2)
Externalizing
3 yrs
Regression
208
Ln-unit increase in
1.9
0.02
-1.6
1.6
problems
Coefficient
exposure
(BASC-2) at 8
m
yrs
Hyperactivity
-0.3
-1.9
1.2
(BASC-2)
Attention
-0.1
-1.6
1.4
(BASC-2)
Conduct
0.4
-1.3
2.1
problems
(BASC-2)
*p < 0.05.
SDQ: Strengths and Difficulties Questionnaire, CPT: Conners continuous performance test, CBC: Child Behavior Checklist, BASC-2: Behavioral Assessment
System for Children 2.
aThe arrows indicate the direction the effect estimate will be if there is an association between PFHxS and reduced behavior. For all the tests included here,
higher scores indicate more difficulties/behavior problems.
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Animal Studies
There were three animal studies evaluating neurodevelopmental outcomes and PFHxS
exposure: two medium confidence studies fRamhai etal.. 2020: Butenhoffetal.. 20091 and one low
confidence study fViberget al.. 20131 (see Figure 3-64). Butenhoffetal. f20091 exposed male and
female Crl:CD Sprague Dawley rats to 0.3,1, 3, or 10 mg/kg-day daily via oral gavage starting at 14
days prior to cohabitation (Fo). Fi pups were not exposed directly but were exposed in utero and
through lactation. The study authors then assessed 5 pups per sex per litter from 10 dams using the
functional observation battery (FOB)19 and an automated motor activity assessment tool atPND22.
In the second medium confidence study, Ramhai etal. f20201 exposed Wistar dams to 0, 0.05, 5, or
25 mg/k bw-day PFHxS via gavage starting at gestational day 7 (GD7) through postnatal day 22 (PD
22). After weaning, one male and one female pup from each litter subsequently underwent
behavioral assessment of motor activity levels20 at each of three ages: PD 27, PD 115, andPD 340.
Additionally, Viberg etal. (20131 evaluated spontaneous locomotor behavior by exposing male and
female NMRI mouse pups at postnatal day 10 (PND10) to a single oral dose of PFHxS at 0.61, 6.1, or
9.2 mg/kg-bw PFHxS. Spontaneous locomotor behavior was then evaluated at 2- and 4-months
post-exposure, and nicotine-induced behavior was evaluated at 4 months.
19FOB evaluations consisted of assessment of (1) autonomic functions: lacrimation, salivation, palpebral
closure, prominence of the eye, pupillary reaction to light, piloerection, respiration, and urination and
defecation; (2) reactivity and sensitivity: sensorimotor responses to visual, auditory, tactile and painful
stimuli; (3) excitability reactions to handling and behavior in the open field; (4) gait and sensorimotor
coordination: gait pattern in the open field, severity of gait abnormalities, air righting reaction and landing
foot splay; forelimb and hindlimb grip strength; and (5) abnormal clinical signs including convulsions,
tremors and other unusual behavior, hypotonia or hypertonia, emaciation, dehydration, unkempt appearance
and deposits around the eyes, nose or mouth. fButenhoff et al.. 20091
20Measured in activity boxes with photocells recording horizontal activity for 30 minutes. Rearing behavior
(vertical activity) was not measured by Ramhfli et al. (20201
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*•
Reporting quality
Allocation
Observational bias/blinding
Confounding/variable control
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Results presentation
Endpoint sensitivity and specificity
Overall confidence
H Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Not reported
Figure 3-64. Confidence scores of neurodevelopmental system effects from
repeated PFHxS dose animal toxicity studies. For additional details see HAWC
link.
Functional observation battery fFOBl
1 One study fButenhoff et al.. 20091 reported on PFHxS effects on FOB assessment on F1
2 pups. The authors reported no statistically significant differences between control animals and
3 PFHxS treated animals on the assessments of FOB parameters.
Learning and memory
4 One study fRamhai etal.. 20201 reported on PFHxS effects on radial arm maze assessments
5 in Wistar male and female rat offspring exposed to PFHxS in utero and through lactation.
6 Assessments were performed at postnatal day (PD) 115 and PD 340, The authors reported that no
7 statistically significant differences between control animals versus PFHxS treated animals.
Motor-related behaviors
8 Butenhoff et al. f20091. Ramh0i etal. f20201 and Viberg etal. f2013 evaluated and
9 reported on locomotor activity (including anxiety-related behaviors) in response to PFHxS
10 exposure. The two medium confidence studies, Butenhoff etal. f20091 and Ramhai etal. f20201.
11 reported no statistically significant differences in motor activity in either sex with in-utero and
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lactational PFHxS dosing of dams from 0.05 to 25 mg/kg-day. One low confidence study, Viberg et
al. (20131 reported decreases in ambulatory (horizontal) activity and rearing behaviors in male and
female NMRI pups at 2 and 4 months following a single oral dose of PFHxS at 0.61, 6.1, or 9.2 mg/kg
bw PFHxS at postnatal day 10 (PND10) during the habituation (first 20 minutes) and end (minutes
40-60) periods of observation at 2 and 4 months after a single exposure to 9.2 mg/kg-day PFHxS on
PND9; however, the authors did not account for the potential impact of litter effects In their
experimental design, and they allocated pups to dosing groups from 3-4 litters in an unclear
fashion, reducing confidence in these findings. Taken together, the potential effects of PFHxS
exposure on motor-related behaviors in rodents remain unknown.
Mechanistic evidence and supplemental information
Seven mechanistic studies were identified relating to the potential for PFHxS to elicit
neurodevelopmental effects. Two of these studies were performed in vivo and five were performed
using in vitro models. Of the two in vivo studies, one was a follow-up to the Viberg etal. (2013)
study described above. Using the same study design as Viberg etal. (2013). and thus possessing the
same methodological limitations, Lee and Viberg f20131 examined changes in proteins21 involved in
a variety of neuronal functions in the cerebral cortex and hippocampus in NMRI male and female
mice at both 24 hours and 4 months following a single dose of PFHxS on PND9 at either 6.2 mg/kg
bw or 9.2 mg/kg bw. While the authors observed significant changes in protein levels at 24 hours in
PFHxS-exposed animals the majority of these changes had resolved at the 4-month timepoint. At 4
months the only significant change was an increase in Tau protein expression (p < 0.01) in the
cerebral cortex of male mice at the 6.1 mg/kg bw dose.
PFHxS was also shown to produce a significant repression of long-term potentiation (LTP)
(p < 0.05), which is associated with learning and memory formation processes, in adult Sprague
Dawley rats exposed via intracerebroventricular injection at the CA1 region of the hippocampus
both 10 and 100 |j.M PFHxS fZhang etal.. 2016al. However, the authors noted no remarkable
changes in field excitatory postsynaptic potential (fEPSP) amplitude (decreased LTP would be
expected to represent weaker synaptic strength and reduced fEPSP) between control and PFHxS
treated groups (Zhang etal.. 2016a). In addition, this study was performed in adult rats therefore
making it difficult to determine how relevant the effects observed by Zhang etal. f2016al are to
human neurodevelopment.
21BNDF: brain derived neurotrophic factor; protein involved in canonical nerve growth (Huang and
Reichardt. 2001): CaMKII: Ca2+/calmodulin dependent protein kinase II; a serine-threonine-specific protein
kinase that is regulated by Ca2/calmodulin. Involved in a variety of neuronal processes including learning and
memory (Yamauchi. 2005). GAP43: Growth Associated Protein 43; Protein expressed at high levels in neural
growth cones during development and axonal regeneration fRosskothen-Kuhl and Illing. 20141
Synaptophysin: protein present in the neuroendocrine cells involved in synaptic transmission fMcmahon et
al.. 19961: Tau: Tau proteins are a group of 6 highly soluble protein isoforms that are produced by alternative
splicing. Tau proteins play a role in the stability of microtubules in axons and are present in abundance in
CNS neurons (Barbier et al.. 2019).
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Evidence from animals prenatally exposed to other per and polyfluoroalkyl substances
(PFAS) such as PFOA and PFOS, suggest that PFAS may affect neurodevelopment (Kawabata etal..
2017: Shrestha etal.. 2017: Salgado etal.. 2016: Zhang etal.. 2016b: Fuentes etal.. 2007: Lau etal..
20031. PFAS-related effects relevant to neurodevelopment include decreased choline
acetyltransferase activity in the prefrontal cortex of exposed rats postnatally fLau etal.. 20031.
delayed neuromotor maturation (e.g., decreased resistance to backward pull-on postnatal day
[PND] 10 and 11) (Fuentes etal.. 20071.
Evidence Integration
Taken together, the available human studies were interpreted to provide slight evidence.
Specifically, five medium confidence epidemiological studies that reported some evidence of
positive associations between PFHxS exposure and ADHD or behaviors potentially related to ADHD
at median blood concentrations in the study populations of 1-5 ng/mL. In addition, several
epidemiology studies examined whether PFHxS exposure has the potential to affect the following
neurodevelopmental outcomes: cognition, social behavior and autism, and other outcomes such as
motor-related behaviors and cerebral palsy. However, associations with these neurodevelopmental
outcomes were inconsistent across studies and generally imprecise, and thus did not contribute to
the overall judgment for potential neurodevelopmental effects.
Th animal evidence base consisted of three studies examining PFHxS effect on FOB and
motor function, and a single study on PFHxS effects on learning and memory. PFHxS-related effects
in these studies were null or of low confidence. Additional animal studies potentially relevant to
interpreting the outcomes examined in the epidemiology studies of PFHxS were unavailable. Thus,
the overall animal evidence was considered indeterminate (see Table 3-27).
The endocrine and nervous systems work in harmony during early development. To this
end, evidence from the endocrine evidence base was also examined to see if any of the studies in
the endocrine database could help inform PFHxS neurotoxicity. While no studies evaluated both
endocrine and neurological outcomes as part of their study designs, the prior judgment that PFHxS
exposure is likely to result in decreased levels of serum thyroxine (T4)—particularly the evidence
after developmental PFHxS exposure (for more details please see Section 3.2.1), is of potential
relevance. In rats, decreased serum T4 is correlated with adverse neurodevelopmental outcomes
fCrofton. 20041. and, in humans, a link between prenatal maternal T4 and decreased cognitive
function in children has been observed fFinken etal.. 2013: Henrichs etal.. 2013: Li etal.. 2010:
Haddowetal.. 1999: Man etal.. 19711. The lack of neurological outcome measurements in the
available endocrine studies examining PFHxS-related toxicity highlights an important data gap.
The available evidence suggests but is not sufficient to infer whether exposure to PFHxS
might cause neurodevelopmental effects in humans given sufficient exposure conditions22 (see
22 The "sufficient exposure conditions" are more fully evaluated and defined for the identified health effects
through dose-response analysis in Section 5.
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1 Table 3-27). This conclusion is based on slight epidemiological evidence primarily from four
2 medium confidence epidemiological studies that reported some evidence of positive associations
3 between PFHxS exposure and ADHD or behaviors potentially related to ADHD at median blood
4 concentrations in the study populations of 1-5 ng/mL.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Table 3-27. Evidence profile table for PFHxS neurotoxicological effects
Evidence stream summary and interpretation
Evidence integration
summary judgment
Evidence from studies of exposed humans (see Nervous System Human Studies Section)
Studies and confidence
Factors that increase
certainty
Factors that decrease
certainty
Summary of key findings
Evidence stream judgment
®oo
Evidence suggests, but is not
sufficient to infer
Primary basis:
Based on human evidence for
decreased ADHD and related
behaviors at median blood
concentrations of 0.9-5
ng/mL
Human relevance:
Evidence comes from
epidemiological studies (see
Nervous System Human
Studies Section)
Cross-stream coherence-.
NA: animal evidence is
indeterminate
Susceptible populations: In
utero or childhood exposure.
• ADHD or related
behaviors
• 9 medium, How
confidence studies
• Exposure-response
gradients in
multiple studies
• Mostly medium
confidence studies,
with positive
associations in 5
of 9
• Unexplained
inconsistency
• Unclear biological
relevance of
etiologic window in
cross-sectional
studies reporting
associations
5 medium and 1 low
confidence studies reported
positive associations between
PFHxS exposure and ADHD or
behavior consistent with
ADHD.
®oo
Slight
Based on some evidence of an
association between PFHxS
exposure or ADHD and related
behaviors, although uncertainty
remains. Other outcomes did
not contribute to this judgment.
Cognition
• 9 medium and 1 low
confidence studies
• No factors noted
• Unexplained
inconsistency,
including by timing
of exposure
measurement.
Inverse associations between
cognition and PFHxS exposure
were observed in multiple
studies, but there were
inconsistencies across studies
and in sub-analyses within
studies.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Evidence stream summary and interpretation
Evidence integration
summary judgment
Social behavior or ASD
• 9 medium confidence
studies
• No factors noted
• Unexplained
inconsistency
• Imprecision
Of 5 studies of ASD, 2 reported
higher likelihood of diagnosis.
Other studies of social
behavior were similarly
inconsistent.
Other neurodevelopmental
effects
• 5 medium confidence
studies
• No factors noted.
• Unexplained
inconsistency for
motor-related
behaviors
• Imprecision for
cerebral palsy
Imedium confidence studies
reported a decrease in motor
scores with higher PFHxS
exposure, while improved
motor function was observed
in two medium confidence
studies. A medium confidence
study reported a non-
statistically significant positive
association with cerebral palsy
in boys.
Evidence from In vivo Animal Studies (see Nervous System Animal Studies Section)
Evidence stream judgment
Studies and confidence
Factors that increase
strength
Factors that decrease
strength
Summary of key findings
Behavioral
• 2 medium 1 low
confidence studies
• No factors noted
• Low confidence study
is only one to observe
an effect
2 medium confidence studies
reported no effects on FOB
parameters, motor activity, or
learning and memory. The low
confidence study observed
decreases in spontaneous
behaviors.
QQQ
Indeterminate
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3.2.6. Cardiometabolic Effects
Cardiometabolic risk refers to the likelihood of developing diabetes, heart disease, or
stroke. Contributors to this risk include a combination of metabolic dysfunctions mainly
characterized by insulin resistance, dyslipidemia, hypertension, and adiposity (obesity).
Human Studies
Serum lipids
High cholesterol, specifically low-density lipoprotein (LDL) cholesterol, is one of the major
controllable risk factors for cardiovascular disease, including coronary heart disease, myocardial
infarction, and stroke. Cholesterol levels are typically measured in the blood. Thirty-eight studies
evaluated the relationship between PFHxS exposure and blood lipids (i.e., cholesterol, LDL
cholesterol, and triglycerides).
Multiple outcome-specific considerations for study evaluation influenced the ratings. First,
for outcome ascertainment, collection of blood during a fasting state is preferred for all blood lipid
measures fNIH. 2020: Nigam. 20111 but lack of fasting was considered deficient for triglycerides
and LDL cholesterol (which is typically calculated using triglycerides). This is because triglyceride
levels remain elevated for several hours after a meal (Nigam. 2011). which is likely to result in
substantial outcome misclassification if there is not standardization across study participants. Self-
reported high cholesterol was also considered deficient for outcome ascertainment due to the high
likelihood of misclassifying cases as controls fNataraian etal.. 20021. Both of these issues are likely
to result in nondifferential outcome misclassification and to generally bias results toward the null.
It is also important for studies to account for factors that meaningfully influence serum lipids, most
notably use of cholesterol lowering medications and pregnancy. Studies that did not consider these
factors by exclusion, stratification, or adjustment were considered deficient for the participant
selection domain. All of the available studies analyzed serum lipids and PFHxS in serum or plasma
using standard, appropriate methods. As described in the Endocrine Effects section, reverse
causation was considered based on binding of lipophilic chemicals (such as PFAS) to serum lipids
fChevrier. 20131. but this is unlikely to significantly bias the results because PFAS, including PFHxS,
do not preferentially bind to serum lipids fForsthuber etal.. 20201. so exposure measurements in
blood, including cross-sectional, were considered adequate for this outcome.
A summary of the study evaluations is presented in Figure 3-65, and additional details can
be obtained from HAWC. Five studies were excluded from further analysis as uninformative due to
critical deficiencies confounding in four studies (Seo etal.. 2018: Yang etal.. 2018: Rotander et al..
2015b: Tao etal.. 20081 and selection bias in two studies fSinisalu etal.. 2021: Yang etal.. 20181.
Twenty-four studies were classified as medium confidence for at least one serum lipid measure
fCakmak etal.. 2022: Dunder et al.. 2022: Averina etal.. 2021: Blomberg etal.. 2021: Canova etal..
2021: Dalla Zuanna etal.. 2021: Gardener etal.. 2021: Li etal.. 2021a: Tian etal.. 2021: Canova etal..
2020: Tensen etal.. 2020a: Liu etal.. 2020a: Spratlen etal.. 2020b: Yang etal.. 2020b: Dong etal..
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1 2019: Lin etal.. 2019: Tain and Ducatman. 2018: Kang etal.. 2018: Mora etal.. 2018: Manzano-
2 Salgado etal.. 2017b: Matilla-Santander etal.. 2017: Zeng etal.. 2015: Starling etal.. 2014b).
3 although 11 of these were low confidence for triglycerides (and LDL cholesterol when calculated
4 from triglycerides), as described above fManzano-Salgado etal.. 2017b: Matilla-Santander etal..
5 2017: Zeng etal.. 2015: Starling etal.. 2014b! Nine studies were classified as low confidence for all
6 serum lipid endpoints fBatzella etal.. 2022: Varshavskv etal.. 2021: Khalil etal.. 2020: Li et al..
7 2020b: Chen etal.. 2019a: Khalil etal.. 2018: Koshv etal.. 2017: Christensenetal.. 20161.
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AvOflna, 2021.7J10155 -I
BuUe/ia, 2022, 10273294
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Rotamwt 2015. 385S642 -
S»0 2018.4238334
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ISO. 2008.25651884
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!G»o«j (malfle) (A H$h ea.-'Miwoe
AdMjuoie lir-cmcl or Medium confidence lavwraH)
Dolictofil (metric) or Low confidence
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
The results for the association between PFHxS exposure and blood lipids are presented in
Table 3-28. It is difficult to directly compare the magnitudes of effect across studies due to the
different analyses and data transformations (e.g., log transformations of PFHxS levels and/or lipid
levels), so the synthesis is focused primarily on direction of association.
In adults, all six medium confidence studies (reported in eight publications) examining total
cholesterol reported positive associations between total cholesterol and PFHxS exposure fCakmak
etal.. 2022: Dunder etal.. 2022: Canova etal.. 2020: Liu etal.. 2020a: Dong etal.. 2019: Lin etal..
2019). with statistical significance in four (Cakmaketal.. 2022: Dunder etal.. 2022: Canova etal..
2020: Lin etal.. 2019). In the four studies that additionally examined exposure modeled as
quartiles, three reported a monotonic exposure-response gradient fCanova etal.. 2020: Liu etal..
2020a: Fisher etal.. 20131. while one reported the strongest association in the third quartile (Linet
al.. 20191. While the direction of association was mostly consistent across studies, in the NHANES
data reported in Dong etal. (2019). the direction of association was not consistent across NHANES
study cycles. The association was inverse (not statistically significant) in 2003-2004 and 2005-
2006, but positive (not statistically significant) in 2007-2008, 2011-2012, and 2013-2014, despite
similar exposure levels across cycles. Further, in the two studies with prospective exposure
measurement, only one found a positive association fDunder et al.. 20221. while the other found an
association in cross-sectional but not prospective analyses fLin etal.. 20191. This raises the
possibility that the observed associations across mostly cross-sectional studies could be due to
reverse causality.
Two low confidence studies (Li etal.. 2020b: Chen etal.. 2019a) in general population adults
also observed positive associations with total cholesterol, with the latter being statistically
significant, while a third low confidence study (Lin etal.. 2020c) found no association in older
residents (55-75 years). The populations in both Lin etal. f2020cl and Li etal. f2020bl were living
in high contamination areas (in Taiwan and Sweden, respectively). In addition, two studies
examined occupational populations with PFAS exposure. These studies were low confidence due to
concerns for potential selection bias and residual confounding. Batzella etal. (2022). examining
PFAS production workers in Italy, and Khalil etal. (2020) examining firefighters in the U.S., both
reported positive, but not statistically significant associations between PFHxS and total cholesterol.
In pregnant women, two studies (Yang etal.. 2020b: Starling etal.. 2014b) out of five (see
Table 3-28) reported higher total cholesterol with higher PFHxS exposure, with statistical
significance in Yang etal. f2020bl and an exposure-response gradient across quartiles in Starling et
al. f2014bl. In a low confidence study of high cholesterol fChristensen etal.. 20161. no association
was observed (OR 1.01, 95% CI: 0.91,1.13), but the study is expected to be biased toward the null
due to nondifferential outcome misclassification.
Three of the medium confidence studies additionally reported analyses of dichotomous
hypercholesterolemia fCanova et al.. 2020: Lin etal.. 2019: Fisher etal.. 20131. Cutoffs for high
cholesterol differed across studies: in Fisher etal. f20131 the cutoff for total cholesterol was 5.2
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
mmol/L; in Canovaetal. (20201. the cutoff was 190 mg/mL, and in Lin etal. (20191. the outcome
was initiation of cholesterol lowering medication, or total cholesterol of 240 mg/mL/LDL cutoff of
160 ng/mL). Significantly higher odds of high cholesterol (OR of 1.4-1.6 in the highest quartiles)
were reported in both Fisher etal. f20131 and Canovaetal. f20201. with a monotonic exposure-
response gradient across quartiles. In Lin etal. f20191. higher odds (not statistically significant)
were observed in an analysis of high cholesterol at baseline, but not when risk of high cholesterol
was analyzed prospectively.
Results for LDL cholesterol and triglycerides in adults were less consistent than total
cholesterol in the medium confidence studies, with most studies showing similar results across the
different outcome markers, but a few reporting inverse associations for LDL and/or triglycerides
fCakmak etal.. 2022: DallaZuanna etal.. 2021: Matilla-Santander etal.. 20171.
In adolescents and children, there was very limited evidence of an association, with 4 of 12
medium confidence studies reporting higher total cholesterol with higher PFHxS exposure (Canova
etal.. 2021: Kang etal.. 2018: Mora etal.. 2018: Zeng etal.. 20151. and only one reporting
statistically significance, but without an exposure-response gradient across quartiles (Canova etal..
20211. The other medium confidence studies reported no association (Averina etal.. 2021:
Blomberg etal.. 2021: Papadopoulou etal.. 2021: Tensen etal.. 2020a: Tain and Ducatman. 2018:
Manzano-Salgado etal.. 2017bl. For triglycerides, 4 of 12 studies reported positive associations
fBlomberg etal.. 2021: Spratlen etal.. 2020b: Manzano-Salgado etal.. 2017b: Zeng etal.. 20151. Of
note, both Spratlen etal. (2 02 Obi and (Blomberg etal.. 20211 reported statistically significant
positive associations in neonates, though the third study in neonates found no association (Tianet
al.. 20201. Looking at the two studies of low confidence in adolescents (Koshv etal.. 20171 and
children (Khalil etal.. 20181. both reported higher total cholesterol with higher exposure, with the
difference being statistically significant in Koshv etal. f20171. but both had serious limitations.
Overall, there is some evidence that higher PFHxS exposure is associated with higher total
cholesterol levels in adults, with less consistent evidence for parallel changes in triglycerides. The
majority of studies in adults, including pregnant women, support this association, though there are
remaining uncertainties, including less consistent evidence for LDL cholesterol and triglycerides.
Additionally, a possible explanation for the observed associations is the presence of residual
confounding. It is plausible that an association between PFAS exposure and consumption of high
cholesterol foods, as suggested in some studies fSusmann etal.. 2019: Schaider etal.. 20171. could
induce a positive association with serum lipids; however, the currently available evidence does not
allow for evaluation of this possibility as most studies that adjusted for dietary habits were in
children, where the evidence was less consistent. In addition, there is potential for confounding
across the PFAS. In the studies with stronger association, there were similar associations with other
PFAS, including PFOS, PFOA, and PFNA, and PFHxS is moderately positively correlated with them.
With the available evidence, it is not possible to rule this out, but the association with cholesterol
was still present in a study with weak correlations (—0.3) between PFHxS and PFOS and PFOA
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1 fCakmak etal.. 20221. Given the overall consistency across studies and the observation of exposure-
2 response gradients across quartiles in multiple studies, there is reasonable support for a positive
3 association with this outcome.
Table 3-28. Associations between PFHxS exposure and blood lipids in medium
confidence epidemiology studies
Reference
Population
Median
exposure (IQR)
or as specified
(ng/mL)
Effect
estimate
Total cholesterol3
LDLa
Triglycerides3
General population, adults
Dong et al.
(2019)
NHANES cross-
sectional (2003-
2014 pooled),
U.S.; 8,950
adults
1.6
P (95% CI) for
1 unit
increase
0.98 (-0.89, 2.85)
0.72 (-1.63, 3.06)
NR
Fisher et al.
(2013)
Canadian Health
Measures
Survey
2.2(1.2-3.6)
P (95% CI) for
1 log-unit
increase
0.03 (0.01,0.05)*
0.06(0.01,0.11)*
0.02 (-0.02,0.06)
Cakmak et al.
(2022)
(2007-2009)
cross-sectional,
Canada; 2,345
adults
OR (95% CI)
for high
cholesterol vs.
Q1
Q2: 1.05 (0.69,1.61)
Q3: 1.43 (0.85,1.4)
Q4: 1.57(0.93, 2.64)
p-trend: 0.001*
NR
NR
(2007-2017);
6,045
participants
1.5 (GM)
% change for
increase
equivalent to
GM
2.8(1.1, 4.5)*
-3.8 (-9, 1.7)
-1.4 (-5.0, 2.3)
Lin etal. (2019)
Participants
2.3 (1.4-3.8)
Mean diff
2.24 (0.15, 4.33)*
1.32 (-0.59, 3.22)
3.91 (-1.77, 9.59)
from
randomized trial
of diabetes
(95% CI) for
twofold
increase
prevention, U.S.;
888 overweight
and pre-diabetic
adults
quartiles vs.
Q1
Q2: 3.87 (-2.89, 10.63)
Q3: 9.28 (2.38, 16.19)*
Q4: 7.43 (0.53, 14.33)*
Q2: 1.22 (-4.94,
7.38)
Q3: 6.22 (-0.06,
12.52)
Q4: 3.88 (-2.39,
10.17)
Q2: 9.64 (-8.75,
28.03)
Q3: 16.43 (-2.34,
35.22)
Q4: 11.23 (-7.52,
29.99)
Cross-
sectional
OR (95% CI)
for high lipids
1.08 (0.94, 1.25)
NR
1.03 (0.90, 1.18)
Prospective
HR (95%) for
high lipids
Total: 1.00 0.92 (1.09)
Placebo: 1.02 (0.89,
1.17)
Lifestyle: 1.02 (0.90,
1.15)
NR
Total: 1.14(1.00,
1.28)*
Placebo: 1.23
(1.03,1.47)*
Lifestyle: 1.19
(0.98,1.44)
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Reference
Population
Median
exposure (IQR)
or as specified
(ng/mL)
Effect
estimate
Total cholesterol3
LDLa
Triglycerides3
Liu et al.
(2020a)
Cross-sectional
analysis from
randomized
clinical trial of
weight loss; 326
overweight
adults
2.4(1.6-3.6)
Means ± SE
for tertiles
Tl: 181.6 ±7.8
T2: 189.3 ± 7.6
T3: 192.5 ± 7.8
p-trend = 0.15
NR
Tl: 119.4 ± 11.2
T2: 133.6 ± 11.0
T3: 130.8 ± 11.2
p-trend = 0.37
Dunder et al.
(2022)
Cohort study
(2001-2004),
Sweden; 864
older adults (70
yrs at baseline)
3.1 (2.0-5.8)
P (95% CI) for
In-unit
increase (for
lipids over 10
years)
0.08 (0.01, 0.15)*
0.04 (-0.01, 0.10)
0.04 (0.01, 0.07)*
Canova et al.
(2020)
Cross-sectional
study in highly
contaminated
area (2017-
2019), Italy;
15,720 young
adults (20-39
yrs)
3.6(1.6-7.8)
P (95% CI) for
In-unit
increase
2.02(1.45,2.58)*
(exposure-response
gradient across
quartiles)
1.31 (0.81, 1.8)*
0.02 (0.01,
0.02)*b
OR (95% CI) vs
Q1 for
abnormal
lipids
Q2: 1.18(1.06, 1.30)*
Q3: 1.19(1.07, 1.32)*
Q4: 1.41(1.25, 1.58)*
Q2: 1.21 (1.08,
1.35)*
Q3: 1.15 (1.02,
1.29)*
Q4: 1.37 (1.20,
1.55)*
Q2: 1.11 (0.93,
1.32)
Q3: 1.17 (0.98,
1.40)
Q4: 1.22 (1.02,
1.46)*b
Pregnant women
Yang et al.
(2020b)
Pregnancy
cohort (2013-
2014), China,
436 women
0.3 (0.2-0.5)
P (95% CI) for
In-unit
increase
0.18 (0.05, 0.32)*
0.09 (0.001,
0.19)*
0.07 (-0.1, 0.24)b
Gardener et al.
(2021)
Pregnancy
cohort (2009),
U.S., 433
women
0.5 (0.3-0.9)
Means ± CI
for quartiles
No clear association
(reported only on
figure)
NR
No clear
association
(reported only on
figure)
Starling et al.
(2014b)
Norwegian
Mother and
Child cross-
sectional
analysis (2003-
2004), Norway;
891 women
0.6 (0.4-0.9)
P (95% CI) for
In-unit
increase
3.00 (-1.75,7.76)
1.92 (-2.50,
6.33)b
-0.01 (-0.05,
0.03)b
quartiles vs.
Q1
Q2: 0.65 (-6.87,8.17)
Q3: 1.62 (-6.08,9.32)
Q4: 4.25 (-3.88,12.39)
Q2: 0.44 (-6.19,
7.08)
Q3: 0.50 (-6.15,
7.16)
Q4: 1.48 (-5.89,
8.85)b
Q2: -0.04 (-0.11,
0.02)
Q3: -0.02 (-0.10,
0.05)
Q4: -0.02 (-0.09,
0.05)b
Matilla-
Santander et al.
(2017)
INMA cross-
sectional
analysis (2003-
2008), Spain;
1,240 women
0.6 (0.4-0.8)
% change
(95% CI) for
log-unit
increase
-0.09 (-8.25, 1.45)
NR
-4.90 (-9.16,
-0.72)*b
quartiles vs.
Q1
Q2: 1.21 (-1.05, 3.45)
Q3: 0.60 (-1.69, 2.94)
Q4: 0.70 (-1.86, 3.38)
NR
Q2: -7.69 (-14.3,
-1.00)
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Reference
Population
Median
exposure (IQR)
or as specified
(ng/mL)
Effect
estimate
Total cholesterol3
LDLa
Triglycerides3
03: -3.92 (-10.9,
3.05)
04: -7.69 (-13.9,
1.40)b
Dalla Zuanna et
Cross-sectional
study in highly
contaminated
area (2017-
2020), Italy; 319
women
2.1(1.1-4.1)
P (95% CI) for
In-unit
increase
-4.91 (-10.06, 0.24)
-8.17 (-12.54,-
3.81)*
NR
al. (2021)
Adolescents and children
Blomberg et al.
Birth cohort
(2007-2009),
Faroe Islands,
459 children
(followed to 9
yrs)
0.2 (0.1-0.2)
P (95% CI) for
doubling
PFAS and
lipids at birth
Overall
0.03 (-0.04, 0.09)
Girls
0.05 (-0.03, 0.14)
Boys
-.003 (-0.1, 0.09)
Overall
0.01 (-0.03, 0.05)
Girls
0.019 (-0.03,
0.07)
Boys
-0.01 (-0.06, 0.05)
Overall
11 (5.9, 17)*b
Girls
13(5.5,21)*
Boys
9.7(1.9, 18)*
(2021)
(additional
results with
different timing
of exposure and
outcome
measurement
are available in
the publication)
PFAS at birth
and lipids at
18 mo
Overall
-0.04 (-0.18, 0.1)
Girls
-0.03 (-0.22, 0.17)
Boys
-0.05 (-0.24, 0.15)
Overall
-0.05 (-0.15, 0.06)
Girls
-0.05 (-0.2, 0.1)
Boys
-0.04 (-0.19, 0.12)
Overall
3.5 (-3.9, 11)
Girls
7.9 (-2.5, 19)
Boys
-0.87 (-11, 9.9)
PFAS and
lipids at 9 yrs
Overall
-0.02 (-0.14, 0.1)
Girls
-0.05 (-0.21, 0.1)
Boys
0.02 (-0.15, 0.19)
Overall
-0.06 (-0.14, 0.03)
Girls
-0.06 (-0.18, 0.06)
Boys
-0.05 (-0.18, 0.08)
Overall
-1.8 (-8.3,5.2)
Girls
2.6 (-6.3, 12)
Boys
-6.8 (-16, 3)
Jensen et al.
Birth cohort
(2010-2012),
Denmark; 612
children
(followed to 18
mo)
0.3
(5th-95th: 0.1-0.7)
P (95% CI) for
1 unit
increase
3 mo
-0.08 (-0.33, 0.17)
Girls
-0.11 (-0.37, 0.16)
Boys
0.13 (-0.58, 0.85)
18 mo
-0.06 (-0.32, 0.21)
Girls
-0.05 (-0.32, 0.21)
Boys
-0.10 (-1.41, 1.21)
3 mo
0.01 (-0.24, 0.26)
Girls
0.05 (-0.22, 0.32)
Boys
-0.28 (-1.01, 0.44)
18 mo
-0.06 (-0.35, 0.22)
Girls
-0.08 (-0.37, 0.21)
Boys
0.37 (-1.02, 1.76)
b
3 mo
0.18 (-0.07, 0.44)
Girls
0.21 (-0.06, 0.48)
Boys
-0.02 (-0.75, 0.71)
18 mo
-0.24 (-0.51, 0.04)
Girls
-0.22 (-0.50, 0.06)
Boys
-0.62 (-1.95, 0.70)
b
(2020a)
PaoadoDoulou
Six birth
cohorts, Europe,
1,301 children
(6-11 yrs)
prenatal
0.5 (0.3-0.9)
P (95% CI) for
doubling
exposure
NR
0.03 (-0.03, 0.09)
b
0.02 (-0.05, 0.08)
b
et al. (2021)
Children
0.3 (0.2-0.6)
NR
0.02 (-0.06, 0.10)
b
0.00 (-0.08, 0.08)
b
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Reference
Population
Median
exposure (IQR)
or as specified
(ng/mL)
Effect
estimate
Total cholesterol3
LDLa
Triglycerides3
Manzano-
Salgado et al.
(2017b)-
INMA cohort
(2003-2008),
Spain; 627
children (4 yrs)
prenatal
0.6 (0.4-0.8) (GM
(IQR))
P (95% CI) for
doubling
exposure and
cholesterol z-
score
0.02 (-0.09,0.12)
Boys: -0.02 (-0.17,0.13)
Girls: 0.04 (-0.12,0.20)
-0.01 (-0.12,
0.09)b
Boys: -0.04
(-0.18, 0.10)
Girls: 0.00 (-0.15,
0.15)
0.11 (-0.01,
0.21)b
Boys: 0.16(0.03,
0.30)*
Girls: 0.07 (-0.08,
0.22)
SDratlen et al.
(2020b)
WTC cohort
(2001-2002),
U.S.; 222
newborns
cord blood 0.7
(0.5-1.0)
% difference
for 1%
increase
0.03 (-0.02, 0.08)
NR
0.13 (-0.04, 0.23)
Mean ratio vs.
Q1
Q2: 1.03 (0.94, 1.12)
Q3: 1.06(0.98, 1.16)
Q4: 1.07(0.98, 1.16)
p-trend 0.5
NR
Q2: 1.08 (-.92,
1.28)
Q3: 1.22 (1.04,
1.45)
Q4: 1.26 (1.07,
1.49)
p-trend 0.002
Kang et al.
(2018)
Korea
Environmental
Health Survey in
Children and
Adolescents
cross-sectional
analysis (2012-
2014), Korea,
150 children (3-
18 yrs)
0.8 (0.6-1.0)
P (95% CI) for
In-unit
increase
0.99 (-9.53, 11.50)
-4.22 (-13.98,
5.53)
0.08 (-0.09, 0.25)
Averina et al.
(2021)
Cross-sectional
study (2010-
2011), Norway,
940 adolescents
(~16 yrs)
Girls 0.8,
Boys 1.0
(GMs)
P (95% CI) for
log-unit
increase
"No association" (data
not shown)
"No association"
(data not shown)
"No association"
(data not shown)
Jain and
Ducatman
(2018)
NHANES cross-
sectional (2013-
2014), U.S.; 458
children (6-11
yrs)
0.9
Means (95%
CI)
Ql: 154 (149-159)
Q2: 159 (155-163)
Q3: 153 (145-161)
Q4: 158 (153-164)
p = 0.4
NR
NR
Zeng et al.
(2015)
Genetic and
Biomarkers
study for
Childhood
Asthma cross-
sectional
analysis (2009-
2010), Taiwan;
225 adolescents
(12-15 yrs)
1.2 (range 0.2-
10.3) (boys)
P (95% CI) for
1 unit
increase
1.10 (-0.71,2.92)
0.99 (-0.41,
2.39)b
1.80 (-0.67,
4.27)b
Li et al. (2021a)
HOME cohort
(2003-2006);
prenatal 1.3 (0.8—
2.3)
Difference for
IQR increase
NR
NR
0.1 (0.0, 0.2)
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Reference
Population
Median
exposure (IQR)
or as specified
(ng/mL)
Effect
estimate
Total cholesterol3
LDLa
Triglycerides3
U.S.; 186
adolescents (12
yrs)
birth 0.6 (0.4-1.0)
NR
NR
0.1 (-0.1, 0.3)
Mora et al.
Project Viva
cohort (1999-
2002), U.S.; 682
children (7-8
yrs)
prenatal
2.4(1.6-3.8)
P (95% CI) for
IQR increase
0.5 (-1.1,2.2)
similar for boys and
girls
0.5 (-0.9,1.9)
similar for boys
and girls
-0.6 (-2.0,0.8)
Boys: 0.6
(-1.9,3.1)
Girls: -1.1
(-3.1,0.1)
(2018)
child
1.9(1.2-3.4)
-0.3 (-1.0,0.5)
Boys: -0.5 (-1.5,0.4)
Girls: 0.2 (-1.0,1.3)
-0.2 (-0.9,0.4)
Boys: -0.5
(-1.4,0.3)
Girls: 0.3
(-0.6,1.3)
-0.4 (-1.0,0.3)
similar for boys
and girls
Tian et al.
Birth cohort
(2012), China;
306 newborns
prenatal
2.7(2.0-3.5)
P (95% CI) for
In-unit
increase
0.05 (-0.07, 0.16)
0.03 (-0.11, 0.18)
0.02 (-0.11, 0.15)
(2021)
Canova et al.
Cross-sectional
study in highly
contaminated
area (2017-
2019), Italy;
6,669
adolescents
(14-19 yrs) and
2,693 children
(8-11 yrs)
adolescents
2.8(1.6-4.8)
P (95% CI) for
In-unit
increase
1.49 (0.60, 2.37)
1.44(0.68, 2.19)
0.01 (-0.01, 0.02)
b
(2021)
P (95% CI) vs
Q1
Q2: 1.96(0.20, 3.73)*
Q3: 1.72 (-0.10, 3.54)
Q4: 3.80(1.83, 5.77)*
Q2: 2.03 (0.52,
3.55)*
Q3: 1.60 (0.05,
3.16)*
Q4: 3.65 (1.97,
5.33)
Q2: 0.01 (-0.02,
0.04)
Q3: 0.00 (-0.03,
0.03)
Q4: 0.02 (-0.02,
0.05)
children
1.9(1.2-2.8)
P (95% CI) for
In-unit
increase
1.30 (-0.28, 2.88)
0.54 (-0.87, 1.96)
-0.01 (-0.03, 0.01)
P (95% CI) vs
Q1
Q2: 0.46 (-0.73, 1.65)
Q3: 1.68(0.44, 2.91)*
Q4: 1.32 (0.07, 2.56)*
Q2: -1.70 (-4.19,
0.8)
Q3: -1.22 (-3.81,
1.38)
Q4: 0.76 (-1.86,
3.39)
Q2: 0 (-0.04, 0.04)
Q3: 0 (-0.04, 0.04)
Q4: -0.02 (-0.07,
0.02)
*p < 0.05.
NR: not reported.
aUnits and transformations of outcome variables varied across studies.
bLow confidence endpoint within medium confidence study.
Other risk factors for cardiovascular disease
1 Twenty-seven studies report on the association between PFHxS exposure and other risk
2 factors for cardiovascular disease, including blood pressure in the general population (18 studies),
3 blood pressure and hypertensive disorders during pregnancy (6 studies), atherosclerosis (2
4 studies), abdominal aortic calcification (1 study), and ventricular geometry (1 study). The study
5 evaluations for these outcomes are summarized in Figure 3-66. One study was considered high
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
confidence, 18 were medium confidence, and 7 were low confidence. One study (Yang etal.. 20181
evaluating blood pressure was excluded from further analysis (uninformative) due to critical
deficiencies in participant selection and confounding.
Considering blood pressure in the general population, the majority of studies reported no
association between PFHxS exposure and higher blood pressure. A few positive associations with
hypertension or higher blood pressure were observed in studies of adolescents and young adults
(see Table 3-29). Statistically significant associations were reported in a cross-sectional study of
16-year-olds in Norway (Averina etal.. 20211 and a cohort with follow-up to 12 years of age in the
U.S. (Li etal.. 2021a). though the association was not monotonic across quartiles in Averina et al.
f20211. In a region of Italy with high PFAS contamination, a positive association was observed in
young adults aged 20-39 years fPitter etal.. 20201 but not adolescents aged 14-19 years (Canovaet
al.. 20211. Studies in non-age restricted adults fLin etal.. 2020b: Chen etal.. 2019a: Christensen et
al.. 2019: Liu etal.. 2018: Bao etal.. 2017: Christensen etal.. 20161 and children (Papadopoulou et
al.. 2021: Khalil etal.. 2018: Manzano-Salgado etal.. 2017b) reported null findings with blood
pressure and/or odds of hypertension, and there is not a clear biological explanation for this
pattern of results by age.
Results for hypertensive disorders of pregnancy are summarized in Table 3-30. One of four
studies of gestational hypertension Borghese etal. f20201 and two of four studies of preeclampsia
fBirukov etal.. 2021: Borghese etal.. 20201 reported positive associations, with statistical
significance in one. Conversely, two studies reported inverse associations (statistically significant in
one) with gestational hypertension (Liu etal.. 2021a: Huang etal.. 2019c). The other one study of
gestational hypertension (Birukov etal.. 2021) and two studies of preeclampsia (Huang et al..
2019c: Starling etal.. 2014a) reported no association. One low confidence study reported no
association between PFHxS and continuous blood pressure during pregnancy fVarshavskv et al..
20211.
No association with PFHxS exposure was observed in studies of atherosclerosis in adults
(Lind etal. (2017). medium confidence) and markers of atherosclerosis/arterial wall stiffness in
adolescents (Koshvetal. (2017). low confidence). One study examining abdominal aortic
calcification, a marker of subclinical atherosclerotic disease, reported a positive, though not
statistically significant, association in men but not women (Koskela etal.. 2022). Lastly, no
association was observed in a single medium confidence study of ventricular geometry fMobacke et
al.. 20181.
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IS®
Avsrlna, 2021, 7410155-
BangrriH, 2020, 6833725 -
Bao, 2017, 3860099
BaLrella, 2022,10273294-
Birukov, ?0?1. 7410153
Horghese, 2020, 6833656-
Canova. 2021,10176518
Chen, 2019, 5387400-
Christensen, 2016, 385B533
Christensen, 2019, 5080398
Huang, 2019, 5083564-
Khalrl, 2018,4238547
Koshy, 2017, 4238478-
Koskola A et a) 2022 -
Li, 2021,7401102
Lin, 2020, 6311641
Llnd, 2017, 3858504
Liu, 2018,4238396
Uu. 2021, 9944393-
Manzano-Salgado, 2017b 4238509-
Mobacke, 2018, 4354163-
Papadopoulou, 2021, 9960593-
Pftler G, 2020, 6988479 -
Starling, 2014, 2446669
Varshavsky, 2021, 7410195-
Yang,2018,4238462
Zarft Jftdril, 2021, 7404065
Legend
| Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-66. Study evaluation results for epidemiology studies of PFHxS and
cardiovascular disease risk factors. For additional details see HAWC link. Multiple
publications of the same study: Christensen etal. (2019) also includes Liao etal.
f20201
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Table 3-29. Associations between PFHxS exposure and hypertension in
medium confidence epidemiology studies in adolescents and young adults
Reference
confidence
Population
Median
exposure
(IQR) or as
specified
(ug/mL)
Effect estimate
Hypertension
Averina et al. (2021)
Cross-sectional study in Norway; 940
adolescents (~16 yrs)
0.8 (GM in
girls)
OR (95% CI) for
quartiles vs Q1
Q2: 1.63 (0.90, 2.94)
Q3: 1.25 (0.69, 2.28)
Q4: 2.06(1.16, 3.65)*
Li et al. (2021a)
Cohort in U.S.; 221 adolescents
(follow-up through 12 yrs)
1.2 (0.9,
1.8) at 8 yrs
Difference for IQR
increase (outcome
continuous blood
pressure z-score)
Systolic BP
0.2 (0.0, 0.4)*
Canova et al. (2021)
Cross-sectional study in highly PFAS
exposed region, Italy; 6,669
adolescents (14-19 yrs)
2.8(1.6-
4.8)
(3 (95% CI) for In-
unit increase
(outcome
continuous blood
pressure)
Systolic BP
-0.22 (-0.65, 0.21)
Diastolic BP
-0.15 (-0.45, 0.16)
Pitter et al. (2020)
Cross-sectional study in highly PFAS
exposed region, Italy; 15,786 adults
(20-39 yrs)
6.0 (mean)
OR (95% CI) for
quartiles vs Q1
Q2: 1.01 (0.86, 1.19)
Q3: 1.08(0.92, 1.27)
Q4: 1.19(1.00, 1.41)
* p <0.05.
Table 3-30. Associations between PFHxS exposure and gestational
hypertension and preeclampsia in medium confidence epidemiology studies
Reference
Population
Median
exposure in
ng/mL (IQR)
Effect
estimate
Gestational
hypertension
Preeclampsia
Liu et al.
Nested case-control
study within cohort
in China; 544 women
0.1(0.03, 0.1)
OR (95% CI) for
tertiles vs T1
T2: 0.41 (0.25, 0.67)*
T3: 0.29 (0.17, 0.50)*
NR
(2021a)
Huang et al.
Cross-sectional study
in China; 674 women
at delivery
0.2 (0.1-0.2)
OR (95% CI) for
tertiles vs T1
T2: 0.83 (0.31,2.22)
T3: 0.48 (0.16, 1.43)
T2: 1.10 (0.36, 3.38)
T3: 0.80 (0.25, 2.60)
(2019c)
Birukov et al.
Cohort in Denmark;
1,436 women
0.4 (0.3-0.5)
HR (95% CI) for
doubling of
exposure
0.97(0.66, 1.43)
1.14 (0.91, 1.42)
(2021)
Starling et al.
Nested case-control
study within cohort
in Norway; 1,046
women
0.7(0.5-1.0)
HR (95 CI) for
quartiles vs Q1
NR
02:0.86(0.59, 1.26)
03: 1.01 (0.69, 1.49)
04: 0.93 (0.64, 1.36)
(2014a)
Borghese et
Cohort in Canada;
1,739 women
1.0(0.7-1.6)
OR (95% CI) for
tertiles vs T1
T2: 1.03 (0.64, 1.67)
T3: 1.39(0.87, 2.20)
T2: 1.40 (0.54, 3.63)
T3: 3.06 (1.27, 7.39)*
al. (2020)
*p <0.05.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Cardiovascular disease
Five studies report on the association between PFHxS and cardiovascular disease, including
coronary heart disease, myocardial infarction (heart attack), and congestive heart failure. The study
evaluations are summarized in Figure 3-67. Two studies, an analysis of NHANES data for 1999-
2014 and a prospective cohort of farmers and other rural residents, were medium confidence
(Huang etal.. 2018: Mattsson et al.. 20151. The other three were low confidence (Graber etal.. 2019:
Honda-Kohmo etal.. 2019: Christensen etal.. 20161. These cross-sectional studies were focused on
very specific populations—participants in litigation over PFAS exposure (Graber etal.. 2019:
Honda-Kohmo etal.. 20191 or anglers fChristensen etal.. 20161. There were concerns about
confounding in all of these studies, and for sensitivity in Graber etal. f20191 and Christensen et al.
f20161 due to small sample size. Additionally, all the studies except Mattsson et al. f20151—which
used a national register of disease—classified cardiovascular disease based on self-report on
questionnaires, which is likely to suffer from misclassification and which could be differential in
studies wherein exposure was known due to litigation (Graber etal.. 2019: Honda-Kohmo etal..
20191 but is likely nondifferential and thus toward the null in the other studies (Huang etal.. 2018:
Christensen et al.. 20161.
In the two medium confidence studies, no association between PFHxS exposure and
coronary heart disease f Huang etal.. 2018: Mattsson etal.. 20151 or total cardiovascular disease,
congestive heart failure, coronary heart disease, angina pectoris, myocardial infarction, or stroke
(Huang etal.. 20181 was observed. In the low confidence studies, one reported higher odds of
cardiovascular conditions with higher exposure (Graber et al.. 20191 and two reported lower odds
of coronary heart disease (Honda-Kohmo etal.. 2019: Christensen etal.. 20161. although only
results in Honda-Kohmo etal. f20191 were statistically significant An exposure-response gradient
was observed in Honda-Kohmo etal. f20191 across quantiles.
Christensen, 2016, 3858533-
Graber, 2019, 5080653
Honda-Kohmo, 2019, 5080551
Huang, 2018, 5024212-
Mattsson, 2015, 3859607•
s01
CM®
1
*
'
"
'
—i—
+
- +
*
-
~
+
-
1
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
- +
*
-
-
+
+
-
a
+
-
+
+
+
•
~
+
++
-
+
-
Figure 3-67. Study evaluation results for epidemiology studies of PFHxS and
cardiovascular disease. For additional details see HAWC link.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Summary of cardiovascular effects
Overall, there is some evidence of an association between PFHxS exposure and serum lipids.
However, the evidence for other cardiovascular-related effects is mostly null, which raises
questions about the adversity of the observed lipids changes. It is possible that cholesterol is a more
sensitive measure and that the exposure contrasts in the available studies of disease risk were
inadequate to detect differences.
Metabolic effects
Diabetes
Seven studies (reported in seven publications) report on the relationship between PFHxS
exposure and diabetes (i.e., type 2 diabetes). In cross-sectional studies of PFHxS and diabetes
outcomes, there is some concern for reverse causality. Metabolic changes related to diabetes (e.g.,
impairments of renal function) may affect the amount of PFHxS measured in blood. Four out of the
seven available studies were cross-sectional and were considered low confidence studies due to
temporality and other deficiencies as noted in HAWC. Three studies fCharles etal.. 2020: Sun etal..
2018: Cardenas etal.. 20171 had prospective exposure measurement prior to development of
diabetes. Sun etal. f20181 and Charles etal. f20201 used nested case-control study designs and
Cardenas etal. T20171 used a multicenter randomized clinical trial of a diabetes prevention lifestyle
intervention. Thus, these three studies were evaluated as medium confidence. A summary of the
study evaluations for PFHxS and diabetes is presented in Figure 3-68, and additional details of the
studies can be obtained from HAWC.
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Cardenas, 2017, 4167229-
Charies, 2020, 7068869 -
Conway, 2016, 3859824-
He, 2018, 4238388-
Lind, 2014, 2215376-
Sun, 2018, 4241053-
Zare Jeddi, 2021, 7404065-
~
BO
4
4
+
+
P
~
D
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
+
+
+
+
+
+
~
++
-
I I
-
-
~
+
-
+4
~~
4
¦f
-
+
~
-
-
4
!
+
-
Figure 3-68. Summary of study evaluation for PFHxS and type 2 diabetes in
epidemiology studies. For additional details see HAWC link. Multiple publications
of the same study: He etal. f20181 also includes lain f20201 and lain f2021bl
The results for the association between PFHxS exposure and diabetes are presented in
Table 3-31. All the studies evaluated exposure and outcome associations in adults; in Conway et al.
f2016". both adults and children were included in study population. In the three studies of medium
confidence, one reported higher odds of incident diabetes with higher PFHxS exposure fSun etal..
20181. although not statistically significant, while one reported an inverse association (also not
statistically significant) f Charles et al.. 20201 and the other reported no association fCardenas etal..
20171. In the low confidence studies, one study reported higher odds of diabetes with higher
exposure in men fHe etal.. 20181 and one in women fZare leddi etal.. 20211. On the other hand,
there was an inverse association with PFHxS exposure in Conway et al. f20161 with higher
exposure associated with lower odds of diabetes. The third low confidence study fLind etal.. 20141
reported no association.
Overall, the evidence for the association between PFHxS exposure and diabetes is mixed.
There is some indication of higher odds of diabetes in three studies, one medium and two low
confidences, but other studies of similar confidence and design reported null or inverse findings,
and there was inconsistency in sex differences across the two low confidence studies reporting an
effect.
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Table 3-31. Associations between PFHxS exposure and type 2 diabetes in
epidemiology studies
Reference, study
confidence
Population
Median exposure
(IQR) or as
specified
Effect
estimate
exposure
change
Diabetes OR (95% CI)
Charles et al.
Prospective nested case-
control study of Norwegian
Women and Cancer Study
(2001-2006), Norway; 88
women (30-70 yrs)
0.9 (5th-95th: 0.4-4.3)
Controls
IQR change
0.80 (0.54, 1.20)
(2020), medium
Sun et al. (2018).
Prospective nested case-
control study of Nurses Health
Study II (1995-2000), U.S.;
793 adults (32-52 yrs)
2.0(1.3-3.5)
controls
tertiles vs.
T1
Incident type 2
T2: 1.15 (0.79, 1.67)
T3: 1.26 (0.86, 1.86)
medium
Lind et al. (2014),
PIVUS study cross-sectional
(2001-2004), Sweden; 1,016
adults (70 yrs)
2.1 (1.6-3.4)
In-unit
change
1.00 (0.74, 1.35)
low
Cardenas et al.
Diabetes Prevention Program
(1996-1999), U.S.; 957 adults
(25+ yrs)
Geometric mean
(IQR)
2.4(2.4)
log2-unit
change
Incident type 2
0.98(0.86,1.12)b
(2017), medium
He et al. (2018).
NHANES cross-sectional
(2003, 2004, 2005-2006,
2007-2008, 2009-2010,
2011-2012), U.S.; 7,904
adults (20+ yrs)
Mean + SE
Male
2.9 + 0.1
Female
1.9 + 0.04
quartiles vs.
Q1
Men
Q2: 1.99(1.19, 3.33)*
Q3: 1.87(1.15, 3.05)*
Q4: 2.31 (1.37, 3.91)*
Women
Q2: 0.65 (0.41, 1.03)
Q3: 0.87 (0.52, 1.43)
Q4: 1.22 (0.71,2.11)
low
Zare Jeddi et al.
Cross-sectional study in region
with high PFAS contamination
(2017-2019), Italy; 15,876
young adults (20-39 yrs)
3.5 (1.7-7.8)
quartiles vs.
Q1
Q2: 0.97 (0.76, 1.24)
Q3: 1.23 (0.97, 1.57)
Q4: 1.06(0.82, 1.37)
Men
Q2: 1 (0.69, 1.46)
Q3: 1.22 (0.86, 1.72)
Q4: 0.99 (0.7, 1.4)
Women
Q2: 1 (0.72, 1.39)
Q3: 1.39(1.01, 1.91)*
Q4: 1.12 (0.8, 1.58)
(2021). low
Conwav et al.
C8 Health Project cross-
sectional (2005-2006), U.S.;
66,889 children and adults
Mean+ SD
5.2 + 10.4
no diabetes
Unit
change
(No
transformat
ion)
0.74 (0.71, 0.77)
(2016), low
Gestational diabetes
Six studies report on the relationship between PFHxS exposure and gestational diabetes.
The quality of gestational diabetes ascertainment was based on how screening of gestational
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diabetes mellitus (GDM) was performed (e.g., defined by a study protocol versus doctor's diagnosis
at individual clinics). Another important consideration is that GDM associations with exposure are
not interpretable in the presence of diabetes. Thus, for participant selection, it was important for
studies to account for the diabetic status and/or the use of diabetic medications. Studies that did
not consider these factors by exclusion or stratification were considered deficient for the
participant selection domain. Overall, there were five studies that examined the association
between PFHxS exposure and gestational diabetes that were of medium confidence fYu et al.. 2021:
Rahman et al.. 2019: Wang etai. 2018: Valvi etaL 2017: Shapiro etal.. 20161 and one study of low
confidence fMatilla-Santander etal.. 20171. A summary of the study evaluations for PFHxS and
gestational diabetes is presented in Figure 3-69, and additional details of the studies can be
obtained from HAWC.
Matilla-Santarider, 2017, 4238432-
Rahman, 2019, 5024206-
Shapiro, 2016, 3201206
Valvi et al., 2017, 3983872
Wang, 2018, 5079666-
Yu, 2021, 7751046-
_L-
* ¥ 4 ~
¦+
~ ~
~ *> -~
*
Jl\ C-0
'.e°V
Legend
j Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-69. Heatmap of study evaluations for PFHxS and gestational diabetes.
For additional details see HAWC link.
The results for the association between PFHxS exposure and gestational diabetes for all
studies are presented in Table 3-32. Two medium confidence studies fYu et al.. 2021: Shapiro etal..
20161 reported higher odds of GDM with PFHxS exposure, but neither was statistically significant,
and in Shapiro etal. f 2 0161. the exposure-response gradient was nonmonotonic, with the odds
ratio highest in the second quartile. The results were generally null in the three other medium
confidence studies fRahman et al.. 2019: Wang etal.. 2018: Valvi etal.. 20171. In the low confidence
study fMatilla-Santander etal.. 20171. there were higher odds of GDM with PFHxS exposure,
although the exposure-response gradient was again nonmonotonic. Overall, there is no clear
association between PFHxS exposure and GDM.
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Table 3-32. Associations between PFHxS exposure and gestational diabetes in
epidemiology studies
Reference,
study
confidence
Population
Median exposure (IQR)
in ng/mL or as specified
Effect
estimate
exposu re
change
Gestational
diabetes
mellitus (GDM)
OR (95% CI)
Yu et al.
(2021).
medium
Population-based birth cohort study in
Shanghai, China (2013-2016); 2,747
pregnant women
0.5 (0.3) in controls
Log-unit
change
1.15 (0.86, 1.54)
Wang et al.
(2018).
medium
Haidian Maternal & Child Health Hospital
in Beijing, China (2013); 84 pregnant
women with GDM and 168 healthy
pregnant women
0.5 (0.3-0.7) in controls
Unit
change
1.07(0.86, 1.35)
Matilla-
Santander et
al. (2017). low
Population-based birth cohort study
INMA (2003-2008); Spanish regions of
Valencia, Sabadell, and Gipuzoka; 2,150
pregnant women (recruited during first
trimester of pregnancy)
Geometric mean
(Geometric SD)
0.6 (2.0)
Quartiles
Q2: 1.25 (0.51,
3.03)
Q3: 1.81 (0.76,
4.28)
Q4: 1.15 (0.42,
3.12)
Rahman et al.
(2019).
medium
NICHD Fetal Growth Study, Singletons
(2009-2013); 2,334 pregnant women (8-
13 wks of gestation)
Geometric mean (95% CI)
Overall cohort
0.8 (0.7-0.8)
GDM
0.7 (0.6-0.9)
SD
increment
Overall cohort3
0.95 (0.73, 1.23)
With family
history of type 2
diabetes3
1.03 (0.92,1.16)
Shapiro et al.
(2016).
medium
Longitudinal birth cohort study MIREC
(2008-2011); Canada; 1,274 pregnant
women (recruited <14 wks of gestation)
Geometric mean (SD)
GDM 1.1(2.0)
Non-GDM 1.0 (2.3)
Quartiles
Q2: 1.6(0.7, 3.8)
Q3: 1.4(0.6, 3.5)
Q4: 1.2 (0.4, 3.5)
Valvi et al.
(2017).
medium
National Hospital in Torshavn (1997 and
2000); Faroe Islands; 604 mother-child
pairs (recruited at 34 wks of gestation)
Median (IQR)
4.5(2.2, 8.5)
Doubling
1.03 (0.80, 1.33)
Blood glucose and insulin resistance
Homeostatic model assessment (HOMA) is a method for assessing insulin resistance and (3-
cell function from fasting glucose and insulin measured in the plasma fMatthews etal.. 19851. The
HOMA of insulin resistance (HOMA-IR) is often used in studies evaluating future risk of diabetes. It
is important to consider that blood glucose and insulin levels and HOMA-IR are difficult to interpret
in the presence of diabetes, especially if diabetes is treated with hypoglycemic medication since the
treatment will affect insulin production and secretion. Thus, for participant selection, the studies
should account for the diabetic status and/or the use of diabetic medications in participants.
Studies that did not consider these factors by exclusion or stratification were considered deficient
for the participant selection domain, and low confidence overall.
Twenty-eight studies (reported in 31 publications) report on the relationship between
PFHxS exposure and blood glucose and/or insulin resistance. Of these, 15 were considered medium
confidence (Cakmak etal.. 2022: Gardener etal.. 2021: Goodrich etal.. 2021: Li etal.. 2021a: Valvi et
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al.. 2021: Yu etal.. 2021: Duan etal.. 2020: Ren etal.. 2020: Alderete etal.. 2019: Christensen etal..
2019: Tensen etal.. 2018: Kang etal.. 2018: Wang etal.. 2018: Cardenas etal.. 2017: Starling etal..
20171 and ten were low confidence. Many of these studies did not account for diabetic status of the
participants and were thus deficient for participant selection. In addition, three studies were
uninformative due to critical deficiencies in at least one domain and are not considered further
f Zhang etal.. 2019a: Yang etal.. 2018: Tiang etal.. 20141. Study evaluation results are summarized
in Figure 3-49 and additional details are available in HAWC. Fifteen studies reported on general
population adults and adolescents, one examined occupational exposure in firefighters, six studies
reported on pregnant women, and five studies reported on children.
The results for the association between PFHxS exposure and these outcomes for all studies
are presented in Table 3-33. For insulin resistance, two of the medium confidence studies in adults
f Cardenas etal.. 20171 and pregnant women flensen etal.. 20181 reported higher HOMA-IR with
higher PFHxS exposure (both statistically significant). The association in Tensen etal. (20181 was
observed primarily in women with high GDM risk based on predefined risk factors (BMI >27
kg/m2, family history of diabetes mellitus, present multiple pregnancy, glucosuria during
pregnancy, previous GDM, or delivery of macrosomic child). The association in women without
GDM risk was in the same direction but much smaller, which may suggest an interaction between
PFAS exposure and metabolic vulnerability, but this cannot be assessed further using the available
data. The other studies indicated no increase in insulin resistance with higher exposure. For blood
glucose, three of the medium confidence studies in pregnant women (Yu etal.. 2021: Tensen et al..
20181 and 6 weeks postpartum (Wang etal.. 20181 reported statistically significantly elevated
blood glucose with higher PFHxS exposure. One study in adolescents and young adults also
reported a positive association in post-puberty girls undergoing an oral glucose tolerance test, with
a significant association at the 1-hour post glucose test, but an inverse association was reported in
boys and results at other ages did not show an association f Goodrich etal.. 20211. Results in other
studies were generally null.
Overall, there is not a clear association between PFHxS exposure and insulin resistance or
blood glucose. Some positive associations were observed in medium confidence studies, but this
was not consistently observed across studies, including other medium confidence studies of similar
design and power. It is possible that exposure contrast was not adequate to observe an association
in these studies, but the positive associations were observed in studies with exposure levels similar
to the null studies.
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Alderete, 2019, 5080614
Cakmak. 2022. 10273369
Cardenas, 2017, 4167229-
Chen, 2019, 5387400-
Christensen, 2019, 5080398-
Duan, 2020, 5918597 -
Fleisch, 2017, 3858513-
Gardener. 2021. 7021199-
Goodrich. 2021, 9960584 -
Heffernan, 2018, 5079713-
Jensen, 2018, 4354143
Jiang, 2014, 2850910
Kang, 2018, 4937567-
Khalil, 2018, 4238547
Khalil. 2020, 7021479-
Koshy, 2017, 4238478
Li. 2021, 7404102-
Lin, 2009, 1290820-
Lin, 2020, 6988476 -
Lind, 2014, 2215376
Liu, 2018, 4238396
Ren, 2020, 6833646 -
Starling, 2017, 3858473
Valvi 2021 8438216-
Wang, 2018, 5079666
Yang. 2018, 4238462
Yu, 2021, 7751046
Zhang, 2019, 5083675
Legend
I Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metnc) or Low confidence (overall)
I Critically deficient (metric) or Uninformative (overall)
Figure 3-70. Heatmap of study evaluations for insulin resistance and blood
glucosea. For additional details see HAWC link.
aMultiple publications of the same study: Lin et al. (2009a) also includes Nelson et al. (2010); Christensen et al
(2019! also includes Jain (2020); Cakmak et al. (2022) also includes Fisher et al. (2013).
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Table 3-33. Associations between PFHxS exposure and insulin resistance or
blood glucose in epidemiology studies
Median
Reference and
confidence
Population
exposure
(IQR) in ng/
mLoras
specified
Effect
estimate
Insulin resistance
(HOMA-IR)
Blood glucose
Adults and adolescents
Duan et al. (2020),
Medium
Cross-sectional study in
China in 2017; 294
adults
0.3 (20 yrs)
Log mean j^SEM
Adolescents
1.0 + 0.1
Adults
0.6 + 0.04
Mean + SEMb
for log-unit
change
Adolescents
0.05 + 0.03
Adults
0.00 + 0.04
Adolescents
-0.01 ^0.03
Adults
-0.02 +_0.06
Goodrich et al.
(2021), Medium
SOLAR cohort (2001-
2012), U.S.; 328
children (8-13 years)
with 2 years follow-up
Children's Health Study
cross-sectional analysis
within cohort (2002),
U.S.; 137 young adults
(17-22 years)
1.1 (GM) in
SOLAR cohort;
0.8 in CHS
cohort girls
Differences
with high vs
low PFHxS
levels
NR
SOLAR
Puberty
Girls
Fasting: 1 (-9,12)
OGTT 1 hr: 3 (-8, 13)
Boys
Fasting: 0 (-12,13)
OGTT 1 hr: -7 (-19,
5)
Postpuberty
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Median
Reference and
confidence
Population
exposure
(IQR) in ng/
mLoras
specified
Effect
estimate
Insulin resistance
(HOMA-IR)
Blood glucose
Girls
Fasting: 6 (-8,19)
OGTT 1 hr: 25 (12,
39)*
Boys
Fasting: -5 (-20,11)
OGTT 1 hr: -25 (-40,
-9)*
CHS young adult
Girls
Fasting 3 (-17, 23)
OGTT 1 hr: 26 (6,
46)
Boys
Fasting: 1 (-12,13)
OGTT 1 hr: 3 (-10,
17)
Li etal. (2021a):
Medium
Prospective cohort
(2003-2006); U.S.; 221
adolescents (12 yrs,
followed from
pregnancy)
1.9(1.0-3.3) at
age 3
Adjusted
difference for
IQR increase
NR
Exposure in
gestation
-0.3 (-1.4, 0.9)
3 years
0.4 (-0.6,1.5)
12 years
0.5 (-0.7,1.8)
Christensen et al.
(2019): Medium
NHANES cross-sectional
(2007-2014); U.S.;
2,975 adults (>20 yrs)
2007-2008
2.0(1.1,3.5)
2009-2010
1.7 (0.9, 2.9)
2011-2012
1.3 (0.8, 2.3)
2013-2014
1.4 (0.8, 2.6)
Odds ratio
(95% CI) for
quartiles vs. Q1
NR
Q2: 0.88 (0.61, 1.27)
Q3: 0.87 (0.59, 1.29)
Q4: 0.85 (0.55, 1.31)
Cakmak et al.
(2022): Medium
Canadian Health
Measures Survey cross-
sectional (2007-2017);
Canada; 6,024 all ages
1.5 (GM)
% change for
GM increase
-0.1 (-4.1, 4.6)
0.3 (-0.6, 1.3)
Lind et al. (2014):
Low
PIVUS study cross-
sectional (2001-2004),
Sweden; 1,016 adults
(70 yrs)
2.1 (1.6-3.4)
Beta coefficient
(95% CI) for In-
unit change
-0.085 (-0.14, -0.03)*
NR
Cardenas et al.
(2017): Medium
Diabetes Prevention
Program (1996-1999),
U.S.; 957 adults
(25+ yrs)
GM (IQR)
2.4 (2.4)
Beta coefficient
(95% CI) for
doubling
0.34(0.12, 0.55)a
0.29 (-0.13, 0.70)
Lin et al. (2020c):
Low
Cross-sectional study in
high contamination
area (2016-2017),
2.7
Beta coefficient
(95% CI) for
quartiles vs. Q1
NR
Q2: 2.42 (-4.91,
9.75)
Q3: -3.22 (-10.78,
4.35)
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Reference and
confidence
Population
Median
exposure
(IQR) in ng/
mLoras
specified
Effect
estimate
Insulin resistance
(HOMA-IR)
Blood glucose
Taiwan; 397 older
adults (55-75 yrs)
Q4: 2.54 (-5.13,
10.21)
Khaliletal. (2020):
Low
Cross-sectional study of
firefighters (2009), U.S.
38 men
3.1 (GM)
Beta coefficient
(95% CI) for
log-unit change
NR
no association
(figure only)
Liu et al. (2018): Low
POUNDS clinical trial
(2003-2007), U.S.; 621
adults (30-70 yrs)
Male 3.1 (2.3-
4.4)
Female 1.9(1.2-
3.0)
Spearman
correlation
0.07
Change in glucose
0-6 mo in trial: 0.02
6-24 mo: -0.02
Pregnant women
Jensen et al. (2018):
Medium
Odense Child Cohort
(OCC) (2010-2012),
Denmark; 649 pregnant
women (15-49 yrs),
outcome measured at
28 wks gestation
0.3 (0.1-0.6)
% Change (95%
CI) for doubling
High GDM risk
9.5 (1.0, 18.8)*
Low GDM risk
2.8 (-7.5, 14.3)
High GDM risk
1.7 (0.2,3.2)*
Low GDM risk
0.2 (-1.3, 1.7)
Yu et al. (2021).
medium
Population-based birth
cohort study in
Shanghai, China (2013-
2016); 2,747 pregnant
women
0.5(0.3) in
controls
Beta coefficient
(95% CI) for
log-unit change
NR
0.003 (-0.04, 0.05)
OGTT1hr
0.22 (0.06, 0.37)*
OGTT2 hr
0.08 (-0.06, 0.21)
Gardener et al.
(2021): Medium
Vanguard Pilot Study of
the National Children's
Study cross-sectional
(2009); U.S.; 425
pregnant women in 3rd
trimester
0.5 (0.3-0.9)
Means (95% CI)
for quartilers
Non-significant, non-
monotonic increase
(figure only)
NR
Wang et al. (2018):
Medium
Haidian Maternal &
Child Health Hospital in
Beijing, China (January-
March 2013); 84
pregnant women as
GDM and 168 healthy
pregnant women,
outcome measured at 6
wks postpartum
GDM 0.5 (0.3-
0.8)
Non-GDM 0.5
(0.3-0.7)
Odds ratio
(95% CI) for
categories of
blood glucose
(3.2-4.74;
4.75-5.04;
5.06-6.84
mmol/L)
NR
GDM/non-GDM
pooled (adjusted for
status)
Medium vs. Lowest
1.32 (0.72, 2.42)
Highest vs. Lowest
2.29(1.22, 4.29)*
Starling et al. (2017):
Medium
Health Start cohort at
the University of
Colorado Hospital
(2009-2014); U.S.;
1,410 pregnant women
(>16 yrs), outcome
measured at mid-
pregnancy
0.8 (0.5, 1.2)
% Change (95%
CI) for
categories of
exposure
NR
Group 1
-0.009 (-0.029,
0.010)
Group 2
-0.023 (-0.044,
-0.002)
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Reference and
confidence
Population
Median
exposure
(IQR) in ng/
mLoras
specified
Effect
estimate
Insulin resistance
(HOMA-IR)
Blood glucose
Ren et al. (2020):
Medium
Shanghai-Minhang
Birth Cohort (2012);
China; 856 pregnant
women (outcome
measured at 20-28
weeks gestation)
2.8(2.1-3.6)
OR (95% CI) for
high glucose
NR
0.89 (0.51, 1.55)
Children
Kane et al. (2018):
Medium
Korea Environmental
Health Survey in
Children and
Adolescents (KorEHS-C)
subcohort (2012-2014);
South Korea; children
(3-18 yrs)
Geometric
mean (SD)
0.8(1.6)
Beta coefficient
(95% CI) for In-
unit change
NR
0.925 (-1.779,
2.164)
Khaliletal. (2018):
Low
Cross-sectional study of
obese children from
Lipid Clinic at Dayton's
Children Hospital
(April-Oct. 2016); U.S.;
children (8-12 yrs)
1.1 (1.4)
Beta coefficient
(95% CI) for
unit change
-0.11 (-0.10, 0.78)
0.00 (-2.10, 2.09)
Goodrich et al.
(2021), Medium
SOLAR cohort (2001-
2012), U.S.; 328
children (8-13 years)
with 2 years follow-up
1.1 (GM) in
SOLAR cohort;
0.8 in CHS
cohort girls
Differences
with high vs
low PFHxS
levels
NR
Prepuberty
Girls
Fasting-2 (-16,12)
OGTT 1 hr -4 (-18,
10)
Boys
Fasting-7 (-15, 0)
OGTT-7 (-15,0)
Alderete et al.
(2019): Medium
Study of Latino
Adolescents at Risk of
type 2 Diabetes
(SOLAR) cohort (2001-
2011); U.S.; children (8-
14 yrs)
Geometric
mean (SD)
1.7 (2)
Beta coefficient
(95% CI) for In-
unit change
-0.4 (-1.7, 0.8)
0.9 (-2.5, 4.2)
Fleisch et al. (2017):
Low
Project Viva
prospective cohort
(1992-2002); U.S.; 665
mother-children pairs
Geomean (25%,
75%)
Prenatal
2.5 (1.6, 3.8)
Mid-childhood
2.2 (1.2, 3.4)
% Change (95%
CI) for quartiles
vs Q1
Prenatal
02: -6.7 (-23.7, 14.2)
03: -13.5 (-29.6, 6.3)
04: -17.1 (-32.3, 1.6)
Mid-childhood
02: -5.1 (-20.9, 13.8)
03: -6.7 (-22.7, 12.6)
04: -16.8 (-31.4, 0.8)
NR
*P-value or p-trend < 0.05.
NR = not reported; OGTT = oral glucose tolerance test
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Metabolic syndrome
Metabolic syndrome is defined using criteria related to waist circumference, elevated
triglycerides, reduced HDL cholesterol, elevated blood pressure, and elevated fasting glucose. Three
abnormal findings out of the five factors classify a person with metabolic syndrome fAlberti et al..
20091.
Six studies reported on the association between PFHxS exposure and metabolic syndrome.
One study was uninformative due to critical deficiencies in participant selection, outcome
ascertainment, and confounding (Yang etal.. 20181. The other five studies were cross-sectional
fZare leddi etal.. 2021: Christensen etal.. 2019: Fisher etal.. 2013: Lin etal.. 2009b: Lin et al..
2009a) and considered medium confidence. A summary of the study evaluations for PFHxS and
metabolic syndrome is presented in Figure 3-71, and additional details of the studies can be
obtained from HAWC.
There was little indication of increased odds of metabolic syndrome with higher exposure
to PFHxS. One study in older adults in an area with high PFAS contamination (Lin etal.. 2020c)
reported a positive association in the fourth quartile (OR [95% CI]: 1.22 [0.66, 2.25]), but this
association was non-monotonic across quartiles and not statistically significant The other four
studies reported results that were null fZare leddi et al. 2021: Fisher etal.. 2013: Lin etal.. 2009al
or inverse fChristensen etal.. 20191.
ii i i i i i i —i—
I
i
Christensen, 2019, 5080398-
+~
+
R
+
+
B
Legend
Good (metric) or High confidence (overall)
Fisher, 2013, 2919156-
~~
~
~
~
~~
~
~
+
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Lin, 2009, 1290820-
+
+
~
~
~
+
+
-
Lin, 2020, 6988476 -
+
~
4-
+
+
+
¦f
Yang, 2018, 4238462-
B
l
+
m
31
t
» | |
Zare Jeddi, 2021, 7404065-
+
R
| 4-
~
+
*
Figure 3-71, Summary of study evaluations for epidemiology studies of PFHxS
and metabolic syndrome. For additional details see HAWC link.
Adiposity
Twenty-five studies (29 publications) reported on the association between PFHxS exposure
and obesity, BMI, and/or other measures of adiposity. Two studies were excluded as uninformative
due to lack of consideration of potential confounding (Zhang et al.. 2019a: Yang etal.. 20181. Of the
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23 remaining studies, ten were cross-sectional studies fLind etal.. 2022: Canova etal.. 2021:
Thomsen etal.. 2021: Zare Teddi etal.. 2021: Domazetetal.. 2020: Scinicariello etal.. 2020a: Chen et
al.. 2019a: Christensen etal.. 2019: Khalil etal.. 2018: Nelson etal.. 20101 and were classified as low
confidence because of concern that the timing of exposure measurement was not relevant to
development of this chronic outcome, similar to concerns described for diabetes. Thirteen studies
had prospective exposure measurement, including nine that examined the association between
prenatal or early-life exposure measurements and adiposity during childhood, one cohort of people
living near a uranium processing plant, one clinical trial of weight loss diets that examined weight
change, and two studies of gestational weight gain. All of the prospective studies, where exposure
was measured prior to the outcome, were classified as medium confidence. The evaluations for
these studies are summarized in Figure 3-72.
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«&*
Blake. 2018, 5080657
Bloom, 2022, 9959635
Braun. 2016, 3859836
Canova, 2021, 10176518-
Chen, 2019. 5080578-
Chen. 2019, 5387400-
Christensen. 2019, 5080398
Domazet. 2020, 6833700 -
Heftman. 2017. 3859812
Janis. 2021, 7410181
Ka risen, 2017. 3858520
Khalll, 2018, 423854/
Lind, 2022 10176401
Liu. 2018, 4238396-
Man/ano-Salgado, 2017b, 4238509
Marks. 2019, 5381534
Martlnsson 2020. 6311645
Mora. 2017, 3859823 •
Nelson. 2010. 1291110
Papadopoulou, 2021, 9960593
Romano. 2020, 7014708
SclnicorioNo. 2020, 6391244
Thomson. 2021,9959568
Yang. 2018, 4238462
Zare Jeddi, 2021, 7404065
Zhang. 2019, 5083675
Legend
I Good (met/ic) or High confidence (overall)
Adequate (metnc) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Unmformalive (overall)
Figure 3-72. Summary of study evaluations for epidemiology studies of
adiposity. For additional details see HAWC link. Multiple publications of the same
study: Braun et al. f20161 also includes Braun et al. f20201: Liu etal. f202Qcl.
and Li etal. f2021aV Mora etal. f2Q17) also includes lanis etal. f20211.
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The results from the studies of adiposity in children are summarized in Tables 3-34 and 3-
35, which contain the continuous outcome measures and dichotomous outcome (overweight),
respectively. Most studies report null results for the associations between PFHxS and BMI, waist
circumference, or direct measures of body fat. In analyses of overweight/obesity as a dichotomous
outcome, three medium confidence studies (four publications) reported positive associations (Liu_et
al.. 2020c: Martinsson etal.. 2020: Braun etal.. 20161 with odds ratios or relative risks ranging 1.16
to 1.71. However, only one study was statistically significant (Liu etal.. 2020c) and the association
in Martinsson etal. (2020) was non-monotonic across quartiles, with an inverse association in the
third quartile and a positive association in the fourth quartile. n addition, as described in the
Developmental Effects section, one medium confidence study by Gvllenhammar et al. f20181 was
null for weight standard deviation scores over time from 3 to 60 months of age.
In adults, one medium confidence prospective study fLiu etal.. 20181 reported no difference
in weight loss associated with PFHxS exposure but found a statistically significant increase in
weight gain associated with PFHxS exposure in women following the weight loss trial (changes in
body weight: tertile 1: 2.7 ± 0.8, tertile 2: 3.6 ± 0.9, tertile 3: 4.9 ± 0.9, p-trend: 0.009). The second
medium confidence prospective study (Blake etal.. 2018) and the low confidence cross-sectional
studies fLind etal.. 2022: Zare Teddi etal.. 2021: Chen etal.. 2019a: Christensen et al.. 20191
reported no difference in adiposity with higher PFHxS exposure. Additionally, two medium
confidence studies examined gestational weight gain. Marks etal. f2019bl and Romano etal. f20201
reported no association with absolute gestational weight gain (stratified by baseline weight
categories under/normal weight and overweight/obese).
Overall, there is very limited evidence of an association between PFHxS exposure and
adiposity. The strongest evidence comes from a weight loss trial in adults that observed higher
weight gain following the trial, but the lack of coherence with related outcomes in the remaining
studies decreases the strength of the evidence.
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Table 3-34. Associations between maternal exposure to PFHxS and adiposity
in children
Reference, study
confidence
Population
Median
exposure
(IQR)
(Hg/mL)
Effect
estimate
BMI
Waist
circumference
Body fat
Chen et al.
(2019b), medium
Prospective birth
cohort in China; 404
children at 5 yrs
0.2 (range
0.1-0.9)
(3 (95% CI)
for log-
unit
change
Girls: -0.5 (-1.1,
0.2)
Boys: 0.4 (-0.3,1.1)
Girls:-1.2 (-3.1, 0.7)
Boys: 0.6 (-1.3, 2.5)
Body fat percent
Girls: -1.9 (-4.9,1.0)
Boys: 1.8 (-0.7, 4.3)
(3 (95% CI)
fortertiles
(refTl)
Girls
T2: 0.2 (-0.8, 0.3)
T3: -0.2 (-0.8, 0.3)
Boys
T2: 0.1 (-0.5, 0.7)
T3: 0.2 (-0.4, 0.8)
Girls
T2: -0.4 (-2.1, 1.2)
T3: -0.4 (-2.1, 1.3)
Boys
T2: -0.2 (-1.8, 1.4)
T3: 0.5 (-1.1, 2.1)
Girls
T2: -0.8 (-3.4, 1.7)
T3: -1.9 (-4.4, 0.7)
Boys
T2: 0.2 (-2.0, 2.3)
T3: 0.7 (-1.4, 2.8)
Karlsen et al.
(2017), medium
Birth cohort (2007-
2009), Faroe
Islands; 444 children
with follow-up at 18
mos
0.2 (0.1—
0.3)
P (95% CI)
for log-
unit
increase;
T2 and T3
0.10 (-0.01,0.21)
T2: -0.03
(-0.23,0.17)
T3: 0.18
(-0.03,0.38)
NR
NR
371 children with
follow-up at 5 yrs
vs. T1
0.04 (-0.07,0.15)
T2: -0.02
(-0.22,0.19)
T3: 0.07
(-0.14,0.28)
NR
NR
Papadopoulou et
al. (2021).
medium
Six birth cohorts,
Europe, 1,301
children at 6-11 yrs
prenatal
0.5 (0.3—
0.9)
P (95% CI)
for
Quartiles
vs Q1
NR
Q2: -0.02 (-0.22,
0.17)
Q3: 0.05 (-0.18, 0.28)
Q4: 0.03 (-0.23, 0.30)
NR
Children
0.3 (0.2—
0.6)
NR
Q2: -0.12 (-0.31,
0.06)
Q3: 0.10 (-0.13, 0.32)
Q4: 0.04 (-0.22, 0.29)
NR
Thomsen et al.
(2021). low
Cross-sectional
analysis within birth
cohort (2009),
Denmark, 109 boys
at ~12 yrs
0.5 (0.4-
0.7)
P (95% CI)
for log-
unit
increase
NR
NR
Abdominal fat
0.03 (-0.15, 0.20)
Visceral fat
0.02 (-0.11, 0.14)
Total fat
0.01 (-0.22, 0.23)
Manzano-
Salgado et al.
(2017b), medium
INMA birth cohort
(2003-2008), Spain;
1,230 children with
follow-up at 4 yrs
0.6 (GM)
(0.4-0.8)
P (95% CI)
for
doubling
exposure
-0.02 (-0.10,0.07)
-0.04 (-0.14,0.05)
NR
1,086 children with
follow-up at 7 yrs
-0.04 (-0.14,0.06)
-0.04 (-0.12,0.04)
NR
Domazet et al.
(2020), low
Cross-sectional
analysis within
multi-center cohort
0.9 (0.7—
1.1)
% change
(95% CI)
for 10%
increase
NR
NR
Fat mass
-1.07 (-1.99, -0.15)*
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Reference, study
confidence
Population
Median
exposure
(IQR)
(Hg/mL)
Effect
estimate
BMI
Waist
circumference
Body fat
(1997), Europe; 242
children at 9 yrs
Bloom et al.
(2022). low
ECHO cohort (2017-
2019), U.S. 803
children at 4-8 yrs
0.9 (0.5-
1.5)
(3 (95% CI)
for log-
unit
increase
BMI z-score
Without obesity
-0.06 (-0.17, 0.05)
With obesity
0.01 (-0.22, 0.24)
Without obesity
-0.06 (-0.15, 0.04)
With obesity
0.16 (-0.09, 0.40)
Fat mass
Without obesity
-0.08 (-0.42, 0.25)
With obesity
0.63 (-0.68, 1.93)
Percent body fat
Without obesity
-0.003 (-0.01, 0.01)
With obesity
0.01 (-0.02, 0.04)
Scinicariello et
al. (2020a), low
NHANES cross-
sectional study
(2013-2014), U.S.
600 children at 3-11
yrs
0.9 (GM)
(3 (95% CI)
fortertiles
vsTl
BMI z-score
T2: -0.17 (-0.47,
0.13)
T3: -0.26 (-0.57,
0.04)
Weight for age
T2: -0.30 (-0.67,
0.07)
T3: -0.42 (-0.76, -
0.08)*
NR
Khalil et al.
(2018), low
Cross-sectional
study (2016), U.S.
48 children with
obesity at 8-12 yrs
1.1 (1.4)
(3 (95% CI)
for unit
change
0.32 (-0.76, 1.39)
NR
NR
Braun et al.
(2016): Liu et al.
(2020c):
Braun et al.
HOME birth cohort
(2003-2006), U.S.;
204 children with
follow-up at 8 yrs
1.4 (0.8-
2.3)
Difference
(95% CI)
Tertiles vs.
T1
T2: 0.22
(-0.10,0.54)
T3: 0.12
(-0.21,0.45)
T2: 2.7 (0.0,5.4)
T3: 1.1 (-1.7,3.9)
Body fat percent
T2: 2.3 (0.3,4.2)
T3: 1.1 (-0.9,3.1)
(2020): Li et al.
(2021a), medium
212 children with
follow-up at 12 yrs
(3 (95% CI)
for IQR
increase
BMI z-score
Prenatal exposure
0.10 (-0.08, 0.28)
12 year old
exposure
0.09 (-0.14, 0.31)
Prenatal exposure
1.73 (-0.87, 4.33)
12 year old exposure
0.55 (-2.48, 3.57)
Fat mass index
Prenatal exposure
0.10 (-0.07, 0.26)
12 year old exposure
0.08 (-0.11, 0.27)
Body fat percent
Prenatal exposure
0.94 (-0.35, 2.22)
12 year old exposure
0.68 (-0.79, 2.15)
214 children with
follow-up at 12 yrs
(3 (95% CI)
for IQR
increase
T2: -0.65 (-1.90,
0.65)
T3: -0.50 (-1.78,
0.76)
NR
NR
Difference
(95% CI)
Tertiles vs.
T1
Rate of BMI change
from 8-12 yrs
T2: -0.06 (-0.20,
0.09)
T3: -0.01 (-0.15,
0.13)
NR
NR
186 children with
follow-up at 12 yrs
Difference
(95% CI)
NR
Prenatal exposure
0.03 (-0.01, 0.08)
Visceral fat
Prenatal exposure
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Median
Reference, study
confidence
Population
exposure
(IQR)
(Hg/mL)
Effect
estimate
BMI
Waist
circumference
Body fat
for IQR
change
12 year old exposure
0.02 (-0.04, 0.07)
0.09 (-0.01, 0.20)
12 year old exposure
0.10 (-0.05, 0.26)
Hartman et al.
(2017), medium
ALSPAC birth cohort
(1991-1992),
United Kingdom;
359 children with
follow-up at 9 yrs)
1.6(1.3-
2.2)
(3 (95% CI)
for 1 unit
increase
-0.02 (-0.08,0.03)
-0.08 (-0.22,0.06)
DXA total body fat
-0.06 (-0.21,0.09)
DXA trunk fat
-0.01 (-0.11,0.08)
Mora et al.
(2017): Janis et
al. (2021).
medium
Project Viva birth
cohort (1999-2002),
U.S.; 1,006 children
with follow-up at
median 3 yrs
2.4(1.6-
3.8)
(3 (95% CI)
for IQR
increase
0.01 (-0.03,0.05)
0.03 (-0.10,0.16)
Sum of subscapular
and triceps skinfold
thickness
0.16(0.01,0.31)
876 children with
follow-up at median
7 yrs
0.01 (-0.03,0.05)
0.11 (-0.22,0.43)
Sum of subscapular
and triceps skinfold
thickness
0.25 (-0.14,0.64)
DXA total fat mass
index
0.04 (-0.04,0.13)
DXA trunk fat mass
index
0.02 (-0.02,0.06)
531 children with
follow-up at 13 yrs
(3 (95% CI)
BMI z-score
-0.05 (-0.09, 0.00)
NR
Total fat mass index
-0.22 (-0.35, -0.08)*
Truncal fat mass
index
-0.09 (-0.16, -0.03)*
Canova et al.
(2021). low
Cross-sectional
study in highly
contaminated area
(2017-2019), Italy;
6,669 adolescents
(14-19 yrs) and
2,693 children (8-11
yrs)
adolescen
ts
2.8(1.6-
4.8)
(3 (95% CI)
vs Q1
BMI z-score
Q2:-0.08 (-0.15, 0)
Q3: 0.01 (-0.07,
0.09)
Q4: 0.03 (-0.05,
0.12)
Similar for boys and
girls
NR
NR
children
1.9(1.2-
2.8)
(3 (95% CI)
for In-unit
increase
BMI z-score
Q2: 0.06 (-0.08, 0.2)
Q3: -0.20 (-0.34, -
0.06)*
Q4: -0.18 (-0.32, -
0.03)*
NR
NR
*p < 0.05.
T: tertile, GM: geometric mean, DXA: dual-energy X-ray absorptiometry, NR: not reported.
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Table 3-35. Associations between maternal exposure to PFHxS and overweight
status in children in medium confidence epidemiology studies
Reference
Population
Median
exposure
(IQR)
(Hg/mL)
Effect estimate
Overweight
Karlsen et al.
(2017)
Birth cohort (2007-2009), Faroe
Islands; 444 children with follow-up
at 18 mos
0.2 (0.1-0.3)
OR (95% CI) for
log-unit increase;
Tertiles vs. T1
1.12 (0.97, 1.30)
T2: 1.06 (0.82, 1.38)
T3: 1.24 (0.97, 1.58)
371 children with follow-up at 5 yrs
1.11 (0.77, 1.59)
T2: 0.86 (0.47, 1.55)
T3: 1.22 (0.73, 2.04)
Manzano-
Salgado et al.
(2017b)
INMA cohort (2003-2008), Spain;
1,230 children with follow-up at 4
yrs
0.6 (GM)
(0.4-0.8)
RR (95% CI) for
doubling
exposure
0.96 (0.87, 1.07)
1,086 children with follow-up at 7
yrs
0.94 (0.84, 1.05)
Martinsson et
al. (2020)
Case-control study (2003-2008),
Sweden; 1,048 children at 4 yrs
0.7 (0.5-1.0)
OR (95% CI);
Quartiles vs. Q1
Q2: 0.95 (0.66, 1.37)
Q3: 0.66 (0.44, 0.97)
Q4: 1.16(0.81, 1.66)
Braun et al.
(2016):
Liu et al.
HOME birth cohort (2003-2006),
U.S.; 204 children with follow-up at
8 yrs
1.4 (0.8-2.3)
RR (95% CI);
Tertiles vs. T1
T2: 1.33 (0.72, 2.48)
T3: 1.48 (0.75, 2.96)
(2020c)
212 children with follow-up at 12
yrs
RR (95% CI) for
IQR increase
1.71 (1.08, 2.73)*
Mora et al.
(2017)
Project Viva birth cohort (1999-
2002), U.S.; 1,006 children with
follow-up at median 3 yrs
2.4 (1.6-3.8)
RR (95% CI) for
IQR increase
Overweight:
1.03 (0.94,1.13)
Obese:
1.02 (0.89,1.17)
876 children with follow-up at
median 7 yrs
Overweight:
1.04 (0.92,1.17)
Obese:
1.07 (0.94,1.22)
Animal Studies
1 There are two 28-day gavage studies in SD rats fNTP. 2018b: 3M. 2000al. one 4- to 6-week
2 oral gavage exposure study using genetically modified mice fBiiland etal.. 20111. and two
3 reproductive/developmental studies using CD-I mice fChang etal.. 20181 or Sprague Dawley rats
4 fButenhoff etal.. 2009: 3M. 20031 that measure effects relevant to the assessment of the
5 cardiovascular or metabolic systems after repeated oral dose exposure to PFHxS. The studies
6 report on heart weight and histopathology, and alterations of cardiometabolic endpoints such as
7 fasting levels of serum lipids which are considered indicative of potential cardiotoxicity (Gad.
8 20151. Overall study confidence was high for cardiometabolic endpoints evaluated in these studies
9 f Chang etal.. 2018: NTP. 2018b: Biiland etal.. 2011: Butenhoff et al.. 2009: 3M. 2003. 2000a).
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Studies reporting on heart weight and histopathology were considered of low confidence due to
experimental design uncertainties (NTP. 2018a: Butenhoffetal.. 2009: 3M. 20031 (see Figure 3-73).
Specifically, the exposure duration of less a month was not considered sufficient for evaluation of
injury to the cardiovascular system fDaughertv etal.. 20171. raising significant concerns for
insensitivity.
Heart weight and histopathology
There is no clearly preferred measurement for evaluating heart weights (absolute or
relative). Some data show that heart weight is nonproportional to body weight (Bailey etal.. 20041.
other data reports that heart weight in strongly correlated with body weight, with better
correlation in males fNirogi etal.. 20141. Thus, both absolute and relative heart weights are
considered biological relevant metric for this endpoint. Absolute and relative heart weights were
not altered in SD rats exposed to PFHxS for 28 days at 0.625 to 10 mg/kg-day fNTP. 2018a: 3M.
2000a). However, one reproductive/developmental toxicity study reported decreased relative
heart/brain weight (by 8%) in F0 generation male SD rats exposed to PFHxS for 44 days (Butenhoff
etal.. 2009: 3M. 2003): the biological significance of this 8% change is unclear. Importantly, the
same study also reports that absolute and heart-to-body weight ratios were not affected in males or
females exposed to PFHxS.
Heart histopathology was evaluated in a 28-day study fNTP. 2018al and a
reproductive/developmental toxicity study (Butenhoffetal.. 2009: 3M. 2003). both in SD rats.
Exposure to PFHxS from 0.625 to 10 mg/kg-day did not cause a significant effect on the incidence of
nonneoplastic cardiovascular injury in male or female rats (NTP. 2018a: Butenhoffetal.. 2009: 3M.
2003). As noted above, there is concern that the exposure duration of these studies (<1 month) was
too short to expect to see histological manifestations of cardiac injury.
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Chemical administration and characterization
Exposure timing, frequency and duration
Endpoint sensitivity and specificity
Selective reporting and attrition
Confounding/variable control
Observational bias/blinding
Results presentation
Overall confidence
Reporting quality
Allocation
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Not reported
Legend
Figure 3-73. Cardiornetabolic effects, heart weight/histopathology - animal
study evaluation heatmap. For additional details see HAVVC link.
Serum lipids
Levels of plasma cholesterol fGad. 20151 were evaluated in two
reproductive/developmental toxicity studies fChang etal. 2018: ButenhoffetaL 2009: 3M. 20031.
and in four short-term exposure studies (He etal.. 2022: NTP. 2018a: Biiland et al.. 2011: 3M.
2000a), and one chronic exposure study fPfohl etal.. 20201 (see Figure 3-74). In the high
confidence, short-term studies, exposure to PFHxS for 28 days resulted in a 12% to 51% reduction
in serum cholesterol at doses ranging from 1.25 to 10 mg/kg-day in male and female rats in one
study f3M. 2000al and in males only in the other fNTP. 2018b). Likewise, a separate study using
male AP0E*3-Leiden CETP23 mice reported that exposure to 6 mg/kg-day PFHxS decreased total
cholesterol, HDL andnon-HDL cholesterol fBiiland etal.. 2011). Two reproductive/developmental
toxicity studies report that PFHxS exposure for 42 to 44 days decreased serum cholesterol by 19%
to 42% in male F0 SD rats at doses ranging from 0.3 to 10 mg/kg-day (Bute nhoff etal.. 2009: 3M.
20031. whereas F0 CD-I male mice treated with 10 mg/kg-day displayed a 27% reduction in
cholesterol fChang etal.. 20181. However, these effects were not observed in female Sprague
Dawley rats or CD-I mice fChang etal.. 2018: Butenhoff etal.. 2009: 3M. 20031. or male C57BL/6J
mice exposed to 12 or 29 weeks in high fHe etal.. 20221 or medium confidence studies fPfohl et al..
20201 exposed to 0.06 or 0.15 mg/kg-day, respectively.
23APOE*3-Leiden.CETP mice is a genetically modified animal model which better emulates human lipoprotein
profiles and is used to investigate cholesterol metabolism and cardiovascular disease fVeseli et al.. 20171.
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PFHxS exposure-induced effects on serum lipid levels and production were also measured
in rats and mice. In a high confidence study of SD rats, short-term oral exposure for 28 days
decreased serum triglyceride levels by 22% to 46% after exposures ranging from 2.5 to 10 mg/kg-
day fNTP. 2018a: 3M. 2000al. and a medium confidence study using AP0E*3-Leiden.CETP mice
reported decreased serum-free fatty acids (43%) and VLDL-triglyceride production rate (74%),
very-low-density lipoprotein (VLDL) half-life, and VLDL apolipoprotein production in animals
treated with 6 mg/kg-day PFHxS (Biiland et al.. 2011). The same study reported a 75% increase in
lipoprotein lipase in exposed mice fBiiland etal.. 2011). Two high confidence
reproductive/developmental toxicity studies also evaluated PFHxS-induced alterations in other
serum lipids. In SD rats, exposure to 10 mg/kg-day, decreased serum triglycerides by 27% in F0
males fButenhoffet al.. 2009: 3M. 20031 but a similar study using CD-I mice did not observe
significant treatment-related changes in serum triglycerides in male or female F0 animals at PFHxS
levels up to 3mg/kg-day (Chang etal.. 2018). Medium and high confidence studies exposing using
C57BL/6] mice to 0.15 or 0,06 mg/kg-day PFHxS for 29 or 12 weeks respectively report no
significant effect on serum tryglycerides (He etal.. 2022: Pfohl et al.. 2020). Overall, a consistent
pattern of dose-dependent decreases in cholesterol and other lipids in the blood of animals exposed
to PFHxS were observed across high and medium confidence studies of varied design in both rats
and mice, although effects were largely absent in female rodents and studies that exposed mice to
PFHxS at lower doses. However, as described below there are limitations in using animal models
(including the APOE-modified mice) to emulate human lipid regulation.
Reporting quality-;
Confounding/variable control
Selective reporting and attrition -j
Chemical administration and characterization-^
Exposure timing, frequency and duration -J
Results presentation -J
Endpoint sensitivity and specificity -I
Overall confidence -\
Legend
I Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
NR| Not reported
Figure 3-74. Cardiornetabolic effects, serum lipids - animal study evaluation
heatmap. For additional details see HAWC link.
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Considerations for interpreting the human relevance of the animal cardiometabolic evidence
The results from the available animal studies should be interpreted with caution because of
known cardiometabolic differences between humans and laboratory animal models commonly
used in toxicological studies fGetz and Reardon. 20121. This section briefly highlights what is
currently known regarding cardiometabolic differences between humans and laboratory animal
models commonly used in toxicological studies to inform potential future studies. The
pathophysiology of cardiovascular disease in humans is a complex process driven by multiple risk
factors (e.g., diabetes, hyperlipidemia, hypertension, and aging), which lead to metabolic and pro-
inflammatory alterations. Unfortunately, there is no single animal model that completely
recapitulates all the features of human disease fOppi etal.. 20191. Furthermore, there are
significant differences between rodent and human cardiovascular systems that should be taken into
consideration. Murine plasma cholesterol is approximately threefold lower, the major lipoprotein in
mice is HDL, not LDL fGetz and Reardon. 20121. and differences in bile acid composition contribute
to lower intestinal absorption of cholesterol and higher cholesterol excretion fOppi etal.. 20191.
These differences contribute to significantly lower cholesterol levels in mice when compared with
humans and having lower cholesterol levels in turn confers protection from cardiovascular injuries
such as atherosclerosis fOppi etal.. 20191.
Although the available animal evidence suggests the cardiovascular system may be
responsive to PFHxS-induced responses, additional studies using experimental models and designs
that better emulate human disease would help to fully characterize the pathology of potential
cardiometabolic responses to this chemical. Future studies should focus on the use of genetically
manipulated or experimentally induced rodent models that can emulate human metabolic and
pathological conditions fKodavantietal.. 20151. For example, studies aimed at evaluating vascular
injuries such as atherosclerosis should focus on the use of animal models that can generate non-
HDL-based hypercholesterolemia such as LDL Receptor or apolipoprotein E (ApoE) null mice fGetz
and Reardon. 20121 and expose animals for sufficient time to develop of arterial injuries
(Daughertv etal.. 20171. Furthermore, future studies focused on potential effects to the
cardiovascular system should include analysis of physiological and biochemical parameters (e.g.,
heart rate, blood pressure, blood gases, and oxygen consumption), which are considered indicative
of adverse responses in the cardiovascular system fGad. 20151.
Evidence Integration
The available evidence on PFHxS-induced cardiometabolic effects in humans is considered
slight (see Table 3-36). There is some evidence of an association between PFHxS exposure and
cardiometabolic effects in humans, specifically an indication of higher serum cholesterol levels. A
similar association has been noted for some other long-chain PFAS, including PFOA and PFOS (U.S.
EPA. 2016a. b). However, there is little evidence of an association between PFHxS exposure and
cardiovascular disease, functional endpoints of cardiovascular function (e.g., blood pressure), or
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other related cardiovascular risk factors. It is possible that cholesterol is a more sensitive measure
to PFHxS exposure and that the exposure levels and contrast were inadequate to detect differences
in disease risk. However, without additional evidence, the lack of coherence across outcomes
reduces confidence in the evidence of the association with cardiovascular effects and indicates that
the observed changes in serum lipids may not be adverse.
The evidence from animal toxicity studies on PFHxS-induced cardiometabolic effects is
considered indeterminate. Animal studies report dose-related decreases in serum cholesterol and
triglyceride levels in male, but not female (largely), rats and mice. The direction of the observed
responses in animals is different from the observations made in human studies (e.g., decreased
serum lipids in animals versus reported increases in humans) and these effects may be caused by
PFHxS-induced alterations in hepatic lipoprotein metabolism (see Serum Biomarkers of Liver
Function Section 3.2.5). Heart weights and histopathology were not affected in exposed animals,
although these low confidence experiments were potentially insensitive. The downstream effects of
the metabolic alterations observed in the available studies are unclear in the absence of additional
experiments and measures of adverse responses in the cardiovascular system. Further,
interpretation of such results is not possible due to major limitations in the animal toxicity
database. As described above, commonly used laboratory rodent species are relatively resistant to
cardiotoxicity effects in part due to differences in lipid profiles fVeseli etal.. 20171. Furthermore,
the available evidence on PFHxS-induced cardiometabolic effects consists of short-term and
developmental exposure studies, whereas longer study durations (between 10 to 12 weeks in mice
Daugherty etal. (2017)) are generally preferred for evaluations cardiovascular system functions
and disease (e.g., atherosclerosis). These experimental design and database deficiencies limit the
interpretation of observed cardiometabolic changes in rodents and their applicability for informing
human health hazard.
The available animal and epidemiological evidence suggests but is not sufficient to infer
whether exposure to PFHxS might cause cardiometabolic effects in humans given sufficient
exposure conditions24. This judgement is based primarily on consistent increases in cholesterol in
humans, but with limitations in the available epidemiological studies that introduce uncertainty
(see description above) and also reflects an inability to interpret the available epidemiology
evidence on PFHxS-induced cardiovascular disease as well as the animal evidence available to
inform this health effect.
24 The "sufficient exposure conditions" are more fully evaluated and defined for the identified health effects
through dose-response analysis in Section 5.
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Table 3-36. Evidence profile table for PFHxS exposure and cardiometabolic effects
Evidence stream summary and interpretation
Evidence integration summary judgment
Evidence from studies of exposed humans
Studies and
confidence
Factors that increase
certainty
Factors that decrease certainty
Summary and key
findings
Evidence stream
judgment
Serum Lipids
25 medium and 9
low confidence
studies
• Consistency in
direction of
association for
cross-sectional
analyses in
adults
• Medium
confidence
studies reporting
an effect
• Exposure-
response
gradient
observed in five
studies
• Potential for residual
confounding across PFAS
• Unexplained inconsistency
among studies with
prospective exposure
measurement and for all
studies of LDL cholesterol and
triglycerides
Majority of studies in
adults report higher
serum cholesterol with
higher PFHxS exposure,
including 40-60%
increases in the odds of
high cholesterol.
®oo
Slight
Generally
consistent findings
for total
cholesterol in
adults. Evidence
for other related
outcomes and age
groups is
inconsistent.
®oo
Evidence suggests, but is not sufficient to
infer
Primary Basis:
based primarily on consistent increases in
cholesterol in humans, but with limitations in
the available epidemiological studies that
introduce uncertainty.
Human relevance:
The animal models used are considered
inadequate to inform potential human
cardiometabolic responses with confidence.
Cross-stream coherence-.
Evidence in animals is indeterminate
Other
Cardiovascular
Risk Factors
1 high, 18
medium, and 7
low confidence
studies
• No factors noted
• Unexplained inconsistency
Positive associations
reported for hypertension
in adolescents and young
adults, but not other
adults or children. One of
four studies of gestational
hypertension and two of
four studies of
preeclampsia reported a
positive association. No
association between
PFHxS exposure
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Evidence stream summary and interpretation
Evidence integration summary judgment
atherosclerosis or
ventricular geometry
Cardiovascular
Disease
2 medium and 3
low confidence
studies
• No factors noted
• Lack of coherence across
outcomes in low confidence
studies
• Unexplained inconsistency -
No associations in the two
medium confidence studies
No association with
cardiovascular disease in
medium confidence
studies. Low confidence
studies report higher
odds of cardiovascular
conditions and lower
odds of coronary heart
disease
Evidence from in vivo animal studies
Studies and
confidence
Factors that increase
certainty
Factors that decrease certainty
Summary and key
findings
Evidence stream
judgment
Heart Weight/
Histopathology
3 low confidence
studies in adult
rats:
• 28-d (x2)
• 44-d
• High and
medium
confidence
studies of serum
lipid measures
• Inconsistent findings across
studies reporting on serum
lipids.
• Unclear biological
significance of decreases in
serum lipids.
• No observed PFHxS-
induced effects on
heart weight or
histopathology in
short-term,
potentially
insensitive studies.
• Dose-dependent
decreases in serum
cholesterol and
triglycerides.
QQQ
Indeterminate
Serum Lipids
5 high
confidence
studies in adult
rats:
• 28-d (x2)
• 42-d
• 44-d
• 84-d
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Evidence stream summary and interpretation
Evidence integration summary judgment
2 medium quality
study:
• 42-d
• 203-d
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3.2.1. Hematopoietic Effects
Human Studies
One epidemiology study fliang etal.. 20141 examined the association between PFHxS
exposure and hematopoietic system effects, specifically the parameters from a complete blood
count (white and red blood cells, hemoglobin, platelets). This study was considered uninformative
due to lack of consideration of confounding, and thus no human studies were synthesized for
hematopoietic effects.
Animal Studies
The toxicity database for PFHxS-induced hematopoietic system effects consists of two 28-
day studies fNTP. 2018a: 3M. 2000al in Crl:Cd Br and Sprague-Dawley (SD) rats, respectively; and
one multigenerational study in Sprague Dawley rats fButenhoff et al.. 20091. All studies exposed the
animals orally via gavage. Hematopoietic system-related outcomes evaluated by these studies
included non-immune blood cells counts and clotting parameters.
Evaluation of the available animal studies showed that these were well conducted for most
hematopoietic-related endpoints. All were considered high confidence. The available studies
generally examined PFHxS hematopoietic effects using doses that ranged between 0 and 10 mg/kg-
day in rats fButenhoff etal.. 2009: 3M. 2000al with the exception of NTP f2018al in which a range
of 0-50 mg/kg-day in female rats and 0-10 mg/kg-day in male rats was used. This approach was to
account for the pharmacokinetic (PK) sex differences that have been observed in rats, in
which PFHxS appears to have a lower mean half-life in female rats versus their male counterparts
(20.7 and 26.9 days respectively (Kim etal.. 2016bll. No overt toxicity was observed at any of the
highest doses tested in any of the available studies. 3M (2000al and NTP
(2018al measured PFHxS related hematopoietic effects using the following parameters: hematocrit,
hemoglobin, platelet counts, prothrombin time, and red blood cell counts. NTP f2018al also
measured PFHxS effects on reticulocyte counts. The study by Butenhoff etal. f20091 measured
hematocrit, hemoglobin, prothrombin time, and red blood cell counts in P0 males and females after
44 days of PFHxS (Butenhoff etal.. 20091.
Figure 3-75 below summarizes the results of animal study evaluations, and Figure 3-76
summarizes the experimental studies and their findings.
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^Ve0V
Reporting quality
Allocation -I
Observational bias/blinding -| nr nr
Confounding/variable control
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Endpoint sensitivity and specificity
Results presentation
Overall confidence
Legend
| Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall;
NR| Not reported
Figure 3-75. Hematological animal study confidence scores from repeated
PFHxS dose animal toxicity studies. For additional details see HAVVC link.
Hemostasis, the physiological process of blood coagulation after injury, is dependent on
interactions between the vasculature and circulating plasma, platelets, blood cells and their related
molecules fHarris et al.. 2012: Gale. 20111. Clinical hematology assays like those available in the
PFHxS evidence based provide insight into bone marrow25 health as well as to assess blood clotting
function. Due to the dynamic interactions between hematopoietic cells and their related molecules,
information on the hematopoietic health of an organism is gained by the interpretation of the
collective battery of assays, rather than individual assay results (Harris et al.. 20121. Therefore, the
collective information from the entirety of the data provided from these available assays was used
to determine the potential for hazard posed by PFHxS on the hematopoietic system.
Hematocrit (Hctl. hemoglobin fHbl. and red blood cell fRBCl count
The hematocrit assay measures the amount (i.e., as a percent of blood volume) of red blood
cells (RBCs) in the blood. This measurement can provide insight on oxygen delivery capacity. All
three studies measured PFHxS effects on hematocrit Two out of the three observed effects related
to PFHxS exposure 3M (2000al observed a significant decrease (5%-6%) in hematocrit in male and
female Crl:Cd Br rats following 28 days of daily oral exposure to 10 mg/kg-day PFHxS (the only
25The bone marrow is the site of blood stem cell formation. Blood stem cells transform into a variety of blood
cells with distinct functions such as white cells (immune function]; red blood cells (oxygen carrying] and
platelet cells (clotting and injury repair] (Manz et al.. 20041.
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tested dose). In the multigenerational study, Butenhoff et al. (20091 also observed a significant
(between 6% and 8%) decrease in hematocrit in male SD rats exposed to PFHxS at >3 mg/kg-day
for 44 days in F0 rats; however, females were unaffected. Further, changes in hematocrit were not
observed by NTP f2018al in male or female SD rats exposed for 28 days to doses of PFHxS up to 10
or 50 mg/kg-day, respectively.
Hemoglobin is an oxygen-carrying protein found in red blood cells. Its function is to deliver
oxygen from red blood cells to organs and tissues and to transport carbon dioxide from these back
to the lungs. All three studies measured hemoglobin in response to PFHxS exposure (NTP. 2018a:
Butenhoff etal.. 2009: 3M. 2000a). Similar to the results for hematocrit, Butenhoff et al. (20091
observed a significant decrease (between 5% and 7%) in hemoglobin in male, but not female, rats
orally exposed to >1 mg/kg-day PFHxS after 44 days of exposure, while 3M f2000al observed a
significant decrease (4%-7%) in hemoglobin in male and female rats at the only dose, 10 mg/kg-
day, at day 28. Changes in hemoglobin were not observed by NTP (2018a) in either male or female
SD rats exposed to a similar dose range of PFHxS for 28 days.
Red blood cells carry oxygen, and their abundance can affect how much oxygen is received
by tissues and organs. RBC count provides a screening tool to assist in diagnosing or monitoring
conditions such as anemia. All studies measured RBC counts in response to PFHxS exposure, with
similar findings as for Hct and Hb, specifically: decreased RBC counts (between 7% and 8%) at >3
mg/kg-day in male, but not female, rats exposed to PFHxS for at least 42 days f Butenhoff etal..
20091: decreased RBC counts (between 6% and 7%) in male and female rats exposed to 10 mg/kg-
day PFHxS for 28 days (3M. 2000a): and, in the second 28-day study, no changes in RBC counts in
male or female rats at up to 10 mg/kg-day (males) or 50 mg/kg-day (females) PFHxS (NTP. 2018a).
Reticulocytes count
Reticulocytes are RBC precursors produced in the bone marrow and released into the
bloodstream where they develop into mature RBCs. Reticulocyte counts can provide information
about the health of the bone marrow and its ability to produce RBCs. Only the NTP study measured
reticulocyte counts., A significant decrease (10% -27%) in number of reticulocytes was observed in
SD male rats at >1.25 mg/kg-day and a significant increase (40%) in reticulocyte counts in female
rats at 3.12 mg/kg-day, but not higher or lower doses (NTP. 2018a). The other two studies
fButenhoff etal.. 2009: 3M. 2000al did not evaluate reticulocytes, preventing interpretation as to
whether a compensatory response of the bone marrow to the observed effects on red blood cell
parameters might exist.
Platelet count
Platelets are cell fragments found within the blood that are critical for clot formation when
bloodvessels are damaged. Together with prothrombin time, platelet counts provide information
on coagulation potential. Two studies, 3M f2000al and NTP f2018al. measured PFHxS effects on
platelet counts. 3M f2000al observed a significant decrease (ll%-26%) in total platelet numbers
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1 in male and female rats exposed to 10 mg/kg-day PFHxS for 28 days. NTP (2018a) did not report
2 any changes in platelet counts in male or female rats exposed to PFHxS for 28 days at up to 10
3 mg/kg-day (males) or up to 50 mg/kg-day (females).
Prothrombin time
4 Prothrombin time is an assay measuring the amount of time it takes blood to clot. Two
5 studies, Butenhoff et al. (2009) and 3M (2000a). measured PFHxS effects on prothrombin time.
6 Butenhoff et al. (2009) observed a significant increase (between 3%-6%) in prothrombin time in
7 male, but not female, rats at 0.3, 3 and 10 mg/kg-day (doses tested: 0.3,1, 3, and 10 mg/kg-day).
8 Under similar study conditions, the single dose (10 mg/kg-day) 28-day study by 3M f2000al
9 observed that prothrombin time significantly decreased (between 5%-6%) in female rats and male
10 rats in response to 10 mg/kg-day PFHxS. Figure 3-76 below summarizes the study design and
11 results for each hematology parameter described in these three studies.
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Endpoint Name Study Name
Hematocrit (Hct) 3M, 2000, 3981194
Experiment Name
28 Day Oral
Animal Description
Rat, Crl:Cd Br (f)
Rat, CrhCd Br (,)
Butenhoff. 2009, 1405789
NTP, 2018, 4309363
Multi-Generational Oral
28 Day Oral
Hemoglobin (Hb) 3M, 2000, 3981194
28 Day Oral
P0 Rat. Sprague-Dawley (5)
Rat, Sprague-Dawley (i)
Rat, Sprague-Dawley ()
Rat, Crl:Cd Br (:)
Rat, Crl:Cd Br (V)
Butenhoff. 2009, 1405789
NTP. 2018, 4309363
Multi-Generational Oral
28 Day Oral
Red Blood Cells (RBQ) 3M, 2000, 3981194
28 Day Oral
Butenhoff, 2009, 1405789
NTP. 2018, 4309363
Multi-Generational Oral
28 Day Oral
Reticulocytes (RET) NTP, 2018, 4309363
Platelet (PLAT) 3M, 2000, 3981194
28 Day Oral
28 Day Oral
P0 Rat Sprague-Dawley ( v)
Rat, Sprague-Dawley ( , )
Rat, Sprague-Dawley ( )
Rat, Crl:Qd Br ( )
Rat, Crl:Cd Br ()
P0 Rat, Sprague-Dawley (J)
Rat, Sprague-Dawley ( )
Rat, Sprague-Dawley (
Rat, Sprague-Dawley (i)
Rat, Sprague-Dawley (;)
Rat, Crl:Cd Br ( _ )
NTP. 2018, 4309363
Prothrombin Time (PT) 3M. 2000, 3981194
28 Day Oral
28 Day Oral
Rat, Cri:Cd Br (i)
Rat, Sprague-Dawley (2)
Rat, Sprague-Dawley (-])
Rat, Crl:Cd Br (r )
Rat, Crl:Cd Br(x)
Butenhoff. 2009, 1405789 Multi-Generational Oral P0 Rat, Sprague-Dawley (,')
Observation Time
Sludy Day 28
Recovery Day 14
Recovery Day 28
Study Day 28
Recovery Day 14
Recovery Day 28
Day 44
Day 29
Day 29
Study Day 28
Recovery Day 14
Recovery Day 28
Study Day 28
Recovery Day 14
Recovery Day 28
Day 44
Day 29
Day 29
Study Day 28
Recovery Day 14
Recovery Day 28
Study Day 28
Recovery Day 14
Recovery Day 28
Day 44
Day 29
Day 29
Day 29
Day 29
Study Day 28
Recovery Day 14
Recovery Day 28
Study Day 28
Recovery Day 14
Recovery Day 28
Day 29
Day 29
Study Day 28
Recovery Day 14
Recovery Day 28
Study Day 28
Recovery Day 14
Recovery Day 28
Day 44
PFHxS-Related Hematopoietic Effects
6 No significant change
A Significant increase
^7 Significant decrease
mg/kg-day
Figure 3-76. Hematopoietic effects of PFHxS exposure in animals, For
additional details see HAWC link.
Evidence Integration
The currently available evidence is inadequate to assess whether PFHxS exposure may
cause hematopoietic effects in humans. The evidence informing the potential for PFHxS exposure to
cause hematopoietic effects is limited to hematology measures in three high confidence studies in
rats, with exposure durations of 28-44 days, and which together are considered to provide slight
evidence (see Table 3-37). Two of the three studies were consistent to some degree, demonstrating
a pattern of changes in male rats. Specifically, male rats exposed to PFHxS at doses ranging from 0
to 10 mg/kg-day for 28-44 days exhibited decreases in multiple RBC parameters (i.e., Hct, Hb, and
RBCs), However, there were inconsistencies, such as reported decreases in platelets counts in one
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28-day study (3M. 2000a). which were not observed in a separate 28-day study with similar study
design (NTP. 2018a). Prothrombin time was reported to increase in male rats as a result of PFHxS
exposure in one study fButenhoff et al.. 20091 and decrease in male and female rats in another f3M.
2000a). Butenhoff et al. f20091 did not measure hematological parameters in female rats). There
was unexplained inconsistency across studies. The two 28-day studies fNTP. 2018a: 3M. 2000a]
reported opposite findings, despite similar study designs and rat strains (the Crl:CD Br rats used by
3M (2000a) are a Sprague Dawley strain). Specifically, NTP (2018a) did not observe consistent
effects on these same parameters (i.e., Hct, Hb, RBCs, and platelets were unchanged; reticulocytes
were decreased) in male animals exposed to doses of PFHxS ranging from 0.625 to 10 mg/kg-day.
Thus, there is no clear explanation (e.g., study methods; doses; exposure duration; species, strain,
or sex) for this inconsistency.
As noted above, the observations in male rats across RBC parameters and other measures
reported in 3M (2000a) and Butenhoff et al. (2009) appear somewhat coherent RBCs play an
important role in hemostasis, as increased Hct has been shown to increase blood viscosity
(reviewed in Litvinov and Weisel (2017)). Additionally, RBCs interact with platelets and modulate
their reactivity through cell signaling molecules or through direct adhesive RBC-platelet
interactions (reviewed in Litvinov and Weisel f20171I Therefore, if RBC counts, along with Hb and
Hct measures are decreased following PFHxS exposure, then it is reasonable that an increase in
prothrombin time would be observed.
The observed effects in the study by Butenhoff et al. (2009) were dose dependent, with
effects generally observed at or greater than 3 mg/kg-day, although some changes at lower doses
were also noted. The duration dependence of these effects could not be determined; the 28-day
study by 3M (2000a) that reported similar findings to those observed by Butenhoff et al. (2009)
only tested 10 mg/kg-day and the PFHxS-related effects on RBC parameters were no longer
observed at or after recovery day 14. Further the magnitude of effects across the various
hematological endpoints measured (ranging from about 4% to 8%) is small and their biological
significance is questionable. The animal evidence is considered slight due to the questionable
biological significance and unexplained inconsistencies in the reported PFHxS effects on
hematology among the available studies.
The currently available evidence is inadequate to assess whether PFHxS may cause
adverse hematopoietic effects in humans given sufficient exposure conditions26. This conclusion is
based on the three available animal studies that assessed PFHxS doses ranging from 0 to 10 mg/kg-
day in male rats.
26 The "sufficient exposure conditions" are more fully evaluated and defined for the identified health effects through
dose-response analysis in Section 5.
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Table 3-37. Evidence profile table for PFHxS hematopoietic effects
Evidence stream summary and interpretation
Evidence integration summary
judgment
Evidence from studies of exposed humans (see Hematopoietic Human Studies Section)
Studies and confidence
Factors that
increase certainty
Factors that decrease
certainty
Summary and key
findings
Evidence stream
judgment
Inferences across evidence
streams
No informative studies
(1 uninformative)
No informative studies identified
ooo
Indeterminate
©OO
Evidence is inadequate
Primary basis:
Despite coherent decreases in
multiple RBC parameters in two
studies in male rats, there were
unexplained inconsistencies
across studies and an unclear
biological significance of effect
magnitude for most endpoints
Human relevance:
Without evidence to the
contrary, effects in rodent
models are considered relevant
to humans.
Cross-stream coherence:
NA; human evidence
indeterminate
Susceptible Populations
and life stages:
NA
Evidence from in vivo animal studies (see Hematopoietic Animal Studies Section)
Studies and confidence
Factors that increase
certainty
Factors that decrease
certainty
Summary and key
findings
Evidence stream
judgment
3 high confidence
studies in rats
• All high
confidence studies
• Unexplained
inconsistencies
across sexes and
studies.
• Unclear biological
significance of
effect magnitude
for most endpoints
(~4%-8%)
2 of the 3 studies
reported male rats
exposed for 28-44 d
exhibited small
decreases in multiple,
coherent RBC
parameters (i.e., Hct,
Hb, and RBCs), as well
as decreases in
prothrombin time.
However, these effects
were observed in both
sexes in one study,
only males in a second
study, and results were
null in the third.
©oo
Slight
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3.2.8. Female Reproductive Effects
Human Studies
Studies of possible female reproductive effects of PFHxS are available for fecundity (i.e.,
time to pregnancy), reproductive hormones, pubertal development, gynecological conditions
(endometriosis and polycystic ovary syndrome [PCOS]), ovarian reserve (including POI), menstrual
cycle characteristics, and developmental measures (anogenital distance). While the evidence for
each of these outcomes is synthesized separately, many of them are closely interconnected, with
almost all of the outcomes having the potential to influence fecundity, as well as each other. For
example, fecundity may be reduced by gynecological conditions and diminished ovarian reserve.
Both of these may influence or be influenced by reproductive hormones levels, as are menstrual
cycle characteristics, timing of pubertal development, and anogenital distance. The direction of
association across these related outcomes is not always straightforward, which complicates
considerations of coherence across outcomes. For example, low levels of anti-Mullerian hormone
(discussed with ovarian reserve) may indicate difficulty getting pregnant (i.e., decreased fecundity)
but high levels may be associated with PCOS, which may also decrease fecundity. In addition,
preterm birth and spontaneous abortion could be driven by either female reproductive or
developmental toxicity. These latter two outcomes are reviewed in the developmental section of
this assessment but are also included in the consideration of coherence across outcomes for female
reproductive effects.
In total, 35 epidemiology studies are available for these outcomes. The study evaluations
are summarized below for each outcome or group of outcomes.
Fecundity (time to pregnancy)
Fecundity is the biological capacity to reproduce. Time to pregnancy, defined as the number
of calendar months or menstrual cycles from the time of cessation of contraception to detection of
pregnancy, is the primary outcome measure used to study fecundity. Many of the other outcomes
described in this section contribute to fecundity. There are nine epidemiology studies that report
on the association between PFHxS exposure and fecundity and related outcomes. A summary of the
study evaluations is presented in Figure 3-77, and additional details can be obtained from HAWC.
One study fCariou etal.. 20151 was considered uninformative due to lack of consideration of any
potential confounders and excluded from further analysis. Of the remaining studies, two were
preconception cohorts and considered medium confidence fCrawford etal.. 2017: Vestergaard etal..
2012). and four were pregnancy cohorts and considered low confidence (Bach etal.. 2018: Bach et
al.. 2015: Velez etal.. 2015: l0rgensen et al.. 2014). The pregnancy cohorts were rated lower due to
potential selection bias from excluding women who were unable to conceive. Two studies examined
related outcomes in women undergoing treatment for infertility. Wang etal. f2021al describes a
cohort of women undergoing in vitro fertilization (IVF)-embryo transfer and reports rates of human
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chorionic gonadotropin (hCG) negativity following treatment; this study was rated medium
confidence. Kim etal. (2020bl is a cross-sectional study of fertilization rate in women who
underwent fully stimulated assisted reproductive treatment at an IVF clinic; this study was rated
low confidence primarily due to concerns for residual confounding.
=* Se
^>ce
Bach, 2015, 3981559-
+
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4-
4-f
+
-
Bach, 2018, 5080557-
•
~
"
Cariou. 2015, 3859840-
¦
•
a
-
n
m
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Crawford, 2017, 3859813-
~
-M-
*
~
+
Jorgensen, 2014, 2851025-
~
-
a
~
Critically deficient (metric) or Uninformative (overall)
Multiple judgments exist
Kim, 2020, 6833596 -
+
+
-*
4>
--
•f
Vestergaard, 2012, 1332472-
tfr
++
-+
+
~
-f
+
Velez, 2015, 2851037-
~
*
+
+
-
Wang, 2021,10176703-
*
~
+
~
Figure 3-77. Summary of study evaluation for epidemiology studies of
fecundity. For additional details see HAWC link.
The results for the association between PFHxS exposure and fecundity are presented in
Table 3-38. A fecundability ratio less than 1 indicates a decrease in fecundity/increase in time to
pregnancy. Of the seven studies, two low confidence studies fBach etal.. 2018: Velez etal.. 20151
reported a statistically significant decrease in fecundity/increase in time to pregnancy with
increased exposure (only in parous women in Bach et al. f201811. The remaining studies reported
no decrease in fecundity. In addition to the time to pregnancy results, three studies fBach et al..
2015: Velez etal.. 2015: Vestergaard et al.. 20121 also analyzed infertility as an outcome. Only the
low confidence study by Velez etal. (20151 reported an increase in infertility with increased
exposure (OR:1.27 (95% CI:1.09,1.48), Neither study of IVF outcomes (fertilization rate, hCG
negativity] reported an association between PFHxS exposure and reduced fertility.
There is unexplained inconsistency in the evidence for this association. A decrease in
fecundity with higher exposure was observed in two low confidence studies, but not the other four
studies, which included the two medium confidence studies. The primary limitation in both Bach et
al. f20181 and Velez etal. f20151 was the potential for selection bias resulting from enrollment of
participants during pregnancy. This approach would exclude women who were ultimately unable to
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1 conceive. If there is a true association between PFHxS and fecundity, this would be a bias against
2 the most exposed women, which would likely result in an underestimate of the association.
3 However, if there is no association, selection would not be related to exposure, so is unlikely to
4 cause bias. Thus, the observed associations should not be dismissed as due to selection bias. On the
5 other hand, as suggested by the authors, the lack of association in nulliparous women in Bach etal.
6 f20181 suggests the possibility of confounding by factors related to previous pregnancies in the
7 results of parous women, which could also exist in Velez etal. (20151. where the population was
8 only 29% nulliparous. Overall, there is considerable uncertainty in the strength of this
9 inconsistently observed association.
Table 3-38. Summary of results for epidemiology studies of fecundity
Reference,
confidence
Population
Exposure
median
(IQR)
Comparison for
effect estimate
Fecundability ratio
(95% CI)
Bach et al. (2015).
low
Aarhus pregnancy cohort (2008-2013),
Denmark; 1,372 nulliparous women
0.5 (0.4-
0.6)
0.1 ng/mL increase
1.00(0.99,1.01)
Quartiles vs. Q1
Q2: 1.05 (0.89,1.24)
Q3: 1.06 (0.89,1.25)
Q4: 1.12 (0.94,1.32)
Bach et al. (2018).
low
Danish National Birth Cohort sub-
sample (1996-2002), Denmark
Nulliparous women (n = 638)
0.9 (0.7—
1.2)
Quartiles vs. Q1
Q2: 1.03 (0.81-1.32)
Q3: 1.05 (0.83-1.35)
Q4: 0.92 (0.72-1.18)
Parous women (n = 613)
Q2: 0.74 (0.55-1.01)
Q3: 0.79 (0.59-1.04)
Q4: 0.60 (0.45-0.80)*
Velez et al.
(2015), low
MIREC pregnancy cohort (2008-2011),
Canada; 1,625 women (29% nulliparous)
1
SD increase
0.91 (0.86,0.97)*
Vestergaard et al.
(2012), medium
Preconception cohort (1992-1995),
Denmark; 222 nulliparous women
1.2 (0.9-
1.8)a
log-unit increase
1.33(1.01,1.75)
Above median vs.
below
1.29(0.90,1.83)
Crawford et al.
(2017), medium
Time to Conceive cohort (2008-2009),
U.S.; 99 women (40% nulliparous)
1.6 (GM)
dichotomous cutoff
75th percentile
Cycle-specific model
1.40 (0.79,2.49)
d-specific model
0.96(0.31,1.71)
Jgrgensen et al.
(2014). low
INUENDO pregnancy cohort (2002-
2004), Greenland, Poland, Ukraine; 938
women
1.9
In-unit increase
Pooled
0.97(0.85,1.11)
Greenland (n = 448, 31% nulliparous)
2.0
Tertiles vs. T1
T2: 1.05 (0.79,1.38)
T3: 0.90 (0.68,1.19)
Poland (n = 203, 92% nulliparous)
2.4
T2: 0.86 (0.57,1.30)
T3: 0.94 (0.62,1.42)
Ukraine (n = 287, 79% nulliparous)
1.6
T2: 0.85 (0.59,1.23)
T3: 1.11(0.78,1.58)
*p < 0.05.
aln participants with pregnancy.
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Reproductive hormones in females
Reproductive hormones and related proteins examined in the evaluated studies include
testosterone, estradiol, insulin like growth factor 1 (IGF-1), follicle stimulating hormone (FSH),
luteinizing hormone (LH), progesterone, as well as sex hormone-binding globulin (SHBG), all
measured in blood, or in one study, saliva. Reproductive hormone levels are associated with all of
the other female reproductive outcomes discussed in this section, but the relationships are often
complex.
Key issues for the evaluation of studies of reproductive hormones were sample collection
and processing. For testosterone, LH, FSH, and prolactin, due to diurnal variation, blood sample
collection should occur at the same time of day for all participants, and if not, time of collection
must be accounted for in the analysis. If there is no consideration of time of collection, the study is
classified as deficient for outcome ascertainment and low confidence overall for these hormones as
this is expected to result in nondifferential outcome misclassification. This applied to eight studies
(Timmermann etal.. 2022: Avcan. 2019: Elavarasi etal.. 2019: Heffernan etal.. 2018: Lopez-
Espinosa etal.. 2016: Lewis etal.. 2015: Osterman etal.. 2008: Martin. 19781. Lastly, the etiologic
timing of PFHxS exposure relevant for influencing reproductive hormones is unclear and likely
dependent on several factors, and thus all exposure windows with available data were considered,
including cross-sectional since circulating hormone levels can be rapidly upregulated or
downregulated in response to a change in exposure.
Fifteen studies (reported in 16 publications) examine potential associations between PFHxS
exposure and reproductive hormones. One study was deemed uninformative due to multiple
serious deficiencies in the participant selection, confounding, and analysis domains (McCoy etal..
20171. Most studies examined only testosterone and estradiol and measured exposure and outcome
concurrently, though some studies measured additional hormones and/or measured exposure
prospectively (prenatal exposure in Maisonet et al. f20151.Tensen etal. f2020bl. and Timmermann
etal. (20221. early pregnancy for outcomes in late pregnancy (Yang etal.. 2022b). and pre-
menopause in Harlow etal. (202111. Eight studies (Timmermann etal.. 2022: Yang etal.. 2022b:
Harlow etal.. 2021: Wang etal.. 2021b: Heffernan etal.. 2018: Zhang etal.. 2018b: Barrett etal..
2015: Lewis etal.. 20151 examined associations in adults, three studies (Zhou etal.. 2016: Lewis et
al.. 2015: Maisonet et al.. 20151 in adolescents, one study fLopez-Espinosa et al.. 20161 in children,
and three studies flensen et al.. 2020b: Liu etal.. 2020b: Yao etal.. 20191 in infants. The study
evaluations are summarized in Figure 3-78. Six studies were considered medium confidence and
seven were low confidence. However, of the medium confidence studies, two did not consider time
of day of sample collection for hormones and were thus low confidence for testosterone (Yao etal..
2019: Lopez-Espinosa etal.. 20161. Notably, two studies (Heffernan etal.. 2018: Zhang etal.. 2018b)
included participants with gynecological conditions (polycystic ovarian syndrome [PCOS] and
premature ovarian insufficiency (POI), respectively). These conditions are associated with changes
in reproductive hormone levels, and thus stratified results were used. These studies may also be
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affected by reverse causality, as menstrual cyclicity is associated with both hormone levels and
these conditions, and menstrual cycle length/regularity may influence PFAS excretion (discussed
further below, see Menstrual cycle characteristics below).
Barrett, 2015, 2850382-
44
4
+
+
f+
+
4
Harlow, 2021, 8569305-
iH
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Heffernan, 2018, 5079713-
£
Jensen, 2020, 6311643-
+
-M-
"
4-
B
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Lewis, 2015, 3749030-
_
4
,
~
*
Multiple judgments exist
Liu, 2020, 6569227 -
~
*
~
~+
*
Lopez-Espinosa, 2016, 3859832-
~+ ++
+ *
4
~+
Maisonet, 2015, 3859841 -
-*¦
+¦
+
~
~+
Mccoy, 2017, 4238432-
-
+
+4-
¦
Timmermann, 2022, 10176553-
I 4
++
-
4
-
Wang, 2021, 7404063-
+~
++
+4-
¦M-
Yang, 2022, 10176804-
4
++
+4
4
+
Yao, 2019, 5187556-
+ *
- I
-
Zhang, 2018, 5079665-
.
-
+
-
-
Zhou, 2016, 3856472-
•f
•f
+
Figure 3-78. Summary of study evaluations for epidemiology studies of female
reproductive hormones. For additional details see HAWC link. Multiple
publications of the same study: Yao et al. f2019) also includes Yao etal. (20211
Estradiol
Nine studies examined estradiol levels in association with PFHxS. In six studies of adults,
one low confidence study reported lower estradiol with higher exposure in women with premature
ovarian insufficiency (POI) ((3: -0.19 (95% CI: -0.37, -0.02)} but no change in women without POI
(Zhang etal.. 2018b). Conversely, one low confidence study reported higher estradiol with higher
exposure in adult women without PCOS (p: 223, SE 255), although this was not statistically
significant, and no change was observed in women with PCOS fHeffernan et al.. 20181. In both of
these studies, the results in controls (without POI or PCOS) are more straightforward to interpret
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
since the presence of these conditions may influence hormones levels and as discussed below, PFAS
levels. The remaining studies of adults, all medium confidence, including one in healthy non-
pregnant women fBarrettetal.. 20151. one in pregnant women fYang etal.. 2022bl. one in
premenopausal (or transitioning to menopause) women fHarlow et al.. 2 0211. and one in
postmenopausal women fWang etal.. 2021bl. reported no association. In younger populations, a
single low confidence study of adolescents reported no association fZhou etal.. 20161. while a
single low confidence study of children fLopez-Espinosa et al.. 20161 reported higher ln-estradiol
levels with higher PFHxS (2.1% difference (95% CI: -2.2, 6.5)). Lastly, in one medium confidence
study of infants (Yao etal.. 20191. there was higher estradiol with higher PFHxS ((3: 0.30 (95% CI:
0.27, 0.37)). Overall, there are three studies reporting higher estradiol (one statistically significant)
in at least one subpopulation, one study reporting lower estradiol, and five studies reporting no
association with PFHxS exposure. There was no apparent pattern of association by study
confidence or study sensitivity ratings/exposure levels and contrast, and thus these inconsistent
results are difficult to interpret
Testosterone
As described above, most studies were low confidence for testosterone. In adult women, there were
five studies available, all low confidence except Harlow et al. f20211. Two of these reported
nonstatistically significant inverse associations between testosterone and PFHxS exposure. Lewis et
al. (20151 reported results stratified by age group and observed stronger associations in lower ages
((3 (95% CI) for 20-<40: -3.3 (-8.7, 2.5), 40-<60: -2.4 (-8.7, 4.3), 60-80: -0.2 (-8.3, 8.7). Zhang et
al. (2018b). also reported an inverse association in controls without POI ((3 -0.11, 95% CI: -0.27,
0.05). In contrast, Heffernan et al. (20181 reported a statistically significant positive association in
controls without PCOS ((3 0.50, SE 0.17). Studies in pre- and post-menopausal women reported no
association fHarlowetal.. 2021: Wang etal.. 2021bl. In adolescents, three studies were available.
Maisonet et al. f20151. a medium confidence study, reported higher testosterone levels in 15-year-
old girls with the increasing tertiles of PFHxS exposure, although there was no apparent exposure-
response gradient across the narrow tertiles (1.3-1.9 ng/mL ((3: 0.18 (95% CI: 0.00,0.37), and
>1.9ng/mL ((3: 0.18 (95% CI: 0.00, 0.35) compared with <1.2ng/mL PFHxS). Lewis etal. (20151
reported an inverse association ((3 -5.3, 95% CI: -11.6,1.5) (with median exposure of 0.8 ng/mL)
while Zhou etal. f20161 reported no association (with mean PFHxS exposure of 1.2 ng/mL). One
low confidence study in children reported no association with testosterone fLopez-Espinosa et al..
20161 with median exposure of 7 ng/mL, and one low confidence study in infants fYao etal.. 20191
reported an inverse association ((3 = -0.16 (95% CI: -0.36, 0.04) with median exposure of 0.3
ng/mL.
Overall, there are three of ten studies reporting inverse associations between testosterone
and PFHxS exposure, including two of five studies in adults, one of three studies in adolescents, zero
of one study in children, and one of one study in infants. In addition, one study in adults reported a
positive association. There was no apparent pattern of association by exposure levels. The study
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with the highest exposure levels and greatest contrast (Lopez-Espinosa etal.. 20161 reported no
association, while inverse associations were observed in studies with narrow contrast (Yao etal..
2019: Zhang etal.. 2018bl. although not statistically significant
Other hormones and related molecules
For other hormones and related molecules, Lopez-Espinosa etal. f20161 examined
associations between PFHxS and IGF-1, reporting inverse, although nonmonotonic in categorical
analyses, associations. Sex hormone-binding globulin (SHBG) was not associated with PFHxS levels
in four studies (Harlow etal.. 2021: Wang etal.. 2021b: Heffernan etal.. 2018: Maisonetetal..
20151. Barrett etal. T20151 observed no evidence of association with luteal phase progesterone in
saliva in normally cycling women, while in infants, Liu etal. f2020bl reported a small but not
statistically significant positive association (2.8% increase) with progesterone. Zhang etal. f2018bl
reported positive associations with FSH ((3 0.16, 95% CI: 0.04, 0.28) and prolactin ((3 0.11, 95% CI:
-0.01, 0.22) in women with premature ovarian sufficiency, but no association in controls, while
Harlow etal. (20211 reported an inverse association with FSH only in nulliparous women (-4.62,
95% CI; -8.60, -0.47). InTensen etal. (2020b). there were positive associations (p > 0.05) with LH,
androstenedione, and DHEAS in infant girls. Lastly, Timmermann etal. f20221 reported a
statistically non-significant inverse association with prolactin in pregnant women at gestational
week 10 (3.1% decrease) but no difference at gestational week 28.
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Campbell, 2016, 3860110-
Carwile, 2021. 9959594 -
Christensen, 2011, 1290803-
Crawford, 2017, 3859813-
Ding, 2022, 10273297-
Ernst, 2019, 5080529-1
Hammarstrand S et al. 2021 •
Louis, 2012, 1597490
Singer, 2018, 5079732-
Vagi, 2014, 2718073-
Wang, 2017, 3856459
Wise, 2022, 9959470 -
Zhang, 2018, 5079665-
Zhou, 2017, 3859799-1
+4
4
*4-
4
4
4
44
4
4
4
4-
+
4
4
4
4-
4
+
4
+
4
4
4
4
4
4
+
+
4
4
4-
4-
4
0
4
-¥
+
¥
44
44
-
4
4
-
4
-
4
H
~
4
¦
4
-
4
-
-
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4
"
+
-
-
4
+
4
-
+
~
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*
-
-
+
4
+•
-
44
4
4
4
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•
Legend
I Good (metric) or High confidence (overall)
+ I Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-79. Summary of study evaluation for epidemiology studies of other
female reproductive effects (menstrual cycle characteristics, gynecological
conditions, ovarian reserve, and pubertal development). For additional details
see HAWC link.
Menstrual cycle characteristics
1 Three epidemiology studies report on the association between PFHxS exposure and
2 menstrual cycle characteristics. One was a pregnancy cohort in Norway (Singer etal.. 20181. one
3 was a cross-sectional study of participants in a preconception cohort in China (Zhou etal.. 2017a).
4 and one was a cross-sectional study of reproductive aged Black women in the U.S. (Wise etal..
5 20221. For this outcome, there is potential for reverse causation because menstruation is one of the
6 mechanisms by which PFAS are removed from the body. It is expected that a longer cycle would
7 result in less clearance of PFAS, and therefore higher PFAS in the body, possibly resulting in inflated
8 effect estimates. Thus, all three studies were considered low confidence (see Figure 3-58], There
9 were also concerns for potential outcome misclassification due to self-report, since the
10 questionnaires used were not validated. Zhou et al. (2 017a) reported an increase in odds of
11 irregular and long cycle (OR (95% CI) for continuous exposure = 1.80 (1.17,2.77) and 1.73
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(1.13,2.65), respectively), and a decrease in the odds of menorrhagia (OR = 0.14 (0.06,0.36). Singer
etal. (2018) also reported higher PFHxS levels in participants with irregular (4% change, 95% CI:
-3,11) and long cycles (5% change, 95% CI; -4,14), although neither was statistically significant.
Wise etal. f20221 reported lower intensity of menstrual bleed with higher exposure, but no
difference in bleed length in days. These associations with irregular and long cycles in two studies
and lower bleeding in one study is consistent with either a true association or reverse causation
due to less PFAS excretion through menstruation compared to women with regular cycles, and it is
difficult to interpret with currently available evidence.
Gynecological conditions
Four epidemiology studies report on the association between PFHxS exposure and
endometriosis. Three of the studies were cross-sectional, which decreases confidence for this
chronic outcome due to the inability to establish temporality fBuck Louis etal.. 2018: Wang etal..
2017: Campbell etal.. 2016). There is potential for reverse causality as described above since
endometriosis can influence the menstrual cycle, and this could be toward a protective direction
given that endometriosis can be associated with heavier and more frequent bleeding. Because of
this issue, these studies were classified low confidence, although the study by Buck Louis et al.
f20181 is considered stronger in other study design aspects than the remaining two studies; this
study included two groups of women, one group scheduled for surgery (laparoscopy or
laparotomy), and one group identified through a population database who underwent pelvic MRI to
identify endometriosis (Buck Louis etal.. 2018) (see Figure 3-79). The remaining two studies were
deficient for outcome ascertainment, specifically due to self-report of endometriosis diagnosis
(Campbell et al.. 2016) and case definition including only endometriosis-related infertility among
surgically confirmed cases fWang etal.. 20171. Both of these methods are likely to include
asymptomatic cases among the controls. In addition, one study that reported results only on a
mixture of PFAS was determined to meet the PECO criteria due to very high exposure to PFHxS in
participants. Hammarstrand etal. (2021) examines a population in Ronneby, Sweden with high
PFAS contamination in drinking water. This study estimated exposure using residence location
linked to data on the municipal water supply (validated against serum measurements in a
subsample) and was thus not able to develop individual PFAS estimates. PFHxS and PFOS were
predominant in this population (subsample mean serum levels in participants living in the area at
the time of high contamination were 243 and 279, respectively, compared to 15 for PFOA), so any
effect observed can likely be largely attributed to those PFAS, but it is not possible to separate their
effects, and thus the study is considered low confidence.
Two of the low confidence studies, including the Buck Louis etal. (2018) study, reported
slightly increased odds of endometriosis with higher exposure, although the estimates were
imprecise (Buck Louis etal. (2018): operative sample OR: 1.14 (95% CI: 0.58,2.24); population
sample OR: 1.52 (95% CI: 0.40,5.80); Campbell etal. C20161 OR (95%) versus Tl: T2: 0.66
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(0.37,1.19), T3: 0.47 (0.25,0.87)). Hammarstrand etal. (2021) found no association with
endometriosis despite the very high exposure to PFHxS and PFOS.
In addition, two studies examined PCOS and PFHxS exposure, including the study in
Ronneby, Sweden fHammar strand etal.. 20211 described above and a case-control study in the U.S.
fVagi etal.. 20141. Vagi etal. f20141 suffers from potential for reverse causality due to association
with menstruation, similar to the studies of endometriosis. Because PCOS is associated with
irregular menstruation and thus less frequent bleeding, it is possible that effect estimates will be
inflated. This study is low confidence for this reason and concerns with participant selection and
confounding. There was no association between PFHxS and PCOS, but due to the study limitations,
this is difficult to interpret Hammarstrand etal. f20211 reported higher odds of PCOS in
participants with the highest exposure (HR: 2.18, 95% CI: 1.43, 3.34), but this is also difficultto
interpret due to the co-exposure with PFOS.
Ovarian reserve
Three studies examined the association between PFHxS exposure and ovarian reserve, an
indication of a woman's egg count or remaining reproductive potential. The available studies were
two medium confidence studies, a cohort fCrawford etal.. 20171 and a nested case-control study
fDonlev etal.. 20191. examining anti-Mullerian hormone (AMH), and a low confidence case-control
study examining POI fZhang et al.. 2018bl. AMH is commonly used as an endocrine marker for age-
related decline of ovarian reserve in healthy women, with reduced AMH an indication of small
primordial follicle pool, as well as predicting poor oocyte yield for in vitro fertilization (Grvnnerup
etal.. 2012). However, a single measurement in healthy women may not be informative in
predicting fecundity (ACOG. 2019) and, as mentioned above, elevated levels of AMH are associated
with PCOS, so these results should be interpreted with caution. In contrast to AMH, POI is a more
specific outcome (defined as an elevated FSH level greater than 25 IU/L on two occasions more
than four weeks apart and oligo/amenorrhea for at least four months in Zhang etal. f2018bl. but
because this definition is closely tied to menstruation, there are concerns for reverse causality as
with the previous outcomes, which would be expected to be biased away from the null. In Zhang et
al. (2018b). there were higher odds of POI with higher exposure, with an exposure-response
gradient across tertiles (OR (95% CI) versus tertile 1: T2: 2.04 (1.03, 4.04), T3: 6.63 (3.22,13.65)).
In Crawford et al. f20171. there was an inverse association between AMH and PFHxS, consistent
with decreased ovarian reserve, although this was not statistically significant ((3: -0.12, p = 0.4). No
association was observed with AMH in Donley etal. f20191. despite similar exposure contrast
(median 1.6 ng/mL) in the two AMH studies and lower exposure levels in Zhang etal. (2018b). The
results of Zhang etal. (2018b) and Crawford et al. (2017) are coherent with each other as well as
with the positive association with FSH observed in women with POI in Zhang etal. (2018b).
although no association was observed in control women without POI (discussed with reproductive
hormones). Overall, due to the study limitations and small number of studies, there is still
considerable uncertainty.
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Pubertal development
Three medium confidence studies, including birth cohorts in Denmark fErnstetal.. 20191
and the U.S. fCarwile etal.. 20211 and a case-control study nested in a birth cohort in the United
Kingdom fChristensen etal.. 20111. and low confidence cross-sectional study in the U.S. fWise etal..
20221 examined timing of pubertal development with prenatal PFHxS exposure. Ernst etal. T20191
and Carwile etal. (20211 reported results for several pubertal outcome measures, while
Christensen etal. (20111 and Wise etal. (20221 focused on age at menarche. In Ernst etal. (20191.
with median exposure of 1.1 ng/mL (10th-90th percentile: 0.6-1.7), the participants in the third
tertile of exposure had earlier age of breast development, axillary hair, and menarche, although
none were statistically significant Looking at a combined puberty indicator outcome, there was
lower age at puberty in the third tertile (age difference -2.22 months; 95% CI: -8.37, 3.93). Carwile
etal. f20211. with median exposure of 1.9 ng/mL, reported no association with pubertal
development score or peak height velocity (i.e., the age at which a child experiences the largest
increase in height, a proxy for pubertal timing). In Christensen etal. (20111. with median exposure
of 1.5 ng/mL (IQR 0.5-0.8), there was not a clear association, as there were higher odds of earlier
age at menarche when PFHxS was analyzed as dichotomous based on above/below the median (OR
1.11; 95% CI: 0.76,1.64) but lower odds when analyzed as continuous (OR 0.89; 95% CI: 0.65,
1.22), neither statistically significant. Lastly, the low confidence study found no association with age
at menarch (Wise etal.. 20221. Overall, there is considerable uncertainty for this outcome given the
inconsistency in three medium confidence studies and imprecision of the effect estimates.
Menopause
One medium confidence study, a cohort of midlife women in the U.S., examined timing of
menopause fDing etal.. 20221. The effect estimate is in the direction of earlier onset of natural
menopause, though not statistically significant, (relative survival: 0.90, 95% CI: 0.76,1.05 for total
effect (including author-proposed mediation by FSH)).
Animal Studies
The database of animal toxicity studies for PFHxS-induced female reproductive effects
consists of five oral exposure studies that include two short-term studies in Harlan Sprague Dawley
or Crl:CD BR rats exposed for 28 days fNTP. 2018a: 3M. 2000bl. two reproductive/developmental
toxicity studies in Crl:CD (SD) rats or Crl:CDl (ICR) mice with exposures starting during premating
through postnatal days (PND) 22-35 f Chang etal.. 2018: Bute nhoff etal.. 2009: 3M. 20031 and a
developmental toxicity study in Wistar rats with exposure during gestion and lactation (gestational
days [GD] 7 to PND 22) (Ramh0i etal.. 20181. The studies evaluated several endpoints relevant to
the assessment of female reproductive toxicity, namely mating and fertility, estrous cycle, hormone
levels, histopathology, organ weight and markers of sexual differentiation and maturation fU.S.
EPA. 19961. Other developmental outcomes reported in the Ramhai etal. f20181 study are
described in the synthesis of developmental effects (see Section 3.2.3).
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Mating and fertility
Mating and fertility measures (i.e., fertility index, mating index and pre-coital interval) were
evaluated across two high confidence studies with no outstanding issues regarding risk of bias or
sensitivity (see Figure 3-80}. The studies exposed F0 female SD rats or CD-I mice to doses ranging
from 3 to 10 mg/kg-day during premating, gestation, and lactation (PND 22) fChang etal.. 2018:
Butenhoff et al.. 2009: 3M. 2003). No treatment-related effects were noted in mating and fertility
indices, including length of pre-coital interval in female parental animals.
Reporting quality
Allocation
Observational bias/blinding
Confounding/variable control
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Results presentation
Endpoint sensitivity and specificity •
Overall confidence
!«
-H-
-
*
NR
NR
4-+
4-+
4-+
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Unlnformative (overall)
Not reported
Figure 3-80. PFHxS mating and fertility animal study evaluation heatmap. For
additional details see HAWC link.
Estrous cycle characteristics
Effects on the estrous cycle were measured in four studies: a short-term study in rats
exposed for 28 days (NTP, 2018a) and two reproductive-developmental toxicity studies in F0 rats
or mice exposed during premating gestation, and lactation (PND 22) (Chang etal.. 2018: Butenhoff
etai, 2009: 3M. 2003). and one sub-chronic study that exposed ICR mice for 42 days (Yin et al..
2021) (see Figure 3-81). Two of the studies were considered high confidence fNTP. 2018a:
Butenhoffetal.. 2009: 3M. 20031 and two were considered medium confidence because of
uncertainties surrounding presentation of results and selection of animals for outcome assessment
fYin et al.. 2021: Chang etal.. 20181 (see Figure 3-81). Yin etal. f20211 reported decreased
increased estrous cycle duration in treated animals, but the remaining studies which evaluated this
outcome report that PFHxS exposure had no effects in the number of cycles, cycle length, or time in
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each estrous stage (proestrus, estrus, metestrus, and diestrus) of female rats or mice exposed to
doses of 0.3-50 mg/kg-day and 0.3-3 mg/kg-day, respectively fChang et al.. 2018: NTP. 2018a:
Butenhoffetal.. 2009: 3M. 20031.
Reporting quality -
*+ ~+
a
Allocation -
+
*
+
I
Observational bias/blinding -
NR
NR 1
~t
NR
Confounding/variable control -
H
Selective reporting and attrition -
~•f
tt
-
Chemical administration and characterization -
++
*+
+
Exposure timing, frequency and duration -
++
H
Results presentation -
++-
D
++
Endpoint sensitivity and specificity -
++
Overall confidence -
Dl
++
H
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Not reported
~ Multiple judgments exist
Figure 3-81. PFHxS estrous cycle animal study evaluation heatmap. For
additional details see HAWC link.
Hormone levels
The available studies have measured reproductive hormones including testosterone, follicle
stimulating hormone (FSH), Luteinizing hormone (LH), and estrogen. Serum testosterone levels
were measured in female rats in a single short-term high confidence study with no notable
concerns in any of the study evaluation domains (NTP. 2018al (see Figure 3-82). Female rats were
exposed to 0, 3.12, 6.25,12.5, 25, and 50 mg/kg-day PFHxS for 28 days. Serum testosterone levels
were slightly increased in PFHxS-exposed rats at all doses (9%-29% compared with controls) but
the changes were not statistically significant compared with controls and did not display a dose-
response gradient A medium confidence study using ICR mice reported that exposure to 5 mg/kg-
day PFHxS decreased serum FSH, LH, and estrogen (Tin etal.. 20211. These observations suggest
that PFHxS exposure may alter reproductive hormones in exposed female animals, however several
issues were identified with the Yin etal. f20211 study including lack of randomization and selective
reporting. Therefore, additional studies are needed.
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Reporting quality
Allocation
Observational bias/blinding
Legend
Chemical administration and characterization
Selective reporting and attrition
Confounding/variable control
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Not reported
Exposure timing, frequency and duration
Results presentation
Endpoint sensitivity and specificity
Overall confidence
Figure 3-82. PFHxS hormone levels animal study evaluation heatmap. For
additional details see HAWC link.
Histopathologv
Histopathology of female reproductive organs including the ovary, uterus, vagina, and
clitoral and mammary glands were examined across four studies. Two short-term studies in rats
exposed for 28 days fNTP. 2018a: 3M. 2000b] and two reproductive-developmental toxicity studies
in F0 rats or mice exposed from 14 days of premating to PND 22 (Chang et al.. 2018: Butenhoff et
al.. 2009: 3M. 20031. Three of the studies were considered high confidence fNTP. 2018a: Butenhoff
etai, 2009: 3M. 2003. 2000b) and one was rated as medium confidence due to deficiencies in the
presentation of histopathological findings (data were only reported qualitatively) fChanget al..
20181 (see Figure 3-83).
Bilateral dilation of the uterus (minimal to mild severity) was reported in rats in the control
(1/10 rats) and PFHxS exposure groups (1/1,1/1, 3/3, and 1/10 rats at 3.12, 6.25,12.5, and 50
mg/kg-day, respectively) in the NTP f 2018a study. Although lesions were observed in 100% of the
animals evaluated in the 12.5 mg/kg-day dose group, the incidence rates were identical for the
control and high dose groups (10%) and a limited number of animals were examined in the other
exposure groups; therefore, the biological interpretation of these findings is unclear. Butenhoff et
al. f20091 and 3M f20031 also observed uterine lesions in rats (mild-moderate distention and
microphage infiltration of mostly moderate severity) but the incidence rates were not significantly
different between control and PFHxS exposure (10 mg/kg-day). Two medium confidence mouse
studies report conflicting evidence. Chang etal. (20181 reported no lesions in the uterus of CD-I
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mice exposed to 10 mg/kg-day PFHxS for 42 days fChang etal.. 20181 However, a similar study
also using CD-I mice exposed to 5 mg/kg-day PFHxS for 42 days reported decreased number of
secondary follicles and corpora lutea, but no effect on primordial or primary follicles fYin etal..
20211. A single case of minimal focal necrosis was reported in the mammary gland of rats (1/10) at
a dose of 10 mg/kg-day fButenhoff et al.. 2009: 3M. 20031 but no lesions were observed in the
mammary gland of rats exposed to doses ranging from 3.12-50 mg/kg-day in a different study
(NTP. 2018al. Histological examination of the ovaries (including primordial follicle counts), clitoral
gland and vagina showed no treatment-related effects in exposed rats or mice (Chang etal.. 2018:
NTP. 2018a: Butenhoff et al- 2009: 3M.2003. 2000b).
^
Reporting quality
Allocation
Observational bias/blinding-* NR NR
Confounding/variable control
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Results presentation
Endpoint sensitivity and specificity
Overall confidence
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
NRj Not reported
Figure 3-83. PFHxS female reproductive histopathology animal study
evaluation heatmap. For additional details see HAWC link-
Organ weight
There are six available animal toxicity studies that evaluated effects on reproductive organ
weights in females (i.e., ovary and uterus). One study exposed CD-I mice for 42 days fYin etal..
20211. two studies exposed SD rats for 28 days fNTP. 2018a: 3M, 2000bl and three reproductive-
developmental toxicity studies examining effects in F0 rats and mice exposed during premating
and/or gestation and lactation (PND 22) fChang etal.. 2018: Rarnheii etal.. 2018: Butenhoff et al..
2009: 3M. 20031 and in F1 mice exposed in utero, via lactation and directly from PND 22 to PND 35
fChang etal.. 20181. Overall study confidence was medium in the Chang etal. f20181 study due to
incomplete reporting of organ weight data (quantitati ve results were not provided) (see Figure 3-
84). The study by Yin etal. (20211 was also considered medium confidence due to concerns related
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to animal selection for outcome assessment There were no major concerns with respect to risk of
bias or sensitivity in the other studies deemed as high confidence fNTP, 2018a: Ramh0i etal.. 2016:
Butenhoffetal.. 2009: 3M. 2003. 2000bl. Yin et al. f20211 reported decreased absolute (but not
relative) ovary weight in animals exposed to 50 mg/kg-day for 42 days. However, in all other
available studies PFHxS exposure did not significantly impact ovarian and uterine weights (both
absolute and relative] in animals at doses ranging from 0.05-50 mg/kg-day in any of the studies
(Chang et al.. 2018: NTP. 2016a: Ramh0i etal.. 2018: Butenhoff et al.. 2009: 3M. 2003. 2000bl.
Reporting quality A
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Results presentation
Endpoint sensitivity and specificity
Overall confidence
*
*
NR
NR
Legend
I Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
1 Deficient (metric) or Low confidence (overall)
I Critically deficient (metric) or Uninformative (overall)
|NR Not reported
Figure 3-84. PFHxS female reproductive organ weight animal study evaluation
heatmap. For additional details see HAWC link.
Landmarks of female reproductive system development and maturation
Markers of sexual differentiation and maturation, namely anogenital distance (AGD)27 and
onset of puberty (vaginal patency], were evaluated in F1 offspring in two reproductive-
developmental toxicity studies of medium confidence in rats exposed during gestion to PND 22
(Ramh0i etal.. 2018) or in mice exposed in utero, via lactation and directly from PND 22 to PND 35
(Chang et al.. 2018). Key issues related to animal allocation and presentation of results for AGD (no
adjustment for body weightZ8) reduced confidence in one study fRamhai et al.. 20181 (see Figure 3-
85). Ambiguity surrounding the reporting of sample size raised potential concerns in the second
study fChangetal.. 20181.
27AGD is a phenotypical marker of androgen levels during gestational development (Thankamonv et al..
20161. Increased AGD in considered indicative of an adverse response in the developing female reproductive
system fU.S. EPA. 19961.
28Relative AGD adjusted to the cube root of body weight is the preferred measurement for this endpoint
(Daston and Kimmel. 1998).
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Statistically significant reductions in relative AGD (adjusted to body weight) evaluated on
PND 1 were noted in F1 mice exposed to 1 mg/kg-day (5% compared with controls) but the effects
were not seen at other dose levels (0.3 and 3 mg/kg-day) (Chang etal.. 20181. Furthermore,
absolute AGD was unaffected by treatment in F1 mice or rats up to doses of 45 mg/kg-day (Chang
etal.. 2018: Ramh0i etal.. 20181. Similarly, PFHxS had no effect on the onset of puberty (vaginal
patency) in F1 mice exposed to doses of 0.3-3 mg/kg-day.
Reporting quality -
-M- -t-f-
Allocation -
~
+
Observational bias/blinding -
NR
NR
Confounding/variable control -
++¦
Selective reporting and attrition -
Exposure timing, frequency and duration
Endpoint sensitivity and specificity
Results presentation -
Overall confidence-
Legend
| Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall]
Not reported
Figure 3-85. PFHxS female reproductive sexual differentiation and maturation
animal study evaluation heatmap. For additional details see HAWC link.
Evidence Integration
The available studies provide inadequate evidence to determine whether PFHxS exposure
has the potential to affect female reproduction in humans. This conclusion is based on studies in
both humans and animals (see Table 3-39).
The available evidence on PFHxS-induced female reproductive effects in human studies is
considered indeterminate. Outcomes evaluated in human studies include fecundity, reproductive
hormones, pubertal development, menstrual cycle characteristics, gynecological conditions, and
ovarian reserve. Associations were observed with many of these outcomes in some studies, but
there was considerable inconsistency across studies within outcomes and uncertainty due to
considerations such as reverse causality and confounding (e.g., parity for fecundity) that reduced
study confidence. Looking across outcomes, there is some coherence. The observed increase in
estradiol and FSH and decrease in testosterone in some studies (one study for FSH) is coherent
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with risk factors for endometriosis, which in turn is coherent with reduced ovarian reserve and
fecundity. Similarly, the decrease in anogenital distance in one study of newborn girls (see
Developmental Effects Section) is coherent with the decrease is testosterone levels in some of the
studies, including the single study in infants. These connections between the outcomes increase the
strength of the evidence, but because of the limitations described above, there is too much
uncertainty in the association to draw a stronger judgment than indeterminate.
The available animal evidence on PFHxS-induced female reproductive effects is also
considered indeterminate. One medium confidence, study using mice reported PFHxS-induced
alterations in estrus cycle, histopathology, ovary weight, and reproductive hormone levels (Yin et
al.. 20211. In all other medium and high confidence studies there were no clear exposure-related
effects were observed in reproductive organ weights, estrous cycle characteristics, histopathology,
reproductive hormones levels, and functional measures of mating and fertility. In addition to the
inconsistencies between the Yin, 2021, 9960589@@author-year and the other available studies
there are no subchronic or chronic exposure studies available, which also limits the interpretation
of the current findings.
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Table 3-39. Evidence profile table for PFHxS exposure and female reproductive effects
Evidence stream summary and interpretation
Evidence
integration
summary
judgment
Evidence from studies of exposed humans
ooo
Evidence inadequate
Primary Basis:
Evidence is
inconsistent across
studies or largely
null.
Human relevance:
Without evidence to
the contrary, effects
in rodent models are
considered relevant
to humans.
Cross-stream
coherence'. N/A,
evidence
indeterminate for
both human and
animal studies.
Susceptible
populations and
lifestages:
None identified.
Studies and confidence
Factors that increase
certainty
Factors that decrease certainty
Summary and key findings
Evidence stream
judgment
Fecundity
3 medium and 5 low
confidence studies
• No factors noted
• Unexplained inconsistency
• High risk of bias
Decreased fecundity/longer time
to pregnancy in 2 low confidence
studies, but no effect in medium
confidence studies.
QQQ
Indeterminate
Associations
between exposure
and female
reproductive
outcomes observed
in studies of
multiple outcomes.
Inconsistency across
studies and
concerns for reverse
causality and other
bias hinder
interpretation.
Reproductive hormones
7 medium and 7 low
confidence studies
• No factors noted
• Unexplained inconsistency
• High risk of bias -Most
testosterone studies were low
confidence
3 of 9 studies report higher
estradiol. 3 of 9 studies report
lower testosterone.
Pubertal development
3 medium and 2 low
confidence studies
• No factors noted
• Unexplained inconsistency
Earlier age of puberty (not
statistically significant) in one
study, but no clear association in
other studies
Menstrual cycle
3 low confidence studies
• Consistency
• Low confidence studies-
potential reverse causality
Higher odds of irregular and long
cycle in 2 studies, lower odds of
menorrhagia in 1 study, and less
intense bleeding in one study
Gynecological conditions
5 low confidence studies
• No factors noted
• Unexplained inconsistency
• All low confidence studies-
potential reverse causality
• Imprecision of effect estimate
Higher odds of endometriosis in 2
of 4 studies. Lower odds of
endometriosis-related infertility
in one study. 1 of 2 studies
reported higher likelihood of
PCOS, but there is potential for
confounding by PFOS.
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Evidence stream summary and interpretation
Evidence
integration
summary
judgment
Ovarian reserve
2 medium and 1 low
confidence studies
• Coherence in
associations
between POI and
AMH in one study
• Potential for reverse causality
• Unexplained inconsistency
across studies of AMH
Higher odds of premature ovarian
insufficiency (POI) and lower
levels of anti-Mullerian hormones
(AMH) (in 1/2 studies)
Evidence from in vivo animal studies
Studies and confidence
Factors that increase
certainty
Factors that decrease certainty
Summary and key findings
Evidence stream
judgment
Mating and fertility
2 high confidence studies in
adult rats and mice:
• 14-d (x2)
• No factors noted
• No factors noted
No observed effects on mating or
fertility index
QQQ
Indeterminate
[Note: although no
notable findings, no
long-term studies
were available]
Estrous cycle
2 high confidence studies in
adult rats:
• 28-d
• 14-d premating to
PND22
2 medium confidence study
in adult mice:
• 14-d premating to
PND22
• 42-d
• Unexplained
inconsistency across
studies
Altered cycle duration reported in
one medium confidence study
Hormone levels
1 high confidence study in
adult rats
• 28-d
• Lack of expected dose
response
Slight increase in testosterone,
decreased estrogen, LH, and FSH
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Evidence stream summary and interpretation
Evidence
integration
summary
judgment
• 1 medium confidence
study in adult mice.
• 42-d
Histopathology
3 high confidence studies in
adult rats
• 28-d (x2)
• 14-d premating to
PND22
1 medium confidence study
• 14-d premating to
PND22
1 low confidence study
• 42-d
• Unexplained inconsistency
across studies
Decreased number of secondary
follicles and corpora lutea in 1
low confidence study
Organ weights
1 high confidence study in
adult rats
• 28-d (x2)
• 14-d premating to
PND22
3 medium confidence
studies in rats and mice
• GD7-PND22
• 14-d premating to
PND22
• Unexplained inconsistency
across studies
Decreased ovary weight reported
in 1 medium confidence study
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Evidence stream summary and interpretation
Evidence
integration
summary
judgment
• 42-d
Developmental effects
2 medium confidence
studies in rats and mice
• GD7-PND22
• GD0-PND22
No observed effects on female
reproductive organ development
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3.2.9. Male Reproductive Effects
Human Studies
Twelve epidemiology studies (reported in 15 publications) examined the association
between PFHxS exposure and male reproductive effects. The outcomes included in these studies
were semen parameters, reproductive hormones, timing of pubertal development, and anogenital
distance. These studies are described below.
Semen parameters
Semen concentration and sperm motility and morphology were considered the core
endpoints for the assessment of semen parameters. Other outcomes, such as specific sperm
morphology and motility defects, were not consistently reported across studies and were
considered secondary; these outcomes are most useful to probe into associations observed in the
core endpoints. Key issues for the assessment of semen parameters involve sample collection and
sample analysis. Samples should be collected after an abstinence period of 2-7 days, and analysis
should take place within 2 hours of collection and follow guidelines established by the World
Health Organization fWHO. 20101. While exposure would ideally be measured during the period of
spermatogenesis rather than concurrent with the outcome, a cross-sectional design is considered
adequate because the period of spermatogenesis is fairly short (<3 months) relative to the half-life
of PFHxS (years), and there is no concern for reverse causality with this outcome.
Five epidemiology studies (reported in seven publications) examined the association
between PFHxS exposure and semen quality. The evaluations for these studies are summarized in
Figure 3-65, and additional details can be obtained from HAWC. Three studies were medium
confidence: one was a cross-sectional analysis of male partners in a pregnancy cohort fToftetal..
20121 and two were cross-sectional studies of healthy young men fPetersenetal.. 2022: Toensen et
al.. 20131. The remaining two studies were low confidence due to multiple identified deficiencies
and were cross-sectional studies of men seeking infertility assessment (Huang etal.. 2019b: Song et
al.. 20181. All the studies analyzed PFHxS in serum using appropriate methods and thus exposure
misclassification is expected to be minimal.
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Huang,2019, 5406374
Joensen, 2013, 2919160
Petersen, 2022, 10273364-
Song,2018, 4220306
Toft, 2012, 1332467-
[tf*
It'",,!!!'
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-86. Semen parameters epidemiology study evaluation heatmap. For
additional details see HAWC link.
The results for the association between PFHxS exposure and semen quality in medium
confidence studies are presented in Table 3-34. The studies analyzed the outcomes differently so
the effect estimates are not directly comparable, but a negative effect estimate indicates a reduction
in sperm quality with higher exposure. There was a statistically significant and dose-dependent
decrease in normal sperm morphology in one medium confidence study fToftet al.. 20121 and an
imprecise and non-dose-dependent decrease (>10% change] in concentration in the same study
fToftet al.. 20121. A low confidence study f Huang et al.. 2019bl reported a higher concentration
(p < 0.05] and motility (p > 0.05] with PFHxS exposure. No association was reported in the other
medium fPetersen etal.. 2022: loensen etal.. 20131 or low (Song etal.. 2018] studies. Other
publications of the same study described in Toftetal. f2012] reported no clear association between
PFHxS exposure and sperm DNA damage (Leter etal.. 2014: Specht et al.. 20121. indicating that
PFHxS-induced DNA damage is unlikely to explain the decreases in the percent of sperm with
normal morphology (and the slightly decreased sperm numbers] observed in Toft etal. f201211.
Exposure levels were slightly higher in Toftetal. f20121 than loensen etal. f20131. which could
explain the differing results, but this cannot be confirmed with the currently available evidence.
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Table 3-40. Associations between PFHxS and semen sperm parameters in
medium confidence epidemiology studies
Reference
Population
Median
exposure
(IQR)
(ng/mL)
Effect
estimate
Concentration
Motility3
(%
progressively
motile)
Morphology3
(% normal)
Petersen et
al. (2022)
Cross-sectional study of
young men (2017-2019),
Denmark; 1,041 men
(18-20 yrs)
0.3 (P5-P95:
0.2-0.6)
% Change
vs. T1
T2: 0 (-12, 13)
T3: 2 (-10, 16)
T2: -7 (-12, -1)
T3: -2 (-8, 4)
T2: 1 (-10, 12)
T3: 6 (-5, 18)
Joensen et
al. (2013)
Cross-sectional study of
men evaluated for
military service (2008-
2009), Denmark; 247
men (18-22 yrs)
0.7 (0.5-0.9)
(3 (95% CI)
for 1-unit
increase
Cubic root
transformed
0.05 (-0.12,0.22)
% Immotile
Square
transformed
-2.82 (-232,227)
Square root
transformed
0.12
(-0.02,0.26)
Toft et al.
(2012)
INUENDO cohort cross-
sectional analysis (2002-
2004), Greenland,
Ukraine, Poland; 588
men
1.1
(P33-P66:
0.7-1.5)
% Change
vs. T1
(mill/ mL)
T2: -12 (-52,28)
T3: -11 (-57,35)
T2: 11 (-12,35)
T3: 10 (-18,37)
T2: -27 (-58,3)
T3: -35 (-70,-
1)*
*p < 0.05, CD: critically deficient, T: tertile.
aPercent motile in population was 37% in Petersen et al. (2022), 58% in Joensen et al. (2013), and 56%-64% in Toft
et al. (2012), varying by country. Percent normal morphology in population was 6% in Petersen et al. (2022), 7% in
Joensen et al. (2013) and 6%-7% in Toft et al. (2012).
Reproductive hormones in males
Testosterone and estradiol were considered the primary endpoints for male reproductive
hormones, although findings for LH, FSH, and SHBG were also reviewed where available. Key issues
for the evaluation of these studies were sample collection and processing. For testosterone, LH, and
FSH, blood sample collection should be performed in the morning due to diurnal variation, and if
not possible, time of collection must be accounted for in the analysis. If there is no consideration of
time of collection, the study is classified as deficient for outcome ascertainment and low confidence
overall for these hormones.
Nine studies (reported in ten publications) examined the associations between PFHxS and
male reproductive hormones. Most studies examined only testosterone and estradiol. All the
studies measured exposure and outcome concurrently which was considered appropriate since
levels of these hormones are capable of being rapidly upregulated or downregulated and they are
not expected to directly bind to or otherwise interact with circulating PFAS. Four studies (Petersen
etal.. 2022: Lewis etal.. 2015: Toensen etal.. 2013: Specht etal.. 20121 examined associations in
adults, two studies in adolescents (Zhou etal.. 2016: Lewis etal.. 20151. one study in children
(Lopez-Espinosa et al.. 20161. and three studies in infants (Tensen et al.. 2020b: Liu etal.. 2020b:
Yao etal.. 20191. The study evaluations are summarized in Figure 3-66. Four studies were rated
medium in overall study confidence f Petersen etal.. 2022: Liu etal.. 2020b: Lopez-Espinosa et al..
2016: Toensen etal.. 20131. and five were low confidence flensen et al.. 2020b: Yao etal.. 2019: Zhou
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
etai, 2016: Lewis et al, 2015: Spechtetal.. 20121. However, of the medium confidence studies, one
did not consider timing of sample collection and was thus low confidence for testosterone (Lopez-
Espinosa et al.. 20161.
Joensen, 2013, 2919160-
Lewis, 2015, 3749030-
Liu, 2020, 6569227 -
Lopez-Espinosa, 2016, 3859832-
Petersen KU et al. 2022-^^1
Specht, 2012, 1289939
Yao, 2019, 5187556
:
'
'
+
i
i
+
-
DO
-
*
~
~
>
m
+
H
*
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Multiple judgments exist
+
-f-
S
++
++
+
¦f
-
r
~
•f
+
+
~
+
+
¥
*
+
+
*
~~
++
*•
i ^ 1
-
4-
+*
*¦
+
~
r
~
~
+
-
Figure 3-87. Summary of study evaluation for epidemiology studies of male
reproductive hormones. For additional details see HAWC link.
Testosterone
As described above, most studies were low confidence for testosterone. In adult men, four
studies were available and two were low confidence. In the two medium confidence studies, both
populations of young men in Sweden floensen et al.. 20131 and Denmark fPetersen etal.. 20221. no
association was reported between PFHxS exposure and testosterone levels, at mean concentrations
of 0.7 and 0.3, respectively. Non-statistically significant inverse associations were observed in one
low confidence study of adults (Lewis etal.. 20151. and only in age groups 20 to <40 and 40 to 60 ((3
(95% CI]; for 20 to 40: -1.2 (-4.7, 2.4], for 40 to 60: -3.6 (-8.2, 1.2], and 60 to 80: 3.3 (-3.8,10.8],
The other low confidence study did not report quantitative results but stated that associations were
not consistent across countries in the study (Spechtetal.. 20121. For adolescents, one low
confidence study fLewis etal.. 20151 reported a non-statistically significant positive association (p
2.4, 95% CI: -9.1, 15.2], and the other reported no association fZhou et al.. 20161. A study in
children fLopez-Espinosa etal.. 20161 reported a non-statistically significant inverse association (p
-2.7, 95%CI: -6.4, 1.2], while two studies in infants (lensen et al.. 2020b: Yao etal.. 20191 reported
no association. Overall, there is inconsistent evidence of an association between PFHxS exposure
and testosterone. Some low confidence studies report inverse associations, but the medium
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
confidence studies reported no association. It is possible that this is due to differences in PFHxS
levels, as the medium confidence studies had exposure levels lower than the studies that observed
an association (median blood concentrations 0.3-0.7 ng/mL versus 1.3-1.8 ng/mL in Lewis et al.
f20151 and 8 ng/mL in Lopez-Espinosa etal. f201611. but given the concerns for outcome
misclassification in the low confidence studies, the results are difficult to interpret
Estradiol
Six studies examined associations between PFHxS exposure and estradiol in male subjects.
Among the three medium confidence studies (Petersen etal.. 2022: Lopez-Espinosa et al.. 2016:
Toensen etal.. 20131 reported no association between increasing PFHxS exposure and estradiol.
Results across the low confidence studies are mixed, as Zhou etal. f 20161 reported higher estradiol
levels with higher PFHxS exposure, while Spechtetal. f20121 reported that estradiol levels were
not consistently associated with PFHxS across countries with no data shown and Yao etal. f20191
reported no association.
Other reproductive hormones
For other reproductive hormones, SHBG was not associated with PFHxS levels in Spechtet
al. f20121. Toensen etal. f20131. or Petersen et al. f20221. FSH and LH were not associated with
PFHxS in Toensen etal. f20131 or Petersen etal. f20221 and associations were not consistent across
regions in Spechtetal. f20121. In Tensenetal. f2020bl. positive butnonstatistically significant
associations were reported with LH, dehyroepiandosterone (DHEA), dehydroepiandrosterone-
sulfate (DHEAS), androstenedione, and 17-hydroxyprogesterone (17-OHP). Liu etal. (202Obi
reported a small but not statistically significant positive association (2.7% increase) with
progesterone in infants.
Overall, there is little evidence of an association between PFHxS exposure and male
reproductive hormones, but there are limitations in the available evidence that hinder
interpretation of the null findings.
Pubertal development
Two medium confidence studies, birth cohorts in Denmark (Ernst etal.. 20191 and the U.S.
fCarwile etal.. 20211. examined timing of pubertal development with PFHxS exposure. Ernst et al.
f20191 used maternal exposure (median 1.1 ng/mL, 10th-90th percentile: 0.6-1.7) while Carwile et
al. f20211 used childhood exposure at around 8 years of age. One study reported that the
participants in the third tertile of exposure had earlier genital development, pubic hair, axillary
hair, acne, voice break, and first ejaculation, with axillary hair acne, and voice break being
statistically significant Looking at a combined puberty indicator outcome, there was lower age of
puberty in the third tertile (age difference -6.89 (95% CI: -12.57, -1.20)) (Ernst etal.. 20191. The
second study reported no association between PFHxS exposure and a pubertal development score
or age at peak height velocity fCarwile etal.. 20211.
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Summary of human studies on male reproductive effects
Overall, there is some limited evidence of an association between PFHxS exposure and
sperm motility, timing of pubertal development, and anogenital distance, but there is considerable
uncertainty in the available data due to lack of consistency across the studies on each outcome and
lack of coherence with reproductive hormones.
Animal Studies
The database of animal toxicity studies on PFHxS-induced male reproductive effects
consists of five oral exposure studies that include two short-term studies in Harlan Sprague Dawley
rats exposed for 28 days fNTP. 2018c: 3M. 2000bl. two multigeneration reproduction studies in
Crl:CD (SD) rats or Crl:CDl (ICR) mice with exposures starting during 2-week premating through
postnatal days (PND) 22-35 fChang etal.. 2018: Butenhoff etal.. 20091 and a single-generation
reproduction study in Wistar rats with exposure during gestation and lactation (gestational days
[GD] 7 to PND 22) (Ramh0i etal.. 2018). The studies evaluated several endpoints relevant to the
assessment of male reproductive toxicity, namely mating and fertility, sperm measures, hormone
levels, histopathology, organ weights, and morphological markers of sexual differentiation and
maturation fU.S. EPA. 19961.
Sperm parameters
Sperm measures (count, motility, morphology, concentration, and production rate) were
evaluated in three low confidence studies that exposed animals for 28 or 44 days (see Figure 3-88).
In SD rats, exposure to PFHxS for 28 days did not impact sperm count, spermatid count, or sperm
motility. Additionally, Butenhoff et al. f20091. 3M f20031 and Chang etal. f 20181 did not observe
PFHxS-induced alterations in sperm motility, morphology, or concentration after exposing SD rats
or CD-I mice for 44 and 42 days respectively. Overall, these results suggest that PFHxS exposure
does not affect sperm measures. However, these findings should be interpreted with caution as the
available studies were of low confidence due to experimental design features that may have
resulted in reduced sensitivity and a potential bias toward the null29
29In rodent models such as the rat it takes approximately eight weeks for spermatogonia to develop to
spermatozoa fFoster and Gray. 20131. Damage to the spermatogonial cells would not be detected in ejaculate
or cauda epididymis samples from animals exposed for periods that are shorter than eight weeks fU.S. EPA.
19961.
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Reporting quality
mm
Allocation -
*
,
m
Observational bias/blinding -
NR
NR
+4
Confounding/variable control -
*4
Selective reporting and attrition -
•M-
-M-
Chemical administration and characterization -
++
H
•M-
Exposure timing, frequency and duration -
Endpoint sensitivity and specificity -
Results presentation -
+~
+-*•
_
Overall confidence
Li
Legend
| Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
B Critically deficient (metric) or Uninformative (overall'
NR| Not reported
Figure 3-88. Male reproductive animal study evaluation heatmap - sperm
measures. For additional details see HAWC link.
Histopathologv
1 Histopathology of male reproductive organs was evaluated in two high confidence studies
2 and one medium confidence study (see Figure 3-89). In SD rats, exposure to PFHxS for 28 to 44 days
3 at doses ranging from 0.3 to 10 mg/kg-day did not affect the histopathology of the testes, preputial
4 glands, epididymis, or seminal vesicles fNTP. 2018c: Butenhoffetal. 2009: 3M. 2003. 2000bl.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Reporting quality
Allocation
Observational bias/blinding
Confounding/variable control
Selective reporting and attrition
Chemical administration and characterization
Exposure timing, frequency and duration
Endpoint sensitivity and specificity
Results presentation
Overall confidence
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (melric) or Uninformative (overall]
MR, Not reported
Figure 3-90. Male reproductive animal study evaluation heatmap -
reproductive hormones. For additional details see HAWC link.
Organ weights
1 Potential PFHxS-induced effects on male reproductive organ weights were evaluated in
2 three high confidence studies using SD rats fNTP. 2018c: Butenhoff et al.. 2009: 3M. 2003. 2000b)
3 and one medium confidence study using Wistar rats fRamhdi etal.. 20181 (see Figure 3-91). In SD
4 rats, exposure to PFHxS for 28 to 44 days at doses ranging from 0.3 to 10 mg/kg-day did not affect
5 the weights of the testis, epididymis, or seminal vesicle fNTP. 2018c: Butenhoff etal.. 2009: 3M.
6 2003. 2000bl. Furthermore, gestational plus lactational exposure to PFHxS (0.05 to 25 mg/kg-day)
7 also did not affect organ weights for epididymis, ventral prostrates, seminal vesicles, levator ani, or
8 testes in Wistar rats fRamhai etal.. 20181.
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Reporting quality -
Allocation -
Observational bias/blinding
Confounding/variable control -
Selective reporting and attrition -
Chemical administration and characterization
Exposure timing, frequency and duration
Endpoint sensitivity and specificity
Results presentation
Overall confidence
I Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall
NRj Not reported
Figure 3-91. Male reproductive animal study evaluation heatmap -
reproductive organ weights. For additional details see HAWC link.
Landmarks of male reproductive system development and maturation
1 One medium confidence gestational exposure study evaluated PFHxS-induced effects on
2 androgen sensitive developmental landmarks in F1 Wistar rats (Ramhgjj etal.. 20181. Gestational
3 plus lactational exposure to PFHxS at doses ranging from 0.05 to 45 mg/kg-day did not affect
4 anogenital distance or nipple retention in Wistar rats. The developmental effects and pregnancy
5 outcomes of PFHxS exposure are summarized in Section 3.2.3.
Functional measures
6 Functional measures were evaluated in medium and high confidence studies using mice or
7 rats (see Figure 3-92). PFHxS exposure for 14 days before mating at doses ranging from 0.3 to 10
8 mg/kg-day did not have a significant impact on mating or fertility indices in rats or mice f Chang et
9 al.. 2018: Ramhdi etal.. 2018: Butenhoffetal.. 2009: 3M. 20031.
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Toxicological Review of Perfluorohexanesulfonic Acid and Related Salts
Reporting quality A
Reporting quality -I
Allocation- i+
Allocation -
Observational bias/blinding
Confounding/variable control
Selective reporting and attrition
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall
Not reported
Legend
Chemical administration and characterization
Exposure timing, frequency and duration
Endpoint sensitivity and specificity
Results presentation A
Overall confidence
Figure 3-92. Male reproductive animal study evaluation heatmap -
developmental effects and functional measures. For additional details see H AWC
link.
Evidence Integration
The available studies provide inadequate evidence to determine whether PFHxS exposure
has the potential to affect male reproduction in humans. This conclusion is based on studies in both
humans and animals (see Table 3-41).
The available evidence on PFHxS-induced male reproductive effects in human studies is
considered indeterminate. Outcomes evaluated in human studies include semen parameters, male
reproductive hormones, and onset of puberty. No associations were observed for reproductive
hormone measures. Exposure-related alterations in sperm morphology and age of puberty were
reported. However, considerable uncertainties were also identified that reduce the strength of
evidence (see Table 3-41).
The available evidence on PFHxS-induced male reproductive effects in animal toxicity
studies is also considered indeterminate. Experimental studies using different laboratory rodent
species measured parameters considered indicative of potential adverse responses, including
reproductive organ weights, sperm measures, histopathology, reproductive hormones, and
developmental and functional measures. No significant exposure-related effects were observed for
the measured reproductive parameters in the available studies. While a judgment of compelling
evidence of no effect was considered for characterizing the animal evidence, significant
uncertainties in the animal study database prevent judgments about PFHxS exposure and male
reproductive toxicity from being drawn. Specifically, the short exposure duration in the available
studies is considered inadequate for the evaluation of sperm measures, only a single study
evaluated androgen levels, and other reproductive hormones were not studied.
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Table 3-41. Evidence profile table for PFHxS exposure and male reproductive effects
Evidence stream summary and interpretation
Evidence integration
summary judgment
Evidence from studies of exposed humans
Studies and confidence
Factors that increase certainty
Factors that decrease
certainty
Summary and key findings
Evidence
stream
judgment
QQQ
Evidence inadequate
Sperm parameters
3 medium and 2 low
confidence studies
• No factors noted
• Unexplained
inconsistency
across studies
• Imprecision -for
sperm
concentration
Decreased normal morphology and
concentration in one medium
confidence study.
QQQ
Indeterminate
Some
evidence of
association
with sperm
motility, and
pubertal
development.
Significant
uncertainty
due to lack of
Primary Basis:
Evidence is inconsistent across
studies or largely null.
Human relevance:
Without evidence to the
contrary, effects in rodent
models are considered
Reproductive hormones
4 medium and 5 low
confidence studies
• Unexplained
inconsistency
across studies
• Low confidence
studies
Inverse association with testosterone
and estradiol in some low confidence
studies, but medium confidence
studies were null. No association
with LH or FSH levels.
relevant to humans. The
rodent and human male
reproductive systems share
many conserved features.
Cross-stream coherence-.
N/A, human and animal
evidence indeterminate
Pubertal development
2 medium confidence
study
• No factors noted
Significant association between
exposure and lower puberty age in 1
of 2 studies.
consistency
and
coherence
Susceptible populations and
lifestages:
N/A evidence inadequate to
draw inferences
Evidence from in vivo animal studies
Studies and confidence
Factors that increase certainty
Factors that decrease
certainty
Summary and key findings
Evidence
stream
judgment
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Evidence stream summary and interpretation
Evidence integration
summary judgment
Sperm parameters
3 low confidence studies
in adult rats and mice:
• 28-d
• 44-d
• 42-d
• All low
confidence
studies - Low
sensitivity
No observed effects on sperm
measures in low confidence,
insensitive studies
ooo
Indeterminate
Certainty in
the
consistently
null findings
was reduced
due to
notable data
gaps.
Histopathology
2 high confidence studies
in adult rats:
• 28-d
• 44-d
1 medium confidence
study in adult rats
• 42-d
• High or medium confidence in
studies, with sensitive
outcome measures and low
risk of bias.
• No factors noted
No observed effects on
histopathological outcomes
Hormone levels
1 high confidence study in
adult rats
• 28-d
No observed effects on testosterone
levels
Organ weights
3 high confidence studies
in adult rats
• 28-d(x2)
• 44-d
1 medium confidence
study in rats
• GD7-PND22
No observed effects on reproductive
organ weights
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Evidence stream summary and interpretation
Evidence integration
summary judgment
Developmental effects
1 high confidence study in
rats
• GD7-PND22
No observed effects on male
reproductive organ development
Functional measures
2 high confidence studies
in rats and mice
• 14-d (x2)
No observed effects on mating or
fertility index
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3.2.10. Renal Effects
Human Studies
Seventeen studies (reported in 27 publications) investigate the relationship between PFHxS
exposure and markers of renal function, specifically measures of glomerular filtration rate (GFR)
and uric acid (UA). Three studies (Zhang etal.. 2019b: Seo etal.. 2018: Rotander etal.. 2015b) were
considered uninformative due to critical deficiencies in confounding (see Figure 3-93). The
remaining 14 studies were primarily cross-sectional analyses and were classified as low confidence
primarily due to concerns for reverse causality without other major methodological limitations. In
essence, as described in Watkins etal. f20131. decreased renal function (as measured by decreased
GFR or other measures) could plausibly lead to higher levels of PFAS, including PFHxS, in the blood.
This hypothesis is supported by data presented by Watkins etal. (2013). although there is some
uncertainty in the conclusions due to the use of modeled exposure data as a negative control and
the potential for the causal effect to occur in addition to reverse causality. The results least likely to
be affected by reverse causality were analyses in four studies (four publications) designed to assess
reverse causality (e.g., stratification by glomerular filtration stage or modeling with PFHxS as the
dependent variable) (Lin etal.. 2021: Moon. 2021): Tain (2019): (Zeng etal.. 2019c: Conway etal..
2018) and two studies with prospective designs (Lin etal.. 2021): Blake etal. (2018). Of these, Lin
etal. (2021) had the benefit of both prospective data analysis and additional analyses and was thus
rated as medium confidence. Across studies, because of the potential for reverse causation, there is
considerable uncertainty in interpreting the results of the available studies. However, the
informative studies were otherwise well conducted and had adequate or good ratings for all
domains other than exposure measurement.
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Blake, 2018, 5080657-
Cakmak, 2022, 10273369
Chen, 2019. 5387400-
Conway, 2018, 5080465-
Jain and Ducatman, 2019, 5080477-
Kataria, 2015, 3859835-
Lin, 2020, 6988476-
Lin, 2021, 7410157
Mao, 2020, 6988481
Qin, 2016, 3981721
Rotander, 2015, 3859842-
Sagiv, 2015, 3859838-
Seo, 2018,4238334-
Wang, 2019, 5080583-
Watkins, 2013, 2850974 -
Zeng, 2019, 5918630
Zhang,2019,5083675
Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
Critically deficient (metric) or Uninformative (overall)
Figure 3-93. Renal effects human study evaluation heatmap. For additional
details see HAWC link. Multiple publications of the same study: lain and Ducatman
f2019bl also includes lain and Ducatman f2019al. lain >20191 lain f20131. lain
f2Q21h). lain (2020). lain (2021a). Moon f2021). and Scinicariello etal.
f2020hl.
1 Across the 14 available studies, there is an indication of impaired renal function (i.e., lower
2 GFR, higher UA, creatinine, or disease) in nine fCakmak et al.. 2022: Lin etal.. 2021: Lin etal..
3 2020c: Mao etal.. 2020: Blake etal.. 2018: Qin etal.. 2016: Sagiv etal.. 2015: Watkins et al.. 20131.
4 including multiple NHANES publications (Moon. 2021: Scinicariello etal. 2020b: fain and
5 Di-icatmar.i. 2019b 1. but there are some inconsistencies (see Table 3-42). In adults, Blake et al.
6 f20181. Sagiv etal. (20151. Moon (20211. Lin etal. (2021) reported lower GFR with higher
7 exposure, all statistically significant, though the association in Lin etal. (20211 was observed only
8 in participants with hypertension (the direction was in the opposite direction for participants
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without hypertension). A different analysis of NHANES data overlapping with Moon (20211. Tain
and Ducatman (2019b). reported an inverted U-shape response with GFR (higher exposure levels in
the second and third tertiles than first and fourth, also observed in analyses stratified by sex). In
contrast to the majority of studies, Conway etal. f20181 and Wang etal. f2019al reported higher
GFR with higher exposure (not statistically significant). Looking at hyperuricemia, Scinicariello et
al. f2020bl reported higher odds (unstratified by sex) with an exposure-response gradient
observed across quartiles. Zeng etal. (2019c) reported higher odds in women but not men, while
Lin etal. (2020c) reported higher uric acid in the fourth quartile in men but not women. A positive
association with creatinine was observed in Cakmaketal. (2022) and with kidney stones in (Mao et
al.. 20201. However, no association was observed with chronic kidney disease in the only study that
reported it fWang etal.. 2019cl. In children and adolescents, Watkins etal. f20131 reported lower
GFR with higher exposure and Oin etal. f20161 reported higher UA, while Kataria etal. f 20151 also
reported the inverted U-shape with GFR.
Overall, there are generally consistent associations between impaired renal function and
PFHxS exposure but the potential for reverse causation is an important source of uncertainty.
However, in the studies with less potential for reverse causation, there is an indication that this bias
is unlikely to fully explain the observed associations. Significant associations were observed in both
studies with prospective exposure measurement fLin etal.. 2021: Blake etal.. 20181. though only in
participants with hypertension in Lin etal. f20211. While prospective measurement does not
eliminate the possibility of reverse causation due to ongoing exposure prior to study enrollment,
the effect is likely lower. Further, Lin etal. (2021) performed a secondary analysis using baseline
GFR as the independent variable and repeated measures of PAS as the dependent variable and
found that PFAS levels did not differ significantly by baseline GFR. A similar analysis without
repeated measures in Moon f20211 also indicated that reverse causation was not likely to explain
the results.
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Table 3-42. Associations between PFHxS exposure and renal function
Reference,
confidence
Study population
Median exposure level
(IQR) in ng/mL
Form and units of
effect estimate
Effect estimate
Glomerular filtration rate (GFR)
Decrease indicates impaired renal function
Wang et al.
(2019a), Low
Cross-sectional study
(2015-2016); China; 1,612
adults
0.7(0.01,2.7)
Mean change (95% CI)
in eGFR per In-unit
change
0.24 (-0.02, 0.50)
Watkins et al.
(2013). Low
Cross-sectional study of
9,660 children in U.S.
exposed to high PFOA
IQR 1.3
Mean change (95% CI)
per IQR increase exp
-1.0 (-1.5, -0.4)*
Jain and Ducatman
(2019b). Low
Cross-sectional study
(NHANES) (2007-2014);
U.S.; 6,836 adults
1.4
Adjusted geometric
means (95% CI) by
glomerular function
stage (GF-1 is normal or
high filtration; GF-3B/4
is moderately to
severely decreased)
All participants
GF-1: 1.20 (1.14-1.27)
GF-2: 1.73 (1.61-1.86)
GF-3: 1.83 (1.63-2.05)
GF-3B/4: 1.01 (0.78-1.31)
Moon (2021), Low
Cross-sectional study
(NHANES) (2003-2018);
U.S.; 14,373 adults
1.5 (0.8-2.6)
P (p-value) for In-unit
increase
-1.52 (-2.10, -0.94)*
Kataria et al.
(2015). Low
Cross-sectional study of
1,960 adolescents in U.S.
2
P (95 CI) for quartiles
vs. Q1
Q2: 1.4 (-3.6,6.3)
Q3: 1.9 (-3.4,7.1)
Q4: -0.3 (-4.4,3.8)
Sagiv et al. (2015),
Low
Cross-sectional study of
1,645 pregnant women in
U.S.
2.4
(1.6-3.8)
% change GFR
-4.3 (-5.3, -3.3)*
Geometric means (IQR)
of exp by quartile
Ql: 3.0(1.9,4.3)
Q2: 2.7(1.7,4.1)
Q3: 2.3 (1.5,3.2)
Q4: 2.2 (1.5,3.5)*
Lin et al. (2021).
Medium
Cohort study within
placebo and lifestyle
intervention arms of a
diabetes prevention
randomized controlled
trial of 875 adults in the
U.S.
2.4(1.6-3.8)
P (95 CI) for doubling of
baseline exposure
0.21 (-0.79, 1.21)
With hypertension
-2.35 (-4.46, -0.25)*
Without hypertension
1.24 (0.09, 2.39)*
Blake etal. (2018).
Low
Prospective cohort of
residents near a uranium
processing site (1990-
2008); U.S.; 210 adults
2.7
(1.7-4.1)
Percent change (95%
CI) in eGFR per IQR
change
-2.06 (-3.53, -0.59)*
Conwav et al.
(2018), Low
Cross-sectional study of
53,650 adults in U.S.
exposed to high PFOA
3.0
(1.9-4.8)
OR (95% CI) for 1-unit
increase
GF-1: 2.07 (1.69-2.55)
GF-2: 2.29 (1.86-2.81)
GF-3A: 2.37 (1.87-2.84)
GF-3B: 2.30(1.83-2.90)
GF-4/5:1.0 (ref)
Uric acid (UA)
Increase indicates impaired renal function
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Reference,
confidence
Study population
Median exposure level
(IQR) in ng/mL
Form and units of
effect estimate
Effect estimate
Zeng et al. (2019c),
Low
Cross-sectional study of
1,612 adults in China
0.7 (0.01-2.7)
Mean difference per
log-unit increase
0.01 (-0.15, 0.03)
GF-1: -0.01 (-0.06, 0.04)
GF-2:-0.00 (-0.03, 0.03)
GF-3: 0.05 (-0.04, 0.15)
GF-4: -0.04 (-0.23, 0.15)
OR (95% CI) for
hyperuricemia for log-
unit increase
1.01 (0.97, 1.06)
Women: 1.18(1.01,
1.37)*
Men: 0.99 (0.95,1.04)
Chen et al. (2019a),
Low
Cross-sectional study of
122 adults in China
GM 0.8, range 0.3-2.4
P (95% CI) for In-unit
increase
-4.42 (-24.23, 15.38)
Qin et al. (2016),
Low
Cross-sectional study of
225 children in Taiwan
1.3
(0.6-2.8)
|3 (95 CI) for In-unit
increase
0.14 (0.02,0.26)*
OR (95% CI) for quartile
increase exp and high
UA
1.4 (0.9,2.1)
Jain and Ducatman
(2019a), Low
Cross-sectional study
(NHANES) (2007-2014);
U.S.; 6,836 adults
1.4
P (p-value) for 1-unit
increase
In GF-1 participants
Women: 0.023 (<0.01)*
Men: 0.015 (0.06)
Scinicariello et al.
(2020b), Low
Cross-sectional study
(NHANES) (2009-2014);
U.S.; 4,917 adults
1.4 (GM)
P (95% CI) in serum uric
acid for quartiles vs Q1
02:0.14(0.02, 0.26)*
03: 0.22 (0.08, 0.36)*
04: 0.33 (0.19, 0.47)*
OR (95% CI) in
hyperuricemia for
quartiles vs Q1
02: 1.15 (0.89, 1.50)*
03: 1.33 (0.95, 1.86)*
04:1.51(1.12,2.03)*
Kataria et al.
(2015), Low
Cross-sectional study of
1,960 adolescents in the
U.S.
2
P (95% CI) for quartiles
vs. Q1
02: 0.04 (-0.1,0.2)
03: 0.05 (-0.1,0.2)
04: -0.05 (-0.2,0.1)
Lin et al. (2020c),
Low
Cross-sectional study
(2016-2017); Taiwan; 397
older adults (55-75 yrs)
2.7(1.9-3.7)
P (95% CI) in serum uric
acid for quartiles vs Q1
02: 0.01 (-0.32, 0.33)
03: -0.1 (-0.44, 0.23)
04: 0.39(0.05, 0.72)*
Women:
02: 0 (-0.36, 0.35)
03: -0.1 (-0.46, 0.26)
03: 0.05 (-0.31, 0.42)
Men:
02: -0.31 (-0.97, 0.35)
03: 0.3 (-0.37, 0.96)
04: 0.89(0.22, 1.56)*
Creatinine
Increase indicates impaired renal function
Cakmak et al.
(2022). Low
Cross-sectional study
(2007-2017); Canada;
6,045 adults
1.5 (GM)
% change per 1 mean
increase in PFDA
1.0(0.1, 1.8)*
Chronic kidney disease
Wang et al.
(2019b), Low
Cross-sectional study
(2015-2016); China; 1,612
adults
0.7 (0.01-2.7)
OR (95% CI) for chronic
kidney disease per In-
unit change in PFDA
1.01 (0.94, 1.07)
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Reference,
confidence
Study population
Median exposure level
(IQR) in ng/mL
Form and units of
effect estimate
Effect estimate
Kidney stones
Mao etal. (2020).
Low
Cross-sectional study
(NHANES) (2007-2016);
U.S.; 8,453 adults
1.5 (0.8-2.5)
OR (95% CI) for kidney
stone history for
tertiles vs T1
T2: 1.24(1.03, 1.51)*
T3: 1.35 (1.10, 1.68)*
*p < 0.05.
Animal Studies
1 There are two 28-day oral gavage exposure studies in Sprague Dawley rats fNTP. 2018b:
2 3M. 2000a) and two 42-44 day exposure oral gavage studies in CD-I mice (Chang etal.. 20181 and
3 Sprague Dawley rats (Bute nhoff etal.. 2009: 3M. 20031 that measure effects relevant to the
4 assessment of the urinary system after repeated oral dose exposure to PFHxS. The studies report on
5 clinical chemistry (serum) biomarkers of effect, histopathology, and organ weights. Overall study
6 confidence was high for most endpoints evaluated in these studies with the exception of organ
7 weights and serum markers in Chang etal. f 20181. which had incomplete reporting of null data
8 (results were only discussed qualitatively) resulting in a medium confidence rating (see Figure 3-
9 94).
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Reporting quality
Allocation
Observational bias/blinding
Confounding/variable control
Selective reporting and attrition -|
Chemical administration and characterization
Exposure timing, frequency and duration -j
Endpoint sensitivity and specificity
Results presentation
Overall confidence
S Legend
Good (metric) or High confidence (overall)
Adequate (metric) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
H Critically deficient (metric) or Uninformative (overall]
Not reported
Figure 3-94. Renal effects - animal study evaluation heatmap. For additional
details see HAWC link.
Clinical chemistry
Serum biomarkers of renal injury (including blood urea nitrogen [BUN], creatinine,
creatinine kinase, and total protein) were measured in Sprague Dawley rats after short-term (28
day) exposure fNTP. 2018b: 3M. 2000al. and two 42- or 44-day exposure studies using CD-I mice
and Sprague Dawley rats fChang etai. 2018: Butenhoff etai. 2009: 3M. 20031. In the F0 generation
male Sprague Dawley rats, 44 days of exposure to PFHxS at the highest tested dose, 10 mg/kg-day,
resulted in a 31% increase in BUN when compared with controls (Butenhoff et al.. 2009: 3M. 20031.
However, no effects were observed for creatinine, creatinine kinase, or total protein in male
animals and female animals from the same study (Butenhoff et al.. 2009: 3M. 20031: a similar study
using CD-I mice reported no effects on creatinine, urea nitrogen, and electrolytes in F0 generation
male and female animals exposed to same levels of PFHxS (10 mg/kg-day) for 44 days; and two 28-
day study using SD rats reported no exposure-related effects in creatinine, creatinine kinase, blood
urea nitrogen (BUN), or total protein after PFHxS exposure at doses ranging from 0.6 to 10 mg/kg-
day (NTP. 2018b: 3M. 2000al. BUN is considered a late biomarker of renal injury not normally
affected until at least half of the kidney mass is compromised fKhan etai.. 20181. The biological
significance of the PFHxS-induced BUN increase observed in the NTP study is not clear as BUN was
not affected in similar studies, and other clinical indicators of kidney damage were not altered in
the available studies.
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Histopathology
Renal histopathology was evaluated across two 28-day gavage studies fNTP. 2018a: 3M.
2000a) and one 42- to 44-day exposure toxicity study fButenhoffetal.. 2009: 3M. 20031. All studies
used Sprague Dawley rats. Exposure to PFHxS for 28 to 44 days at doses ranging from 0.3 to 10
mg/kg-day did not have any notable treatment-related impacts on kidney histopathology. One 28-
day short-term study also evaluated the urinary bladder and reported no effects fNTP. 2018a). In
this study, chronic progressive nephropathy30 graded as minimal occurred in the kidneys of all
exposed animals, including controls.
Organ weight
Absolute and relative (to body weight) kidney weights were measured in the two 28-day
gavage studies using Sprague Dawley rats fNTP. 2018a: 3M. 2000a] and the two 42- to 44-day
exposure studies using Sprague Dawley rats fButenhoffetal.. 2009: 3M. 2003) or CD-I mice (Chang
etal.. 2018). Exposure to 10 mg/kg-day PFHxS for 28 days increased relative kidney weights in
male Sprague Dawley rats (NTP. 2018a). This response was not observed in female animals (NTP.
2018a) and none of the remaining studies exposing rats or mice to similar doses and durations
(ranging from 28 to 44 days) did not observe significant PFHxS-induced changes in relative or
absolute kidney weights f Chang etal.. 2018: Butenhoffetal.. 2009: 3M. 2003. 2000a).
Evidence Integration
The available evidence suggests but is not sufficient to infer that exposure to PFHxS might
cause renal system effects in humans given sufficient exposure conditions31 (see Table 3-43).
The available evidence on PFHxS-induced renal effects in humans is considered slight. The
evidence for potential renal system effects in humans is based on reported associations between
PFHxS exposure and impaired renal function in nine out of 14 informative epidemiological studies
including several statistically significant findings. There is considerable uncertainty remaining due
to the potential for reverse causation, but study analyses examining this bias indicate that it is
unlikely to fully explain the observed associations.
The available evidence on PFHxS-induced renal effects in animal toxicity studies is also
considered indeterminate. The experimental animal evidence informing potential renal system
effects is limited to two 28-day gavage studies in Sprague Dawley rats fNTP. 2018a: 3M. 2000a].
and two 42- to 44-day exposure studies using Sprague Dawley rats fButenhoffetal.. 2009: 3M.
20031 or CD-I mice f Chang etal.. 20181. The studies were generally well conducted (confidence
ratings were high/medium) and reported on relevant measurements, including serum biomarkers
30Chronic progressive nephropathy is a commonly observed spontaneous lesion frequently observed in 2 to
13-week studies using SD rats fKhan etal.. 20181.
31The "sufficient exposure conditions" are more fully evaluated and defined for the identified health effects
through dose-response analysis in Section 5.
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1 of renal injury (i.e., BUN, creatinine, and creatinine kinase), kidney and urinary bladder
2 histopathology and kidney weights. Although a few significant findings were observed, PFHxS
3 exposure generally did not affect the renal system in the available studies. However, the absence of
4 long-term studies limits the evaluation of potential renal system toxicity in animals following
5 PFHxS exposure, hence a conclusion of compelling evidence of no effect was not considered
6 appropriate.
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Table 3-43. Evidence profile table for PFHxS urinary system effects
Evidence stream summary and interpretation
Evidence integration
summary judgment
Evidence from studies of exposed humans
Studies and
confidence
Factors that increase certainty
Factors that
decrease
certainty
Summary and key findings
Evidence stream
judgment
Evidence suggests
ooo
Renal Functions
1 medium and 13 low
confidence studies
• Consistency
• Precision
• Primarily low
confidence
studies -
potential
reverse
causality
9 of 14 studies reported associations
between PFHxS exposure and
impaired renal function. Reverse
causality is an important source of
uncertainty.
®oo
Slight
Primary Basis:
Generally consistent
evidence across studies
in humans.
Human relevance:
N/A
Cross-stream coherence:
N/A. Evidence in animals
Evidence from in vivo animal studies
is indeterminate.
Studies and
confidence
Factors that increase certainty
Factors that
decrease
certainty
Summary and key findings
Evidence stream
judgment
Serum Biomarkers of
Renal Injury,
Histopathology,
Organ Weights
3 high confidence
studies in adult rats:
• All high or medium confidence
studies
• Unexplained
inconsistency
• Increased BUN reported in one
study, bit no effects in
remaining studies and no
response in other markers of
renal disease.
QQQ
Indeterminate
• 28-d (x2)
• 44-d
1 medium confidence
study using mice
• No PFHxS-induced effects on
histopathological outcomes.
• No observed PFHxS-induced
effects on kidney weights
• 44-d
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3.2.11. Other Noncancer Health Effects
Human Studies
No epidemiological studies in the database were identified to inform health effects other
than those discussed in prior sections.
Animal Studies
Several other health effects were examined in experimental animals; however, there were
very little data to inform whether PFHxS exposure might have the potential to cause these effects.
Specifically, the high confidence, 28-day rat study conducted by NTP f2018cl investigated the
potential for PFHxS exposure to cause effects on the alimentary system (including the esophagus,
large, small intestine, pancreas, salivary glands, and stomach), musculoskeletal system, and
respiratory system. For each of these systems, there were no clear PFHxS exposure-related effects
in male or female animals, with the exception of an observation of minimal32 olfactory epithelium
degeneration and minimal hyperplasia along with minimal suppurative inflammation in females,
but not males, in the highest exposure group (8/10 rats in 50 mg/kg-day exposure group). Overall,
the sparsity of evidence on these outcomes prevents any interpretation from being drawn.
Evidence Integration
The currently available evidence is inadequate to assess whether PFHxS may cause other
noncancer health effects in humans, including those related to the alimentary system,
musculoskeletal system, and respiratory system. In general, the data available for these health
outcomes were largely null and/or absent (i.e., indeterminate evidence from human and animal
studies) and considerable data gaps remain for these health effects.
3.3. CARCINOGENICITY
3.3.1. Cancer
The systematic review identified twelve epidemiologic studies that evaluated the risks of
cancer associated with exposures to PFHxS fLi etal.. 2022a: Velarde etal.. 2022: Liu etal.. 2021b:
Omoike etal.. 2021: Lin etal.. 2020a: Tsai etal.. 2020: Ghisari etal.. 2017: Wielsae etal.. 2017:
Christensen et al.. 2016: Bonefeld-largensen et al.. 2014: Hardell etal.. 2014: Yeung etal.. 20131. Six
cancer studies by (Li etal.. 2022a: Velarde etal.. 2022: Omoike etal.. 2021: Lin etal.. 2020a:
Wiels0e etal.. 2017: Christensen et al.. 2016) were evaluated as 'Uninformative.' One study (Yeung
etal.. 2013) was screened as related to hepatocellular carcinoma cancer, but actually examined the
serum and liver concentrations of PFAS, including PFHxS, among patients who had liver
32Minimal refers to average histological severity grade as follows: 1 = minimal; 2 = mild; 3 = moderate; 4 =
marked) as determined by NTP (2018c).
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transplants—some of whom had hepatocellular carcinoma cancer; this study did not assess cancer
risk and was not evaluated for study quality.
No animal in vivo, mutagenicity or ge no toxicity studies were identified in the database.
Bonefeld-Jorgensen, 2014, 2851186
Christen sen, 2016, 3058533
Ghisari, 2017 3860243-
Hardell. 2014 2968084
Li H 2021
Lin HW et a!.. 2020. 6835434 -
I iu, ?0?1, 10176563
Omoike Oe otol 2020. 7021502
tsal MS et al,, 2020, 6833693 -
Velarde MC el al 2022 9956482
Wielsoe. 2017 3858479
^ Legend
2 Good (melric) or High confidence (overall)
Adequate (melnc) or Medium confidence (overall)
Deficient (metric) or Low confidence (overall)
01 Critically deficient (metric) oi Unin formative (overall)
* Multiple judgments exist
Figure 3-95. Study evaluation results for epidemiology studies of PFHxS and
cancer. For additional details see HAWC link.
Human Studies
The study of prostate cancer fHardell etal.. 20141 was low confidence due to concern about
the exposure measurement not representing the etiologically relevant time period, potential for
confounding, insufficiencies in the analysis, and concerns about sensitivity (see Figure 3-95).
Hardell etal. f20141 reported a no n-significantly increased risk of prostate cancer among men with
PFHxS concentrations in blood that were above the median value; and a higher, borderline
significant, risk of prostate cancer among men with PFHxS concentration greater than the 75th
percentile. Hardell etal. f20141 also reported that men with PFHxS concentrations above the
median and with a first-degree relative with prostate cancer were at significantly increased risk.
The study of thyroid cancer (Liu etal.. 2021b) was low confidence due to concern about the
exposure measurement not representing the etiologically relevant time period, deficiencies
regarding the outcome definition, and potential for confounding, (see Figure 3-95). Liu etal.
f2021bl reported significantly decreased risk of thyroid cancer associated with increasing quartiles
of PFHxS. The first study of breast cancer fBonefeld-largensen et al.. 20141 was low confidence due
to concerns about participant selection and potential selection bias as there was: (1) no explanation
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of why 29% of cases were withdrawn from the National Patient Registry, (2) no comparisons of the
subjects' details between the withdrawn cases and the originally selected cases, and (3) no
consideration of how the originally matched controls might no longer match the final set of cases.
Bonefeld-largensen etal. f20141 studied the effect of PFHxS on the risks of breast cancer in Danish
women using a case-control study, and initially found a significantly decreased risk of breast cancer
with increases in continuously measured PFHxS, although in subsequent analyses, excluding 72
breast cancer cases (29% of the cases) which were withdrawn from the National Patient Registry,
the effects changed slightly and lost statistical significance. The second of breast cancer Ghisari et
al. (20171 was low confidence because it was based on the same case-control as Bonefeld-l0rgensen
etal. f20141 and had the same deficiencies. Ghisari etal. f20171 investigated genetic
polymorphisms as potential effect modifiers of the risk of PFAS on breast cancer. They reported
that none of the genetic polymorphisms evaluated was an effect modifier, but that some genotypes
(CYP1B1 Val/Val, COMT Val/Val, CYP17 Al/Al and CYP19 CT) were associated with significantly
decreased risks of breast cancer associated with increased PFHxS exposure. The third study of
breast cancer (Tsai etal.. 20201 was low confidence due to concern about the exposure
measurement not representing the etiologically relevant time period, potential for confounding,
and concerns about low sensitivity (see Figure 3-95). Tsai etal. f20201 reported significantly
increased risk of breast cancer per In-transformed unit increase in PFHxS concentration in blood
among women <= 50 years of age who were estrogen receptor positive; and non-significantly
decreased risk of breast cancer per In-transformed unit increase in PFHxS concentration in women
<= 50 years of age and estrogen receptor negative and in all women > 50 years of age. In summary,
the available epidemiologic evidence on PFHxS and the risk of cancer is limited and generally
uninformative.
Animal Studies
No studies were identified in the evidence base evaluating the carcinogenicity of PFHxS in
animals.
Evidence Integration Summary
The available evidence for any effect of PFHxS on the risk of developing or dying from
cancer is scant, inconsistent, and limited to low confidence studies. Thus, the available human
evidence on breast, thyroid or prostate cancer is considered indeterminate and, overall, based on
EPA guidelines (U.S. EPA. 20051, there is inadequate information to assess carcinogenic
potential.
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4. SUMMARY OF HAZARD IDENTIFICATION
CONCLUSIONS
4.1. SUMMARY OF CONCLUSIONS FOR NONCANCER HEALTH EFFECTS
As described in detail in Section 3, the currently available evidence indicates that exposure
to perfluorohexane sulfuric acid [PFHxS] and its related salts likely results in thyroid (see Section
3.2.1) and immune (see Section 3.2.2) effects in humans given sufficient PFHxS exposure
conditions. These judgments are based primarily on data from epidemiologic studies for immune
effects and on short-term (28-day exposure), and reproductive (gestational and postnatal
exposure) oral exposure studies in rodents for thyroid effects. Further characterizations of the
exposure conditions relating to these two identified hazards are provided in Section 5.
The hazard identification judgment that the evidence indicates PFHxS exposure is likely to
cause thyroid toxicity, specifically decreased thyroid hormones, in humans given sufficient PFHxS
exposure conditions, is based primarily on a short-term study and two multigenerational studies in
rats reporting a consistent and coherent pattern of hormonal changes at PFHxS exposure levels
>2.5 mg/kg-day. A consistent dose-dependent decrease of T4, and to a lesser extent T3, in adult and
juvenile rats, with a magnitude of effect (up to 70%) in the absence of effects in TSH was observed
(with males being more sensitive). In addition, one multigenerational study reported increased
incidence of minimal thyroid hypertrophy and moderate hyperplasia in male rats after PFHxS
exposure. Due to the similarities in thyroid hormone production between rodents and humans, the
effects in rodents were considered relevant to humans. A detailed discussion of thyroid effects is
included in Section 3.2.1.
The hazard identification judgment that the evidence indicates PFHxS exposure is likely to
cause immunotoxicity in humans given sufficient exposure conditions is based on generally
consistent evidence of reduced antibody response to vaccination at median blood concentrations of
0.2-0.6 ng/mL in children. The direction of association was generally consistent across studies and
timing of exposure and outcome measures, although not all the results were statistically significant
Further, three studies reported higher odds of infectious disease with higher PFHxS exposure,
including total infectious disease, lower respiratory infection, throat infection, pseudocroup, and
gastroenteritis. Lastly, there was some evidence of hypersensitivity, based primarily on a single
well-conducted study of asthma, although findings were inconsistent across studies. A detailed
discussion of immune effects is included in Section 3.2.2.
The evidence suggests but is not sufficient to infer that, given sufficient exposure
conditions, PFHxS exposure may result in adverse health effects on the hepatic, cardiometabolic,
and neurodevelopmental systems, along with developmental effects. These judgments highlight the
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notable data gaps and uncertainties identified in the available epidemiological and experimental
animal PFHxS studies (see Section 3.2.3, Section 3.2.4, Section 3.2.5, and Section 3.2.6). The
uncertainties in the above-mentioned hazards were considered too large for developing toxicity
values (see Section 5). However, to convey some sense of the magnitude of a potential estimate for
developmental effects, calculations based on this suggestive evidence are provided for comparison
purposes. The objective was to inform the database uncertainty factor (UF) for quantitative
estimates of thyroid and immune effects.
For all other health effects described in Section 3 (i.e., renal, male, and female reproductive,
cardiometabolic, hematopoietic, and other noncancer effects) the evidence is inadequate to assess
whether PFHxS exposure might cause effects in humans. No quantitative estimates were attempted
for these health effects.
The potential for multi-organ effects of PFHxS exposure exists. As an example, the reported
hypertrophy and hyperplasia in the follicular epithelium cells of the thyroid and in the centrilobular
hepatocytes in the F0 male rats exposed to 10 mg/kg-day PFHxS (Butenhoff et al.. 2009) may be
related effects. It has been shown that exposure to compounds that cause microsomal enzyme
induction in the liver can result in a compensatory hypertrophy and hyperplasia of the thyroid due
to increased plasma turnover of T4 and TSH fButenhoffetal.. 2009: Sanders etal.. 19881. However,
as discussed in Section 3.2.1, the authors did not measure thyroid hormones as part of their study
design and therefore the reported observation that thyroid hypertrophy and hyperplasia are
compensatory mechanisms due to turnover of T4 and TSH is speculative. In addition, decreases in
T3 and T4 observed in adult and juvenile animals exposed to PFHxS could be linked to metabolic
effects as well as neurodevelopmental effects such as cognitive decline in children discussed in
detail Section 3.2.1). Lastly, the decreased immune response observed in children exposed to PFHxS
could lead to increased risk of infection as well as cancer fGermolec et al.. 20221. although neither
of these latter effects were well-studied in the available PFHxS evidence base.
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Table 4-1. Hazard conclusions across published EPA PFAS human health assessments
Health outcome
PFAS assessmentsabc
PFHxS
PFDA
PFHxA
PFBA
PFBSd
Gen X chemicalsd
PFOAd
PFOSd
Endocrine/ Thyroid
+
+
+
+
ND
Human: +
Animal: +/-
Human: +/-
Animal: +/-
Hepatic/Liver
+/-
+
+
+
+
Human: +
Animal: +
Human: -
Animal: +
Developmental
+/-
+
+
+
¦
+/-
Human: +
Animal: +
Human: +
Animal: +
Reproductive
+/-
Human: -
Animal: +/-
ND
Immunotoxicity
+
"
-
+/-
Human: +
Animal: +
Human: +/-
Animal: +
Renal
-
-
-
¦
+/-
Human: +/-
Animal: +/-
ND
Hematopoietic/
Hematological
-
-
¦
-
ND
+/-
ND
ND
Ocular
-
-
ND
-
ND
ND
ND
ND
Serum Lipids
-
+/-
ND
ND
-
ND
Human: +
Animal: +
Human: +
Hyperglycemia
-
-
ND
ND
ND
ND
Human: -
Animal: -
Animal: +/-
Nervous System
-
+/-
-
ND
ND
ND
Human: -
Animal: -
Animal: +/-
Cardiovascular
-
+/-
ND
ND
-
ND
ND
ND
Cancer
-
-
-
-
-
+/-
+/-
+/-
Assessments used multiple approaches for summarizing their noncancer hazard conclusion scales; for comparison purposes, the conclusions are presented as
follows:'+' = evidence demonstrates or evidence indicates (e.g., PFHxA), or evidence supports (e.g., PFBS);= suggestive evidence,= inadequate
evidence (e.g., PFHxA) or equivocal evidence (e.g., PFBS);= sufficient evidence to conclude no hazard (no assessment drew this conclusion); ND = no data
available for this outcome for this PFAS.
bThe assessments all followed the EPA carcinogenicity guidelines (U.S. EPA, 2005) a similar presentation to that used to summarize the noncancer judgments is
applied for the cancer hazard conclusions, as follows:'+' = carcinogenic to humans or likely to carcinogenic to humans;'+/-' = suggestive evidence of
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carcinogenic potential;= inadequate information to assess carcinogenic potential;= not likely to be carcinogenic to humans(no assessment drew this
conclusion); ND = no carcinogenicity data available for this PFAS.
cThe hazard conclusions for the various EPA PFAS assessments presented in this table were not considered during evidence integration and thus did not inform
the evidence integration conclusions presented in the PFHxA assessment.
dThe U.S. EPA PFOA (U.S. EPA, 2016b) and PFOS (U.S. EPA, 2016a) assessments did not use structured language to summarize the noncancer hazard
conclusions. The presentation in this table was inferred from the hazard summaries found in the respective assessments; however, this is for comparison
purposes only and should not be taken as representative of the conclusions from these assessments. Those interested in the specific noncancer hazard
conclusions for PFOA and PFOS must consult the source assessments. Note that new assessments for PFOA and PFOS are currently being finalized to support a
National Primary Drinking Water Regulation; note that hazard conclusions in these updated assessments will differ from those presented in this table as the
new assessments use structured language to summarize the noncancer hazard conclusions. For access to the more recent draft assessment materials please
follow this link.
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4.2. SUMMARY OF CONCLUSIONS FOR CARCINOGENICITY
The evidence currently available to make a judgment as to whether PFHxS exposure might
affect the development of any specific cancers is scant, inconsistent, and limited to low confidence
studies. Consistent with EPA guidance fU.S. EPA. 20051 to apply a standard descriptor as part of the
hazard narrative and to express a conclusion regarding the weight of evidence for the carcinogenic
hazard potential, a descriptor of inadequate information to assess carcinogenic potential is
applied for PFHxS.
4.3. CONCLUSIONS REGARDING SUSCEPTIBLE POPULATIONS AND
LIFESTAGES
Understanding of potential areas of susceptibility to the identified human health hazards of
PFHxS can help to inform expectations of variability in responses across individuals, as well as
uncertainties and confidence in candidate toxicity values (see Section 5.2). The available human
and animal evidence indicate that early lifestages represent a susceptible population for the
adverse effects of PFHxS exposure. High confidence experimental studies report alterations in
thyroid function, including reduced serum T4 and T3, after gestational and early postnatal PFHxS
exposures in rats (see Section 3.2.1). In addition, medium confidence epidemiological studies report
that exposure to PFHxS was associated with decreased immune response after routine vaccinations
against tetanus and diphtheria vaccines in children at ages 5 and 7 (see Section 3.2.2). Although
there are considerable uncertainties in the developmental epidemiological database (e.g., potential
impact on PFHxS biomarkers due to pregnancy hemodynamics), consistent and coherent
epidemiological findings on fetal growth restriction including several medium and high confidence
developmental epidemiological studies also provide support for examination of critical in utero
exposure windows (see Section 3.2.3).
The significant difference in clearance between male and female rats (7.2 vs. 84.1 mL/kg-
day, respectively; see Section 3.1.4 for details) implies a sex-dependent susceptibility in that
species: for given dose, blood and tissue levels are predicted and were observed to be significantly
higher in male rats than female rats. While clearance levels in male and female mice were quite
similar to each other (3.9 and 3.2 mL/kg-day), the markedly lower clearance in female mice
compared to female rats predicts a strong species difference for susceptibility to developmental
effects. Results for adult humans are consistently much lower than observed in either mice or rats
(0.02-0.07 mL/kg-day), which is predicted to result in a strong species difference in susceptibility.
But only one of the human studies observed a clear sex difference, with that in younger women
being about 50% higher than men and older women fZhang etal. f2013bl: see Table 3-4).
Additional clearance due to menstrual fluid loss could significantly reduce internal doses in women
of childbearing age. The rate of menstrual fluid clearance estimated by Verner and Longnecker
(2015) (0.033 mL/kg-day) is only slightly lower than (80% of) the geometric mean clearance for
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fecal and urinary elimination (0.041 mL/kg-day), so blood levels in a 30-year-old woman might be
55% of those in a 30-year-old man exposed to the same dose (lain and Ducatman. 20221. In
addition, serial blood measurement of PFHxS in pregnant women show that the decrease in
clearance due to the lack of menstruation during pregnancy does not result in an increase in
internal dose fOh etal.. 20221. This implies that other pharmacokinetic changes during pregnancy
mediate the decreased clearance during that time and that the clearance for women of reproductive
age (prior to pregnancy) is also appropriate for evaluating maternal dosimetry for developmental
endpoints in humans. Animal-to-human extrapolations do account for the species- and sex-specific
clearance observed among mice and rats, so in that regard PK-related susceptibility is addressed.
Given the effects seen in the developing individuals (i.e., altered thyroid and immune
functions), prenatal and early postnatal lifestages represent a potentially sensitive population for
the effects of PFHxS exposure. No evidence was available to inform other factors that could inform
the potential for susceptibility to PFHxS exposure including demographics, genetic variability,
health status, behaviors or practices or social determinants. The potential impact of these other
susceptibility factors remains unknown.
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5. DERIVATION OF TOXICITY VALUES
5.1. NONCANCER AND CANCER HEALTH EFFECT CATEGORIES
CONSIDERED
The available evidence indicates that oral exposure to perfluorohexane sulfuric acid
[PFHxS] and its related salts is likely to cause adverse immune effects in humans on the basis of the
evidence presented in human studies and adverse thyroid effects on the basis of the evidence
presented in animal toxicity studies. The dose levels associated with these two identified hazards
were considered for the derivation of reference doses (RfDs) as presented below. The available
evidence suggests but is not sufficient to infer that PFHxS exposure may result in developmental,
neurodevelopmental, cardiometabolic, and hepatic effects. Given the uncertainty in these latter
conclusions, ultimately no toxicity values were derived for these health effects. A dose-response
assessment is typically not performed for health effect judgments of "evidence suggests," although
when the database contains at least one well-conducted study, quantitative analyses may still be
useful for some purposes, such as providing a sense of the magnitude and uncertainty of estimates
for health effects of concern, ranking potential hazards, informing responses in potentially
susceptible populations and lifestages, or setting research priorities fU.S. EPA. 2020. 20051. The
available evidence on PFHxS-induced developmental effects includes high confidence
epidemiological studies in which the observed outcome (low birth weight) occurs during a
susceptible lifestage and is associated with increased lifetime risk for developing a variety of
adverse health conditions such as type 2 diabetes, cardiovascular disease, neurodevelopmental
disorders, and renal disease (Tian etal.. 2019a: Reyes and Manalich. 2005: Hack etal.. 19951. Thus,
for comparison purposes during toxicity value derivation for immune and thyroid effects, a point of
departure (POD) was estimated for developmental effects (see Section 5.2.1). For all other health
effects (i.e., female, and male reproductive, hematopoietic, and renal) the currently available
evidence is inadequate to assess whether PFHxS exposure might be capable of causing these
potential health effects; therefore, these endpoints were not considered for the derivation of
toxicity values.
There are no available studies to inform the potential for PFHxS to cause adverse health
effects via inhalation exposure precluding the derivation of reference concentration (RfC) (see
Section 5.2.3). Likewise, evidence pertaining to the evaluation of carcinogenicity was considered
inadequate to assess carcinogenic potential of PFHxS in humans, precluding the derivation of
cancer toxicity values via any exposure route (see Section 5.3).
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5.2. NONCANCER TOXICITY VALUES
Noncancer toxicity values, including reference doses (RfDs) for oral exposure and reference
concentrations (RfCs) for inhalation exposure, are estimates of an exposure for a given duration to
the human population (including susceptible subgroups and/or life stages) that are likely to be
without an appreciable risk of adverse health effects over a lifetime. The RfD derived in Section
5.2.1 corresponds to chronic, lifetime exposure and is the primary focus of this document In
addition, a less-than-lifetime, subchronic toxicity value (referred to as a "subchronic RfD"), which
corresponds to exposure durations ranging from a month to 10% of the life span in humans, is
derived in Section 5.2.2. Subchronic toxicity values may be useful for certain decision-making
contexts (e.g., site-specific risk assessments with less-than-lifetime exposures). Both RfD and
subchronic RfD derivations include organ-/system-specific RfDs (osRfDs) associated with health
effect-specific PODs considered for use in deriving the RfD (or subchronic RfD). As with the
subchronic RfD, osRfDs can be useful for certain decision-making contexts (e.g., cumulative risk
assessment). Subsequent decisions related to dosimetric extrapolation, application of uncertainty
factors, and confidence in toxicity values are discussed below. No information exists to inform the
potential toxicity of inhaled PFHxS or derive an RfC; this decision is discussed in Section 5.2.3.
5.2.1. Oral Reference Dose (RfD) Derivation
Study/Endpoint Selection
Data sufficient to support dose-response analyses and POD calculations for oral exposure to
PFHxS or its salts were available for both identified human health hazards: thyroid and immune
effects. As mentioned above, although a definitive health hazard was not identified, a POD was also
calculated for developmental effects because the evidence base for developmental effects caused by
PFHxS includes well-conducted epidemiological studies. In addition, derivation of a POD for
developmental outcomes was considered informative of the potential magnitude of effects relevant
to susceptible populations and lifestages and thus might inform toxicity value derivation for thyroid
or immune effects.
Rationales for study selection, details of the POD calculations, and toxicity value estimation,
as well as determination of confidence in the derived toxicity values, are detailed in this section.
The general considerations used to prioritize studies for estimating PODs for potential use in
derivation of toxicity values are described in the IRIS PFAS Protocol (see Appendix A). Well-
conducted (i.e., high or medium confidence) human studies that were deemed influential to the
hazard conclusions were prioritized for POD derivation and compared with PODs derived from
well-conducted animal studies when possible. Such human studies were available for
developmental and immunotoxicity effects.
A summary of endpoints and rationales considered for toxicity value derivation is presented
below.
This document is a draft for review purposes only and does not constitute Agency policy.
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Thyroid effects
Human studies provide conflicting evidence as to the potential effects of PFHxS on thyroid
outcomes (e.g., thyroid hormone levels). While a few studies did suggest an association between
increasing PFHxS exposure levels and decreased circulating thyroid hormones (i.e., T4) or
subclinical thyroid disease, these associations were not consistent across studies (see Section 3.2.1
for details). Overall, the available human evidence on PFHxS effects on the thyroid was considered
indeterminate, and thus these studies were not considered for use in deriving toxicity values.
The database of animal studies examining PFHxS-induced thyroid effects includes two
short-term studies in rats and mice fChang etal.. 2018: NTP. 2018al and two multigenerational
reproductive studies (one study, two publications: Ramhai etal. f20181 and Ramhai etal. f20201:
fButenhoff etal.. 200911. Of these, a study in ICR mice f Chang etal.. 20181 was judged as low
confidence and thus was not considered for POD derivation, leaving three high confidence studies
in SD rats (NTP. 2018a: Butenhoff etal.. 20091 or Wistar rats (Ramh0i etal.. 2020: Ramh0i etal..
20181.
NTP (2018a) examined effects on serum concentrations of total and free T4 in adult rats,
while Ramhai etal. f 20181 evaluated effects of PFHxS on free T4 serum levels in exposed dams and
their offspring (exposed during gestation and lactation) through PND 22. NTP f2018al observed a
statistically significant, dose-dependent decrease (p < 0.01) of free and total T4 levels starting at the
lowest experimental dose (0.625 mg/kg-day) in male rats (up to 60% in free T4 and 78% decrease
in total T4). In female rats, T4 levels were significantly decreased beginning at higher doses (12.5
mg/kg-day and above), with 38% decrease in free T4 and 33% decreases in total T4 at the highest
dose (50 mg/kg-day) (p < 0.01). Ramh0i etal. (2018) reported similar findings to those reported by
NTP f2018al in Wistar rat dams, with statistically significant, dose-dependent decreases in serum-
free T4 at 5 mg/kg-day and above in dams at PND 22 after exposure from GD 7 through PND16 or
17 fRamh0i etal.. 20181. In addition, Ramh0i etal. f20181 also reported statistically significant
(p < 0.001) decreases in free T4 in the F1 offspring born from these PFHxS-exposed dams, with free
T4 decreases at >5.0 mg/kg-day at both the end of exposure, PND16 or 17 (26%-32% decrease),
and when pups were euthanized at PND22 (26%-71% decrease). Total T4 assay measurements are
more reliable that those provided by the assays available to measure free T4 in rodents as these are
insufficiently sensitive to measure the very small quantity of unbound (ie 'free') T4 in circulation
and therefore less reliable than total T4 measurements (personal communication with Mary
Gilbert, EPA, ORD). For this reason, total, but not free, T4 was moved forward for POD and
candidate value derivation.
Two studies measured T3 in serum (Ramh0i etal.. 2020: NTP. 2018a). NTP (2018a)
observed a statistically significant and dose-dependent decrease (p < 0.05) in serum T3 levels in
male, but not female, SD rats at >0.625 mg/kg-day (p < 0.01). Ramh0i etal. (2020) analyzed
samples taken in Ramh0i etal. f 20181 and observed a significant decrease in serum T3 in Wistar rat
dams atthe highest tested dose: 19% decrease at 25 mg/kg-day (p < 0.001) measured on PND 22
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after exposure from GD 7 through postnatal day 16 or 17. Overall, for TH changes, findings for both
T4 and T3 in nonpregnant adult females were relatively insensitive as compared with adult males
and thus set aside from further consideration.
Butenhoff et al. f20091 reported increased incidences of hypertrophy/hyperplasia in the
thyroid. In this 44-day exposure study, Butenhoff et al. f20091 observed increased incidences of
hypertrophy (characterized as "minimal") of thyroid follicular epithelial cells in adult male rats that
were exposed to 0.3 mg/kg-day PFHxS and an increase in "moderate" hypertrophy at the 10 mg/kg-
day PFHxS dose for up to 44 days. Hypertrophy was not observed in control animals. Decreased
thyroid hormone levels are judged relevant to human health, given the many similarities in the
production, regulation, and functioning of thyroid hormones between rodents and humans fVansell.
2022: Stagnaro-Green and Rovet. 2016: Dong etal.. 2015: Navarro etal.. 2014: Rovet. 2014: Berbel
etal.. 2010: Morreale de Escobar et al.. 2008: Cuevas etal.. 2005: Rovet. 2005: Zoeller and Rovet.
2004: Hood and Klaassen. 2000: Hood etal.. 1999a: Hood etal.. 1999b). In addition, rodents are
known to be more sensitive to increases in thyroid follicular hypertrophy and hyperplasia than
humans, and thus the observed changes in thyroid hormone levels (which are not known to suffer
from this same limitation) were preferentially advanced over these histopathological changes for
deriving points of departure and the increases in thyroid hypertrophy/hyperplasia were not
considered further (see Table 5-1).
Table 5-1. Endpoints considered for dose-response modeling and derivation
of points of departure for thyroid effects in animals
Endpoint
Study reference
and confidence
Exposure route
and duration
Test strain,
species, and
sex
POD
Derivation
Notes
Decreased Total
T4
NTP (2018a). high
confidence
Gavage, 28 d
Rat/SD/Male
Yes
Dose-dependent effects
were observed across
sexes, but responses were
much more sensitive in
males, even after
considering sex-dependent
PK differences.
Ramh0i et al.
(2018), high
confidence
Exposure in utero
and lactation
GD7-PND16 or 17;
measurements
taken at PND
16/17
Rat/Wistar/Fl
Combined3
Yes
Dose-dependent effects in
combined serum from
(male plus female)
offspring were consistent
across timepoints.
Responses in dams were
Exposure in utero
and lactation
GD7-PND16/17
measurements
taken at PND 22
Rat/Wistar/Fl
Combined3
Yes
much less sensitive.
Gavage
Rat/Wistar/PO
Female
No
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Endpoint
Study reference
and confidence
Exposure route
and duration
Test strain,
species, and
sex
POD
Derivation
Notes
GD7-PND16; Free
T4 measured at
GD15
Gavage
GD7-PND 16; Free
T4 measured at
PND 22
Rat/Wistar/PO
Female
No
Decreased T3
NTP (2018a). high
confidence
Gavage, 28 d
Rat/SD/Male
Yes
Dose-dependent effects
were only observed in male
rats.
Ramh0i et al.
(2020), high
confidence
Gavage
GD7-PND16/17;
T3 measured at
PND 22
Rat/Wistar/PO
Female
No
Decrease was only
observed in exposed dams
and F1 pups at the highest
dose. Responses in dams
were much less sensitive.
In utero and
lactation
GD7-PND16/17
measurements
taken at PND
16/17
Rat/Wistar/Fl
Combined3
Yes
Thyroid
histopathology
Butenhoff et al.
(2009)
44 d
Rat/SD/PO Male
No
Concern for potential
reduced human relevance
as compared with TH
measures.
aRamh0i et al. (2018) reported as combined male and female fetal and juvenile rats; individual female pup data not
reported. TH= Thyroid hormone.
Immune effects
Consistent findings of reduced antibody responses from human epidemiological studies
provide moderate human evidence of immunosuppression with PFHxS exposure. This conclusion is
based primarily on two medium confidence studies (reported in three publications) in children
(Grandiean etal.. 2017b: Grandiean etal.. 2017a: Grandiean etal.. 20121. supported by additional
studies in children and adults (Kielsen etal.. 2016: Stein etal.. 2016b: Stein etal.. 2016a: Granum et
al.. 20131. Although there may be some residual uncertainty regarding the potential for
confounding by other PFAS, including PFOA and PFOS, the evidence overall supports a concern for
immunosuppression in PFHxS-exposed humans.
The two medium confidence studies of antibody response following vaccination are birth
cohorts of similar populations in the Faroe Islands (see Table 5-2) (Grandiean etal.. 2017b:
Grandiean etal.. 2017a: Grandiean etal.. 20121. Across these studies, PFHxS exposure was
measured during gestation, and at 18 months and 5, 7, and 13 years, and measures of antibody
levels were taken at 5, 7, and 13 years for both diphtheria and tetanus. Inverse associations,
indicating immunosuppression, were generally observed between PFHxS exposure and antibody
levels across different combinations of timing of exposure and outcome measures, and similar
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findings were reported for other long-chain PFAS. However, there are a minority of combinations
for which positive associations (higher antibody levels with higher PFHxS exposure) were observed
(not statistically significant). This heterogeneity in results does not have a clear biologic
explanation and the relevant etiologic window of exposure for this outcome is not known, although
f Grandiean etal.. 2017bl noted that associations were generally weaker for two early life windows
of PFHxS when exposures were measured at 18 months (as compared to PFHxS exposures
measured prenatally or in early infancy) antibodies were measured at age 5 years, and for PFHxS
exposures measured at 5 years of age and antibodies measured at age 5 years. Still, given the
inverse associations observed for most of the exposure-outcome combinations and the low risk of
bias in these studies (sensitivity was the primary concern), they are considered appropriate
candidates for POD derivation. In Budtz-largensen and Grandiean f20181. the study authors
performed benchmark dose modeling for a subset of the data presented in these papers, specifically
antibody levels at age 7 and PFHxS concentrations at age 5, and antibody levels at age 5
(prebooster) and perinatal PFHxS concentrations. The authors selected these combinations due to
the strong inverse associations and because they are reasonably representative of the study results
across exposure/outcome combinations, so after review of the BMD methods, their exposure-
response results were used to inform the benchmark dose analyses. EPA selected a different BMR in
deriving the BMDs and BMDLs (see Appendix E, Section 1 for more details).
Table 5-2. Endpoints considered for dose-response modeling and derivation
of points of departure for immune (decreased serum antibody) effects in
humans
Study
reference and
confidence
Antibody type;
Measurement timing
POD derivation
Notes
Antibody
concentrations
for diphtheria
and tetanus
Grandiean et al.
(2012) and Grandiean
etal. (2017a):
Grandiean et al.
(2017b): medium
confidence
No
Effect was generally coherent with epidemiological
evidence for other antibody effects. However, while
these results contribute to understanding the hazard
for PFHxS, the analytic models in these specific
publications used log-transformed exposure and log-
transformed outcome variables and such log-log
models cannot be used for BMD calculations and thus
PODs were not derived.
Budtz-
J0rgensen and
Grandiean
(2018) using
data from
Grandiean et
al. (2017b):
(Grandiean et
al., 2017a):
Grandiean et
al. (2012)
Decreased serum anti-
tetanus antibody
concentration in
children at age 7 yrs and
PFHxS measured at age
5 yrs
Yes
Both vaccine antibody types and the two exposure
and outcome measurement timing combinations
were generally coherent with the broader
epidemiological evidence for antibody effects.
Results were based on analytic models using log-
transformed outcome and untransformed exposure
which were suitable for BMD calculations and POD
derivations (see Appendix D1 for more details on
BMD modeling results).
Decreased serum anti-
diphtheria antibody
concentration in
children at age 7 yrs and
PFHxS measured at age
5 yrs
Yes
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Study
reference and
confidence
Antibody type;
Measurement timing
POD derivation
Notes
medium
confidence
Decreased serum anti-
tetanus antibody
concentration in
children at age 5 yrs and
PFHxS measured
perinatally
Yes
Decreased serum anti-
diphtheria antibody
concentration in
children at age 5 yrs and
PFHxS measured
perinatally
Yes
Developmental effects
Although the human evidence on developmental effects was highly uncertain and ultimately
judged as slight (see Section 3.2.3), the database includes several well-conducted medium and high
confidence epidemiological studies reporting birth weight deficits of varying magnitude in male or
female neonates or both. A meta-analysis of the available studies showed a small but statistically
significant decrease in birth weight per each ln-unit increase in PFHxS exposure (see Section 3.2.3;
and Appendix C). However, in contrast to previous meta-analyses for PFOS and PFOA fDzierlenga et
al. f20201 and Steenland etal. f201811. differences in detected deficits based on sample timing were
evident for early sampled studies as well as high and medium/high confidence studies combined.
Notably large effects were seen for postpartum measures, but this stratum was based on
considerably fewer studies. This suggests that studies based on post-partum samples may be most
prone to potential bias from pregnancy hemodynamics, but the meta-analytical data are indicative
of complex patterns of influence due to pregnancy hemodynamic that are not completely
understood. Nevertheless, the apparent influence of pregnancy hemodynamics introduces
considerable uncertainty in the interpretation of these associations of evidence of PFHxS-induced
developmental effects and was a major contributing factor in the overall evidence integration
judgment for this health effect (see Section 3.2.3). Despite these important concerns regarding
sample timing, as noted above, derivation of a POD(s) for developmental outcomes was considered
potentially informative to toxicity value derivation for thyroid or immune effects.
For developmental effects, 22 epidemiology studies evaluated associations between PFHxS
exposure and fetal growth restriction, seven of which were considered high confidence. Three of
these high confidence studies measured maternal blood levels of PFHxS in the first trimester (Buck
Louis etal.. 2018: Sagiv etal.. 2018: Manzano-Salgado etal.. 2017al. One study each sampled in the
second fShoaff etal.. 20181 third trimester fValvi etal.. 20171. while two studies collected samples
across multiple trimesters (Starling etal.. 2017: Bach etal.. 20161.
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Five of the seven high confidence studies reported adverse associations between birth
weight and PFHxS, with no evidence of adverse associations reported in Valvi etal. (20171 or Sagiv
etal. ("20181.
Thus, the five high confidence studies considered for illustrative use in dose-response
analysis (see Table 5-3) were: Buck Louis etal. f20181: Shoaffetal. f 20181. Starling etal. f 20171.
Manzano-Salgado etal. f20191. and Bach etal. f20161. These studies showed consistent results
especially when re-expressed on the ln-unit scale for consistency (range: -12 to -22 grams per each
ln-unit PFHxS increase).
As previously described, while no toxicity value for developmental effects will be derived
due to the high uncertainty of any such value as compared with values based on thyroid or immune
effects, the PODs for developmental effects are still useful for the purposes delineated above in
Section 5.1.
Table 5-3. Mean birth weight deficit studies considered for dose-response
modeling and derivation of points of departure for developmental effects in
humans
Study reference
and confidence
Population-overall
population, sex-
specific and all
births vs. term
births only
PFHxS
biomarker
sample timing
POD
derivation
Notes
Buck Louis et al.
(2018): high
confidence
Overall population;
term births
Trimester 1
Yes
Effect size was large in magnitude; study showed
some association for other endpoints such as
birth length deficits. Maternal samples were
collected during trimester one (range: 10-13.9
wks) which should minimize the pregnancy
hemodynamic impact.
Manzano-Salgado
et al. (2019): high
confidence
Overall population;
all births
Trimester 1
Yes
Results based on continuous exposure increases
were moderate in magnitude and consistent
with larger birth weight deficits based on
categorical data; study showed some coherence
across other endpoints such as postnatal growth
and other fetal growth indices. Maternal
samples were collected during trimester one
(mean = 12.3 wks) which should minimize the
pregnancy hemodynamic impact. Multi-PFAS
models were developed.
Shoaff et al. (2018):
high confidence
Overall population;
term births
Trimester 2
Yes
Effect size was moderate in magnitude; study
showed some coherence across other endpoints
such as postnatal growth. Although the mean
reported sampling period was 18 wks, it was
variable across study participants (range: 16-40
wks) which may make a subset of these data
(i.e., those with later sampling) more prone to
potential bias from pregnancy hemodynamic
changes.
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Study reference
and confidence
Population-overall
population, sex-
specific and all
births vs. term
births only
PFHxS
biomarker
sample timing
POD
derivation
Notes
Starling et al.
(2017): high
confidence
Overall population;
term births
Trimesters 2-3
Yes
Effect size was moderate in magnitude. Multi-
PFAS models were developed. Median of 27
gestational wks of sampling. Concerns regarding
the influence of pregnancy hemodynamic
changes are generally greater for any trimester
three PFHxS measures, but authors statistically
adjusted for sampling timing.
Bach et al. (2016):
high confidence
Overall population;
sex-specific; term
births
Trimester 1-2
Yesa
Results based on continuous exposure increases
were moderate in magnitude and consistent
with larger deficits based on categorical data and
across sexes; this study also showed some
coherence across other endpoints such as head
circumference. Maternal samples were largely
collected during trimesters one and two (mode:
12 wks) which may minimize the pregnancy
hemodynamic impact.
Valvi et al. (2017):
high confidence
Sex-specific; all
births
Trimester 3
No
Study reported increased birth weight (i.e., no
adverse effects).
Sagiv et al.
(2018): high
confidence
Sex-specific; term
births
Trimester 1
No
Study showed mixed results.
aStudy reported sex-specific findings that boys have larger deficits compared with girls. The associations between
exposure and birth weight were not consistent across quantiles of exposures in girls. Results based overall
population were used for POD derivation since the general population was the target population.
Estimation or Selection of Points of Departure (PODs)
Benchmark dose modeling
Consistent with EPA's Benchmark Dose Technical Guidance Document fU.S. EPA. 20121. the
BMD and 95% lower confidence limit on the BMD (BMDL) were estimated using a BMR to
represent a minimal, biologically significant level of change. The BMD Technical Guidance fU.S. EPA.
20121 sets up a hierarchy by which benchmark responses (BMRs) are selected. The first and
preferred approach uses a biological or toxicological basis to define what minimal level of response
or change is biologically significant. In the absence of information regarding the level of change that
is considered biologically significant, a BMR of 1 SD from the control mean for continuous data or a
BMR of 10% extra risk for dichotomous data is used to estimate the BMD and BMDL. The BMRs
selected for dose-response modeling of PFHxS-induced health effects are listed in Table 5-4 along
with the rationale for their selection. Further details, including the modeling output and graphical
results for the model selected for each endpoint, can be found in Appendix D. When dose-response
modeling was not feasible, or adequate modeling results were not obtained, no-observed-adverse-
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1 effect level (NOAEL) or lowest observed adverse effect level (LOAEL) values were identified and
2 used as the POD.
Table 5-4. Benchmark response levels selected for BMD modeling of PFHxS
outcomes
Endpoint
BMR
Rationale
Thyroid effects
Decreased serum-total T4
1 standard deviation
No information is readily available that allows
for determining a minimally biological
significant response. The BMD Technical
Guidance (U.S. EPA, 2012) recommends a BMR
based on 1 SD for continuous endpoints when
biological information is not sufficient to
identify the BMR.
Decreased serum-total T3
Immune effects
Decreased antibody concentrations for
diphtheria and tetanus in children
Zi standard deviation
No information is readily available that allows
for determining a minimally biological
significant response. The BMD Technical
Guidance (U.S. EPA, 2012) recommends a BMR
based on 1 SD for continuous endpoints when
biological information is not sufficient to
identify the BMR. Diphtheria and tetanus are
serious and sometimes fatal infections. In
addition, childhood represents a sensitive
lifestage when immunosuppression during the
developmental stage may impede children's
ability to protect against a range of immune
hazards. Given the potential severity of this
outcome, a BMR of 1/2 SD was selected (see
additional discussion in Appendix D, Section
1.1).
Developmental Effects
Decreased birth weight in humans
5% extra risk of exceeding adversity
cutoff (hybrid approach)
A 5% extra risk is commonly used for
dichotomous developmental endpoints as
recommended by Benchmark Dose Technical
Guidance (U.S. EPA, 2012). For birth weight, a
public health definition of low birth weight
exists, and the hybrid approach was used to
estimate the dose at which the extra risk of
falling below that cutoff equaled 5% (see
Appendix D).
3 When modeling was feasible, the estimated BMDLs were used as PODs (see Table 5-5).
4 Further details, including the modeling output and graphical results for the model selected for each
5 endpoint, can be found in Appendix D. For the modeling of immune effects, potential confounding
6 by other PFOS and PFOA was considered in the POD derivation by comparing the effect estimates
7 from the analyses in and BMDLs for PFHxS from single-PFAS models against those from multi-PFAS
8 models controlling for PFOS and PFOA in analyses by Budtz-largensen and Grandiean f20181 (see
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1 Appendix D, Section 1 for details). When dose-response modeling was not feasible, or adequate
2 modeling results were not obtained, NOAEL or LOAEL values were identified based on biological
3 rationales when possible and used as the POD. The PODs (based on BMD modeling or
4 NOAEL/LOAEL selection) for the endpoints advanced for dose-response analysis are presented in
5 Table 5-5 alongside the corresponding PODhedS derived based on the PK extrapolations as
6 described in Section 3.1.6.
Table 5-5. Points of Departure (PODs) considered for the derivation of PFHxS
candidate toxicity values
Endpoint
Study/confidence
Species/
Sex
POD type
(% change if
NOAEL or
LOAEL)
Free Acid
POD
(mg/kg-d)f
DDEFC
Free Acid
PODHEDd
(mg/kg-d)
Thyroid
Decreased Total T4
28-d study
NTP (2018a). hiah
confidence
SD rat, male
LOAEL3 (-44%)
0.684
5.73 x 10"3
3.92 x 10"3
Multigenerational
Study
Ramh0i et al.
(2018). hiah
confidence
Wistar rat,
Combined Fi
(PND 16/17)
NOAELb (+4%)
0.051
4.88 x 10"4
2.49 x 10"5
Decreased T3
Multigenerational
Study
Ramh0i et al.
(2020). hiah
confidence
Wistar rat,
Combined Fi
(PND 16/17)
NOAELb(-7%)
5.5
4.88 x 10"4
2.68 x 10"3
28-d study
NTP (2018a). hiah
confidence
SD rat, male
LOAEL3 (-22%)
0.684
5.73 x 10"3
3.92 x 10"3
Endpoint
Study/Confidence
Species/Sex
POD type
(% change if NOAE
or LOAEL)
POD
(mg/kg-d)
PODinternal
(mg/L)
PODhe^
(mg/kg-d)
Immune (developmental)
Decreased serum
anti-tetanus
antibody
concentration in
children at age 7
and PFHxS cone
measured at age 5
Budtz-J0rgensen
and Grandiean
(2018): Grandiean
et al. (2012).
medium confidence
Human
(children)/both
BMDLy2SD
e
2.82 x 10"4
1.16 x 10"s
Decreased serum
anti-diphtheria
antibody
concentration in
children at age 7
and PFHxS cone
measured at age 5
Budtz-J0rgensen
and Grandiean
(2018): Grandiean
et al. (2012).
medium confidence
Human
(children)/both
BMDLy2SD
e
3.00 x 10"4
1.23 x 10"s
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Decreased serum
anti-tetanus
antibody
concentration in
children at age 5
and PFHxS cone
measured
perinatally
Budtz-J0rgensen
and Grandiean
(2018): Grandiean
et al. (2012).
medium confidence
Human
(children)/both
BMDL/2sd
e
1.44 x 10"2
5.90 x 10"7
Decreased serum
anti-diphtheria
antibody
concentration in
children at age 5
and PFHxS cone
measured
perinatally
Budtz-J0rgensen
and Grandiean
(2018): Grandiean
et al. (2012).
medium confidence
Human
(children)/both
BMDL/2sd
e
1.37 x 10"2
1.01 x 10"6
Developmental8
Decreased birth
weight
Bach et al. (2016).
high confidence
Human
(newborn)/Both
BMDL5Er , Hybrid
__e
1.12 x 10"3
8.29 x 10"s
Buck Louis et al.
(2018). hiah
confidence
Human
(newborn)/Both
BMDL5Er , Hybrid
__e
1.71 x 10"3
1.27 x 10"7
Manzano-Salgado
et al. (2019), hiah
confidence
Human
(newborn)/Both
BMDL5Er , Hybrid
__e
1.33 x 10"3
9.84 x 10"s
aNo models provided adequate fit; therefore, a freestanding LOAEL, no NOAEL was identified as there were
statistically significant effects in the lowest dose.
bNo models provided adequate fit; therefore, NOAEL approach was used.
Tor thyroid effects, PODhed= POD x DDEF, where the DDEF corresponding to the rat sex for the observation is
taken from Error! Reference source not found.Table 3-7; the lower DDEF for female rats used for observations in
combined sex groups.
dFor immune and developmental effects observed at PND 16/17 in rats or associated with serum concentrations
measured in children at age 5 PODHEowas calculated assuming steady-state serum concentrations using CLfor
human males and older women, since the endpoint is assumed to depend on serum concentrations in the
offspring, for which the lower clearance (not including menstrual fluid loss) is relevant. For effects observed at
birth or associated with perinatal maternal serum concentrations, CL for humans included menstrual fluid loss,
since maternal serum concentrations throughout pregnancy are similar to or below pre-pregnancy
concentrations, which result from the total clearance of the reproductive age woman.
e BMD modeling was done on serum concentrations and hence there was no POD based on external dose.
fPOD for PFHxS free acid were calculated by taking the LOAEL or NOAEL and multiplying by the ratio of potassium
salt/ molecular weight of the free acid.
g Although PODs were derived for five birth weight studies (see above), there was less uncertainty in three
developmental epidemiological studies noted here with earlier maternal biomarker sampling (Manzano-Salgado
et al., 2019; Buck Louis et al., 2018; Bach et al., 2016).
Derivation of Candidate Lifetime Toxicity Values for the Reference Dose (RfDJ
1 As discussed, below the developmental period is recognized as a susceptible lifestage when
2 exposure during a critical time window is more relevant to the induction of adverse effects than
3 lifetime exposure. Thus, the derivation of a lifetime value for developmental thyroid and immune
4 endpoints following PFHxS exposure is supported. Exposure during pregnancy was also considered
5 a potentially susceptible lifestage. Consistent with EPA guidelines fU.S. EPA. 19941. the thyroid
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hormone PODs following 28-day PFHxS exposure in adult SD rats were not considered for
derivation of candidate lifetime values given the high degree of uncertainty associated with using
PODs from a 28-day rodent study to protect against effects observed in a chronic setting. However,
these endpoints were considered for the derivation of the subchronic RfD (see Section 5.2.2).
Overall, the developmental immune endpoints from epidemiological studies and thyroid endpoints,
specifically decreases in T3 and total T4, from a multigenerational rodent study of PFHxS, were
preferentially advanced for the derivation of candidate lifetime values.
For developmental immune effects, PODhed values were derived for decreased serum
antibody levels (for both diphtheria and tetanus) in children (male and female) at different timing
of exposure and outcome measurement combinations, specifically antibody levels at age 7 and
PFHxS concentrations at age 5, and antibody levels at age 5 and perinatal PFHxS concentrations
fBudtz-largensen and Grandiean. 20181 (see Table 5-5). The BMDLy2sD(HED) of 1.16 x 10~8 mg/kg-day
for decreased serum anti-tetanus antibody concentrations at age 7 and PFHxS measured at age 5 is
selected for the derivation of osRfDs for immune effects. Confidence in the BMDL estimate was
highest (medium confidence) for this endpoint in comparison with other exposure-outcome
combinations evaluated by Grandiean etal. (2012) and Budtz-l0rgensen and Grandiean (2018)
based on a better fit model for PFHxS in the single-PFAS model and less uncertainty with respect to
potential confounding with other co-occurring PFAS (i.e., PFOS and PFOA) (see Appendix D,
Sectionl.l for more details). The BMDLy2sD(HED) of 1.23 x 10~8 mg/kg-day for decreased serum anti-
diphtheria antibody concentrations at age 7 and PFHxS measured at age 5 is also selected for the
derivation of osRfDs for immune effects. Confidence in this BMDL estimate was somewhat lower
[medium/low confidence) for this endpoint than for anti-tetanus antibody concentrations at age 7
(see Appendix D, Sectionl.l for more details). Further, although both tetanus and diphtheria are
rare in the United States, tetanus remains more of a concern primarily among older adults, who are
unvaccinated or inadequately vaccinated and therefore are at higher risk of disease and mortality
fLiang etal.. 20181. The estimated BMDLy2sD (2.82 x 10~4 mg/L) for this endpoint in the single-PFAS
model is at about the 10th percentile of the observed distribution. No information was available to
judge the fit of the model in the range of the BMDLs, but the BMD and BMDL were both within the
range of observed values and the model fit PFHxS well (see Appendix D, Section 1.1 for more
details). The fact that the derived PODhed for immune effects on both tetanus and diphtheria
antibody concentrations at the same ages are relatively close (1.16 x 10~8 mg/kg-day versus
1.23 x 10"8 mg/kg-day) lends support to the choice of the PODhed of 1.16 x 10~8 mg/kg-day for
decreased serum anti-tetanus antibody concentrations at age 7 and PFHxS measured at age 5 for
the derivation of the osRfD.
For thyroid osRfD, PODhed values were derived for decreased total thyroxine (T4) as well as
decreased triiodothyronine (T3) in a multigenerational reproductive study, with exposure
including all of gestation fRamhai etal.. 2020: Ramhai etal.. 20181 and a 28-day comprehensive
toxicity study in rats fNTP. 2018al (see Table 5-5). The PODhed of 2.49 x 10"5 for decreased total T4
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in combined Fi Wistar rats is selected for the derivation of osRfD for thyroid effects as it was the
most sensitive and reliable measure of thyroid hormone function (see Table 5-5). As described
previously, although candidate toxicity values were not derived for developmental effects
(decreased birth weight), PODs for this outcome were derived as they were considered informative
of the magnitude of effects relevant to susceptible lifestages and may help inform uncertainty factor
selection for developmental immune effects and thyroid effects.
Under EPA's A Review of the Reference Dose and Reference Concentration Processes (U.S. EPA.
2002) and Methods for Derivation of Inhalation Reference Concentrations and Application of
Inhalation Dosimetry (U.S. EPA. 1994). five possible areas of uncertainty and variability were
considered in deriving the candidate values for PFHxS. An explanation of these five possible areas
of uncertainty and variability and the values assigned to each as a designated uncertainty factor
(UF) to be applied to the candidate PODhed values are listed in Table 5-6, below.
Table 5-6. Uncertainty factors for the development of the lifetime RfD for
PFHxS
Value
Justification
UFa
l
A UFa of 1 is applied to the POD derived from developmental immune effects as these responses
were observed in epidemiological studies.
3
For thyroid effects, a UFa of 3 is applied to account for uncertainty in characterizing the
pharmacokinetic and pharmacodynamic differences between mice or rats and humans following
oral PFHxS exposure. Some aspects of the cross-species extrapolation of pharmacokinetic
processes have been accounted for using a DDEF to convert external doses from rodents to
administered doses in humans; however, residual uncertainty related to potential
pharmacodynamic differences remains.
UFh
10
A UFh of 10 is applied for developmental immune and thyroid effects. This is to account for
interindividual variability in humans in the absence of quantitative information on potential
differences in pharmacokinetics and pharmacodynamics relating to PFHxS exposure in humans.
(See discussion below for additional details).
UFs
1
A UFs of 1 is applied to reduced antibodv responses in children (Budtz-J0rgensen and Grandiean,
2018; Grandiean et al., 2012). The developmental period is recognized as a susceptible lifestage
when exposure during a critical window of development is more relevant than lifetime exposure
in adulthood (U.S. EPA, 1991). Additional considerations for the UFS for immune effects are
discussed below.
1
A UFs of 1 is applied to thyroid effects observed in the Fl animals from reproductive study
(Ramh0i et al., 2018); the developmental period is a susceptible lifestage where exposure during
certain time windows (e.g., pregnancy and gestation) is more relevant to the induction of
developmental effects than lifetime exposure (U.S. EPA, 1991).
UFl
1
A UFl of 1 is applied for LOAEL-to-NOAEL extrapolation when the POD is a BMDL as is the case for
developmental immune endpoint or POD is a NOAEL as is the case for the thyroid endpoint.
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Value
Justification
UFd
3
A UFD of 3 is applied to account for deficiencies and uncertainties in the database. Although
limited, the evidence base in laboratory animals consists of high/medium confidence short-term
studies in rodents and a high confidence developmental study in mice. The database for PFHxS
also includes several high/medium confidence epidemiological studies most informative for
immune and developmental effects, which are sensitive effects of PFHxS exposure. However,
uncertainties remain regarding the lack of studies examining effects with long-term exposure in
adults—including in women of reproductive age (which may have increased susceptibility),
studies of potential multigenerational effects, and studies of postnatal development,
neurotoxicity, and thyroid toxicity during developmental lifestages. In all, the data are too sparse
to conclude with certainty that the quantified developmental effects are likely to be the most
sensitive; thus, a UFD of 1 was not selected. However, a UFD of 10 was also not selected given the
availability of data from well-conducted studies on a range of health outcomes in multiple
species, including sensitive evaluations of developmental and immune endpoints in humans. See
discussion below for additional details.
UFc
See
Table 5-
8
Composite Uncertainty Factor = UFa x UFh x UFs x UFl x UFd
As described in EPA's A Review of the Reference Dose and Reference Concentration Processes
fU.S. EPA. 20021. the interspecies uncertainty factor (UFa) is applied to account for extrapolation of
animal data to humans, and accounts for uncertainty regarding the pharmacokinetic and
pharmacodynamic differences across species. As is usual in the application of this uncertainty
factor, the pharmacokinetic uncertainty is mostly accounted for through the application of
dosimetric approaches for estimation of HEDs. This leaves some residual uncertainty around the
pharmacokinetics and the uncertainty surrounding pharmacodynamics. For developmental
immune effects, a UFa = 1 was applied to the POD as these responses were observed in
epidemiological studies. For thyroid effects, a UFa = 3 was applied to the POD derived from rodent
studies to account for interspecies uncertainty. While uncertainty in the pharmacokinetic processes
has largely been accounted for by using a DDEF to convert external rodent doses to human
administered doses, a UFa = 3 was applied to address the remaining pharmacokinetic uncertainty
and to address the pharmacodynamic uncertainty in extrapolating those effects to humans (see
Uncertainty in HED Calculations for more details.).
For developmental immune effects in children, a UFh of either 3 or 10 was considered.
Specifically, it can be argued that the PODs are derived from susceptible individuals because
children's immune systems are not fully formed and are presumably more sensitive to these effects
than most other populations, and thus, the UFh should be reduced (although uncertainty regarding
differences across individuals exposed during this sensitive lifestage would still remain). However,
a counter argument is that currently there are no data to compare the responses in children with
other populations or lifestages, so it is unclear whether these individuals are indeed particularly
susceptible to these specific effects. As described in U.S. EPA f20201. other factors, in addition to
lifestage, may increase susceptibility, including: demographics, genetic variability, health status,
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behavior or practices, and social determinants. Ultimately, since the current evidence is insufficient
to address these uncertainties, a UFh of 10 is applied for developmental immune effects. For thyroid
effects, a UFh of 10 is applied to address differences due to intraspecies variability, including
potentially more sensitive or severe effects in susceptible populations or lifestages.
The duration extrapolation factor (UFS) accounts for the uncertainty in extrapolating from
less than chronic PFHxS exposure to lifetime exposure. A UFS = 1 was applied to the PODs for
thyroid effects as the selected POD was derived from a reproductive study with exposure
encompassing the critical window of gestation (Ramh0i etal.. 20181. This developmental window is
recognized as a susceptible lifestage when exposure is more relevant to the induction of
developmental effects than lifetime exposure fU.S. EPA. 19911. The reduced antibody responses
were measured in children 5-7 years of age, which also constitutes a sensitive lifestage. However,
given the slow clearance rates for this chemical, particularly in humans (see Table 3-5), PFHxS is
expected to accumulate in the body through adulthood. Therefore, it is plausible that longer
exposure durations can result in effects at lower exposure levels. Although the MOA for PFHxS-
induced immunosuppressive responses in humans is unknown, early-life exposures may alter the
immune system and lead to unpredictable outcomes later in life or during other susceptible
lifestages of reduced immunocompetence such as pregnancy, advanced lifestages, or
immunocompromised states flPCS. 20121 that show increased sensitivity with continuous, longer-
term exposures. Still, given the expectation that the children and their mothers have been exposed
to elevated levels of PFHxS for many years, the observed effects on immune response are
considered the result of a cumulative, prolonged PFHxS exposure to the subjects from conception
until the age when the response was evaluated. Further, the consequences of perturbed immune
system function (in this case, suppressed antibody responses leading to potentially increased risk
of disease) during development are expected to be generally more severe and longer lasting that
those that manifest in healthy adults. Thus, a UFS of 1 was considered appropriate.
The database uncertainty factor (UFd) is applied to account for the potential of deriving an
under-protective reference value as a result of incomplete characterization of a chemical's toxicity
(U.S. EPA. 20021. For PFHxS, a UFd of 3 was selected to account for deficiencies and uncertainties in
the database. Although limited, the evidence base in laboratory animals consists of high/medium
confidence short-term studies in rodents and a high confidence developmental study in mice. The
database for PFHxS also includes several high/medium confidence epidemiological studies most
informative for immune and developmental effects, which are sensitive effects of PFHxS exposure.
However, uncertainties remain regarding the lack of studies examining effects with long-term
exposure in adults—including in women of reproductive age (which may have increased
susceptibility), studies of potential multigenerational effects, and studies of postnatal development,
neurotoxicity, and thyroid toxicity during developmental lifestages. Typically, the specific study
types lacking in a chemical's database that influence the value of the UFd to the greatest degree are
developmental toxicity and multigenerational reproductive toxicity studies. While the PFHxS
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database does include high confidence reproductive/developmental toxicity studies in rats and
mice, these only span one-generation. Therefore, despite their quality, these studies fail to cover
potential transgenerational impacts of longer-term exposures evaluated in two-generation studies.
The availability of a two-generation multigenerational reproductive study could result in reference
values below those currently derived for PFHxS. However, the concern over a lack of two-
generation study in the available literature is diminished when the PFHxS, PFDA, PFOA, and PFOS
evidence bases are considered together. Although limited in their ability to assess reproductive
health or function, measures of possible reproductive toxicity occurred at doses equal to or higher
than those that resulted in effects in other organ systems (e.g., thyroid, liver) when measured after
exposure to PFHxS in utero through PND 22 fRamhai etal.. 20181. Similar results were observed for
the animal databases for PFOA and PFOS indicating reproductive effects were not uniquely
sensitive markers of toxicity for these long-chain PFAS fATSDR. 2018b! Further, no notable male or
female reproductive effects were observed in epidemiological or toxicological studies investigating
exposure to PFHxS fMDH. 2019], Given these overall uncertainties with the database, a 3-fold UF
was applied.
The uncertainty factors described in Table 5-6 and the text above were applied and the
resulting candidate values are shown in Table 5-7. The candidate values are derived by dividing the
PODhed by the composite uncertainty factor:
Candidate values for PFHxS = PODhed + UFc.
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Table 5-7. Lifetime candidate values for PFHxS
Endpoint
Study/
confidence
Strain/
species/sex
Free Acid
PODhed
(mg/kg-d)
UFa
UFh
UFs
UFl
UFd
UFc
Candidate
value
(mg/kg-d)
Thyroid
Decreased Total T4
Ramh0i et al. (2018),
high confidence
Wistar rat, combined Fi
Wistar rat,
Combined Fi
(PND 16/17)
2.49 x 10"5
3
10
1
1
3
100
2 x 10"7
Decreased T3
Multigenerational Study
Ramh0i et al. (2020),
high confidence
Wistar rat,
Combined Fi
(PND 16/17)
2.68 x 10"3
3
10
1
1
3
100
3 x 10"5
Developmental Immune Effects
Decreased serum
anti-tetanus
antibody
concentration in
children at age 7
Budtz-J0rgensen and
Grandiean (2018):
Grandiean et al.
(2012): medium
confidence
Human
(children),
male and
female
1.16 x 10~s
1
10
1
1
3
30
4 x 10"10
Decreased serum
anti-diphtheria
antibody
concentration in
children at age 7
Budtz-J0rgensen and
Grandiean (2018):
Grandiean et al.
(2012): medium
confidence
Human
(children),
male and
female
1.23 x 10"s
1
10
1
1
3
30
4 x 10"10
Selection of Lifetime Toxicity Value(s)
Selection of organ-/system-specific oral reference doses fosRfDs)
1 Table 5-7 shows osRfDs selected for the individual organ systems identified in Section 3.2
2 (i.e., thyroid and developmental immune effects).
3 The value of 4 x 10"10 mg/kg-day (rounded from 3.9 x 10"10 and, separately, 4.1 x 10"10
4 mg/kg-day in Table 5-7 for decreased serum anti-tetanus and anti-diphtheria antibody
5 concentrations in children (male and female) at age 7 years and PFHxS measured at age 5 years
6 from the Grandiean etal. f20121 and Budtz-largensen and Grandiean f20181 was selected as the
7 osRfD for developmental immune effects. The respective PODhed values for these two endpoints
8 (decreased anti-tetanus as well as decreased anti-diphtheria antibodies) were close in value
9 (1.16 x 10"8 versus 1.23 x lO"8, respectively) and the candidate values round to the same toxicity
10 value.
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For the thyroid effects, an osRfD of 2 x 10"7 mg/kg-day (rounded from 2.49 x 10"7 in Table
5-7) was selected based on decreased total T4 in F1 pups exposed to PFHxS in the Ramh0i et al.
f2018I As there was no other reason to select one POD over the other (e.g., different levels of
confidence in the POD calculations), the more sensitive POD for total T4 was selected over the POD
for T3.
The confidence decisions about the study, evidence base, quantification of the POD, and
overall RfD for these organ-/system-specific values are described in detail inTable 5-8, along with
the rationales for selection of confidence levels. In deciding overall confidence, confidence in the
evidence base is prioritized over the other confidence decisions. The overall confidence in the
osRfDs for both immune and thyroid effects is judged as medium. Selection of the overall RfD is
described in the following section.
Table 5-8. Confidence in the organ-/system-specific RfDs for PFHxS
Confidence
categories
Designation
Discussion
Thyroid 2 x 10-7 RfD = mg/kg-d
Confidence in
study3 used to
derive osRfD
High
Confidence in Ramh0i et al. (2018) was hiah and is based on a well-designed experimental design
using established accroaches, recommendations, and best oractices (HAWC link).
Confidence in
evidence base
supporting this
hazard
Medium
Confidence in the evidence base for thyroid effects is medium based on consistent findings in
animals of decreases in T3 and T4 in adult and iuvenile rats in the absence of effects on TSH (NTP,
2018a: Ramh0i et al., 2018), but with unexplained inconsistency in the available epidemiological
studies and other uncertainties (see Table 3-6).
Confidence in
quantification of the
PODhed
Medium
Confidence in the quantification of the PODhed and osRfD is medium given POD was based on a
NOAEL (data did not fit BMD models) and because a DDEF was applied to estimate the PODhed- The
uncertainty associated with the use of a DDEF is less than the uncertainty introduced from the use
of a NOAEL because the DDEF is based on PFHxS-specific pharmacokinetic data (see Uncertainty in
HED Calculations). Considering these limitations, confidence in the POD was medium.
Overall confidence
in osRfD
Medium
The overall confidence in the osRfD is medium. The medium confidence in the POD derivation is
offset by the high confidence in the study and medium confidence in the evidence base for thyroid
effects.
Developmental Immune RfD = 4 x io~10
Confidence in
study3 used to
derive osRfD
Medium
Confidence in Grandiean et al. (2012): Budtz-J0rgensen and Grandiean (2018) was rated as
medium based on some concerns for sensitivity from narrow exposure contrast, which decreases
confidence in null associations onlv (HAWC link).
Confidence in
evidence base
supporting this
hazard
Medium
Confidence in the evidence base for immune effects is medium based on consistent findings of
reduced antibody responses from two medium confidence birth cohort studies (Grandiean et al.,
2017b: Grandiean et al., 2017a: Grandiean et al., 2012) and a low confidence study in adults
(Grandiean et al., 2017b). Limitations in this evidence base include the lack of epidemiological
studies in adults or long-term/chronic studies in animals, and a general lack of studies examining
effects on the immune system across different developmental immunotoxicity categories,
including sensitization and allergic response and autoimmunity and autoimmune disease.
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Confidence
categories
Designation
Discussion
Confidence in
quantification of the
PODhed
Medium
The POD is based on BMD modeling within the range of the observed data and a BMDL/2sd estimate
that is associated with little uncertainty due to potential confounding by PFOA or PFOS (see
Appendix D, Section 1.1 for more details). The PODhedS for decreased anti-tetanus and decreased
anti-diphtheria antibodies were close in value (1.16 x 10~S vs. 1.23 x 10~S, respectively) which
increases confidence in the quantification of the PODhed- There is uncertainty as to the most
sensitive window of vulnerability with respect to the exposure/outcome measurement timing
(BMDs/BMDLs were estimated from PFHxS levels measured at age 5 or perinatally and anti-tetanus
antibody concentrations measured at age 7 or 5) and the effect on antibodies at age 7 were more
sensitive that those measured at age 5 (see Appendix D, Section 1.1 for more details); however,
Grandiean et al. (2017b) reported that estimated PFOS and PFOA "concentrations at 3 m and 6
m showed the strongest inverse associations with antibody concentrations at age 5 yrs, particularly
for tetanus." Thus, it is possible that adverse effects of PFHxS during infancy could be more
sensitive than between ages 5 and 7 yrs.
Overall confidence
in osRfD
Medium
The overall confidence in the osRfD is medium and is driven by medium confidence in the evidence
base for immune effects, the quantification of the POD, and the study used for BMD modeling.
aAII study evaluation details can be found on HAWC.
Selection of overall reference dose fRfDl and confidence statement
Table 5-9. RfD and organ-/system-specific RfDs for PFHxS
Reference Dose (RfD
Basis
RfD (mg/kg-d)
Confidence
Immune (developmental)
effects
4 x io10
Medium
Organ-/system-specific RfDs
osRfDs)
Organ / System
Outcomes and studies
PODhed (mg/kg-d)
UFC
osRfD (mg/kg-d)a
Confidence
Thyroid
Decreased serum Total T4 in
F1 Wistar rats
(Ramh0i et al., 2018)
2.49 x 10"5
100
2 x 10"7
Medium
Immune
(developmental)
Decreased serum anti-
tetanus and anti-diphtheria
antibody concentrations
measured in children at age
7 with PFHxS exposure
measured at age 5
Grandiean et al. (2012):
Budtz-J0rgensen and
Grandiean (2018): Budtz-
J0rgensen and Grandiean
(2018): Grandiean et al.
(2012)
1.16 x 10"9 and 1.23 x
io-9
30
4 x IO"10
Medium
aThe RfD or osRfD values for different salts of PFHxS would be calculated by multiplying the RfD or osRfD values for
the free acid of PFHxS (i.e.., the toxicity values in the table above) by the ratio of molecular weights. For example,
. ,, , . . . ... MW apotassium salt 438 . „ „ p. . . .
for the potassium salt the ratio would be: = — = 1.095. This same method of conversion
MW free acid 400
can be applied to other salts of PFHxS, such as the ammonium or sodium salts, using the corresponding molecular
weights.
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From the identified human health effects of PFHxS and derived osRfDs for thyroid and
developmental immune effects (see Table 5-10), an RfD of 4 x 10-10 mg/kg-day was selected based
on decreased serum anti-tetanus and anti-diphtheria antibody concentrations in children. As
described in Table 5-9, confidence in the RfD is medium, based on medium confidence in the
developmental immune osRfD. This osRfD is based on the two lowest PODhedS available on PFHxS
immune effects (an evidence based interpreted with medium confidence) using a study considered
medium confidence. The selected osRfD is based on effects in children and expected to be protective
across all lifestages. The selection considered both available osRfDs as well as the overall
confidence and composite uncertainty for those osRfDs. The thyroid osRfD was based on
application of a composite uncertainty threefold greater than that applied in deriving the immune
osRfD. Further, when comparing the sensitivity of thyroid and immune osRfDs, the thyroid value is
over 3,000-fold higher. Had the osRfD for thyroid effects been chosen as the overall RfD, this would
have raised concerns over the ability of the thyroid RfD to be protective against potential immune
effects (and it may not be protective against other developmental effects, such as decreased birth
weight (see Table 5-6) if those other effects could be reliably quantified). Selection of the RfD on the
basis of developmental immune effects is presumed to be protective of possible thyroid and other
potential adverse health effects (including potential effects on birth weight) in humans. Finally,
since the developmental immune osRfD is based on effects observed in males and females, the
overall RfD would be protective for both sexes.
5.2.2. Subchronic Toxicity Values for Oral Exposure (Subchronic Oral Reference Dose [RfD])
Derivation
In addition to providing an RfD for lifetime exposure in health systems, this document also
provides an RfD for less-than-lifetime ("subchronic") exposures. These candidate subchronic
toxicity values were based on the endpoints and PODs in Table 5-5 including the shorter duration
studies that were not advanced for consideration in developing the lifetime RfD. Given that the
immune and thyroid effects considered for the RfD were observed after exposure to PFHxS during
susceptible lifestages, these endpoints were also considered for the derivation of candidate
subchronic toxicity values, applying identical uncertainty factors to those used for the lifetime RfDs
(see Table 5-6).
The datasets advanced for derivation of the subchronic toxicity values were selected on the
basis of several considerations, including whether there is an endpoint with less uncertainty and/or
greater sensitivity, and whether the endpoint is protective of both sexes and all lifestages.
Ultimately, similar to the datasets advanced for the lifetime thyroid osRfD derivation, decreased
total T4 and decreased T3 endpoints from the Ramh0i etal. (2018) study was advanced over
identical endpoints from the high confidence NTP (2018a) study. This is because the Ramh0i et al.
f20181 study included exposure to PFHxS during gestation, this exposure is interpreted as a critical
sensitive window for effects on the developing thyroid system. Further, consistent with the decision
when estimating the lifetime osRfD, the POD for total T4 was advanced over the POD for T3 from
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Ramh0i etal. (20181 given the increased sensitivity of the POD. The NOAELhed of 2.49 x 10"5 mg/kg-
day for decreased total T4 in F1 generation rats in the Ramh0i etal. (20181 study was selected for
the thyroid subchronic osRfD (see Table 5-5). The UFs applied to the derivation of a subchronic RfD
thyroid POD in rat offspring are the same as those applied in the derivation of lifetime RfD values.
See Table 5-6 for details.
Likewise, the same datasets on developmental immune effects were advanced for
derivation of the subchronic osRfD, with the same inherent confidence and uncertainties.
Selection of Subchronic Toxicity Value(s)
As described above, subchronic osRfDs associated with each health effect are presented as
they may be useful for certain decision purposes (i.e., site-specific risk assessments with less-than-
lifetime exposures). The osRfD values selected were associated with decreased serum anti-tetanus
antibody concentrations for immune effects and decreased total T4 levels for thyroid effects.
Confidence in each osRfD is described in Table 5-8 and consider confidence in the study used to
derive the quantitative estimate, the overall health effect, specific evidence base, and quantitative
estimate for each osRfD.
Selection of Subchronic RfD and Confidence Statement
Organ-/system-specific subchronic RfD values for PFHxS selected in the previous section
are summarized in Table 5-10.
Table 5-10. Subchronic RfD organ-/system-specific RfD values for PFHxS
Subchronic Reference Dose (RfD)
Basis
RfD (mg/kg-d)
Confidence
Immune (developmental)
effects
4 x io10
Medium
Subchronic organ-/system-specific RfDs
Organ / system
Outcomes and studies
PODHED(mg/kg-
d)
UFc
osRfD (mg/kg-d)
Confidence
Thyroid
Decreased serum T4
(free) in F1 Wistar rats
Ramh0i et al. (2018)
2.49 x 10"5
(NOAEL)
100
2 x 10"7
Medium
Immune
(developmental)
Decreased serum anti-
tetanus and anti-
diphtheria antibody
concentrations
measured in children at
age 7 with PFHxS
exposure measured at
age 5 Grandiean et al.
1.16 xl0"s and
1.23 x 10"s
(BMDUsd)
30
4 x 10"10
Medium
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Subchronic Reference Dose (RfD)
Basis
RfD (mg/kg-d)
Confidence
Immune (developmental)
effects
4 x io10
Medium
Subchronic organ-/system-specific RfDs
Organ / system
Outcomes and studies
PODHED(mg/kg-
d)
UFc
osRfD (mg/kg-d)
Confidence
(2012): Budtz-
J0rgensen and
Grandiean (2018):
Grandiean et al.
(2012): Budtz-
J0rgensen and
Grandiean (2018)
1.16-1.23 x 10"9
From the identified targets of PFHxS toxicity and derived subchronic osRfDs (see Table 5-
10), an RfD of 4 x 10-10 mg/kg-day based on decreased serum anti-tetanus and diphtheria antibody
concentrations in children is selected for less-than-lifetime exposure. Confidence in the RfD is
medium, based on medium confidence in the immune osRfD, as described in Table 5-8. The
considerations for selecting the immune osRfD for the lifetime RfD are the same as those applied in
selecting the subchronic RfD.
5.2.3. Inhalation Reference Concentration (RfC) Derivation
No studies examining inhalation effects of short-term, subchronic, chronic, or gestational
exposure for PFHxS in humans or animals have been identified, precluding the derivation of an RfC.
5.3. CANCER TOXICITY VALUES
Considering the limitations in the PFHxS evidence base on cancer (see Section 3.3) and in
accordance with the Guidelines for Carcinogen Risk Assessment fU.S. EPA. 20051. EPA concluded
that based on the available evidence, a classification of "Inadequate Information to Assess
Carcinogenic Potential" of PFHxS in humans. The lack of adequate carcinogenicity data for PFHxS
precludes the derivation of quantitative estimates of cancer for either oral (e.g., an oral slope factor
[OSF]) or inhalation (e.g., an inhalation unit risk [IUR]) PFHxS exposure.
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This document is a draft for review purposes only and does not constitute Agency policy.
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