vvEPA
EPA/600/R-23/061
United States	. . ,
Environmental Protection	iviarcnzuzj
Agency	www.epa.gov/isa
Integrated Science
Assessment for Lead
Appendix 5: Renal Effects
External Review Draft
March 2023
Health and Environmental Effects Assessment Division
Center for Public Health and Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency

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DISCLAIMER
1	This document is an external review draft for peer review purposes only. This information is
2	distributed solely for the purpose of predissemination peer review under applicable information quality
3	guidelines. It has not been formally disseminated by the Environmental Protection Agency. It does not
4	represent and should not be construed to represent any agency determination or policy. Mention of trade
5	names or commercial products does not constitute endorsement or recommendation for use.
6
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DOCUMENT GUIDE
This Document Guide is intended to orient readers to the organization of the Lead (Pb) Integrated Science
Assessment (ISA) in its entirety and to the sub-section of the ISA at hand (indicated in bold). The ISA consists of
the Front Matter (list of authors, contributors, reviewers, and acronyms), Executive Summary, Integrated Synthesis,
and 12 appendices, which can all be found at https://cfpub.epa.gov/ncea/isa/recordisplav.cfm?deid=357282.
Front Matter
Executive Summary
Integrative Synthesis
Appendix 1. Lead Source to Concentration
Appendix 2. Exposure, Toxicokinetics, and Biomarkers
Appendix 3. Nervous System Effects
Appendix 4. Cardiovascular Effects
Appendix 5. Renal Effects
Appendix 6. Immune System Effects
Appendix 7. Hematological Effects
Appendix 8. Reproductive and Developmental Effects
Appendix 9. Effects on Other Organ Systems and Mortality
Appendix 10. Cancer
Appendix 11. Effects of Lead in Terrestrial and Aquatic Ecosystems
Appendix 12. Process for Developing the Pb Integrated Science Assessment
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CONTENTS
LIST OF TABLES	5-v
LIST OF FIGURES 	5-vi
ACRONYMS AND ABBREVIATIONS 	5-vii
APPENDIX 5 RENAL EFFECTS	5-1
5.1	Introduction and Summary of the 2013 Integrated Science Assessment	5-1
5.2	Scope	5-3
5.3	Renal Disease and Histology	5-4
5.3.1	Epidemiologic Studies of Kidney Disease	5-4
5.3.2	Toxicological Studies of Kidney Histology	5-10
5.4	Glomerular Filtration Rate and Other Markers of Kidney Function	5-12
5.4.1	Glomerular Filtration Rate	5-13
5.4.2	Albumin, Creatinine, and Albumin-to-Creatinine Ratio	5-17
5.4.3	Uric Acid and Urea	5-21
5.4.4	Proteinuria and Hematuria	5-24
5.4.5	N-Acetyl-p-D-Glucosaminidase and p2-Microglobulin	5-25
5.4.6	Toxicological Studies of Other Indicators of Kidney Function	5-26
5.5	Toxicological Studies of Metal Co-Exposures with Pb	5-27
5.6	Activation of Renin-Angiotensin-Aldosterone System	5-27
5.7	Renal Outcomes Among Children 	5-28
5.7.1 Summary of Renal Outcomes Among Children	5-30
5.8	Reverse Causality	5-31
5.8.1 Summary of Reverse Causality	5-33
5.9	Biological Plausibility	5-34
5.10	Summary and Causality Determination	5-37
5.11	Evidence Inventories - Data Tables to Summarize Study Details	5-43
5.12	References	5-77
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LIST OF TABLES
Table 5-1 Summary of evidence indicating a causal relationship between Pb
exposure and renal effects.	5-41
Table 5-2 Epidemiologic studies of Pb exposure and kidney disease.	5-43
Table 5-3 Animal toxicological studies of Pb exposure and kidney histology.	5-48
Table 5-4 Epidemiologic studies of Pb exposure and estimated glomerular filtration
rate.	5-52
Table 5-5 Animal toxicological studies of Pb exposure and glomerular filtration rate.	5-58
Table 5-6 Epidemiologic studies of Pb exposure and albumin, creatinine, and
albumin-to-creatinine ratio.	5-59
Table 5-7 Animal toxicological studies of Pb exposure and albumin and creatinine. 	5-63
Table 5-8 Epidemiologic studies of Pb exposure and uric acid.a	5-65
Table 5-9 Animal toxicological studies of Pb exposure and measures of uric acid and
urea.	5-67
Table 5-10 Epidemiologic studies of Pb exposure and proteinuria and hematuria.	5-69
Table 5-11 Epidemiologic studies of Pb exposure and renal tubular impairment
markers.51	5-70
Table 5-12 Animal toxicological studies of Pb exposure and other markers of kidney
function. 	5-71
Table 5-13 Epidemiologic studies of Pb exposure and renal outcomes in children.	5-74
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LIST OF FIGURES
Figure 5-1 Modification of association between blood Pb (quartile 1-3 versus quartile
4) and chronic kidney disease incidence.	5-6
Figure 5-2 Kaplan-Meier curve comparing low to high body Pb burden and the
development of either a two-fold increase in serum creatinine from
baseline, the need for long-term hemodialysis, or death among type 2
diabetics.	5-8
Figure 5-3 Association between blood Pb and renal outcomes among patients with
type 2 diabetes.	5-9
Figure 5-4 Associations between biomarkers of Pb exposure and estimated
glomerular filtration rate. 	5-14
Figure 5-5 Association between blood Pb and hyperuricemia among men and women,
Korea National Health and Nutrition Examination Survey, 2016.	5-22
Figure 5-6 Associations between natural log-transformed blood Pb (0-4 (j,g/dL) and
serum uric acid and elevated serum uric acid (>5.5 mg/g).	5-29
Figure 5-7 Subgroup analysis between blood Pb and serum uric acid among
adolescents, National Health and Nutrition Examination Survey 1999-
2006.	5-30
Figure 5-8 Locally weighted smoothing plot of adjusted associations between blood
Pb levels (with [left panel] and without [right paned] logarithmic
transformation) and serum creatinine. 	5-32
Figure 5-9 Potential biological pathways for renal effects following Pb exposure.	5-35
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ACRONYMS AND ABBREVIATIONS
P2-MG	p2-microglobulin
AAS	angiotensin-aldosterone system
ACE	angiotensin-converting enzyme
ACR	albumin-to-creatinine ratio
ALB	albumin
AQCD	Air Quality Criteria Document
BLB	body lead burden
BLL	blood lead level
BMI	body mass index
BUN	blood urea nitrogen
CI	confidence interval
CKD	chronic kidney disease
CKD-EPI	Chronic Kidney Disease Epidemiology
Collaboration
CKiD	Chronic Kidney Disease in Children
d	day, days
DKD	diabetic kidney disease
EAF	electric arc furnace
EBE	early biological effect
EDTA	ethylenediaminetetraacetic acid
eGFR	estimated glomerular filtration rate
ESRD	end-stage renal disease
ETAAS	Electrothermal Atomic Absorption
Spectrometry
EWAS	environment wide association study
F	female
FDR	false discovery rate
GFAAS	Graphite Furnace Atomic Absorption
Spectrometry
GFR	glomerular filtration rate
GW	gestation week
FlbAlc	hemoglobin Ale
F1DL	high-density lipoprotein
hr	hour, hours
FIR	hazard ratio
ICP-MS	Inductively Coupled Plasma Mass
Spectrometry
IQR	interquartile ratio
ISA	Integrated Science Assessment
KIM-1	Kidney Injury Molecule 1
KNHANES	Korea National Health and Nutrition
Examination Survey
KRIEFS	Korean Research Project on the
Integrated Exposure Assessment to
Hazardous Materials for Food Safety
MCDS	Malmo Cancer and Diet Study
MCDS-CC	cardiovascular cohort of the Malmo
Cancer and Diet Study
MDRD	Modification of Diet in Kidney Disease
mo	months
M	male
M/F	male/female
MONICA	Monitory of Trends and Cardiovascular
Disease
NAG	N-acetyl-P-D-glucosaminidase
NAS	Normative Aging Study
NGAL	neutrophil gelatinase-associated
lipocalin
NHANES	National Health and Nutrition
Examination Survey
NO3	nitrate
OR	odds ratio
Pb	lead
PbO	lead oxide
Pb(N03)2	lead nitrate
PECOS	Population, Exposure, Comparison,
Outcome, and Study
PND	postnatal day
Q	quartile
RAAS	renin-angiotensin-aldosterone system
SD	standard deviation
SE	standard error
SES	socioeconomic status
SPHERL	Study for Promotion of Health in
Recycling Lead
SUA	serum uric acid
T	tertile
UA	uric acid
wk	week, weeks
WHO	World Health Organization
yr	year, years
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APPENDIX 5
RENAL EFFECTS
Summary of Causality Determinations for Pb Exposure and
Renal Effects
This appendix characterizes the scientific evidence that supports causality
determinations for lead (Pb) exposure and renal effects. The types of studies evaluated
within this appendix are consistent with the overall scope of the ISA as detailed in the
Process Appendix (see Section 12.4). In assessing the overall evidence, the strengths
and limitations of individual studies were evaluated based on scientific considerations
detailed in Table 12-5 of the Process Appendix (Section 12.6.1). More details on the
causal framework used to reach these conclusions are included in the Preamble to the
ISA (U.S. EPA. 2015). The evidence presented throughout this appendix supports the
following causality conclusions:
Outcome
Causality Determination
Reduced Kidney Function
Causal
The Executive Summary, Integrated Synthesis, and all other appendices of this Pb ISA
can be found at https://cfpub.epa.gov/ncea/isa/recordisplav.cfm?deid=357282.
5.1 Introduction and Summary of the 2013 Integrated Science
Assessment
In the 2013 Lead Integrated Science Assessment U.S. EPA (2013) the epidemiologic and
toxicological evidence was judged to be "suggestive of a causal relationship" between Pb exposures and
reduced kidney function among adults. Prospective epidemiologic studies in adult men in the general
population (Tsaih et al.. 2004; Kim et al.. 1996) supported the temporal relationship between Pb exposure
and reduced kidney function at blood Pb levels (BLLs) <10 (ig/dL. As indicated by the male cohort of the
Normative Aging Study (NAS), Kim et al. (1996) noted an increase in serum creatinine with increasing
BLLs. Similarly, Tsaih et al. (2004) indicated a 0.009 mg/dL (95% confidence interval [CI]: -0.0008,
0.0188) annual increase in serum creatinine over 10 years, with a one-unit increase in natural log-
transformed tibia Pb. Similar findings were observed when considering patella Pb as well. These
population-based prospective cohort studies showed a longitudinal association between BLLs and
increases in serum creatinine after adjustment for key potential confounders. In an additional prospective
study, higher baseline BLLs were associated with greater chronic kidney disease (CKD) progression over
time (i.e., reduced estimated glomerular filtration rate [eGFR] -0.040 mL/min/1.73 m2 [95% CI: -0.0072,
-0.008]) in CKD patients (Yu et al.. 2004). Re-examination of a study from the 2006 Pb Air Quality
Criteria Document (AQCD) (U.S. EPA. 2006a) provided data to conclude that in a population with likely
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higher past exposures to Pb, a 10-fold increase in concurrent blood Pb was associated with a decrease in
estimated creatinine clearance and that a 3.5 (ig/dL increase in blood Pb had the same negative impact on
eGFR as did an increase of 4.7 years in age or 7 kg/m2 in body mass index (Akesson et al.. 2005). Cross-
sectional studies of the general adult population added support to the associations observed in prospective
epidemiologic studies. The majority of cross-sectional studies reported associations between higher
measures of Pb exposure and impaired renal function (Navas-Acicn et al.. 2009; Muntner et al.. 2005;
Muntner et al.. 2003). Other studies in clinical trials of CKD patients treated with
ethylenediaminetetraacetic acid (EDTA) chelation provide supportive results; however, these studies had
uncertainties concerning small sample sizes and lack of researcher blinding.
With respect to the animal toxicology evidence, the 2013 Pb ISA noted that at BLLs > 30 (ig/dL,
there was clear evidence that Pb exposure caused changes to kidney morphology and function (Khalil-
Manesh et al.. 1992b; Khalil-Manesh et al.. 1992a). Evidence for functional changes in animals following
lower Pb exposures resulting in BLLs < 20 (ig/dL was generally not available. At BLLs between 20 and
30 (ig/dL, studies with various exposure scenarios and in various lifestages provided evidence for reduced
kidney function measures (e.g., decreased creatinine clearance, increased serum creatinine, increased
blood urea nitrogen [BUN]). In addition, previous reviews have clearly established that exposure to Pb
can result in the production of reactive oxygen species and markers of inflammation in the blood or
kidneys over a similar range of BLLs (see (U.S. EPA. 2013)).
However, there were important uncertainties identified in the 2013 Pb ISA. First, because
epidemiologic studies report effects in adult populations with past Pb exposures that are likely higher,
uncertainty exists as to the Pb exposure level, timing, frequency, and duration contributing to the
associations observed with blood or bone Pb levels. Second, due to the kidney's role in removing toxins
from the blood, it is plausible that reverse causality could explain the associations observed in
epidemiologic studies. While the epidemiologic and animal toxicological studies mentioned above
suggest that reverse causality does not contribute substantially to associations between higher BLLs and
reduced kidney function, reverse causation remained a plausible hypothesis. Thus, this bidirectional
relationship is possible and additional evidence was needed to fully elucidate the extent to which
diminished kidney function may itself result in increased blood or bone Pb levels.
When considered as a whole, although there was evidence of impaired kidney function in some
epidemiologic studies, as well as animal toxicological evidence of oxidative stress and impaired kidney
function providing biological plausibility for those associations, important uncertainties remained. In
particular, uncertainties related to the potential for reverse causality in epidemiologic studies and the lack
of animal toxicological studies indicating impaired kidney function at lower BLLs were noted. As a
result, the relationship between Pb exposure and reduced kidney function was judged to be suggestive of
a causal relationship.
The following sections provide an overview of study inclusion criteria for this Appendix (Section
5.2), an evaluation of the health evidence published since the 2013 Pb ISA (Sections 5.3-5.8), a summary
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of the biologically plausible pathways by which exposure to Pb could result in the health outcomes
observed in epidemiologic studies (Section 5.9), a discussion of the causal determination for Pb exposure
and renal effects (Section 5.10), tables providing toxicological and epidemiologic study-specific details
(Section 5.11), and references (Section 5.12).
5.2 Scope
The scope of this appendix is defined by Population, Exposure, Comparison, Outcome, and Study
Design (PECOS) statements. The PECOS statements define the objectives of the review and establish
study inclusion criteria, thereby facilitating identification of the most relevant literature to inform the Pb
ISA.1 In order to identify the most relevant literature, the body of evidence from the 2013 Pb IS A was
considered in the development of the PECOS statements for this Appendix. Specifically, well-established
areas of research; gaps in the literature; and inherent uncertainties in specific populations, exposure
metrics, comparison groups, and study designs identified in the 2013 Pb ISA inform the scope of this
Appendix. The 2013 Pb ISA used different inclusion criteria than the current ISA, and the studies
referenced therein often do not meet the current PECOS criteria (e.g., due to higher or unreported
biomarker levels). Studies that were included in the 2013 Pb ISA, including many that do not meet the
current PECOS criteria, are discussed in this appendix to establish the state of the evidence prior to this
assessment. With the exception of supporting evidence used to examine the biological plausibility of Pb-
associated renal effects, recent studies were only included if they satisfied all of components of the
following discipline-specific PECOS statements:
Epidemiologic Studies:
Population: Any human population, including specific populations or lifestages that might be at
increased risk of a health effect;
Exposure: Exposure to Pb2 as indicated by biological measurements of Pb in the body - with a
specific focus on Pb in blood, bone, and teeth; validated environmental indicators of Pb
exposure3; or intervention groups in randomized trials and quasi-experimental studies;
1	The following types of publications are generally considered to fall outside the scope and are not included in the
ISA: review articles (which typically present summaries or interpretations of existing studies rather than bringing
forward new information in the form of original research or new analyses), Pb poisoning studies or clinical reports
(e.g., involving accidental exposures to very high amounts of Pb described in clinical reports that may be extremely
unlikely to be experienced under ambient air exposure conditions), and risk or benefits analyses (e.g., that apply
concentration-response functions or effect estimates to exposure estimates for differing cases).
2	Recent studies of occupational exposure to Pb were considered insofar as they addressed a topic area that was of
particular relevance to the NAAQS review (e.g., longitudinal studies designed to examine recent versus historical Pb
exposure).
3	Studies that estimate Pb exposure by measuring Pb concentrations in PMio and PM2 5 ambient air samples are only
considered for inclusion if they also include a relevant biomarker of exposure. Given that size distribution data for
Pb-PM are fairly limited, it is difficult to assess the representativeness of these concentrations to population
exposure [Section 2.5.3 (U.S. EPA. 201311. Moreover, data illustrating the relationships of Pb-PMio and Pb-PM2 5
with BLLs are lacking.
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1	Comparison: Populations, population subgroups, or individuals with relatively higher versus
2	lower levels of the exposure metric (e.g., per unit or log unit increase in the exposure metric,
3	or categorical comparisons between different exposure metric quantiles);
4	Outcome: Renal effects including, but not limited to, renal function and CKD; and
5	Study Design: Epidemiologic studies consisting of longitudinal and retrospective cohort studies,
6	case-control studies, cross-sectional studies with appropriate timing of exposure for the health
7	endpoint of interest, randomized trials and quasi-experimental studies examining
8	interventions to reduce exposures.
9	Experimental Studies:
10	Population: Laboratory nonhuman mammalian animal species (e.g., mouse, rat, guinea pig,
11	minipig, rabbit, cat, dog) of any lifestage (including preconception, in utero, lactation,
12	peripubertal, and adult stages);
13	Exposure: Oral, inhalation, or intravenous routes administered to a whole animal (in vivo) that
14	results in a BLL of 30 (ig/dL or below;1'2
15	Comparators: A concurrent control group exposed to vehicle-only treatment or untreated
16	control;
17	Outcomes: Renal effects; and
18	Study Design: Controlled exposure studies of animals in vivo.
5.3 Renal Disease and Histology
19	The primary function of the kidneys is to filter waste from the body while maintaining
20	appropriate levels of water and essential chemicals, such as electrolytes. Kidney disease occurs when
21	kidney function becomes impaired and cannot perform these functions adequately. Section 5.3.1 evaluates
22	the epidemiologic evidence for kidney disease and exposure to Pb. Kidney disease is often accompanied
23	by changes in the structure of the kidney. For example, glomerular or tubular hypertrophy can be used as
24	an indication of kidney dysfunction and disease. Similarly, changes in the number or morphology of renal
25	tubules or podocytes can also be indicative of kidney disease. Thus, Section 5.3.2 presents the animal
26	toxicological studies that have examined histological sections of kidneys for abnormalities and changes in
27	structure following Pb exposure.
5.3.1 Epidemiologic Studies of Kidney Disease
28	The 2013 Pb IS A (U.S. EPA. 2013) and 2006 Pb AQCD (U.S. EPA. 2006b) highlighted several
29	studies indicating an association between biomarkers of Pb exposure and indicators of decreased renal
30	function and progression of CKD. Several recent studies specifically evaluated biomarkers of reduced
1	Pb mixture studies are included if they employ an experimental arm that involves exposure to Pb alone.
2	This level represents an order of magnitude above the upper end of the distribution of U.S. young children's BLL.
The 95th percentile of the 2011-2016 National Health and Nutrition Examination Survey distribution of BLL in
children (1-5 years; n = 2,321) is 2.66 (ig/dL (Eganetal.. 2021) and the proportion of individuals with BLL that
exceed this concentration varies depending on factors including (but not limited to) housing age, geographic region,
and a child's age, sex, and nutritional status.
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kidney function and the development of CKD or end-stage renal disease (ESRD). Study-specific details,
including Pb biomarker levels, study population characteristics, potential confounders, and select results
from these studies are highlighted in Table 5-2. Study details in Table 5-2 include standardized results
(kidney disease associated with a 1 (ig/dL increase in BLL or a 10 jxg/g increase in bone Pb level) as well
as results that could not be standardized with the information provided in each paper.
5.3.1.1 Chronic Kidney Disease
The 2013 Pb ISA presented a number of occupational studies evaluating the association between
Pb exposure and CKD, but the results were relatively inconsistent. More recent evidence helps to
disentangle the evidence previously presented and consistently indicates an association between
biomarkers of Pb exposure and CKD development. A study among the cardiovascular cohort of the
Malmo Cancer and Diet Study (MCDS-CC) in Malmo, Sweden evaluated the development of CKD by
assessing baseline BLLs (obtained in 1991-1994) and incident CKD (assessed in 2007-2012) (Harariet
al.. 2018). In this study, CKD was confirmed through medical records. When each individual quartile of
blood Pb was compared with the lowest, there was no association with incident CKD. However, when the
three lower quartiles (Q1-Q3 median 2.2 (ig/dL) were compared with the highest (Q4 median 4.6 |ig/dL).
an association was observed between blood Pb and CKD (hazard ratio [HR]: 1.49 [95% confidence
interval (CI): 1.07, 2.08]), while controlling for baseline eGFR in the models. This association remained
stable even after stratification by several covariates (Figure 5-1).
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Covariates
Overall
Age
Sex
Smoking
Alcohol intake
Waist circumference
Diabetes mellitus
Hypertension
Low Education
Categories
Overall
<58 years
>58 years
Female
Male
Never
Former
Current
<6.6 ^ day
>6.6 g day
<82 cm
>82 cm
No
Yes
No
Yes
No
Yes
Hazard Ratios
(95% CI)
1.49 (1.07,
1.21 (0.64,
1.61 (1.09,
1.41 (0.73,
1.58 (1.06,
1.42(0.78,
1.36(0.82,
1.56 (0.82,
1.46 (0.87,
1.53 (0.97,
1.61	(0.68,
1.46(1.01,
1.62	(1.10,
0.91 (0.44,
0.88 (0.31,
1.57(1.11,
1.79(1.07,
1.29 (0.83,
2.08)
2.28)
2.37)
2.73)
2.35)
2.58)
2.26)
2.98)
2.45)
2.41)
3.83)
2.11)
2.38)
1.89)
2.47)
2.23)
2.99)
2.00)
1
1.5
i—i—i—r
2.5 3 3.5 4
P-value
for
interaction
0.4
0.4
0.9
0.9
0.7
0.2
0.6
0.3
.6 .7 .8 .9 1
Hazard ratios (95% CI)
Cm = centimeters; g = grams.
Source: Harari et al. (2018).
Figure 5-1 Modification of association between blood Pb (quartile 1-3 versus
quartile 4) and chronic kidney disease incidence.
A case-control study in Taiwan matched healthy controls by age and sex to those with CKD (Wu
et al.. 2019). In this study, CKD was defined as an eGFR < 60 mL/min/1.73 m2 for at least 3 consecutive
months. When compared with the lowest tertile (<2.784 (ig/dL) of blood Pb, the odds of CKD increased
with each increasing tertile of red blood cell Pb. Compared with the lowest tertile, the highest tertile
(>4.635 (ig/dL) of blood Pb, was associated with an odds ratio (OR) of 6.48 (95% CI: 3.23, 12.99) for
CKD. Since Pb can lead to oxidative damage in the kidney, the authors tested the association between red
blood cell Pb and CKD modified by selenium. Selenium has antioxidant properties and selenium
homeostasis is maintained by the kidney. When examined, serum selenium appeared to modify this
association.
A large National Health and Nutrition Examination Survey (NHANES, 1999-2016) analysis
included an environment wide association study (EWAS) on 262 environmental chemicals (Lee et al..
2020). Individual CKD components including albuminuria (urinary albumin [ALB]-to-creatinine ratio
[ACR] > 30 mg/g) and reduced eGFR (<60 mL/min/1.73 m2 based on the Chronic Kidney Disease
Epidemiology Collaboration (CKD-EPI) calculation) and a set of composite CKD measures were used as
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outcome measures in this study. A discovery data set was created by combining five NHANES cycles
(1999-2000, 2003-2004, 2007-2008, 2011-2012, and 2015-2016). Individual regression analyses were
conducted for each survey cycle and combined using a random-effects meta-analysis. Chemicals with a
false discovery rate (FDR) < 1% in the meta-analysis were considered as potential risk factors for CKD.
Identified chemicals were then reanalyzed in the rest of the survey cycles (2001-2002, 2005-2006, 2009-
2010, and 2013-2014) and referred to as the "validation" set. Blood Pb was analyzed in both the
discovery and validation sets for reduced eGFR and the composite CKD definitions (the FDR for
albuminuria was >1%). When assessing a composite CKD measurement (ACR > 300 mg/g and eGFR
<60 mL/min/1.73 m2, ACR >30 mg/g and eGFR < 45 mL/min/1,73m2 or eGFR <30 mL/min/1.73 m2),
there was a positive association with blood Pb in the discovery (OR: 1.73 [95% CI: 1.54, 1.95]) and
validation (OR: 1.61 [95% CI: 1.35, 1.90]) sets. In contrast, Kim et al. (2015) cross-sectionally evaluated
the association between blood Pb and self-reported CKD using the Korea National Health and Nutrition
Examination Survey (KNHANES 2011) and found a null association (OR: 1.05 [95% CI: 0.85, 1.30])
after controlling for confounders. The association remained null after stratifying by diabetic status.
5.3.1.2 End-Stage Renal Disease
ESRD is diagnosed when CKD progresses to a level in which renal replacement therapy
(hemodialysis or transplantation) is required. Sommar et al. (2013) combined studies including the
Northern Sweden Health and Disease Study and MCDS. The Northern Sweden Health and Disease Study
incorporates data from three different cohorts: the Vasterbotten Intervention Project, the Northern Sweden
World Health Organization (WHO) Monitory of Trends and Cardiovascular Disease (MONICA) study,
and Mammography Screening Project. All included studies collected baseline data on erythrocyte Pb
levels. Cases of ESRD were identified through the Swedish Renal Registry and linked with erythrocyte
Pb data from the above cohorts. Controls were selected from within each of the respective studies and
were matched on age, sex, cohort, and time of sampling. In a combined cohort of over 130,000
individuals, 118 cases of ESRD were identified (with 378 controls). Here, a one-unit (fig/dL) increase in
erythrocyte Pb was associated with an OR of 1.14 (95% CI: 1.03, 1.26).
5.3.1.3 Diabetic Nephropathy
Diabetic nephropathy refers to a reduction in kidney function leading to ESRD among those with
Type 1 or II diabetes mellitus. The development of ESRD or CKD is more likely among those with
diabetes mellitus, compared with the general population. Huang et al. (2013) evaluated type 2 diabetics
with stage 3 diabetic nephropathy (eGFR range: 30-60 mL/min/1.73 m2). Body Pb burden (BLB) and
blood Pb were assessed in this study. A combination of X-Ray fluorescence detecting bone Pb
concentrations and calcium disodium EDTA demobilization tests are typically used to assess BLB.
Typically, a BLB < 80 |ig is considered to be within the normal range, while a BLB >600 |ig is equivalent
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to Pb poisoning. This small study (n = 89) indicated a decrease in eGFR associated with a one-unit
increase in either BLB (-0.022 mL/min/1.73 m2 [95% CI: -0.039, —0.005]) or blood Pb
(-0.298 mL/min/1.73 m2 [95% CI: -0.525, -0.071]). Additionally, there was an increased risk of the
"primary outcome" (either a two-fold increase in serum creatinine from baseline, the need for long-term
hemodialysis, or death) with a one-unit increase in Pb BLB (HR: 1.01 [95% CI: 1.01, 1.02]), and a BLB
between 80-600 pg was associated with an HR of 2.79 (95% CI: 1.25, 6.25). The Kaplan-Meier analysis
conducted within this study demonstrated that diabetic patients with higher BLB (>80 (ig) were more
likely to reach the primary outcome at an accelerated rate compared with those with lower BLB
(Figure 5-2).
13
>
it
3
10	15
Time (month)
Cum. survival (low-normal BLB)
Event times (low-normal BLB)
Cum. survival (high-normal BLB)
Event times (high-normal BLB)
BLB = body lead burden.
Source: Huang et a!. (2013).
Figure 5-2 Kaplan-Meier curve comparing low to high body Pb burden and
the development of either a two-fold increase in serum creatinine
from baseline, the need for long-term hemodialysis, or death
among type 2 diabetics.
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A recent cross-sectional study evaluated diabetic kidney disease (DKD) in those with type 2
diabetes (Hagedoorn et al.. 2020). The authors directly calculated GFR by measuring creatinine in a 24-
hour urine sample, rather than calculating eGFR from a single serum creatinine measurement. In addition,
the study also evaluated albuminuria, defined as a 24-hour urinary ALB excretion >30 mg/day. Each
doubling of blood Pb (on a log2 scale) was associated with an OR of 1.83 (95% CI: 1.07, 3.15) for
creatinine clearance < 60 mL/min/1.73 m2 and an OR of 1.75 (95% CI: 1.11, 2.74) for albuminuria. Wan
et al. (2021) cross-sectionally evaluated diabetic patients in China by evaluating the association between
BLLs and both an ACR >30 mg/g and DKD (defined as ACR > 30 mg/g or eGFR < 60 mL/min/1.73 m2).
When comparing the highest quartile of blood Pb (>3.7 (ig/dL) with the lowest quartile of blood Pb
(<1.8 (ig/dL), the odds of an elevated ACR (>30 mg/g) (OR: 1.31 [95% CI: 1.02, 1.69]) and the presence
of DKD (OR: 1.36 [95% CI: 1.06, 1.74]) were higher. The dose response indicated increased odds of
DKD with increasing blood Pb and a decrease in eGFR with each quartile increase in BLL (Figure 5-3).
High ACR
P for trend ¦ 0.026
One In BLL 5D increment
BLL Quartile 4
BLL Quartile 3
BLL Quartile 2
BLL Quartile 1
0.5 1.0 1.5
Odds ratio (95%C1)
2.0
DKD
Pfor trend = 0.011
One In BLL SD increment
BLL Quartile 4
BLL Quartile 3
BLL Quartile 2
BLL Quartile 1
0.5
1.0
1.5
2.0
Odds ratio (95%CI)
Ln ACR
One In BLL SD increment
BLL Quartile 4
BLL Quartile 3
BLL Quartile 2
BLL Quartile 1
Pfor trend < 0.001
-0,1 0.0 0.1 0.2 0.3
regression coefficients (95%CI)
0.4
eGFR
Pfor trend < 0,001
One In BLL SD increment
BLL Quartile 4
BLL Quartile 3
BLL Quartile 2
BLL Quartile 1
-6.0 -4.0 -2.0 0 2.0
regression coefficients (95%CI)
ACR = albumin-to-creatinine ratio; BLL = blood lead level; DKD = diabetic kidney disease; eGFR = estimated glomerular filtration
rate; SD = standard deviation.
Source: Wan et al. (2021).
Figure 5-3 Association between blood Pb and renal outcomes among
patients with type 2 diabetes.
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5.3.1.4
Nephrolithiasis
Nephrolithiasis, or kidney stones, can be the result of a disruption in calcium homeostasis.
Exposure to Pb, a nephrotoxicant, can potentially compete with calcium in binding to calcium-binding
receptors, leading to the development of kidney stones. A prospective study evaluated baseline BLLs and
the development of incident nephrolithiasis (verified by medical records) in a Flemish population as part
of the Cadmium in Belgium (CadmiBel) study (Hara et al.. 2016). Baseline blood Pb measurements were
obtained between 1985 and 1989, and the incidence of nephrolithiasis was measured through October
2014. Approximately half of the population (747 out of 1302) had a second blood Pb measurement
between 1991 and 2004. According to the baseline measurement, there was an increased risk of incident
nephrolithiasis for each doubling of blood Pb (HR: 1.35 [95% CI: 1.06, 1.73]). A similar risk was noted
when averaging the baseline and the follow-up BLLs (HR: 1.32 [95% CI: 1.03, 1.71]). Furthermore,
applying an additional regression dilution bias correction increased the magnitude of the baseline
association (HR: 1.44 [95% CI: 1.07, 1.93]). Conversely, anNHANES (2007-2016) analysis cross-
sectionally assessed the association between the self-reported prevalence of kidney stones and BLLs (Sun
et al.. 2019). Compared with the lowest or referent group (blood Pb: 0.05 (.ig/dL). increasing blood Pb
values corresponded to ORs indicative of a protective effect against kidney stones in this population, with
the highest blood Pb group (>5 (ig/dL) corresponding to an OR of 0.64 (95% CI: 0.46, 0.90). This
association persisted even when stratifying by sex, ethnicity, and body mass index (BMI).
5.3.1.5 Summary of Kidney Disease
The sections above present mostly positive associations between BLLs and some kidney diseases
from epidemiologic studies. More specifically, all but a single epidemiologic study demonstrated a
positive association between measures of body Pb and some measure of CKD (Lee et al.. 2020; Wu et al..
2019; Harari et al.. 2018). ESRD (Sommar et al.. 2013). and diabetic nephropathvCWan et al.. 2021;
Hagedoorn et al.. 2020; Huang et al.. 2013). However, evidence for an association between measures of
Pb and nephrolithiasis (i.e., kidney stones) was limited to a couple of studies with conflicting results (Sun
et al.. 2019; Hara et al.. 2016). Importantly, epidemiologic studies demonstrating positive associations
between measures of Pb and kidney disease were conducted in a variety of geographical areas and in
different study populations. Moreover, in general, these analyses also controlled for a number of potential
confounders, thus increasing confidence in these associations.
5.3.2 Toxicological Studies of Kidney Histology
In previous Pb ISAs, some studies reported that exposure to Pb induced changes in renal
structure. For example, Roncal et al. (2007) found that Pb increased tubulointerstitial injury and
arteriolopathy in rats. The BLL in this study was 26 (ig/dL. Moreover, Jabeen et al. (2010) reported that
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Pb exposure (no specified BLL) decreased kidney cortical thickness, decreased the diameter of renal
corpuscles, and increased renal tubular atrophy in mice. In contrast to these studies, Vvskocil et al. (1995)
reported that Pb exposure to female rats resulting in a BLL of 36 (ig/dL caused no change in kidney
function or nephrotoxicity. More information on these and other studies examining renal effects following
Pb exposure can be found in Table 4-28 of the 2013 Pb ISA (U.S. EPA. 2013).
A number of studies published since the 2013 Pb ISA with BLLs < 30 (ig/dL have examined
kidney tissue for indications of abnormalities following Pb exposure by drinking water or gavage. Basgen
and Sobin (2014) reported that in young mice, exposure to Pb leading to BLLs ranging from 2.74 (ig/dL
to 4.7 (ig/dL resulted in a statically significant glomerular volume increase (p < 0.05), but similar
numbers of podocytes and podocyte volume densities. At higher BLLs (11.7 (ig/dL to 20.3 (.ig/dL). this
change to kidney structure was not observed. With respect to glomerular components at lower BLLs, the
authors reported a statistically significant effect (p < 0.05) on mesangial volume and capillary lumen
volume, but not podocyte volume (Basgen and Sobin. 2014). Similarly, although control rats had a well-
preserved nucleus and normal tubular and glomerular morphology, renal tubules from rats exposed to Pb
(21.9 (ig/dL BLL) had irregular cell shapes, changes in cell and nuclear sizes, and minimal amounts of
cytoplasm (Alcaraz-Contreras et al.. 2016). Cells from renal tubules also displayed a loss of apical
microvilli (Alcaraz-Contreras et al.. 2016). In an additional study, Pb exposure resulting in a BLL of
-12 (ig/dL on postnatal day (PND) 21 and -23 (ig/dL on PND 30 resulted in a statistically significant
decrease (p = 0.01) of 1-a-hydroxylase at PND 21, but not PND 30 by western blot relative to controls.
These authors further noted that the western blot results were in agreement with immunohistochemistry
on kidney cells. (Rahman et al.. 2018). Shi et al. (2020) reported that kidney tissue from rats with a BLL
of -10.21 (ig/dL displayed cellular debris, tubular dilation, glomerulus hypercellularity, and other signs of
distress while control kidney tissue showed no major histopathological changes. In agreement with this
study, Laamech et al. (2016) also reported that relative to control animals, Pb-treated mice with a BLL of
18 (ig/dL displayed glomerular hypercellularity. Gao et al. (2020) similarly reported histopathological
changes consistent with damage following Pb exposure in rats. In this study, the BLL was 10.6 (ig/dL and
the authors reported congestion and vasodilation of the renal interstitium and swelling of tubules in Pb-
exposed animals while controls appeared to have normal kidney structure (Gao et al.. 2020). Likewise, Li
et al. (2017) reported hyperemic glomeruli, increased glomerular volume, and swelling of some renal
tubular epithelial cells after Pb exposure resulting in an average BLL of -30 (ig/dL, while histological
sections from the control mice were normal.
In addition to the drinking water and gavage studies described above, Andielkovic et al. (2019)
reported that Pb exposure (BLL -30 (ig/dL) resulted in acute passive kidney hyperemia, but no significant
pathologic changes following gavage. Moreover, Carlson et al. (2018) reported that in mice, exposure to
Pb by drinking water resulted in minor renal lesions that were similar to those in control mice (e.g.,
simple tubular hyperplasia) and that these lesions were not indicative of major systemic health problems.
However, it is worth noting that the BLL in this study was only 2.89 (ig/dL, and thus, extensive renal
lesions may not be expected.
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In addition to the analyses described above, recent studies have examined the effects of Pb after
inhalation exposure. Following inhalation exposure to Pb-oxide nanoparticles for 6 weeks (resulting in
-14 (ig/dL BLL), Dumkova et al. (2017) reported minor changes in kidney appearance relative to some,
but not all control mice. These changes were mainly areas of mild inflammation around the renal
corpuscles and tubules. Similarly, ultrastructural analysis of the kidneys also revealed only minor
differences between Pb-treated and control mice. However, these authors noted thicker lamina densa, and
the average distance between endothelial cell and podocyte cytoplasmic membranes increased following
Pb exposure (Dumkova et al.. 2017). In an additional study by the same author, Dumkova et al. (2020a)
used Pb nitrate nanoparticles and a longer inhalation time (11 weeks, resulting in a BLL of 8.5 (ig/dL) and
reported that there were obvious morphological changes in renal tubules when compared with control
mice. Moreover, pedicles of podocytes were reported to be irregularly arranged or lost altogether. After a
5-week clearance period, Pb levels in the kidneys and blood declined substantially (BLL 1 |ig/dL). and
there was evidence of regeneration in tubular and glomerular kidney tissue. However, in another analysis
by the same author, Dumkova et al. (2020b) reported that an 11-week exposure with Pb-oxide
nanoparticles resulted in no significant change in mouse kidney morphology when compared with
controls with BLLs as high as 17 (ig/dL. Thus, it is possible that exposure to different forms of Pb results
in differing degrees of kidney damage, but additional studies would be needed to confirm this possibility.
When considered as a whole, substantial evidence exists from studies published since the last Pb
ISA suggesting that exposures resulting in BLLs < 30 (ig/dL result in histological abnormalities in the
kidneys. Moreover, these abnormalities were reported following all tested routes of Pb exposure (i.e.,
drinking water, gavage, and inhalation). Additional information on the experimental design of more
recent renal histology studies can be found in Table 5-9.
5.3.2.1 Summary of Kidney Histology Studies
Most animal toxicological studies demonstrate that exposure to Pb results in abnormalities or
damage to kidney cells or tissue (see Section 5.3.2). Effects include changes in glomerular and nucleus
morphology, as well as changes in the amount of cellular cytoplasm. Histological effects were also
identified following both oral and inhalation exposures.
5.4 Glomerular Filtration Rate and Other Markers of Kidney
Function
The gold standard for assessing kidney function involves measurement of the GFR through
administration of an exogenous radionuclide or radiocontrast marker (e.g., 1251-iothalamate, iohexol)
followed by timed sequential blood samples or, more recently, kidney imaging, to assess clearance
through the kidneys. This procedure is invasive and time-consuming. Therefore, serum levels of
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endogenous compounds are routinely used to estimate GFR in large epidemiologic studies and clinical
settings. Creatinine is the most commonly measured endogenous compound; measures of urea (e.g.,
BUN) and uric acid (UA) have also been examined for this purpose. Increased serum concentration or
decreased kidney clearance of these markers can indicate kidney dysfunction. The main limitation of
endogenous compounds identified to date is that non-kidney factors impact their serum levels.
Specifically, since creatinine is derived from creatinine in muscle, muscle mass and diet affect serum
levels resulting in variations in different population subgroups (e.g., women and children compared with
men) that are unrelated to kidney function. Measured creatinine clearance, involving measurement and
comparison of creatinine in both serum and urine, can address this problem. However, measured
creatinine clearance utilizes timed urine collections, traditionally over a 24-hour period, and the challenge
of complete urine collection over an extended time period makes compliance difficult. Therefore,
equations to estimate kidney filtration that utilize serum creatinine but also incorporate age, sex, race,
and, in some cases, weight (in an attempt to adjust for differences in muscle mass) have been developed.
Although these are imperfect surrogates for muscle mass, such equations are currently the preferred
outcome assessment method.
5.4.1 Glomerular Filtration Rate
5.4.1.1 Epidemiologic Studies of Estimated Glomerular Filtration Rate
Glomerular filtration rate can be estimated based on a variety of different biological factors and
measured kidney function markers. An equation from the Modification of Diet in Kidney Disease
(MDRD) Study (Levey et al.. 2000; Levey et al.. 1999) calculates eGFR based on serum creatinine, race,
sex, and age. With widespread use of the MDRD equation, it became clear that the equation possibly
underestimates GFR at high levels, even in the normal range. A second, creatinine-based equation,
Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), was recently developed in order to be
more accurate than the MDRD equation, particularly at higher GFRs. This equation also incorporates
serum creatinine, race, sex, and age. However, both equations do not consider an adjustment for muscle
mass, therefore alternative biomarkers, such as cystatin C, a cysteine protease inhibitor that is filtered,
reabsorbed, and catabolized in the kidney (Fried. 2009). have also been developed. The normal range of
GFR is between 90 and 120 mL/min/1.73 m2, and GFR< 60 mL/min/1.73 m2is typically indicative of
kidney disease, while GFR <15 mL/min/1.73 m2 is a marker of renal failure.
The 2006 Pb AQCD (U.S. EPA. 2006b) and the 2013 Pb ISA (U.S. EPA. 2013) considered
several studies that evaluated associations between biomarkers of Pb exposure and eGFR specifically in
healthy adult populations as well as populations with comorbid conditions. Most studies indicated a
relationship between Pb biomarkers and decreases in eGFR. Yu et al. (2004) studied eGFR (MDRD)
among CKD patients in Taiwan and reported an association between blood Pb and an accelerated
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decrease in eGFR. The 2013 Pb ISA (U.S. EPA. 2013) highlighted several cross-sectional studies that
examined the association between BLLs and either eGFR or creatinine clearance. Navas-Acien et al.
(2009) evaluated the association between BLLs and reduced eGFR (eGFR < 60 mL/min/1.73 m2)
measured with the MDRD equation. This study reported reduced eGFR for the highest quartiles of blood
Pb (>2.4 (.ig/dL). compared with the lowest (<1.1 (ig/dL). Several recent studies have also longitudinally
and cross-sectionally evaluated the association between blood Pb and various measures of eGFR. Study-
specific details, including BLLs, study population characteristics, confounders, and select results from
these studies are highlighted in Figure 5-4 and Table 5-4. Studies in Figure 5-4 are standardized to be
interpreted as changes in eGFR associated with a 1 (ig/dL increase in BLL. Study details in Table 5-4
include standardized results as well as results that could not be standardized using the information
provided in each paper.
Study	Population	Pb distribution	Period
(jig/m3) ;
Yuetal.2004	Adult CKD patients	Mean (SD): 4.2 (2.2)	4 Years 	•	
, ,	Community residents living near an	....	I
Chung et al. 2020	, A ~	&	Geometric Mean (IQR)	-5 Years		•	 ;
electric arc turnace (bAr)	:
Distance from EAF	i
< 500 m: 2.41 (1.22-6.19)	j
500-1000 m: 2.26 (1.16-4.83)	]
1000-! 500 m: 2.12 (1.05-4.67)	j
1500-2000m: 2.23 (0.98-4.3!)	j
> 2000 m: 2.03 (1.03-4.31)	j
Chung et al. 2014	KNHANES	Geometric mean: 2.5	Concurrent	—•—	j
-8 -7 -6 -5 -4 -3 -2 -1 0
l	,	\
Change in eGFR (mL/min/t.73 mA2 body surface area) (95% CI)
per 1 ug/dL increase in blood Pb
CKD = chronic kidney disease.
Note: Studies published since the 2013 Pb ISA. Associations presented per 1 |jg/dL increase in BLL.
Figure 5-4 Associations between biomarkers of Pb exposure and estimated
glomerular filtration rate.
A recent analysis of the cardiovascular cohort of the Malmo Diet and Cancer Study (MDCS-CC)
evaluated the change in eGFR from baseline to follow-up (Harari et al.. 2018). Study participants were
initially recruited between 1991 and 1994 (mean age: 57), when BLLs and eGFR (CKD-EPI) were
initially assessed. Follow-up occurred between 2007 and 2012 (mean age: 73), when eGFR was re-
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assessed. Compared with the lowest quartile of blood Pb (Ql: 0.15-1.85 (.ig/dL). eGFR was reduced in
each of the higher quartiles. The highest quartile of blood Pb (3.3-25.8 (ig/dL) was associated with a
2.3 mL/min/1.73 m2 decrease (95% CI: -3.8, -0.73) in eGFR. Another recent longitudinal study of eGFR
and BLLs was conducted in China (Liu et al.. 2020). This study, among middle aged and older adults,
evaluated the annual decline in eGFR (CKD-EPI) from baseline (2010) through the final follow-up
(2013). Annual decline in eGFR was calculated as follows: Baseline eGFR - Follow-up eGFR)/Years of
follow-up. Compared with the lowest quartile (<0.843 (ig/dL) there was a 0.83 mL/min/1.73 m2 (95% CI:
0.31, 1.35) decline in eGFR for those in the highest quartile (>1.895 (ig/dL) per year. In addition, Chung
et al. (2020) described a longitudinal cohort of those living near an electric arc furnace (EAF) in Taiwan.
This study evaluated blood Pb assessed at baseline (measured in 2010-2011) and eGFR (method not
specified; measured in 2015-2016). At follow-up, every 1 (ig/dL increase in blood Pb was associated with
a 2.25 mL/min/1.73 m2 (95% CI: -3.50, -1.01) decrease in eGFR. A smaller prospective cohort study
(BioCycle study) evaluated several kidney markers, including eGFR (MDRD) among premenopausal
women in the United States (Pollack et al.. 2015). The BioCycle study followed women for 2 menstrual
cycles and included a total of 16 clinic visits (8 per cycle) timed to certain days of the menstrual cycle.
Each doubling of blood Pb was associated with a -3.73% change in eGFR (95% CI: -6.55, -0.83).
However, there was no association between a doubling of blood Pb and either eGFR
< 90 mL/min/1.73 m2 (OR: 0.32 [95% CI: 0.08, 1.21]), or < 60 mL/min/1.73 m2 (OR: 0.32 [95% CI: 0.08,
1.21]).
Other studies evaluating biomarkers of Pb exposure and renal function were cross-sectional in
nature. Cross-sectional studies can be useful for determining associations but are unable to establish the
temporality of the association. Recently, the Study for Promotion of Health in Recycling Lead
(SPHERL), a cross-sectional study evaluating newly hired Pb workers at battery manufacturing and Pb
recycling plants in the United States, assessed blood Pb (taken at baseline, before large potential
occupational exposure) and concurrent eGFR (CKD-EPI) (Muiai et al.. 2019). However, the SPHERL
study only included men (n = 447) and indicated null associations with eGFR, whether using creatinine,
cysteine C, or a combination of creatinine and cystatin C with increasing BLLs.
In addition, several nationally representative studies (KNHANES, NHANES) also evaluated the
association between blood Pb and eGFR. Kim and Lee (2012) evaluated BLLs and eGFR (MDRD) cross-
sectionally using KNHANES (2008-2010). Compared with the lowest quartile of blood Pb (Ql:
<1.734 (ig/dL), the highest quartile (Q4: >3.010 (ig/dL) was associated with a 3.835 mL/min/1.73 m2
decrease (95% CI: -5.730, -1.939) in eGFR. Similarly, increased odds of reduced eGFR
(<80 mL/min/1.73 m2) were observed when comparing Q4 with Ql (OR: 1.631 (95% CI: 1.246, 2.136).
In another KNHANES (2008) study, Chung et al. (2014) evaluated blood Pb and eGFR (CKD-EPI)
among adults over 20 years old. In linear models, there was a 2.61 mL/min/1.73 m2 decrease (95% CI:
-3.29, -1.97) in eGFR for each unit increase in blood Pb. Additionally, increased odds of reduced eGFR
(<60 mL/min/1.73 m2) were observed when comparing the highest quartile of blood Pb (Q4 mean:
4.13 (ig/dL) with the lowest (Ql mean: 1.38 |ig/dL). Buser et al. (2016) cross-sectionallv evaluated the
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relationship between blood Pb and eGFR (CKD-EPI) using NHANES (2007-2012). This study reported
an average 2.67 mL/min/1.73 m2 decrease (95% CI: -4.78, -0.56) in eGFR when comparing the highest
quartile (Q4: >1.82 (ig/dL) to the lowest quartile (Q1 < 0.79 (ig/dL) of blood Pb. Another large NHANES
(2003-2014) analysis (Jain. 2019) evaluated BLLs and decreased kidney function (eGFR (CKD-EPI)
< 60 mL/min/1.73 m2). Participants with BLLs >2.15 (ig/dL had greater odds (OR: 1.567 [95% CI: 1.346,
1.823]) of decreased kidney function compared with those with lower BLLs.
As described above, Lee et al. (2020) conducted an EWAS on 262 environmental chemicals using
NHANES (1999-2016). Reduced eGFR (<60 mL/min/1.73 m2, CKD-EPI) was assessed within this study.
The discovery data set was created by combining five NHANES cycles (1999-2000, 2003-2004, 2007-
2008, 2011-2012, and 2015-2016). Individual regression analyses were conducted for each survey cycle
and combined using a random-effects meta-analysis. Identified chemicals were then reanalyzed in the rest
of the survey cycles (2001-2002, 2005-2006, 2009-2010, and 2013-2014) and referred to as the
'validation' set. Blood Pb was analyzed in both the discovery and validation sets for reduced eGFR.
Overall, the association between reduced eGFR and one standard deviation (SD) increase in the log-
transformed blood Pb concentration was positive in both the discovery (OR: 1.30 [95% CI: 1.19, 1.42])
and validation (OR: 1.20 [95% CI: 1.10, 1.30]) sets.
5.4.1.2 Toxicological Studies of Glomerular Filtration Rate
In the previous Pb ISAs, some studies found that exposure to Pb-induced changes in indicators of
renal function and structure. For example, in a few studies by the same authors in rats (mean blood Pb
-30-45 (ig/dL), decreases in GFR consistent with hyperfiltration and renal hypertrophy were reported
(U.S. EPA. 2013). This is important given that kidney hyperfiltration can be seen in early-stage diabetes,
and over time, can eventually lead to decreased kidney function. Since the publication of the document,
Shi et al. (2020) reported that a 28-day Pb drinking water exposure in rats (BLL of-10.21 (ig/dL) resulted
in a statistically significant decrease in GFR. Decreases is GFR are also important, potentially indicating
progression of kidney disease and ultimately, kidney failure. Additional information on the experimental
design of this toxicological study can be found in Table 5-5.
5.4.1.3 Integrated Summary of Glomerular Filtration Rate
The 2006 Pb AQCD (U.S. EPA. 2006b) reported an association between BLLs and accelerated
decreases in eGFR in CKD patients (Yu et al.. 2004). Since the 2013 Pb ISA (U.S. EPA. 2013).
longitudinal cohort studies have all reported an association between increases in BLLs and decreases in
eGFR (Chung et al.. 2020; Liu et al.. 2020; Harari et al.. 2018; Pollack et al.. 2015). In agreement with
these longitudinal studies, cross-sectional epidemiologic studies from the previous and current review
generally reported positive associations between measures of blood or bone Pb concentrations and
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decreased eGFR(Jain. 2019; Buser et al.. 2016; Chung et al.. 2014; Kim and Lee. 2012; Navas-Acien et
al.. 2009). In agreement with the majority of the epidemiologic evidence, an animal toxicological study
reported that Pb-exposed rats had a statistically significantly lower (p < 0.05) GFR relative to control rats
(Shi et al.. 2020) (Section 5.4.1.2). When considered as a whole, there is clear evidence that exposure to
Pb can result in a decrease in eGFR.
5.4.2 Albumin, Creatinine, and Albumin-to-Creatinine Ratio
5.4.2.1 Epidemiologic Studies of Albumin, Creatinine, and Albumin-to-Creatinine
Ratio
Increased levels of creatinine in blood or serum, or decreased levels of these markers in urine can
be indicative of impaired kidney function. The 2013 Pb ISA (U.S. EPA. 2013) noted positive associations
between biomarkers of Pb exposure and serum creatinine. The ISA highlighted several longitudinal NAS
studies (Tsaih et al.. 2004; Kim et al.. 1996) and cross-sectional analyses (Akesson et al.. 2005)that
evaluated the effects of bone and blood Pb exposure on creatinine. Several of these analyses indicated
positive associations between biomarkers of Pb exposure and increases in creatinine. Kim et al. (1996)
conducted a sensitivity analysis that excluded a subset of the cohort with high past Pb exposures. The
results among individuals with past Pb exposures (measured as early as 1979) < 10 (ig/dL were consistent
with the results based on the entire cohort, suggesting that the association between blood Pb and increased
serum creatinine is not heavily influenced by high past Pb exposures. In addition, increases in urinary
ALB and ACR are also commonly used to assess kidney function. All of these measures can help indicate
how well the kidney is functioning. Recent evidence continues to generally indicate an increased
association between biomarkers of Pb exposure and increases in ALB, creatinine, and ACR. Study-
specific details, including BLLs, study population characteristics, confounders, and select results from
these studies are highlighted in Table 5-6. Study details in Table 5-6 include standardized results (ACR
associated with a 1 (ig/dL increase in BLL or a 10 jxg/g increase in bone Pb level) as well as results that
could not be standardized with the information provided in each paper.
The BioCycle study evaluated several different markers of kidney function, including eGFR
(Section 5.4.1.1) and blood Pb among premenopausal women (Pollack et al.. 2015). During the course of
two menstrual cycles (8 weeks) there was a 3.47% increase (95% CI: 0.85, 6.16) in creatinine with each
doubling of blood Pb. However, there was no associated increase in ALB (-0.38% [95% CI: -1.28, 0.52])
during the study period. This study also assessed several other biomarkers of kidney damage and
indicated no further associations between blood Pb and kidney dysfunction. In an NHANES (2007-2012)
analysis, Buser et al. (2016) evaluated urinary ALB. However, the study did not observe an association
with urinary ALB and blood Pb (6.29 mg/g creatinine (95% CI: -6.39, 20.80) when comparing the
highest quartile (Q4: >1.82 (ig/dL) with the lowest quartile (Q1 < 0.79 (ig/dL) of blood Pb.
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Muiai et al. (2019) evaluated ACR within the SPHERL study. The SPHERL study was a cross-
sectional analysis evaluating newly hired male Pb workers at battery manufacturing and Pb recycling
plants in the United States and assessed blood Pb (taken at baseline, before large potential occupational
exposure) and concurrent ACR. The authors indicated a null association between blood Pb and ACR
(-0.071 mg/g (95% CI: -0.14, 0.59), among the men enrolled in the study. Jain (2019) also assessed
decreased kidney function as ACR> 30 mg/g (measure of albuminuria) among NHANES (2003-2014)
participants. For those with BLLs >2.15 (ig/dL, increased odds (OR: 1.206 [95% CI: 1.05, 1.385]) of
ACR >30 mg/g creatinine were observed compared with those with lower BLLs. However, Zhu et al.
(2019) evaluated blood Pb and ACR within another NHANES (2009-2012) cohort and reported a null
association between quartiles of blood Pb and ACR.
In the EWAS study, described above, discovery and validation sets were created using NHANES
(1999-2016) data on 262 environmental chemicals. In addition to other indicators, the authors also
evaluated albuminuria (ACR >30 mg/g). In the discovery set, individual regression analyses were
conducted for each survey cycle and combined using a random-effects meta-analysis. Chemicals with a
FDR < 1% in the meta-analysis were considered as potential risk factors for CKD and reanalyzed in the
validation set. Blood Pb was generally associated with albuminuria measured as ACR >30 mg/g, but the
results were less consistent when the discovery set was compared with the validation set (discovery set:
OR: 1.23 [95% CI: 1.07, 1.42], validation set: OR: 1.08 [95% CI: 0.97, 1.20]). However, when measured
as ACR> 300 mg/g, greater congruence was observed between the estimates (discovery set: OR: 1.39
[95% CI: 1.22, 1.59], validation set: OR: 1.38 [95% CI: 1.16, 1.63]).
5.4.2.2 Toxicological Studies of Creatinine and Albumin
Previous Pb reviews included animal toxicological studies reporting that exposure to Pb increased
serum levels of creatinine (see Table 4-28 in the 2013 Pb ISA). For example, Berrahal et al. (2011)
reported that in rats with BLLs of 12.7 (ig/dL and 7.5 (ig/dL, serum creatinine levels were elevated. In
addition, an animal toxicology study demonstrated increased urinary ALB following exposure to Pb (BLL
of 20 (ig/dL). Studies published since the 2013 Pb ISA are presented in sections 5.4.2.2.1 and 5.4.2.2.2
below. Moreover, additional information on the experimental design of toxicological studies of creatinine
and ALB published since the 2013 Pb ISA can be found in Table 5-7.
5.4.2.2.1 Creatinine
Since the publication of the 2013 Pb ISA, rodent toxicological studies have further demonstrated
changes in creatinine levels following Pb exposure via drinking water or gavage. Zou etal. (2015)
reported a statistically significant increase in serum levels of creatinine (BLL of 21.7 (ig/dL) following a
30-day exposure in mice relative to controls. Similarly, Laamech et al. (2016) reported a statistically
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significant increase in plasma levels of creatinine in 40-day Pb-treated animals (18 (ig/dL BLL). In
addition, Shi etal. (2020) reported that a 28-day Pb exposure in rats (BLL of-10.21 (ig/dL) resulted in a
statistically significant increase in serum creatinine, as well as significantly (p < 0.05) lower urine
creatinine (potentially indicating impaired kidney function). Following a single exposure in rats, (BLL of
-30 (ig/dL), Andielkovic et al. (2019) reported a small, but statistically significant increase (p < 0.05) in
serum levels of creatinine. Finally, in kidney tissue, Gao et al. (2020) demonstrated a statistically
significant decrease in creatinine activity following a 4-week Pb exposure (BLL of 10.6 (ig/dL).
In addition to the drinking water and gavage studies mentioned above, a Pb nitrate nanoparticle
inhalation study reported changes in creatinine levels. Following Pb nitrate nanoparticle inhalation for 11
weeks (but not 2 or 6 weeks, BLL at 11 weeks was 8.5 (.ig/dL). Dumkova et al. (2020a) reported a
statistically significant decrease in blood creatinine in mice. Notably, this inhalation study demonstrated a
decrease in creatinine levels while the oral exposure studies mentioned above generally demonstrated an
increase in these markers. Given this is a single inhalation study, it is difficult to deduce whether the
result is repeatable, and if so, whether the difference is due to the route of exposure, the use of synthetic
Pb particles, or another factor.
Finally, not all animal toxicological studies demonstrated changes in creatinine levels. Corsetti et
al. (2017) reported no significant difference in serum creatinine levels following a 45-day Pb exposure
(BLL 21.6 (ig/dL) relative to control animals. Carlson et al. (2018) similarly reported that exposure to Pb
resulting in a BLL of 2.89 (ig/dL yielded creatinine levels that were not always within reference ranges
but were not statistically different from the levels of control mice. Furthermore, in an analysis using Pb-
oxide nanoparticles, and in contrast to their previous study (see (Dumkova et al.. 2020a) above),
(Dumkova et al.. 2020b) observed no change in creatinine levels at 2, 6, or 11 weeks, potentially
indicating a difference between Pb-oxide and Pb nitrate nanoparticle inhalation exposure (BLLs ranged
from 10.4 to 17.4 (.ig/dL). It should be noted that creatinine levels were within reference ranges in both
studies.
When the animal toxicological studies are considered together, there is evidence that exposure to
Pb can result in changes in creatinine levels. Following drinking water or gavage exposure, most studies
demonstrated an increase in serum creatinine levels, which could indicate impaired kidney function.
However, it should be noted that a couple of these oral exposure studies, one of which was at a very low
BLL (2.89 (ig/dL), reported no change following Pb exposure. Results using Pb nanoparticle inhalation
exposure were more variable, demonstrating either a decrease or no change in creatinine levels.
5.4.2.2.2 Albumin
Since the publication of the 2013 Pb ISA, no animal toxicological studies have examined changes
urinary ALB. Moreover, none of the existing studies demonstrated an increase in ALB serum or blood
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levels. Studies either demonstrated no effect (Dumkova et al.. 2020a; Andielkovic et al.. 2019; Corsetti et
al.. 2017)or a decrease in ALB lcvcls(Dumkova et al.. 2020b) following exposure to Pb.
5.4.2.3 Integrated Summary of Creatinine and Albumin Levels
Increased levels of creatinine in blood or serum, or a decrease in urine, can be indicative of
impaired kidney function. The 2013 ISA (U.S. EPA. 2013) included longitudinal epidemiologic studies
that evaluated the effect of bone Pb exposure on serum creatinine levels (Tsaih et al.. 2004; Kim et al..
1996). These studies both reported positive associations between increases in serum creatinine levels and
bone Pb measurements. These results are in agreement with a more recent study in premenopausal women
reporting a positive association between serum creatinine levels and increasing BLLs (Pollack et al..
2015).
Positive epidemiologic associations are supported by animal toxicological studies with BLLs
below 30 (ig/dL from both current and previous reviews. In particular, studies using oral exposures
generally demonstrate higher creatinine levels in Pb-exposed animals when compared with controls (Shi
et al.. 2020; Andielkovic et al.. 2019; Laamech et al.. 2016; Zou et al.. 2015; Berrahal et al.. 2011; Roncal
et al.. 2007) (Section 5.4.2.2). However, more recent oral exposure studies demonstrated no change in
serum creatinine levels in laboratory animals following Pb exposure (Carlson et al.. 2018; Corsetti et al..
2017).
With respect to inhalation exposure to Pb (Dumkova et al.. 2020b) reported no change in
creatinine levels. Nonetheless, it should be noted that Dumkova et al. (2020b) was unique in that it used
engineered Pb-oxide nanoparticles to expose mice via inhalation, rather than exposure through drinking
water or ingestion as in other animal toxicological studies. Moreover, these results are in contrast to those
from the same authors using Pb-nitrate nanoparticles, which reported a decrease in creatinine levels at
similar time points (Dumkova et al.. 2020a). Thus, in animal toxicological studies, it is possible that the
route of exposure or the type of Pb particles used (e.g., Pb-oxide versus Pb-nitrate) could influence serum
creatinine levels. Nonetheless, the overall evidence indicates that exposure to Pb can produce increased
levels of creatinine in blood or serum from both epidemiologic and animal toxicological studies. With
respect to the levels of ALB, there is little evidence from epidemiologic or animal toxicological studies
that exposure to Pb can increase serum, blood, or urine ALB levels.
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5.4.3
Uric Acid and Urea
5.4.3.1 Epidemiologic Studies of Uric Acid and Urea
UA is excreted in the urine and is the product of purine metabolism. Increased serum UA (SUA)
levels can be indicative of reduced kidney excretion and is associated with multiple clinical outcomes
including gout and CKD. Exposure to Pb is thought to alter UA homeostasis by effecting its kidney
excretion (Emmerson and Ravenscroft. 1975) and increased UA can result in Pb-related nephrotoxicity
(Weaver et al.. 2005). Recent epidemiologic evidence supports an association between biomarkers of Pb
exposure and increases in SUA. Study-specific details, including BLLs, study population characteristics,
confounders, and select results from these studies are highlighted in Table 5-8. Study details in Table 5-8
could not be standardized (UA associated with a 1 (ig/dL increase in blood Pb) with the information
provided in each paper.
Park and Kim (2021) evaluated the association between blood Pb and SUA levels using
KNHANES (2016-2017). This study noted an increase in SUA among women (0.019 mg/dL [95% CI:
0.001, 0.037 mg/dL]), but not men (-0.018 mg/dL [95% CI: -0.038, 0.002 mg/dL]) for each doubling of
log-transformed blood Pb. This study also considered hyperuricemia (SUA levels >7 mg/dL in males or
>6 mg/dL in females) but indicated null associations for both women and men. Arrebola et al. (2019)
evaluated continuous SUA levels and the presence or absence of hyperuricemia (SUA levels >7 mg/dL in
males or >6 mg/dL in females, SUA lowering medication use, or gout diagnosed by a physician) in the
BIOAMBIENT.ES study. The study population had relatively low BLLs (median: 0.106 (.ig/dL). BLLs
were not associated with SUA levels (0.01 ng/dL [95% CI: -0.02, 0.04 mg/dL]) or with hyperuricemia
(OR: 1.12 [95% CI: 0.90, 1.41]). Another KNHANES analysis evaluated the effect between
hyperuricemia (SUA levels >7 mg/dL in males or >6 mg/dL in females) and BLLs (Jung et al.. 2019).
This study also did not indicate an association between blood Pb and hyperuricemia (Figure 5-5).
Notably, no epidemiologic studies have examined the potential relationship between exposure to
Pb and changes in measures of urea.
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Lead men
Lead women
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Adapted from: Jung et al. (2019).
Figure 5-5 Association between blood Pb and hyperuricemia among men
and women, Korea National Health and Nutrition Examination
Survey, 2016.
5.4.3.2 Animal Toxicological Studies of Uric Acid and Urea
Previous Pb reviews contained animal toxicological studies reporting that exposure to Pb
increased serum levels of creatinine (see Table 4-28 in the 2013 Pb ISA). Roncal et al. (2007)
demonstrated an increase in both serum UA and BUN following exposure to Pb (BLL 26 (.ig/dL).
Similarly, Wang et al. (2010) demonstrated increased serum urea nitrogen levels following exposure to
Pb. However, Pb levels were measured in serum, and thus the BLL was unknown. Studies published since
the 2013 Pb ISA are presented in sections 5.4.3.2.1 and 5.4.3.2.2 below. Additional information on the
experimental design of toxicological studies of UA and urea published since the 2013 Pb ISA can be
found in Table 5-10.
5.4.3.2.1	Uric Acid
Since the publication of the 2013 Pb ISA, Shi et al. (2020) reported that rats with a BLL of
-10.21 (ig/dL had a statistically significant increase in UA relative to controls. However, Laamech et al.
(2016) reported a statistically significant decrease (18 (ig/dL BLL), and Andielkovic et al. (2019) reported
no change (-30 (ig/dL BLL) in UA following exposure to Pb. Thus, there is limited evidence from animal
toxicologic studies for increased levels of UA.
5.4.3.2.2	Urea
Since the publication of the 2013 Pb ISA, rodent toxicological studies have further demonstrated
changes in measures of urea following Pb exposure via drinking water or gavage. Zou et al. (2015)
P «,«=0,202
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reported a statistically significant increase in BUN (BLL of 21.7 (ig/dL) following a 30-day exposure in
mice relative to controls. Similarly, following exposure to Pb.Laamech et al. (2016) reported a
statistically significant increase in plasma levels of urea (18 (ig/dL BLL). In addition, Shi et al. (2020)
reported that a 28-day Pb exposure in rats (BLL of-10.21 (ig/dL) resulted in a statistically significant
increase in BUN. Similarly, in kidney tissue, Gao et al. (2020) demonstrated a statistically significant
increase in BUN activity following a 4-week Pb exposure (BLL of 10.6 (.ig/dL). In contrast to studies that
found an increase in serum BUN following Pb exposure, Andielkovic et al. (2019) reported a statistically
significant (p < 0.05) decrease in serum BUN (BLL of -30 (ig/dL). In addition, both Corsetti et al. (2017)
(BLL 21.6 (ig/dL) and Carlson et al. (2018) (BLL of 2.89 (ig/dL) reported that exposure to Pb did not
result in urea levels that were statistically different from those of control animals.
In addition to the studies above, a couple of Pb nanoparticle inhalation studies (by the same
authors) reported mixed results. Following Pb nitrate nanoparticle inhalation for 11 weeks (but not 2 or
6 weeks; BLL at 11 weeks was 8.5 (.ig/dL). Dumkova et al. (2020a) reported a statistically significant
decrease in urea levels. However, in an analysis using Pb-oxide nanoparticles, no change in urea was
reported at 2, 6, or 11 weeks (Dumkova et al.. 2020b). potentially indicating a difference between Pb-
oxide and Pb nitrate nanoparticle inhalation exposure (BLLs ranged from 10.4 to 17.4 (ig/dL).
The majority of the studies published since the last ISA indicate that oral exposure to Pb can
result in changes in measures of urea (e.g., BUN). Most of these studies demonstrated an increase in
serum urea levels, consistent with impaired kidney function. Inhalation studies conducted by the same
laboratory were more variable, demonstrating no change or decreases in these markers. Additional
information regarding the experimental designs of the of urea and UA studies included in this section can
be found in Table 5-9.
5.4.3.3 Integrated Summary of Uric Acid and Urea
Similar to other molecular markers that estimate kidney function, increased SUA, urea, and BUN
levels can be indicative of impaired kidney function. Increased SUA levels are also associated with
multiple clinical outcomes including gout and CKD. In an epidemiologic study, Park and Kim (2021)
reported an increase in SUA among women, but not men. However, Arrebola et al. (2019) and Jung et al.
(2019) reported that BLLs were not associated with either SUA levels or the presence of hyperuricemia.
Animal toxicology studies were similarly mixed. Thus, there is limited evidence from epidemiologic and
animal toxicological studies for increases in the levels of UA following Pb exposure.
With respect to measures of urea, some animal toxicological studies with mean blood Pb values
<30 (ig/dL have demonstrated a relationship between exposure to lead and increased serum BUN levels
(Shi et al.. 2020; Laamech et al.. 2016; Zou et al.. 2015). Similarly, Gao et al. (2020) demonstrated a
statistically significant increase in kidney tissue BUN levels. Other oral exposure studies were mixed,
either showing a decrease (Andielkovic et al.. 2019) or no effect (Carlson et al.. 2018; Corsetti et al..
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2017). Inhalation studies by the same authors were also mixed, with some studies demonstrating a
significant decrease in blood urea levels following inhalation of engineered Pb-nitrate (Dumkova et al..
2020b) but not Pb-oxide n an o p art i c 1 e s (D u in k o v a et al.. 2020a) in rats. Some evidence from animal
toxicology studies suggests that oral exposure can increase the levels of urea in blood following exposure
to Pb.
5.4.4 Proteinuria and Hematuria
5.4.4.1 Epidemiologic Studies of Proteinuria and Hematuria
Increased levels of protein (proteinuria) and blood cells (hematuria) in the urine can be markers
of renal damage. Hematuria can either be benign or indicative of more serious outcomes including
glomerulonephritis, CKD, kidney stones, or cancer. The 2013 Pb ISA (U.S. EPA. 2013) did not include
any epidemiologic studies of proteinuria or hematuria. Study-specific details, including BLLs, study
population characteristics, confounders, and select results from more recent studies examining these
endpoints are highlighted in Table 5-10. Study details in Table 5-10 include standardized results
(associated with a 1 (ig/dL increase in BLL) as well as results that could not be standardized with the
information provided in each paper.
Chung etal. (2014) evaluated the association between blood Pb and proteinuria using KNHANES
(2008). Proteinuria was defined as >1 on a urine dipstick test (equivalent to >30 mg/dL). This study
indicated that when compared with the lowest quartile (mean: 1.38 (.ig/dL). the odds of proteinuria (OR:
1.22 [95% CI: 1.00, 1.50]) were greater among participants in the highest quartile (mean: 4.13 (ig/dL).
Han etal. (2013) evaluated the association between hematuria (>1 on urine dipstick test) and BLLs using
KNHANES (2008-2010). A null association was observed when the highest quartile (Q4 >3.22 (ig/dL)
was compared with the lowest (Ql: <1.89 (ig/dL) (OR: 0.78 [95% CI: 0.443, 1.361]).
5.4.4.2 Toxicological Studies of Proteinuria and Hematuria
The previous ISA contained no evidence of proteinuria or hematuria from animal toxicological
studies with reported BLLs. One study reported an increase in urinary protein levels but only measured
Pb in serum Wang et al. (2010). No animal toxicological studies have been conducted with BLLs
examining these outcomes since the 2013 Pb ISA. Thus, consistent with the epidemiologic studies
presented above, there is only limited evidence for an effect of Pb on proteinuria and no evidence for an
effect on hematuria.
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5.4.4.3 Integrated Summary of Proteinuria and Hematuria
There is little evidence from epidemiologic or animal toxicological studies that exposure to Pb
results in proteinuria or hematuria
5.4.5 N-Acetyl-p-D-Glucosaminidase and ^-Microglobulin
5.4.5.1 Epidemiologic Studies of N-Acetyl-P-D-Glucosaminidase and P2-Microglobulin
Many markers of kidney dysfunction may be insensitive for early detection of kidney damage.
Recently, the development of early biological effect (EBE) markers of preclinical kidney damage has
received substantial attention. Exposure to Pb is thought to directly affect the deterioration of tubular
function, which can lead to the loss of essential divalent metals. The renal tubular biomarker N-acetyl-(3-
D-glucosaminidase (NAG) is a lysosomal enzyme that is sensitive to renal impairment. Another renal
tubular biomarker, (32-microglobulin (P2-MG), is typically reabsorbed through glomerular filtration.
Increases in either NAG or P2-MG correspond to damage to the renal tubules. Study-specific details,
including BLLs, study population characteristics, confounders, and select results from these studies are
highlighted in Table 5-11. Study details in Table 5-11 could not be standardized (associated with a
1 (ig/dL increase in blood Pb) with the information provided in each paper.
Lim et al. (2016) evaluated the association between BLLs and both NAG and P2-MG in the
Korean Research Project on the Integrated Exposure Assessment to Hazardous Materials for Food Safety
(KRIEFS). This study indicated null associations between log-transformed blood Pb and both NAG (0.09
units/g creatinine [95% CI: -0.05, 0.23 units/g creatinine]) and P2-MG (0.01 jxg/g creatinine [95% CI:
-0.13, 0.15 jxg/g creatinine]). Jung et al. (2016) also evaluated the association between blood Pb and
NAG among participants residing near a cement plant in South Korea. There were null associations when
high NAG levels (>5.67 U/L) were compared with low NAG levels between quartiles of blood Pb and
NAG.
5.4.5.2 Toxicological Studies of N-Acetyl-P-D-Glucosaminidase and P2-Microglobulin
A study from the 2013 Pb ISA indicated an increase in P-2 microglobulin and N-acetyl-P-D-
glucosaminidase following Pb exposure (Wang et al.. 2010). However, this study only measured Pb levels
in serum (serum Pb level: 20 (ig/dL) and thus, the BLL is unknown. Similarly, Javakumar et al. (2009)and
Khalil-Manesh et al. (1992b) reported a change in N-acetyl-P-D-glucosaminidase following Pb exposure
(BLLs and 45 (ig/dL, and >55 (ig/dL, respectively). Since the 2013 Pb ISA, no animal toxicological
studies have been conducted with BLLs less than 30 (ig/dL to examine these markers.
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5.4.5.3 Integrated Summary of N-Acetyl-P-D-Glucosaminidase and P2-Microglobulin
Few epidemiologic studies have been conducted examining (3-2 microglobulin and N-acetyl-(3-D-
glucosaminidase following Pb exposure, and these studies reported no association with BLLs. With
respect to animal toxicological studies, a few studies from previous reviews demonstrated changes in N-
acetyl-P-D-glucosaminidase following Pb exposure, but a couple of these studies were at BLLs
>55 (ig/dL. Thus, when considered together, epidemiologic and animal toxicological studies provide little
evidence for an effect of Pb exposure on these markers at BLLs < 30 (ig/dL.
5.4.6 Toxicological Studies of Other Indicators of Kidney Function
In addition to the markers potentially indicating impaired kidney function discussed above, other
markers have been examined in a small number of studies. Increases in total serum protein can also be
indicative of impaired kidney function. However, Andielkovic et al. (2019) reported no change in total
serum protein following Pb exposure (BLL -30 (ig/dL). Moreover, other studies either reported no
changes or decreases in total protein in blood at timepoints ranging from 2 weeks to 11 weeks following
Pb nitrate (Dumkova et al.. 2020a) or Pb-oxide (Dumkova et al.. 2020b) nanoparticle inhalation exposure
(BLLs < 17.4 (ig/dL in these studies).
Changes in the balance of metal ions in the kidney and blood can also be indicative of impaired
kidney function. In particular, lower calcium levels can be indicative of kidney disease. Dumkova et al.
(2020a) reported a significant decrease in calcium levels in the kidney but not in blood following Pb
nitrate nanoparticle inhalation for 2 weeks (but not 6 or 11 weeks when BLLs were higher; BLL at
2 weeks was 4 (ig/dL). No changes in the blood levels of sodium or potassium were reported, but there
was a statistically significant decrease in phosphorous levels in blood at 2 and 11 weeks (but not at
6 weeks). In an additional analysis using Pb-oxide nanoparticles, Dumkova et al. (2020b) reported a
statistically significant decrease in kidney calcium levels after 2 and 6 weeks, but not after 11 weeks of
exposure (BLLs: 10.4 (ig/dL at 2 weeks, 14.8 (ig/dL at 6 weeks and 17.4 (ig/dL at 11 weeks). In addition,
this study found no changes in sodium or potassium levels in the kidney at any time point. There were
also no changes in calcium, potassium, or sodium levels in the blood. Moreover, Andielkovic et al. (2019)
reported: 1) a statistically significant decrease in serum calcium and iron; 2) no change in blood copper,
zinc, or phosphorus levels; and 3) a decrease (p < 0.05) in kidney tissue zinc, but not copper following Pb
exposure (BLL -30 (ig/dL). Finally, Zou et al. (2015) reported no change in zinc levels but a decrease in
iron levels in blood relative to control animals. When considered as a whole, there is limited evidence for
changes in calcium and other ion levels in blood or tissue following exposure to Pb. Additional
information on the experimental design of toxicological studies presented in this section can be found in
Table 5-12.
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5.5
Toxicological Studies of Metal Co-Exposures with Pb
A limited number of studies evaluated the effect of Pb on the kidney in conjunction with exposure
to other metals. Andielkovic et al. (2019) evaluated the effect of Pb exposure in combination with
cadmium. Although the levels of creatinine, BUN, and UA were similar following co-exposure with
cadmium, total serum protein and ALB levels were statistically lower than controls following co-
exposure. In an additional study, Zou et al. (2015) reported a statistically significant increase in serum
levels of creatinine and BUN following co-exposure of Pb and zinc, but the levels of these markers were
lower than the levels following exposure to Pb alone.
With respect to metal ions and co-exposure, Andielkovic et al. (2019) reported that co-exposure
of Pb with cadmium resulted in a statistically significant decrease (p < 0.05) in the levels of zinc (but did
not exacerbate the decrease compared with Pb alone) and no change in copper ion levels (similar to Pb
alone) in kidney tissue. However, co-exposure with cadmium did result in a greater decrease in serum
calcium, iron, and blood copper levels, but not zinc blood levels when compared with exposure to Pb
alone. In addition, Zou et al. (2015) reported that co-exposure with zinc significantly increased blood iron
levels relative to Pb exposure alone.
Overall, only a few studies have examined the potential effects of metal co-exposure on kidney-
related endpoints. Moreover, these studies varied in their co-exposure metals and outcome assessments.
Thus, it is difficult to draw conclusions on the effects of metal co-exposure with Pb on either markers of
kidney function or ion concentrations.
5.6 Activation of Renin-Angiotensin-Aldosterone System
The renin-angiotensin-aldosterone system (RAAS) plays an important role in the regulation of
blood pressure and kidney homeostasis. For example, angiotensin II (Ang II) stimulates arteriolar
vasoconstriction, leading to increases in blood pressure or hypertension. Angiotensin-converting enzyme
(ACE) is involved in the activation of Ang II. The 2013 Pb ISA stated that vascular reactivity to Ang II
increased following Pb exposure (Robles et al.. 2007). In addition, exposure to Pb resulted in increases in
kidney or serum ACE activity and renal Ang II-positive cells (Rodriguez-Iturbe et al.. 2005; Sharifi et al..
2004; Carmignani et al.. 1999). Moreover, use of an ACE inhibitor or blocking the Ang II receptor type 1
(AT-1) ameliorated Pb-induced increases in blood pressure (SimSes etal.. 2011). Since the 2013 Pb ISA,
Fioresi et al. (2014) reported no change in ACE activity in plasma and cardiac tissue. Taken together,
there is some evidence from older studies to suggest that exposure to Pb can result in changes in RAAS.
Additional information on the study design of Fioresi et al. (2014) can be found in Table 5-12.
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5.7
Renal Outcomes Among Children
The 2013 Pb ISA (U.S. EPA. 2013) and 2006 Pb AQCD (U.S. EPA. 2006b) highlighted several
studies indicating a lack of association between biomarkers of Pb exposure and renal outcomes among
children. Many studies presented previously were among children with high exposures to Pb. Fadrowski
et al. (2010) conducted an NHANES analysis that evaluated relatively low blood Pb values (median:
1.5 (ig/dL) and two different measures of eGFR (cystatin C-based and creatinine-based). This study
indicated an increase in eGFR based on an association between cystatin C and the highest quartile
(>2.6 (ig/dL) compared with the lowest (<1 (ig/dL). More recent analyses not only continue to evaluate
children with low BLLs, but also use techniques to more accurately measure GFR (either directly or an
estimate) in children. Study-specific details, including Pb biomarker levels, study population
characteristics, confounders, and select results from these studies are highlighted in Table 5-13. Study
details in Table 5-13 include standardized results (associated with a 1 (ig/dL increase in BLL) as well as
results that could not be standardized with the information provided in each paper.
A recent longitudinal analysis evaluated the association between the erythrocyte fraction of Pb
(Ery-Pb) in maternal blood and subsequent measurements of renal function, including kidney volume,
eGFR (calculated based on serum cystatin C and deemed appropriate for use in children), and serum
cystatin C, among children (~ 4.5 years) (Skroder et al.. 2016). The Ery-Pb was assessed at both 14 weeks
(GW14) and 30 weeks (GW30) of gestation. Linear regression analyses identified an association between
decreased kidney volume and maternal Ery-Pb at 30 weeks of gestation (-0.071 cm3/m2 [95% CI: -1.4,
-0.030]), but not at 14 weeks of gestation (-0.061 cm3/m2 [95% CI: -0.36, 0.24]). When stratified by sex,
this association was stronger among girls (-1.1 cm3/m2 [95% CI: -2.1, -0.049]) than among boys
(-0.80 cm3/m2 [95% CI: -1.80, 0.20]), for each 10 (ig/kg increase in Ery-Pb. However, no differences in
effect were observed when this outcome was stratified by birthweight or by children with stunted height.
When considering other markers of renal dysfunction, no associations were present for eGFR (GW14
0.089 mL/min/1.73 m2 [95% CI: -0.012, 0.30]; GW30 0.71 mL/min/1.73 m2 [95% CI: -0.24,0.17]) or
serum cystatin C (GW14 -0.00088 mg/L [95% CI: -0.0028, 0.001]; GW30 0.000027 [95% CI: -0.0018,
0.0018]).
Fadrowski et al. (2013) conducted a cross-sectional study evaluating children (aged 1-16) with
CKD who were part of the Chronic Kidney Disease in Children (CKiD) prospective study. This study
measured GFR directly by measuring the plasma disappearance inhexol curves (children had blood draws
at 10, 20, 120, and 300 minutes after an injection of inhexol). The average percent change in GFR within
the study was -2.1% (95% CI: -6.0, 1.8) for a 1 (ig/dL increase in blood Pb. In the pediatric population,
there are two main diagnoses for CKD: glomerular and nonglomerular. Glomerular CKD diagnoses
include focal segmental glomerulosclerosis, hemolytic uremic syndrome, and systemic immunological
diseases (systemic lupus erythematosus), whereas nonglomerular CKD includes
aplastic/hypoplastic/dysplastic kidneys, reflux nephropathy, obstructive uropathy, and congenital urologic
disease. Generally, nonglomerular CKD has an earlier onset and a slower rate of disease progression
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(Hooper et al.. 2021). When stratified by the type of CKD (glomerular versus nonglomerular), children
with glomerular CKD experienced a -12.1% change (95% CI: -22.2, -1.9) in GFR, compared with a
-0.7% change (95% CI: -4.8, 3.4) among those with nonglomerular CKD. In another cross-sectional
analysis, Cardenas-Gonzalez et al. (2016) evaluated BLLs and two biomarkers of kidney injury (Kidney
Injury Molecule 1 [KIM-1] and neutrophil gelatinase-associated lipocalin [NGAL]) among Mexican
children living in an area with a high prevalence of CKD. This study indicated null associations between
blood Pb and biomarkers of kidney injury (results not shown).
An NHANES (1999-2006) analysis evaluated blood Pb and SUA among adolescents aged 12-19
(Hu et al.. 2019). This study considered several confounders related to sociodemographic factors, blood
biochemistry markers, and dietary intake. Overall, a one-unit increase in natural log (ln)-transformed
blood Pb was associated with a 0.14 mg/dL (95% CI: 0.10, 0.17) increase in SUA. Additionally, the
magnitude of the association was larger when examining elevated SUA (>5.5 mg/dL) and a one-unit
increase in ln-transformed blood Pb (OR: 1.29 [95% CI: 1.17, 1.42]). Moreover, a restricted cubic spline
analysis indicated a linear dose-response relationship between ln-transformed blood Pb and both
continuous SUA and elevated SUA (>5.5 mg/dL) (Figure 5-6). Additionally, Hu et al. (2019) evaluated
several of the model covariates (e.g., sex, race, and eGFR) in a subgroup analysis. The comparisons for
these are shown in Figure 5-7. The authors reported that there were generally no interactions between
blood Pb and other adjusted variables, except for educational attainment. Thus, the positive association
remained, regardless of subgrouping.
		
0	I	2	S
LnBLL (llg'dL)
BLL = blood lead level; dL = deciliter; |jg = micrograms; Ln = natural logarithm; OR = odds ratio.
Source: Hu et al. (2019).
Figure 5-6 Associations between natural log-transformed blood Pb (0-
4 (jg/dL) and serum uric acid and elevated serum uric acid
(>5.5 mg/g).
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Subgroups
N Mean ± SD
|i( 95% CI)
Sex


Male
4184
5.6 ±1.2
Female
4119
*-
1+
©
Age, years


< 17
6261
4.9 ± 1.2
> 17
2042
5.2 ± 1.3
Race


Non-Hispanic White
2109
5.1 + 1.3
Nuii-Hibpajiic Black
2641
4.9 ±1.2
Mexican American
2905
5.0 ± 1.3
Other Hispanic
318
5.0 ± 1.2
Other race
330
5.2 ± 1.4
Education


< high school
6998
5.0+1.3
s high school
1301
5.2 ± 1.3
Physical Activity


Sedentary
572
4.9 ± 1.4
Low
803
5.0 ± 1,3
Moderate
584
5.0 ± 1.3
High
1537
5.3 ± 1.3
BMI, kg/m2


Tertile 1 (< 17.S)
603
4.3 ± 1.1
Tertile 2 (17.5-22.1)
3291
4.7 ± 1.1
Tertile 3 (:> 22,1)
4333
5.3 ± 1.3
Serum Colinine, ng/mL


< 0,1
4014
4.8 ±1.2
0.1-10
3117
5.0 ± 1.3
2 10
1108
5.4 + 1.3
l-GFR, iiiL/miii per 1.73 m2
Tertile 1 (< 130)
Tertile 2 (130-152)
Tertile 3 (> 152)
0.11 (0.06, 0.17)
0.14 (0.09, 0.19)
0.15(0.11, 0.19)
0.05 (-0.02, 0.13)
0.12 (0.04, 0.20)
0.16 (0.10,0.23)
0.14 (0.08,0.19)
0.07 (-0.12, 0.26)
-0.05 (-0.28, 0.17)
0.16 (0.12, 0.20)
-0.03 (-0.12, 0.06)
0.04 (-0.08, 0.16)
0.16 (0.03, 0.28)
0.10 (-0.04, 0.24)
0.14 (0.05, 0.22)
0.06 (-0.08, 0.19)
0.15 (0.10, 0.20)
0.07(0.01.0.12)
0.13 (0.08,0.18)
0.08 (0.02, 0.14)
0.10 (-0.02, 0.21)
2750
4.9 ± 1.2
—<
0.19 (0.11, 0.27)
2749
5.1 + 1.3

0.11 (0.05, 0.16)
2757
5.0 ± 1.3

0.06(0.00,0.12)
P for interaction
0.056
0.056
0.808
0.002
0.268
0.271
0.310
0.047
"T
-0.4 -0,3 -0,2 -0,1 0 0,1 0.2 0.3 0,4
BMI = body mass index; CI = confidence interval; eGFR = estimated glomerular filtration rate; kg = kilograms; m = meters; min =
minute; mL = milliliter; ng = nanograms; SD = standard deviation.
Source: Hu et al. 12019).
Figure 5-7 Subgroup analysis between blood Pb and serum uric acid among
adolescents, National Health and Nutrition Examination Survey
1999-2006.
5.7.1 Summary of Renal Outcomes Among Children
1	Skroder, 2016, 468576f||§|author-year} conducted a longitudinal analysis evaluating the
2	association between the erythrocyte fraction of Pb (Ery-Pb) in maternal blood and subsequent
3	measurements of renal function among children (-4.5 years). The Ery-Pb was assessed at both 14 weeks
4	(GW14) and 30 weeks (GW30) of gestation. Linear regression analyses identified an association between
5	decreased kidney volume and maternal Ery-Pb at 30 weeks of gestation, but not at 14 weeks. No
6	associations were present with eGFR or serum cy statin C. In addition, an NHANES (1999-2006) analysis
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evaluated blood Pb and serum SUA among adolescents aged 12-19 taking into account several
confounders related to sociodemographic factors, blood biochemistry markers, and dietary intake.
Overall, there was a positive association between a one-unit increase in transformed blood Pb and
continuous and elevated SUA (Hu et al.. 2019). This study also evaluated several of the model covariates
(e.g., sex, race, and eGFR) in a subgroup analysis, and no interaction was reported between blood Pb and
other adjusted variables, except for educational attainment. In addition to these studies, a cross-sectional
study evaluated children (aged 1-16) with CKD and measured GFR directly by measuring the plasma
disappearance inhexol curves. Overall, this study did not indicate an association between blood Pb and
GFR, except among those with a specific type (glomerular) of CKD (Fadrowski et al.. 2013). Similarly,
an additional cross-sectional analysis did not report an association between BLLs and biomarkers of
kidney function among Mexican children living in an area with a high prevalence of CKD (Cardenas-
Gonzalez et al.. 2016). Taken together, there is limited evidence for an effect between biomarkers of Pb
exposure and renal outcomes among children.
5.8 Reverse Causality
In observational research, reverse causality occurs when an association between an exposure and
outcome is explained by the outcome that causes or alters the exposure. Reverse causality is a potential
concern in studies of kidney function due to the role of the renal system in the excretion of toxins from
the blood. Specifically, increased BLLs could result from reduced excretion due to kidney damage rather
than as a causative factor for kidney impairment. The potential for reverse causality in epidemiologic
studies is especially plausible in cross-sectional studies and studies conducted in study populations that
are already experiencing renal dysfunction. In contrast, prospective analyses that include baseline
measurements of biomarkers of Pb exposure and incident changes in renal function may help control for
the possibility of reverse causality.
The 2006 Pb AQCD (U.S. EPA. 2006b) presented a longitudinal NAS study by Kim et al. (1996)
where positive associations between BLLs and serum creatinine were reported over most of the range of
serum creatinine (Figure 5-8). In locally weighted regression models, these associations were observed
within the normal creatinine range, where reduced excretion of Pb is a less likely explanation of the
observed association. A follow-up to this study evaluated the association between blood and bone Pb
levels and serum creatinine among those with serum creatinine <1.5 mg/dL (Tsaih et al.. 2004). This
study indicated that the longitudinal associations did not materially change, suggesting that Pb dose
contributed to renal dysfunction.
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— 130
5 <1 47)
o
E
A
C
c
«
0)
6
E
3
k_
a)
CO
3
«
3
"O
<
115
(1.30)
100
(1.13)
85
(0.96)
"T
	i	1	
1	2	3
(20.7) (41.4) (62.2)
Adjusted Blood Lead, nmol/L (ng/dL)
Source: Kim et al. (1996).
130
(147)
115
(1 30)
100
(1.13)
85
(0.96)
1	1	1	1	1—
0 0.1 0.3 0.9 2.7
(2.1) (6.2) (18.6) (55.9)
Adjusted Blood Lead, jxmol/L (ng/dL)
Figure 5-8 Locally weighted smoothing plot of adjusted associations
between blood Pb levels (with [left panel] and without [right
paned] logarithmic transformation) and serum creatinine.
The use of eGFR provides a better estimate of progressive changes in renal function than
creatinine clearance. In a longitudinal study evaluated in the 2013 Pb ISA, Yu et al. (2004) indicated that
baseline BLLs were associated with a decline in eGFR among CKD patients. More recent longitudinal
analyses assessed changes in eGFR (Chung et al.. 2020; Liu et al.. 2020; Harari et al.. 2018; Pollack et al..
2015) among a variety of populations free of kidney disease at baseline. Notably, in a population-based
cohort study with an extensive follow-up period (Baseline: 1991-1994, Follow-up: 2007-2012), Harari et
al. (2018) reported that increased baseline BLLs were associated with substantial decreases in eGFR from
baseline. Since this study also adjusted for baseline eGFR, the larger decreases in kidney function
observed in participants with higher Pb exposures ostensibly occurred in participants with similar baseline
kidney function. Smaller cohort studies further supported this study by noting decreases in eGFR with
increased BLLs (Chung et al.. 2020; Liu et al.. 2020; Pollack et al.. 2015).
Furthermore, several recent epidemiologic studies evaluated the association between BLLs and
the development of CKD or ESRD. In a population-based cohort in Sweden that showed Pb-related
reductions in eGFR, Harari et al. (2018) also observed a relationship between BLLs at baseline and
incident CKD after further adjustment for baseline eGFR. Additionally, a comprehensive analysis by
Sommar et al. (2013) involved a combination of several existing cohort studies and subsequently linked
incident ESRD cases to members of the cohorts. This study identified a modest association between BLLs
and incident ESRD. These studies provide further evidence that links baseline blood Pb data to the
development of long-term kidney disease.
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In addition to the epidemiologic evidence, the expanded literature base of animal toxicological
studies provide strong support that the associations reported in epidemiologic studies are the result of
exposure to Pb, not reverse causality. This is due to the large amount of evidence from animal
toxicological studies demonstrating health effects such as impaired kidney function and kidney damage
providing additional support that associations reported in epidemiologic studies are indeed the result of
exposure to Pb.
Overall, recent evidence further supports that reverse causality does not contribute substantially
to the association between higher BLLs and decreases in kidney function. Several recent studies
longitudinally evaluated either the change in eGFR from baseline or the development of CKD or ESRD
and baseline blood Pb measurements taken years prior to the assessment of kidney function. While
reverse causality may contribute to some associations between biomarkers of Pb exposure and renal
function, recent evidence does not support reverse causality as the driving force behind these associations.
5.8.1 Summary of Reverse Causality
Epidemiologic evidence has generally reported increased associations between biomarkers of Pb
exposure and renal effects, without evidence of reverse causality. Specifically, longitudinal studies
evaluating a decline in eGFR in relation to blood Pb further suggest that reverse causality does not
substantially affect the association between biomarkers of Pb exposure and decreased kidney function.
The 2006 Pb AQCD (U.S. EPA. 2006b) reported an association between baseline BLLs and accelerated
decreases in eGFR in CKD patients (Yu ct al.. 2004). Several recent longitudinal studies among healthy
populations, free of kidney disease, also further support changes in eGFR from baseline, associated with
baseline blood Pb (Chung et al.. 2020; Liu et al.. 2020; Harari et al.. 2018; Pollack et al.. 2015).
Specifically, Harari et al. (2018). which had an extensive follow-up period (-16 years of follow-up),
noted that increased baseline BLLs were associated with substantial decreases in eGFR from baseline.
In addition, several recent epidemiologic studies also evaluated the association between
biomarkers of Pb exposure and the development of CKD or ESRD. In the population-based cohort in
Sweden that also noted Pb-related reductions in eGFR, Harari et al. (2018) observed a relationship
between incident CKD and BLLs at baseline, after further adjustment for baseline eGFR. Additionally,
Sommar et al. (2013) combined several existing cohort studies and subsequently linked them to an ESRD
database. This study identified a modest association between BLLs and incident ESRD. These studies
provide further evidence that links baseline blood Pb data to the development of long-term kidney
disease.
Toxicological evidence indicating associations between blood Pb and markers of oxidative stress
and impaired kidney damage provides additional support that associations reported in epidemiologic
studies are in fact the result of exposure to Pb. The combined toxicological and epidemiologic evidence
suggests that reverse causality does not substantially contribute to the association between higher BLLs
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and decreased kidney function. While reverse causality may contribute to some associations between
biomarkers of Pb exposure and renal function, the available evidence does not support it as the driving
force behind these associations.
5.9 Biological Plausibility
Sections 5.3 to 5.8 of this Appendix describe the health effects associated with exposure to Pb
from epidemiologic and animal toxicological studies. Based largely on the animal toxicological evidence
presented in these sections, as well as in previous ISAs and AQCDs, this section describes the biological
pathways that potentially underlie the renal outcomes identified in epidemiologic studies and that are
associated with Pb exposure. Figure 5-9 graphically depicts these proposed pathways as a continuum of
pathophysiological responses—connected by arrows—that may ultimately lead to the apical renal events
associated with exposures to Pb at concentrations observed in epidemiologic studies. Note that the role of
biological plausibility in contributing to the weight-of-evidence causality determinations reached in the
current Pb ISA is discussed in Section 5.10.
When considering the available health evidence, plausible pathways connecting Pb exposure to
the apical events reported in epidemiologic studies are presented in Figure 5-9. The first pathway begins
with oxidative stress directly resulting in kidney damage and increases in blood pressure. The second
pathway involves Pb activation of RAAS resulting in increases in blood pressure. Once these pathways
are initiated, there is evidence from experimental and observational studies that exposure to Pb may result
in a series of pathophysiological responses that could lead to adverse renal events such as CKD and
kidney failure.
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Upregulation of
Renin-Angiotensin
System
Increased
Blood
Pressure/
Hypertension
4
T
T,	 1
Impaired Renal
Function (e.g.,
changes in GFR,
Increased Serum
Creatinine Levels
1 	
	~
Chronic Kidney
Disease and its
Progression
Note: The boxes above represent the effects for which there is experimental or epidemiologic evidence related to ozone exposure,
and the arrows indicate a proposed relationship between those effects. Solid arrows denote evidence of essentiality as provided, for
example, by an inhibitor of the pathway or a genetic knockout model used in an experimental study involving Pb exposure Shading
around multiple boxes is used to denote a grouping of these effects. Arrows may connect individual boxes, groupings of boxes, and
individual boxes within groupings of boxes. Progression of effects is generally depicted from left to right and color-coded (gray,
exposure; green, initial effect; blue, intermediate effect; orange, effect at the population level or a key clinical effect). Here,
population level effects generally reflect the results of epidemiologic studies. When there are gaps in the evidence, there are
complementary gaps in the figure and the accompanying text below.
Figure 5-9 Potential biological pathways for renal effects following Pb
exposure.
It has been well established that exposure to Pb can stimulate the production of reactive oxygen
species and markers of inflammation in the blood or kidneys (see (U.S. EPA. 2013)). and evidence
published since the last Pb ISA further supports these findings. For example, in rats Andielkovic et al.
(2019) reported a statistically significant increase (p < 0.05) in total oxidative status and the oxidative
stress index in blood following Pb exposure (-30 (ig/dL BLL). These authors also reported a decrease
(p < 0.05) in the total antioxidative status in blood following Pb exposure (-30 (ig/dL BLL). Moreover,
Pb exposure to rat primary proximal tubular cells increased intracellular reactive oxygen species
production in a concentration-dependent manner (Wang et al.. 2011). In both of these studies, the authors
reported higher levels of lipid peroxidation (e.g., malondialdehyde or thiobarbituric acid reactive
substance levels) in kidney tissue (Andielkovic et al.. 2019) and primary cells (Wang et al.. 2011) relative
to controls. Other studies similarly demonstrated increased indicators of lipid peroxidation in serum and
renal tissue after exposure to Pb (Gao et al.. 2020; Shi et al.. 2020; Li et al.. 2017; Laamech et al.. 2016;
Berrahal et al.. 2011; Lodi et al.. 2011; Moneim et al.. 2011; Wang et al.. 2011; Masso-Gonzalez and
Antonio-Garcia. 2009). This is important given that lipid peroxidation can be an indicator of tissue
damage and because numerous studies that included kidney histology have demonstrated abnormalities
and damage to kidney cells or tissue following Pb exposure (Gao et al.. 2020; Shi et al.. 2020; Alcaraz-
Contreras et al.. 2016; Laamech et al.. 2016; Basgen and Sobin. 2014; Roncal et al.. 2007; Rodriguez-
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Iturbe et al.. 2005; Fowler etal.. 1980). Some of these Pb-induced kidney changes have been found to be
the result of Pb-induced cellular necrosis (Fowler et al.. 1980) or apoptosis (Rana. 2008). and studies have
demonstrated that inhibiting Pb-induced oxidative stress and inflammation can ameliorate kidney damage
(Rana et al.. 2020; Shafiekhani et al.. 2019). These kidney abnormalities could plausibly result in
impaired kidney function. Following exposure to Pb, markers of impaired kidney function such as
increased levels of creatinine and BUN)have been reported in animal toxicological studies (Shi et al..
2020; Andielkovic et al.. 2019; Laamech et al.. 2016; Zou et al.. 2015; Berrahal et al.. 2011; Roncal et al..
2007). In addition, the previous ISA included studies in which exposure to Pb resulted in either decreased
(Shi et al.. 2020) or elevated glomerular filtration rates (GFR) (Khalil-Manesh et al.. 1993; Khalil-Manesh
etal.. 1992b; Khalil-Manesh et al.. 1992a). both of which can be indicative of kidney disease. These
studies demonstrated that decreased GFR can be indicative of reduced blood filtration by the kidneys,
while increased GFR can be consistent with the hyperfiltration and renal hypertrophy that can occur in
advanced diabetes.
Pb-induced oxidative stress can also lead to the adverse kidney outcomes reported in
epidemiologic studies through hypertension. As detailed in the cardiovascular disease appendix, oxidative
stress can lead to increases in blood pressure through a number of different pathways. An increase in
blood pressure due to Pb-induced oxidative stress is supported by a study demonstrating that in rats, the
antioxidant vitamin E could attenuate both Pb-induced oxidative stress and blood pressure increases
(Vaziri et al.. 1999). This is important given that a chronic increase in blood pressure can lead to
glomerular and renal vasculature injury, which could plausibly result in renal dysfunction and CKD.
The second pathway by which exposure to Pb could potentially lead to the outcomes reported in
epidemiologic studies is through RAAS. RAAS plays an important role in the regulation of blood
pressure and kidney homeostasis. For example, Ang II is an important part of RAAS that stimulates
arteriolar vasoconstriction, leading to increases in blood pressure and hypertension, which as noted above,
could plausibly contribute to kidney dysfunction, CKD, and kidney failure. Following Pb exposure,
vascular reactivity to Ang II was found to increase (Robles et al.. 2007). Exposure to Pb also resulted in
increases in kidney and serum ACE activity as well as renal Ang II-positive cells (Rodrigucz-lturbc et al..
2005; Sharifi et al.. 2004; Carmignani et al.. 1999). Moreover, use of an ACE inhibitor or blocking the
AT-1 receptor (which binds ANG II) ameliorated Pb-induced increases in blood pressure (Simocs et al..
2011).
When considering the available evidence, there are plausible pathways connecting Pb exposure to
renal effects (Figure 5-9). The first potential pathway begins with Pb-induced oxidative stress, which
results in kidney damage and increases in blood pressure, while the second potential pathway is through
the activation of RAAS, which can also result in an increase in blood pressure. Increased blood pressure
can then lead to kidney damage and impaired function, which if sufficiently severe, can lead to kidney
disease. Collectively, these proposed pathways provide biological plausibility for the associations
between Pb levels and adverse renal effects reported in epidemiologic studies.
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5.10
Summary and Causality Determination
In the 2013 Pb ISA, a suggestive relationship between exposure to Pb and renal effects was
judged appropriate on the basis of the health evidence and its associated uncertainties. Studies published
since the 2013 ISA greatly expand the evidence base and serve to strengthen the evidence for a
relationship between exposure to Pb and renal-related health effects. In addition, more recent evidence
has greatly reduced (but not eliminated) key uncertainties from the last review, particularly those
associated with the potential for reverse causality in epidemiologic studies (see below). This section
presents the causality determination for Pb exposures and renal effects, relying upon the framework for
causality determinations described in the Preamble to the ISAs (U.S. EPA. 2015). Key health evidence
supporting this determination is also summarized in Table 5-1.
In the 2013 Pb ISA, prospective epidemiologic studies in older adult, mostly white, men
supported the relationship between long-term Pb exposure and reduced kidney function at mean BLLs
<10 (ig/dL (Tsaih et al.. 2004; Kim et al.. 1996). Other population-based prospective cohort studies
reported a longitudinal association between BLLs and increases in serum creatinine and CKD progression
overtime (Yu et al.. 2004). In addition, most epidemiologic cross-sectional studies discussed in the last
review reported that higher tissue Pb concentrations (e.g., blood or bone Pb levels) are associated with
impaired renal function (Navas-Acicn et al.. 2009; Muntner et al.. 2005; Muntner et al.. 2003). Important
uncertainties were raised in the last review with respect to the epidemiologic evidence, particularly the
potential for reverse causality. That is, given the kidney's role in removing toxins from the blood,
increased BLLs could result from reduced excretion due to pre-existing kidney damage rather than as the
causative factor for kidney impairment. It was further noted in the last review that the existence of an
association in adults with normal renal function does not preclude the possibility of reverse causation
because the variation in Pb clearance within the range of normal kidney function is unknown. Other
uncertainties identified in the epidemiologic evidence from the last review were related to the Pb
exposure level, timing, frequency, and duration contributing to the associations reported in these studies
given that most were performed in adult populations with likely higher past Pb exposures. With respect to
the animal toxicology evidence, the 2013 Pb ISA noted that at BLLs >30 (ig/dL, there was clear evidence
that Pb exposure caused changes to the kidney morphology and function (Khalil-Manesh et al.. 1992b;
Khalil-Manesh et al.. 1992a). Evidence for functional changes in animals at lower BLLs was more limited
and therefore, more uncertain. When the health evidence was considered along with these uncertainties,
particularly uncertainties related to the potential for reverse causality, the 2013 ISA concluded that
evidence was suggestive of, but not sufficient to infer, a causal relationship between exposure to Pb and
renal effects.
More recent epidemiologic and animal toxicological studies greatly expand the evidence base
from the 2013 Pb ISA. Not only do these newer studies strengthen the evidence of a relationship between
exposure to Pb and renal effects, they also serve to appreciably reduce the uncertainties identified in the
last review. As noted above, the potential for reverse causality was the most influential uncertainty for the
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conclusion in the last review that the scientific evidence was suggestive of, but not sufficient to infer, a
causal relationship between exposure to Pb and renal effects. That is, increased BLLs could result from
reduced excretion due to kidney damage (unrelated to Pb exposure) rather than as a causative factor for
kidney impairment. Cross-sectional studies and studies conducted in populations that are already
experiencing renal dysfunction have the greatest potential for reverse causality. However, prospective
analyses that include both baseline measurements of biomarkers of Pb exposure as well as incident
changes in renal function provide some assurances that associations observed across the epidemiologic
literature are due to a true association with Pb and are not the result of reverse causality. Thus, it is
important to note the more recent longitudinal analyses finding positive associations between exposure to
Pb and kidney disease (Harari et al.. 2018) and decreases in eGFR (Chung et al.. 2020; Liu et al.. 2020).
These longitudinal studies are in agreement with other types of epidemiologic studies reporting similar
associations between exposure to Pb and kidney disease (Wan et al.. 2021; Hagcdoorn et al.. 2020; Lee et
al.. 2020; Wu et al.. 2019; Huang et al.. 2013; Sommar et al.. 2013) and decreases in eGFR (Chung et al..
2020; Liu et al.. 2020; Pollack et al.. 2015). Additional evidence suggesting the that results in
epidemiologic studies are not attributable to reverse causality comes from an epidemiologic study
demonstrating that exposure to Pb is associated with changes in creatinine levels consistent with reduced
kidney function and disease (Pollack et al.. 2015). Importantly, this more recent creatinine study is also
consistent with two longitudinal studies from the prior review presenting similar results (Tsaih et al..
2004; Kim et al.. 1996). Moreover, these epidemiologic studies were performed in a number of different
geographical areas and in diverse study populations, further reducing the chance that epidemiologic
results are due to reverse causality.
Strong support that the associations reported in epidemiologic studies are not from reverse
causality also come from the expanded literature base of animal toxicological studies. In particular, there
is a large body of animal toxicological studies published since the last review largely demonstrating renal
damage or structural abnormalities in rodents following exposure to Pb (Dumkova et al.. 2020a; Gao et
al.. 2020; Shi et al.. 2020; Dumkova et al.. 2017; Alcaraz-Contreras et al.. 2016; Laamech et al.. 2016;
Basgen and Sobin. 2014; Rodriguez-Iturbe et al.. 2005; Fowler etal.. 1980). With respect to
concentrations, effects in rodents were observed in studies at BLLs ranging from -3.0 (ig/dL to
-30 (ig/dL. It is important to note that there is some uncertainty of an effect at this lowest level given that
the same study did not report similar morphological effects at higher BLLs (Basgen and Sobin. 2014) and
that Carlson et al. (2018) reported that renal lesions in mice with a BLL of -3.0 (ig/dL were similar to the
lesions in controls. Nonetheless, there is substantial evidence from animal histological studies for kidney
abnormalities following exposure to Pb, thus providing additional support that the positive associations
for renal disease and impaired renal function reported in longitudinal and cross-sectional epidemiologic
studies are not due to reverse causality. Moreover, these animal toxicology studies also serve to reduce,
but not eliminate, the uncertainty noted in the last review with respect to effects in animals at the lowest
BLLs.
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Epidemiologic studies are also coherent with animal toxicological studies in that they both
provide some evidence of a positive relationship between exposure to Pb and molecular markers of
impaired kidney function in blood, urine, or tissue. As noted above, the 2013 ISA (U.S. EPA. 2013)
evaluated a couple of longitudinal epidemiologic studies that reported positive associations between
increases in serum creatinine levels and bone Pb measurements (Tsaih et al.. 2004; Kim et al.. 1996).
These studies are in agreement with a more recent epidemiologic study describing a positive association
between increasing BLLs and serum creatinine increases in premenopausal women (Pollack et al.. 2015).
In coherence with these epidemiologic studies are a number of animal toxicological studies from the
previous and current review with BLLs below 30 (ig/dL. Although not all studies demonstrated an
increase, most of these studies reported higher blood creatinine levels in Pb-exposed animals compared
with controls (Shi et al.. 2020; Andielkovic et al.. 2019; Laamech et al.. 2016; Zou et al.. 2015; Berrahal
et al.. 2011; Roncal et al.. 2007).
Similar to creatinine levels, changes in measures of blood urea can also be indicative of renal
disease. Although there were no epidemiologic studies examining measures of urea, animal toxicological
studies published since the 2013 Pb ISA (blood Pb values of < 30 (ig/dL) generally indicated that
exposure to Pb can increase serum or kidney measures of urea (Gao et al.. 2020; Shi et al.. 2020;
Laamech et al.. 2016; Zou et al.. 2015). It should be noted, however, that there is at least some variability
with respect to the direction of serum urea levels following Pb exposure. In contrast to the studies
mentioned above, both Andielkovic et al. (2019) and Dumkova et al. (2020a) reported a statistically
significant (p < 0.05) decrease in measures of urea relative to controls, while other studies reported no
effect (Carlson et al.. 2018; Corsetti et al.. 2017) (BLL of 2.89 (ig/dL). It is difficult to interpret whether
there is biological significance to a decrease in serum urea levels relative to control animals, but
nonetheless, most animal toxicological studies reported changes in the levels of urea following exposure
to Pb, with most of those changes being increases. Moreover, the results of these creatinine and urea
studies further strengthen the thesis that the effects observed in epidemiologic studies are truly due to Pb
exposure. Other potential markers of kidney function evaluated in epidemiologic and animal toxicological
studies (e.g., UA, proteinuria) were more limited in number with varying results, and therefore, more
uncertain.
As described throughout this causal determination section, there is considerable animal
toxicological evidence supporting Pb as the causative agent for the positive epidemiologic associations
between measures of Pb exposure and adverse health outcomes. Section 5.9 of this document includes
that information to construct a plausible pathway by which exposure to Pb could result in impaired kidney
function or renal disease. In brief, Section 5.10 notes that exposure to Pb can stimulate the production of
reactive oxygen species in the blood or kidneys of exposed laboratory animals (see (U.S. EPA. 2013)
Section 4.5.3.1). Some studies have also reported increases in lipid peroxidation in kidney tissue or
primary cells relative to control animals (Section 5.9). Lipid peroxidation is often an indicator of tissue
damage and thus, is consistent with the animal histology studies mentioned above demonstrating renal
damage following Pb exposure. Given these results in animal toxicological studies, it is plausible that
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associations with renal dysfunction and renal disease (e.g., CKD) reported in epidemiologic studies could
be due to underlying kidney damage from Pb-induced oxidative stress.
The biological plausibility section (Section 5.9) also notes that Pb could potentially lead to the
outcomes reported in epidemiologic studies through RAAS, which has an important role in the regulation
of blood pressure and kidney homeostasis. Ang II is a component of RAAS that stimulates arteriolar
vasoconstriction, leading to increases in blood pressure and hypertension, and Ang II levels can be
increased by exposure to Pb (Sections 5.6 and 5.9). Importantly, prolonged blood pressure increases can
eventually lead to glomerular and renal vasculature injury, plausibly resulting in the renal dysfunction and
renal disease associations observed in epidemiologic studies.
In summary, the recent evidence described throughout this section extends the consistency and
coherence of the evidence base reported in the 2013 Pb ISA. Recent epidemiologic and animal toxicology
studies have also served to greatly reduce uncertainties noted in the previous review, especially with
respect to the potential for reverse causality in epidemiologic studies. Direct evidence for Pb exposure-
related renal effects can be found in numerous animal toxicological studies. In coherence with these
results are epidemiologic studies which found that Pb exposure is associated with some of the same renal
endpoints reported in animal toxicological studies (e.g., eGFR, blood markers of renal impairment). For
some markers of renal function, there is a limited number of studies evaluating these endpoints, and there
are some inconsistencies in results across some of the animal toxicological and epidemiological studies.
In general, these studies largely demonstrate a relationship between exposure to Pb and indicators of
kidney distress. Moreover, animal toxicological studies demonstrating renal damage following Pb
exposure provide coherence and biological plausibility for the consistent epidemiologic associations
reported between body Pb concentrations and renal disease. Thus, the collective evidence is sufficient to
conclude that there is a causal relationship between Pb exposure and renal effects. The key evidence,
as it relates to the causal framework, is summarized in Table 5-1.
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Table 5-1 Summary of evidence indicating a causal relationship between Pb
exposure and renal effects.
Rationale for
Causality
Determination3
Key Evidence13
References'3
Pb Biomarker Levels
Associated with Effects0
Generally consistent
Positive associations
(Wu et al.. 2019: Harari et al.. BLLs: -2 to >25
evidence from
between body Pb
2018: Sommar et al.. 2013)
epidemiologic studies
measurements (e.g., blood

of CKD
Pb) and CKD or ESRD


incidence

Generally consistent
evidence from
epidemiologic studies
of diabetic
nephropathy
Mostly positive associations
between body Pb
measurements (e.g., blood
Pb) and diabetic nephropathy
(Wan et al.. 2021: Haqedoorn BLB: <80 to 600 |jg
et al.. 2020; Huang et al..
2013).
BLLs: -1.5 to 6 pg/dL
Generally consistent
Mostly positive associations
(Chung et al.. 2020: Liu et al.. BLLs: -3 to >30 ug/dL
evidence from
between body Pb
2020: Jain. 2019: Buser et al..
epidemiologic studies
measurements (e.g., blood
2016: Chung etal.. 2014: Kim
of eGFR
Pb) and eGFR
and Lee. 2012: Navas-Acien

et al.. 2009: Akesson et al..


2005: Tsaih etal.. 2004: Kim


etal.. 1996)
Generally consistent Mostly positive associations
evidence from	between body Pb levels and
epidemiologic studies increases in creatinine
for creatinine in blood
or urine
(Pollack et al.. 2015: Tsaih et BLLs: -0.9 to 10 pg/dL
al.. 2004: Kim et al.. 1996)
Mostly null findings
from epidemiologic
studies for measures
of UA
Increase in SUA among
women, but not men
(Park and Kim. 2021)
BLL: -2 pg/dL
Null results between body Pb
and measures of UA and
hyperuricemia
(Arrebola et al.. 2019: Jung et BLLs:-0.1 to 2 pg/dL
al.. 2019)
Generally consistent
evidence from animal
toxicological studies
for changes in GFR
Pb-exposed rats had a
statistically significantly lower
(p < 0.05) GFR relative to
control rats
(Shi et al.. 2020)
BLL-10.21 pg/dL
Pb-exposed rats had a
statistically significant
increase in GFR indicative of
renal hyperfiltration and
hypertrophy
{Khalil-Manesh, 1993,
50791 ;Khalil-Manesh, 1992,
49502; Khalil-Manesh; 1992,
49543)
BLL: -30-45 pg/dL
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Rationale for
Causality	Key Evidence*	References*	Associatedwfth
Determination3	Associated witn tnects
Consistent evidence Animal toxicological studies (Gao et al.. 2020: Shi et al.. BLL:~10-30 [jg/dL
from animal
toxicological studies
of kidney histology
consistently demonstrate
renal damage or
abnormalities in animals
following Pb exposure
2020; Dumkova et al.. 2017;
Alcaraz-Contreras et al..
2016: Laamech et al.. 2016:
Basqen and Sobin, 2014:
Rodriauez-lturbe et al.
Fowler et al.. 1980)
2005:
Some evidence from
animal toxicological
studies for increased
creatinine in blood or
urine
Most animal studies involving
exposure via drinking water
or gavage demonstrated a
statistically significant
increase in serum creatinine
(or decrease in urine)
following exposure to Pb
A single animal toxicology
study using an inhalation
exposure methodology
reported a decrease in
creatinine levels
(Shi et al.. 2020: Andielkovic
et al.. 2019: Laamech et al..
2016: Zou et al.. 2015)
BLL:~10-30 pg/dL
(Dumkova et al.. 2020a)
BLL: -14 pg/dL
A couple of animal toxicology	g|_|_ 2 89 pg/dL
studies using a drinking water (Carlson et al.. 2018)
exposure methodology
reported no change in	BLL 21.6 pg/dL
creatinine levels in mice {Corsett|. 2017' 4856550
Some evidence from Most animal studies involving Gao, 2020, 7087494; Zou, BLL:~10-30 pg/dL
animal toxicological
studies for changes
in blood or urine
levels of urea
exposure via drinking water
or gavage demonstrated a
statistically significant
increase in measures of urea
following exposure to Pb
A couple of animal toxicology
studies reported a decrease
in urea levels
2015, 2830614; Shi, 2020,
7084022; Laamech, 2016,
6716234}
(Andielkovic et al.. 2019)
(Dumkova et al.. 2020a)
BLL:~23 pg/dL
BLL:~14 pg/dL
An animal toxicology study
reported no change in BUN
levels in mice
(Carlson et al.. 2018)
BLL 2.89 pg/dL
BLB = body Pb burden; BLL = blood Pb level; BUN = blood urea nitrogen; CKD = chronic kidney disease; eGFR = estimated
glomerular filtration rate; ESRD = end-stage renal disease; GFR = glomerular filtration rate; Pb = lead; SUA = serum uric acid;
UA = uric acid.
aBased on aspects considered in judgments of causality and weight of evidence in causal framework in Table I and Table II of the
Preamble to the ISAs (U.S. EPA. 2015).
bDescribes the key evidence and references, supporting or contradicting, contributing most heavily to causality determination and,
where applicable, to uncertainties or inconsistencies. References to earlier sections indicate where the full body of evidence is
described.
°Describes the Pb biomarker levels at which the evidence is substantiated.
1
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5.11 Evidence Inventories - Data Tables to Summarize Study Details
Table 5-2 Epidemiologic studies of Pb exposure and kidney disease.
Reference and Study
Design
Study Population Exposure Assessment
Outcome
Confounders
Effect Estimates and
95% Cis*
Harari et al. (2018)
Malmo,
Sweden
Baseline: 1991-1994,
Follow-up: 2007-2012
Cohort
Cardiovascular Blood Pb (ICP-MS) [jg/dL
cohort of Malmo Diet Median: 2.5 (Range; 0.15-
and Cancer Study 25.8)
(MDCS-CC)	Max: 25.8
n = 4,341 enrolled in Quartiles
cohort, 2,567
followed up
Median (range)
Q1 1.5 (0.15-1.85)
Q2 2.2 (1.85-2.47)
Q3 2.9 (24.7-3.30)
Q4 4.6 (3.3-25.8)
Q1 +Q2 + Q3 2.2 (0.15-
3.30)
CKD
Age of outcome 73
Linear regression or
Cox proportional
hazards regression
adjusted for age, sex,
smoking, alcohol
intake, hypertension,
diabetes, waist
circumference, eGFR
at baseline, education
level
CKD (HR)a
Q1 Reference
Q2 0.83 (0.54, 1.28)
Q3 0.83 (0.53, 1.29)
Q4 1.3 (0.85, 2.00)
Q4 vs. Q1 + Q2 + Q3
1.49 (1.07, 2.08)
Age at measurement 57
Wu et al. (2019)
Taiwan
Case-control
n = 658
220 CKD patients,
438 controls (age
and gender
matched)
Red blood cell Pb
(ICP-MS) (|jg/dL)
Tertiles
T1 <2.794
T2 2.794-4.635
T3 > 4.635
Age at measurement
Mean (SE)
Cases 65.14(0.91)
Controls 64.21 (0.60)
CKD
CKD: eGFR
<60 mL/min/1.73 m2 for 3
consecutive mo
Unconditional logistic
regression adjusted
for age, sex,
educational level,
alcohol, tea, and
coffee drinking,
analgesic use,
diabetes,
hypertension, urinary
creatinine, total
urinary arsenic, blood
cadmium, and blood
selenium
Blood Pb log-transformed
ORa
T1 Reference
T2 3.26 (1.58, 6.71)
T3 6.48 (3.23, 12.99)
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Reference and Study
Design
Study Population Exposure Assessment
Outcome
Confounders
Effect Estimates and
95% Cis*
Lee et al. (2020)
United States
1999-2016
Cross-sectional (EWAS)
NHANES
n = 46,748
Adults >18
Blood Pb (ICP-MS)
Distribution not reported
Age at Measurement:
Mean (SD) 47 (19)
CKD
CKD 1: ACR > 30 mg/g or
eGFR < 60 mL/min/1.73 m2
CKD 2: ACR > 300 mg/g, or
ACR > 30 mg/g and
eGFR < 60 mL/min/1.73 m2,
eGFR < 45 mL/min/1.73 m2
logistic regression
adjusted for age, sex,
diabetes,
hypertension, BMI,
race/ethnicity,
smoking, and SES
or
CKD 3 ACR > 300 mg/g and
eGFR < 60 mL/min/1.73 m2, or
ACR > 30 mg/g and
eGFR < 45 mL/min/1.73 m2, or
eGFR < 30 mL/min/1.73 m2)
Per SD of the log-
transformed blood Pb
concentration
ORa
CKD 1
Discovery set: 1.27 (1.12,
1.45)
Validation set: 1.12 (1.00,
1.24)
CKD 2
Discovery set: 1.43 (1.29,
1.58)
Validation set: 1.45 (1.29,
1.63)
CKD 3
Discovery set: 1.73 (1.54,
1.95)
Validation set: 1.61 (1.35,
1.90)
Kim et al. (2015)
South Korea
2011
Cross-sectional
KNHANES
n = 1,797
Participants >20 yr of
Blood Pb (GFAAS) (|jg/dL)
Mean (SD)2.37 (1.02)
f
Age at Measurement:
Mean (SD) 46 (14)
CKD
logistic regression OR: 1.05 (0.85, 1.30)a
(eGFR < 60 mL/min/1.73 m2or adjusted forage, sex,
ACR > 30 mg/g)
BMI, smoking,
hyperlipidemia,
hypertension,
diabetes, blood
mercury, and blood
cadmium
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Reference and Study
Design
Study Population Exposure Assessment
Outcome
Confounders
Effect Estimates and
95% Cis*
Sommar et al. (2013)
Sweden
1985 for Vasterbotten
Intervention Project, 1985
for MONICA, 1995 for
Mammography Screening
Project, and 1991-1996 for
Malmo Diet and Cancer
study. Follow-up through
linkage to Swedish Renal
Registry in 2006
Prospective nested case-
referent (mean 7.7 yr of
follow-up, range 1-16 yr)
Vasterbotten
Intervention Project,
the Northern
Sweden WHO
Monitoring of Trends
and Cardiovascular
Disease (MONICA)
study,
Mammography
Screening Project,
and Malmo Diet and
Cancer study
n = 118 cases and
378 controls
Blood (erythrocyte Pb
measured by ICP-MS)
(Hg/dL)
Geometric Mean
Cases 6.62
Referents 5.50
Age at Measurement:
Mean(Range)63 (40-80)
ESRD
(GFR <10-15 mL/min),
starting renal replacement
therapy (i.e., dialysis or
transplantation)
Conditional logistic OR
regression adjusted 1.14(1.03,
for diabetes, BMI, and
hypertension
Three controls
(referents) matched to
each ESRD cases by
cohort, age, sex, and
time of sampling
1.26)
Huang et al. (2013)
China
24-mo observation period
Cohort
n = 85
Patients with type 2
diabetes with
nephropathy (aged
30-83)
eGFR
Primary outcome (2-fold
increase in serum creatinine
from baseline values, need for
long-term dialysis, or death)
BLB (X-ray fluorescence and Diabetic Nephropathy
EDTA) (pg)
Low (BLB < 80 |jg)
Mean (SD) 58.1 (16.7)
Max: 79.8
High (BLB 80-600 pg)
Mean (SD) 132.4 (46.1)
Max 316.8
Blood (ETAAS) (|jg/dL)
Low (BLB < 80 pg)
Mean (SD) 3.8 (3.0)
Max 10.4
High (BLB 80-600 pg)
Mean (SD) 4.6 (3.1)
Max: 10.3
Longitudinal
eGFR (mL/min/1.73 m2
1 pg increase in BLB
-0.022 (-0.039, -0.005)
1 pg/dL increase in Blood
Pb
-0.298 (-0.525, -0.071)
multivariate analysis
or Cox regression
analysis adjusting for
age, sex, smoking,
BMI, history of CVD,
MAP, cholesterol,
triglycerides, HbA1c,
serum creatinine, daily Primary outcome
protein intake, daily BLB: HR: 1.01 (95% CI:
protein excretion 1.01,1.02)
BLB > 80 pg: HR 2.79 (CI:
1.25, 6.25)
Age at Measurement
Mean (SD) 60.1 (9.5) Range
33-83
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Reference and Study
Design
Study Population Exposure Assessment
Outcome
Confounders
Effect Estimates and
95% Cis*
Haqedoorn et al. (2020)
The Netherlands
2009-2016
Cross-sectional
Blood Pb (ICP-MS) (pg/dL) DKD
DIAbetes and
LifEstyle Cohort
Twente-1 (DIALECT-	(|QR) ^ (Q ^
n = 231	1-86>
With type 2 diabetes Age at Measurement:
Mean (SD) 64 (9)
(Creatinine clearance
< 60 mL/min/1.73 m2) and/or
presence of albuminuria (ALB
excretion > 30 mg/d)
Logistic regression	OR for doubling of blood
adjusted for age, sex,	Pb (log 2 transformed)
HbA1c, insulin use, yr	(pmol/L)a
of diabetes, MAP,
alcohol intake, pack	Creatinine clearance
yr, and blood	< 60 mL/min/1.73 m2
cadmium	OR 1.83 (1.07, 3.15)
Albuminuria > 30 mg/d
OR 1.75 (1.11, 2.74)
Wan et al. (2021)
China
May-August 2018
Cross-sectional
Environmental
Pollutant Exposure
and Metabolic
Diseases in
Shanghai n = 4,234
Blood (AAS) Pb (pg/dL)
Median (IQR)
2.6 (1.8, 3.6)
Age at Measurement
Median (IQR)
67 (62-72) yr
DKD	Linear or logistic
regression adjusting
ACR (high, >30 mg/g); DKD as for age, sex, duration
defined by American Diabetes of diabetes, education
Association (ACR > 30 mg/g or status, current
eGFR < 60 mL/min per	smoking, BMI, HbA1c,
1.73 m2)	dyslipidemia,
hypertension
OR (4th vs. 1st quartile of
Blood Pb)a
DKD 1.36 (1.06, 1.74)
ACR (>30 mg/g) 1.31,
(1.02, 1.69))
Hara et al. (2016)
Northeastern Belgium
Baseline blood Pb (1985-
1989), follow-up through
2014
Cohort
Cadmium in Belgium Blood Pb (ETAAS with
(CadmiBel) study
n = 1,302
Flemish residents
(>20 yr), randomly
recruited from 10
districts in
northeastern
Belgium
Zeeman correction) (pg/dL)
Geometric Mean (IQR) 6.00
(3.31, 10.35)
Age at Measurement:
Mean (SD) 47.8 (15.6)
Nephrolithiasis (Self-reported Cox regression
and verified by investigators adjusted for age, sex,
against medical records. serum magnesium,
Cases were symptomatic, and 24 hr urinary volume,
often hospitalized for diagnosis and calcium
and treatment)
Per doubling of blood Pb
(pmol/L)a(HR)
Baseline Pb 1.35 (1.06,
1.73)
Mean (baseline and follow-
up averaged): 1.32 (1.03,
1.71)
Baseline with regression
dilution bias correction
1.44 (1.07, 1.93)
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Reference and Study
Design
Study Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and
95% Cis*
Sun etal. (2019)
NHANES
Blood Pb (ICP-MS)d (|jg/dL)
Nephrolithiasis (Self-reported
Logistic regression
Weighted OR (95% CI)

n = 21,402
Median: 1.22
history of kidney stones)
adjusting for age, sex,

2007-2016

95th: 3.89

race/ethnicity, BMI,
Compared with reference

Adult (>20 yr)
Max: 61.29

educational level,
level (0.05 pg/dL)
Cross-sectional
participants from

marital status, annual
0.50 pg/dL: 0.88 (0.81,

NHANES


family income,
0.95)




smoking, physical
1.00 pg/dL: 0.75 (0.63,




activity, intake of total
0.89)




energy, calcium,
1.50 pg/dL: 0.67 (0.52,




phosphate, sodium,
0.85)




potassium,
2.00 pg/dL: 0.62 (0.46,




magnesium, total fluid,
0.83)




alcohol, caffeine,
2.5 pg/dL: 0.60 (0.44,




vitamin B6, vitamin C,
0.82)




and vitamin D, and
3.0 pg/dL: 0.60 (0.43,




eGFR
0.84)





3.5 pg/dL: 0.60 (0.44,





0.86)





4.0 pg/dL: 0.61 (0.44,





0.86)





4.5 pg/dL: 0.63 (0.45,





0.88)





5.0 pg/dL: 0.64 (0.46,





0.90)
AAS = angiotensin-aldosterone system; ACR = albumin-to-creatinine ratio; ALB = albumin; BLB = body Pb burden; BMI = body mass index; CI = confidence interval; CKD = chronic
kidney disease; CVD = cardiovascular disease; DKD = diabetic kidney disease; eGFR = estimated glomerular filtration rate; EDTA = ethylenediaminetetraacetic acid; ESRD = end
stage renal disease; ETAAS = Electrothermal Atomic Absorption Spectrometry; EWAS = environment wide association study; GFAAS = Graphite Furnace Atomic Absorption
Spectrometry; GFR = glomerular filtration rate; HbA1c = hemoglobin A1c; HR = hazard ratio; hr = hour; ICP-MS = Inductively Coupled Plasma Mass Spectrometry; IQR = interquartile
ratio; MAP = mean arterial pressure; MDCS-CC = cardiovascular cohort of the Malmo Diet and Cancer Study; mo = months; MONICA = Monitory of Trends and Cardiovascular
Disease; NHANES = National Health and Nutrition Examination Survey; OR = odds ratio; Pb = lead; Q = quartile; SE = standard error; SES = socioeconomic status; T = fertile;
yr = year.
'Effect estimates are standardized to a 1 |jg/dL increase in blood Pb or a 10 |jg/g increase in bone Pb, unless otherwise noted. If the Pb biomarker is log-transformed, effect estimates
are standardized to the specified unit increase for the 10th-90th percentile interval of the biomarker level. Effect estimates are assumed to be linear within the evaluated interval.
Categorical effect estimates are not standardized.
aUnable to be standardized.
blncrement unclear.
Confidence intervals estimated based on reported p-values.
dBlood Pb analysis method not reported, assumed based on data set (NHANES).
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Table 5-3
Animal toxicological studies of Pb exposure and kidney histology.
Study
Species (Stock/Strain), n,
Sex
Timing of
Exposure
Exposure Details
(Concentration,
Duration)
BLL as Reported (ng/dl_)
Endpoints Examined
Basqen and
Sobin (2014)
Mouse
Control
(Pb-free drinking water),
M/F, n = 12, (6/6)
30 ppm, M/F, n = 12, (6/6)
330 ppm, M/F, n = 12, (6/6)
In utero to PND
28
Drinking water from
dams was treated with
99.4% Pb acetate. Litters
were then exposed to 0,
30, or 330 Pb acetate in
drinking water for 28 d
0.03 ± 0.01 |jg/dL for control
males
0.03 ± 0.01 |jg/dL for control
females
3.63 [jg/dL ± 0.71 pg/dLfor
30 ppm males
2.74 pg/dL ± 0.36 pg/dL for
30 ppm females
Kidney Histology, podocyte
characteristics and glomerular
volume post 4-wk exposure
16.02 [jg/dL ± 3.25 pg/dLfor
330 ppm males
13.35 pg/dL ± 1.31 pg/dLfor
330 ppm females
Li etal. (2017)
Mouse (Balb/c)
Control
(water), F, n = 8
100 mg/kg/d Pb acetate, F,
n = 8
6-7 wk old mice
8 wk
Plain water or
100 mg/kg/d Pb acetate
for 1 d then given skim
milk from d -2-15
0.43 ± 0.05 pg/L for control
(4.3 ± 0.05 pg/dL)
302.20 ± 25.32 pg/L for
100 mg/kg/d Pb acetate
(30.2 ± 25.32 pg/dL)
Kidney Histology post
exposure
Alcaraz-
Contreras et al.
(2016)
Rat (Wistar)
Control (water), M, n = 5
2,000 ppm Pb acetate, M,
n = 5
2 mo old rats
exposed to Pb
for 8 wk
2 mo old rats received
drinking water, or
drinking water with
2000 ppm Pb acetate for
8 wk
21.9 ±2.0 pg/dLfor
2000 ppm group
Kidney Histologyl d post I
wk exposure
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Study
Species (Stock/Strain), n,
Sex
Timing of
Exposure
Exposure Details
(Concentration,
Duration)
BLL as Reported (ng/dl_)
Endpoints Examined
Rahman et al.
(2018)
Rat (Wistar)
Control (tap water), M/F,
n = 7-8
0.2% Pb acetate, M/F,
n = 7-8/group
PND 1 to PND
30
Pups were exposed to
0.2% Pb acetate from
PND 1 to PND 21
through dam's drinking
water. Then rats were
exposed directly through
drinking water until PND
30. Control animals were
given tap water
throughout
2.2	± 0.7 |jg/dL for control-
PND 21
12.4 ± 3.3 |jg/dL for 0.2% Pb
acetate-PND 21
3.3	± 1.7 |jg/dL for control-
PND 30
22.7 ± 6.0 [jg/dL for 0.2% Pb
acetate-PND 30
Kidney Histology at PND 21
and PND 30
Andielkovic et
al. (2019)
Rat (Wistar)
Control water, M, n = 8
150 mg/kg b.w., M, n = 6
Single exposure
by oral gavage
(age of rats not
reported)
Single oral dose of
150 mg/kg b.w. Pb
acetate
-25 |jg/L for control
(-2.5 pg/dL)
-225 pg/L for 150 mg/kg b.w.
Pb acetate
(-22.5 pg/dL)
Kidney histology 24-hr post
exposure
Carlson et al.
(2018)
Mouse (Control)
(water), M/F, n = 16
0.03 mM Pb, M/F, n = 8
Treatment began
no earlier than
an age
of 5 wk for 11 wk
Pb-free water or 0.03
mM Pb acetate dissolved
in drinking water for
11 wk
Control (water) not detected
2.89 ± 0.44 pg/dL for
0.03 mM
Kidney Histology one wk after
11 wk exposure
Dumkova et al.
(2017)
Mouse
Experiment 1:
Control (clean air), F,
n = 5
Adult mice
exposed for 6 wk
Experiment 1:
1.23 x 10s particles/cm3
of PbO inhalation
exposure or clean air for
6 wk (24/hr d, 7 d a wk)
Experiment 2:
<11 ng/g for control
(<1.166 pg/dL)
132 ng/g for Pb-exposed
(13.992 pg/dL; not specified
from which experiment
measurement was derived)
Kidney Histology post 6 wk
exposure
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Study
Species (Stock/Strain), n,
Sex
Timing of
Exposure
Exposure Details
(Concentration,
Duration)
BLL as Reported (ng/dl_)
Endpoints Examined

1.23 x 10® PbO
particles/cm3, F, n = 5
Experiment 2:
Control (clean air), F,
n = 5
0.956 x 10s particles/cm3,
F, n = 5

0.956 x 10s particles/cm3
of PbO inhalation
exposure or clean air for
6 wk (24/hr d, 7 d a wk)
(Experiment 2 was a
replicant of experiment
1):


Laamech et al.
(2016)
Mouse
Control
(distilled water), M/F,
n = 10
5 mg/kg/d Pb acetate,
M/F, n = 10
Age of mice in
experiment not
reported
Distilled water or
5 mg/kg/d Pb acetate
dissolved in distilled
water for 40 d
0.009 |jg/ml_ for control
(distilled water) (0.9 pg/dL)
0.18 |jg/ml_ for 5 mg/kg/d Pb
acetate (18 pg/dL)
Kidney Histology 2 d post
exposure
Shi et al.
(2020)
Rat (SD)
Control (deionized water),
M, n = 8
0.5% Pb acetate, M, n = 8
28 d after PND
21
After 21 d of milk
feeding, 0.5% Pb acetate
or deionized water for
28 d
0.18 ± 0.07 |jg/dL for Control
(deionized water)
10.21 ± 0.93 [jg/dL for 0.5%
Pb acetate
Kidney Histology post
exposure
Gao et al.
(2020)
Rat (SD)
Control
(Distilled water), M/F,
n = 10
5 mg/kg Pb acetate, M/F,
n = 10
Age of mice in
experiment not
reported
5 mg/kg Pb acetate orally
for 35 d followed by
recovery to d 63
<0.02 mg/kg for distilled water
(<2.12 [jg/dL)
0.10 ± 0.03 mg/kg for
5 mg/kg Pb acetate (d 64)
(10.6 ± 0.03 [jg/dL)
Kidney Histology following the
end of the experiment on d 63
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Study
Species (Stock/Strain), n, Timing of
Sex	Exposure
Exposure Details
(Concentration,
Duration)
BLL as Reported (ng/dl_)
Endpoints Examined
Dumkova et al. Mouse (Control)
(2020b)	(clean air), F, n = 10 (wk,
6 wk, 11 wk)
PbO, F, n = 10 (2 wk, 6 wk,
11 wk)
PbO recovery, F, n = 10
(6 wk PbO, 5 wk clean air)
Age of mice in
experiment
unclear
PbO 78.0 |jg PbO/m3 or
clean air for 24 hr/d
7 d/wk for 2 wk, 6 wk, or
11 wk. A recovery group
was exposed to PbO for
6 wk and then clean air
for 5 wk (11 wk total)
<3 ng/g in control (2 wk, 6 wk,
11 wk) (0.3 [jg/dL)
104 ng/g PbO 2 wk
(10.4 [jg/dL)
148 ng/g PbO 6 wk
(14.8 [jg/dL)
174 ng/g PbO 11 wk
(17.4 pg/dL)
Kidney histology at 2 wk,
6 wk, and 11 wk
Dumkova et al.
(2020a)
Mouse (Control)
(clean air), F, n = 10 (d 3,
2 wk, 6 wk, 11 wk)
Pb(N03)2 (68.6 |ag/m3), F,
n = 10 (d 3, 2 wk, 6 wk,
11 wk)
Recovery (Pb(N03)2
68.6 |ag/m3), F, n = 10
(6 wk Pb/5 wk recovery)
6-8 wk old mice
exposed for 3 d,
2 wk, 6 wk, or
11 wk
Pb(NOs) (68.6 |ag/mA3)
or clean air-exposed
mice for 3 d, 2 wk, 6 wk,
or 11 wk. To assess
recovery, a separate
group of mice were
exposed for 11 wk
followed by 5 wk of clean
air
<0.3 ng/g for control at all
timepoints (<0.3 |ig/dl_)
(d 3, 2 wk, 6 wk, 11 wk)
31 ng/g for Pb(N03)2 d 3
(3.1 ng/dL)
40 ng/g for Pb(N03)2 2 wk
(4.0 ng/dL)
47 ng/g for Pb(N03)2 6 wk
(4.7 ng/dL)
Kidney Histology post 3 d,
2 wk, 6 wk, 11 wk, and 11 wk
plus clearance for 5 wk
(-16 wk)
8 5 ng/g for Pb(N03)2 11 wk
(8.5 ng/dL)
10 ng/g forPb(N03)2
exposure 6 wk and clean air
for 5 wk (1.0 pg/dL)
d = days; hr = hours; mo = months; M = male; M/F = male/female; N03 = nitrate, PND = postnatal day, Pb(N03)2 = Pb nitrate, PbO = Pb oxide; wk = weeks.
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Table 5-4
Epidemiologic studies of Pb exposure and estimated glomerular filtration rate.
Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Yu et al. (2004)
Adult CKD
Blood Pb (ETAAS with
Change in eGFR
Cox proportional hazard model
Change in eGFR per 1 [jg/dL

patients
Zeeman correction) (pg/dL)
(MDRD) over 4 yr
examined whether a predictor
increase in blood Pb
Taipei, Taiwan; 48-mo
longitudinal study
period
n = 121
Mean (SD)
4.2 (2.2)
(mL/min/1.73 m2)
was associated with renal
function including age, sex,
BMI, hyperlipidemia,
-4.01 (-7.24, -0.78)a

10th—90th percentile
2.0-5.1

hypertension, smoking, use of
ACE inhibitor, baseline serum

Cohort



creatinine, daily protein
excretion daily protein intake,
underlying kidney disease

Harari et al. (2018)
Malmo,
Sweden
Baseline: 1991-1994,
Follow-up: 2007-2012
Cohort
Cardiovascular
cohort of Malmo
Diet and Cancer
Study (MDCS-
CC)
n = 4,341
enrolled in
cohort, 2,567
followed up
Blood Pb (ICP-MS) [jg/dL
Median: 2.5 (Range; 0.15-
25.8)
Max: 25.8
Quartiles
Median (range)
Q1 1.5 (0.15-1.85)
Q2 2.2 (1.85-2.47)
Q3 2.9 (24.7-3.30)
Q4 4.6 (3.3-25.8)
Q1 +Q2 + Q3 2.2 (0.15—
3.30)
Change in eGFR
(CKD-EPI) from
baseline
Age of outcome 73
Linear regression adjusted for
age, sex, smoking, alcohol
intake, hypertension, diabetes,
waist circumference, eGFR at
baseline, education level
Change in eGFRc
(mL/min/1.73m2)
Q1 (Reference)
Q2 -1.70 (-3.10, -0.26)
Q3 -2.90 (-4.30, -1.50)
Q4 -2.30 (-3.80, -0.73)
Age of measurement 57
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Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Liu et al. (2020)
Shiyan City of Hubei
Province
China
Baseline between
September-June
2010, follow-up in
2013
Mean follow-up: 4.6 yr
Cohort
Dongfeng-
Tongji
n = 1,434
Retirees from
Blood Pb (ICP-MS) [jg/dL
Median (IQR)
1.23 (0.84-1.90)b
Quartiles
Q1 < 0.843
Dongfeng Motor Q2 0.843-1.232
Corporation
Q3 1.232-1.895
Q4 > 1.895
Age at Measurement:
Mean (SD) 62.4 (7.5)
Annual eGFR (CKD-
EPI) decline
([Baseline eGFR-
eGFR at follow-up]/
number of follow-up
yr)
Linear regression adjusted for
age, sex, baseline eGFR,
batch (from the 3 case-
controls), occupational
category, BMI, smoking status,
drinking status, education
level, and fasting plasma
glucose
Annual decline in eGFR
(mL/min/1.73 m2) per In-
transformed increase in blood
Pbcd
Q1 Referent
Q2 0.30 (-0.20, 0.81)
Q3 0.30 (-0.20, 0.81)
Q4 0.83 (0.31, 1.35)
Chung et al. (2020) n = 770
Taiwan
Recruited 2010-2011
and follow-up in 2015-
2016
Cohort
Community
residents living
near an EAF
Blood Pb (ICP-MS) (pg/dL)
Geometric mean (IQR)
Distance from EAF
< 500 m 2.41 (1.22-6.19)
500-1000 m 2.26 (1.16-
4.83)
1000-1500 m 2.12 (1.05-
4.67)
1500-2000 m 2.23 (0.98-
4.31)
>2000 m: 2.03 (1.03-4.31)
eGFR (method not
specified)
General linear models
adjusting for age, sex,
ethnicity, living near the main
road and smoking
Per 1 pg increase in blood Pb:
(mL/min/1.73 m2)
eGFR: -2.25 (-3.50, -1.01)
Age at measurement
Median 60
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Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Pollack et al. (2015)
Buffalo, NY
United States
women followed
2 menstrual cycles (8 f°r 2 menstrual
visits per cycle) 2005- cyc'es
2007
Cohort
BioCycle	Blood Pb (ICP-MS) (pg/dL) eGFR (MDRD)
n = 259	Median (IQR) 0.86 (0.68—
1.2)
Premenopausal Mean (SD) 1 03 (0.63)
Age at Measurement:
Mean (SD) 27.4 (8.2)
Linear mixed models adjusted
forage, BMI, race, average
calories, alcohol intake,
smoking, and cycle day
Percent Change in Kidney
Biomarkers per 2-fold increase
in blood Pbd
eGFR: -3.73 (-6.55, -0.83)
OR
eGFR (<90 mL/min/1.73 m2)
0.32 (0.08, 1.21)
eGFR (<60 mL/min/1.73 m2)
0.32 (0.08, 1.21)
Results presented as percent
change in nontransformed
outcome per 2-fold increase in
nontransformed exposure
Navas-Acien et al.
(2009)
United States
1999-2006
Cross-sectional
NHANES
adults
n = 14,778
Aged >20 yr
Blood Pb (ICP-MS) (pg/dL) Reduced eGFR
Logistic regression adjusted for OR
Geometric mean 1.58
Quartiles
Range (Median)
Q1
Q2
Q3
Q4
<1.1 (0.8)
1.2 to 1.6 (1.3)
1.7 to 2.4 (1.9)
>2.4 (3.2)
(MDRD) (eGFR
< 60 mL/min/1.73 m2
survey year, age, sex,
race/ethnicity, BMI, education,
smoking, cotinine, alcohol
intake, hypertension, diabetes,
menopausal status
Q1 Referent
Q2 1.21 (0.64, 2.28)
Q3 1.32 (1.00, 1.76)
Q4 1.20 (1.07, 1.36)
Age of measurement
Mean (SD)
Reduced eGFR 67.6 (0.5)
No reduced eGFR 44.7 (0.3)
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Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Muiai etal. (2019)
United States
May 2015 to
September 2017
Cross-sectional
SPHERL
n = 447 men
Newly hired Pb
workers at
battery
manufacturing
and Pb
recycling plants
Blood Pb (ICP-MS) (|jg/dL)
Geometric mean (IQR)
1.66 (1.3-2.5)
Age at Measurement:
Mean (SD) 28.7 (10.2)
eGFR (CKD-EPI),
ACR
Linear regression adjusted for
age, MAP, BMI, smoking,
waist-to-hip ratio, total
cholesterol to HDL ratio,
plasma glucose, y-glutamyl
transferase, and
antihypertensive drug
treatment
Per doubling of blood Pb
(mL/min/1.73 m2)d
eGFRcrt (serum creatinine)
-0.135 (-3.40, 3.13)
eGFRcys (serum cystatin)
-0.222 (-3.07, 2.62)
eGFRcc (serum creatinine and
cystatin): -0.281 (-3.07, 2.50)
Per doubling of blood Pb
(mg/mmol)
ACR: -0.071 (-0.14, 0.59)
Kim and Lee (2012)
South Korea
2008-2010
Cross-sectional
KNHANES
n = 5,924
Participants >20
yr of age
Blood Pb (GFAAS with
Zeeman correction) (pg/dL)
Geometric mean (95% CI)
2.289 (95% CI: 2.258,
2.319)
Quartiles
Q1 <1.743
Q2 > 1.734-2.305
Q3 >2.305-3.010
Q4 > 3.010
eGFR (MDRD)
(Considered reduced
if < 80 mL/min per
1.73 m2)
Linear and logistic regression
adjusted for age, sex,
residence area, education
level, smoking status, drinking
status, hypertension, diabetes,
hemoglobin, blood cadmium,
and blood mercury
Continuous eGFRd
(mL/min/1.73 m2)
Doubling of Pb
-2.624 (-3.803
1.445)
Q1 Reference
Q2 -0.491 (-2.048, 1.0651)
Q3 -2.341 (-4.013, -0.669)
Q4 -3.835 (-5.730, -1.939)
Reduced eGFR (OR (95% Cl))d
Doubling of Pb
1.324 (1.139, 1.540)
Q1 Reference
Q2 1.031 (0.806, 1.319)
Q3 1.161 (0.892, 1.511)
Q4 1.631 (1.246, 2.136)
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Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Chung et al. (2014)
South Korea
2008
Cross-sectional
KNHANES
n =2,005
>20 yr with data
for blood Pb and
cadmium.
Pregnant
women were
excluded
Blood Pb (GFAAS with
Zeeman correction) (pg/dL)
Geometric mean: 2.5
Quartiles (Mean)
Q1 1.38
Q2 2.10
Q3 2.74
Q4 4.13
Age at Measurement:
Mean(Range)46(20-87)
eGFR (CKD-EPI)
Linear regression adjusted for
age, sex, smoking,
hypertension, or diabetes.
Logistic regression adjusted for
age, sex, smoking
hypertension, BMI, and blood
cadmium
Per 1 [jg/dL increase in blood
Pb (mL/min/1.73 m2)
-2.61 (95% CI: -3.29, -1.97)
OR (95% CI) (Q4 vs. Q1, per
1 [jg/dL increase in blood Pb
eGFR (<60 mL/min/1.73 m2)
1.08 (95% CI: 0.99, 1.17)
Buser et al. (2016)
United States
2007-2012
Cross-sectional
NHANES
n =4,875
Pregnant and
breastfeeding
women were
excluded
Blood Pb (ICP-MS) (pg/dL)
Quartiles
Q1 <0.79
Q2 0.80-1.20
Q3 1.21-1.82
Q4 > 1.82 pg/dL
Age at Measurement
Geometric Mean 44.1
eGFR (CKD-EPI)
Linear regression adjusting for
age, race/ethnicity, sex,
diabetes, alcohol intake,
education, smoking status,
body weight, hypertension,
weak/failing kidney, serum
cotinine, and blood cadmium
eGFR (mL/min/1.73 m2)d
Q1 Reference
Q2 -1.17 (-2.91, 0.57)
Q3 -1.62 (-3.60, 0.36)
Q4 -2.67 (-4.78, -0.56)
Jain (2019) NHANES	Blood Pb (ICP-MS) (pg/dL) Reduced eGFR Logistic regression adjusting OR (95% Cl)cd
n = 25,427	(CKD-EPI) for sex, race/ethnicity, smoking
United States	75th percentile: 2.15 (<60 mL/min/1.73 m2) status, age, BMI, survey year, eGFR (<60 mL/min/1.73 m2):
>20 yr of age	fasting time, poverty income 1.567 (1.346, 1.823)
9nm-9ni4	„ x ™ ratio, diabetes, and
Age at measurement >20 yr	hypertension
Cross-sectional
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Refe,enD?SfgnnS'Udy Population Exposure Assessme„,
Outcome
Confounders
Effect Estimates and 95% Cis*
Per SD of the log-transformed
blood Pb concentration11
OR eGFR (<60 mL/min/1.73 m2)
Discovery set: 1.35 (1.24, 1.48)
Validation set 1.27 (1.11, 1.45)
OR eGFR (<45 mL/min/1.73 m2)
Discovery set: 1.60 (1.39, 1.85)
Validation set 1.63 (1.42, 1.88)
OR eGFR (<30 mL/min/1.73 m2)
Discovery set: 1.98 (1.50, 2.62)
Validation set 2.25 (1.75, 2.90)
ACE = angiotensin-converting enzyme ACR = albumin-to-creatinine ratio; BMI = body mass index; CI = confidence interval; CKD = chronic kidney disease; CKD-EPI = Method of
eGFR calculation from the Chronic Kidney Disease Epidemiology Collaboration; EAF = electric arc furnace; eGFR = estimated glomerular filtration rate; ETAAS = Electrothermal
Atomic Absorption Spectrometry; GFAAS = Graphite Furnace Atomic Absorption Spectrometry; HDL = high-density lipoprotein; ICP-MS = Inductively Coupled Plasma Mass
Spectrometry; IQR = interquartile range; KNHANES = National Health and Nutrition Examination Survey; MAP = mean arterial pressure; MDCS-CC = cardiovascular cohort of the
Malmo Diet and Cancer Study; MDRD = Method of eGFR calculation from the Modification of Diet in Kidney Disease study; mo = months; NHANES = National Health and Nutrition
Examination Survey; OR = odds ratio; Q = quartile; SD = standard deviation; SES = socioeconomic status; SPHERL = Study for Promotion of Health in Recycling Lead; Pb = lead;
yr = years.
'Effect estimates are standardized to a 1 |jg/dL increase in blood Pb or a 10 |jg/g increase in bone Pb, unless otherwise noted. If the Pb biomarker is log-transformed, effect
estimates are standardized to the specified unit increase for the 10th-90th percentile interval of the biomarker level. Effect estimates are assumed to be linear within the evaluated
interval. Categorical effect estimates are not standardized.
Confidence interval estimated from reported p-value.
bUnits converted from |jg/L.
increment unclear.
dUnable to be standardized.
Lee et al. (2020)
United States
1999-2016
Cross-sectional
NHANES
n = 46,748
Adults >18 yr of
age
Blood Pb (ICP-MS)
Distribution not reported
Age at Measurement:
Mean (SD) 47 (19)
Reduced eGFR
(CKD-EPI) (<60, <45,
or
<30 mL/min/1.73 m2)
Logistic regression adjusted for
age, sex, diabetes,
hypertension, BMI,
race/ethnicity, smoking, and
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Table 5-5
Animal toxicological studies of Pb exposure and glomerular filtration rate.
Study
Species
(Stock/Strain),
n, Sex
Timing of Exposure
Exposure
Details
(Concentration,
Duration)
BLL as Reported (iig/dL
Endpoints Examined
Shi et al. (2020)
Rat (SD)
Control
(deionized
water), M, n = 8
0.5% Pb
acetate, M, n = 8
28 d after PND 21
After21dof	0.18 ± 0.07 [jg/dL for Control GFR postexposure
milk feeding,	(deionized water)
0.5% Pb acetate
or deionized	1021 ± o.93 pg/dL for 0.5% Pb
water for 28 d	acetate
d = days; GFR = glomerular filtration rate; M = male; Pb = lead; PND = postnatal day; SD = standard deviation.
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Table 5-6
Epidemiologic studies of Pb exposure and albumin, creatinine, and albumin-to-creatinine ratio.
Reference and Study	Study
Design	Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Tsaih et al. (2004)
Boston, MA
1991-1995, ~4 yr of
follow-up
Cohort
NAS
n = 448
Adult males,
mostly white
Blood Pb (Blood (GFAAS
with Zeeman correction)
(Hg/dL)
Mean (SD) 6.5 (4.2)
10th—90th 2.1-7.6
Bone Pb (K-XRF) (pg/g)
Mean (SD)
Tibia 21.5 (13.5)
Patella 32.4 (20.5)
Age at measurement
Mean (SD) 66.0 (6.6)
Change in
serum creatinine
(mg/dL) peryr
Age at outcome
Mean (SD) 72.0
(6.5)
Log linear regression
adjusted for age, BMI,
hypertension, diabetes,
smoking status, alcohol
consumption, analgesic use,
baseline serum creatinine
Annual change in serum creatinine
(mg/dL/yr)
Blood Pb
Overall 0.002 (-0.001, 0.004)
Diabetic 0.013 (0.005, 0.02)
Nondiabetic 0.001 (0, 0.002)
Hypertensive 0.001 (-0.002, 0.005)
Normotensive 0.002 (0, 0.003)
Tibia Pb
Overall, 0.035 (-0.014, 0.084)
Diabetic 0.412 (0.146, 0.678)
Nondiabetic 0.025 (-0.024, 0.074)
Hypertensive 0.116 (0.017, 0.214)
Normotensive 0.002 (-0.057, 0.061)
Kim et al. (1996)
Boston, MA
1979-1994
Retrospective cohort
NAS
n = 459
Adult males,
mostly white
Blood Pb (Blood (GFAAS
with Zeeman correction)
(MQ/dL)
Median 8.6
10th—90th percentile: 4.0-
17.5
Change in	Random-effects modeling
Serum	adjusted for baseline age,
creatinine	time since initial visit, BMI,
(mg/dL)	smoking status, alcohol
ingestion, education level,
and hypertension
Change in serum creatinine (mg/dL)
Peak blood Pb < 40 pg/dL
0.0017 (0.0005, 0.003)
Peak blood Pb < 25 pg/dL
0.0021 (0.0007, 0.0035)
Peak blood Pb < 10 pg/dL
0.0033 (0.0012, 0.0053)
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Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Akesson et al. (2005)
Sweden
1999-2000
WHILA, adult Median (5-95% CI)	Creatinine
women	concurrent blood Pb: 2.2	clearance/100
n = 820	(1.1,4.6) [jg/dL	(mL/min)
10th—90th percentile: 1.3-3.8
Linear regression adjusted
for age, BMI, diabetes,
hypertension, regular use of
nephrotoxic drug, smoking
status
Creatinine clearance/100 (mL/min)
for each unit increase in blood Pb
-0.018 (-0.03, -0.006)
Cross-sectional
Pollack et al. (2015)
Buffalo, NY
United States
2 menstrual cycles (8
visits per cycle) 2005-
2007
Cohort
BioCycle
n = 259
Premenopausal
women followed
for 2 menstrual
cycles
Blood Pb (ICP-MS) (pg/dL)
Median (IQR) 0.86 (0.68-1.2)
Mean (SD) 1.03 (0.63)
Age at Measurement:
Mean (SD) 27.4 (8.2)
Creatinine and
ALB
(BUN, CO2,
Chloride,
Potassium,
Urate, Calcium,
Protein,
Glucose)
Linear mixed models
adjusted forage, BMI, race,
average calories, alcohol
intake, smoking, and cycle d
Percent Change in kidney
Biomarkers per 2-fold increase in
blood Pba
Creatinine: 3.47 (0.85, 6.16)
ALB -0.38 (-1.28, 0.52)
BUN: -0.13 (-4.97, 4.96)
C02: -0.57 (-1.43, 0.29)
Chloride: 0.20 (-0.09, 0.48)
Potassium: 0.01 (-1.15, 1.18)
Urate: 0.90 (-2.22, 4.12)
Calcium: -0.21 (-0.67, 0.25)
Protein: -0.76 (-1.61, 0.09)
Glucose: 0.93 (-0.28, 2.15)
*Results presented as percent
change in nontransformed outcome
per 2-fold increase in
nontransformed exposure
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Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Buser et al. (2016)
United States
2007-2012
Cross-sectional
NHANES
n = 4,875
Pregnant and
breastfeeding
women were
excluded
Blood Pb (ICP-MS) (pg/dL)
Quartiles
Q1 <0.79
Q2 0.80-1.20
Q3 1.21-1.82
Q4 > 1.82 [jg/dL
Age at Measurement:
Geometric Mean 44.1
Urinary ALB Linear regression adjusting
for age, race/ethnicity, sex,
diabetes, alcohol intake,
education, smoking status,
body weight, hypertension,
weak/failing kidney, serum
cotinine, and blood cadmium
ALB (percent difference)3
Q1 Reference
Q2 -4.02 (-13.76, 6.93)
Q3 -9.24 (-19.43, 2.22)
Q4 6.29 (-6.39, 20.80)
Muiai et al. (2019)
SPHERL
Blood Pb (ICP-MS) (pg/dL) ACR
Linear regression adjusted
Per doubling of blood Pb

n = 447 men
Geometric mean (IQR)
forage, MAP, BMI, smoking,
(mg/mmol)a
United States

1.66 (1.3-2.5)
waist-to-hip ratio, total
ACR:

Newly hired Pb
cholesterol to HDL ratio,
-0.071 (-0.14, 0.59)
May 2015 to
September 2017
workers at

plasma glucose, y-glutamyl
battery
Age at Measurement:
transferase, and

manufacturing
Mean (SD) 28.7 (10.2)
antihypertensive drug

Cross-sectional
and Pb recycling
plants

treatment

Jain (2019)
United States
2003-2014
Cross-sectional
NHANES
n = 25,427
>20 yr
Blood Pb (ICP-MS) (pg/dL) ACR
75th percentile 2.15
Age at measurement >20 yr
Logistic regression adjusting OR (95% Cl)ab
for sex, race/ethnicity,
smoking status, age, BMI,
survey year, fasting time,
poverty income ratio,
diabetes, and hypertension
ACR (>30 mg/g creatinine)
1.206 (1.05, 1.385)
Zhu et al. (2019)
United States
2009-2012
Cross-sectional
NHANES
n = 2926
>20 yr
Blood Pb (ICP-MS) (pg/dL) ACR
Quartiles
Q1 <0.0685
Q2 0.0686-0.1029
Q3 0.1030-0.1600
Q4 >0.1601
Age at Measurement:
Mean (SE)42.1 (0.46)
Linear regression adjusted
forage, sex, BMI, obesity,
ethnicity, education,
smoking, hypertension,
diabetes, and CKD
Blood Pb and continuous ACR (In-
transformed) (mg/g)a
Q1 Reference
Q2 0.04 (-0.06, 0.13)
Q3 -0.05 (-0.18, 0.08)
Q4 0.06 (-0.08, 0.20)
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Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Lee et al. (2020)
United States
1999-2016
Cross-sectional
NHANES	Blood Pb (ICP-MS)
n = 46,748	Distribution not reported
Adults >18	Age at Measurement:
Mean (SD) 47 (19)
ACR (>30 and Logistic regression adjusted Per SD of the log-transformed blood
>300 mg/g) for age, sex, diabetes,
hypertension, BMI,
race/ethnicity, smoking, and
Pb concentration3
OR ACR (>30 mg/g)
Discovery set: 1.23(1.07, 1.42)
Validation set 1.08 (0.97, 1.20)
OR ACR (>300 mg/g)
Discovery set: 1.39 (1.22, 1.59)
Validation set 1.38 (1.16, 1.63)
ACR = albumin-to-creatinine ratio; ALB = albumin; BMI = body mass index; BUN = blood urea nitrogen; CI = confidence interval; CKD = chronic kidney disease; GFAAS = Graphite
Furnace Atomic Absorption Spectrometry; ICP-MS = Inductively Coupled Plasma Mass Spectrometry; IQR = interquartile ratio; K-XRF = K-shell X-Ray Fluorescence; MAP = mean
arterial pressure; NHANES = National Health and Nutrition Examination Survey; OR = odds ratio; Pb = lead; Q = quartile; SD = standard deviation; SES = socioeconomic status;
SPHERL = Study for Promotion of Health in Recycling Lead; yr = years.
'Effect estimates are standardized to a 1 |jg/dL increase in blood Pb or a 10 |jg/g increase in bone Pb, unless otherwise noted. If the Pb biomarker is log-transformed, effect
estimates are standardized to the specified unit increase for the 10th—90th percentile interval of the biomarker level. Effect estimates are assumed to be linear within the evaluated
interval. Categorical effect estimates are not standardized.
aUnable to be standardized.
increment unclear.
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Table 5-7
Animal toxicological studies of Pb exposure and albumin and creatinine.
Study
Species (Stock/Strain), Timing of
n, Sex	Exposure
Exposure Details
(Concentration,
Duration)
BLL as Reported (ng/dl_)
Endpoints Examined
Zou etal. (2015)
Mouse (Control)
(re-distilled water), M,
n = 10
250 mg/L Pb acetate, M,
n = 10
3-wk exposure	250 mg/L Pb acetate 1.8 (jg/dL for Control (re-distilled water)
of	or distilled water for
approximately	3 wk
30-d-old	21.7 |jg/dL for 250 mg/L-PND 58
mice
Markers of Kidney Function:
Creatinine post 3-wk
exposure
Corsetti et al. (2017) Mouse (Control)
(Pb-free water), M, n = 8
200 ppm Pb, M, n = 8
d 30 to d 75 Mice were exposed to <5 |jg/dL for 0 ppm
ordinary or Pb
containing drinking	„ , „ , 		
water for 45 d	21.6 pg/dL for 200 ppm
Markers of Kidney Function:
serum creatinine post 45-d
exposure
Andielkovic et al.
(2019)
Rat (Wistar)
Control water, M, n = 8
150 mg/kg b.w., M, n = 6
Single	Single oral dose of
exposure by 150 mg/kg b.w. Pb
oral gavage acetate
(age of rats not
reported)
-25 |jg/L for Control (-2.5 pg/dL)
-225 pg/L for 150 mg/kg b.w. Pb
acetate
(-22.5 pg/dL)
Markers of Kidney Function:
serum levels of creatinine 24
hr post single exposure
Zinc and copper levels in the
kidney 24 hr post single
exposure
Shi et al. (2020)
Rat (SD)
Control (deionized water),
M, n = 8
0.5% Pb acetate, M,
n = 8
28 d after PND After 21 d of milk
21	feeding, 0.5% Pb
acetate or deionized
water for 28 d
0.18 ± 0.07 pg/dL for Control (deionized GFR and Markers of Kidney
water)	Function: Creatinine post
exposure
10.21 ± 0.93 pg/dL for 0.5% Pb acetate
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Study
Species (Stock/Strain), Timing of
n, Sex	Exposure
Exposure Details
(Concentration,
Duration)
BLL as Reported (ng/dl_)
Endpoints Examined
Laamech et al.
(2016)
Mouse
Control
(distilled water), M/F,
n = 10
5 mg/kg/d Pb acetate,
M/F, n = 10
Age of mice in
experiment not
reported
Distilled water or
5 mg/kg/d Pb acetate
dissolved in distilled
water for 40 d
0.009 |jg/ml_ for control (distilled water)
(0.9 pg/dL)
0.18 pg/mL for 5 mg/kg/d Pb acetate
(18 pg/dL)
Markers of Kidney Function:
plasma levels of creatinine
2 d post exposure
Gao et al. (2020)
Rat (SD)
Control
(Distilled water), M/F,
n = 10
5 mg/kg Pb acetate, M/F,
n = 10
Age of mice in
experiment not
reported
5 mg/kg Pb acetate
orally for 35 d
followed by recovery
to d 63
<0.02 mg/kg for distilled water
(<2.12 pg/dL)
0.10 ± 0.03 mg/kg for5mg/kg Pb
acetate (d 64) (10.6 ± 0.03 pg/dL)
Markers of Kidney Function:
creatinine activity following
the end of the experiment on
d 63
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Study
Species (Stock/Strain), Timing of
n, Sex	Exposure
Exposure Details
(Concentration,
Duration)
BLL as Reported (ng/dl_)
Endpoints Examined
Dumkova et al.
(2020b)
Mouse (Control)
(clean air), F, n = 10
(2 wk, 6 wk, 11 wk)
PbO, F, n = 10 (2 wk,
6 wk, 11 wk)
PbO recovery, F, n = 10
(6 wk PbO, 5 wk clean
air)
Age of mice in
experiment
unclear
PbO 78.0 |jg PbO/m3
or clean air for 24 hr/d
7 d/wk for 2 wk, 6 wk,
or 11 wk. a recovery
group was exposed to
PbO for 6 wk and
then clean air for 5 wk
(11 wk total)
<3 ng/g in control (2 wk, 6 wk, 11 wk)
(0.3 pg/dL)
104 ng/g PbO 2 wk (10.4 pg/dL)
148 ng/g PbO 6 wk (14.8 pg/dL)
174 ng/g PbO 11 wk (17.4 pg/dL)
Markers of Kidney Function:
Creatinine at 2 wk, 6 wk, and
11 wk
d = days; GFR = glomerular filtration rate; hr = hours; F = female; M = male; M/F = male/female; Pb = lead; PbO = Pb oxide; PND = postnatal day; SD = standard deviation;
wk = weeks.
Table 5-8 Epidemiologic studies of Pb exposure and uric acid.
Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis
Park and Kim (2021)
South Korea
2016-2017
Cross-sectional
KNHANES
n =4,784
Participants
>20
Blood Pb (GFAAS) (pg/dL)
Geometric mean:
Overall, 1.69
Men 1.95
Women 1.50
Age at measurement >20
SUA and	Linear and logistic regression
hyperuricemia	adjusting for age, residence
(SUA	area, education level, smoking
>7.0 mg/dL in	status, drinking status, physical
men and	activity, hypertension, glucose,
>6.0 mg/dL in	triglyceride, cholesterol, eGFR,
women)	blood cadmium and blood
mercury
Per doubling of Blood Pb
Log SUA (mg/dL)
Men: -0.018 (-0.038, 0.002)
Women: 0.019 (0.001, 0.037)
Hyperuricemia (OR) per doubling
of blood Pba
Men: 0.928 (0.718, 1.198)
Women: 1.095 (0.727, 1.649)
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Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis
Arrebola et al. (2019)
BIOAMBIENT.E
Blood Pb (method not
UA and
logistic or linear regression
Per 1 unit increase in log-

S study
indicated) (pg/dL)
hyperuricemia
adjusting for sex, age, weight
transformed Pb
Spain
n = 882

(UA> 7.0 mg/dL
loss in past 6 mo, smoking

2009-2010
Cross-sectional
458 males and
424 females
Median 0.106
75th 0.181
in males or
>6.0 mg/dL in
status, alcohol consumption,
education, region of
Log SUA (mg/dL)


90th 0.284
females,
recruitment, place of residence
5.95 (-0.02, 0.05)


95th 0.355
prescribed any
medication for

Hyperuricemia (OR)


Age at measurement
lowering UA
levels, diagnosis

1.12 (0.90, 1.41)


Median 35.4-38.1
of gout by a
physician)


Jung etal. (2019)
South Korea
2016
KNHANES
n = 2,682
1124 men and
1528 women)
aged >19 yr
Blood Pb (GFAAS) (|jg/dL) Hyperuricemia Logistic regression adjusting for See Figure 5-5
Hyperuricemia
Median (IQR) 2.04 (1.59-2.51)
No Hyperuricemia
Median (IQR) 1.73 (1.34-2.28)
Age at measurement
Hyperuricemia
Mean (SE) 46.4 (1.3)
No hyperuricemia
Mean (SD) 46.9 (0.5)
(SUA
>7.0 mg/dL in
men and
>6.0 mg/dL in
women)
age, BMI, eGFR, residence,
education, smoking status,
alcohol consumption, physical
activity, and blood pressure
BMI = body mass index; CI = confidence interval; eGFR = estimated glomerular filtration rate; IQR = interquartile ratio; GFAAS = Graphite Furnace Atomic Absorption Spectrometry;
KNHANES = Korea National Health and Nutrition Examination Survey; mo = months; OR = odds ratio; SD = standard deviation; SE = standard error; SUA = serum uric acid;
UA = uric acid; yr = years.
aUnable to be standardized.
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Table 5-9
Animal toxicological studies of Pb exposure and measures of uric acid and urea.
Study
Species
(Stock/Strain),
n, Sex
Timing of Exposure
Exposure
Details
(Concentration,
Duration)
BLL as Reported (ng/dl_)
Endpoints Examined
Zou etal. (2015)
Mouse (Control) 3-wk exposure of
(re-distilled	approximately 30-d-old
water), M, n = 10 mice
250 mg/L Pb
acetate, M,
n = 10
250 mg/L Pb
acetate or
distilled water
for 3 wk
1.8 |jg/dL for Control (re-
distilled water)
21.7 [jg/dL for 250 mg/L-PND
58
Markers of Kidney Function: BUN
post 3-wk exposure
Andielkovic et al.
(2019)
Rat (Wistar)
Control water,
n = 8
M,
150 mg/kg b.w.,
M, n = 6
Single exposure by oral
gavage (age of rats not
reported)
Single oral dose
of 150 mg/kg
b.w. Pb acetate
-25 |jg/L for Control
(-2.5 pg/dL)
-225 pg/L for 150 mg/kg b.w.
Pb acetate
(-22.5 pg/dL)
Markers of Kidney Function:
serum levels of BUN 24 hr post
single exposure
Zinc and copper levels in the
kidney 24 hr post single
exposure
Shi et al. (2020)
Rat (SD)
Control
(deionized
water), M, n =
0.5% Pb
acetate, M, n :
28 d after PND 21
After 21 d of
milk feeding,
0.5% Pb acetate
or deionized
water for 28 d
0.18 ± 0.07 pg/dL for Control
(deionized water)
10.21 ± 0.93 pg/dL for 0.5% Pb
acetate
Markers of Kidney Function: BUN
and UA post exposure
Carlson et al. (2018) Mouse (Control) Treatment began no earlier Pb free water or Control (water) not detected
(water), M/F,
n = 16
0.03 mM Pb,
M/F, n = 8
than an age
of 5 wk for 11 wk
0.03 mM Pb
acetate
dissolved in
drinking water
for 11 wk
2.89 ± 0.44 pg/dL for 0.03 mM
Markers of Kidney Function: BUN
1 wk after 11-wk exposure
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Study
Species
(Stock/Strain),
n, Sex
Timing of Exposure
Exposure
Details
(Concentration,
Duration)
BLL as Reported (ng/dl_)
Endpoints Examined
Laamech et al. (2016) Mouse
Control
(distilled water),
M/F, n = 10
5 mg/kg/d Pb
acetate, M/F,
n = 10
Age of mice in experiment
not reported
Distilled water or
5 mg/kg/d Pb
acetate
dissolved in
distilled water
for 40 d
0.009 |jg/ml_ for control (distilled
water) (0.9 pg/dL)
0.18 |jg/ml_ for 5 mg/kg/d Pb
acetate (18 pg/dL)
Markers of Kidney Function:
plasma levels of urea and UA 2 d
post exposure
Gao et al. (2020)
Rat (SD)
Control
(Distilled water),
M/F,
n = 10
5 mg/kg Pb
acetate, M/F,
n = 10
Age of mice in experiment
not reported
5 mg/kg Pb
acetate orally for
35 d followed by
recovery to d 63
<0.02 mg/kg for distilled water
(<2.12 [jg/dL)
0.10 ± 0.03 mg/kg for 5 mg/kg
Pb acetate (d 64)
(10.6 ± 0.03 [jg/dL)
Markers of Kidney Function: BUN
activity following the end of the
experiment on d 63
Dumkova et al. (2020b)
Mouse (Control)
(clean air), F,
n = 10 (2 wk,
6 wk, 11 wk)
PbO, F, n = 10
(2 wk, 6 wk,
11 wk)
PbO recovery,
F, n = 10 (6 wk
PbO, 5 wk clean
air)
Age of mice in experiment
unclear
PbO 78.0 |jg
PbO/m3 or clean
air for 24 hr/d
7 d/wk for 2 wk,
6 wk, or 11 wk.
a recovery
group was
exposed to PbO
for 6 wk and
then clean air for
5 wk (11 wk
total)
<3 ng/g in control (2 wk, 6 wk,
11 wk) (0.3 [jg/dL)
104 ng/g PbO 2 wk
(10.4 [jg/dL)
148 ng/g PbO 6 wk
(14.8 [jg/dL)
174 ng/g PbO 11wk
(17.4 pg/dL)
Markers of Kidney Function:
Urea at 2, 6, and 11 wk
BUN = blood urea nitrogen; d = days; F = female; hr = hours; M = male; M/F = male/female; Pb = lead; PbO = Pb oxide; SD = standard deviation; wk = weeks.
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Table 5-10 Epidemiologic studies of Pb exposure and proteinuria and hematuria.
Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Chung et al. (2014)
South Korea
2008
Cross-sectional
KNHANES
n = 2,005
>20 yr with data
for blood Pb and
cadmium.
Pregnant women
were excluded
Blood (GFAAS with Zeeman
correction) (pg/dL)
Geometric mean: 2.5
Quartiles (Mean)
Q1 1.38
Q2 2.10
Q3 2.74
Q4 4.13
Proteinuria Linear regression adjusted for
age, sex, smoking,
hypertension, or diabetes.
Logistic regression adjusted for
age, sex, smoking
hypertension, BMI, and blood
cadmium
OR (95% CI) (Q4 vs. Q1, per
1 [jg/dL increase in blood Pb)
1.08 (1.00, 1.16)
Age at Measurement:
Mean(Range)46 (20-87)
Han et al. (2013)
South Korea
2008-2010
Cross-sectional
KNHANES
n = 4,701
Blood (GFAAS with Zeeman
correction) (pg/dL)
Geometric mean: 1.08
Quartiles
Q1 < 1.89
Q2 1.89-2.46
Q3 2.47-3.22
Q4 > 3.22
Age at Measurement:
Mean 50 yr
Hematuria	Logistic regression adjusting for
age, sex, residential region,
education level, and anemia
OR (95% Clf
Q1 Reference
Q2 1.00 (0.767,
Q3 0.90 (0.687,
Q4 0.94 (0.701,
1.303)
1.178)
1.253)
BMI = body mass index; BUN = blood urea nitrogen; CI = confidence interval; GFAAS = Graphite Furnace Atomic Absorption Spectrometry; KNHANES = Korea National Health and
Nutrition Examination Survey; OR = odds ratio; Q = quartile; yr = years.
'Effect estimates are standardized to a 1 |jg/dL increase in blood Pb or a 10 |jg/g increase in bone Pb, unless otherwise noted. If the Pb biomarker is log-transformed, effect
estimates are standardized to the specified unit increase for the 10th—90th percentile interval of the biomarker level. Effect estimates are assumed to be linear within the evaluated
interval. Categorical effect estimates are not standardized.
aUnable to be standardized.
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Table 5-11 Epidemiologic studies of Pb exposure and renal tubular impairment markers.3
Reference and Study
Design
Study Population Exposure Assessment Outcome
Confounders
Effect Estimates and 95% Cis
~ metal. (2016)
South Korea
2010-2012
Cross-sectional
KRIEFS
n = 1953
participants > 19
without kidney
disease
Blood Pb (GFAAS)
(Hg/dL)
Geometric mean 2.21
Age at Measurement
Mean 45.5
Renal tubular Linear regression adjusting for
impairment age, sex, BMI, household
(NAG and (32- income, smoking, alcohol
MG)	consumption, hypertension, and
diabetes
Log-transformed Pb
NAG (Unit/g creatinine)
0.09 (-0.05, 0.23)
p2-MG (|jg/g creatinine)
0.01 (-0.13, 0.15)
Jung etal. (2016)
Jangseong-gun
South Korea
June-August 2013 and
August-November
2014
Cross-sectional
n = 547
Participants living
near cement plant
Blood Pb (AAS
[flameless method])
(Hg/dL)
Quartiles
Q1 0.77-2.13
Q2 2.13-2.70
Q3 2.70-3.50
Q4 3.50-10.37
Renal tubular Logistic regression adjusting for Renal tubular impairment
impairment
(NAG > 5.67 U/L
sex, age, occupation, smoking,
air pollution exposure,
hypertension, diabetes, urine
cadmium, urine mercury
OR (95% CI)
Q1 Reference
Q2 0.96 (0.49,
Q3 0.89 (0.44,
Q4 0.67 (0.32,
1.87)
1.77)
1.41)
Age at Measurement:
Mean (SD) 64.32 (11.02)
AAS = Atomic Absorption Spectrometry, (B2-MG = (B2-microglobulin; BMI = body mass index; CI = confidence interval; GFAAS = Graphite Furnace Atomic Absorption Spectrometry;
KRIEFS = Korean Research Project on the Integrated Exposure Assessment to Hazardous Materials for Food Safety; NAG = acetyl-(B-D-glucosaminidase; OR = odds ratio;
Q = quartile; SD = standard deviation.
aUnable to be standardized.
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Table 5-12 Animal toxicological studies of Pb exposure and other markers of kidney function.
Study
Species
(Stock/Strain),
n, Sex
Timing of Exposure
Exposure
Details
(Concentration,
Duration)
BLL as Reported (ng/dL>
Endpoints Examined
Andielkovic et al.
Rat (Wistar)
Single exposure by oral
Single oral dose
-25 |jg/L for Control
Total protein, zinc, and copper
(2019)
Control water,
gavage (age of rats not
of 150 mg/kg
(-2.5 pg/dL)
levels in the kidney 24 hr post

M, n = 8
reported)
b.w. Pb acetate
single exposure




-225 pg/L for 150 mg/kg b.w.


150 mg/kg b.w.,


Pb acetate


M, n = 6


(-22.5 pg/dL)

Fioresi et al. (2014)
Rat (Wistar)
Control (tap
water), M,
n = 9-12
Age 2 mo to 3 mo
100 ppm Pb
acetate in
drinking water
for 30 d
<0.5 pg/dL for control
13.6 ± 1.07 pg/dL for
100 ppm group
ACE activity measured post 30-d
exposure
100 ppm group,
M,
n = 9-12
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Exposure
Species	Details
Study	(Stock/Strain), Timing of Exposure ,_ . ..	BLL as Reported (ng/dU	Endpoints Examined
n sex	(Concentration,
'	Duration)
Dumkova et al. (2020a) Mouse
6-8 wk old mice exposed for Pb (N03)2
(Control)
(clean air), F,
n = 10 (d 3,
2 wk, 6 wk,
11 wk)
Pb(N03)2
(68.6 ug/mA3),
F, n = 10 (d 3,
2 wk, 6 wk,
11 wk)
Recovery
(Pb(N03)2
68.6 |jg/m3), F,
n = 10 (6 wk
Pb/5 wk
recovery)
3 d, 2 wk, 6 wk, or 11 wk
or
(68.6 |jg/m3
clean air-
exposed mice
for 3 d, 2 wk,
6 wk, or 11 wk.
To assess
recovery a
separate group
of mice were
exposed for
11 wk followed
by 5 wk of clean
air
<0.3 ng/g for control at all
timepoints (<0.3 |jg/dL)
(d 3, 2 wk, 6 wk, 11 wk)
31 ng/g for Pb(N03)2 d 3
(3.1 pg/dL)
40 ng/g for Pb(N03)2 2 wk
(4.0 pg/dL)
47 ng/g for Pb(N03)2 6 wk
(4.7 pg/dL)
85 ng/g for Pb(N03)2 11 wk
(8.5 pg/dL)
10 ng/g for Pb(N03)2 exposure
6 wk and clean air for 5 wk
(1.0 pg/dL)
Total protein, calcium, sodium,
and potassium levels in the
kidney post 3 d, 2 wk, 6 wk,
11 wk, and 11 wk plus clearance
for 5 wk (-16 wk)
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Study
Species
(Stock/Strain),
n, Sex
Timing of Exposure
Exposure
Details
(Concentration,
Duration)
BLL as Reported (ng/dL>
Endpoints Examined
Dumkova et al. (2020b)
Mouse
(Control)
(clean air), F,
n = 10 (2 wk,
6 wk, 11 wk)
PbO, F, n = 10
(2 wk, 6 wk,
11 wk)
PbO recovery,
F, n = 10 (6 wk
PbO, 5 wk
clean air)
Age of mice in experiment
unclear
PbO 78.0 |jg
PbO/m3 or clean
air for 24 hr/d
7 d/wk for 2 wk,
6 wk, or 11 wk.
A recovery
group was
exposed to PbO
for 6 wk and
then clean air for
5 wk (11 wk
total)
<3 ng/g in control (2 wk, 6 wk,
11 wk) (0.3 [jg/dL)
104 ng/g PbO 2 wk
(10.4 [jg/dL)
148 ng/g PbO 6 wk
(14.8 [jg/dL)
174 ng/g PbO 11 wk
(17.4 [jg/dL)
Total protein post 2 wk, 6 wk,
and 11 wk exposure
d = days; hr = hours; F = female; M = male; PbO = Pb oxide; wk = weeks.
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Table 5-13 Epidemiologic studies of Pb exposure and renal outcomes in children.
Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Fadrowski et al. (2010)
NHANES III
Whole blood Pb
eGFR (cystatin C
Linear regression
eGFR (mL/min/1.73 m2), compared with

n = 769
(GFAAS) (pg/g)
and serum
adjusted for age, sex,
referent (Q1 )a
1988-1994
Adolescents

creatinine-based
race/ethnicity, urban vs.

aged 12-20
Median (IQR) 1.5 (0.7,
2.9)
Quartile
estimates)
rural residence, tobacco
smoke exposure,
Cystatin C-based
Cross-sectional


obesity, annual
household income, and
Q2 -1.4 (-7.4, 4.5)
Q3 -2.6 (-7.3, 2.2)


Q1 < 1.0

educational level of the
Q4 -6.6 (-12.6, -0.7)


Q2 1.0-1.5

family reference person


Q3 1.6-2.9


Creatinine-based


Q4 >2.9


Q2 -0.5 (-6.1, 5.1)
Q3 -1.7 (-6.9, 3.5)


Age at measurement


Q4 -1.9 (-7.4, 3.5)


12-15 46%





16-20 54%



Skroderetal. (2016)
Maternal and
Erythrocyte Pb (ICP-MS
Kidney volume,
Linear regression
Per pg/kg Eyr-Pba

Infant Nutrition
followed by dilution in
eGFR, serum
adjusted for gender,

Bangladesh
Interventions,
alkali solution (GW14)
cystatin C
birth weight, season of
GW14

Matlab
or acid digestion

birth, age at outcome
June 2002-June 2004
n = 1,511
(GW30)) (pg/g)
Blood pressure in
measurements, height
Kidney volume (cm3/m2) 0.062 (-0.36, 0.24)

(GW14); 713

children
for age Z-score,
eGFR (mL/min/1.73 m2) 0.089 (-0.012,0.30)
Cohort
(GW30)
GW14
Age at outcome
maternal BMI at GW8,
parity, SES, and
Serum cystatin C (mg/L)

Mother-child
Median (95th) 73 (172)
4.5 yr
supplementation
-0.00088 (-0.0028, 0.001)

pairs
GW30

group
GW30
Kidney Volume (cm3/m2)

Median (95th) 86 (506)






-0.071 (-1.4, -0.030)


Age at Measurement:
Mean (SD) 26 (6) (age






eGFR (mL/min/1.73 m2) 0.71 (-0.24,0.17)


of mothers)


Serum cystatin C (mg/L)
0.000027 (-0.0018, 0.0018)
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Reference and Study
Design
Study
Population
Exposure Assessment
Outcome
Confounders
Effect Estimates and 95% Cis*
Fadrowski et al. (2013)
CkiD
Whole blood Pb (high
GFR
Linear regression
Change (mL/min/1.73 m2) in GFR

n = 391 (485 Pb
resolution ICP-MS)

adjusted for age, sex,
-0.9 (-2.6, 0.8)
United States and
measurements)
(HQ/dL)
GFR directly
race, ethnicity, BMI,
Canada

Median (Range) 1.2
(0.2-6.2)
measured at yr 2
poverty, CKD diagnosis
Percent change in GFR

Children with
and 4 of CkiD
(glomerular or
2007-2009
CKD (1-16 yr of
age)
study
nonglomerular), urine
protein to creatinine
Total sample -2.1 (-6.0, 1.8)
With glomerular CKD -12.1 (-22.2, -1.9)
Cross-sectional

Age at measurement
0-5 13%
6-11 38%
12-19 49%

ratio, and In-
transformed blood
cadmium
With nonglomerular CKD -0.7 (-4.8, 3.4)
Cardenas-Gonzalez et
n = 83
Whole blood Pb
Kidney Injury
Linear regression
No associations between blood Pb and
al. (2016)
Children
(GFAAS) (pg/dL)
Molecule 1 (KIM-
1) and neutrophil
adjusted for age, sex,
BMI, urinary specific
kidney injury biomarkers (data not shown)
San Luis Potosi
attending 2
Geometric mean
gelatinase-
gravity, or urinary

Mexico
elementary
(Range)
associated
creatinine


schools in San
5.95 (1.47-26.89)
lipocalin (NGAL)


2014
Luis Potosi,



Mexico





Age at Measurement



Cross-sectional

Mean (SD) 8.13 (1.93)



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Reference^and Study ^.udy^ Exposure Assessmen, 0uKome
Confounders
Effect Estimates and 95% Cis*
Hu et al. (2019)
NHANES
n = 8,303
Blood Pb (AAS with SUA
Zeeman correction)
(pg/dL)
Mean: 1.3
Linear regression	Per 1 unit increase in In-transformed blood
adjusted age, sex, BMI, Pba
race, education status, SUA (mg/dL) 0.14 (0.10, 0.17)
United States
1999-2006
Adolescents
aged 12-19
hemoglobin, HDL-C;
and eGFR
OR (SUA >5.5 mg/dL) 1.29 (1.17, 1.42)
Cross-sectional
Age at Measurement
Mean (SD) 15.5 (2.3)
AAS = Atomic Absorption Spectrometry; BMI = body mass index; CKD = chronic kidney disease; CKiD = Chronic Kidney Disease in Children; eGFR = estimated glomerular filtration
rate; GFAAS = Graphite Furnace Atomic Absorption Spectrometry; GFR = glomerular filtration rate; GW = gestation week; HDL-C = high-density lipoprotein cholesterol; ICP-
MS = Inductively Coupled Plasma Mass Spectrometry; IQR = interquartile ratio; KIM-1 = kidney injury molecule 1; NGAL = neutrophil gelatinase-associated lipocalin;
NHANES = National Health and Nutrition Examination Survey; OR = odds ratio; Pb = lead; Q = quartile; SD = standard deviation; SES = socioeconomic situation; SUA = serum uric
acid; UA = uric acid; yr = years.
'Effect estimates are standardized to a 1 |jg/dL increase in blood Pb or a 10 |jg/g increase in bone Pb, unless otherwise noted. If the Pb biomarker is log-transformed, effect
estimates are standardized to the specified unit increase for the 10th-90th percentile interval of the biomarker level. Effect estimates are assumed to be linear within the evaluated
interval. Categorical effect estimates are not standardized.
aUnable to be standardized.
1
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