DRAFT - DO NOT CITE OR QUOTE
EPA/635/R-ll/001Da
United States www.epa.gov/iris
Environmental Protection
Agency
TOXICOLOGICAL REVIEW
OF
METHANOL (NONCANCER)
(CAS No. 67-56-1)
In Support of Summary Information on the
Integrated Risk Information System (IRIS)
July 2013
NOTICE
This document is a Final Interagency Science Discussion/Agency Review draft. This
information is distributed solely for the purpose of pre-dissemination peer review under
applicable information quality guidelines. It has not been formally disseminated by EPA. It does
not represent and should not be construed to represent any Agency determination or policy. It is
being circulated for review of its technical accuracy and science policy implications.
U.S. Environmental Protection Agency
Washington, DC
-------
DISCLAIMER
This information is distributed solely for the purpose of pre-dissemination peer review
under applicable information quality guidelines. It has not been formally disseminated by EPA.
It does not represent and should not be construed to represent any Agency determination or
policy. Mention of trade names or commercial products does not constitute endorsement or
recommendation for use.
July 2013 ii Do Not Cite or Quote
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CONTENTS TOXICOLOGICAL REVIEW OF METHANOL (Noncancer)
(CAS NO. 67-56-1)
LIST OF TABLES vi
LIST OF FIGURES ix
LIST OF ABBREVIATIONS AND ACRONYMS x
AUTHORS, CONTRIBUTORS, AND REVIEWERS xiii
CHEMICAL MANAGER XIII
AUTHORS XIII
CONTRIBUTORS XIII
TECHNICAL SUPPORT STAFF XIV
REVIEWERS XV
INTERNAL EPA RE VIEWERS XV
EXTERNAL PEER REVIEWERS XVI
EXECUTIVE SUMMARY xvii
INTRODUCTION XVII
CHEMICAL AND PHYSICAL INFORMATION XVII
TOXICOKINETICS XVIII
HAZARD IDENTIFICATION XX
DOSE-RESPONSE ASSESSMENT AND CHARACTERIZATION XXII
RELATIONSHIP OF THE RFC AND RFD TO BACKGROUND METHANOL
BLOOD LEVELS AND MONKEY BLOOD LEVELS ASSOCIATED WITH
EFFECTS OF UNCERTAIN ADVERSITY XXIV
1.. INTRODUCTION 1-1
2. .CHEMICAL AND PHYSICAL INFORMATION 2-1
3. .TOXICOKINETICS 3-1
3.1. OVERVIEW 3-1
3.2. KEY STUDIES 3-11
3.3. HUMAN VARIABILITY IN METHANOL METABOLISM 3-19
3.4. PHYSIOLOGIC ALLY BASED PHARMACOKINETIC MODELS 3-21
3.4.1. Model Requirements for EPA Purposes 3-21
3.4.2. MethanolPBPK Models 3-25
3.4.3. Selected Modeling Approach 3-27
3.4.4. Monkey PK Data and Analysis 3-32
3.4.5. Summary and Conclusions 3-33
4. .HAZARD IDENTIFICATION 4-1
4.1. STUDIES IN HUMANS - CASE REPORTS, OCCUPATIONAL AND
CONTROLLED STUDIES 4-1
4.1.1. Case Reports 4-1
4.1.2. Occupational Studies 4-3
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4.1.3. Controlled Human Studies 4-5
4.2. ACUTE, SUBCHRONIC AND CHRONIC STUDIES IN ANIMALS - ORAL
AND INHALATION 4-7
4.2.1. Oral Studies 4-7
4.2.2. Inhalation Studies 4-11
4.3. REPRODUCTIVE AND DEVELOPMENTAL STUDIES - ORAL AND
INHALATION 4-20
4.3.1. Oral Reproductive and Developmental Studies 4-20
4.3.2. Inhalation Reproductive and Developmental Studies 4-23
4.3.3. Other Reproductive and Developmental Studies 4-40
4.4. NEUROTOXICITY 4-47
4.4.1. Oral Neurotoxicity Studies 4-47
4.4.2. Inhalation Neurotoxi city Studies 4-50
4.4.3. Neurotoxicity Studies Employing i.p. and in vitro Methanol Exposures 4-58
4.5. IMMUNOTOXICITY 4-63
4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS 4-68
4.6.1. Summary of Key Studies in Methanol Toxicity 4-68
4.7. NONCANCER MOA INFORMATION 4-77
4.7.1. Role of Methanol and Metabolites in the Developmental Toxicity of Methanol 4-77
4.7.2. Role of Folate Deficiency in the Developmental Toxicity of Methanol 4-82
4.7.3. Methanol-Induced Formation of Free Radicals, Lipid Peroxidation, and Protein
Modifications 4-83
4.7.4. Exogenous Formate Dehydrogenase as a Means of Detoxifying the Formic Acid that
Results from Methanol Exposure 4-87
4.7.5. Summary and Conclusions Regarding MOA for Developmental Toxicity 4-88
4.8. EVALUATION OF CARCINOGENICITY 4-90
4.9. SUSCEPTIBLE POPULATIONS AND LIFE STAGES 4-90
4.9.1. Possible Childhood Susceptibility 4-90
4.9.2. Possible Gender Differences 4-91
4.9.3. Genetic Susceptibility 4-92
5. .DOSE-RESPONSE ASSESSMENTS 5-1
5.1. INHALATION REFERENCE CONCENTRATION (RFC) 5-1
5.1.1. Choice of Principal Study and Critical Effect(s) 5-1
5.1.2. Methods of Analysis for Identifying the POD—Application of PBPK and BMD
Models 5-8
5.1.3. RfC Derivation - Including Application of Uncertainty Factors 5-16
5.1.4. Previous RfC Assessment 5-25
5.2. ORAL REFERENCE DOSE (RFD) 5-25
5.2.1. Choice of Principal Study and Critical Effect-with Rationale and Justification 5-25
5.2.2. RfD Derivation-Including Application of Uncertainty Factors 5-28
5.2.3. Previous RfD Assessment 5-30
5.3. UNCERTAINTIES IN THE INHALATION RFC AND ORAL RFD 5-30
5.3.1. Choice of Study/Endpoint 5-32
5.3.2. Choice of Model for BMDL Estimation 5-35
5.3.3. Route-to-Route Extrapolation 5-35
5.3.4. Statistical Uncertainty at the POD 5-36
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5.3.5. Choice of Species/Gender 5-36
5.3.6. Relationship of the RfC and RfD to Background Levels of Methanol in Blood 5-38
5.3.7. Relationship of the RfC and RfD to Methanol Blood Levels In Monkeys Associated
with Unquantifiable Effects of Uncertain Adversity 5-40
5.4. CANCER ASSESSMENT 5-42
6. .REFERENCES 6-1
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LIST OF TABLES
Table 2-1 Relevant physical and chemical properties of methanol 2-1
Table 3-1 Background blood methanol and formate levels in human studies 3-2
Table 3-2 Human blood methanol and formate levels following methanol exposure 3-3
Table 3-3 Monkey blood methanol and formate levels following methanol exposure 3-4
Table 3-4 Mouse blood methanol and formate levels following methanol exposure 3-5
Table 3-5 Rat blood methanol and formate levels following methanol exposure 3-6
Table 3-6 Plasma methanol concentrations in monkeys 3-17
Table 3-7 Plasma formate concentrations in monkeys 3-17
Table 3-8 Serum folate concentrations in monkeys 3-18
Table 3-9 Routes of exposure optimized in models - optimized against blood
concentration data 3-27
Table 3-10 Key methanol kinetic studies for model validation 3-30
Table 4-1 Mortality rate for subjects exposed to methanol-tainted whisky in relation to
their level of acidosis 4-2
Table 4-2 Reproductive and developmental toxicity in pregnant Sprague-Dawley rats
exposed to methanol via inhalation during gestation 4-25
Table 4-3 Reproductive parameters in Sprague-Dawley dams exposed to methanol during
pregnancy, and then allowed to deliver their pups 4-27
Table 4-4 Embryonic and Developmental effects in CD-I mice after methanol inhalation 4-30
Table 4-5 Benchmark doses at two added risk levels 4-31
Table 4-6 Developmental Phase-Specific Embryotoxicity and Teratogenicity in
CD-I mice after methanol inhalation 4-32
Table 4-7 Developmental phase-specific embryotoxicity in CD-I mice induced by
methanol inhalation (15,000 ppm) during neurulation 4-33
Table 4-8 Reproductive parameters in monkeys exposed via inhalation to methanol
during prebreeding, breeding, and pregnancy 4-36
Table 4-9 Mean serum levels of testosterone, luteinizing hormone, and corticosterone
(± SD) in male Sprague-Dawley rats after inhalation of methanol, ethanol,
n-propanol orn-butanol at threshold limit values 4-38
Table 4-10 Maternal and litter parameters when pregnant female C57BL/6J mice were
injected i.p. with methanol 4-41
Table 4-11 Developmental studies of rodent embryos exposed to methanol 4-44
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Table 4-12 Reported thresholds concentrations (and author-estimated ranges) for the
onset of embryotoxic effects when rat and mouse conceptuses were incubated
in vitro with methanol, formaldehyde, and formate 4-46
Table 4-13 Brain weights of rats exposed to methanol vapors during gestation and
lactation 4-56
Table 4-14 Intraperitoneal injection neurotoxicity studies 4-61
Table 4-15 Effect of methanol on Wistar rat acetylcholinesterase activities 4-63
Table 4-16 Effect of methanol on neutrophil functions in in vitro and in vivo studies
in male Wistar rats 4-64
Table 4-17 Effect of intraperitoneally injected methanol on total and differential
leukocyte counts and neutrophil function tests in male Wistar rats 4-65
Table 4-18 Effect of methanol exposure on animal weight/organ weight ratios and on
cell counts in primary and secondary lymphoid organs of male Wistar rats 4-67
Table 4-19 The effect of methanol on serum cytokine levels in male Wistar rats 4-68
Table 4-20 Summary of noncancer effects reported in repeat exposure and
developmental studies of methanol toxicity in experimental animals (oral) 4-69
Table 4-21 Summary of repeat exposure and developmental studies of methanol
toxicity in experimental animals (inhalation exposure) 4-70
Table 4-22 Developmental outcome on GD10 following a 6-hour 10,000 ppm
(13,104 mg/m3) methanol inhalation by CD-mice or formate gavage
(750 mg/kg) on GD8 4-78
Table 4-23 Summary of ontogeny of relevant enzymes in CD-I mice and humans 4-79
Table 4-24 Dysmorphogenic effect of methanol and formate in neurulating CD-I
mouse embryos in culture (GD8) 4-80
Table 4-25 Time-dependent effects of methanol administration on serum liver and
kidney function, serum ALT, AST, BUN, and creatinine in control and
experimental groups of male Wistar rats 4-86
Table 4-26 Effect of methanol administration on male Wistar rats on malondialdehyde
concentration in the lymphoid organs of experimental and control groups and
the effect of methanol on antioxidants in spleen 4-87
Table 5-1 Summary of studies considered most appropriate for use in derivation of an
RfC 5-7
Table 5-2 The EPA PBPK model estimates of methanol blood levels (AUC) adjusted for
background (control) levels in rat dams following methanol inhalation
exposures and reported mean brain weights of 6-week-old male pups 5-13
Table 5-3 Maximum methanol blood levels (Cmax) adjusted for background, in mice
following inhalation exposures to methanol along with the corresponding
incidence of extra cervical ribs observed 5-15
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Table 5-4 Summary of PODs for critical endpoints, application of UFs and conversion to
candidate RfCs using PBPK modeling 5-17
Table 5-5 Comparison of the lowest rodent and monkey methanol blood LOAELs
(excluding background) observed in developmental neurotoxicity studies 5-24
Table 5-6 Summary of PODs for critical endpoints, application of UFs and conversion to
candidate RfDs using PBPK modeling 5-29
Table 5-7 Summary of uncertainties in methanol noncancer assessment 5-31
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LIST OF FIGURES
Figure 3-lMethanol metabolism and key metabolic enzymes in primates and rodents 3-9
Figure 3-2Folate-dependent formate metabolism. Tetrahydrofolate (THF)-mediated one
carbon metabolism is required for the synthesis of purines, thymidylate, and
methionine 3-10
Figure 3-3Plot of fetal (amniotic) versus maternal methanol concentrations in GD20 rats 3-14
Figure 3-4Conceptus versus maternal blood AUC values for rats and mice 3-24
Figure 3-5 Schematic of the PBPK model used to describe the inhalation, oral, and i.v.
route pharmacokinetics of methanol 3-31
Figure 4-lExposure response array for noncancer effects reported in animals from repeat
exposure and developmental studies of methanol (Oral) 4-72
Figure 4-2Exposure response array for noncancer effects reported in animals from repeat
exposure and developmental studies of methanol (Inhalation) 4-73
Figure 5-lFit of the Hill model to decreased mean brain weight in male rats at 6 weeks
age using estimated AUC of methanol in blood (adjusted for background) as
the dose metric. The BMD is estimated based on a BMR of one SD change
from the control mean 5-14
Figure 5-2Fit of the nested logistic (NLogistic) model- to the incidence of extra cervical
rib in fetal mice versus Cmax adjusted for background of methanol in blood
from a GD6-GD15 inhalation study in mice. The BMD is estimated based on a
BMR of 0.05 extra risk 5-16
Figure 5-3Projected impact of daily peak RfD and RfC exposures on sample background
methanol blood levels (mg MeOFt/Liter [mg/L] blood) in humans 5-40
Figure 5-4Relationship of monkey blood levels associated with effects of uncertain
adversity with projected impact of daily peak RfC and RfD exposures on
sample background methanol blood levels (mg MeOFt/Liter [mg/L] blood) in
humans 5-42
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LIST OF ABBREVIATIONS AND ACRONYMS
ACGIH
ADH
ADH1
ADH3
AIC
ALD
ALDH2
ALT
ANOVA
AP
AST
ATP
ATSDR
AUC
P-NAG
Bav
BMD
BMD1SD
BMDL
BMDL1S
1SD
BMDS
BMR
BSD
BUN
BW,bw
Ci pool
C-section
CA
CAR
CASRN
CAT
CERHR
American Conference of Governmental and
Industrial Hygienists
alcohol dehydrogenase
alcohol dehydrogenase-1
formaldehyde dehydrogenase-3
Akaike Information Criterion
aldehyde dehydrogenase
mitochondrial aldehyde dehydrogenase-2
alanine aminotransferase
analysis of variance
alkaline phosphatase
aspartate aminotransferase
adenosine triphosphate
Agency for Toxic Substances and Disease
Registry
area under the curve, representing the
cumulative product of time and
concentration for a substance in the blood
N-acetyl-beta-D-glucosaminidase
oral bioavailability
benchmark dose(s)
BMD for response one standard deviation
from control mean
lower limit of a one-sided 95% confidence
interval on BMD (benchmark dose)
BMDL for response one standard deviation
from control mean
benchmark dose software
benchmark response
butathione sulfoximine
blood urea nitrogen
body weight
one carbon pool
peak concentration of a substance in the
blood during the exposure period
Cesarean section
chromosomal aberrations
conditioned avoidance response
Chemical Abstracts Service Registry
Number
catalase
Center for the Evaluation of Risks to
Human Reproduction at the NTP
CH3OH
CHL
CI
Cls
*~inax
CNS
C02
con-A
CR
CSF
Css
CT
CVB
CvBbg
CvBmb
CYP450
d,5,A
D2
DA
DIPE
DMDC
DNA
DNT
DOPAC
DPC
DTH
EFSA
EKG
EO
EPA
ERF
EtOH
F
Fo
Fi
F2
F344
FAD
FAS
FD
methanol
Chinese hamster lung (cells)
confidence interval
clearance rate
peak concentration
central nervous system
carbon dioxide
concanavalin-A
crown-rump length
Cancer slope factor
steady-state concentration
computed tomography
concentration in venous blood
background concentration in venous blood
concentration in venous blood minus
constant background
cytochrome P450
delta, difference, change
dopamine receptor
dopamine
diisopropyl ether
dimethyl dicarbonate
deoxyribonucleic acid
developmental neurotoxicity test(ing)
dihydroxyphenyl acetic acid
days past conception
delayed-type hypersensitivity
European Food Safety Authority
electrocardiogram
Executive Order
U.S. Environmental Protection Agency
European Ramazzini Foundation
ethanol
fractional bioavailability
parental generation
first generation
second generation
Fisher 344 rat strain
folic acid deficient
folic acid sufficient
formate dehydrogenase
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FP folate paired
FR folate reduced
FRACIN fraction inhaled
FS folate sufficient
FSH follicular stimulating hormone
y-GT gamma glutamyl transferase
g gravity
g, kg, mg, ug gram, kilogram, milligram, microgram
G6PD glucose-6-phosphate dehydrogenase
GAP43 growth-associated protein (neuronal growth
cone)
GD gestation day
GFR glomerular filtration rate
GI gastrointestinal track
GLM generalized linear model
GLP good laboratory practice
GSH glutathione
HAP hazardous air pollutant
HCHO formaldehyde
HCOO formate
Hct hematocrit
HEC human equivalent concentration
HED human equivalent dose
HEI Health Effects Institute
HERO Health and Environmental Research Online
(database system)
HH hereditary hemochromatosis
5-HIAA 5-hydroxyindolacetic acid
HMGSH S-hydroxymethylglutathione
Hp haptoglobin
HPA hypothalamus-pituitary-adrenal (axis)
HPLC high-performance liquid chromatography
HSDB Hazardous Substances Databank
HSP70 biomarker of cellular stress
5-HT serotonin
IL interleukins
i.p. intraperitoneal (injection)
IPCS International Programme on Chemical
Safety
IQ intelligence quotient
IRIS Integrated Risk Information System
IUR inhalation unit risk
i.v. intravenous (injection)
kj first-order urinary clearance
km
klv
KLH
KLL
Km
ksl
L, dL, mL
LD50
LDH
LH
LLF
LMI
LOAEL
M, mM, uM
MeOH
MLE
M-M
MN
MOA
4-MP
MRI
mRNA
MTBE
MTX
N2O/O2
NAD+
NADH
NET
NCEA
ND
NEDO
NIEHS
first-order urinary clearance scaling
constant; first order clearance of methanol
from the blood to the bladder for urinary
elimination
first order uptake from the intestine
first order methanol oral absorption rate
from stomach
rate constant for urinary excretion from
bladder
respiratory /cardiac depression constant
keyhole limpet hemocyanin
alternate first order rate constant
apparent Michaelis-Menten constant;
substrate concentration at half the
maximum velocity (Vmax)
first order transfer between stomach and
intestine
liter, deciliter, milliliter
median lethal dose
lactate dehydrogenase
luteinizing hormone
(maximum) log likelihood function
leukocyte migration inhibition (assay)
lowest-observed-adverse-effect level
molar, millimolar, micromolar
methanol
maximum likelihood estimate
Michaelis-Menten
micronuclei
mode of action
4-methylpyrazole (fomepizole)
magnetic resonance imaging
messenger RNA
methyl tertiary butyl ether
methotrexate
nitrous oxide
nicotinamide adenine dinucleotide
reduced form of nicotinamide adenine
dinucleotide
nitroblue tetrazolium (test)
National Center for Environmental
Assessment
not determined
New Energy Development Organization (of
Japan)
National Institute of Environmental Health
Sciences
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NIOSH National Institute of Occupational Safety
and Health
nmol nanomole
NOAEL no-observed-adverse-effect level
NOEL no-observed-effect level
NP nonpregnant
NR not reported
NRC National Research Council
NS not specified
NTP National Toxicology Program at NIEHS
NZW New Zealand White (rabbit strain)
OR osmotic resistance
ORD Office of Research and Development
OSF oral slope factor
OU oculus uterque (each eye)
OXA oxazolone
P, p probability
PB blood:air partition coefficient
PBPK physiologically based pharmacokinetic
model
PC partition coefficient
PEG polyethylene glycol
PFC plaque-forming cell
PK pharmacokinetic
PMN polymorphonuclear leukocytes
PND postnatal day
POD point of departure
ppb, ppm parts per billion, parts per million
PR body :blood partition coefficent
PWG Pathology Working Group of the NTP of
NIEHS
Q wave the initial deflection of the QRS complex
QCC cardiac output scaling constant
QP pulmonary (alveolar) ventilation
QRS portion of electrocardiogram corresponding
to the depolarization of ventricular cardiac
cells.
R2 square of the correlation coefficient, a
measure of the reliability of a linear
relationship.
RBC red blood cell
RfC reference concentration
RfD reference dose
RNA ribonucleic acid
R0bg zero-order endogenous production rate
ROS reactive oxygen species
S9 microsomal fraction from liver
SAP serum alkaline phosphatase
s.c. subcutaneous
SCE sister chromatid exchange
S-D Sprague-Dawley rat strain
SD standard deviation
S.E. standard error
SEM standard error of mean
SGPT serum glutamate pyruvate transaminase
SHE Syrian hamster embryo
SOD superoxide dismutase
SOP standard operating procedure(s)
T; T,/2, t/2 time; half-life
T wave the next deflection in the electrocardiogram
after the QRS complex; represents
ventricular repolarization
TAME tertiary amyl methyl ether
TAS total antioxidant status
Tau taurine
THF tetrahydrofolate
TLV threshold limit value
TNFa tumor necrosis factor-alpha
TNP-LPS trinitrophenyl-lipopolysaccharide
TRI Toxic Release Inventory
U83836E vitamin E derivative
UF(s) uncertainty factor(s)
UFA UF associated with interspecies (animal to
human) extrapolation
UFD UF associated with deficiencies in the
toxicity database
UFH UF associated with variation in sensitivity
within the human population
UFS UF associated with subchronic to chronic
exposure
Vd volume of distribution
Vmax pseudo-maximal velocity of metabolism
VmaxC multiplier for allometric scaling of Vmax
VDR visually directed reaching test
VitC vitamin C
VPR ventilation perfusion ratio
v/v volume of solute/volume of solution
VYS visceral yolk sac
WBC white blood cell
WOE weight of evidence
w/v weight (mass of solute)/volume of solution
X2 chi square
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AUTHORS, CONTRIBUTORS, AND REVIEWERS
Chemical Manager
Jeffrey Gift, Ph.D.
National Center for Environmental Assessment
U.S Environmental Protection Agency
Research Triangle Park, NC
Authors
Stanley S.Barone, Jr.; Ph.D.
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Washington, DC
J. Allen Davis, MSPH
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
Jeffrey Gift, Ph.D.
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
Annette lannucci, M.S.
Sciences International (first draft)
2200 Wilson Boulevard
Arlington, VA
Paul Schlosser, Ph.D.
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Washington, DC
Contributors
Bruce Allen, Ph.D.
Bruce Allen Consulting
101 Corbin Hill Circle
Chapel Hill, SC
Hugh Barton, Ph.D.
National Center for Computational Toxicology
U.S. Environmental Protection Agency
Research Triangle Park, NC
J. Michael Davis, Ph.D.
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
Robinan Gentry, M.S.
ENVIRON International
650 Poydras Street
New Orleans, LA
Susan Goldhaber, M.S.
Alpha-Gamma Technologies, Inc.
3301 Benson Drive
Raleigh, NC
Mark Greenberg, Ph.D.
Senior Environmental Employee Program
U.S. Environmental Protection Agency
Research Triangle Park, NC
George Holdsworth, Ph.D.
Oak Ridge Institute for Science and Education
Badger Road
Oak Ridge, TN
Angela Howard, Ph.D.
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
July 2013
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Lisa Lowe, Ph.D.
Oak Ridge Institute for Science and Education
Badger Road
Oak Ridge, TN
Greg Miller
Office of Policy, Economics & Innovation
U.S. Environmental Protection Agency
Washington, DC
Sharon Oxendine, Ph.D.
Office of Policy, Economics & Innovation
U.S. Environmental Protection Agency
Washington, DC
Torka Poet, Ph.D.
Battelle, Pacific Northwest National
Laboratories
902 Battelle Boulevard
Richland, WA
John Rogers, Ph.D.
National Health & Environmental Effects
Research laboratory
U.S. Environmental Protection Agency
Research Triangle Park, NC
Reeder Sams, II, Ph.D.
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
Kan Shao, Ph.D.
Oak Ridge Institute for Science and Education
Badger Road
Oak Ridge, TN
Roy Smith, Ph.D.
Air Quality Planning & Standards
U.S. Environmental Protection Agency
Research Triangle Park, NC
Frank Stack
Alpha-Gamma Technologies, Inc.
3301 Benson Drive
Raleigh, NC
Justin TeeGuarden, Ph.D.
Battelle, Pacific Northwest National
Laboratories
902 Battelle Boulevard
Richland, WA
Chad Thompson, Ph.D., MBA
ToxStrategies
Katy, TX
Lutz Weber, Ph.D., DABT
Oak Ridge Institute for Science and Education
Badger Road
Oak Ridge, TN
Errol Zeiger, Ph.D.
Alpha-Gamma Technologies, Inc.
3301 Benson Drive
Raleigh, NC
Technical Support Staff
Kenneth J. Breito
Senior Environmental Employment Program,
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
Ellen Lorang
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
J. Sawyer Lucy
Student Services Authority
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
Deborah Wales
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
Richard N. Wilson
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
Barbara Wright
Senior Environmental Employment Program
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
July 2013
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Reviewers
This document has been provided for review to EPA scientists, interagency reviewers
from other federal agencies and White House offices, and the public, and has been peer reviewed
by independent scientists external to EPA. A summary and EPA's disposition of the comments
received from the independent external peer reviewers and from the public is included in
Appendix A.
Internal EPA Reviewers
Jane Caldwell, Ph.D.
National Center for Environmental Assessment
U.S Environmental Protection Agency
Washington, DC
Ila Cote, Ph.D., DABT
National Center for Environmental Assessment
U.S Environmental Protection Agency
Washington, DC
Robert Dewoskin Ph.D., DABT
National Center for Environmental Assessment
U.S Environmental Protection Agency
Research Triangle Park, NC
Joyce Donahue, Ph.D.
Office of Water
U.S. Environmental Protection Agency
Washington, DC
Marina Evans, Ph.D.
National Health and Environmental Effects
Research Laboratory
U.S Environmental Protection Agency
Research Triangle Park, NC
Lynn Flowers, Ph.D., DABT
National Center for Environmental Assessment
U.S Environmental Protection Agency
Research Triangle Park, NC
Brenda Foos, M.S.
Office of Children's Health Protection and
Environmental Education
U.S Environmental Protection Agency
Washington, DC
Jennifer Jinot, Ph.D.
National Center for Environmental Assessment
U.S Environmental Protection Agency
Washington, DC
Eva McLanahan, Ph.D.
National Center for Environmental Assessment
U.S Environmental Protection Agency
Research Triangle Park, NC
Connie Meacham, M.S.
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC
John Vandenberg, Ph.D.
National Center for Environmental Assessment
U.S Environmental Protection Agency
Research Triangle Park, NC
Debra Walsh, M.S.
National Center for Environmental Assessment
U.S Environmental Protection Agency
Research Triangle Park, NC
July 2013
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External Peer Reviewers
Janusz Z. Byczkowski, Ph.D.
Independent Consultant
Fairborn, OH
Thomas M. Burbacher, Ph.D.
Professor
University of Washington
Seattle, WA
David C. Dorman, Ph.D.
Professor
NCSU-College of Veterinary Medicine
Raleigh, NC
Kenneth McMartin, Ph.D.
Professor
LSU Health Sciences Center
Shreveport, LA
Stephen Roberts, Ph.D. (Chair)
Professor
University of Florida
Gainesville, FL
Andrew Salmon, Ph.D.
Senior Toxicologist
California EPA- OEHHA
Lafayette, CA
Lisa M. Sweeney, Ph.D.
Consultant
Henry M. Jackson Foundation for the
Advancement of Military Medicine
Naval Medical Research Unit-Dayton
Kettering, OH
July 2013
XVI
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EXECUTIVE SUMMARY
Introduction
1 Methanol is a high production volume chemical with many commercial uses. It is a basic
2 building block for numerous chemicals. Many of its derivatives are used in the construction,
3 housing or automotive industries. Consumer products that contain methanol include varnishes,
4 shellacs, paints, windshield washer fluid, antifreeze, adhesives, and deicers.
5 Methanol can be formed in the mammalian organism as a metabolic byproduct.
6 Endogenous background levels [naturally generated from within the body] are not the same as
7 exogenous exposure (exposure from a source outside the body), but the combination of
8 endogenous background levels of methanol plus exogenous methanol exposure can lead to
9 toxicity. Diet can contribute to background levels of methanol, principally from the ordinary
10 ingestion of fruits and vegetables. This Toxicological Review provides scientific support and
11 rationale for a hazard identification and dose-response assessment of the noncancer effects
12 associated with chronic exposures to exogenous sources of methanol that add to background
13 levels of methanol. For the purpose of this methanol (noncancer) assessment, EPA estimates that
14 a diet that includes fruits and vegetables would not increase methanol blood levels above 2.5
15 mg/L (see discussion in Section 5.3.6). Thus, for a population with background blood levels of
16 methanol at or below 2.5 mg/L, the inhalation reference concentration (RfC) and oral reference
17 dose (RfD) that are derived in this assessment represent estimates (with uncertainty spanning
18 perhaps an order of magnitude) of daily exposures to the human population (including sensitive
19 subgroups) that are likely to be without an appreciable risk of deleterious effects during a
20 lifetime. In Section 5 (Dose Response Assessments), the basis for a RfC of 2x 101 mg/m3 and a
21 RfD of 2 mg/kg-day are described.
22 This health assessment does not assess the potential carcinogenicity of methanol, or the
23 health effects associated with background levels of methanol that arise from metabolic and
24 dietary sources such as vegetables, fruits and juices that naturally contain methanol or have
25 components (e.g., plant pectin) that convert to methanol. Hence, as discussed in Section 3.4.3.2
26 (Model Structure), responses observed in oral and inhalation studies of laboratory animals
27 exposed to methanol are evaluated against blood concentrations of methanol in control animals.
Chemical and Physical Information
28 Methanol is the smallest member of the family of aliphatic alcohols. Also known as
29 methyl alcohol or wood alcohol, among other synonyms, it is a clear, colorless, very volatile, and
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1 flammable liquid. Methanol is widely used as a solvent in many commercial and consumer
2 products. It is freely miscible with water and other short-chain aliphatic alcohols but has little
3 tendency to distribute into lipophilic media.
Toxicokinetics
4 Due to its very low oil:water partition coefficient, methanol is taken up efficiently by the
5 lung or the intestinal tract and distributes freely in body water (blood volume, extracellular and
6 intracellular fluid, etc.) without any tendency to accumulate in fatty tissues. Methanol can be
7 metabolized completely to CC>2, but may also, as a regular byproduct of metabolism, enter the
8 formic acid Ci-pool (1-carbon unit pool), and become incorporated into biomolecules. Animal
9 studies indicate that blood methanol levels increase with the breathing rate and that metabolism
10 becomes saturated at high exposure levels. Because of its volatility methanol can be exhaled with
11 air, and also excreted unchanged via urine. As discussed in Section 3.1 (Toxicokinetics
12 Overview), the enzymes responsible for metabolizing methanol are different in rodents and
13 primates (Figure 3-1). Several published rat, mouse, and human PBPK models which attempt to
14 account for these species differences are described in Section 3.4.2 (Methanol PBPK Models).
15 The development of methanol PBPK models was organized around a set of criteria,
16 described in Section 3.4.1.2 (Criteria for the Development of Methanol PBPK Models), that take
17 into account the dose routes used in key toxicity studies, the availability of pharmacokinetic
18 information necessary for PBPK model development and the most likely toxicological mode of
19 action (MOA). Specifically, EPA developed new PBPK models or modified the existing ones,
20 which allowed for the estimation of monkey and rat internal dose metrics. A human model was
21 also developed to extrapolate those internal metrics to inhalation and oral exposure
22 concentrations that would result in the same internal dose in humans (human equivalent
23 concentrations [HECs] and human equivalent doses [HEDs]). The procedures used for the
24 development, calibration and use of these EPA models are summarized in Section 3.4
25 (Physiologically Based Pharmacokinetic Models), with further details provided in Appendix B,
26 "Development, Calibration and Application of a Methanol PBPK Model."
27 Developmental malformations and anomalies in gestationally exposed fetal mice (and
28 developmental neurotoxicity, as indicated by reduced absolute brain weight, in gestationally and
29 lactationally exposed fetal and neonate rats) observed in inhalation studies are sensitive
30 endpoints considered in the derivation of an RfC. However, questions remain regarding the
31 relative involvement of parent methanol, formaldehyde, and reactive oxygen species (ROS) in
32 the MOA for these developmental effects. Given the reactivity of formaldehyde and the lack of
33 relevant pharmacokinetic information, PBPK models that predict levels of formaldehyde (or
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1 subsequent metabolites of formaldehyde) in the blood would be difficult to validate.l However,
2 the high reactivity of formaldehyde (see Section 3.1 [Toxicokinetics Overview]) would limit its
3 unbound and unaltered transport as free formaldehyde from maternal to fetal blood (see
4 discussion in Section 3.4.1.1 [MOA and Selection of a Dose Metric] and 4.7.1 [Role of Methanol
5 and Metabolites in the Developmental Toxicity of Methanol]), and the ROS MOA requires the
6 presence of methanol to alter embryonic catalase activity. Hence, it is likely that all of these
7 MO As require methanol to be present at the target site. For this reason, and because adequate
8 pharmacokinetic information was available, PBPK models that estimate levels of parent
9 methanol in blood were developed and validated for rats and humans. Because actual measured
10 internal blood methanol levels suitable for use as estimates of peak concentrations (Cmax) in mice
11 were provided in the Rogers et al. (1993b) study, and these data were considered better than a
12 predictive model, the mouse PBPK model was not used or discussed in detail in this
13 toxicological review. A simple PK model for monkey methanol kinetics was also developed and
14 used to evaluate the results of monkey developmental studies (Burbacher et al., 2004a: 2004b:
15 1999a: 1999b).
16 A pregnancy-specific PBPK model does not exist for methanol and limited data exist for
17 the development and validation of a fetal/gestational/conceptus compartment. For this reason,
18 and because levels of methanol in non-pregnant and pregnant adult females, and fetal blood (all
19 measures of maternal exposure) are expected to be similar following the same oral or inhalation
20 methanol exposure (see discussion in Section 3.4.1.2 [Criteria for the development of Methanol
21 PBPK Models]), EPA developed and used non-pregnancy models for the appropriate species and
22 routes of exposure for the derivation of candidate RfCs and RfDs. It is recognized that these
23 models may not accurately represent neonate blood levels following the gestation, lactation and
24 inhalation exposure regimen used in one of the key rat studies (NEDO, 1987), but they are
25 considered appropriate for use in deriving HEC values from this study assuming the ratio of
26 maternal to offspring blood methanol would be similar in rats and humans (see discussion in
27 Sections 5.1.3.2.2 [Animal-to-Human Extrapolation UFA]).
28 The rat and human methanol PBPK models fit multiple data sets for inhalation, oral, and
29 i.v. exposures, from multiple research groups using consistent parameters that are representative
30 of each species but are not varied within species or by dose or source of data. Also, a simple PK
31 model calibrated to non-pregnant (NP) monkey data, which were shown to be essentially
32 indistinguishable from pregnant monkey PK data, was used to estimate blood methanol area
33 under the curve (AUC) values (internal doses) in that species. In the case of the mouse, a PK
1 The PBPK models developed by EPA estimate total amount of methanol cleared by metabolic processes, but this
has limited value as a metric of formaldehyde or formate dose since it ignores metabolic processes that may differ
between species and between the mother and the fetus/neonate.
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1 model developed from in vivo blood methanol levels in (Rogers et al., (1993b) resulted in more
2 reliable estimates compared to the PBPK model and was used for derivation of effect levels in
3 this species. Section 5 (Dose Response Assessments and Characterization) describes how the
4 human PBPK model was used in the derivation of candidate RfCs and RfDs.
Hazard Identification
5 In humans, acute central nervous system (CNS) toxicity can result from relatively low
6 ingested doses (as low as 3-20 mL of methanol), which can metabolize to formic acid and lead to
7 metabolic acidosis. The resulting acidosis can potentially cause lasting nervous system effects
8 such as blindness, Parkinson-like symptoms, and cognitive impairment. These effects can be
9 observed in humans when blood methanol levels exceed 200 mg/L.
10 CNS effects have not been observed in rodents following acute exposures to methanol,
11 and NEDO (1987) reported that methanol blood levels around 5,000 mg/L were necessary to
12 cause clinical signs and CNS changes in cynomolgus monkeys. The species differences in
13 toxicity from acute exposures appear to be the result of a limited ability of humans to metabolize
14 formic acid.
15 Occupational studies and case reports offer valuable information on the effects of
16 methanol following acute human exposures, but the relatively small amount of data for
17 subchronic, chronic, or in utero human exposures are inconclusive. However, a number of
18 reproductive, developmental, subchronic, and chronic toxicity studies have been conducted in
19 mice, rats, and monkeys.
20 Data regarding effects from oral exposure in experimental animals exist, but they are
21 more limited than data from the inhalation route of exposure (see Sections 4.2 [Acute,
22 Subchronic, and Chronic Studies in Animals - Oral and Inhalation], 4.3 [Reproductive and
23 Developmental Studies - Oral and Inhalation], and 4.4 [Neurotoxicity]). Two oral studies in rats
24 (Soffritti et al.. 2002: TRL, 1986), one oral study in mice (Apaja, 1980) and several inhalation
25 studies in monkeys, rats and mice (NEDO, 1987, 1985a, b) of 90-days duration or longer have
26 been reported. Some noncancer effects of methanol exposure were noted in these studies,
27 principally in the liver and brain tissues, but they occurred at relatively high doses.
28 A number of studies have used the inhalation route of exposure to assess the potential of
29 reproductive or developmental toxicity of methanol in mice, rats, and monkeys (see Section 4.3.2
30 [Inhalation Reproductive and Developmental Studies]). These studies indicate that fetal and
31 neonate toxicity occurs at lower doses than maternal toxicity. At exposure concentrations of
32 5,000 ppm or above, methanol has been shown to cause an increase in litters with resorptions
33 (Bolon etal., 1993), and severe malformations (exencephaly and cleft palate) in mice, the most
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1 sensitive gestational days being GD6 and GD7 (i.e., early organogenesis) (Rogers and Mole,
2 1997; Rogers et al., 1993a: Rogers et al., 1993b). Increased occurrences of ossification
3 disturbances and skeletal anomalies were observed at exposure concentrations of 2,000 ppm in
4 mice (Rogers et al.. 1993b) and at 10,000 ppm in rats (Nelson et al.. 1985). NEDO (1987)
5 conducted a series of developmental and reproductive studies, including a two generation and a
6 follow up one generation reproductive toxicity study in rats, which used exposure times of 20
7 hours/day or more at concentrations between 100 and 5,000 ppm. Details were not reported (e.g.,
8 means, variances, sample sizes, pup-to-litter correlations) that would allow for an analysis of the
9 findings from this study. However, a follow-up one-generation study conducted by NEDO (1987)
10 contained enough information to confirm and quantify the primary endpoint identified, pup brain
11 weight changes. This developmental neurotoxicity study is discussed in Section 4.4.2 (Inhalation
12 Neurotoxicity Studies). Section 4.4.2 also describes another key developmental neurotoxicity
13 study conducted in pregnant cynomolgus monkeys exposed to 200-1,800 ppm methanol for 2.5
14 hours/day throughout pre-mating, mating, and gestation (Burbacher et al., 2004a: 2004b: 1999a:
15 1999b). Potential compound-related effects noted were a shortening of the gestation period by
16 less than 5%, and developmental neurotoxicity (particularly delayed sensorimotor development)
17 in the monkeys.
18 As discussed in Section 4.6.1.2 (Key Studies, Inhalation), due largely to the lack of clear
19 dose-response information, the data from the monkey developmental study are not conclusive,
20 and there was insufficient evidence to determine if the primate fetus is more sensitive, or less
21 sensitive, than rodents to the developmental or reproductive effects of methanol. Taken together,
22 however, the NEDO (1987) rat study and the Burbacher et al. (2004a: 2004b: 1999a: 1999b)
23 monkey study suggest that prenatal exposure to methanol can result in adverse effects on
24 developmental neurology pathology and function, which can be exacerbated by continued
25 postnatal exposure. Among an array of findings indicating developmental neurotoxicity and
26 developmental malformations and anomalies that have been observed in rodents, a decrease in
27 the brain weights of gestationally and lactationally exposed neonatal rats (NEDO, 1987) and an
28 increase in the incidence of cervical ribs of gestationally exposed fetal mice (Rogers et al.,
29 1993b) are considered the most robust endpoints for the purposes of RfD and RfC derivation.
30 See Section 4.6 (Synthesis of Major Noncancer Effects) for a more extensive summary of the
31 dose-related effects that have been observed following subchronic or chronic exposure.
32 Sections 4.7 (Noncancer MOA Information) and 5.3.5 (Choice of Species/Sex), provide a
33 discussion of the uncertainty regarding human relevance of the mouse and rat developmental
34 studies due to differences in the way humans and rodents metabolize methanol. Adult humans
35 metabolize methanol principally via alcohol dehydrogenase (ADH1) and rodents via catalase and
36 ADH1. Recent studies in mice have demonstrated that high catalase activity can reduce, and low
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1 catalase activity can enhance, methanol's embryotoxic effects. However, the MOAfor these
2 effects, and the role of catalase, have not been determined. Further, while catalase does not
3 appear to be involved in adult human methanol metabolism, less is known about the metabolism
4 of methanol in human infants (see Section 3.3 [Human Variability in Methanol Metabolism]).
5 Thus, the effects observed in rodents are considered relevant for the assessment of human health.
Dose-Response Assessment and Characterization
6 As discussed above and in Section 5.1.1 (Choice of Principal Study and Critical
7 Effect[s]), reproductive and developmental effects are considered the most sensitive and
8 quantifiable effects reported in studies of methanol. Because the oral reproductive and
9 developmental studies employed single and comparatively high doses (i.e., oral versus
10 inhalation), the developmental effects observed in the inhalation studies were used to derive the
11 RfC and, using a route-to-route extrapolation, the RfD.
12 Clearly defined toxic endpoints at moderate exposure levels have been observed in
13 inhalation studies of reproductive and developmental toxicity (see Section 5.1.1.2 [Selection of
14 Critical Effect[s]). Three endpoints from inhalation developmental toxicity studies were critically
15 evaluated for derivation of the RfC: (1) increased occurrences of ossification disturbances and
16 skeletal abnormalities (i.e., formation of cervical ribs) in CD-I mice exposed to methanol during
17 organogenesis (Rogers et al., 1993b): (2) reduced brain weights in rats exposed to methanol from
18 early gestation through 8 weeks of postnatal life (NEDO, 1987): and (3) deficits in sensorimotor
19 development in the offspring of monkeys exposed to methanol throughout gestation (Burbacher
20 et al.. 2004a: 2004b: 1999a: 1999b).
21 Rogers et al. Q993b) exposed CD-I mice to air concentrations of 0; 1,000; 2,000; and
22 5,000 ppm methanol for 7 hours/day on GD7 to GDI7. A lower limit of a one-sided 95%
23 confidence interval on the BMD (BMDL) of 43 mg/L was estimated for the internal peak blood
24 methanol (Cmax) associated with 5% extra risk for the formation of cervical ribs (see Section
25 5.1.2.3 [BMD Approach Applied to Cervical Rib Data in Mice] and Appendix D [RfC Derivation
26 Options]). This BMDLos was then divided by 100 to account for uncertainties associated with
27 human variability (UFH), the animal-to-human extrapolation (UFA) and the database (UFD), and
28 to reduce it to a level that is within the range of blood levels for which the human PBPK model
29 was calibrated (see discussion in Section 5.1.3.2 [Application of UFs]). The PBPK model was
30 then used to convert this adjusted internal BMDLos of 0.43 mg/L to a human equivalent
31 candidate RfC of 20.0 mg/m3 (see Section 5.1.3 [RfC Derivation - Including Application of
32 Uncertainty Factors]) and a candidate RfD of 1.9 mg/kg-day (see Section 5.2.2 [RfD Derivation
33 - Including Application of Uncertainty Factors]).
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1 NEDO (1987) exposed fetal Sprague-Dawley rats and their dams to air concentrations of
2 0, 500, 1,000 and 2,000 ppm methanol from the first day of gestation (GDI) until 8 weeks of
3 age, and brain weights were determined at 3, 6, and 8 weeks of age. A BMDL of 858 mg-hr/L
4 was estimated for the area under the curve (AUC) internal blood methanol dose, associated with
5 a brain weight reduction at 6 weeks equal to one standard deviation (SD) from the control mean
6 (see Section 5.1.2.2 [BMD Approach Applied to Brain Weight Data in Rats], and Appendix D
7 [RfC Derivation Options[). This BMDLiso was then divided by 100 to account for uncertainties
8 associated with human variability (UFn), the animal-to-human extrapolation (UFA) and the
9 database (UFD), and to reduce it to a level that is within the range of blood levels for which the
10 human PBPK model was calibrated (see discussion in Section 5.1.3.2 [Application of UFs]). The
11 PBPK model was then used to convert this adjusted internal BMDLiso of 8.58 mg-hr/L to a
12 human equivalent candidate RfC of 17.8 mg/m3 (see Section 5.1.3 [RfC Derivation - Including
13 Application of Uncertainty Factors]) and a candidate RfD of 5.2 mg/kg-day (see Section 5.2.2
14 [RfD Derivation - Including Application of Uncertainty Factors]).
15 Burbacher et al. (2004a; 2004b: 1999a: 1999b) exposed M. fascicularis monkeys to
16 0, 200, 600, or 1,800 ppm methanol 2.5 hours/day, 7 days/week during pre-mating/mating and
17 throughout gestation (approximately 168 days). A BMDLSo of 19.6 mg/L was estimated for the
18 blood methanol Cmax associated with a one SD delay in sensorimotor development in the
19 offspring as measured by a visually directed reaching (VDR) test (see Appendix D [RfC
20 Derivation Options]). However, only the unadjusted VDR response for females exhibited a
21 response that could be modeled and the dose-response was marginally significant, with only the
22 high dose exhibiting a response significantly different from controls. Although, the metabolism
23 of methanol in monkeys is comparable to humans (Section 3.1 [Toxicokinetics Overview]) and a
24 delay in VDR is a potentially relevant CNS effect (Section 4.4.2 [Inhalation Neurotoxicity
25 Studies]), EPA concluded that the use of this data for RfC/D derivation was not preferable, given
26 the availability of more reliable dose-response data from the Rogers et al. (1993b) and NEDO
27 (1987) rodent studies.
28 In summary, after the evaluation of different species, different endpoints, different
29 protocols and different data sources, the Rogers et al. (1993b) mouse, NEDO (1987) rat, and
30 Burbacher et al. (2004a: 2004b: 1999a: 1999b) monkey studies exhibited developmental effects
31 at similar doses, providing consistent results. As described in Sections 5.1.1.2 (Selection of
32 Critical Effects) and 5.2.1.1 (Expansion of the Oral Database by Route-to-Route Extrapolation),
33 because the Rogers et al. (1993b) and NEDO (1987) studies identified relevant effects in relevant
34 species that could be adequately quantified in a dose-response analysis, they are considered the
35 most appropriate studies for use in the RfC and RfD derivation. The candidate RfC of 2x 101
36 mg/m3 based on decreased brain weight observed in the NEDO (1987) rat developmental study
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1 (see Table 5-4 [Summary of POD values for critical endpoints, application of UFs and
2 conversion to candidate RfCs using PBPK modeling]) was selected as the RfC for methanol. The
3 candidate RfD of 2 mg/kg-day based on the formation of extra cervical ribs observed in the
4 Rogers et al. (1993b) mouse developmental study (see Table 5-6 [Summary of POD values for
5 critical endpoints, application of UFs and conversion to candidate RfDs using PBPK modeling])
6 was selected as the RfD for methanol. As described in Sections 5.1.3 (RfC Derivation -
7 Including Application of Uncertainty Factors) and 5.2.2 (RfD Derivation - Including Application
8 of Uncertainty Factors), the UFs employed for both the RfC and RfD derivations include a UFn
9 of 10 for intraspecies variability, a UFA of 3 to address pharmacodynamic uncertainty and a UFD
10 of 3 for database uncertainty.
Relationship of the RfC and RfD to Background Methanol
Blood Levels and Monkey Blood Levels Associated with
Effects of Uncertain Adversity
11 In Section 5.3.6, EPA compares the expected increase in methanol levels in blood
12 resulting from exposure to methanol at the level of the RfC or RfD to background blood levels of
13 methanol estimated from (1) daily endogenous production and dietary exposure estimates from
14 the UK report (COT, 2011) and (2) a sample background distribution derived from relevant study
15 groups in Table 3-1 of this toxicological review. Both the EPA and the UK data are consistent
16 with approximately 2.5 mg/L representing a high end of the range of background (as defined in
17 Section 5.3.6) methanol blood levels. EPA estimates that the shift in EPA's sample background
18 methanol blood level distribution that would be associated with daily exposures of the entire
19 population to methanol at the RfC or the RfD would result in approximately 85% and 94%
20 increases, respectively, in the number of individuals with daily peak methanol blood levels at or
21 above 2.5 mg/L. EPA's PBPK model predicts that a continuous daily methanol exposure at the
22 RfD or RfC would raise the peak methanol blood level of an individual with a high end
23 background methanol blood level of 2.5 mg/L to just under 3 mg/L. As discussed in Section
24 5.3.7, this 3 mg/L methanol blood level is at the low end of the range of methanol blood levels
25 that have been reported in monkey chronic and gestational exposure studies to be associated with
26 CNS and reproductive/developmental effects of uncertain, but potential adversity.
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1.INTRODUCTION
1 This document presents background information and justification for the Integrated Risk
2 Information System (IRIS) Summary of the hazard and dose-response assessment of methanol.
3 IRIS Summaries may include oral reference dose (RfD) and inhalation reference concentration
4 (RfC) values for chronic and other exposure durations, and a carcinogenicity assessment.
5 The RfD and RfC, if derived, provide quantitative information for use in risk assessments
6 for noncancer health effects known or assumed to be produced through a nonlinear (presumed
7 threshold) mode of action (MOA). The RfD (expressed in units of milligrams per kilogram per
8 day [mg/kg-day]) is defined as an estimate (with uncertainty spanning perhaps an order of
9 magnitude) of a daily exposure to the human population (including sensitive subgroups) that is
10 likely to be without an appreciable risk of deleterious effects during a lifetime. The inhalation
11 RfC (expressed in units of milligrams per cubic meter [mg/m3]) is analogous to the oral RfD but
12 provides a continuous inhalation exposure estimate. The inhalation RfC considers toxic effects
13 for both the respiratory system (portal-of-entry) and for effects peripheral to the respiratory
14 system (extrarespiratory or systemic effects). Reference values are generally derived for chronic
15 exposures (up to a lifetime), but may also be derived for acute (< 24 hours), short-term
16 (>24 hours up to 30 days), and subchronic (>30 days up to 10% of lifetime) exposure durations,
17 all of which are derived based on an assumption of continuous exposure throughout the duration
18 specified. Unless specified otherwise, the RfD and RfC are derived for chronic exposure
19 duration.
20 Development of these hazard identification and dose-response assessments for the
21 noncancer effects of methanol has followed the general guidelines for risk assessment as set forth
22 by the National Research Council (NRC) (1983). EPA Guidelines and Risk Assessment Forum
23 Technical Panel Reports that may have been used in the development of this assessment include
24 the following: Guidelines for the Health Risk Assessment of Chemical Mixtures (U.S. EPA,
25 1986), Recommendations for and Documentation of Biological Values for Use in Risk
26 Assessment (U.S. EPA, 1988), Guidelines for Developmental Toxicity Risk Assessment (U.S.
27 EPA, 1991), Interim Policy for Particle Size and Limit Concentration Issues in Inhalation
28 Toxicity Studies (U.S. EPA, 1994a), Methods for Derivation of Inhalation Reference
29 Concentrations and Application of Inhalation Dosimetry (U.S. EPA, 1994b), Use of the
30 Benchmark Dose Approach in Health Risk Assessment (U.S. EPA, 1995), Guidelines for
31 Reproductive Toxicity Risk Assessment (U.S. EPA, 1996), Guidelines for Neurotoxicity Risk
32 Assessment (U.S. EPA, 1998a), Science Policy Council Handbook: Risk Characterization (U.S.
33 EPA, 2000a), Supplementary Guidance for Conducting Health Risk Assessment of Chemical
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1 Mixtures (U.S. EPA, 2000b), A Review of the Reference Dose and Reference Concentration
2 Processes (U.S. EPA. 20021 Science Policy Council Handbook: Peer Review (U.S. EPA. 2006b).
3 and A Framework for Assessing Health Risks of Environmental Exposures to Children (U.S.
4 EPA, 2006a), benchmark Dose Technical Guidance Document (U.S. EPA, 2012).
5 Primary, peer-reviewed literature identified through January 2013 was included where
6 that literature was determined to be relevant to the assessment. The relevant literature included
7 publications on methanol that were identified through Toxicology Literature Online (TOXLINE),
8 PubMed, the Toxic Substance Control Act Test Submission Database (TSCATS), the Registry of
9 Toxic Effects of Chemical Substances (RTECS), the Chemical Carcinogenesis Research
10 Information System (CCRIS), the Developmental and Reproductive Toxicology/Environmental
11 Teratology Information Center (DART/ETIC), the Hazardous Substances Data Bank (HSDB),
12 the Genetic Toxicology Data Bank (GENE-TOX), Chemical abstracts, and Current Contents.
13 Other peer-reviewed information, including health assessments developed by other
14 organizations, review articles, and independent analyses of the health effects data were retrieved
15 and included in the assessment where appropriate. Studies that had not been peer-reviewed and
16 were potentially critical to the conclusions of the assessment were separately and independently
17 peer-reviewed. Any pertinent scientific information submitted by the public to the IRIS
18 Submission Desk or by reviewers during internal and external peer reviews was also considered
19 in the development of this document. It should be noted that references added to the
20 Toxicological Review after the external peer review in response to peer reviewer's comments
21 have not changed the overall qualitative and quantitative conclusions.
22 An initial keyword search was based on the Chemical Abstracts Service Registry Number
23 (CASRN) and several common names for methanol. The subsequent search strategy focused on
24 the toxicology and toxicokinetics of methanol, particularly as they pertain to target tissues,
25 effects at low doses, different developmental stages, sensitive subpopulations, and background
26 levels from endogenous and exogenous sources. A more targeted search was completed for the
27 construction and parameterization of a methanol physiologically-based pharmacokinetic (PBPK)
28 model. The focus of this targeted search included existing PBPK models for primary alcohols
29 and pharmacokinetic information for major metabolites and related enzymes. Both the general
30 and targeted searches identified a multitude of studies that used methanol for laboratory
31 procedures. Exclusion terms such as 'extract of methanol' were used in order to cull such
32 irrelevant studies. The literature keyword searches are narrowed down further by manual review.
33 Selection of studies for inclusion in the Toxicological Review was based on consideration of the
34 extent to which the study was informative and relevant to the assessment and general study
35 quality considerations. In general, the relevance of health effect studies was evaluated as outlined
36 in EPA guidance [A Review of the Reference Dose and Reference Concentration Processes (U.S.
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1 EPA, 2002) and Methods for Derivation of Inhalation Reference Concentrations and Application
2 of Inhaled Dosimetry (U.S. EPA, 1994b)]. All animal studies of methanol involving repeated
3 oral, inhalation, or dermal exposure that were considered to be of acceptable quality, whether
4 yielding positive, negative, or null results, were considered in assessing the evidence for health
5 effects associated with chronic exposure to methanol. In addition, animal toxicity studies
6 involving short-term duration and other routes of exposure were evaluated to inform conclusions
7 about health hazards. The references considered and cited in this document, including
8 bibliographic information and abstracts, can be found on the Health and Environmental Research
9 Online (HERO) website.2
10 For other general information about this draft assessment or other questions relating to
11 IRIS, the reader is referred to EPA's IRIS Hotline at (202) 566-1676 (phone), (202) 566-1749
12 (fax), or hotline.iris@epa.gov.
2HERO is a database of scientific studies and other references used to develop EPA's risk assessments aimed at
understanding the health and environmental effects of pollutants and chemicals. It is developed and managed in
EPA's Office of Research and Development (ORD) by the National Center for Environmental Assessment (NCEA).
The database includes more than 750,000 scientific articles from the peer-reviewed literature. New studies are added
continuously to HERO.
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2.CHEMICAL AND PHYSICAL INFORMATION
1 Methanol is also known as methyl alcohol, wood alcohol; Carbinol; Methylol; colonial
2 spirit; Columbian spirit; methyl hydroxide; monohydroxymethane; pyroxylic spirit; wood
3 naphtha; and wood spirit. Some relevant physical and chemical properties are listed in Table 2-1
4 below (HSDB. 2009: IPCS. 1997).
Table 2-1 Relevant physical and chemical properties of methanol.
Property
CASRN:
Empirical formula:
Molecular weight:
Vapor pressure:
Vapor Density:
Specific gravity:
Boiling point:
Melting point:
Water solubility:
Log octanol-water partition coefficient:
Conversion factor (in air):
Value
67-56-1
CH3OH
32.04
160 mniHg at 30 °C
1.11
0.7866 g/mL (25 °C)
64.7 °C
-98 °C
Miscible
-0.82 to -0.68
1 ppm =1.31 mg/m3; 1 mg/m3= 0.763 ppm
5
6
7
8
9
10
11
12
Methanol is a clear, colorless liquid that has an alcoholic odor (TPCS, 1997). Endogenous
levels of methanol are present in the human body as a result of both metabolism3 and dietary
sources such as fruit, fruit juices, vegetables and alcoholic beverages,4 and can be measured in
exhaled breath and body fluids (Turner et al.. 2006: NTP-CERHR. 2004: IPCS. 1997). Dietary
exposure to methanol also occurs through the intake of some food additives. The artificial
sweetener aspartame and the beverage yeast inhibitor dimethyl dicarbonate (DMDC) release
methanol as they are metabolized (Stegink et al., 1989). In general, aspartame exposure does not
contribute significantly to the background body burden of methanol (Butchko et al., 2002). The
Methanol is generated metabolically through enzymatic pathways such as the methyltransferase system (Fisher et
al.. 20001.
4 Fruits and vegetables contain methanol (Cal/EPA. 2012). Further, ripe fruits and vegetables contain natural pectin,
which is degraded to methanol in the body by bacteria present in the colon (SiragusaetaL 1988). Increased levels
of methanol in blood and exhaled breath have also been observed after the consumption of ethanol (Fisher etal.
2000).
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1 United Kingdom (UK) Food Standards Agency has stated that endogenous methanol production
2 ranges from 300 to 600 mg/day (Lindinger et al., 1997) and that diet can contribute up to an
3 additional 1,000 mg/day, principally from fruits and vegetables (COT, 2011). Oral, dermal, or
4 inhalation exposure to methanol in the environment, consumer products, or workplace also
5 occur.
6 Methanol is a high production volume chemical with many commercial uses and it is a
7 basic building block for hundreds of chemical products. Many of its derivatives are used in the
8 construction, housing or automotive industries. Consumer products that contain methanol include
9 varnishes, shellacs, paints, windshield washer fluid, antifreeze, adhesives, de-icers, and Sterno
10 heaters. In 2009, the Methanol Institute (2009b) estimated a global production capacity for
11 methanol of about 35 million metric tons per year (close to 12 billion gallons), a production
12 capacity in the United States (U.S.) of nearly 3.7 million metric tons (1.3 billion gallons), and a
13 total U.S. demand for methanol of over 8 million metric tons. Methanol is among the highest
14 production volume chemicals reported in the U.S. EPA's Toxic Release Inventory (TRI).5 It is
15 among the top chemicals on the 2008 TRI lists of chemicals with the largest total on-site and off-
16 site recycling (6th), energy recovery (2nd) and treatment (1st) (U.S. EPA, 2009a). TRI also
17 reports that approximately 135,000,000 pounds of methanol was released or disposed of in the
18 United States in 2008, making methanol among the top five chemicals on the list entitled "TRI
19 On-site and Off-site Reported Disposed of or Otherwise Released in pounds for facilities in All
20 Industries for Hazardous Air Pollutant Chemicals U.S. 2008" (U.S. EPA. 2009c).
21 While production has switched to other regions of the world, demand for methanol is
22 growing steadily in almost all end uses. A large reason for the increase in demand is its use in the
23 production of biodiesel, a low-sulfur, high-lubricity fuel source. Global demand for biodiesel is
24 forecast to increase by 32% per year, rising from 30 million gallons in 2004, to 150 million
25 gallons by 2008, and to 350 million gallons by 2013 (Methanol Institute, 2009a). Power
26 generation and fuel cells could also be large end users of methanol in the near future (Methanol
27 Institute. 2009b).
5 The information in TRI does not indicate whether (or to what degree) the public has been exposed to toxic
chemicals. Therefore, no conclusions on the potential risks can be made based solely on this information (including
any ranking information). For more detailed information on this subject refer to The Toxics Release Inventory (TRI)
and Factors to Consider When Using TRI Data (U.S. EPA. 2009b).
July 2013 2-2 Draft - Do Not Cite or Quote
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3.TOXICOKINETICS
3.1. Overview
1 As has been noted, methanol occurs naturally in the human body as a product of
2 metabolism and through intake of fruits, vegetables, and alcoholic beverages (Cal/EPA, 2012;
3 Turner et al., 2006; NTP-CERHR, 2004; IPCS, 1997). Table 3-1 summarizes background blood
4 methanol levels in healthy humans which were found to range from 0.25-5.2 mg/L. Formate, a
5 metabolite of methanol, also occurs naturally in the human body (IPCS, 1997). Table 3-1 outlines
6 background levels of formate in human blood. In most cases, methanol and formate blood levels
7 were measured in healthy adults following restriction of methanol-producing foods from the
8 diet.6
9 The absorption, excretion, and metabolism of methanol are well known and have been
10 consistently summarized in reviews such as NTP-CERHR (2004). IPCS (1997). U.S. EPA
11 (1996). Kavet and Nauss (1990). HEI (1987). and Tephly and McMartin (1984). Therefore, the
12 major portion of this toxicokinetics overview is based upon those reviews.
13 Studies conducted in humans and animals demonstrate rapid absorption of methanol by
14 inhalation, oral, and dermal routes of exposure. Table 3-2 outlines increases in human blood
15 methanol levels following various exposure scenarios. Blood levels of methanol following
16 various exposure conditions have also been measured in monkeys, mice, and rats, and are
17 summarized in Tables 3-3, 3-4, and 3-5, respectively. Once absorbed, methanol pharmacokinetic
18 (PK) data and physiologically based pharmacokinetic (PBPK) model predictions indicate rapid
19 distribution to all organs and tissues according to water content, as an aqueous-soluble alcohol.
20 Tissue:blood concentration ratios for methanol are predicted to be similar through different
21 exposure routes, though the kinetics will vary depending on exposure route and timing (e.g.,
22 bolus oral exposure versus longer-term inhalation). Because smaller species generally have faster
23 respiration rates relative to body weight than larger species, they are predicted to have a higher
24 rate of increase of methanol concentrations in the body when exposed to the same concentration
25 in air.
6 Background levels among people who are on normal/non-restricted diets may be higher than those on restricted
diets.
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Table 3-1 Background blood methanol and formate levels in human studies.
Description of human subjects
12 adults who drank no alcohol for
24 hr
12 adults who drank no alcohol for
24 hr
12 males on restricted diet (no
methanol-containing or methanol-
producing foods) for 12 hr
4 adult males who fasted for 8 hr, drank
no alcohol for 24 hr, and took in no
fruits, vegetables, or juices for 18 hr
8 adults who had no fruit, alcohol or
drugs for 48 hr
3 males who ate a breakfast with no
aspartame-containing cereals and no
juice
5 males who ate a breakfast with no
aspartame-containing cereals and no
juice (second experiment)
22 adults on restricted diet (no
methanol-containing or methanol-
producing foods) for 24 hr
35 adults who drank no alcohol for
1 week, fasted 4 hours
12 adults fasted 5 hours
30 fasted adults
24 fasted infants
30 adults. No dietary restrictions. Blood
levels were estimated from
concentrations in breath.
18 males, fasted 3 hr, no other dietary
restrictions
Methanol (mg/L)
mean ± SDa
(Range)
1.7 ±0.9
(0.4-4.7)
1.8 ±0.7
(No range data)
0.570 ±0.305
(0.25-1.4)
1.75 ±0.65
(1.2-2.6)
No mean data
(0.3-2.4)
1.82 ± 1.21
(0.57-3.57)
1.93 ±0.93
(0.54-3.15)
1.8 ±2.6
(No range data)
0.64 ±0.45
(No range data)
1.1
(0.4-2.2)
<4
(No range data)
<3.5
(No range data)
1.25±0.29a
(0.45-1.7)
2.62 ± 1.33
(0.7-5.2)
Formate (mg/L)
mean ± SD
(Range)
No data
No data
3.8±1.1
(2.2-6.6)
No data
No data
9.08 ±1.26
(7.31-10.57)
8.78 ±1.82
(5.36-10.83)
11.2±9.1
(No range data)
No data
No data
19.1
(No range data)
No data
No data
No data
Reference
Batterman and
Franzblau (1997)
Batterman et al. (1998)
Cook et al. (1991)
Davoli et al. (1986)
Ernstgard et al. (2005)
Lee et al. (1992)
Lee et al. (1992)
Osterloh et al. (1996):
Chuwers et al. (1995)
Sarkola and Eriksson
(2001)
Schmutte et al. (1988)
Stegink et al. (1981)
Stegink et al. (1983)
Turner et al.(2006)
Woo et al. (2005)
Arithmetic mean and standard deviation calculated from mean values listed in Table 1 of Turner et al. (2006).
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Table 3-2 Human blood methanol and formate levels following methanol exposure.
Human subjects; Exposure
type of sample Exposure duration or
collected a'b route method
5 adults
-, j i. ^ i 1 dose in
7 adults Oral
water
Fasted 5 hours
Males; post T . , ,. -- •
r , Inhalation 75 nun
exposure samples
Males and females
with exercise; post Inhalation 2 hr
exposure samples
Males and females;
post exposure Inhalation 4 hr
samples
Males without
exercise; post Inhalation 6 hr
exposure samples
Males with
exercise; post Inhalation 6 hr
exposure samples
Females; post T , , . . „ ,
^ , Inhalation 8 hr
exposure samples
Methanol
exposure
concentration
7 mg/kg bw
12.5mg/kgbw
Oppm
191 ppm
Oppm
100 ppm
200 ppm
Oppm
200 ppm
Oppm
200 ppm
Oppm
200 ppm
Oppm
800 ppm
Blood
Blood methanol formate
mean mean
(mg/L) (mg/L) Reference
9.04
0.570
1.881
0.64
3.72
7.82
1.8
6.5
1.82
6.97
1.93
8.13
1.8
30.7
, T , , Schmutte et al.
No data Q988)
3-8 Cooketal.
3.6 (199D
, T , ^ Ernstgard et
N°data al.(25Q5)
Osterloh et al.
14.3 (1996)
9.08
8-70 Lee et al.
8.78 (1992)
9.52
XT , . Battermanet
No data al(m§)
aUnless otherwise specified, it is assumed that whole blood was used for measurements.
Information about dietary restrictions is included in Table 3-1.
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Table 3-3 Monkey blood methanol and formate levels following methanol exposure.
Strain-sex
Monkey; cynomolgus;
female; mean blood
methanol and range of
plasma formate at 30 min
post daily exposure during
premating, mating, and
pregnancy
Monkey; cynomolgus;
female; Lung only
inhalation of anesthetized
monkeys post exposure a
Monkey; Rhesus male;
post exposure blood level
Exposure Exposure
route duration
2.5 hr/day,
7days/wk during
TII.- premating,
Inhalation v .. 6'
mating, and
gestation
(348 days)
Inhalation 2 hr
Inhalation 6 hr
Methanol
exposure
concentration
Oppm
200 ppm
600 ppm
1,800 ppm
10 ppm
45 ppm
200 ppm
900 ppm
900 ppm - FD
200 ppm
1,200 ppm
2,000 ppm
Blood
methanol
mean
(mg/L)
2.4
5
11
35
0.021
0.096
0.67
3.4
6.8
3.9
37.6
64.4
Blood
formate
mean or
range
(mg/L)
8.7
8.7
8.7
10
0.0032
0.012
0.11
0.13
0.44
5.4-13.2
at all doses
Reference
Burbacher
etal.
(20Q4a;
1999a)
Dorman et
al. (1994)
Horton et al.
(1992)
FD=folate deficient
aMethanol and formate blood levels obtained from radiolabeled methanol and do not include background levels of methanol or
formate.
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Table 3-4 Mouse blood methanol and formate levels following methanol exposure.
Species/strain/sex
Mouse;CD-l;female; peak
concentration (Cmax)
Mouse;CD-l;female; peak
concentration (Cmax)
Mouse;CD-l;female; post
exposure plasma methanol
and peak formate level
Mouse;CD-l;female; post
exposure blood methanol
level
Mouse;CD-l;female; mean
post exposure plasma
methanol level
Mouse;CD-l;female;
plasma level 1 hr post
dosing
Mouse;CD-l;female; peak
plasma level
Methanol
Exposure Exposure exposure
route duration concentration
lOOmg/kgbw
Injection Gmg 500mg/kgbw
2,500 mg/kgbw
Oral GDIS 2,500 mg/kgbw
10,000 ppm
T , , . 6 hr 10,000 ppm
Inhalation QnGD8 ^^
15,000 ppm
2,500 ppm
5,000 ppm
Inhalation 8 hi
10,000 ppm
15,000 ppm
0
1,000 ppm
2,000 ppm
T , , ,. 7 hr/day on „ „ „„
Inhalation rnfi pni^ 5,000 ppm
7,500 ppm
10,000 ppm
15,000 ppm
°ral~ GD6-GD15 4,000 mg/kgbw
Gavage 6 6
1,500 mg/kgbw
Gavage GD8 1,500 mg/kgbw
(+ 4-MP)
Blood
methanol
mean
(mg/L)
252
869
3,521
3,205
2,080
2,400
7,140
1,883
3,580
6,028
11,165
1.6
97
537
1,650
3,178
4,204
7,330
3,856
1,610
1,450
Blood
formate
mean
(mg/L)
No data
No data
28.5
23
34.5
No data
No data
No data
35
43
Reference
Ward et al.
(1997)
Ward et al.
(1997)
Dorman et al.
(1995)
Pollack and
Brouwer
(1996): Perkins
et al. (1995a)
Rogers et al.
(1993b)
(1995)
4-MP=4-methylpyrazole (fomepizole)
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Table 3-5 Rat blood methanol and formate levels following methanol exposure.
Species; strain/sex: type Exposure
of sample collected route
Rat; Sprague-Dawley;
female; post exposure T , , . .
ui j it, 11 i Inhalation
blood methanol level on
3 days
Rat; Sprague-Dawley;
female; post exposure Inhalation
blood methanol level
Rat; LongEvans; female;
post exposure plasma level Inhalation
onGD7-GD12
Rat; LongEvans; female; 1
hr post exposure blood Inhalation
level
Rat; Long-Evans; male
and female; Ihrpost T . , ,.
, ' , , , . Inhalation
exposure blood level in
pups
Rat/Fischer-344 male; post T , , ,.
, , , , ' Inhalation
exposure blood level
Rat; Long-Evans; male; T . , ,.
' , ' Inhalation
post- exposure serum level
Rat/Fischer-344 male;
25 min post exposure
blood level for 4-wk T , , ^.
, ,,„ . . Inhalation
animals; —250 mm post
exposure for 104-wk
animals
Rat/Fischer-344 female;
25 min post exposure
blood level for 4-wk T , , ..
, ,,„ . . Inhalation
animals; —250 mm post
exposure for 104-wk
animals
Exposure
duration
7 hr/day for
19 days
8hr
7 hr/day on
GD7-GD19
6 hr/day on
GD6-
PND21
6 hr/dciv on
PNDl-
PND21
6hr
6hr
19.5 hr/day
for 4/104 wk
19 hr/day for
4/104 wk
Methanol
exposure
concentration
5,000 ppm
' rr
10,000 ppm
20,000 ppm
1,000 ppm
5,000 ppm
10,000 ppm
15,000 ppm
20,000 ppm
Oppm
15,000 ppm
4,500 ppm
4,500 ppm
200 ppm
1,200 ppm
2,000 ppm
200 ppm
5,000 ppm
10,000 ppm
Oppm
10 ppm
100 ppm
1,000 ppm
Oppm
10 ppm
100 ppm
1,000 ppm
Blood
methanol
mean or
range
(mg/L)
1,000-2,170
1,840-2,240
5,250-8,650
83
1,047
1,656
2,667
3,916
1.8-2.7
3,169-3,826
555
1,260
3.1
26.6
79.7
7.4
680-873
1,468
4.01/3.78
1.56/3.32
3.84/3.32
53.59/12.08
13.39/3.60
6.73/3.70
4.34/4.32
88.33/8.50
Blood
formate
mean or
range
(mg/L)
No data
No data
No data
No data
No data
5.4-13.2 at
all doses
No data
No data
No data
Reference
Nelson et al.
(19851
Pollack and
Brouwer
(1996);
Perkins et al.
(1995a)
Stanton et al.
(19951
• Weiss et al.
(19961
Horton et al.
(1992)
Cooper et al.
(19921
NEDO (1985b)
NEDO (1985b)
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Species; strain/sex: type Exposure
of sample collected route
Rat; Long-Evans; male; T , , . .
ui j f \ i i Inhalation
peak blood formate level
Rat; Sprague-Dawley; T . ..
,, ' , . .. Injection
female ;peak concentration .
(Cmax) ^'Y'^
Rat;Sprague-Dawley; T . ..
f i i i\- Injection
female ;peak concentration ,. ,
(Cmax)
Rat; Long-Evans; male; „ ,
peak blood methanol and
Ł t gavage
formate 6 6
Methanol
Exposure exposure
duration concentration
0 ppm FS
OppmFR
1,200 ppm-FS
6 hr
1,200 ppm-FR
2,000 ppm-FS
2,000 ppm-FR
100 mg/kg bw
GD14
500 mg/kg bw
100 mg/kg bw
GD20
500 mg/kg bw
2,000 mg/kg bw
FS
2,000 mg/kg bw
FR
3, 000 mg/kg bw-
FS
c. , , 3, 000 mg/kg bw
Single dose ' 6 6
3,500 mg/kg bw-
FS
3,500 mg/kg bw-
FP
3,500 mg/kg bw-
FR
Blood
methanol
mean or
range
(mg/L)
No data
123.7
612.9
149.0
663.6
No data
4,800
4,800
4,800
Blood
formate
mean or
range
(mg/L) Reference
8.3
10.1
8.3 Lee et al.
46.0 (1994)
8.3
83.0
XT , . Wardetal.
N° data (1997)
XT , . Wardetal.
N° data (1997)
9.2
538
9.2
Leeetal.
718 (19941
9.2
38.2
860
FS = Folate sufficient; FR = Folate reduced; FP = Folate paired
1 At doses that do not saturate metabolic pathways, a small percentage of methanol is
2 excreted directly in urine. Because of the high blood:air partition coefficient for methanol and
3 rapid metabolism in all species studied, the bulk of clearance occurs by metabolism, though
4 exhalation and urinary clearance become more significant when doses or exposures are
5 sufficiently high to saturate metabolism (subsequently in this document, "clearance" refers to
6 elimination by all routes, including metabolism, as indicated by the decline in methanol blood
7 concentrations). Metabolic saturation and the corresponding clearance shift have not been
8 observed in humans and nonhuman primates because doses used were limited to the linear range,
9 but the enzymes involved in primate metabolism are also saturable.
10 The primary route of methanol elimination in mammals is through a series of oxidation
11 reactions that form formaldehyde, formate, and carbon dioxide (Figure 3-1). As noted in
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1 Figure 3-1, methanol is converted to formaldehyde by alcohol dehydrogenase-1 (ADH1) in
2 primates and by catalase (CAT) and ADH1 in rodents. Although the first step of metabolism
3 occurs through different pathways in rodents and nonhuman primates, Kavet and Nauss (1990)
4 report that the reaction proceeds at similar rates (Vmax =30 and 48 mg/hr/kg in rats and
5 nonhuman primates, respectively). In addition to enzymatic metabolism, methanol can react with
6 hydroxyl radicals to spontaneously yield formaldehyde (Harris et al., 2003). Mannering et al.
7 (1969) also reported a similar rate of methanol metabolism in rats and monkeys, with 10 and
8 14% of a 1 g/kg dose oxidized in 4 hours, respectively; the rate of oxidation by mice was about
9 twice as fast, 25% in 4 hours. In an HEI study by Pollack and Brouwer (1996), the metabolism of
10 methanol was 2 times as fast in mice versus rats, with a Vmax for elimination of 117 and
11 60.7 mg/hr/kg, respectively. Despite the faster elimination rate of methanol in mice versus rats,
12 mice consistently exhibited higher blood methanol levels than rats when inhaling equivalent
13 methanol concentrations (See Tables 3-4 and 3-5). Possible explanations for the higher methanol
14 accumulation in mice include faster respiration (inhalation rate/body weight) and increased
15 fraction of absorption by the mouse (Perkins et al., 1995a). Sweeting et al. (2010) examined
16 methanol dosimetry in CD-I mice, New Zealand white (NZW) rabbits, and cynomolgus
17 monkeys, and found that peak plasma concentrations are not significantly different, but clearance
18 in rabbits is approximately half that of mice following a single 0.5 or 2 g/kg i.p. (intraperitoneal)
19 injection. This suggests that rabbit clearance is similar to that in rats and monkeys, since
20 Mannering et al. (1969) found that rat and monkey clearance rates are also about half that in
21 mice. Sweeting et al. (2010) did not report the clearance rates from monkeys, but the 6-hour
22 AUC in monkeys was similar to that in rabbits. Because smaller species generally have faster
23 breathing rates than larger species, humans would be expected to absorb methanol via inhalation
24 more slowly than rats or mice inhaling equivalent concentrations. If humans eliminate methanol
25 at a comparable rate to rats and mice, then humans would also be expected to accumulate less
26 methanol than those smaller species. However, if humans eliminate methanol more slowly than
27 rats and mice, such that the ratio of absorption to elimination stays the same, then humans would
28 be expected to accumulate methanol to the same internal concentration but to take longer to
29 reach that concentration.
30 In all species, formaldehyde is rapidly converted to formate, with the half-life for
31 formaldehyde being ~1 minute. Formaldehyde is oxidized to formate by two metabolic pathways
32 (Teng et al., 2001). The first pathway (not shown in Figure 3-1) involves conversion of free
33 formaldehyde to formate by the so-called low-affinity pathway (affinity = l/Km = 0.002/|jM)
34 mitochondrial aldehyde dehydrogenase-2 (ALDH2). The second pathway (Figure 3-1) involves a
35 two-enzyme system that converts glutathione-conjugated formaldehyde
36 (^-hydroxymethylglutathione [HMGSH]) to the intermediate ^-formylglutathione, which is
July 2013 3-8 Draft - Do Not Cite or Quote
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1 subsequently metabolized to formate and glutathione (GSH) by S-formylglutathione hydrolase.7
2 The first enzyme in this pathway, formaldehyde dehydrogenase-3 (ADH3), is rate limiting, and
3 the affinity of HMGSH for ADH3 (affinity = l/Km = 0.15/nM) is about a 100-fold higher than
4 that of free formaldehyde for ALDH2. In addition to the requirement of GSH for ADH3 activity,
5 oxidation by ADH3 is (NAD+ [nicotinamide adenine dinucleotide])-dependent. Under normal
6 physiological conditions NAD+ levels are about two orders of magnitude higher than NADH,
7 and intracellular GSH levels (mM range) are often high enough to rapidly scavenge
8 formaldehyde (Svensson et al., 1999; Meister and Anderson, 1983): thus, the oxidation of
9 HMGSH is favorable. In addition, genetic ablation of ADH3 results in increased formaldehyde
10 toxicity (Deltour et al., 1999). These data indicate that ADH3 is likely to be the predominant
11 enzyme responsible for formaldehyde oxidation at physiologically relevant concentrations,
12 whereas ALDHs likely contribute to formaldehyde elimination at higher concentrations (Dicker
13 and Cedebaum. 1986).
Primates
K
Alcohol dehvdrogenase \.
(ADH1) /
V
K
l-oi rnnldi'liwlr dehvdrogenase \.
(ADH3) /
^
'\
S-formylfjIutalhionc hydrolase
V/
K
1 \
Folatc-dcpcndent pathway \,
(see Figure 3-2) /
v
CHJOH
(Mcthanol)
4
HCHO
(Formaldehyde)
|( + GSH)
HMGSH
(hydroxvmethvI-GSH)
I
(S-formyi glutathione)
> 4( - GSH)
HCOO (Formate)
1 <
-
CO2 (Carbon dioxide)
Rodents
A
/ Catalase (CAT)
\ andADHl
^
A
jf Formaldc'hvde dehvdrogenase
\ (ADH3)
^
{ S-formvlijlutathiune hvdrolase
^
y^ CAT-peroxide and
I-ohitc-depcndenl pathway
N
Source: IPCS (1997).
Figure 3-1 Methanol metabolism and key metabolic enzymes in primates and rodents.
7 Other enzymatic pathways for the oxidation of formaldehyde have been identified in other organisms, but this is
the pathway that is recognized as being present in humans (Caspi et al.. 2006: http://metacvc.org).
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1 Rodents convert formate to carbon dioxide (€62) through a folate-dependent enzyme
2 system and a CAT-peroxide system (Dikalova et al., 2001). Formate can undergo adenosine
3 triphosphate- (ATP-) dependent addition to tetrahydrofolate (THF), which can carry either one or
4 two one-carbon groups. Formate can conjugate with THF to form jV10-formyl-THF and its isomer
5 A^-formyl-THF, both of which can be converted to TV5, jV70-methenyl-THF and subsequently to
6 other derivatives that are ultimately incorporated into DNA and proteins via biosynthetic
7 pathways (Figure 3-2). There is also evidence that formate generates CO2" radicals, and can be
8 metabolized to CO2 via CAT and via the oxidation of jV10-formyl-THF (Dikalova et al.. 2001).
Cytoplasm
Mitochondria
10-formylTHF
/
"
methenylTHF
^^*~* formates
THF
\/^~- senne ~
MmWMT
tnethyleneTHF ^vine ~
AfTHFDI /y
J^/f FDH
^- formate-^^.^' / i
// XCQ methenylTHF
THF
=iss glycine ' methy
eneTHF 1
I
1 MTHfR
5-methylTHF
MS J^-~*~~~~--^
homocysteine
*
AdoHyc
^- AdoMet
=> dTMP
N
Vlethionine
J
*m
Source: Montserrat et al. (2006).
Figure 3-2 Folate-dependent formate metabolism. Tetrahydrofolate (THF)-mediated one
carbon metabolism is required for the synthesis of purines, thymidylate, and
methionine.
9 Unlike rodents, formate metabolism in primates occurs solely through a folate-dependent
10 pathway. Black et al. (1985) reported that hepatic THF levels in monkeys are 60% of that in rats,
11 and that primates are far less efficient in clearing formate than are rats and dogs. Studies of
12 human subjects involving [14C]formate suggest that -80% is exhaled as 14CO2, 2-7% is excreted
13 in the urine, and -10% undergoes metabolic incorporation (Hanzlik et al., 2005, and references
14 therein ). Sweeting et al. (2010) have reported that formic acid accumulation in primates within
15 6 hours of a 2 g/kg i.p. exposure to methanol was 5-fold and 43-fold higher than in rabbits and
16 mice, respectively. Mice deficient in formyl-THF dehydrogenase exhibit no change in LDso (via
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1 intraperitoneal [i.p.]) for methanol or in oxidation of high doses of formate. Thus it has been
2 suggested that rodents efficiently clear formate via high capacity folate-dependent pathways,
3 peroxidation by CAT, and by an unknown third pathway; conversely, primates do not appear to
4 exhibit such capacity and are more sensitive to metabolic acidosis following methanol poisoning
5 (Cook etal.. 2001).
6 Blood methanol and formate levels measured in humans under various exposure
7 scenarios are reported in Table 3-2. As noted in Table 3-2, 75-minute to 6-hour exposures of
8 healthy humans to 200 ppm methanol vapors, the American Council of Governmental Industrial
9 Hygienists (ACGIH) threshold limit value (TLV) for occupational exposure (ACGIH. 2000).
10 results in increased levels of blood methanol but not formate. A limited number of monitoring
11 studies indicate that levels of methanol in outdoor air are orders of magnitude lower than the
12 TLV (TPCS, 1997). Table 3-3 indicates that exposure of monkeys to 600 ppm methanol vapors
13 for 2.5 hours increased blood methanol but not blood formate levels. Normal dietary exposure to
14 aspartame, which releases 10% methanol during metabolism, is unlikely to significantly increase
15 blood methanol or formate levels (Butchko et al., 2002). Exposure to high concentrations of
16 aspartame is unlikely to increase blood formate levels; no increase in blood formate levels were
17 observed in adults ingesting "abusive doses" (100-200 mg/kg) of aspartame (Stegink et al.,
18 1981). Kerns et al. (2002) studied the kinetics of formate in 11 methanol-poisoned patients
19 (mean initial methanol level of 57.2 mmol/L or 1.83 g/L) and determined an elimination half-life
20 of 3.4 hours for formate. Kavet and Nauss (1990) estimated that a methanol dose of 11 mM or
21 210 mg/kg is needed to saturate folate-dependent metabolic pathways in humans. There are no
22 data on blood methanol and formate levels following methanol exposure of humans with reduced
23 ADH activity or marginal folate tissue levels, a possible concern regarding sensitive populations.
24 As discussed in greater detail in Section 3.2, a limited study in folate-deficient monkeys
25 demonstrated no increase in blood formate levels following exposure to 900 ppm methanol
26 vapors for 2 hours. In conclusion, limited available data suggest that typical occupational,
27 environmental, and dietary exposures are likely to increase baseline blood methanol but not
28 formate levels in most humans.
3.2. Key Studies
29 Toxicokinetic and metabolism studies (Burbacher et al., 2004b; Burbacher et al., 1999b;
30 Medinsky et al., 1997; Pollack and Brouwer, 1996; Dorman et al., 1994) provide key information
31 on interspecies differences, methanol metabolism during gestation, metabolism in the nonhuman
32 primate, and the impact of folate deficiency on the accumulation of formate.
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1 As part of an effort to develop a physiologically based toxicokinetic model for methanol
2 distribution in pregnancy, Pollack and Brouwer (1996) conducted a large study that compared
3 toxicokinetic differences in pregnant and nonpregnant (NP) rats and mice. Methanol disposition8
4 was studied in Sprague-Dawley rats and CD-I mice that were exposed to 100-2,500 mg/kg of
5 body weight pesticide-grade methanol in saline by i.v. or oral routes. Exposures were conducted
6 in NP rats and mice, pregnant rats on gestation days (GD) GD7, GDI4, and GD20, and pregnant
7 mice on GD9 and GDIS. Disposition was also studied in pregnant rats and mice exposed to
8 1,000-20,000 ppm methanol vapors for 8 hours. Three to five animals were examined at each
9 dose and exposure condition.
10 • Based on the fit of various kinetic models to methanol measurements taken from all
11 routes of exposure, the authors concluded that high exposure conditions resulted in
12 nonlinear disposition of methanol in mice and rats.9 Both linear and nonlinear
13 pathways were observed with the relative contribution of each pathway dependent on
14 concentration. At oral doses of 100-500 mg/kg of body weight, methanol was
15 metabolized to formaldehyde and then formic acid through the saturable nonlinear
16 pathway. A parallel, linear route characteristic of passive-diffusion accounted for an
17 increased fraction of total elimination at higher concentrations. Nearly 90% of
18 methanol elimination occurred through the linear route at the highest oral dose of
19 2,500 mg/kg of body weight.
20 • Oral exposure resulted in rapid and essentially complete absorption of methanol. No
21 significant change in blood area under the curve (AUC) methanol was seen between
22 NP and GD7, GDI4 and GD20 rats exposed to single oral gavage doses of 100 and
23 2,500 mg/kg, nor between NP and GD9 and GDIS mice at 2,500 mg/kg. The data as a
24 whole suggested that the distribution of orally and i.v. administered methanol was
25 similar in rats versus mice and in pregnant rodents versus NP rodents with the
26 following exceptions:
27 • There was a statistically significant increase in the ratio of apparent volume of
28 distribution (Vd) to fractional bioavailability (F) by -20% (while F decreased but not
29 significantly), between NP and GD20 rats exposed to 100 mg/kg orally. However,
30 this trend was not seen in rats or mice exposed to 2,500 mg/kg, and the result in rats
31 at 100 mg/kg could well be a statistical artifact since both Vd and F were being
32 estimated from the same data, making the model effectively over-parameterized.
8 Methanol concentrations in whole blood and urine were determined by gas chromatography with flame ionization
detection (Pollack and Kawagoe. 19911.
9 A model incorporating parallel linear and nonlinear routes of methanol clearance was required to fit the data from
the highest exposure groups.
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1 • There were statistically significant decreases in the fraction of methanol absorbed by
2 the fast process (resulting in a slower rise to peak blood concentrations, though the
3 peak is unchanged) and in the Vmax for metabolic elimination between NP and GDIS
4 mice. No such differences were observed between NP and GD9 mice.
5 • The authors estimated a twofold higher Vmax for methanol elimination in mice versus
6 rats following oral administration of 2,500 mg/kg methanol, suggesting that similar
7 oral doses would result in lower methanol concentrations in the mouse versus rat.
8 • Methanol penetration from maternal blood to the fetal compartment was examined in
9 GD20 rats by microdialysis.10 A plot of the amniotic concentration versus maternal
10 blood concentration (calculated from digitization of Figure 17 of Pollack and
11 Brouwer (1996) report) is shown in Figure 3-3. The ratio is slightly less than 1:1
12 (dashed line in plot) and appears to be reduced with increasing methanol
13 concentrations, possibly due to decreased blood flow to the fetal compartment.
14 Nevertheless, this is a very minor departure from linearity, consistent with a substrate
15 such as methanol that penetrates cellular membranes readily and distributes
16 throughout total body water.
10 Microdialysis was conducted by exposing the uterus (midline incision), selecting a single fetus in the middle of
the uterine horn and inserting a microdialysis probe through a small puncture in the uterine wall proximal to the
head of the fetus.
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5000
D)
4000
2 3000
'c
o>
c 2000H
o
o
'I 1000 H
0
0
= -4E-05)? + 1.0782x
R2 = 0.9919
1000 2000 3000 4000 5000
Maternalblood.concent ration(rng/L)
Source: Pollack and Brouwer (1996).
Note: Data extracted from Figure 17 by digitization, and amniotic concentration obtains as ("Fetal Amniotic Fluid/Maternal
Blood Methanol") x ("Maternal Methanol").
Figure 3-3 Plot of fetal (amniotic) versus maternal methanol concentrations in GD20 rats.
1 Inhalation exposure resulted in less absorption in both rats and mice as concentrations of
2 methanol vapors increased, which was hypothesized to be due to decreased breathing rate and
3 decreased absorption efficiency from the upper respiratory tract.n Based on blood methanol
4 concentrations measured following 8-hour inhalation exposures to concentrations ranging from
5 1,000-20,000 ppm, the study authors (Pollack and Brouwer, 1996) concluded that, across this
6 range, methanol accumulation in the mouse occurred at a two- to threefold greater rate compared
7 to the rat. They speculated that faster respiration rate and more complete absorption in the nasal
8 cavity of mice may explain the higher methanol accumulation and greater sensitivity to certain
9 developmental toxicity endpoints (see Section 4.3.2).
10 The Pollack and Brouwer (1996) study was useful for comparing effects in pregnant and
11 NP rodents exposed to high doses, but the implication of these results for humans exposed to
12 ambient levels of methanol is not clear (NTP-CERHR. 2004).
1: Exposed mice spent some exposure time in an active state, characterized by a higher ventilation rate, and the
remaining time in an inactive state, with lower (~1A of active) ventilation. The inactive ventilation rate was
unchanged by methanol exposure, but the active ventilation showed a statistically significant methanol-
concentration-related decline. There was also some decline in the fraction of time spent in the active state, but this
was not statistically significant.
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1 Sweeting et al. (2011; 2010) studied methanol and formic acid pharmacokinetics in male
2 C57BL/6 mice, male C3H mice, male CD-I mice, male NZW rabbits and male cynomolgous
3 monkeys (Macacafascicularis) following a 0.5 or 2 g/kg i.p. exposure to methanol. Blood
4 samples were taken over the entire methanol elimination period for rabbits (48 hours) and CD-I
5 mice (12 hours for 0.5 g/kg exposure; 24 hours for 2 g/kg exposure), over a 12-hour exposure
6 window for the C57BL/6 and C3H mice and a 6-hour post exposure window for monkeys.
7 Following the 2 g/kg dose, methanol blood levels exhibited saturated elimination kinetics in all
8 three species, and peak methanol concentrations were similar (68, 87 and 79 ± 10 mmol/L in
9 C57BL/6, C3H and CD-I mice, respectively; 114 ± 7 mmol/L in rabbits and 94 ± 14 mmol/L in
10 monkeys), though the peak concentrations in C57BL/6 (p < 0.01) and CD-I (p < 0.05) mice were
11 significantly lower than rabbits. Methanol clearance rates were 2.5-fold higher in CD-I mice
12 than in rabbits after the 2 g/kg exposure, and 2-fold higher after the 0.5 g/kg exposure. When
13 measured over the entire elimination period, plasma methanol AUCs in the rabbits were 175 ± 27
14 after a 0.5 g/kg dose and 1,893 ± 345 mmol-hr/L after a 2 g/kg dose. Comparable plasma
15 methanol AUCs in CD-I mice were more than 2-fold lower (71 ± 9 after a 0.5 g/kg dose, and
16 697 ± 50 mmol-hr/L after a 2 g/kg dose). At 12-hours (after a 2 g/kg dose), the plasma methanol
17 AUC values for C57BL/6, C3H and CD-I mice were 465 ± 14, 550 ± 30 and 640 ± 33
18 mmol-hr/L, respectively, and rabbits had an AUC value of 969 ± 77 mmol-hr/L. The elimination
19 period for plasma formic acid AUCs in the rabbits were 3.02 ±1.3 mmol-hr/L after a 0.5 g/kg
20 dose, and 10.6 ±1.4 mmol-hr/L after a 2 g/kg dose. In comparison, plasma formic acid AUCs in
21 CD-I mice were nearly 6-fold lower at 0.5 g/kg (71 ± 9 mmol-hr/L) and more than 3-fold lower
22 at 2 g/kg (697 ± 50 mmol-hr/L). Twelve hours after a 2 g/kg (i.p.) dose, the plasma formic acid
23 AUC values for C57BL/6, C3H, and CD-I mice were 2.1 ± 0.3, 1.6 ± 0.2, and 1.9 ± 0.2
24 mmol-hr/L, respectively, and rabbits had a formic acid AUC value of 3.0 ± 0.3 mmol-hr/L. All of
25 the 12-hour formic acid AUCs for the mice were significantly lower (p < 0.05) than the rabbit,
26 but none of the mouse strains differed from each other (p < 0.05). Formic acid accumulation at
27 6-hours post-exposure in monkeys (7.75 ±3.5 mmol-hr/L) was 5-fold and 43-fold higher than in
28 rabbits (1.5 ± 0.2 mmol-hr/L) and CD-I mice (0.15 ± 0.04 mmol-hr/L), respectively.
29 Burbacher et al. (2004a; 1999a) examined toxicokinetics in Macaca fascicularis monkeys
30 prior to and during pregnancy. As part of the report (Reproductive and Offspring Developmental
31 Effects Following Maternal Inhalation Exposure to Methanol in Nonhuman Primates [which
32 includes the commentary of the Institute's Health Review Committee]), the HEI review
33 committee (Burbacher et al., 1999a) noted that this was a quality study using a relevant species.
34 The study objectives were to assess the effects of repeated methanol exposure on disposition
35 kinetics, determine whether repeated methanol exposures result in formate accumulation, and
36 examine the effects of pregnancy on methanol disposition and metabolism. Reproductive,
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1 developmental, and neurological toxicity associated with this study were also examined and are
2 discussed in Sections 4.3.2 and 4.4.2. In a 2-cohort design, 48 adult females
3 (6 animals/dose/group/cohort) were exposed to 0, 200, 600, or 1,800 ppm methanol vapors
4 (99.9% purity) for 2.5 hours/day, 7 days/week for 4 months prior to breeding and during the
5 entire breeding and gestation periods. Six-hour methanol clearance studies were conducted prior
6 to and during pregnancy. Burbacher et al. (2004a; 1999a) reported that:
7 • At no point during pregnancy was there a significant change in baseline methanol
8 blood levels, which ranged from 2.2-2.4 mg/L throughout (Table 3-6).
9 • PK studies were performed initially (Study 1), after 90 days of pre-exposure and prior
10 to mating (Study 2), between GD66 and GD72 (Study 3), and again between GD126
11 and GDI32 (Study 4). These studies were analyzed using classical PK (one-
12 compartment) models.
13 • Disproportionate mean, dose-normalized, and net blood methanol dose-time profiles
14 in the 600 and 1,800 ppm groups suggested saturation of the metabolism-dependent
15 pathway. Data from the 600 ppm group fit a linear model, while data from the
16 1,800 ppm group fit a Michaelis-Menten model.
17 • Methanol elimination rates modestly increased between Study 1 and Study 2 (90 days
18 prior to mating). This change was attributed to enzyme induction from the subchronic
19 exposure.
20 • Blood methanol levels were measured every 2 weeks throughout pregnancy, and
21 while there was measurement-to-measurement variation, there was no significant
22 change or trend over the course of pregnancy (Table 3-6). An upward trend in
23 elimination half-life appeared to correspond with a downward trend in blood
24 methanol clearance between Studies 2, 3, and 4. However, the changes were not
25 statistically significant and the time-courses for blood methanol concentration
26 (elimination phase) appeared fairly similar.
27 • Significant differences between baseline and plasma formate levels (p = 0.005), and
28 between prebreeding and pregnancy (p = 0.0001) were observed but were not dose
29 dependent (Table 3-7).
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1 • Significant differences in serum folate levels between baseline and prepregnancy
2 (p = 0.02), and between prepregnancy and pregnancy (p = 0.007) were not dose
3 dependent (Table 3-8).
Table 3-6 Plasma methanol concentrations in monkeys.
Exposure Group
Control (n=ll)
200 ppm (n=12)
600ppm(n=ll)
1,800 ppm (n=12)
Mean"
Baseline
2.3 ±0.1
2.2 ±0.1
2.4 ±0.1
2.4 ±0.1
plasma methanol level
Pre-breeding
2.3±0.1
4.7 ±0.1
10.5 ±0.3
35.6 ±1.0
(mg/L) during each
Breeding
2.3 ±0.1
4.8 ±0.1
10.9 ±0.2
35.7 ±0.9
exposure period
Pregnancy1"
2.7 ±0.1
5.5 ±0.2
11.0 ±0.2
35.5 ±0.9
aValues are presented as means ± SE in mg/L.
bw = 9 for control, 200 ppm, and 600 ppm pregnancy groups; n = 10 for 1,800 ppm pregnancy group.
Source: Burbacher et al. (1999a).
Table 3-7 Plasma formate concentrations in monkeys.
Mean" plasma formate level (mg/L) during each exposure period
Exposure Group
Control (n=ll)
200 ppm (n=12)
600 ppm (n= 11)
1,800 ppm (n=12)
Baseline
8.3 ±9.2
7.4 ±0.9
6.9 ±0.5
6.4 ±0.9
Pre-breeding
7.8 ±0.5
8.3 ±0.5
7.8 ±0.5
8.7 ±0.5
Breeding
10.1 ±0.9
9.7 ±0.5
9.2 ±0.5
11 ±0.5
Pregnancy1"
8.3 ± 1.4
7.8 ±0.5
8.7 ± 1.4
10± 1.4
aValues are presented as means ± SE in mg/L; transformed from mM, for consistency.
bn = 9 for control, 200 ppm, and 600 ppm pregnancy groups; n = 10 for 1,800 ppm pregnancy group.
Source: Burbacher et al. Q999a).
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Table 3-8 Serum folate concentrations in monkeys.
Mean" serum folate level (jig/L) during each exposure period
Exposure Group
Control (n=ll)
200ppm(n=12)
600ppm(n=ll)
1,800 ppm(n=12)
Baseline
14.4 ±1.0
11.9±1.3
12.5± 1.4
12.6 ±0.7
Day 70
Pre-pregnancya
14.0 ±1.2
13.2 ±1.6
15.4 ±1.2
14.8 ± 1.2
Day 98
Pre-pregnancya
13.4 ±1.2
12.9 ±1.3
13.4 ±1.0
15. 3 ±1.1
Day 55
Pregnancy"
16.0 ±1.1
15.5 ±1.5
14.8 ±1.1
15.9 ± 1.2
Day 113
Pregnancy1"'0
15.6±1.1
13.4 ±1.3
16.4 ±1.0
15.7 ±1.0
aValues are presented as means ± SE in |ig/L.
bNumber of days exposed to methanol
cn = 9 for control, 200 ppm, and 600 ppm pregnancy groups; n = 10 for 1,800 ppm pregnancy group.
Source: Burbacher et al. (1999a).
1 A series of studies by Medinsky et al. (1997) and Dorman et al. (1994) examined
2 metabolism and pharmacokinetics of [14C]methanol and [14C]formate in normal and folate-
3 deficient cynomolgus, M. fascicularis monkeys that were exposed to [14C]methanol through an
4 endotracheal tube while anesthetized. In the first stage of the study, 4 normal 12-year-old
5 cynomolgus monkeys were each exposed to 10, 45, 200, and 900 ppm [14C]methanol vapors
6 (>98% purity) for 2 hours. Each exposure was separated by at least 2 months. After the first stage
7 of the study was completed, monkeys were given a folate-deficient diet supplemented with 1%
8 succinylsulfathiazole (an antibacterial sulfonamide used to inhibit folic acid biosynthesis from
9 intestinal bacteria) for 6-8 weeks in order to obtain folate concentrations of <3 ng/mL serum and
10 <120 ng/mL erythrocytes. Folate deficiency did not alter hematocrit level, red blood cell count,
11 mean corpuscular volume, or mean corpuscular hemoglobin level. The folate-deficient monkeys
12 were exposed to 900 ppm [14C]methanol for 2 hours. The results of the Medinsky et al. (1997)
13 and Dorman et al. (1994) studies showed:
14 • Dose-dependent changes in toxicokinetics and metabolism did not occur as indicated
15 by a linear relationship between inhaled [14C]methanol concentration and
16 end-of-exposure blood [14C]methanol level, [14C]methanol AUC and total amounts of
17 exhaled [14C]methanol and [14C]carbon dioxide.
18 • Methanol concentration had no effect on elimination half-life (<1 hour) and percent
19 urinary [14C]methanol excretion (<0.01%) at all doses.
20 • Following exposure to 900 ppm methanol, urinary excretion or exhalation of
21 [14C]methanol did not differ significantly between monkeys in the folate sufficient
22 and deficient state. There was no significant [14C]formate accumulation at any dose.
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1 • Peak blood [14C]formate levels were significantly higher in folate-deficient monkeys,
2 but did not exceed endogenous blood levels reported by the authors to be between 0.1
3 and 0.2 mmol/L (4.6-9.2 mg/L).
4 An HEI review committee (Medinsky et al., 1997) noted that absolute values in this study
5 cannot be extrapolated to humans because the use of an endotracheal tube in anesthetized
6 animals results in an exposure scenario that is not relevant to humans. However, the data in this
7 study suggest that a single exposure to methanol (10- 900 ppm for 2 hours) is unlikely to result in
8 a hazardous elevation in formate levels, even in individuals with moderate folate deficiency.
3.3. Human Variability in Methanol Metabolism
9 The ability to metabolize methanol may vary among individuals as a result of genetic,
10 age, and environmental factors. Reviews by Agarwal (2001), Burnell et al.(1989), Bosron and Li
11 (1986), and Pietruszko (1980), discuss genetic polymorphisms for ADH. Class IADH, the
12 primary ADH in human liver, is a hetero- or homodimer composed of randomly associated
13 polypeptide units encoded by three separate gene loci (ADH1 A, ADH1B, and ADH1C).
14 Polymorphisms have been found to occur at the ADH1B (ADH1B*2, ADH1B*3) and ADH1C
15 (ADH1C*2) gene loci; however, no human allelic polymorphism has been found in ADH1 A.
16 The ADH1B*2 phenotype is estimated to occur in -15% of Caucasians of European descent,
17 85% of Asians, and <5% of African Americans. ADH1C* 1 is also highly prevalent in Asians, but
18 has only been examined in a few studies of Chinese and Korean samples (Eng et al., 2007).
19 Fifteen percent of African Americans have the ADH1B*3 phenotype, while it is found in <5% of
20 Caucasian Europeans and Asians. To date, there are two reports of polymorphisms in ADH3
21 (Cichoz-Lach et al., 2007; Hedberg et al., 2001), yet the functional consequence(s) for these
22 polymorphisms remains unclear.
23 Although racial and ethnical differences in the frequency of the occurrence of ADH
24 alleles in different populations have been reported, ADH enzyme kinetics (Vmax and Km) have not
25 been reported for methanol. There is an abundance of information pertaining to the kinetic
26 characteristics of the ADH dimers to metabolize ethanol in vitro. Methanol blood concentrations
27 of 2.62 ± 1.33 mg/L (Table 3-1) in 18 Korean males ( Woo et al., 2005) were considerably higher
28 than the sample U.S. background distribution of 1.36 mg/L and 0.77 mg/L estimated in Section
29 5.3.6. However, the functional and biological significance is not well understood due to the lack
30 of data documenting metabolism and disposition of methanol or ethanol in individuals of known
31 genotype. Thus, while potentially significant, the contribution of ethnic and genetic
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1 polymorphisms of ADH to the interindividual variability in methanol disposition and metabolism
2 cannot be reliably quantified at this time.
3 Because children generally have higher baseline breathing rates and are more active, they
4 may receive higher methanol doses than adults exposed to equivalent concentrations of any air
5 pollutant (NTP-CERHR, 2004). There is evidence that children under 5 years of age have
6 reduced ADH activity. A study by Pikkarainen and Raiha (1967) measured liver ADH activity
7 using ethanol as a substrate and found that 2-month-old fetal livers have -3-4% of adult ADH
8 liver activity. ADH activity in 4 to 5 month old fetuses is -10% of adult activity, and an infant's
9 activity is -20% of adult activity. ADH continues to increase in children with age and reaches a
10 level that is within adult ranges at 5 years of age. Adults were found to have great variation in
11 ADH activity (1,625 to 6,530/g liver wet weight or 2,030 to 5,430 mU/100 mg soluble protein).
12 Smith et al. (1971) also compared liver ADH activity in 56 fetuses (9 to 22 weeks gestation),
13 37 infants (premature to <1 year old), and 129 adults (>20 years old) using ethanol as a substrate.
14 ADH activity was 30% of adult activity in fetuses and 50% of adult activity in infants. There is
15 evidence that some human infants are able to efficiently eliminate methanol at high exposure
16 levels, however, possibly via CAT (Tran et al., 2007).
17 ADH3 exhibits little or no activity toward small alcohols, thus the previous discussion is
18 not relevant to the ontogeny of formaldehyde elimination (clearance). While such data on ADH3
19 activity does not exist, ADH3 mRNA is abundantly expressed in the mouse fetus (Ang et al.,
20 1996) and is detectible in human fetal tissues (third trimester), neonates and children (Hines and
21 Mccarver, 2002: Estonius et al.. 1996).
22 As noted earlier in this section, folate-dependent reactions are important in the
23 metabolism of formate. Individuals who are commonly folate deficient include those who are
24 pregnant or lactating, have gastrointestinal (GI) disorders, have nutritionally inadequate diets, are
25 alcoholics, smoke, have psychiatric disorders, have pernicious anemia, or are taking folic acid
26 antagonist medications such as some antiepileptic drugs (NTP-CERHR, 2004; IPCS, 1997).
27 Groups which are known to have increased incidence of folate deficiencies include Hispanic and
28 African American women, low-income elderly, and mentally ill elderly (NTP-CERHR, 2004).
29 A polymorphism in methylene tetrahydrofolate reductase reduces folate activity and is found in
30 21% of Hispanics in California and 12% of Caucasians in the United States. Genetic variations in
31 folic acid metabolic enzymes and folate receptor activity are theoretical causes of folate
32 deficiencies.
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3.4. Physiologically Based Pharmacokinetic Models
1 In accordance with the needs of this human health assessment, particularly the derivation
2 of human health effect benchmarks from studies of the developmental effects of methanol
3 inhalation exposure in mice (Rogers et al., 1993b), monkeys (Burbacher et al., 2004b: Burbacher
4 et al., 1999b) and rats (NEDO, 1987) models were evaluated for their ability to estimate mouse,
5 monkey and rat internal dose metrics. A human model was developed to extrapolate those
6 internal metrics to inhalation and oral exposure concentrations that would result in the same
7 internal dose in humans (HECs and HEDs). The procedures used for the development,
8 calibration and use of these models are summarized in this section, with further details provided
9 in Appendix B, "Development, Calibration and Application of a Methanol PBPK Model."
3.4.1. Model Requirements for EPA Purposes
3.4.1.1. MOA and Selection of a Dose Metric
10 Dose metrics closely associated with one or more key events that lead to the selected
11 critical effect are preferred for dose-response analyses compared to metrics not clearly
12 correlated. For instance, internal (e.g., blood, target tissue) measures of dose are preferred over
13 external measures of dose (e.g., atmospheric or drinking water concentrations), especially when,
14 as with methanol, blood methanol concentrations increase disproportionally with dose (Rogers et
15 al., 1993b). This is likely due to the saturable metabolism of methanol. In addition, respiratory
16 and GI absorption may vary between and within species. Mode of action (MOA) considerations
17 can also influence whether to model peak concentrations (Cmax) or a time-dependent metric such
18 as area under the curve (AUC), and whether to model the parent compound with or without its
19 metabolites for selection of the most adequate dose metric.
20 As discussed in Section 4.3, developmental effects following methanol exposures have
21 been noted in both rats and mice (Rogers et al., 1993a: Rogers etal., 1993b: NEDO, 1987;
22 Nelson etal., 1985), but are not as evident or clear in primate exposure studies (Burbacher et al.,
23 2004b: Clary, 2003: Andrews et al., 1987). The report of the New Energy Development
24 Organization (NEDO, 1987) of Japan, which investigated developmental effects of methanol in
25 rats, indicated that there is a potential that developing rat brain weight is reduced following
26 maternal and neonatal exposures. These exposures included both in utero and postnatal
27 exposures. The methanol PBPK models developed for this assessment do not explicitly describe
28 these exposure routes. Mathematical modeling efforts have focused on the estimation of human
29 equivalent external exposures that would lead to an increase in maternal blood levels of methanol
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1 or its metabolites presumed to be associated with developmental effects as reported in rats
2 (NEDO, 19871 mice (Rogers et al.. 1993b) and monkeys (Burbacher et al.. 2004b: Burbacher et
3 al., 1999b). PBPK models were developed for all species, but because measured internal blood
4 methanol levels suitable for use as estimates of peak concentrations (Cmax) are provided by
5 Rogers et al. (1993b), a mouse PBPK model is not used or discussed in this toxicological review.
6 However, limited discussion of the mouse models is included, as they are useful in evaluating
7 model structure.
8 In a recent review of the reproductive and developmental toxicity of methanol, a panel of
9 experts concluded that methanol, not formate, is likely to be the proximate teratogen and
10 determined that blood methanol level is a useful biomarker of exposure (NTP-CERHR, 2004;
11 Dormanetal., 1995). The NTP-CERHR Expert Panel based their assessment of potential
12 methanol toxicity on an assessment of circulating blood levels (NTP-CERHR, 2004). While
13 recent in vitro evidence indicates that formaldehyde is more embryotoxic than methanol and
14 formate (Harris et al., 2004; 2003), the high reactivity of formaldehyde would limit its unbound
15 and unaltered transport as free formaldehyde from maternal to fetal blood (Thrasher and Kilburn,
16 2001), and the capacity for the metabolism of methanol to formaldehyde is likely lower in the
17 fetus and neonate versus adults (see discussion in Section 3.3). Thus, even if formaldehyde is
18 ultimately identified as the proximate teratogen, methanol would likely play a prominent role, at
19 least in terms of transport to the target tissue.
20 Given the reactivity of formaldehyde, models that predict levels of formaldehyde in the
21 blood are difficult to validate. However, production of formaldehyde or formate following
22 exposure to methanol can be estimated by summing the total amount of methanol cleared by
23 metabolic processes.12 This metric of formaldehyde or formate dose has limited value since it
24 ignores important processes that may differ between species, such as elimination (all routes) of
25 these two metabolites, but it can be roughly equated to the total amount of metabolites produced
26 and may be the more relevant dose metric if formaldehyde is found to be the proximate toxic
27 moiety. Thus, both blood methanol and total metabolism metrics are considered to be important
28 components of the PBPK models. Dose metric selection and MOA issues are discussed further in
29 Section 4.7.
3.4.1.2. Criteria for the Development of Methanol PBPK Models
30 The development of methanol PBPK models that would meet the needs of this
31 assessment was organized around a set of criteria that reflect: (1) the MOA(s) being considered
12 This assumption is more likely to be appropriate for formaldehyde than formate as formaldehyde is a direct
metabolite of methanol.
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1 for methanol; (2) absorption, distribution, metabolism, and elimination characteristics; (3) dose
2 routes necessary for interpreting toxicity studies or estimating HECs; and (4) general parameters
3 needed for the development of predictive PK models.
4 The criteria with a brief justification are provided below:
5 • (1) Must simulate blood methanol concentrations and total methanol metabolism.
6 Blood methanol is the recommended dose metric for developmental effects, but total
7 metabolism may be a useful metric.
8 • (2) Must be capable of simulating experimental blood methanol and total metabolism
9 for the inhalation route of exposure in rats (a) and humans (b), and the oral route in
10 humans (c). These routes are important for determining dose metrics in the most
11 sensitive test species under the conditions of the toxicity study and in the relevant
12 exposure routes in humans.
13 • (3) The model code should easily allow designation of respiration rates during
14 inhalation exposures. A standard variable in inhalation route assessments is
15 ventilation rate. Blood methanol concentrations will depend strongly on ventilation
16 rate, which varies significantly between species.
17 • (4) Must address the potential for saturable metabolism of methanol. Saturable
18 metabolism has the potential to bring nonlinearities into the exposure: tissue dose
19 relationship.
20 • (5) Model complexity should be consistent with modeling needs and limitations of the
21 available data. Model should adequately describe the biological mechanisms that
22 determine the internal dose metrics (blood methanol and total metabolism) to assure
23 that it can be reliably used to predict those metrics in exposure conditions and
24 scenarios where data are lacking. Compartments or processes should not be added
25 that cannot be adequately characterized by the available data.
26 Although existing rat models are useful for the evaluation of the dose metrics associated
27 with methanol's developmental effects and the relevant toxicity studies, including gestational
28 exposures, no pregnancy-specific PBPK model exists for methanol, and limited data exists for
29 the development and validation of a fetal/gestational/conceptus compartment. However, EPA
30 determined that nonpregnancy models for the appropriate species and routes of exposure could
31 prove to be valuable because, as discussed in Section 3.2, levels of methanol in NP, pregnant and
32 fetal blood are expected to be similar following the same oral or inhalation exposure. Pollack and
33 Brouwer (1996) determined that methanol distribution in rats and mice following repeated oral
34 and i.v. exposures up to day 20 of gestation is "virtually unaffected by pregnancy, with the
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1
2
3
4
5
6
7
possible exception of the immediate perinatal period." Ward et al. (1997) report a "nonlinear"
relationship between the maternal blood and conceptus, but the nonlinear perception given by
Figure 8 in their paper is the result of the data being plotted on a log-y/linear-x scale. Replotting
the data from their Table 5 (AUC) shows the results to be linear, especially in the low-dose
region which is of the greatest concern (Figure 3-4).
10000
re
1 1000
O
« 100
1 i
o
i
0 10
t
A
V "'"
;
^
>
D 1000 2000 3000
----- Y"
* rat
• mouse
y = x
4000 5000
Maternal AUC (ug/mL-day)
_ 3500
">
•c 3000
B
f, 250°
3
U 2000
< 1500 • "
v> m -
a. 1000
§ 500
o
0
^'
0 1000 2000 3000
•
• rat
• mouse
y=x
4000 5000
Maternal AUC (ug/mL-day)
Source: Ward et al. (1997).
Note: Plotted (A) on a log-linear scale, as in Figure 8 of Ward et al. (1997). and (B) on a linear-linear scale. In both panels the
line y = x is plotted (dashed line) for comparison.
Figure 3-4 Conceptus versus maternal blood AUC values for rats and mice.
The critical window for methanol induction of cervical rib malformations in CD-I mice
has been identified as occurring between GD6 and GD7 (Rogers and Mole, 1997; Rogers et al.,
1993 a), a developmental period roughly equivalent to week 3 of human development (Chernoff
and Rogers, 2004). Methanol blood kinetics measured during and after inhalation exposure in NP
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1 and pregnant mice on GD6-GD10 and GD6-GD15 (Perkins et al.. 1996: Dormanetal.. 1995:
2 Perkins et al., 1995a: Rogers et al., 1993b) are also similar. Further, the available data indicate
3 that the maternal blood:fetal partition coefficient is approximately 1 at dose levels most relevant
4 to this assessment (Ward et al., 1997: Horton et al., 1992). Further supporting data exist for
5 ethanol, which is quite similar to methanol in its partitioning and transport properties. In rats
6 (Zorzano and Herrera, 1989: Guerri and Sanchis, 1985), sheep (Brien etal., 1985: Cumming et
7 al., 1984), and guinea pigs (Clarke et al., 1986), fetal and maternal blood concentrations of
8 ethanol are virtually superimposable; maternal to fetal blood ratios are very close to 1, including
9 during late gestation. Also, fetal brain concentrations in guinea pigs (Clarke etal., 1986) were
10 very similar to the maternal concentrations. Consequently, fetal methanol concentrations are
11 expected to be roughly equivalent to that in the mother's blood. Thus, pharmacokinetics and
12 blood dose metrics for NP rats and humans are expected to provide reasonable approximations of
13 pregnancy levels and fetal exposure, particularly during early gestation, that improve upon
14 default estimations from external exposure concentrations.
15 In addition to the absolute maternal-fetal concentration similarity noted above, it is
16 common practice to use blood concentrations as an appropriate metric for risk extrapolation via
17 PBPK modeling for effects in various tissues, based on the reasonable expectation that any
18 tissue:blood differences will be similar in both the test species and humans. For example, even if
19 the brain:blood ratio was around 1.2 in the mouse or rat, because tissue:blood ratios depend on
20 tissue composition which is expected to be quite similar in rats and humans, the brain:blood
21 levels in humans is also expected to be close to 1.2. Therefore, the potential error that might
22 occur by using blood instead of brain concentration in evaluating the dose-response in rats will
23 be cancelled out by using blood instead of brain concentration in the human. Measured fetal
24 blood levels are virtually identical to maternal levels for methanol (and ethanol) thus indicating
25 that the rate of metabolism in the fetus is not sufficient to significantly reduce the fetal
26 concentration of methanol versus maternal. Use of a PBPK model to predict maternal levels will
27 give a better estimate of fetal exposure than use of the applied dose or exposure, because there
28 are animal-human differences in adult PK of methanol for which the model accounts, based on
29 PK data from humans as well as rodents.
3.4.2. Methanol PBPK Models
30 As has been discussed, methanol is well absorbed by both inhalation and oral routes and
31 is readily metabolized to formaldehyde, which is rapidly converted to formate in both rodents
32 and humans. As was discussed in Section 3.1, the enzymes responsible for metabolizing
33 methanol are different in adult rodents and humans. Several rat, mouse and human PBPK models
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1 that attempt to account for these species differences have been published (Fisher et al., 2000;
2 Wardetal.. 1997: Perkins et al.. 1995a: Hortonetal.. 1992). Two methanol PK models
3 (Bouchard et al., 2001; Ward et al., 1997) were identified as potentially appropriate for use in
4 animal-to-human extrapolation of methanol metabolic rates and blood concentrations. An
5 additional methanol PBPK model by Fisher et al. (2000) was considered principally because it
6 had an important feature - pulmonary compartmentalization (see below for details) - worth
7 adopting in the final model.
3.4.2.1. Wardetal. (1997)
8 The PBPK model of Ward et al. (1997) describes inhalation, oral and i.v. routes of
9 exposure and is parameterized for both NP and pregnant mice and rats (Table 3-9). The model
10 has not been parameterized for humans.
11 Respiratory uptake of methanol is described as a constant infusion into arterial blood at a
12 rate equal to the minute ventilation times the inhaled concentration and includes a parameter for
13 respiratory bioavailability, which for methanol is <100%. This simple approach is nonstandard
14 for volatile compounds but is expected to be appropriate for a compound like methanol, for
15 which there is little clearance from the blood via exhalation. Oral absorption is described as a
16 biphasic process, dependent on a rapid and a slow first-order rate constant.
17 Methanol elimination in the Ward et al. (1997) model is primarily via saturable hepatic
18 metabolism. The parameters describing this metabolism come from the literature, primarily
19 previous work by Ward and Pollack (1996) and Pollack et al. (1993). A first-order elimination of
20 methanol from the kidney compartment includes a lumped metabolic term that accounts for both
21 renal and pulmonary excretion.
22 The model adequately fits the experimental blood kinetics of methanol in rats and mice
23 and is therefore suitable for simulating blood dosimetry in the relevant test species and routes of
24 exposure (oral and i.v.). The Ward et al. (1997) model meets criteria 1, 2a, 2c, 3, 4, and 5
25 outlined in Section 3.4.1.2. The most significant limitation is the absence of parameters for the
26 oral and inhalation routes in the human. A modified version of this model that includes human
27 parameters and a standard PBPK lung compartment might be suitable for the purposes of this
28 assessment.
3.4.2.2. Bouchard et al. (2001)
29 The Bouchard et al. (2001) model is not actually a PBPK model but is an elaborate
30 classical PK model, since the transfer rates are not determined from blood flows, ventilation,
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1 partition coefficients, and the like. The Bouchard et al. (2001) model uses a single compartment
2 for methanol: a central compartment represented by a volume of distribution where the
3 concentration is assumed to equal that in blood. The model was developed for inhalation and i.v.
4 kinetics only. Methanol is primarily eliminated via saturable metabolism. The model adequately
5 simulates blood kinetics in NP rats and humans following inhalation exposure and in NP rats
6 following i.v. exposure; there is no description for oral absorption. Because methanol distributes
7 with total body water (Ward et al., 1997; Horton etal., 1992), this simple model structure is
8 sufficient for predicting blood concentrations of methanol following inhalation and i.v. dosing.
9 The Bouchard et al. (2001) model has the advantage of simplicity, reflecting the
10 minimum number of compartments necessary for representing blood methanol pharmacokinetics.
11 Because volume of distribution can be easily and directly estimated for water-soluble compounds
12 like methanol or fit directly to experimental kinetics data, concern over the scalability of this
13 parameter is absent. The model has been parameterized for a required human exposure route,
14 inhalation (Table 3-9). The model meets criteria 1, 2b, 3, 4, and 5 described in Section 3.4.1.2.
15 However, the Bouchard model has a specific and significant limitation. The model has not been
16 parameterized for the oral route in humans. As such, the model cannot be used to conduct the
17 necessary interspecies extrapolation.
Table 3-9 Routes of exposure optimized in models - optimized against blood
concentration data.
Route
Injection (i.v.)
Inhalation
Oral
Ward et al. (1997)
Mouse Rat Human
P/NP P/NP
P/NP
P/NP NP
Bouchard et al. (2001)
Mouse Rat Human
NP
- NP NP
-
P = Pregnant NP = Nonpregnant
Source: Ward et al. (1997); Bouchard et al. (2001).
3.4.3. Selected Modeling Approach
18 As discussed earlier regarding model criteria, fetal methanol concentrations can
19 reasonably be assumed to equal maternal blood concentration. Thus, methanol pharmacokinetics
20 and blood dose metrics for NP laboratory animals and humans are expected to improve upon
21 default extrapolations from external exposures as estimates of fetal exposure during early
22 gestation. The same level of confidence cannot be placed on the whole-body rate of metabolism,
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1 in particular as a surrogate for formaldehyde dose. Because of formaldehyde's reactivity and the
2 limited fetal metabolic (ADH) activity (see Sections 3.3 and 4.9.1), fetal formaldehyde
3 concentration increases (from methanol) will probably not equal maternal increases in
4 formaldehyde concentration. But since there is no model that explicitly describes formaldehyde
5 concentration in the adult, let alone the fetus, the metabolism metric is the closest one can come
6 to predicting fetal formaldehyde dose. This metric is expected to be a better predictor of
7 formaldehyde dose than applied methanol dose or even methanol blood levels, which do not
8 account for species differences in conversion of methanol to formaldehyde.
9 Most of the published rodent kinetic models for methanol describe the metabolism of
10 methanol to formaldehyde as a saturable process but differ in the description of metabolism to
11 and excretion of formate (Bouchard et al., 2001; Fisher et al., 2000; Ward et al., 1997). The
12 model of Ward et al. (1997) used one saturable and one first-order pathway to describe methanol
13 elimination in mice. The saturable pathway described in Ward et al. (1997) can specifically be
14 ascribed to metabolic formation of formaldehyde in the liver, while the renal first-order
15 elimination described in that paper represents nonspecific clearance of methanol (e.g.,
16 metabolism, excretion, or exhalation), since it was not fit to route-specific elimination data.
17 However, Pollack and Brouwer (1996) obtained a rate constant for the urinary elimination rate
18 from rat urine excretion data, so it can be made specific to that route by use of that parameter.
19 The model of Ward et al. (1997) does not describe kinetics of formaldehyde subsequent to its
20 formation and does not include any description of formate.
21 Bouchard et al. (2001) employed a metabolic pathway for conversion of methanol to
22 formaldehyde and a second pathway described as urinary elimination of methanol in rats and
23 humans. They then explicitly describe two pathways of formaldehyde transformation, one to
24 formate and the other to "other, unobserved formaldehyde byproducts." Finally, formate removal
25 is described by two pathways, one to urinary elimination, and one via metabolism to CC>2 (which
26 is exhaled). All of these metabolic and elimination steps are described as first-order processes,
27 but the explicit descriptions of formaldehyde and formate kinetics significantly distinguish the
28 model of Bouchard et al. (2001) from that of Ward et al. (1997), which only describes methanol.
29 There are two other important distinctions between the Ward et al. (1997) and Bouchard
30 et al. (2001) models. The former is currently capable of simulating blood data for all exposure
31 routes in mice but not humans, while the latter is capable of simulating human inhalation route
32 blood pharmacokinetics but not those in mice. The Ward et al. (1997) model has more
33 compartments than is necessary to adequately represent methanol disposition but has been fit to
34 PK data in pregnant and NP mice for all routes of exposure (i.v., oral, and inhalation). The Ward
35 et al. (1997) model has also been fit to i.v. and oral route PK data in rats. Based primarily on the
36 extensive amount of fitting that has already been demonstrated for this model, it was determined
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1 that a modified Ward et al. (1997) model, with the addition of a lung compartment as described
2 by Fisher et al. (2000), should be used for the purposes of this assessment. The ability of the
3 Ward et al. (1997) mouse PBPK model to describe dosimetry in that species supports the
4 biological basis for this model structure; and hence, the expectation that it can be used to predict
5 dosimetry in humans. However, as mentioned previously, the mouse parameterized PBPK model
6 is not used in this assessment. See Appendix B for a more complete discussion of the selected
7 modeling approach and modeling considerations.
3.4.3.1. Available PK Data
8 Although limited human data are available, several studies exist that contain PK and
9 metabolic data in mice, rats, and nonhuman primates for model parameterization (Table 3-10).
3.4.3.2. Model Structure
10 As described in detail in Appendix B, a model was developed which includes
11 compartments for alveolar air/blood methanol exchange, liver, fat, bladder (human simulations)
12 and the rest of the body (Figure 3-5). This model is a revision of the model reported by Ward et
13 al. (1997), reflecting significant simplifications (removal of compartments for placenta,
14 embryo/fetus, and extra-embryonic fluid) and two elaborations (addition of a second GI lumen
15 compartment to the existing stomach lumen compartment and addition of a bladder
16 compartment), while maintaining the ability to describe methanol blood kinetics in rats and
17 humans. A fat compartment was included because it is the only tissue with a tissue:blood
18 partitioning coefficient appreciably different than 1, and the liver is included because it is the
19 primary site of metabolism. A bladder compartment was also added for use in simulating human
20 urinary excretion to capture the difference in kinetics between changes in blood methanol
21 concentration and urinary methanol concentration. The model code describes inhalation, oral,
22 and i.v. dose routes, and data exist from studies (Table 3-10) that were used to fit parameters and
23 evaluate model predictions for all three of those routes. In humans, inhalation exposure data an
24 i.v. study and a single short-duration oral PK study were available for model calibration and
25 validation.
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Table 3-10 Key methanol kinetic studies for model validation.
i.v. dose
Reference (mg/kg)
Batterman & Franzblau
(1997)
Batterman et al. (1998)
Ernstgard et al. (2005)
Haffner et al. (1992) 10
Osterloh et al. (1996):
Chuwers et al. (1995):
D'Alessandro et al. (1994)
Schmutte et al. (1988)
Sedivec et al. (1981)
Burbacher et al. (2004a):
Burbacher et al. (2004b)
Medinsky et al. (1997):
Dorman et al. (1994)
Hortonetal.0992) 10° <***
only)
Perkins et al. (1996.
1995a. b)
Oral/
Inhalation dermal/
(ppm) i.p.
Dermal
800 (8 hr)
100 (2hr)
200 (2hr)
200 (4 hr)
Oral
l.lmg/L
78-231 (8 hr)
0-1,800 (2.5
hr, 4 mo)
10-900 (2 hr)
50-2,000
(6hr)
1,000-20,000
(8hr)
Pollack and Brouwer 1000-20000 °ral:
(1996) 100-2,500 '"" ' 100-2,500
Pollack et al. (1993) ( ' mg/kg
Ward et al. (1997) 100, 500
Ward and Pollack (1996) (Rat)
Rogers and Mole (1997)
Rogers et al. (1993b)
Oral:
2,500
mg/kg
1,000-15,000
(7 hr, 10 days)
aData obtained from the reported figure, from the corresponding reference.
1 The approach to model calibration and specific data
2 rats and humans are described in detail in Appendix B. The
Species
Human
Male/female
Human
Male/female
Human
Male/female
Human males
Human
Male/female
Human
Human
Male
Monkeys
Cynomolgus
Pregnant, NP
Monkeys
Cynomolgus
Folate deficient
Monkey Rhesus,
and Rat Fischer-
344
Mouse and Rat
Rat: Sprague-
Dawley, &
Mouse; CD-I
Pregnant, NP
Mouse CD-I,
GDIS; Rat
Sprague-Dawley,
GD14 & GD20
Mouse CD-I
Pregnant
Samples
Blood
Blood,
Urine,
Exhaled
Blood,
Exhaled
Blood
Blood,
Urine
Blood
Urine,
Blood
Blood
Blood,
Urine,
Exhaled
Blood,
Urine,
Exhaled
Blood,
Urine
Blood
Blood,
Conceptus
Blood
Digitized
figures"
Figure 1
Figure 1
Figure lin
Osterloh et
al. (1996)
Figure 1
Figures 2,
3, 6, 7, 8
Figure 7
sets used for Sprague-Dawley (S-D)
metabolism of methanol was
described using Michaelis-Menten kinetics. Simulated metabolic elimination of methanol is not
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1 linked in the PBPK model to production of formaldehyde or formate; it is simply another route
2 of methanol elimination. Metabolism of formaldehyde (to formate) is not explicitly simulated by
3 the model, and this model tracks neither formate nor formaldehyde. Since the metabolic
4 conversion of formaldehyde to formate is rapid (<1 minute) in all species (Kavet and Nauss,
5 1990), the rate of methanol metabolism may approximate a formate production rate, though this
6 has not been verified.
9
10
11
Inhalation Fracin
exposure
fV->
Bladder
(human only}
bl
Urine
I
o
c
o
Q.
Alveolar Air
Lung blood
Exhaled
air
(rat ,j;-),,..,.--N
only) "
Body
Fat
a-
(D
m
o
o
0.
Metabolism
Endogenous
production
Note: Parameters: Fracin (FRACIN), fraction of exposure concentration reaching gas exchange region in lungs; Bav, oral
bioavailability; kas, first-order oral absorption rate from stomach; k^, first-order uptake from 2nd GI compartment; ksi, first-order
transfer between stomach and 2nd GI; Vmax and Km , apparent Michaelis-Menten rate constants for metabolism in liver; kls first-
order rate constant for urinary elimination; ku, rate constant for urinary excretion from bladder. For the rat only, high levels of
methanol in the body compartment lead to respiratory and cardiac depression, indicated by the dashed line. Rat data were
consistent with Bav = 100%, but humans with Bav = 83%.
Figure 3-5 Schematic of the PBPK model used to describe the inhalation, oral, and i.v.
route pharmacokinetics of methanol.
The primary purpose of this assessment is for the determination of noncancer risk
associated with exogenous oral or inhalation exposure to methanol that add to background levels
of methanol derived from a diet that includes fruits and vegetables. However, because
background methanol levels can impact model parameter estimation and internal dose
predictions, the PBPK models developed for this assessment incorporate a zero-order liver
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1 infusion term for methanol designed to approximate reported background levels. The PBPK
2 model estimate of background levels was then subtracted for benchmark dose (BMD) modeling.
3 For example, when the metric is blood AUC, BMD analysis used the PBPK-predicted difference,
4 AUC (exposed rats) - AUC (control rats), as the dose metric. In short the level of effect was
5 correlated with the internal dose above background in the test animal (PODAUC). The human
6 PBPK model was then used to estimate the human equivalent oral dose (PODHEo) or inhalation
7 concentration (PODHEc) associated with this internal dose. To do this, the human PBPK model
8 used an upper bound background level (discussed in Section 5.3.6) of 2.5 mg/L (except when
9 study specific data were available during model calibration) and the PODHED or PODHEc was
10 selected such that the predicted increase in human blood levels over this background matched the
11 PODAUC.
3.4.3.3. Model Parameters
12 The EPA methanol model uses a consistent set of physiological parameters obtained
13 predominantly from the open literature (Appendix B, Table B-l); the Ward et al. (1997) model
14 employed a number of data-set specific parameters.13 Parameters for blood flow, ventilation, and
15 metabolic capacity were scaled as a function of body weight raised to the 0.75 power, according
16 to the methods of Ramsey and Andersen (1984).The process by which the rat and human
17 inhalation and oral models were calibrated and analyzed for parameter sensitivity is discussed in
18 Appendix B, "Development, Calibration and Application of a Methanol PBPK Model." An
19 evaluation of the importance of selected parameters on the model estimates of blood methanol
20 was performed using the subroutines within acslX v2.3 (Aegis Technologies, Huntsville,
21 Alabama).
3.4.4. Monkey PK Data and Analysis
22 In order to estimate internal doses (blood Cmax and AUC values) for the monkey health-
23 effects study of Burbacher et al. (1999b) and further elucidate the potential differences in
24 methanol pharmacokinetics between NP and pregnant individuals (2nd and 3rd trimester), a
25 focused reanalysis of the data of Burbacher et al. (1999a) was performed. The monkeys in this
26 study were exposed for 2.5 hours/day, with the methanol concentration raised to approximately
27 the target concentration for the first 2 hours of each exposure and the last 30 minutes providing a
28 chamber "wash-out" period, when the exposure chamber concentration was allowed to drop to 0.
13 Some data sets provided in the Ward et al. (1997) model code were corrected to be consistent with figures in the
published literature describing the experimental data.
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1 Blood samples were taken and analyzed for methanol concentration at 30 minutes, 1, 2, 3, 4, and
2 6 hours after removal from the chamber (or 1, 1.5, 2.5, 3.5, 4.5, and 6.5 hours after the end of
3 active exposure). These data were analyzed to compare the PK in NP versus pregnant animals,
4 and fitted with a simple PK model to estimate 24-hour blood AUC values for each exposure
5 level. Details of this analysis are provided in Appendix B. The chamber concentrations for
6 "pregnancy" exposures recorded by Burbacher et al. (1999a: Table 2) and average body weights
7 for each exposure group at the 2nd trimester time point were used along with the model
8 described in Appendix B to calculate Cmax above background and 24-hour blood methanol AUC
9 above background (Table B-6) for the dose-response analysis of data from the Burbacher et al.
10 (1999a: 1999b) developmental study in monkeys described in Appendix D.
3.4.5. Summary and Conclusions
11 Rat and human versions of a methanol PBPK model have been developed and calibrated
12 to data available in the open literature. The model simplifies the structure used by Ward et
13 al.(1997), while adding specific refinements such as a standard lung compartment employed by
14 Fisher et al. (2000) and a two-compartment GI tract.
15 Although the developmental endpoints of concern are effects which occur following in
16 utero and (to a lesser extent) lactational exposure, no pregnancy-specific PBPK model exists for
17 methanol and limited data exists for the development and validation of a
18 fetal/gestational/conceptus compartment. The fact that the unique physiology of pregnancy and
19 the fetus/conceptus are not represented in a methanol model would be important if methanol
20 pharmacokinetics differed significantly during pregnancy or if the observed partitioning of
21 methanol into the fetus/conceptus versus the mother showed a concentration ratio significantly
22 greater than or less than 1. Methanol pharmacokinetics during GD6-GD10 in the mouse are not
23 different from NP mice (Pollack and Brouwer, 1996), and the maternal blood:fetus/conceptus
24 partition coefficient is reported to be near 1 (Ward et al., 1997; Horton et al., 1992). Maternal
25 blood kinetics in monkeys differs little from those in NP animals (see Section 3.2 for details).
26 Further, in both mice and monkeys, to the extent that late-pregnancy blood levels differ from NP
27 for a given exposure, they are higher; i.e., the difference between model predictions and actual
28 concentrations is in the same direction. These data support the assumption that the ratio of actual
29 target-tissue methanol concentration to (predicted) NP maternal blood concentrations will be
30 about the same across species, and hence, that using NP maternal blood levels in place of fetal
31 concentrations will not lead to a systematic error when extrapolating risks.
32 The critical gestational window for the reduced brain weight effect observed in the
33 NEDO (1987) rat study is broader than for the mouse cervical rib effect. In addition, NEDO
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1 (1987) rats were exposed not only to methanol gestationally but also lactationally and via
2 inhalation after parturition. The findings in the mice and rats up to GD20 (similar blood
3 methanol kinetics between NP and pregnant animals and a maternal blood:fetal partition
4 coefficient close to 1) are assumed to be applicable to the rat later in pregnancy. However, the
5 additional routes of exposure to the pups in this study present uncertainties (see additional
6 discussion in Sections 5.1.2.2 and 5.1.3.2.2) and suggest that average blood levels in pups might
7 be greater than those of the dam.
8 Methanol is transported directly from the maternal circulation to fetal circulation via the
9 placenta, but transfer via lactation involves distribution to the breast tissue, then milk, then
10 uptake from the pup's GI tract. Therefore blood or target-tissue levels in the breast-feeding infant
11 or rat pup are likely to differ more from maternal levels than do fetal levels. In addition, the
12 health-effects data indicate that most of the effects of concern are due to fetal exposure, with a
13 relatively small influence due to postnatal exposures. Therefore, it would be extremely difficult
14 to distinguish the contribution of postnatal exposure from prenatal exposure to a given effect in a
15 way that would allow the risk to be estimated from estimates of both exposure levels, even if one
16 had a lactation/child PBPK model that allowed for prediction of blood (or target-tissue) levels in
17 the offspring. Finally, one would still expect the target-tissue concentrations in the offspring to be
18 closely related to maternal blood levels (which depend on ambient exposure and determine the
19 amount delivered through breast milk), with the relationship between maternal levels and those
20 in the offspring being similar across species. Further, as discussed in Section 5.1.3.2.2, it is likely
21 that the difference in blood levels between rat pups and dams would be similar to the difference
22 between mothers and human offspring. Therefore, it is assumed that the potential differences
23 between pup and dam blood methanol levels do not have a significant impact on this assessment
24 and the estimation of HECs.
25 Therefore, the development of a lactation/child PBPK model is not necessary, given the
26 minimal change that is likely to result in risk extrapolations, and use of NP maternal blood levels
27 as a measure of risk in the offspring is considered preferable over use of default extrapolation
28 methods. In particular, the existing human data allow for predictions of maternal blood levels,
29 which depend strongly on the rate of maternal methanol clearance. Since bottle-fed infants do
30 not receive methanol from their mothers, they are expected to have lower or, at most, similar
31 overall exposures for a given ambient concentration than the breast-fed infant, so that use of
32 maternal blood levels for risk estimation should also be adequately protective for that group.
33 The final rat and human methanol PBPK models fit multiple data sets for inhalation, oral,
34 and i.v. (rat only) exposures, using consistent parameters that are representative of each species
35 but are not varied within species or by dose or source of data. Also, a simple PK model calibrated
36 to early gestation monkey data, which were shown to be essentially indistinguishable from NP
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1 and late-gestation pregnant monkey PK data, was used to estimate blood methanol peak
2 concentrations (internal doses) in that species. The models are used to estimate chronic human
3 exposure concentrations from internal dose metrics for use in the RfC and RfD derivations
4 discussed in Section 5.
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4.HAZARD IDENTIFICATION
4.1. Studies in Humans - Case Reports, Occupational and Controlled
Studies
4.1.1. Case Reports
1 An extensive library of case reports has documented the consequences of acute
2 accidental/intentional methanol poisoning. Nearly all have involved ingestion, but a few have
3 involved percutaneous and/or inhalation exposure.
4 As many of the case reports demonstrate, the association of Parkinson-like symptoms
5 with methanol poisoning is related to the observation that lesions in the putamen are a common
6 feature both in Parkinson's disease and methanol overexposure. These lesions are commonly
7 identified using Computed Tomography (CT) or by Magnetic Resonance Imaging (MRI). Other
8 areas of the brain (e.g., the cerebrum, cerebellum, and corpus callosum) also have been shown to
9 be adversely affected by methanol overexposure. The associated effects are further discussed in
10 Appendix C, Human Case Studies.
11 Various therapeutic procedures [e.g., infusion of ADH1 inhibitors ethanol or fomepizole
12 (4-methylpyrazole)], sodium bicarbonate or folic acid administration, and hemodialysis) have
13 been used in many of these methanol overexposures, and the reader is referred to the specific
14 case reports for details in this regard (see Appendix C). The reader also is referred to Kraut and
15 Kurtz (2008) and Barceloux et al. (2002) for a more in-depth discussion of the treatments in
16 relation to clinical features of methanol toxicity.
17 Most cases of accidental/intentional methanol poisoning reveal a common set of
18 symptoms, many of which are likely to be presented upon hospital admission. These include:
19 • blurred vision and bilateral or unilateral blindness
20 • convulsions, tremors, and coma
21 • nausea, headache, and dizziness
22 • abdominal pain
23 • diminished motor skills
24 • acidosis
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1 • dyspnea
2 • behavioral and/or emotional deficits
3 • speech impediments
4 Acute symptoms generally are nausea, dizziness, and headache. In the case reports cited
5 in Appendix C, the onset of symptom sets as well as their severity varies depending upon how
6 much methanol was ingested, whether or not and when appropriate treatment was administered,
7 and individual variability. A longer time between exposure and treatment, with few exceptions,
8 results in more severe outcomes (e.g., convulsions, coma, blindness, and death). The diminution
9 of some acute and/or delayed symptoms may reflect concomitant ingestion of ethanol or how
10 quickly therapeutic measures (one of which includes ethanol infusion) were administered in the
11 hospital setting.
12 Those individuals who are in a metabolic acidotic state (e.g., pH <7.0) are typically the
13 individuals who manifest the more severe symptoms. Many case reports stress that, unlike blood
14 pH levels <7.0, blood levels of methanol are not particularly good predictors of health outcome.
15 According to a publication of the American Academy of Clinical Toxicology (Barceloux et al.,
16 2002), "the degree of acidosis at presentation most consistently correlates with severity and
17 outcome."
Table 4-1 Mortality rate for subjects exposed to methanol-tainted whisky in relation to
their level of acidosis.
Subjects" Number Percent deaths
All patients 323 6.2
Acidotic (CO2 <20 mEq) 115 19
Acidotic (CO2 <10 mEq) 30 50
"These data do not include those who died outside the hospital or who were moribund on arrival.
Source: Bennett et al. (1953).
18 As the case reports (Appendix C) demonstrate, those individuals who present with more
19 severe symptoms (e.g., coma, seizures, and severe acidosis) generally exhibit higher mortality
20 (even after treatment) than those without such symptoms. In survivors of poisoning, persistence
21 or permanence of vision decrements and particularly blindness often have been observed.
22 Because of the strong correlation between outcomes of methanol poisoning with severity of
23 acidosis (e.g., Table 4-1), formate is usually assumed to be the proximal cause of the acute
24 effects of methanol. Most of the symptoms of methanol poisoning (listed in the individual
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1 studies in Appendix C) are common to the several other types of metabolic acidosis (Berkow and
2 Fletcher, 1992). It has been postulated that formaldehyde may be the toxic moiety for the
3 symptoms of methanol poisoning that are seemingly distinct from acidotic symptoms (Hayasaka
4 et al., 2001). However, the predominant role of formic acid as the major metabolic agent for
5 methanol ocular toxicity has been demonstrated in monkeys, who experienced ocular toxicity
6 following methanol exposure that was essentially identical to that produced in monkeys exposed
7 to formate (Mcmartin et al., 1979). Since formaldehyde has a very short half life, it is unlikely to
8 be distributed from the liver to the brain or eye fast enough to cause CNS or ocular damage.
9 Nevertheless, methanol is distributed to multiple organ systems and there is evidence that it can
10 be metabolized to formaldehye in situ by other organ systems, including studies that have found
11 ADH activity in non-liver cells (Jelski et al., 2006; Motavkin et al., 1988; BuhleretaL 1983)
12 and a rat study that reports dose-dependent increases of formaldehyde DNA adducts derived
13 from exogenous methanol exposure in multiple tissues such as liver, lung, spleen, thymus, bone
14 marrow, kidney, and WBC (exogenous adduct levels were less than 10% of endogenous adduct
15 levels for most organ systems) (Luetal., 2012).
16 Correlation of symptomatology with blood levels of methanol has been shown to vary
17 appreciably between individuals. Blood methanol levels in the case reports involving ingestion
18 ranged from values of 300 to over 10,000 mg/L. The lowest value (200 mg/L) reported (Adanir
19 et al., 2005) involved a case of percutaneous absorption (with perhaps associated inhalation
20 exposure) that led to vision and CNS deficits after hospital discharge. In one case report
21 (Rubinstein et al., 1995) involving ingestion, coma and subsequent death were associated with an
22 initial blood methanol level of 360 mg/L.
23 Upon MRI and CT scans, the more seriously affected individuals typically have focal
24 necrosis in both brain white matter and more commonly, in the putamen. Bilateral hemorrhagic
25 and nonhemorrhagic necrosis of the putamen is considered by many radiologists as the most
26 well-known sequelae of methanol overexposure.
4.1.2. Occupational Studies
27 Occupational health studies have been carried out to investigate the potential effects of
28 chronic exposure to lower levels of methanol than those seen in acute poisoning cases such as
29 those described in Appendix C. For example, Frederick et al. (1984) conducted a health hazard
30 evaluation on behalf of the National Institute for Occupational Safety and Health (NIOSH) to
31 determine if vapor from duplicating fluid (which contains 99% methanol) used in mimeograph
32 duplicating machines caused adverse health effects in exposed persons. A group of 84 teacher's
33 aides were selected for study, 66 of whom responded with a completed medical questionnaire. A
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1 group of 297 teachers (who were not exposed to methanol vapors to the same extent as the
2 teacher's aides) completed questionnaires as a control group. A 15-minute breathing zone sample
3 was taken from 21 duplicators, 15 of which were greater than the NIOSH-recommended short
4 term ceiling concentration of 800 ppm (1,048 mg/m3). The highest breathing zone concentrations
5 were in the vicinity of duplicators for which no exhaust ventilation had been provided
6 (3,080 ppm [4,036 mg/m3] was the highest value recorded). Upon comparison of the self-
7 described symptoms of the 66 teacher's aides with those of 66 age-matched teachers chosen from
8 the 297 who responded, the number of symptoms (potentially related to methanol) was
9 significantly higher in the teacher's aides. These included blurred vision (22.7 versus 1.5%),
10 headache (34.8 versus 18.1%), dizziness (30.3 versus 1.5%), and nausea (18 versus 6%). By
11 contrast, symptoms that are not usually associated with methanol exposure (painful urination,
12 diarrhea, poor appetite, and jaundice) were similar in incidence among the groups.
13 To further investigate these disparities, NIOSH physicians (not involved in the study)
14 defined a hypothetical case of methanol toxicity by any of the following four symptom
15 aggregations: (1) visual changes; (2) one acute symptom (headache, dizziness, numbness,
16 giddiness, nausea or vomiting) combined with one chronic symptom (unusual fatigue, muscle
17 weakness, trouble sleeping, irritability, or poor memory); (3) two acute symptoms; or (4) three
18 chronic symptoms. By these criteria, 45% of the teacher's aides were classified as being
19 adversely affected by methanol exposure compared to 24% of teachers (p < 0.025). Those
20 teacher's aides and teachers who spent a greater amount of time using the duplicators were
21 affected at a higher rate than those who used the machines for a lower percentage of their work
22 day.
23 Tanner (1992) reviewed the occupational and environmental causes of Parkinson!sm,
24 spotlighting the potential etiological significance of manganese, carbon monoxide, repeated head
25 trauma (such as suffered by boxers), and exposure to solvents. Among the latter, Tanner (1992)
26 discussed the effects of methanol and n-hexane on the nervous system. Acute methanol
27 intoxication resulted in inebriation, followed within hours by GI pain, delirium, and coma.
28 Tanner (1992) pinpointed the formation of formic acid, with consequent inhibition of
29 cytochrome oxidase, impaired mitochondrial function, and decreased ATP formation as relevant
30 biochemical and physiological changes for methanol exposure. Nervous system injury usually
31 includes blindness, Parkinson-like symptoms, dystonia, and cognitive impairment, with injury to
32 putaminal neurons most likely underlying the neurological responses.
33 Kawai et al. (1991) carried out a biomarker study in which 33 occupationally exposed
34 workers in a factory making methanol fuel were exposed to concentrations of methanol of up to
35 3,577 ppm (4,687 mg/m3), as measured by personal samplers of breathing zone air. Breathing
36 zone exposure samples were correlated with the concentrations of methanol in urine at the end of
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1 the shift in 38 exposed individuals and 30 controls (r = 0.82). Eleven of 22 individuals who
2 experienced high exposure to methanol (geometric mean of 459 ppm [601 mg/m3]) complained
3 of dimmed vision during work while 32% of this group of workers experienced nasal irritation.
4 These incidences were statistically significant compared to those of persons who worked in low-
5 exposure conditions (geometric mean of 31 ppm [41 mg/m3]). One 38-year-old female worker
6 who had worked at the factory for only 4 months reported that her visual acuity had undergone a
7 gradual impairment. She also displayed a delayed light reflex.
8 Lorente et al. (2000) carried out a case control study of 100 mothers whose babies had
9 been born with cleft palates. Since all of the mothers had worked during the first trimester,
10 Lorente et al. (2000) examined the occupational information for each subject in comparison to
11 751 mothers whose babies were healthy. Industrial hygienists analyzed the work histories of all
12 subjects to determine what, if any, chemicals the affected mothers may have been exposed to
13 during pregnancy. Multivariate analysis was used to calculate odds ratios, with adjustments made
14 for center of recruitment, maternal age, urbanization, socioeconomic status, and country of
15 origin. Occupations with positive outcomes for cleft palate in the progeny were hairdressing
16 (OR = 5.1, with a 95% confidence interval [CI] of 1.0-26) and housekeeping (OR = 2.8, with a
17 95% CI of 1.1-7.2). Odds ratios for cleft palate only and cleft lip with or without cleft palate
18 were calculated for 96 chemicals. There seemed to be no consistent pattern of association for any
19 chemical or group of chemicals with these impairments, and possible exposure to methanol was
20 negative for both outcomes.
4.1.3. Controlled Human Studies
21 Two controlled studies have evaluated humans for neurobehavioral function following
22 exposure to -200 ppm (262 mg/m3) methanol vapors in a controlled setting. The occupational
23 TLV established by the American Conference of Governmental Industrial Hygienists (2000) is
24 200 ppm (262 mg/m3). In a pilot study by Cook et al. (1991), 12 healthy young men (22-32 years
25 of age) served as their own controls and were tested for neurobehavioral function following a
26 random acute exposure to air or 191 ppm (250 mg/m3) methanol vapors for 75 minutes. The
27 majority of results in a battery of neurobehavioral endpoints were negative. However, statistical
28 significance was obtained for results in the P-200 and N1-P2 component of event-related
29 potentials (brain wave patterns following light flashes and sounds), the Sternberg memory task,
30 and subjective evaluations of concentration and fatigue. As noted by the Cook et al.(1991),
31 effects were mild and within normal ranges. Cook et al. (1991) acknowledged limitations in their
32 study design, such as small sample size, exposure to only one concentration for a single duration
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1 time, and difficulties in masking the methanol odor from experimental personnel and study
2 subjects.
3 In a randomized double-blind study, neurobehavioral testing was conducted on 15 men
4 and 11 women (healthy, aged 26-51 years) following exposure to 200 ppm (262 mg/m3)
5 methanol or water vapors for 4 hours (Chuwers et al., 1995): subjects served as their own
6 controls in this study. Exposure resulted in elevated blood and urine methanol levels (up to peak
7 levels of 6.5 mg/L and 0.9 mg/L, respectively) but not formate concentrations. The majority of
8 study results were negative. No significant findings were noted for visual, neurophysiological, or
9 neurobehavioral tests except for slight effects (p < 0.05) on P-300 amplitude (brain waves
10 following exposure to sensory stimuli) and Symbol Digit testing (ability to process information
11 and psychomotor skills). Neurobehavioral performance was minimally affected by methanol
12 exposure at this level. Limitations noted by Chuwers et al. (1995) are that studies of alcohol's
13 affect on P-300 amplitude suggest that this endpoint may be biased by unknown factors and
14 some experimenters and subjects correctly guessed if methanol was used.
15 Although the slight changes in P-200 and P-300 amplitude noted in both the Chuwers et
16 al. (1995) and Cook et al. (1991) studies may be an indication of moderate alterations in
17 cognitive function, the results of these studies are generally consistent and suggest that the
18 exposure concentrations employed were below the threshold for substantial neurological effects.
19 This is consistent with the data from acute poisoning events which have pointed to a serum
20 methanol threshold of 200 mg/L for the instigation of acidosis, visual impairment, and CNS
21 deficits.
22 Mann et al. (2002) studied the effects of methanol exposure on human respiratory
23 epithelium as manifested by local irritation, ciliary function, and immunological factors. Twelve
24 healthy men (average age 26.8 years) were exposed to 20 and 200 ppm (26.2 and 262 mg/m3,
25 respectively) methanol for 4 hours at each concentration; exposures were separated by 1-week
26 intervals. The 20 ppm (26.2 mg/m3) concentration was considered to be the control exposure
27 since previous studies had demonstrated that subjects can detect methanol concentrations of
28 20 ppm (26.2 mg/m3) and greater. Following each single exposure, subclinical inflammation was
29 assessed by measuring concentrations of interleukins (IL-8, IL-lp, and IL-6) and prostaglandin
30 E2 in nasal secretions. Mucociliary clearance was evaluated by conducting a saccharin transport
31 time test and measuring ciliary beat frequency. Interleukin and prostaglandin data were evaluated
32 by a 1-tailed Wilcoxon test, and ciliary function data were assessed by a 2-tailed Wilcoxon test.
33 Exposure to 200 (262 mg/m3) versus 20 ppm (26.2 mg/m3) methanol resulted in a statistically-
34 significant increase in IL-lp (median of 21.4 versus 8.3 pg/mL) and IL-8 (median of 424 versus
35 356 pg/mL). There were no significant effects on IL-6 and prostaglandin E2 concentration,
36 ciliary function, or on the self-reported incidence of subjective symptoms of irritation. The
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1 authors concluded that exposure to 200 ppm (262 mg/m3) methanol resulted in a subclinical
2 inflammatory response.
3 In summary, adult human subjects acutely exposed to 200 ppm (262 mg/m3) methanol
4 have experienced slight neurological (Chuwers et al., 1995) and immunological effects
5 (increased subclinical biomarkers for inflammation) with no self-reported symptoms of irritation
6 (Mann et al., 2002). These exposure levels were associated with peak methanol blood levels of
7 6.5 mg/L (Chuwers et al., 1995). Nasal irritation effects have been reported by adult workers
8 exposed to 459 ppm (601 mg/m3) methanol (Kawai et al., 1991). Frank effects such as blurred
9 vision, bilateral or unilateral blindness, coma, convulsions/tremors, nausea, headache, abdominal
10 pain, diminished motor skills, acidosis, and dyspnea begin to occur as blood levels approach
11 200 mg methanol/L, while 800 mg/L appears to be the threshold for lethality. Data for
12 subchronic, chronic or in utero human exposures are very limited and inconclusive.
4.2. Acute, Subchronic and Chronic Studies in Animals - Oral and
Inhalation
13 A number of studies in animals have investigated the acute, subchronic, and chronic
14 toxicity of methanol. Most are via the inhalation route. Presented below are summaries of the
15 noncancer effects reported in these bioassays. Carcinogenic effects are not described or discussed
16 in this assessment.
4.2.1. Oral Studies
4.2.1.1. Acute Toxicity
17 Although there are few studies that have examined the short-term toxic effects of
18 methanol via the oral route, a number of median lethal dose (LD50) values have been published
19 for the compound. As listed in Lewis (1992), these include 5,628 mg/kg in rats, 7,300 mg/kg in
20 mice, and 7,000 mg/kg in monkeys.
4.2.1.2. Subchronic Toxicity
21 An oral repeat dose study was conducted by the U.S. EPA (TRL, 1986) in rats. Sprague-
22 Dawley rats (30/sex/dose) at no less than 30 days of age were gavaged with 0, 100, 500, or
23 2,500 mg/kg-day of methanol. Six weeks after dosing, 10 rats/sex/dose group were subjected to
24 interim sacrifice, while the remaining rats continued on the dosing regimen until the final
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1 sacrifice (90 days). This study generated data on weekly body weights and food consumption,
2 clinical signs of toxicity, ophthalmologic evaluations, mortality, blood and urine chemistry (from
3 a comprehensive set of hematology, serum chemistry, and urinalysis tests), and gross and
4 microscopic evaluations for all test animals. Complete histopathologic examinations of over
5 30 organ tissues were done on the control and high-dose rats. Histopathologic examinations of
6 livers, hearts, and kidneys and all gross lesions seen at necropsy were done on low-dose and mid-
7 dose rats. There were no differences between dosed animals and controls in body weight gain,
8 food consumption, or upon gross or microscopic evaluations. Elevated levels (p < 0.05 in males)
9 of serum alanine transaminase (ALT)14 and serum alkaline phosphatase (SAP), and increased
10 (but not statistically significant) liver weights in both male and female rats suggest possible
11 treatment-related effects in rats bolus dosed with 2,500 mg methanol/kg-day despite the absence
12 of supportive histopathologic lesions in the liver. Brain weights of high-dose group
13 (2,500 mg/kg-day) males and females were significantly less than those of the control group at
14 terminal sacrifice. The only histopathology noted was a higher incidence of colloid in the
15 hypophyseal cleft of the pituitary gland in the high-dose versus control group males
16 (13/20 versus 0/20) and females (9/20 versus 3/20). Based on these findings, 500 mg/kg-day of
17 methanol is considered an NOAEL from this rat study.
4.2.1.3. Chronic Noncancer Toxicity
18 A report by Soffritti et al. (2002) summarized a European Ramazzini Foundation (ERF)
19 chronic duration experimental study of methanol15 in which the compound was provided to
20 100 Sprague-Dawley rats/sex/group ad libitum in drinking water at concentrations of 0, 500,
21 5,000, and 20,000 ppm (v/v). The animals were 8 weeks old at the beginning of the study. In
22 general, ERF does not randomly assign animals to treatment groups, but assigns all animals from
23 a given litter to the same treatment group (Bucher, 2002). All rats were exposed for up to
24 104 weeks, and then maintained until they died naturally. Rats were housed in groups of 5 in
25 Makrolon cages (41 x 25 x 15 cm) in a room that was maintained at 23 ± 2°C and 50-60%
26 relative humidity. The in-life portion of the experiment ended at 153 weeks with the death of the
27 last animal. Mean daily drinking water, food consumption, and body weights were monitored
28 weekly for the first 13 weeks, every 2 weeks thereafter for 104 weeks, then every 8 weeks until
29 the end of the experiment. Clinical signs were monitored 3 times/day, and the occurrence of
14 Also known as serum glutamate pyruvate transaminase (SGPT)
15 Soffritti et al. (2002) report that methanol was obtained from J.T. Baker, Deventer, Holland, purity grade 99.8%.
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1 gross changes was evaluated every 2 weeks. All rats were necropsied at death then underwent
2 histopathologic examination of organs and tissues.16
3 Soffritti et al. (2002) reported no substantial dose-related differences in survival, but no
4 data were provided. Using individual animal data available from the ERF website,17 Cruzan
5 (2009) reports that male rats treated with methanol generally survived better than controls, with
6 50% survival occurring at day 629, 686, 639 and 701 in the 0, 500, 5,000, and 20, 000 mg/L
7 groups, respectively. There were no significant differences in survival between female control
8 and treatment groups, with 50% survival occurring at day 717, 691, 678 and 708 in the 0, 500,
9 5,000, and 20,000 mg/L groups, respectively. Body weight and water and food consumption
10 were monitored in the study, but the data were not documented in the published report.
11 Soffritti et al. (2002) reported that water consumption in high-dose females was reduced
12 compared to controls between 8 and 56 weeks and that the mean body weight in high-dose males
13 tended to be higher than that of control males. Overall, there was no pattern of compound-related
14 clinical signs of toxicity, and the available data did not provide any indication that the control
15 group was not concurrent with the treated group (Cruzan, 2009). Soffritti et al. (2002) further
16 reported that there were no compound-related signs of gross pathology or histopathologic lesions
17 indicative of noncancer toxicological effects in response to methanol.
18 Apaja (1980) performed dermal and drinking water chronic bioassays in which male and
19 female Eppley Swiss Webster mice (25/sex/dose group; 8 weeks old at study initiation) were
20 exposed 6 days per week until natural death to various concentrations of malonaldehyde and
21 methanol. The stated purpose of the study was to determine the carcinogenicity of
22 malonaldehyde, a product of oxidative lipid deterioration in rancid beef and other food products
23 in advanced stages of degradation. However, due to its instability, malonaldehyde was obtained
24 from the more stable malonaldehyde bis (dimethylacetal), which was hydrolyzed to
25 malonaldehyde and methanol in dilute aqueous solutions in the presence of a strong mineral acid.
26 In the drinking water portion of this study, mice were exposed to 3 different concentrations of the
27 malonaldehyde/methanol solution and three different control solutions of methanol alone,
28 0.222%, 0.444% and 0.889% methanol in drinking water (222, 444 and 889 ppm, assuming a
29 density of 1 g/mL), corresponding to the stoichiometric amount of methanol liberated by
30 hydrolysis of the acetal in the three test solutions. The methanol was described as Mallinckrodt
16 Histopathology was performed on the following organs and tissues: skin and subcutaneous tissue, brain, pituitary
gland, Zymbal glands, parotid glands, submaxillary glands, Harderian glands, cranium (with oral and nasal cavities
and external and internal ear ducts) (5 sections of head), tongue, thyroid and parathyroid, pharynx, larynx, thymus
and mediastinal lymph nodes, trachea, lung and mainstem bronchi, heart, diaphragm, liver, spleen, pancreas,
kidneys, adrenal glands, esophagus, stomach (fore and glandular), intestine (four levels), urinary bladder, prostate,
gonads, interscapular fat pad, subcutaneous and mesenteric lymph nodes, and any other organs or tissues with
pathologic lesions.
17 http://www.ramazzini.it/fondazione/foundation.asp.
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1 analytical grade. No unexposed control groups were included in these studies. However, the
2 author provided pathology data from historical records of untreated Swiss mice of the Eppley
3 colony used in two separate chronic studies, one involving 100 untreated males and 100
4 untreated females (Toth etal., 1977) and the other involving 100 untreated females
5 histopathological analyzed by Apaja (Apaja, 1980).
6 Mice in the Apaja (1980) study were housed five/plastic cage and fed Wayne Lab-Blox
7 pelleted diet. Water was available ad libitum throughout life. Liquid consumption per animal was
8 measured at 3 times/week. The methanol dose in the dermal study (females only) was 21.3 mg
9 (532 mg/kg-day using an average weight of 0.04 kg as approximated from Figure 4 of the study),
10 three times/week. The methanol doses in the drinking water study were reported as 22.6, 40.8
11 and 84.5 mg/day (560, 1,000 and 2,100 mg/kg-day using an average weight of 0.04 kg as
12 approximated from Figures 14-16 of the study) for females, and 24.6, 43.5 and 82.7 mg/day
13 (550, 970, and 1,800 mg/kg-day using an average weight of 0.045 kg as approximated from
14 Figures 14-16 of the study) for males, 6 days/week. The animals were checked daily and body
15 weights were monitored weekly. The in-life portion of the experiment ended at 120 weeks with
16 the death of the last animal. Like the Soffritti et al. (2002) study, test animals were sacrificed and
17 necropsied when moribund.18
18 The authors reported that survival of the methanol exposed females of the drinking water
19 study was lower than untreated historical controls (p < 0.05), but no significant differences in
20 survival was noted for males. An increase in liver parenchymal cell necrosis was reported in the
21 male and female high-dose groups, with the incidence in females (8%) being significant
22 (p < 0.01) relative to untreated historical controls. Incidence of acute pancreatitis was higher in
23 high-dose males (p <0.001), but did not appear to be dose-related in females, increasing at the
24 mid- (p <0.0001) and low-doses (p <0.01) when compared to historical controls but not
25 appearing at all in the high-dose females. Significant increases relative to untreated historical
26 controls were noted in amyloidosis of the spleen, nephropathy and pneumonia, but the increases
27 did not appear to be dose related.
18 The following tissues were fixed in 10% formalin (pH 7.5), embedded in paraffin, sectioned, stained routinely
with hematoxylin and eosin (special stains used as needed) and histologically evaluated: skin, lungs, liver spleen,
pancreas, kidneys, adrenal glands, esophagus, stomach, small and large intestines, rectum, urinary bladder, uterus
and ovaries or testes, prostate glands and tumors or other gross pathological lesions.
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4.2.2. Inhalation Studies
4.2.2.1. Acute Toxicity
1 Lewis (1992) reported a 4-hour median lethal concentration (LCso) for methanol in rats of
2 64,000 ppm (83,867 mg/m3).
3 Japan's NEDO sponsored a series of toxicological tests on monkeys (M fascicularis),
4 rats, and mice, using inhalation exposure.19 These are unpublished studies; accordingly, they
5 were externally peer reviewed by EPA in 2009.20 A short-term exposure study evaluated
6 monkeys (sex unspecified) exposed to 3,000 ppm (3,931 mg/m3), 21 hours/day for 20 days
7 (1 animal), 5,000 ppm (6,552 mg/m3) for 5 days (1 animal), 5,000 ppm (6,552 mg/m3) for
8 14 days (2 animals), and 7,000 and 10,000 ppm (9,173 and 13,104 mg/m3, respectively) for up to
9 6 days (1 animal at each exposure level) (NEDO, 1987). Most of the experimental findings were
10 discussed descriptively in the report, without specifying the extent of change for any of the
11 effects in comparison to seven concurrent controls. However, the available data indicate that
12 clinical signs of toxicity were apparent in animals exposed to 5,000 ppm (all exposure durations)
13 or higher concentrations of methanol. These included reduced movement, crouching, weak
14 knees, involuntary movements of hands, dyspnea, and vomiting. In the discussion section of the
15 summary report, the authors stated that there was a sharp increase in the blood levels of methanol
16 and formic acid in monkey exposed to >3,000 ppm (3,931 mg/m3) methanol. They reported that
17 methanol and formic acid concentrations in the blood of monkeys exposed to 3,000 ppm or less
18 were 80 mg/L and 30 mg/L, respectively.21 In contrast, monkeys exposed to 5,000 ppm or higher
19 concentrations of methanol had blood methanol and formic acid concentrations of 5,250 mg/L
20 and 1,210 mg/L, respectively. Monkeys exposed to 7,000 ppm and 10,000 ppm became critically
21 ill and had to be sacrificed prematurely. Food intake was said to be little affected at 3,000 ppm,
22 but those exposed to 5,000 ppm or more showed a marked reduction. Clinically, the monkeys
23 exposed to 5,000 ppm or more exhibited reduced movement, weak knees, and involuntary
24 movement of upper extremities, eventually losing consciousness and dying.
19 In their bioassays, NEDO (NEDO. 1987) used inbred rats of the F344 or Sprague-Dawley strain, inbred mice of
the B6C3F1 strain and wild-caught M. fascicularis monkeys imported from Indonesia. The possibility of disease
among wild-caught animals is a concern, but NEDO (NEDO. 1987) state that the monkeys were initially
quarantined for 9 weeks and measures were taken throughout the studies against the transmission of pathogens for
infectious diseases. The authors indicated that "no infectious disease was observed in monkeys" and that "subjects
were healthy throughout the experiment."
20 An external peer review (ERG. 2009) was conducted by EPA in 2009 to evaluate the accuracy of experimental
procedures, results, and interpretation and discussion of the findings presented in these study reports.
21 Note that Burbacher et al. (1999a) and Burbacher et al. (20Q4a) measured blood levels of methanol and formic
acid in control monkeys of 2.4 mg/L and 8.7 mg/L, respectively (see Table 3-3).
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1 There were no significant changes in growth, with the exception of animals exposed to
2 the highest concentration, where body weight was reduced by 13%. There were few compound-
3 related changes in hematological or clinical chemistry effects, although animals exposed to 7,000
4 and 10,000 ppm showed an increase in white blood cells. A marked change in blood pH values at
5 the 7,000 ppm and 10,000 ppm levels (values not reported) was attributed to acidosis due to
6 accumulation of formic acid. The authors reported that no clinical or histopathological effects of
7 the visual system were apparent, but that exposure to 3,000 ppm (3,931 mg/m3) or more caused
8 dose-dependent fatty degeneration of the liver, and exposure to 5,000 ppm (6,552 mg/m3) or
9 more caused vacuolar degeneration of the kidneys, centered on the proximal uriniferous tubules.
10 A range of histopathologic changes to the CNS was apparently related to treatment. Severity of
11 the effects was increased with exposure concentration. Lesions included characteristic
12 degeneration of the bilateral putamen, caudate nucleus, and claustrum, with associated edema in
13 the cerebral white matter. CNS effects reported in this and the NEDO chronic monkey inhalation
14 study are discussed in greater detail in Section 4.4.2 "Inhalation Neurotoxicity Studies."
15 The NEDO (1987) studies in nonhuman primates, including the chronic study discussed
16 below, have multiple deficiencies that make them difficult to interpret. The reports lack a full
17 description of the materials and methods and raw data from the experiments. The data gaps
18 (e.g., materials and methods, statistical methods, data) are profound and the group sizes are too
19 small to support rigorous statistical analysis. At best, they provide a descriptive, rather than
20 quantitative, evaluation of the inhalation toxicity of methanol (ERG, 2009).
4.2.2.2. Subchronic Toxicity
21 A number of experimental studies have examined the effects of subchronic exposure to
22 methanol via inhalation. For example, Sayers et al. (1944) employed a protocol in which 2 male
23 dogs were repeatedly exposed (8 times daily for 3 minutes/exposure) to 10,000 ppm
24 (13,104 mg/m3) methanol for 100 days. One of the dogs was observed for a further 5 days before
25 sacrifice; the other dog was observed for 41 days postexposure. There were no clinical signs of
26 toxicity, and both gained weight during the study period. Blood samples were drawn on a regular
27 basis to monitor hematological parameters, but few if any compound-related changes were
28 observed. Ophthalmoscopic examination showed no incipient anomalies at any point during the
29 study period. Median blood concentrations of methanol were 65 mg/L (range 0-280 mg/L) for
30 one dog, and 140 mg/L (70-320 mg/L) for the other.
31 White et al. (1983) exposed 4 male Sprague-Dawley rats/group, 6 hours/day, 5 days/week
32 to 0, 200, 2,000, or 10,000 ppm (0, 262, 2,621, and 13,104 mg/m3) methanol for periods of 1, 2,
33 4, and 6 weeks. Additional groups of 6-week-exposure animals were granted a 6-week
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1 postexposure recovery period prior to sacrifice. The lungs were excised intact and lavaged
2 6 times with known volumes of physiological saline. The lavage supernatant was then assayed
3 for lactate dehydrogenase (LDH) and TV-acetyl-^-D-glucosaminidase (/?-NAG) activities. Other
4 parameters monitored in relation to methanol exposure included absolute and relative lung
5 weights, lung DNA content, protein, acid RNase and acid protease, pulmonary surfactant,
6 number of free cells in lavage/unit lung weight, surface protein, LDH, and /?-NAG. As discussed
7 by the authors, none of the monitored parameters showed significant changes in response to
8 methanol exposure.
9 Andrews et al. (1987) carried out a study of methanol inhalation in five Sprague-Dawley
10 rats/sex/group and three M. fascicularis monkeys/sex/group, 6 hours/day, 5 days/week, to 0, 500,
11 2,000, or, 5,000 ppm (0, 660, 2,620, and 6,552 mg/m3) methanol for 4 weeks. Clinical signs were
12 monitored twice daily, and all animals were given a physical examination once a week. Body
13 weights were monitored weekly, and animals received an ophthalmoscopic examination before
14 the start of the experiment and at term. Animals were sacrificed at term by exsanguination
15 following i.v. barbiturate administration. A gross necropsy was performed, weights of the major
16 organs were recorded, and tissues and organs taken for histopathologic examination. As
17 described by the authors, all animals survived to term with no clinical signs of toxicity among
18 the monkeys and only a few signs of irritation to the eyes and nose among the rats. In the latter
19 case, instances of mucoid nasal discharges appeared to be dose related. There were no
20 differences in body weight gain among the groups of either rats or monkeys, and overall,
21 absolute and relative organ weights were similar to controls. The only exception to this was a
22 decrease in the absolute adrenal weight of female high-concentration monkeys and an increase in
23 the relative spleen weight of mid-concentration female rats. These changes were not considered
24 by the authors to have biological significance. For both rats and monkeys, there were no
25 compound-related changes in gross pathology, histopathology, or ophthalmoscopy. These data
26 suggest a NOAEL of 5,000 ppm (6,600 mg/m3) for Sprague-Dawley rats and monkeys under the
27 conditions of the experiment.
28 Two studies by Poon et al. (1995; 1994) examined the effects of methanol on Sprague-
29 Dawley rats, when inhaled for 4 weeks. The effects of methanol were evaluated in comparison to
30 those of toluene and toluene/methanol mixtures (Poon et al., 1994), and to gasoline and
31 gasoline/methanol mixtures (Poon etal., 1995). In the first case (Poon etal., 1994), 10 Sprague-
32 Dawley rats/sex/group were exposed via inhalation, 6 hours/day, 5 days/week to 0, 300, or
33 3,000 ppm (0, 393, 3,930 mg/m3) methanol for 4 weeks. Clinical signs were monitored daily, and
34 food consumption and body weight gain were monitored weekly. Blood was taken at term for
35 hematological and clinical chemistry determinations. Weights of the major organs were recorded
36 at necropsy, and histopathologic examinations were carried out. A 10,000 xg Hver supernatant
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1 was prepared from each animal to measure aniline hydroxylase, aminoantipyrine N-demethylase,
2 and ethoxyresorufin-O-deethylase activities. For the most part, the responses to methanol alone
3 in this experiment were unremarkable. All animals survived to term, and there were no clinical
4 signs of toxicity among the groups. Body weight gain and food consumption did not differ from
5 controls, and there were no compound-related effects in hematological or clinical chemistry
6 parameters or in hepatic mixed function oxidase activities. However, the authors described a
7 reduction in the size of thyroid follicles that was more obvious in female than male rats. The
8 authors considered this effect to possibly have been compound related, although the incidence of
9 this feature for the 0, 300, and 3,000 ppm-receiving females was 0/6, 2/6, and 2/6, respectively.
10 The second experimental report by Poon et al. (1995) involved the exposure of
11 15 Sprague-Dawley rats/sex/group, 6 hours/day, 5 days/week for 4 weeks to 0 or 2,500 ppm
12 (0 and 3,276 mg/m3) to methanol as part of a study on the toxicological interactions of methanol
13 and gasoline. Many of the toxicological parameters examined were the same as those described
14 in Poon et al. (1994) study. However, in this study urinalysis featured the determination of
15 ascorbic and hippuric acids. Additionally, at term, the lungs and tracheae were excised and
16 aspirated with buffer to yield bronchoalveolar lavage fluid that was analyzed for ascorbic acid,
17 protein, and the activities of gamma-glutamyl transferase (y-GT), AP and LDH. Few if any of the
18 monitored parameters showed any differences between controls and those animals exposed to
19 methanol alone. However, two male rats had collapsed right eyes, and there was a reduction in
20 relative spleen weight in females exposed to methanol. Histopathologic changes in methanol-
21 receiving animals included mild panlobular vacuolation of the liver in females and some mild
22 changes to the upper respiratory tract, including mucous cell metaplasia. The incidence of the
23 latter effect, though higher, was not significantly different than controls in rats exposed to
24 2,500 ppm (3,267 mg/m3) methanol. However, there were also signs of an increased severity of
25 the effect in the presence of the solvent. No histopathologic changes were seen in the lungs or
26 lower respiratory tract of rats exposed to methanol alone.
4.2.2.3. Chronic Noncancer Toxicity
27 Information on the chronic noncancer toxicity of inhalation exposure to methanol has
28 come from NEDO (1987) which includes the results of experiments on (1) monkeys exposed for
29 up to 3 years, (2) rats and mice exposed for 12 months, (3) mice exposed for 18 months, and
30 (4) rats exposed for 2 years. These are unpublished studies; accordingly, they were externally
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1 peer reviewed by EPA in 2009.22 Neurotoxic effects reported in the monkey studies are discussed
2 in more detail in Section 4.4.2.
3 In the monkeys, 8 animals (sex unspecified) were exposed to 10, 100, or 1,000 ppm (13,
4 131, and 1,310 mg/m3) methanol, 21 hours/day, for 7 months (2 animals), 19 months,
5 (3 animals), or 29 months (3 animals). There was no indication in the NEDO (1987) report that
6 this study employed a concurrent control group. One of the 3 animals receiving 100 ppm
7 methanol and scheduled for sacrifice at 29 months was terminated at 26 months. Clinical signs
8 were monitored twice daily, body weight changes and food consumption were monitored weekly,
9 and all animals were given a general examination under anesthetic once a month. Blood was
10 collected for hematological and clinical chemistry tests at term, and all animals were subject to a
11 histopathologic examination of the major organs and tissues.
12 While there were no clinical signs of toxicity in the low-concentration animals, there was
13 some evidence of nasal exudate in monkeys in the mid-concentration group. High-concentration
14 (1,000 ppm) animals also displayed this response and were observed to scratch themselves over
15 their whole body and crouch for long periods. Food and water intake, body temperature, and
16 body weight changes were the same among the groups. NEDO (1987) reported that there was no
17 abnormality in the retina of any monkey. When animals were examined with an
18 electrocardiogram, there were no abnormalities in the control or 10 ppm groups. However, in the
19 100 ppm group, one monkey showed a negative change in the T wave. All 3 monkeys exposed to
20 1,000 ppm (1,310 mg/m3) displayed this feature, as well as a positive change in the Q wave. This
21 effect was described as a slight myocardial disorder and suggests that 10 ppm (13.1 mg/m3) is a
22 NOAEL for chronic myocardial effects of methanol and mild respiratory irritation. There were
23 no compound-related effects on hematological parameters. However, 1 monkey in the 100 ppm
24 (131 mg/m3) group had greater than normal amounts of total protein, neutral lipids, total and free
25 cholesterol, and glucose, and displayed greater activities of ALT and aspartate transaminase
26 (AST). The authors expressed doubts that these effects were related to methanol exposure and
27 speculated that the animal suffered from liver disease.23
28 Histopathologically, no degeneration of the optical nerve, cerebral cortex, muscles, lungs,
29 trachea, tongue, alimentary canal, stomach, small intestine, large intestine, thyroid gland,
30 pancreas, spleen, heart, aorta, urinary bladder, ovary or uterus were reported (neuropathological
31 findings are discussed in Section 4.4.2). Most of the internal organs showed no compound-
32 related histopathologic lesions. However, there were signs of incipient fibrosis and round cell
33 infiltration of the liver in monkeys exposed to 1,000 ppm (1,310 mg/m3) for 29 months. NEDO
22 An external peer review (ERG. 2009) was conducted by EPA in 2009 to evaluate the accuracy of experimental
procedures, results, and interpretation and discussion of the findings presented in these study reports.
23 Ordinarily, the potential for liver disease in test animals would be remote, but may be a possibility in this case
given that these monkeys were captured in the wild.
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1 (1987) indicated that this fibrosis occurred in 2/3 monkeys of the 1,000 ppm group to a "strictly
2 limited extent." They also qualitatively reported a dose-dependent increase in "fat granules" in
3 liver cells "centered mainly around the central veins" at all doses, but did not provide any
4 response data. The authors state that 1,000 ppm (1,310 mg/m3) represents a chronic lowest-
5 observed-adverse-effect level (LOAEL) for hepatic effects of inhaled methanol, suggesting that
6 the no effect level would be 100 ppm (131 mg/m3). However, this is a tenuous determination
7 given the lack of information on the pathological progression and significance of the appearance
8 of liver cell fat granules at exposures below 1,000 ppm and the lack detail (e.g., time of sacrifice)
9 for the control group.
10 Dose-dependent changes were observed in the kidney; NEDO (1987) described the
11 appearance of Sudan-positive granules in the renal tubular epithelium at 100 ppm (131 mg/m3)
12 and 1,000 (1,310 mg/m3) and hyalinization of the glomerulus and penetration of round cells into
13 the renal tubule stroma of monkeys exposed to methanol at 1,000 (1,310 mg/m3). The former
14 effect was more marked at the higher concentration and was thought by the authors to be
15 compound-related. This would indicate a no effect level at 10 ppm (13.1 mg/m3) for the chronic
16 renal effects of methanol. The authors observed atrophy of the tracheal epithelium in four
17 monkeys. However, the incidence of these effects was unrelated to dose and therefore, could not
18 be unequivocally ascribed to an effect of the solvent. No other histopathologic abnormalities
19 were related to the effects of methanol. Confidence in these determinations is considerably
20 weakened by limited study details (e.g., materials and methods, statistical methods, data), small
21 group sizes and uncertainty over whether a concurrent control group was used in the chronic
22 study.24 In general, external peer reviewers of the NEDO (1987) monkey studies stated that the
23 deficiencies in these reports were broad and significant, precluding the use of these studies for
24 quantitative dose-response assessment (ERG, 2009). Although the limited information available
25 from the NEDO (1987) summary report suggests that 100 ppm (131 mg/m3) may be an effect
26 level for myocardial effects, renal effects and neurotoxicity (see Section 4.4.2) following
27 continuous, chronic exposure to methanol, NOAEL and LOAEL values are not derived for any
28 of the NEDO (1987) monkey studies.
29 NEDO also performed 12-months inhalation studies in rats and mice (NEDO, 1987), an
30 18-month inhalation study in mice (NEDO, 1985a) and a 24-month inhalation study in rats
31 (NEDO, 1985b). External peer reviewers generally indicated that these rodent studies used good
32 experimental designs, group sizes, endpoints and quality assurance procedures that were
33 consistent with the OECD guidelines in place at the time. However, the reports available for the
34 chronic studies (NEDO, 1985a, b) were far more detailed than the summary reports available for
24 All control group responses were reported in a single table in the section of the NEDO (1987) report that describes
the acute monkey study, with no indication as to when the control group was sacrificed.
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1 the 12-month studies (NEDO, 1987), which suffered from many of the same reporting issues
2 identified for the NEDO monkey studies, including a lack a full description of the materials and
3 methods and raw data from the experiments. For all of the NEDO (1987) mouse, rat and monkey
4 studies, parameters should have been assessed by one way analysis of variance (ANOVA), rather
5 than the t-test comparisons with controls that were apparently performed (ERG, 2009).
6 NEDO (1987) describes a 12-month inhalation study in which 20 F344 rats/sex/group
7 were exposed to 0, 10, 100, or 1,000 ppm (0, 13.1, 131, and 1,310 mg/m3) methanol,
8 approximately 20 hours/day, for a year. Clinical signs of toxicity were monitored daily; body
9 weights and food consumption were recorded weekly for the first 13 weeks, then monthly. Blood
10 samples were drawn at term to measure hematological and clinical chemistry parameters.
11 Weights of the major organs were monitored at term, and a histopathologic examination was
12 carried out on all major organs and tissues. Survival was high among the groups; one high-
13 concentration female died on day 337 and one low-concentration male died on day 340. As
14 described by the authors, a number of procedural anomalies arose during this study. For example,
15 male controls in two cages lost weight because of an interruption to the water supply. Another
16 problem was that the brand of feed was changed during the study. Fluctuations in some clinical
17 chemistry and hematological parameters were recorded. The authors considered the fluctuations
18 to be minor and within the normal range. Likewise, a number of histopathologic changes were
19 observed, which, in every case, were considered to be unrelated to exposure level or due to
20 aging.
21 A companion experiment featured the exposure of 30 B6C3F1 mice/sex/group for 1 year
22 to the same concentrations as the F344 rats (NEDO, 1987). Broadly speaking, the same suite of
23 toxicological parameters was monitored as described above, with the addition of urinalysis.
24 10 mice/sex/group were sacrificed at 6 months to provide interim data on the parameters under
25 investigation. A slight atrophy in the external lacrimal gland was observed in both sexes and was
26 significant in the 1,000 ppm male group compared with controls. An apparently dose-related
27 increase in moderate fatty degeneration of hepatocytes was observed in males (1/20, 4/20, 6/20
28 and 8/20 in the 0, 10, 100, and 1,000 ppm dose groups, respectively) which was significantly
29 increased over controls at the 1,000 ppm dose. However a high (10/20) incidence of moderate to
30 severe fatty degeneration was observed in untreated animals maintained outside of the chamber.
31 In addition, there was a clear correlation between fatty degeneration and body weight (a change
32 which was not associated with treatment at 12 months); heavier animals tended to have more
33 severe cases of fatty degeneration. Thus, methanol's role in fatty liver degeneration in mice is
34 questionable, especially given the failure to confirm the finding in the 18-month study described
35 below (ERG, 2009). The possibility of renal deficits due to methanol exposure was suggested by
36 the appearance of protein in the urine. However, this effect was also seen in controls and did not
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1 display a dose-response effect. Therefore, it is unlikely to be a consequence of exposure to
2 methanol. NEDO (1987) reported other histopathologic and biochemical (e.g., urinalysis and
3 hematology) findings that do not appear to be related to treatment, including a number of what
4 were considered to be spontaneous tumors in both control and exposure groups.
5 NEDO (1987. 1985a)25 exposed 52 male and 53 female B6C3F1 mice/group for
6 18 months at the same concentrations of methanol (0, 10, 100 and 1,000 ppm) and with a similar
7 experimental protocol to that described in the 12-month studies.26 Animals were sacrificed at the
8 end of the 18-month exposure period. NEDO (1985a) reported that "there was no
9 microbiological contamination that may have influenced the result of the study" and that the
10 study included an assessment of general conditions, body weight change, food consumption rate,
11 laboratory tests (urinalysis, hematological, and plasma biochemistry) and pathological tests
12 (pathological autopsy,27 organ weight check and histopathology28). As stated in the summary
13 report (NEDO, 1987), a few animals showed clinical signs of toxicity, but the incidence of these
14 responses was not related to dose. Likewise, there were no compound-related changes in body
15 weight increase, food consumption,29 urinalysis, hematology, or clinical chemistry parameters.
16 High-concentration males had lower testis weights compared to control males. Significant
17 differences were detected for both absolute and relative testis weights. One animal in the high-
18 dose group had severely atrophied testis weights, approximately 25% of that of the others in the
19 dose group. Exclusion of this animal in the analysis still resulted in a significant difference in
20 absolute testis weight compared to controls but resulted in no difference in relative testis weight.
21 High-concentration females had higher absolute kidney and spleen weights compared to controls,
22 but there was no significant difference in these organ weights relative to body weight. At
23 necropsy, there were signs of swelling in spleen, preputial glands, and uterus in some animals.
24 Some animals developed nodes in the liver and lung although, according to the authors, none of
25 these changes were treatment-related. NEDO (1985a) reported that all non-neoplastic changes
26 were "nonspecific and naturally occurring changes that are often experienced by 18-month old
25 This study is described in a summary report (NEDO. 1987) and a more detailed, eight volume translation of the
original chronic mouse study report (NEDO. 1985a). The translation was submitted to EPA by the Methanol
Institute and has been certified by NEDO as accurate and complete (Hashimoto. 2008). An external peer review
(ERG. 2009) was conducted by EPA in 2009 to evaluate the accuracy of experimental procedures, results, and
interpretation and discussion of the findings presented in these study reports.
26 The authors reported that "[t]he levels of methanol turned out to be ~4 ppm in low level exposure group (10 ppm)
for ~11 weeks from week 43 of exposure due to the analyzer malfunction" and that "the average duration of
methanol exposure was 19.1 hours/day for both male and female mice."
27 Autopsy was performed on all cases to look for gross lesions in each organ.
28 Complete histopathological examinations were performed for the control group and high-dose (1,000 ppm)
groups. Only histopathological examinations of the liver were performed on the low- and medium-level exposure
groups because no chemical-related changes were found in the high-level exposure group and because liver changes
were noted in the 12-month mouse study (NEDO. 1987).
29 NEDO (NEDO. 1985a) reports sporadic reductions in food consumption of the 1,000 ppm group, but no
associated weight loss or abnormal test results.
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1 B6C3F1 mice" and that fatty degeneration of liver that was suspected to occur dose-dependently
2 in the 12-month NEDO (1987) study was not observed in this study NEDO (1985a).
3 Another study reported in NEDO (1987, 1985b)30 was a 24-month bioassay in which
4 52 F344 rats/sex/group were kept in whole body inhalation chambers containing 0, 10, 100, or
5 1,000 ppm (0, 13.1, 131, and 1,310 mg/m3) methanol vapor. Animals were maintained in the
6 exposure chambers for approximately 19.5 hours/day for a total of 733-736 days (males) and
7 740-743 days (females). Animals were monitored once a day for clinical signs of toxicity, body
8 weights were recorded once a week, and food consumption was measured weekly from a
9 24-animal subset from each group. Urinalysis was carried out on the day prior to sacrifice for
10 each animal, the samples being monitored for pH, protein, glucose, ketones, bilirubin, occult
11 blood, and urobilinogen. Routine clinical chemistry and hematological measurements were
12 carried out and all animals were subject to necropsy at term, with a comprehensive
13 histopathological examination of tissues and organs.31
14 There was some fluctuation in survival rates among the groups in the rat study, though
15 apparently unrelated to exposure concentration.32 In all groups, at least 60% of the animals
16 survived to term. A number of toxicological responses were described by the authors, including
17 atrophy of the testis, cataract formation, exophthalmia, small eye ball, alopecia, and paralysis of
18 the hind leg. However, according to the authors, the incidence of these effects were unrelated to
19 dose and more likely represented effects of aging. NEDO (1985b) reported a mild, nonsignificant
20 (4%) body weight suppression among 1,000 ppm females between 51 and 72 weeks, but that
21 body weight gain was largely similar among the groups for the duration of the experiment. Food
22 consumption was significantly lower than controls in high-concentration male rats during the day
23 210-365 time interval, but no corresponding weight loss was observed. Among hematological
24 parameters, mid- and high-concentration females had a significantly (p < 0.05) higher differential
25 leukocyte count than controls, but dose dependency was not observed. Serum total cholesterol,
26 triglyceride, free fatty acid, and phospholipid concentrations were significantly (p < 0.05) lower
27 in high-concentration females compared to controls. Likewise, serum sodium concentrations
28 were significantly (p < 0.05) lower in mid- and high-concentration males compared to controls.
30 This study is described in a summary report (NEDO. 1987) and a more detailed, 10-volume translation of the
original chronic rat study report (NEDO. 1985b). The translation was submitted to EPA by the Methanol Institute
and has been certified by NEDO as accurate and complete (Hashimoto. 2008). An external peer review (ERG. 2009)
was conducted by EPA in 2009 to evaluate the accuracy of experimental procedures, results, and interpretation and
discussion of the findings presented in these study reports.
31 Complete histopathological examinations were performed on the cases killed on schedule (week 104) among the
control and high-exposure groups, and the cases that were found dead/ killed in extremis of all the groups. Because
effects were observed in male and female kidneys, male lungs, as well as female adrenal glands of the high-level
exposure group, these organs were histopathologically examined in the low- and mid-exposure groups.
32Survival at the time of exposure termination (24 months) was 69%, 65%, 81%, and 65% for males and 60%, 63%,
60% and 67% for females of the control, low-, mid- and high-exposure groups, respectively.
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1 High-concentration females had significantly lower (p < 0.05) serum concentrations of inorganic
2 phosphorus but significantly (p < 0.05) higher concentrations of potassium compared to controls.
3 Glucose levels were elevated in the urine of high-concentration male rats relative to controls, and
4 female rats had lower pH values and higher bilirubin levels in mid- and high-concentration
5 groups relative to controls. In general, NEDO (1987, 1985b) reported that these variations in
6 urinary, hematology, and clinical chemistry parameters were not related to chemical exposure.
7 NEDO (1987) reported that there was little change in absolute or relative weights of the
8 major organs or tissues. When the animals were examined grossly at necropsy, there were some
9 signs of swelling in the pituitary and thyroid, but these effects were judged to be unrelated to
10 treatment. The most predominant effect was the dose-dependent formation of nodes in the lung
11 of males (2/52, 4/52, 5/52, and 10/52 \p < 0.01] for control, low-, mid-, and high-concentration
12 groups, respectively). Histopathologic examination pointed to a possible association of these
13 nodes with the appearance of pulmonary adenoma (1/52, 5/52, 2/52, and 6/52 for control, low-,
14 mid- and high-concentration groups, respectively) and a single pulmonary adenocarcinoma in the
15 high-dose group (1/52).
16 The authors identified a tentative NOAEL of 100 ppm for the 12-month and 18-month
17 mouse and the 12-month and 24-month rat studies on page 293 of their summary report (NEDO,
18 1987). However, peer reviewers of these studies expressed reservations about the dose-response
19 data quality (e.g., histopathology was only performed on the 10 and 100 ppm groups if the 1000
20 ppm group demonstrated statistically significant difference from controls) and interpretation
21 (e.g., statistical methods were incompletely described and, in some cases, improperly applied)
22 (ERG, 2009). In addition, the evidence for dose-related effects at 1,000 ppm was weak for both
23 the mouse and rat studies. Thus, EPA assigns a low weight-of evidence determination to the
24 1,000 ppm LOAEL identified for these chronic mouse and rat studies.
4.3. Reproductive and Developmental Studies - Oral and Inhalation
25 Many studies have been conducted to investigate the reproductive and developmental
26 toxicity of methanol. The purpose of these studies was principally to determine if methanol has a
27 similar toxicology profile to another widely studied teratogen, ethanol.
4.3.1. Oral Reproductive and Developmental Studies
28 Three studies were identified that investigated the reproductive and developmental effects
29 of methanol in rodents via the oral route (Fu et al., 1996; Sakanashi etal., 1996; Rogers et al.,
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1 1993b). Two of these studies also investigated the influence of folic acid-deficient (FAD) diets
2 on the effects of methanol exposures (Fu et al., 1996; Sakanashi etal., 1996).
3 Rogers et al. (1993b) conducted a developmental toxicity study in which methanol in
4 water was administered to pregnant female CD-I mice via gavage on GD6-GD15. Eight test
5 animals received 4 g/kg-day methanol given in 2 daily doses of 2 g/kg; 4 controls received
6 distilled water. By analogy to the protocol of an inhalation study of methanol that was described
7 in the same report, it is assumed that dams were sacrificed on GDI7, at which point implantation
8 sites, live and dead fetuses, resorptions/litter, and the incidences of external and skeletal
9 anomalies and malformations were determined. In the brief summary of the findings provided by
10 the authors, it appears that cleft palate (43.5% per litter versus 0% in controls) and exencephaly
11 (29% per litter versus 0% in controls) were the prominent external defects following maternal
12 methanol exposure by gavage. Likewise, an increase in totally resorbed litters and a decrease in
13 the number of live fetuses per litter were evident. However, it is possible that these effects may
14 have been caused or exacerbated by the high bolus dosing regimen employed. It is also possible
15 that effects were not observed due to the limited study size. The small number of animals in the
16 control group relative to the test group limits the power of this study to detect treatment-related
17 responses.
18 Sakanashi et al. (1996) tested the influence of dietary folic acid intake on various
19 reproductive and developmental effects observed in CD-I mice exposed to methanol. Starting
20 5 weeks prior to breeding and continuing for the remainder of the study, female CD-I mice were
21 fed folic acid free diets supplemented with 400 (low), 600 (marginal), or 1,200 (sufficient) nmol
22 folic acid/kg. After 5 weeks on their respective diets, females were bred with CD-I male mice.
23 On GD6-GD15, pregnant mice in each of the diet groups were given twice-daily gavage doses of
24 2.0 or 2.5 g/kg-day methanol (total dosage of 4.0 or 5.0 g/kg-day). On GDIS, mice were weighed
25 and killed, and the liver, kidneys, and gravid uteri removed and weighed. Maternal liver and
26 plasma folate levels were measured; and implantation sites, live and dead fetuses, and
27 resorptions were counted. Fetuses were weighed individually and examined for cleft palate and
28 exencephaly. One third of the fetuses in each litter were examined for skeletal morphology. They
29 observed an approximate 50% reduction in liver and plasma folate levels in the mice fed low
30 versus sufficient folic acid diets in both the methanol exposed and unexposed groups. Similar to
31 Rogers et al. (1993b), Sakanashi et al. (1996) observed that an oral dose of 4-5 g/kg-day
32 methanol during GD6-GD15 resulted in an increase in cleft palate in mice fed sufficient folic
33 acid diets, as well as an increase in resorptions and a decrease in live fetuses per litter. They did
34 not observe an increase in exencephaly in the folic acid sufficient (FAS) group at these doses,
35 and the authors suggest that this may be due to diet and the source of CD-I mice differing
36 between the two studies.
July 2013 4-21 Draft - Do Not Cite or Quote
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1 In the case of the animals fed the folate deficient diet, there was a 50% reduction in
2 maternal liver folate concentration and a threefold increase in the percentage of litters affected by
3 cleft palate (86.2% versus 34.5% in mice fed sufficient folic acid) and a 10-fold increase in the
4 percentage of litters affected by exencephaly (34.5% versus 3.4% in mice fed sufficient folic
5 acid) at the 5 g/kg methanol dose. Sakanashi et al. (1996) speculate that the increased methanol
6 effect from the FAD diet could have been due to an increase in tissue formate levels (not
7 measured) or to a critical reduction in conceptus folate concentration following the methanol
8 exposure. Plasma and liver folate levels at GDIS within each dietary group were not
9 significantly different between exposed versus unexposed mice. However, these measurements
10 were taken 3 days after methanol exposure. Dorman et al. (1995) observed a transient decrease in
11 maternal red blood cells (RBCs) and conceptus folate levels within 2 hours following inhalation
12 exposure to 15,000 ppm methanol on GD8. Thus, it is possible that short-term reductions in
13 available folate during GD6-GD15 may have affected fetal development.
14 Fu et al. (1996) also tested the influence of dietary folic acid intake on reproductive and
15 developmental effects observed in CD-I mice exposed to methanol. This study was performed
16 by the same laboratory and used a similar study design and dosing regimen as Sakanashi et al.
17 (1996), but exposed the pregnant mice to only the higher 2.5 g/kg-day methanol (total dosage of
18 5.0 g/kg-day) on GD6-GD10. Like Sakanashi et al. (1996), Fu et al. (1996) measured maternal
19 liver and plasma folate levels on GDIS and observed similar, significant reductions in these
20 levels for the FAD versus FAS mice. However, Fu et al. (1996) also measured fetal liver folate
21 levels at GDIS. This measurement does not address the question of whether methanol exposure
22 caused short-term reductions in fetal liver folate because it was taken 8 days after the
23 GD6-GD10 exposure period. However, it did provide evidence regarding the extent to which a
24 maternal FAD diet can impact fetal liver folate levels in this species and strain. Significantly, the
25 maternal FAD diet had a greater impact on fetal liver folate than maternal liver folate levels.
26 Relative to the FAS groups, fetal liver folate levels in the FAD groups were reduced 2.7-fold for
27 mice not exposed to methanol (1.86 ± 0.15 nmol/g in the FAD group versus 5.04 ± 0.22 nmol/g
28 in the FAS group) and 3.5-fold for mice exposed to methanol (1.69 ± 0.12 nmol/g in the FAD
29 group versus 5.89 ± 0.39 nmol/g in the FAS group). Maternal folate levels in the FAD groups
30 were only reduced twofold both for mice not exposed (4.65 ± 0.37 versus 9.54 ± 0.50 nmol/g)
31 and exposed (4.55 ± 0.19 versus 9.26 ± 0.42 nmol/g). Another key finding of the Fu et al. (1996)
32 study is that methanol exposure during GD6-GD10 appeared to have similar fetotoxic effects,
33 including cleft palate, exencephaly, resorptions, and decrease in live fetuses, as the same level of
34 methanol exposure administered during GD6-GD15 (Sakanashi et al., 1996; Rogers et al.,
35 1993b). This is consistent with the hypothesis made by Rogers et al. (1993b) that the critical
36 period for methanol-induced cleft palate and exencephaly in CD-I mice is within GD6-GD10.
July 2013 4-22 Draft - Do Not Cite or Quote
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1 As in the studies of Sakanashi et al. (1996) and Rogers et al. (1993b), Fu et al. (1996) reported a
2 higher incidence of cleft palate than exencephaly.
4.3.2. Inhalation Reproductive and Developmental Studies
3 Nelson et al. (1985) exposed 15 pregnant Sprague-Dawley rats/group to 0, 5,000, 10,000,
4 or 20,000 ppm (0, 6,552, 13,104, and 26,209 mg/m3) methanol (99.1% purity) for 7 hours/day.
5 Exposures were conducted on GDI-GDI9 in the two lower concentration groups and
6 GD7-GD15 in the highest concentration group, apparently on separate days. Two groups of
7 15 control rats were exposed to air only. Day 1 blood methanol levels measured 5 minutes after
8 the termination of exposure in NP rats that had received the same concentrations of methanol as
9 those animals in the main part of the experiment were 1.00 ± 0.21, 2.24 ± 0.20, and
10 8.65 ± 0.40 mg/mL for those exposed to 5,000; 10,000; and 20,000 ppm methanol, respectively.
11 Evidence of maternal toxicity included a slightly unsteady gait in the 20,000 ppm group during
12 the first few days of exposure. Maternal bodyweight gain and food intake were unaffected by
13 methanol. Dams were sacrificed on GD20, and 13-30 litters/group were evaluated. No effect was
14 observed on the number of corpora lutea or implantations or the percentage of dead or resorbed
15 fetuses. Statistical evaluations included analysis of variance (ANOVA) for body weight effect,
16 Kruskal-Wallis test for endpoints such as litter size and viability and Fisher's exact test for
17 malformations. Fetal body weight was significantly reduced at concentrations of 10,000 and
18 20,000 ppm by 7% and 12-16%, respectively, compared to controls. An increased number of
19 litters with skeletal and visceral malformations were observed at > 10,000 ppm, with statistical
20 significance obtained at 20,000 ppm. Numbers of litters with visceral malformations were 0/15,
21 5/15, and 10/15 and with skeletal malformations were 0/15, 2/15, and 14/15 at 0, 10,000, and
22 20,000 ppm, respectively. Visceral malformations included exencephaly and encephaloceles. The
23 most frequently observed skeletal malformations were rudimentary and extra cervical ribs. The
24 developmental and maternal NOAELs for this study were identified as 5,000 ppm (6,552 mg/m3)
25 and 10,000 ppm (13,104 mg/m3), respectively.
26 NEDO (1987) sponsored a teratology study in Sprague-Dawley rats that included an
27 evaluation of postnatal effects in addition to standard prenatal endpoints. Thirty-six pregnant
28 females/group were exposed to 0, 200, 1,000, or 5,000 ppm (0, 262, 1,310, and 6,552 mg/m3)
29 methanol vapors (reagent grade) on GD7-GD17 for 22.7 hours/day. Statistical significance of
30 results was evaluated by t-test, Mann-Whitney U test, Fisher's exact test, and/or Armitage's
31 x2test-
32 Contrary to the Nelson et al. (1985) report of a 10,000 ppm NOAEL for this rat strain, in
33 the prenatal portion of the NEDO (1987) study, reduced body weight gain and food and water
July 2013 4-23 Draft - Do Not Cite or Quote
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1 intake during the first 7 days of exposure were reported for dams in the 5,000 ppm group.
2 However, it was not specified if these results were statistically significant. One dam in the
3 5,000 ppm group died on GDI9, and one dam was sacrificed on GDIS in moribund condition.
4 On GD20, 19-24 dams/group were sacrificed to evaluate the incidence of reproductive deficits
5 and such developmental parameters as fetal viability, weight, sex, and the occurrence of
6 malformations. The reported reproductive and fetal effects are summarized in Table 4-2. The
7 authors suggest that adverse effects (an increase in late-term resorptions, decreased live fetuses,
8 reduced fetal weight, and increased frequency of litters with fetal malformations, variations, and
9 delayed ossifications) were limited to the 5,000 ppm group. However, dose-response analyses
10 indicate statistically significant linear trends for more than one reproductive/fetal effect in the
11 FI rats, including number of pre-implantation resorptions (p < 0.01), pre-implantation resorption
12 rate (p < 0.01) and bifurcated vertebral center (p < 0.01) (ERG. 2009).
13 Postnatal effects of methanol inhalation were evaluated in the remaining 12 dams/group
14 that were permitted to deliver and nurse their litters. Again, the authors suggest that effects were
15 limited to the 5,000 ppm group, including a 1-day prolongation of the gestation period and
16 reduced post-implantation survival, number of live pups/litter, and survival on PND4 (Table 4-3).
17 However, dose-response analyses indicate statistically significant linear trends for post-
18 implantation embryo survival rate (p < 0.01) and number of surviving pups on postnatal day 4
19 (p < 0.03) (ERG, 2009). When the delay in parturition was considered, methanol treatment had
20 no effect on attainment of developmental milestones such as eyelid opening, auricle
21 development, incisor eruption, testes descent, or vaginal opening. There were no adverse body
22 weight effects in offspring from methanol treated groups. The weights of some organs (brain,
23 thyroid, thymus, and testes) were reduced in 8-week-old offspring exposed to 5,000 ppm
24 methanol during prenatal development.
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Table 4-2 Reproductive and developmental toxicity in pregnant Sprague-Dawley rats
exposed to methanol via inhalation during gestation.
Exposure concentration (ppm)
Effect
0
200
1,000
5,000
Reproductive effects
Number of pregnant females
examined
Number of corpora lutea
Number of implantations
No. of pre-implantation resorptions
Early resorption
Late resorption
Number of live fetuses
Sex ratio (M/F)
Fetal weight (male)
Fetal weight (female)
Total resorption rate (%)
Pre-implantation resorption rate
(%)d
Pre-implantation resorption rate
(%)e
Early resorption rate (%)
Late resorption rate (%)
19
17.0 ±2.6
15.7 ±1.6
0.79 ±0.85
0.68 ±0.75
0.11±0.32
14.95 ±1.61
144/140
3.70 ±0.24
3.51±0.19
11.2 ±9.0
6.6 ±8.2
4.9 ±5.2
4.3 ±4.7
0.6 ±1.9
24
17.2 ±2.7
15.0 ±3.0
0.71 ±1.23
0.71 ±1.23
0.0 ±0.0
14.25 ±3.54
177/165
3.88 ±0.23
3.60 ±0.25
15.6 ±21.3
11. 8± 18.7
5.4 ± 12.1
5.4 ±12.1
0.0 ±0.0
22
16.4 ±1.9
15.5 ±1.2
0.95 ±0.65
0.91 ±0.61
0.05 ±0.21
14.55 ±1.1
164/156
3. 82 ±0.29
3.60 ±0.30
10.6 ±8.4
4.9 ±7.9
6.1 ±4.0
5. 8 ±3.9
0.3 ±1.3
21
16.5 ±2.4
14.5 ±3.3
1.67 ±2.03
0.67 ±0.97
1.00 ±1.79
12.86 ±4.04a
134/136
3.02±0.27C
2.83±0.26C
23.3±22.7a
12.7 ±16.5
14.5 ±23. 3
4.2 ±6.1
10.4±23.4a
Soft tissue malformations
Number of fetuses examined
Abnormality at base of right
subclavian
Excessive left subclavian
Ventricular septal defect
Residual thymus
Serpengious urinary tract
136
0.7 ±2.87(1)
0
0
2.9 ±5.91 (4)
43.0 ±24.64 (18)
165
0
0
0.6 ±2.92(1)
2.4 ± 5.44 (4)
35.2 ±31.62 (19)
154
0
0
0
2.6 ± 5.73 (4)
41.8 ±38.45 (15)
131
0
3. 5 ±9.08 (3)
47.6 ± 36.51 (16)b
53.3 ± 28.6 (20)b
22.1 ±22.91 (13)
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Exposure concentration (ppm)
Effect
0
200
1,000
5,000
Skeletal abnormalities
Number of fetuses examined
Atresia of foramen
costotransversarium
Patency of foramen
costotransversium
Cleft sternum
Split sternum
Bifurcated vertebral center
Cervical rib
Excessive sublingual neuropore
Curved scapula
Waved rib
Abnormal formation of lumbar
vertebrae
148
23.5 ±5.47 (3)
0
0
0
0.8 ±3.28(1)
0
0
0
0
0
177
7.7 ± 1.3(8)
0
0
0
1.6 ±5.61 (2)
0
0
0
0
0
165
3.5 ±8.88 (4)
0.6 ±2.67(1)
0
0
3.0 ±8.16 (3)
0
0
0
0
0
138
45.2±25.18(20)b
13.7 ±20.58 (7)
5.6 ±14.14 (3)
7.0 ±14.01 (5)
14.5 ± 16.69 (ll)b
65.2 ± 25.95 (19)b
49.9 ±27.31 (19)
0.7±3.19(1)
6.1 ±11.84 (5)
0.7±3.19(1)
a;><0.05
V
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Table 4-3 Reproductive parameters in Sprague-Dawley dams exposed to methanol during
pregnancy, and then allowed to deliver their pups.
Exposure concentration (ppm)
Parameter
Number of dams
Duration of gestation (days)
Number of implantations
Number of pups
Number of live pups
Number of live pups on PND4
Sex ratio (M/F)
Postimplantation embryo
survival rate
0
12
21.9 ±0.3
15.8 ±1.6
15.2 ±1.6
15.2 ±1.6
15.0 ±1.7 (2)
88/94
96.3 ±4.2
200
12
21.9 ±0.3
14.8 ±1.2
14.4 ±1.3
14.1 ± 1.4
13. 8 ±1.5 (3)
87/85
94.9 ±5.1
1,000
12
21.9 ±0.3
15.3 ±1.3
14.5 ±1.4
14.3 ± 1.4
14.2 ±1.6(1)
103/703
93.6 ±6.1
5,000
12
22.6±0.5C
14.6 ±l.la
13.1±2.2a
12.6±2.5b
10.3 ± 2.8 (9)c
75/81
86.2±16.2a
V
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1 1,310, and 2,620 mg/m3) methanol from the first day of gestation through the FI generation (see
2 Section 4.4.2).
3 Rogers et al. (1993b) evaluated development toxicity in pregnant female CD-I mice
4 exposed to air or 1,000, 2,000, 5,000, 7,500, 10,000, or 15,000 ppm (0, 1,310, 2,620, 6,552,
5 9,894, 13,104, and 19,656 mg/m3) methanol vapors (> 99.9% purity) in a chamber for
6 7 hours/day on GD6-GD15 in a 3-block design experiment. The numbers of mice exposed at
7 each dose were 114, 40, 80, 79, 30, 30, and 44, respectively. During chamber exposures to air or
8 methanol, the mice had access to water but not food. In order to determine the effects of the
9 chamber exposure conditions, an additional 88 control mice were not handled and remained in
10 their cages; 30 control mice were not handled but were food deprived for 7 hours/day on
11 GD6-GD15. Effects in dams and litters were statistically analyzed using the General Linear
12 Models procedure and multiple ^-test of least squares means for continuous variables and the
13 Fisher's exact test for dichotomous variables. An analysis of plasma methanol levels in
14 3 pregnant mice/block/treatment group on GD6, GD10, and GDIS revealed a dose-related
15 increase in plasma methanol concentration that did not seem to reach saturation levels, and
16 methanol plasma levels were not affected by gestation stage or number of previous exposure
17 days. Across all 3 days, the mean plasma methanol concentrations in pregnant mice were
18 approximately 97, 537, 1,650, 3,178, 4,204, and 7,330 jig/mL in the 1,000, 2,000, 5,000, 7,500,
19 10,000, and 15,000 ppm exposure groups, respectively.
20 The dams exposed to air or methanol in chambers gained significantly less weight than
21 control dams that remained in cages and were not handled. There were no methanol-related
22 reductions in maternal body weight gain or overt signs of toxicity. Dams were sacrificed on
23 GDI 7 for a comparison of developmental toxicity in methanol-treated groups versus the chamber
24 air-exposed control group. Fetuses in all exposure groups were weighed, assessed for viability,
25 and examined for external malformations. Fetuses in the control, 1,000, 2,000, 5,000, and
26 15,000 ppm groups were also examined for skeletal and visceral defects. Incidence of
27 developmental effects is listed in Table 4-4. A statistically significant increase in cervical
28 ribs/litter was observed at concentrations of 2,000, 5,000, and 15,000 ppm. At doses of
29 > 5,000 ppm the incidences of cleft palates/litter and exencephaly/litter were increased with
30 statistical significance achieved at all concentrations with the exception of exencephaly which
31 increased but not significantly at 7,500 ppm.34 A significant reduction in live pups/litter was
32 noted at > 7,500 ppm, with a significant increase in fully resorbed litters occurring at
33 > 10,000 ppm. Fetal weight was significantly reduced at > 10,000 ppm. Rogers et al. (1993b)
34 identified a developmental NOAEL and LOAEL of 1,000 ppm and 2,000 ppm, respectively.
34 Due to the serious nature of this response and the relative lack of a response in controls, all incidence of
exencephaly reported in this study at 5,000 ppm or higher are considered biologically significant.
July 2013 4-28 Draft - Do Not Cite or Quote
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1 They also provide BMD maximum likelihood estimates ( referred to by the authors as MLE) and
2 estimates of the lower 95% confidence limit on the BMD (BMDL; referred to by the authors as
3 benchmark dose [BMD]) for 5% and 1% added risk, by applying a log-logistic dose-response
4 model to the mean percent/litter data for cleft palate, exencephaly and resorption. The BMD0s
5 and BMDLos values for added risk estimated by Rogers et al. (1993b) are listed in Table 4-5.
6 From this analysis, the most sensitive indicator of developmental toxicity was an increase in the
7 proportion of fetuses per litter with cervical rib anomalies. The most sensitive BMDL and BMD
8 from this effect for 5% added risk were 305 ppm (400 mg/m3) and 824 ppm (1,080 mg/m3),
9 respectively.35
35 The BMD analysis of the data described in Section 5 was performed similarly using, among others, a similar
nested logistic model. However, the Rogers et al. (1993b) analysis was performed using added risk and external
exposure concentrations, whereas the analyses in Section 5 used extra risk and internal dose metrics that were then
converted to human equivalent exposure concentrations.
July 2013 4-29 Draft - Do Not Cite or Quote
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Table 4-4 Embryonic and Developmental effects in CD-I mice after methanol inhalation.
Exposure concentration (ppm)
Effects
0
1,000
2,000
5,000
7,500
10,000
15,000
Endpoint
No. live pups/litter
No. fully resorbed litters
Fetus weight (g)
Cleft palate/ litter (%)
Exencephaly /litter (%)
9.9
0
1.20
0.21
0
9.5
0
1.19
0.65
0
12.0
0
1.15
0.17
0.88
9.2
0
1.15
8.8b
6.9a
8.6b
o
J
1.17
46.6C
6.8
7.3C
5a
1.04C
52.7C
27.4C
2.2C
14C
0.70C
48.3C
43.3C
Anomalies
Cervical ribs/litter (%)
Sternebral defects/litter (%)
Xiphoid defects/litter (%)
Vertebral arch defects/litter (%)
Extra lumbar ribs/litter (%)
Ossifications (values are means of litter
Sternal
Caudal
Metacarpal
Proximal phalanges
Metatarsals
Proximal phalanges
Distal phalanges
Supraoccipital score+
28
6.4
6.4
0.3
8.7
means)
5.96
5.93
7.96
7.02
9.87
7.18
9.64
1.40
33.6
7.9
3.8
ND
2.5
5.99
6.26
7.92
7.04
9.90
7.69
9.59
1.65
49.6b
3.5
4.1
ND
9.6
5.94
5.7T
7.96
7.04
9.87
6.91
9.57
1.57
74.4C
20.2C
10.9
1.5
15.6
5.81
5.42
7.93
6.12
9.82
5.47
8.46b
1.48
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
60.0a
100C
73.3C
33.3C
40.0C
5.07C
3.20a
7.60b
3.33C
8.13C
Oc
4.27C
3.20C
"p < 0.05
V
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Table 4-5 Benchmark doses at two added risk levels.
Endpoint
Cleft Palate (CP)
Exencephaly (EX)
CPandEX
Resorptions (RES)
CP, EX, and RES
Cervical ribs
BMDos (ppm)
4,314
5,169
3,713
5,650
3,667
824
BMDLos(ppm)
3,398
3,760
3,142
4,865
3,078
305
BMDoi (ppm)
2,717
2,122
2,381
3,749
2,484
302
BMDLoi (ppm)
1,798
784
1,816
2,949
1,915
58
Source: Rogers et al. (1993b).
1 Bolon et al. (1993) performed an inhalation exposure developmental study in CD-I mice
2 under conditions similar to Rogers et al. (1993b). To determine the determine the developmental
3 phase specificity of methanol induced fetal effects, they evaluated developmental toxicity in
4 CD-I mice (n = 20-27/group) following inhalation exposure (6 hr/day) to 5,000, 10,000, or
5 15,000 ppm methanol either throughout organogenesis (GD 6-15), during the period of neural
6 tube development and closure (GD 7-9), or during a time of potential neural tube reopening
7 (GD9-GD11). To better define the critical gestational window of susceptibility, mice
8 (n = 8-15/group) were exposed to 15,000 ppm on GD 7, GD8 or GD9 or for 2 days on GD7-GD8
9 or GD8-GD9. The results of the dose-response portion of the study are shown in Table 4-6 and
10 the results of the "window of susceptibility" portion of the study are shown in Table 4-7.
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Table 4-6 Developmental Phase-Specific Embryotoxicity and Teratogenicity in CD-I mice
after methanol inhalation.
Gestational Days of Exposure
Methanol Concentration
No. of pregnant dams
No. implants/litter3
0
22
12.5 ±0.4
GD7to
5,000 ppm
27
11.6±0.5
GD9
10,000 ppm
20
12.8 ±0.4
15,000 ppm
20
13.4 ±0.4
GD9 to GD11
15,000 ppm
17
12.8 ±0.4
Embryotoxicity
% Resorptions/litterb
% Litters with > 1 Resorptionb
No. (%) of live fetuses/litter3
Fetal body wt(GD17)a, in
grams(g)
Maternal body wt (GD 17)a, in
grams (g)
Developmental Toxicity
No. of litters examined
Neural tube defects
Cleft palate
2.7
27.3
12.0 ±0.4 (98)
0.92 ±0.05
51.2 ±0.9
10.5
55.6C
10.8 ±0.5 (99)
0.96 ±0.01
49.7 ±0.8
Percentage of affected
22
0
9 (0.7)
27
0
4 (0.3)
16.6
75.0C
11.2 ±0.6
(100)
0.91 ±0.01
51.1±1.1
46.2C
90.0C
7.9 ±1.1 (91)
0.82 ±0.02
45.9 ± 1.8
6.9
41.2
10.5 ± 0.9 (87)
0.83 ±0.01
51.1±1.1
litters (percentage affected fetuses)
20
30 (3.6)
50C (14.6)
17
65C(14.7)
88C (50.4)
17
0
53 (20.1)
Renal pelvic dilatation
Cavitation
Hydronephrosis
Ocular defects
Limb anomalies
Tail anomalies
41 (4.3)
0
0
0
0
100C (49.4)
7 (0.9)
0
0
0
90C(31.2)
45C(13.9)
10C(1.3)
5 (0.5)
40C (8.8)
75C (44.9)
53C(11.3)
53C(17.2)
0
65C(15.1)
100 (36.9)
18 (5.9)
0
41 (24.7)
71 (12.4)
aValues represent mean ± standard error.
bEmbryos from 3/20 litters completely resorbed at 15,000 ppm.
°Denotes lowest dose that was significantly different from control by Shirley's test, p < 0.05
Source: Bolon et al. (1993).
July 2013 4-32 Draft - Do Not Cite or Quote
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Table 4-7 Developmental phase-specific embryotoxicity in CD-I mice induced by
methanol inhalation (15,000 ppm) during neurulation.
Gestational Days of Exposure
No. of pregnant dams
No. of implants/litter3
% Resorptions/litter
% Litters with
> 1 Resorptionb
No. (%)oflive
fetuses/litter3
Fetal body wt
(GD17)a, (grams[g])
Control
(GD7-GD9)b
22
12.5 ±0.4
2.7
27.3
12.0 ±0.04
(98.3)
0.92 ±0.05
GD7 GD8
15 13
11. 3 ±0.9 12.9 ±0.6
38.6 c 4.2
86.7 c 30.8
7.7±1.2C 12.2 ±0.6
(92.3) (98.9)
0.99 ±0.03 0.93 ±0.02
GD9
8
13.2 ±0.8
2.3
25.0
12.9 ±0.8
(99.1)
0.99 ±0.02
GD7-GD8
14
12.9 ±0.5
41.9C
100 c
8.4 ±1.0
(95.5)
0.81 ±0.02
GD8-GD9
11
12.7 ±1.1
10.7
45.5
11.7±1.3
(98.7)
0.90 ±0.03
GD7-GD9b
20
13.4 ±0.4
46.2C
90.0 c
7.9±1.1
(91.0)
0.82± 0.02C
Maternal body wt
(GD 17)a, (grams [g])
Dam with uterus
Dam minus uterus
Neural tube defects'1
51.2 ±0.9
36.9 ±2.1
0
453±20 540±13
34.8 ±0.9 35.8 ±0.4
8 (1.4) 15 (2.2)
54 3 ± 2 5
34.3 ± 1.4
0
46 1 ± 1 8
33.5 ±0.8
67 c (15.6)
52 9 ± 2 5
35.1 ±1.0
27(1.9)
45.9 ± 1.8
Not Done
65 c (14.7)
aValues represent mean ± standard error
bValues from Table 4-6
= 0.05
"Significantly different from controls by Dunn's test, ac = 0.
Percentage affected litters (Percentage affected fetuses)
Source: Bolon et al. (1993).
1 Bolon et al. (1993) reported that transient neurologic signs and reduced body weights
2 were observed in up to 20% of dams exposed to 15,000 ppm. Embryotoxicity (increased
3 resorptions, reduced fetal weights, and/or fetal malformations) was apparent at 10,000 and
4 15,000 ppm, while 3-day exposures at 5,000 ppm yielded only an increase in the percentage of
5 litters with one or more resorptions. Developmental toxicity included neural and ocular defects,
6 cleft palate, hydronephrosis, deformed tails, and limb (paw and digit) anomalies at 10,000 ppm
7 (GD 7-9). The only endpoint increased at 5,000 ppm was renal pelvic dilatation (cavitation).
8 Neural tube defects and ocular lesions occurred after methanol inhalation between GD7-GD9,
9 while limb anomalies were induced only during GD9-GD11; cleft palate and hydronephrosis
10 were observed after exposure during either period. Table 5 (of the Bolon et al. study) shows that
11 neural tube effects are most likely to develop from exposure on GD8 and resorptions are most
12 likely to occur from exposure on GD7. These findings indicate that the spectrum of teratogenic
13 effects depended upon both the timing (i.e., stage of embryonic development) and the number of
14 methanol exposures.
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1 Bolon et al. (1994) observed a spectrum of cephalic neural tube defects in near-term
2 (gestation day 17 [GDI?]) mouse fetuses following maternal inhalation of methanol at a high
3 concentration (15,000 ppm) for 6 hr/day during neurulation (GD7-GD9). Their results suggest
4 that ( 1 ) exposure to a high concentration of methanol injures multiple stem cell populations in
5 the neurulating mouse embryo and (2) significant neural pathology may remain in older
6 conceptuses even in the absence of gross lesions.
7 Rogers and Mole (1997) investigated the critical period of sensitivity to the
8 developmental toxicity of inhaled methanol in the CD-I mouse by exposing 12-17 pregnant
9 females to 0 or 10,000 ppm (0 and 13,104 mg/m3), 7 hours/day on 2 consecutive days during
10 GD6-GD13, or to a single exposure to the same methanol concentration during GD5-GD9.
11 Another group of mice received a single 7-hour exposure to methanol at 10,000 ppm. The latter
12 animals were sacrificed at various time intervals up to 28 hours after exposure. Blood samples
13 were taken from these animals to measure the concentration of methanol in the serum. Serum
14 methanol concentrations peaked at ~4 mg/mL 8 hours after the onset of exposure. Methanol
15 concentrations in serum had declined to pre-exposure levels after 24 hours. All mice in the main
16 body of the experiment were sacrificed on GDI 7, and their uteri removed. The live, dead, and
17 resorbed fetuses were counted, and all live fetuses were weighed, examined externally for cleft
18 palate, and then preserved. Skeletal abnormalities were determined after the carcasses had been
19 cleaned and eviscerated. Cleft palate, exencephaly, and skeletal defects were observed in the
20 fetuses of exposed dams. For example, cleft palate was observed following 2-day exposures to
21 methanol on GD6-GD7 through GD11-GD12. These effects also were apparent in mice receiving
22 a single exposure to methanol on GD5-GD9. This effect peaked when the dams were exposed on
23 GD7. Exencephaly showed a similar pattern of development in response to methanol exposure.
24 However, the data indicated that cleft palate and exencephaly might be competing
25 malformations, since only one fetus displayed both features. Skeletal malformations included
26 exoccipital anomalies, atlas and axis defects, the appearance of an extra rudimentary rib on
27 cervical vertebra No.7, and supernumerary lumbar ribs. In each case, the maximum time point
28 for the induction of these defects appeared to be when the dams were exposed to methanol on or
29 near GD7. When dams were exposed to methanol on GD5, there was also an increased incidence
30 of fetuses with 25 presacral vertebrae (26 is normal). However, an increased incidence of fetuses
31 with 27 presacral vertebrae was evident when dams were exposed on GD7. These results indicate
32 that gastrulation and early organogenesis is a period of increased embryonic sensitivity to
33 methanol.
34 Burbacher et al. (1999a; 1999b) carried out toxicokinetic and reproductive/developmental
35 studies of methanol in M. fascicularis monkeys that were published by the Health Effects
36 Institute (HEI) in a two-part monograph. Some of the data were subsequently published in the
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1 open scientific literature (Burbacher et al., 2004a: Burbacher et al., 2004b). The experimental
2 protocol featured exposure to 2 cohorts of 12 monkeys/group to low exposure levels (relative to
3 the previously discussed rodent studies) of 0, 200, 600, or 1,800 ppm (0, 262, 786, and
4 2,359 mg/m3) methanol vapors (99.9% purity), 2.5 hours/day, 7 days/week, during a premating
5 period and mating period (~180 days combined) and throughout the entire gestation period
6 (-168 days). The monkeys were 5.5-13 years old. The study included an evaluation of maternal
7 reproductive performance and tests to assess infant postnatal growth and newborn health,
8 reflexes, behavior, and development of visual, sensorimotor, cognitive, and social behavioral
9 function (see Section 4.4.2 for a review of the developmental neurotoxicity findings from this
10 study). Blood methanol levels, clearance, and the appearance of formate were also examined and
11 are discussed in Section 3.2.
12 With regard to reproductive parameters, there was a statistically significant decrease
13 (p = 0.03) in length of pregnancy in all treatment groups, as shown in Table 4-8. Cesarean
14 section (C-section) deliveries performed in the methanol exposure groups did not impact this
15 finding (decreased length of pregnancy was observed in vaginally delivered animals). C-section
16 deliveries were performed in response to "signs of difficulty" in the pregnancy, but it is not clear
17 whether this is an indication of either reproductive dysfunction or fetal risk due to methanol
18 exposure. Maternal menstrual cycles, conception rate, and live birth index were all unaffected by
19 exposure. There were also no signs of an effect on maternal weight gain or clinical toxicity
20 among the dams.
21 While pregnancy duration was virtually the same in all exposure groups, there were some
22 indications of increased pregnancy duress only in methanol-exposed monkeys. C-sections were
23 done in 2 monkeys from the 200 ppm group and 2 from the 600 ppm group due to vaginal
24 bleeding, presumed, but not verified, to be from placental detachment.36 A monkey in the
25 1,800 ppm group also received a C-section after experiencing nonproductive labor for 3 nights.
26 In addition, signs of prematurity were observed in 1 infant from the 1,800 ppm group that was
27 born after a 150-day gestation period. The consistent reduction in length of pregnancy observed
28 in may reflect a treatment effect on the fetal neuroendocrine system. The authors suggested that
29 the shortened gestation length could be due to a direct effect of methanol on the fetal
30 hypothalamus-pituitary-adrenal (HPA) axis or an indirect effect of methanol on the maternal
31 uterine environment. Other fetal parameters such as crown-rump length and head circumference
32 were unchanged among the groups. Infant growth and tooth eruption were unaffected by prenatal
33 methanol exposure.
36 Burbacher,, et al. (20041)) and Burbacher et al. (2004a) note, however, that in studies of pregnancy complication
in alcohol- exposed human subjects, an increased incidence of uterine bleeding and abruptio placenta has been
reported.
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Table 4-8 Reproductive parameters in monkeys exposed via inhalation to methanol
during prebreeding, breeding, and pregnancy.
Exposure (ppm)
0
200
600
1,800
Conception rate
9/11
9/12
9/11
10/12
Weight gain (kg)
1.67 ±0.07
1.27 ±0.14
1.78 ±0.25
1.54 ±0.20
Pregnancy duration
(days)3
168 ±2
160 ± 2b
162 ± 2b
162 ± 2b
Live born delivery rate
8/9
9/9
8/9
9/10
aLive-bom offspring only;
bp < 0.05, as calculated by the authors.
Values are means ± SE.
Source: Burbacher et al. (2004b).
1 In later life, 2 females out of the total of 9 offspring in the 1,800 ppm group experienced
2 a wasting syndrome at 12 and 17 months of age. Food intake was normal and no cause of the
3 syndrome could be determined in tests for viruses, hematology, blood chemistry, and liver,
4 kidney, thyroid, and pancreas function. Necropsies revealed gastroenteritis and severe
5 malnourishment. No infectious agent or other pathogenic factor could be identified. Thus, it
6 appears that a highly significant toxicological effect on postnatal growth can be attributed to
7 prenatal methanol exposure at 1,800 ppm (2,300 mg/m3).
8 In summary, the Burbacher et al. (1999a: 1999b) studies suggest that methanol exposure
9 can cause reproductive effects, manifested as a shortened mean gestational period, pregnancy
10 complications that precipitated delivery via a C-section, and developmental neurobehavioral
11 effects which may or may not be related to the shortened gestational period (see Section 4.4.2).
12 The low exposure of 200 ppm may signify a LOAEL for reproductive effects. However, the
13 decrease in gestational length was marginally significant. Also, this effect did not appear to be
14 dose related, the greatest gestational period decrease having occurred at the lowest (200 ppm)
15 exposure level. Thus, a clear NOAEL or LOAEL cannot be determined from this study.
16 In a study of the testicular effects of methanol, Cameron et al. (1984) exposed 5 male
17 Sprague-Dawley rats/group to methanol vapor, 8 hours/day, 5 days/week for 1, 2, 4, and 6 weeks
18 at 0, 200, 2,000, or 10,000 ppm (0, 262, 2,620, and 13,104 mg/m3). The authors examined the
19 possible effects of methanol on testicular function by measuring blood levels of testosterone,
20 luteinizing hormone (LH), and follicular stimulating hormone (FSH) using radioimmunoassay.
21 When the authors tabulated their results as a percentage of the control value for each duration
22 series, the most significant changes were in blood testosterone levels of animals exposed to
23 200 ppm methanol, the lowest concentration evaluated. At this exposure level, animals exposed
24 for 6 weeks had testosterone levels that were 32% of those seen in controls; however, higher
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1 concentrations of methanol were associated with testosterone levels that were closer to those of
2 controls. The lack of a clear dose-response is not necessarily an indication that the effect is not
3 related to methanol. The higher concentrations of methanol could be causing other effects
4 (e.g., liver toxicity) which can influence the results. Male rats exposed to 10,000 ppm methanol
5 for 6 weeks displayed blood levels of LH that were about 3 times higher (mean ± SD) than those
6 exposed to air (311 ± 107% versus 100 ± 23%). In discussing their results, the authors placed
7 greater emphasis on the observation that an exposure level equal to the ACGIH TLV (200 ppm)
8 had caused a significant depression in testosterone formation in male rats.
9 A follow-up study report by the same research group (Cameron et al., 1985) described the
10 exposure of 5 male Sprague-Dawley rats/group, 6 hours/day for either 1 day or 1 week, to
11 methanol, ethanol, n-propanol, or n-butanol at their respective TLVs. Groups of animals were
12 sacrificed immediately after exposure or after an 18-hour recovery period, and the levels of
13 testosterone, LH, and corticosterone measured in serum. As shown in Table 4-9, the data were
14 consistent with the ability of these aliphatic alcohols to cause a transient reduction in the
15 formation of testosterone. Except in the case of n-butanol, rapid recovery from these deficits can
16 be inferred from the 18-hour postexposure data.
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Table 4-9 Mean serum levels of testosterone, luteinizing hormone, and corticosterone
(± SD) in male Sprague-Dawley rats after inhalation of methanol, ethanol,
n-propanol or n-butanol at threshold limit values.
TLV
Condition (ppm)
Single-day exposure
18 hr
End of exposure postexposure
One-week exposure
18 hr
End of exposure postexposure
Testosterone (as a percentage of control)
Control
Methanol
Ethanol
n-Propanol
n-Butanol
200
1,000
200
50
100 ±17
41 ± 16a
64 ± 12a
58±15a
37±8a
100 ± 20
98 ±18
86 ±16
81 ±13
52 ± 22a
100 ± 26
81 ±22
88 ±14
106 ± 28
73 ±34
100 ± 17
82 ±27
101 ±13
89 ±17
83 ±18
Luteinizing hormone
Control
Methanol
Ethanol
n-Propanol
n-Butanol
200
1,000
200
50
100 ±30
86 ±32
110 ±22
117±59
124 ±37
100 ±35
110 ±40
119±54
119±83
115±28
100 ± 28
78 ±13
62 ±26
68 ±22
78 ±26
100 ± 36
70 ±14
81 ±17
96 ±28
98 ±23
Corticosterone
Control
Methanol
Ethanol
n-Propanol
n-Butanol
200
1,000
200
50
100 ± 20
115±18
111±32
112±21
143±lla
ND
ND
ND
ND
ND
100 ±21
74 ±26
60 ±25
79 ±14
85 ±26
ND
ND
ND
ND
ND
*p < 0.05, as calculated by the authors.
ND = No data.
Source: Cameron et al. (1985).
1 In a series of studies that are relevant to the reproductive toxicity of methanol in males,
2 Lee et al. (1991) exposed 8-week-old male Sprague-Dawley rats (9-10/group) to 0 or 200 ppm
3 (0 and 262 mg/m3) methanol, 8 hours/day, 5 days/week, for 1,2, 4, or 6 weeks to measure the
4 possible treatment effects on testosterone production. Study results were evaluated by one factor
5 ANOVA followed by Student's t-test. In the treated rats, there was no effect on serum
6 testosterone levels, gross structure of reproductive organs, or weight of testes and seminal
7 vesicles. Lee et al. (1991) also studied the in vitro effect of methanol on testosterone production
8 from isolated testes, but saw no effect on testosterone formation either with or without the
9 addition of human chorionic gonadotropin hormone.
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1 In a third experiment from the same report, Lee et al. (1991) examined testicular
2 histopathology to determine if methanol exposure produced lesions indicative of changing
3 testosterone levels; the effects of age and folate status were also assessed. This is relevant to the
4 potential toxicity of methanol because folate is the coenzyme of tetrahydrofolate synthetase, an
5 enzyme that is rate limiting in the removal of formate. Folate deficiency would be expected to
6 cause potentially toxic levels of formate to be retained. The same authors examined the relevance
7 of folate levels, and by implication, the overall status of formate formation and elimination in
8 mediating the testicular functions of Long-Evans rats. Groups of 4-week-old male Long-Evans
9 rats were given diets containing either adequate or reduced folate levels plus 1%
10 succinylsulfathiazole, an antibiotic that, among other activities,37 would tend to reduce the folate
11 body burden. At least 9 rats/dietary group/dose were exposed to 0, 50, 200, or 800 ppm (0, 66,
12 262, and 1,048 mg/m3) methanol vapors starting at 7 months of age while 8-12 rats/dietary
13 group/dose were exposed to 0 or 800 ppm methanol vapors at 15 months of age. The methanol
14 exposures were conducted continuously for 20 hours/day for 13 weeks. Without providing
15 details, the study authors reported that visual toxicity and acidosis developed in rats fed the low
16 folate diet and exposed to methanol. No methanol-related testicular lesions or changes in testes
17 or body weight occurred in rats that were fed either the folate sufficient or deficient diets and
18 were 10 months old at the end of treatment. Likewise, no methanol-lesions were observed in
19 18-month-old rats that were fed diets with adequate folate. However, the incidence but not
20 severity of age-related testicular lesions was increased in the 18-month-old rats fed folate-
21 deficient diets. Subcapsular vacuoles in germinal epithelium were noted in 3/12 control rats and
22 8/13 rats in the 800 ppm group. One rat in the 800 ppm group had atrophied seminiferous tubules
23 and another had Leydig cell hyperplasia. These effects, as well as the transient decrease in
24 testosterone levels observed by Cameron et al. (1985; 1984), could be the result of chemically-
25 related strain on the rat system as it attempts to maintain hormone homeostasis.
26 Dorman et al. (1995) conducted a series of in vitro and in vivo studies of developmental
27 toxicity in ICR BR (CD-I) mice associated with methanol and formate exposure. The studies
28 used HPLC grade methanol and appropriate controls. PK and developmental toxicity parameters
29 were measured in mice exposed to a 6-hour methanol inhalation (10,000 or 15,000 ppm),
30 methanol gavage (1.5 g/kg bw) or sodium formate (750 mg/kg by gavage) on GD8. In the in vivo
31 inhalation study, 12-14 dams/group were exposed to 10,000 ppm methanol for 6 hours on GD8,38
32 with and without the administration of fomepizole to inhibit the metabolism of methanol by
33 ADH1. Dams were sacrificed on GD10, and folate levels in maternal RBC and conceptus
37 Succinylsulfathiazole antibiotic may have a direct impact on the effects being measured, the extent of which was
not addressed by the authors of this study.
38 Dorman et al. (1995) state that GD8 was chosen because it encompasses the period of murine neurulation and the
time of greatest vulnerability to methanol-induced neural tube defects.
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1 (decidual swelling) were measured, as well as fetal neural tube patency (an early indicator of
2 methanol-induced dysmorphogenic response). The effects observed included a transient decrease
3 in maternal RBC and conceptus folate levels within 2 hours following exposure and a significant
4 (p< 0.05) increase in the incidence of fetuses with open neural tubes (9.65% in treated versus
5 0 in control). These responses were not observed following sodium formate administration,
6 despite peak formate levels in plasma and decidual swellings being similar to those observed
7 following the 6-hour methanol inhalation of 15,000 ppm. This suggests that these methanol -
8 induced effects are not related to the accumulation of formate. As this study provides information
9 relevant to the identification of the proximate teratogen associated with developmental toxicity in
10 rodents, it is discussed more extensively in Section 4.7.1.
4.3.3. Other Reproductive and Developmental Studies
11 Additional information relevant to the possible effects of methanol on reproductive and
12 developmental parameters has been provided by experimental studies that have exposed
13 experimental animals to methanol during pregnancy via i.p. injections (Sweeting et al., 2011;
14 Degitz et al., 2004b; Rogers et al., 2004). Relevant to the developmental impacts of the chemical,
15 a number of studies also have examined the effects of methanol when included in whole-embryo
16 culture (Miller and Wells. 2011: Hansen et al.. 2005: Harris etal.. 2003: Andrews et al.. 1998:
17 Andrews et al., 1995: Andrews et al., 1993).
18 Pregnant female C57BL/6J mice received two i.p. injections of methanol on GD7
19 (Rogers et al., 2004). The injections were given 4 hours apart to provide a total dosage of 0, 3.4,
20 and 4.9 g/kg. Animals were sacrificed on GDI7 and the litters were examined for live, dead, and
21 resorbed fetuses. Rogers et al. (2004) monitored fetal weight and examined the fetuses for
22 external abnormalities and skeletal malformations. Methanol-related deficits in maternal and
23 litter parameters observed by Rogers et al. (2004) are summarized in Table 4-10.
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Table 4-10 Maternal and litter parameters when pregnant female C57BL/6J mice were
injected i.p. with methanol.
Methanol dose (g/kg)
Parameter
No. pregnant at term
WtgainGD7-GD8(g)
WtgainGD7-GD10(g)
Live fetuses/litter
Resorbed fetuses/litter
Dead fetuses/litter
Fetal weight (g)
0
43
0.33 ±0.10
1.63 ±0.18
7.5 ±0.30
0.4 ±0.1
0.1±0.1
0.83 ± 0.02
3.4 4.9
13 24
0.37 ±0.15 -0.24±0.14a
2.20 ±0.20 1.50 ±0.20
6.3±0.5a 3.7±0.4a
1.3±0.4a 4.4±0.4a
0 0.1±0.1
0.82 ±0.03 0.70±0.02a
ap < 0.05, as calculated by the authors.
Values are means ± SEM.
Source: Rogers et al. (2004).
1 Rogers et al. (2004) used a number of sophisticated imaging techniques, such as confocal
2 laser scanning and fluorescence microscopy, to examine the morphology of fetuses excised at
3 GD7, GD8, and GD9. They identified a number of external craniofacial abnormalities, the
4 incidence of which was, in all cases, significantly increased in the high-dose group compared to
5 controls. For some responses, such as microanophthalmia and malformed maxilla, the incidence
6 was also significantly increased in animals receiving the lower dose. Fifteen compound-related
7 skeletal malformations were tabulated in the report. In most cases, a dose-response effect was
8 evident, resulting in statistically significant incidences in affected fetuses and litters, when
9 compared to controls. Apparent effects of methanol on the embryonic forebrain included a
10 narrowing of the anterior neural plate, missing optical vesicles, and holoprosencephaly (failure of
11 the embryonic forebrain to divide). The authors noted that there was no sign of incipient cleft
12 palate or exencephaly, as had been observed in CD-I mice exposed to methanol via the oral and
13 inhalation routes (Rogers et al., 1993b).
14 In order to collect additional information on cell proliferation and histological changes in
15 methanol-treated fetuses, Degitz et al. (2004b) used an identical experimental protocol to that of
16 Rogers et al. (2004) by administering 0, 3.4, or 4.9 g methanol/kg in distilled water i.p. (split
17 doses, 4 hours apart) to C57BL/6J mice on GD7. Embryos were collected at various times on
18 GD8 and GD10. Embryos from dams exposed to 4.9 g/kg and examined on GD8 exhibited
19 reductions in the anterior mesenchyme, the mesenchyme subjacent to the mesencephalon and the
20 base of the prosencephalon (embryonic forebrain), and in the forebrain epithelium. The optic pits
21 were often lacking; where present their epithelium was thin and there were fewer neural crest
22 cells in the mid- and hindbrain regions. At GD9, there was extensive cell death in areas
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1 populated by the neural crest, including the forming cranial ganglia. Dose-related abnormalities
2 in the development of the cranial nerves and ganglia were seen on GD7. In accordance with an
3 arbitrary dichotomous scale devised by the authors, scores for ganglia V, VIII, and IX were
4 significantly (not otherwise specified) reduced at all dose levels, and ganglia VII and X were
5 reduced only at the highest dose. At the highest dose (4.9 g/kg), the brain and face were poorly
6 developed and the brachial arches were reduced in size or virtually absent. Flow cytometry of the
7 head regions of the embryos from the highest dose at GD8 did not show an effect on the
8 proportion of cells in S-phase.
9 Cell growth and development were compared in C57BL/6J and CD-I mouse embryos
10 cultured in methanol (Degitz et al., 2004a). GD8 embryos, with 5-7 somites, were cultured in
11 0, 1, 2, 3, 4, or 6 mg methanol/mL for 24 hours and evaluated for morphological development.
12 Cell death was increased in both strains in a developmental stage- and region-specific manner at
13 4 and 6 mg/mL after 8 hours of exposure. The proportions of cranial region cells in S-phase were
14 significantly (p < 0.05) decreased at 6 mg/mL following 8- and 18-hour exposures to methanol.
15 After 24 hours of exposure, C57BL/6J embryos had significantly (p < 0.05) decreased total
16 protein at 4 and 6 mg/kg. Significant (p < 0.05) developmental effects were seen at 3, 4, and
17 6 mg/kg, with eye dysmorphology being the most sensitive endpoint. CD-I embryos had
18 significantly decreased total protein at 3, 4, and 6 mg/kg, but developmental effects were seen
19 only at 6 mg/kg. It was concluded that the C57BL/6J embryos were more severely affected by
20 methanol in culture than the CD-I embryos.
21 Sweeting et al. (2011) performed a series of experiments in NZW rabbits, C57BL/6J mice
22 and C3H mice to compare plasma pharmacokinetics of methanol and formic acid and
23 embryotoxicity. For the teratology portion of the study, pregnant female mice and rabbits were
24 given two i.p. doses of 2 g methanol/kg body weight on GD7 or GD8, for a total daily dose of
25 4 g methanol/kg body weight, or two i.p. doses of a saline vehicle control. Methanol exposure
26 did not significantly impact fetal body weights for any of the species and strains tested. No
27 statistically significant effects were reported on rabbit growth parameters and mortality.
28 A 4.4-fold increase in tail abnormalities per litter, including shortening and absence, was
29 reported in rabbit fetuses. However, due to the variability of this endpoint among litters, this
30 difference was not statistically significant. Non-significant increases were reported in exposed
31 rabbit litters for several other effects that were not observed in controls, including two fetuses
32 with open posterior neuropores, one with an abdominal wall defect (prune belly), and three with
33 frontal nasal hyperplasia. In C3H mice, methanol in utero exposure caused a 2-fold increase in
34 fetal resorptions, but this increase was not statistically significant over saline treated controls
35 (p < 0.01). In C57BL/6, methanol caused a 66% incidence of fetal ophthalmic abnormalities
36 (p < 0.001) compared to a non-significant 3% incidence in C3H mice. Ophthalmic anomalies
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1 were not observed in saline-exposed controls of either strain. Methanol also caused a 17%
2 increase in fetal cleft palates in C57BL/6 mice (p < 0.05) compared to 0% in saline controls, and
3 0% in C3H mice treated with either methanol or saline. No increase in cephalic NTDs, an
4 endpoint commonly observed in CD-I mice, was observed in C57BL/6 or C3H mice. The
5 different teratological results across these mouse strains could not be explained by differences in
6 methanol or formic acid disposition (the pharmacokinetic results of this study are described in
7 Section 3.2). The authors hypothesize that these differences in embryotoxicity could be due to
8 strain differences in ADH activity and the amount of catalase available for ROS detoxification,
9 or differences in other pathways that involve ROS formation. Sweeting et al. (2011) suggest that
10 their findings indicate that rabbits are resistant to the teratogenic effects of methanol. However,
11 because the critical gestational window for developmental effects could be different for rabbits
12 versus mice, this claim needs to be verified over several gestational days, as has been done for
13 mice. Postpartum lethality was nearly 2-fold higher in the methanol exposed (11%) versus
14 control (5%) rabbit fetuses, and stillbirths were also increased (4% versus 0%). Though these
15 increased incidences were not statistically significant, they may prove to be biologically
16 significant given that postpartum lethality ("wasting syndrome") and a shortened gestational
17 period were possible adverse outcomes observed in methanol exposed monkeys (see discussion
18 of Burbacher et al., (2004b; 1999b) in Section 4.3.2).
19 Table 4-11 displays the results of three studies of whole rodent embryos exposed to
20 methanol (Miller and Wells, 2011; Hansen et al., 2005; Andrews et al., 1993). These data suggest
21 that mouse embryos are more sensitive than rat embryos to the developmental effects of
22 methanol. The Miller and Wells (2011) results also demonstrate that developmental effects from
23 methanol exposure are increased in acatalasemic (aCat)-expressing mouse embryos over their
24 wild type controls (C3HWT) and decreased in mouse embryos expressing human catalase (hCat)
25 over their wild type controls (C57WT). These results suggest that embryonic catalase activity
26 may be a determinant for teratological risk in mice following methanol-exposure.
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Table 4-11 Developmental studies of rodent embryos exposed to methanol.
Species/Strain/GD
Mouse/CD- 1/GD8
Rat/Sprague-
Dawley/GD9
Mouse/CD- 1/GD8
Rat/Sprague-
Dawley/GDlO
Mouse/wild-type
control
(C57WT)/GD9
Mouse/C57BL/6 with
human catalase
(hCat)/GD9
Mouse/wild-type
control C3HeB/FeJ
(C3HWT)/GD9
Mouse/C3Ga.Cg-
Catb/J acatalasemic
(aCat)/GD9
GD = Gestation Day; WT
Embryo Culture Dose
& Duration
0, 2, 4, 6, or 8 mg/mL
for 24 hrs
0, 2, 4, 8, 12 or 16
mg/mL for 24 hrs
4-12 mg/mL for
24 hrs
8 - 20 mg/mL for
24 hrs
0 or 4 mg/L for 24 hrs
0 or 4 mg/L for 24 hrs
0 or 4 mg/L for 24 hrs
0 or 4 mg/L for 24 hrs
Effect
Decrease in developmental score and crown-rump
length at 4 mg/mL and above. Embryo lethality at
8 mg/mL.
Decrease in somite number, head length, and
developmental score at 8 mg/mL and above.
Embryo lethality at 12 mg/mL.
Reduced VYS DNA and rotation at 4 mg/mL;
reduced embryo DNA and protein, neural tube
closure and viability at 8 mg/L; reduced VYS
protein at 10 mg/L
Reduced embryo protein and rotation at 8 mg/mL;
reduced VYS DNA and protein, embryo DNA, and
neural tube closure at 8 mg/L; reduced viability at
16 mg/L
Decreased somites developed and turning, and
increased heart rate at 4 mg/L relative to 0 mg/L.
Decreased neuropore closure at 4 mg/L relative to
0 mg/L and hCat
Increased crown rump length and heart rate relative
to 0 mg/L. Increased somites at 4 mg/L relative to
C57WT
Decreased somites developed at 4 mg/L relative to
Omg/L.
Decreased somites developed at 4 mg/L relative to
0 mg/L. Reduced anterior neuropore closure and
head length at 4 mg/L relative to 0 mg/L and
C3HWT. Lower yolk sac diameters at 4 mg/L
relative to C3HWT.
Reference
Andrews
et al. (1993)
Andrews
et al. (19931
Hansen et al.
(2005)
Hansen et al.
(20051
Miller and
Wells (20111
Miller and
Wells (20111
Miller and
Wells (20111
Miller and
Wells (20111
= Wild Type; VYS = visceral yolk sac
1 In contrast to the in vitro and in vivo findings of Dorman et al. (1995), Andrews et al.
2 (1995) demonstrated that formate can induce similar developmental lesions in whole rat and
3 mouse conceptuses. Using a similar experimental system as Andrews et al. (1993) to examine the
4 developmental toxicity of formate and formic acid in comparison to methanol, Andrews et al.
5 (1995) report that the formates are embryotoxic at doses that are four times lower than equimolar
6 doses of methanol. Among the anomalies observed were open anterior and posterior neuropores,
7 plus rotational defects, tail anomalies, enlarged pericardium, and delayed heart development.
8 Andrews et al. (1998) showed that exposure to combinations of methanol and formate was less
9 embryotoxic than would be expected based on simple toxicity additivity, suggesting that the
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1 embryotoxicity observed following low-level exposure to methanol is mechanistically different
2 from that observed following exposure to formate.
3 The whole embryo study by Hansen et al. (2005) also determined the comparative
4 toxicity of methanol and its metabolites, formaldehyde and sodium formate, in GD8 mouse
5 (CD-I) and GD10 rat (Sprague-Dawley) conceptuses. Whole embryos were incubated for
6 24 hours in media containing methanol (mouse: 4-12 mg/mL; rat: 8-20 mg/mL), formaldehyde
7 (mouse: 1-6 |ig/mL; rat: 1-8 |ig/mL) and sodium formate (mouse: 0.5-4 mg/mL; rat:
8 0.5-8 mg/mL). In other experiments, the chemicals were injected directly into the amniotic
9 space. The embryos were examined morphologically to determine growth and developmental
10 parameters such as viability, flexure and rotation, crown-rump length, and neuropore closure.
11 For each response, Table 4-12 provides a comparison of the concentrations or amounts of
12 methanol, formaldehyde, and formate that resulted in statistically significant changes in
13 developmental abnormalities compared to controls. For a first approximation, these
14 concentrations or amounts may be taken as threshold-dose ranges for the specific responses
15 under the operative experimental conditions. The data show consistently lower threshold values
16 for the effects of formaldehyde compared to those of formate and methanol. The mouse embryos
17 were more sensitive towards methanol toxicity than rat embryos, consistent with in vivo
18 findings, whereas the difference in sensitivity disappeared when formaldehyde was administered.
19 Hansen et al. (2005) hypothesized that, while the MOA for the initiation of the organogenic
20 defects is unknown, the relatively low threshold levels of formaldehyde for most measured
21 effects suggest formaldehyde involvement in the embryotoxic effects of methanol. Consistent
22 with this hypothesis, formate, a subsequent metabolite of methanol and putative toxicant for the
23 acute effects of methanol poisoning (acidosis, neurological deficits), did not appear to reproduce
24 the methanol-induced teratogenicity in these whole embryo culture experiments.
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Table 4-12 Reported thresholds concentrations (and author-estimated ranges) for the onset
of embryotoxic effects when rat and mouse conceptuses were incubated in vitro
with methanol, formaldehyde, and formate.
Parameter
Methanol
Mouse
Formaldehyde
Formate
Methanol
Rat
Formaldehyde
Formate
In vitro incubation (mg/mL)
Viability (%)
Normal rotation (%)
CR a length
Neural tube closure
(%)
Reduced embryo
protein
Reduced VYS b protein
Reduced embryo DNA
Reduced VYS DNA
8.0
4.0
No change
8.0
8.0
10.0
8.0
4.0
0.004
0.003
No change
0.001
0.003
0.004
0.003
0.001
NS
0.5
No change
2.0
4.0
4.0
No change
0.5
16.0
8.0
No change
12.0
8.0
12.0
12.0
12.0
0.006
0.003
No change
No change
0.004
0.004
0.003
0.003
2.0
4.0
No change
No change
2.0
NR
NR
NR
Microinjection (author-estimated dose ranges in jig)
Viability (%)
Normal rotation (%)
CR a length
Neural tube closure
(%)
Reduced embryo
protein
Reduced VYS b protein
Reduced embryo DNA
Reduced VYS b DNA
aCR = crown-rump length,
bVYS = visceral yolk sac.
NR = not reported
Source: Hansen et al. (2005);
46-89
1-45
No change
1-45
1-45
135-178
46-89
1-45
Harris et al. (
0.003-0.5
0.003-0.5
No change
0.003-0.5
0.501-1.0
1.01-1.5
0.501-1.0
0.003-0.5
2QQ4) (adapted).
1.01-1.5
0.03-0.5
No change
1.01-1.5
No change
No change
No change
0.03-0.5
46-89
46-89
No change
No change
No change
No change
No change
No change
1.01-1.5
1.01-1.5
No change
No change
1.51-2.0
No change
No change
No change
1.51-4.0
0.51-1.0
No change
1.01-1.5
0.51-1.0
1.01-1.5
0.51-1.0
0.51-1.0
1 Harris et al. (2003) provided biochemical evidence consistent with the concept that
2 formaldehyde might be the ultimate embryotoxicant of methanol by measuring the activities of
3 enzymes that are involved in methanol metabolism in mouse (CD-I) and rat (Sprague-Dawley)
4 whole embryos at different stages of development. Specific activities of the enzymes ADH1,
5 ADH3, and CAT, were determined in rat and mouse conceptuses during the organogenesis period
6 of 8-25 somites. Activities were measured in heads, hearts, trunks, and VYS from early- and
7 late-stage mouse and rat embryos. While CAT activities were similar between rat and mouse
8 embryos, mouse ADH1 activities in the VYS were significantly lower throughout organogenesis
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1 when compared to the rat VYS or embryos of either species. ADH1 activities of heads, hearts,
2 and trunks from mouse embryos were significantly lower than those from rats at the 7-12 somite
3 stage. However, these interspecies differences were not evident in embryos of 20-22 somites.
4 ADH3 activities were lower in mouse versus rat VYS, irrespective of the stage of development.
5 However, while ADH3 activities in mouse embryos were markedly lower than those of rats in
6 the early stages of development, the levels of activity were similar to at the 14-16 somite stage
7 and beyond. A lower capacity to transform formaldehyde to formate might explain the increased
8 susceptibility of mouse versus rat embryos to the toxic effects of methanol. The hypothesis that
9 formaldehyde is the ultimate embryotoxicant of methanol is supported by the demonstration of
10 diminished ADH3 activity in mouse versus rat embryos and by the demonstration by Hansen
11 et al. (2005) that formaldehyde has a far greater embryotoxicity than either formate or methanol
12 itself.
4.4. Neurotoxicity
13 A substantial body of information exists on the toxicological consequences to humans
14 who consume or are exposed to large amounts of methanol. As discussed in Section 4.1,
15 neurological consequences of acute methanol intoxication in humans include Parkinson-like
16 responses, visual impairment, confusion, headache, and numerous subjective symptoms. The
17 occurrence of these symptoms has been shown to be associated with necrosis of the putamen
18 when neuroimaging techniques have been applied (Salzman, 2006). Such profound changes have
19 been linked to tissue acidosis that arises when methanol is metabolized to formaldehyde and
20 formic acid through the actions of ADH1 and ADH3. However, the well-documented impact of
21 the substantial amounts of formate that are formed when humans and animals are exposed to
22 large amounts of methanol may obscure the potentially harmful effects that may arise when
23 humans and animals are exposed to smaller amounts. Human acute exposure studies (Chuwers et
24 al.. 1995: Cooketal.. 1991) (See Section 4.1.3) at TLV levels of 200 ppm would indicate that
25 some measures of neurological function (e.g., sensory evoked potentials, memory testing and
26 psychomotor testing) were impaired in the absence of measurable formate production.
4.4.1. Oral Neurotoxicity Studies
27 As discussed in Section 4.2.1.2, an oral subchronic (90 days, beginning at roughly
28 30 days of age) gavage study noted reduced brain weight in high-dose group (2,500 mg/kg-day)
29 male and female S-D rats (30/sex/dose) (TRL, 1986). They also reported a higher incidence of
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1 colloid in the hypophyseal cleft of the pituitary gland in the high-dose versus control group
2 males (13/20 versus 0/20) and females (9/20 versus 3/20). Based on these findings, a 500 mg/kg-
3 day NOAEL was identified for this study
4 Two rodent studies investigated the neurological effects of developmental methanol
5 exposure via the oral route (Aziz et al., 2002; Infurna and Weiss, 1986). One of these studies also
6 investigated the influence of FAD diets on the effects of methanol exposures (Aziz et al., 2002).
7 In the first, Infurna and Weiss (1986) exposed 10 pregnant female Long-Evans rats/dose to 2%
8 methanol (purity not specified) in drinking water on either GDIS-GDI? or GD17-GD19. Daily
9 methanol intake was calculated at 2,500 mg/kg-day by the study authors. Dams were allowed to
10 litter and nurse their pups. Data were analyzed by ANOVA with the litter as the statistical unit.
11 Results of the study were equivalent for both exposure periods. Treatment had no effect on
12 gestational length or maternal bodyweight. Methanol had no effect on maternal behavior as
13 assessed by the time it took dams to retrieve pups after they were returned to the cage following
14 weighing. Litter size, pup birth weight, pup postnatal weight gain, postnatal mortality, and day of
15 eye opening did not differ from controls in the methanol treated groups. Two neurobehavioral
16 tests were conducted in offspring. Suckling ability was tested in 3-5 pups/treatment group on
17 PND1. An increase in the mean latency for nipple attachment was observed in pups from the
18 methanol treatment group, but the percentage of pups that successfully attached to nipples did
19 not differ significantly between treatment groups. Homing behavior, the ability to detect home
20 nesting material within a cage containing one square of shavings from the pup's home cage and
21 four squares of clean shavings, was evaluated in 8 pups/group on PND10. Pups from both of the
22 methanol exposure groups took about twice as long to locate the home material and took less
23 direct paths than the control pups. Group-specific values differed significantly from controls.
24 This study suggests that developmental toxicity can occur at this drinking water dose without
25 readily apparent signs of maternal toxicity.
26 Aziz et al. (2002) investigated the role of developmental deficiency in folic acid and
27 methanol-induced developmental neurotoxicity in PND45 rat pups. Wistar albino female rats
28 (80/group) were fed FAD39 and FAS diets separately. Following 14-16 weeks on the diets, liver
29 folate levels were estimated and females exhibiting a significantly low folic acid level were
30 mated. Throughout their lactation period, dams of both the FAD and the FAS group were given
31 0, 1, 2, or 4% v/v methanol via drinking water, equivalent to approximately 480, 960 and
32 1,920 mg/kg-day.40 Pups were exposed to methanol via lactation from PND1-PND21. Litter size
33 was culled to 8 with equal male/female ratios maintained as much as possible. Liver folate levels
39 Along with the FAD diet, 1% succinylsulfathiazole was also given to inhibit folic acid biosynthesis from intestinal
bacteria.
40 Assuming that Wistar rat drinking water consumption is 60 mL/kg-day (Rogers et al.. 2002X 1% methanol in
drinking water would be equivalent to 1% x 0.8 g/mL x 60 mL/kg-day = 0.48 g/kg-day = 480 mg/kg-day.
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1 were determined at PND21 and neurobehavioral parameters (motor performance using the
2 spontaneous locomotor activity test and cognitive performance using the conditioned avoidance
3 response [CAR] test), and neurochemical parameters (dopaminergic and cholinergic receptor
4 binding and dopamine levels) were measured at PND45. The expression of growth-associated
5 protein (GAP 43), a neuro-specific protein in the hippocampus that is primarily localized in
6 growth cone membranes and is expressed during developmental regenerative neurite outgrowth,
7 was examined using immunohistochemistry and Western blot analysis.
8 A loss in body weight gain was observed at PND7, PND14, and PND21 in animals
9 exposed to 2% (11, 15 and 19% weight gain reduction) and 4% (17, 24 and 29% weight gain
10 reduction) methanol in the FAD group and only at 4% (9, 14 and 17% weight gain reduction)
11 methanol in the FAS group. No significant differences in food and water intake were observed
12 among the different treatment groups. Liver folate levels in the FAD group were decreased by
13 63% in rats prior to mating and 67% in pups on PND21.
14 Based on reports of Parkinson-like symptoms in survivors of severe methanol poisoning
15 (see Section 4.1), Aziz et al. (2002) hypothesized that methanol may cause a depletion in
16 dopamine levels and degeneration of the dopaminergic nigrostriatal pathway.41 Consistent with
17 this hypothesis, they found dopamine levels were significantly decreased (32% and 51%) in the
18 striatum of rats in the FAD group treated with 2% and 4% methanol, respectively. In the FAS
19 group, a significant decrease (32%) was observed in the 4% methanol-exposed group.
20 Methanol treatment at 2% and 4% was associated with significant increases in activity, in
21 the form of distance traveled in a spontaneous locomotor activity test, in the FAS group (13%
22 and 39%, respectively) and more notably, in the FAD group (33% and 66%, respectively) when
23 compared to their respective controls. Aziz et al. (2002) suggest that these alterations in
24 locomotor activity may be caused by a significant alteration in dopamine receptors and
25 disruption in neurotransmitter availability. Dopamine receptor (D2) binding in the hippocampus
26 of the FAD group was significantly increased (34%) at 1% methanol, but was significantly
27 decreased at 2% and 4% methanol exposure by 20% and 42%, respectively. In the FAS group,
28 D2 binding was significantly increased by 22% and 54% in the 2% and 4% methanol-exposed
29 groups.
30 At PND45, the CAR in FAD rats exposed to 2% and 4% methanol was significantly
31 decreased by 48% and 52%, respectively, relative to nonexposed controls. In the FAS group, the
32 CAR was only significantly decreased in the 4% methanol-exposed animals and only by 22% as
33 compared to their respective controls. Aziz et al. (2002) suggest that the impairment in CAR of
41 The nigrostriatal pathway is one of four major dopamine pathways in the brain that are particularly involved in the
production of movement. Loss of dopamine neurons in the substantia nigra is one of the pathological features of
Parkinson's disease (KimetaL 2003).
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1 the methanol-exposed FAD pups may be due to alterations in the number of cholinergic
2 (muscarinic) receptor proteins in the hippocampal region of the brain. Muscarinic receptor
3 binding was significantly increased in the 2% (20%) and 4% (42%) methanol-exposed group in
4 FAD animals, while FAS group animals had a significant increase in cholinergic binding only in
5 the 4% methanol exposed group (21%). High concentrations of methanol may saturate the body's
6 ability to remove toxic metabolites, including formaldehyde and formate, and this may be
7 exacerbated in FAD pups having a low store of folate.
8 Immunohistochemistry showed an increase in the expression of GAP-43 protein in the
9 dentate granular and pyramidal cells of the hippocampus in 2% and 4% methanol-exposed
10 animals in the FAD group. The FAS group showed increased expression only in the 4%
11 methanol-exposed group. The Western blot analysis also confirmed a higher expression of
12 GAP-43 in the 2% and 4% methanol-exposed FAD group rats. Aziz et al. (2002) suggested that
13 up-regulation of GAP-43 in the hippocampal region may be associated with axonal growth or
14 protection of the nervous system from methanol toxicity.
15 The Aziz et al. (2002) study provides evidence that hepatic tetrahydrofolate is an
16 important contributing factor in methanol-induced developmental neurotoxicity in rodents.
17 The immature blood-brain barrier and inefficient drug-metabolizing enzyme system make the
18 developing brain a particularly sensitive target organ to the effects of methanol exposure.
4.4.2. Inhalation Neurotoxicity Studies
19 A review by Carson et al. (1981) has summarized a number of older reports of studies on
20 the toxicological consequences of methanol exposure. In one example relevant to the potential
21 for neurotoxicity from repeat, low level exposure to methanol, the review cites a research report
22 of Chen-Tsi (1959) who exposed 10 albino rats/group (sex and strain unstated) to 1.77 and
23 50 mg/m3 (1.44 and 40.7 ppm) methanol vapor, 12 hours/day, for 3 months. Deformation of
24 dendrites, especially the dendrites of pyramidal cells, in the cerebral cortex was included in the
25 description of histopathological changes observed in adult animals following exposure to
26 50 mg/m3 (40.7 ppm) methanol vapor. One out often animals exposed to the lower methanol
27 concentration also displayed this feature.
28 Information on the neurotoxicity of methanol inhalation exposure in adult cynomolgus
29 monkeys (M. fascicularis) has come from NEDO (1987) which describes the results of a number
30 of inhalation experiments that have already been discussed in Section 4.2.2. The monkey studies
31 that will be discussed here with respect to their neurotoxicity implications include an acute study,
32 a chronic study, and a repeated exposure experiment (of variable duration depending upon
33 exposure level), followed by recovery period (1-6 months), and an experiment looking at chronic
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1 formaldehyde exposure (1 or 5 ppm), a metabolite of methanol. This last experiment was only a
2 pilot study and included only one monkey per exposure condition.
3 As noted in Section 4.2.2.1, histopathologic changes to the CNS reported in monkeys
4 following acute exposure to methanol included characteristic degeneration of the bilateral
5 putamen, caudate nucleus, and claustrum, with associated edema in the cerebral white matter
6 (NEDO, 1987). These lesions increased in severity with increasing exposure. Necrosis of the
7 basal ganglia was noted following exposure to 5,000 ppm for 5 days (1 animal) and 14 days
8 (1 animal). The authors reported that at 3,000 ppm, the monkeys experienced little more than
9 minimal fibrosis of "responsive stellate cells" of the thalamus, hypothalamus, and basal
10 ganglion. This effect was also observed following chronic exposure and is discussed more
11 extensively below.
12 In the chronic experiment, 8 monkeys were included per exposure level (control, 10, 100,
13 1,000 ppm or 13, 131, and 1,310 mg/m3, respectively, for 21 hours/day); however, animals were
14 serially sacrificed at 3 time points: 7 months, 19 months, or >26 months. This design reduced
15 the number of monkeys at each exposure level to 2 subjects at 7 months, and 3 subjects at the
16 subsequent time points (see Section 4.2.2). One of the 3 animals receiving 100 ppm methanol
17 and scheduled for sacrifice at 29 months was terminated at 26 months.
18 Histopathologically, no overt degeneration of the retina, optical nerve, cerebral cortex, or
19 other potential target organs (liver and kidney) was reported in the chronic experiment.
20 Regarding the peripheral nervous system, 1/3 monkeys exposed to 100 ppm (131 mg/m3) and
21 2/3 exposed to 1,000 ppm (1,310 mg/m3) for 29 months showed slight but clear changes in the
22 peroneal nerves. The most pervasive effect noted across the exposure concentrations and
23 durations was "fibrosis of responsive stellate cells," characterized as "neurological disease" in
24 the NEDO (1987) summary report. These "stellate cells" are likely to be astrocytes, star-shaped
25 glial cells in the brain that are among the most numerous cells in all regions of the CNS. As was
26 noted in an independent peer review of this study (ERG, 2009), the degree of fibrosis of
27 responsive stellate cells is an appropriate CNS endpoint of consideration given that stellate
28 astroglia are believed to play a key role in the pathogenesis of CNS disorders and an essential
29 role in response to tissue injury and inflammation by hypertrophy, proliferation, production of
30 growth factors and cytokines, and involvement in extracellular matrix deposition characteristic of
31 fibrosis (De Keyser et al., 2008). A peer reviewer also recommended that, because there did not
32 appear to be an effect of duration on the incidence of this neurological endpoint, the results can
33 be pooled across durations to obtain a clearer view of dose-response results (ERG, 2009). As
34 reported in "appended Table 3" of the NEDO (1987) report, the incidence of stellate cell fibrosis
35 at 10 ppm (13.1 mg/m3), 100 ppm (131 mg/m3) or 1,000 ppm (1,310 mg/m3) for exposure
36 durations of 7 months or longer were: [3/8, 7/8 and 7/8 within the cerebral white matter]; [0/8,
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1 3/8 and 3/8 inside the nucleus of the thalamus]; [3/8, 6/8 and 4/8 in the hypothalamus]; [4/8, 7/8
2 and 7/8 in the mesencephalon central gray matter]; [2/8, 7/8 and 7/8 in the pons tegmentum]; and
3 [0/8, 5/8 and 4/9 in the medulla oblongata tegmentum]. All monkeys that had degeneration of the
4 inside nucleus of the thalamus also had degeneration of the cerebral white matter.
5 According to NEDO (1987), the stellate cell response "disappeared as soon as exposure
6 was stopped" in groups exposed to 1,000 ppm or less for 7 months and was "not characteristic of
7 degeneration." Because the RfD and RfC represent "lifetime" exposures, the transient nature of
8 the effect upon cessation of exposure is not as relevant. Further, the authors also noted that the
9 stellate cell response represented an "abnormal increase" in 3 of 8 monkeys exposed to 10 ppm
10 methanol, was "widely observed" in monkeys exposed to 100 ppm and more, was "nearly absent
11 in normal monkeys in the control group" and that "in the groups exposed to a large quantity of
12 methanol or for a long time their presence tended to become permanent, so a relation to the long
13 term over which the methanol was inhaled is suspected." There is a question concerning whether
14 an appropriate, concurrent control was used as all control group responses are reported in a
15 single table in the section of the NEDO (1987) report that describes the acute monkey study, with
16 no indication as to when the control group was sacrificed. However, responses in the mid- and
17 high- dose groups appeared to be increased over responses in the low-dose groups.
18 In the recovery experiment, monkeys were exposed for 7 months to 1,000 ppm
19 (3 animals), for 20 days to 2,000 ppm (3 animals), for 20 days to 3,000 ppm (4 animals), for
20 5-14 days to 5,000 ppm (5 animals) or for 6 days to 7,000 ppm (2 animals) methanol, followed
21 by recovery periods of various durations. Monkeys exposed to 3,000 ppm for 20 days followed
22 by a 6-month recovery period experienced relatively severe fibrosis of responsive stellate cells
23 and elucidation of the medullary sheath. However, resolution of some of the glial responses was
24 noted in the longer duration at lower exposure levels, with no effects observed on the cerebral
25 white matter in monkeys exposed for 7 months to 1,000 ppm methanol followed by a 6-month
26 recovery period. In general, the results from the recovery experiment corroborated results
27 observed in the chronic experiment. NEDO (1987) interpreted the lack of glial effects after a
28 6-month recovery as an indication of a transient effect. However, glial responses to neural
29 damage do not necessarily persist following resolution of neurodegeneration (Aschner and
30 Kimelberg, 1996). In addition, the reported data do not fully support that changes in cerebral
31 white matter were transient (ERG, 2009). Two of three monkeys exposed to 2,000 ppm exhibited
32 stellate cell changes in at least one lobe after 1 and 11 months recovery. Also, the only monkey
33 exposed 7 months with a 1 month recovery period exhibited such changes at autopsy. While the
34 monkeys exposed to 1,000 ppm for 7 months with a 5 month 20 day recovery period were devoid
35 of stellate cell changes, the small sample size (n=2) does not allow for the stellate cell effect to
36 be characterized as transient.
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1 The limited information available from the NEDO (1987) summary report suggests that
2 100 ppm (131 mg/m3) may be an effect level following continuous, chronic exposure to
3 methanol. However, as noted in Section 4.2.2.1, the NEDO (1987) studies in nonhuman
4 primates, have multiple reporting deficiencies and data gaps that make them difficult to interpret.
5 In addition, confidence in the dose-response data from this study is weakened by the apparent
6 lack of a concurrent control group and the small number of animals at each exposure level for
7 each serial sacrifice (2-3 monkeys/time point/exposure level). In general, peer reviewers of this
8 study stated that it provides descriptive, rather than quantitative, support for the evaluation of the
9 inhalation toxicity of methanol (ERG, 2009). Thus, a clear NOAEL or LOAEL cannot be
10 determined from these monkey studies.
11 Weiss et al. (1996) exposed 4 cohorts of pregnant Long-Evans rats (10-12 dams/
12 treatment group/cohort) to 0 or 4,500 ppm (0 and 5,897 mg/m3) methanol vapor (high-
13 performance liquid chromatography [HPLC] grade), 6 hours/day, from GD6 to PND21. Pups
14 were exposed together with the dams during the postnatal period. Average blood methanol levels
15 in pups on PND7 and PND14 were about twice the level observed in dams. However, methanol
16 exposure had no effect on maternal gestational weight gain, litter size, or postnatal pup weight
17 gain up to PND1842. Neurobehavioral tests were conducted in neonatal and adult offspring; the
18 data generated from those tests were evaluated by repeated measures ANOVA. Three
19 neurobehavioral tests conducted in 13-26 neonates/group included a suckling test, conditioned
20 olfactory aversion test, and motor activity test. In contrast to earlier test results reported by
21 Infurna and Weiss (1986), methanol exposure had no effect on suckling and olfactory aversion
22 tests conducted on PND5 and PND10, respectively. Results of motor activity tests in the
23 methanol group were inconsistent, with decreased activity on PND18 and increased activity on
24 PND25. Tests that measured motor function, operant behavior, and cognitive function were
25 conducted in 8-13 adult offspring/group. Some small performance differences were observed
26 between control and treated adult rats in the fixed wheel running test only when findings were
27 evaluated separately by sex and cohort. The test requires the adult rats to run in a wheel and
28 rotate it a certain amount of times in order to receive a food reward. A stochastic spatial
29 discrimination test examined the rats' ability to learn patterns of sequential responses. Methanol
30 exposure had no effect on their ability to learn the first pattern of sequential responses, but
31 methanol-treated rats did not perform as well on the reversal test. The result indicated possible
32 subtle cognitive deficits as a result of methanol exposure. A morphological examination of
33 offspring brains conducted on PND1 and PND21 indicated that methanol exposure had no effect
42 The fact that this level of exposure caused effects in the Sprague-Dawley rats of the NEDO (1987) study but did
not cause a readily apparent maternal effect in Long-Evans rats of this study could be due to differences in strain
susceptibility.
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1 on neuronal migration, numbers of apoptotic cells in the cortex or germinal zones, or
2 myelination. However, neural cell adhesion molecule (NCAM) 140 and NCAM 180 gene
3 expression in treated rats was reduced on PND4 but not 15 months after the last exposure.
4 NCAMs are glycoproteins required for neuron migration, axonal outgrowth, and establishing
5 mature neuronal function patterns.
6 Stanton et al. (1995) exposed 6-7 pregnant female Long-Evans rats/group to 0 or
7 15,000 ppm (0 and 19,656 mg/m3) methanol vapors (> 99.9% purity) for 7 hours/day on
8 GD7-GD19. Mean serum methanol levels at the end of the 1st, 4th, 8th, and 12th days of
9 exposure were 3,836, 3,764, 3,563, and 3,169 |ig/mL, respectively. As calculated by authors,
10 dams received an estimated methanol dose of 6,100 mg/kg-day. A lower body weight on the first
11 2 days of exposure was the only maternal effect; there was no increase in postimplantation loss.
12 Dams were allowed to deliver and nurse litters. Parameters evaluated in pups included mortality,
13 growth, pubertal development, and neurobehavioral function. Examinations of pups revealed that
14 two pups from the same methanol-exposed litter were missing one eye; aberrant visually evoked
15 potentials were observed in those pups. A modest but significant reduction in body weight gain
16 on PND1, PND21, and PND35 was noted in pups from the methanol group. For example, by
17 PND35, male pups of dams exposed to methanol had a mean body weight of 129 grams versus
18 139 grams in controls (p < 0.01). However, postnatal mortality was unaffected by exposure to
19 methanol. The study authors did not consider a 1.7-day delay in vaginal opening in the methanol
20 group to be an adverse effect. Preputial separation was not affected by prenatal methanol
21 exposure. Neurobehavioral status was evaluated using 8 different tests on specific days up to
22 PND160. Tests included motor activity on PND13-PND21, PND30, and PND60, olfactory
23 learning and retention on PND18 and PND25, behavioral thermoregulation on PND20-21,
24 T-maze delayed alternation learning on PND23-PND24, acoustic startle reflex on PND24, reflex
25 modification audiometry on PND61-PND63, passive avoidance on PND73, and visual evoked
26 potentials on PND160. A single pup/sex/litter was examined in most tests, and some animals
27 were subjected to multiple tests. The statistical significance of neurobehavioral testing was
28 assessed by one-way ANOVA, using the litter as the statistical unit. Results of the
29 neurobehavioral testing indicated that methanol exposure had no effect on the sensory, motor, or
30 cognitive function of offspring under the conditions of the experiment. However, given the
31 comparatively small number of animals tested for each response, it is uncertain whether the
32 statistical design had sufficient power to detect small compound-related changes.
33 NEDO (1987) sponsored a teratology study that included an evaluation of postnatal
34 effects in addition to standard prenatal endpoints in Sprague-Dawley rats. Thirty-six pregnant
35 females/group were exposed to 0, 200, 1,000, or 5,000 ppm (0, 262, 1,310, and 6,552 mg/m3)
36 methanol vapors (reagent grade) on GD7-GD17 for 22.7 hours/day. Statistical significance of
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1 results was evaluated by t-test, Mann-Whitney U test, Fisher's exact test, and/or Armitage's
2 x2 test.
3 Postnatal effects of methanol inhalation were evaluated in the remaining 12 dams/group
4 that were permitted to deliver and nurse their litters. Effects were only observed in the
5 5,000 ppm. There were no adverse effects on offspring body weight from methanol exposure.
6 However, the weights of some organs (brain, thyroid, thymus, and testes) were reduced in
7 8-week-old offspring following prenatal-only exposure to 5,000 ppm methanol. An unspecified
8 number of offspring were subjected to neurobehavioral testing or necropsy, but results were
9 incompletely reported.
10 As described in Section 4.3.2, NEDO (1987) performed a two-generation reproductive
11 study that evaluated the effects of pre- and postnatal methanol exposure (20 hours/day) on
12 reproductive and other organ systems of Sprague-Dawley rats and in particular the brain. They
13 reported reduced brain, pituitary, and thymus weights, in the offspring of FO and FI rats exposed
14 to 1,000 ppm methanol. In particular, they noted a reduction in absolute brain weights in Fl pups
15 at 8 weeks (male and female), 16 weeks (males) and 24 weeks (females) and in F2 pups at 8
16 weeks (male and female). Details were not reported (e.g., means, variances, sample sizes, pup-to-
17 litter correlations) that would allow for further analysis of these findings.
18 Seeking to confirm the possible compound-related effect of methanol on the brain NEDO
19 (1987) conducted an additional developmental study in which Sprague-Dawley rats were
20 exposed to 0, 500, 1,000, and 2,000 ppm (0, 655, 1,310, and 2,620 mg/m3) methanol from the
21 first day of gestation through the FI generation. According to NEDO (1987 page 201 ), another
22 purpose of the supplementary study was "to know from what period after birth such changes
23 would appear." Information important for a determination of possible litter correlations (e.g., pup
24 litter assignments) was not reported for the supplemental experiment. However, the number of
25 pups per dose group per "period after birth" was reported (11-14/sex/dose/postnatal period) and
26 it is reasonable to assume that, consistent with the standard culling protocol used for both the Fl
27 and F2 generations of the two-generation study (NEDO, 1987 pages 185 and 189 ), the pups for
28 each gender, dose and exposure time combination came from a different litter (to avoid problems
29 associated with litter correlation). Brain weights were measured in the 11-14 offspring/sex/group
30 at 3, 6, and 8 weeks of age. As illustrated in Table 4-13, brain weights were significantly reduced
31 in 3-week-old males and females exposed to > 1,000 ppm. At 6 and 8 weeks of age, brain
32 weights were significantly reduced in males exposed to > 1,000 ppm and females exposed to
33 2,000 ppm. Due to the toxicological significance of this postnatal effect, the brain weight
34 changes observed by NEDO (1987) following gestational and postnatal exposures and following
35 gestation-only exposure (in the teratology study discussed above) are evaluated quantitatively
36 and discussed in more detail in Section 5 of this review.
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Table 4-13 Brain weights of rats exposed to
lactation.
methanol vapors during gestation and
Brain weight (g)
Mean ± SD Mean ± SD, (% of control) at each exposure level
Offspring age
3 weeks3
3 weeks3
6 weeks3
6 weeks3
8 weeks3
8 weeks3
8 weeks'3
8 weeks'3
Sex 0 ppm 200 ppm
Male 1.45 ±0.06
Female 1.41 ±0.06
Male 1.78 ±0.07
Female 1.68 ±0.08
Male 1.99 ±0.06
Female 1.85 ±0.05
Male 2.00 ± 0.05 Vinn°/\
Female 1.86 ±0.08 VlOW\
500 ppm
1.46 ±0.08
(101%)
1.41 ±0.07
(100%)
1.74 ±0.09
(98%)
1.71 ±0.08
(102%)
1.98 ±0.09
(99%)
1.83 ±0.07
(99%)
~
~
1,000 ppm
1.39±0.05C
(96%)
1.33±0.07d
(94%)
1.69±0.06d
(95%)
1.62 ±0.07
(96%)
1.88±0.08d
(94%)
1.80 ±0.08
(97%)
1.99 ±0.07
(100%)
1.90 ±0.08
(102%)
2,000 ppm
1.27±0.06e
(88%)
1.26±0.09e
(89%)
1.52±0.07e
(85%)
1.55±0.05e
(92%)
1.74±0.05e
(87%)
1.67±0.06e
(90%)
~
~
5,000 ppm
~
~
~
~
~
~
1.81±0.16d
(91%)
1.76 ±1.09
(95%)
aExposed throughout gestation and F] generation.
bExposed on gestational days 7-17 only.
°p<0.05;
dp<0.0l;
>< 0.001;
p values as calculated by the authors. Values are means ± SD
Source: NEDO (1987).
1 Burbacher et al. (1999a: 1999b) carried out toxicokinetic, reproductive, developmental
2 and postnatal neurological and neurobehavioral studies of methanol in M. fascicularis monkeys
3 that were published by HEI in a two-part monograph. Some of the data were subsequently
4 published in the open scientific literature (Burbacher et al., 2004a: Burbacher et al., 2004b). The
5 experimental protocol featured exposure to 2 cohorts of 12 monkeys/group to low-exposure
6 levels (relative to the previously discussed rodent studies) of 0, 200, 600, or 1,800 ppm (0, 262,
7 786, and 2,359 mg/m3) methanol vapors (99.9% purity), 2.5 hours/day, 7 days/week, during a
8 premating period and mating period (-180 days combined) and throughout the entire gestation
9 period (-168 days). The monkeys were 5.5-13 years old. The outcome study included an
10 evaluation of maternal reproductive performance (discussed in Section 4.3.2) and tests to assess
11 infant postnatal growth and newborn health, neurological outcomes included reflexes, behavior,
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1 and development of visual, sensorimotor, cognitive, and social behavioral function. Blood
2 methanol levels, elimination, and the appearance of formate were also examined and are
3 discussed in Section 3.2. The effects observed were in the absence of appreciable increases in
4 maternal blood formate levels.
5 Neurobehavioral function was assessed in 8-9 infants/group during the first 9 months of
6 life (Burbacher et al.. 2004b: Burbacher et al.. 1999b). Although results in 7/9 tests were
7 negative, 2 effects were possibly related to methanol exposure. The Visually Directed Reaching
8 (VDR) test is a measure of sensorimotor development and assessed the infants' ability to grasp
9 for a brightly colored object containing an applesauce-covered nipple. Beginning at 2 weeks after
10 birth, infants were tested 5 times/day, 4 days/week. Performance on this test, measured as age
11 from birth at achievement of test criterion (successful object retrieval on 8/10 consecutive trials
12 over 2 testing sessions), was reduced in all treated male infants. The times (days after birth) to
13 achieve the criteria for the VDR test were 23.7 ± 4.8 (n = 3), 32.4 ± 4.1 (n = 5), 42.7 ± 8.0
14 (n = 3), and 40.5 ± 12.5 (n = 2) days for males and 34.2 ± 1.8 (n = 5), 33.0 ± 2.9 (n = 4),
15 27.6 ± 2.7 (n = 5), and 40.0 ± 4.0 (n = 7) days for females in the control to 1,800 ppm groups,
16 respectively. Statistical significance was obtained in the 1,800 ppm group when males and
17 females were evaluated together (p = 0.04) and in the 600 ppm (p = 0.007) for males only.
18 However, there was no significant difference between responses and/or variances (indicating lack
19 of a dose-response trend) among the dose levels for males and females combined (p = 0.244), for
20 males only (p = 0.321) and for males only, excluding the high-dose group (p = 0.182). However,
21 there was a significant dose-response trend for females only (p = 0.0265). The extent to which
22 VDR delays were due to a direct effect of methanol on neurological development or a secondary
23 effect due to the methanol-induced decrease in length of pregnancy and subsequent prematurity
24 is not clear. Studies of reaching behavior have shown that early motor development in pre-term
25 human infants without major developmental disorders differs from that of full-term infants
26 (Fallang et al., 2003). Clinical studies have indicated that the quality of reaching and grasping
27 behavior in pre-term infants is generally less than that in full-term infants (Fallang et al., 2003;
28 Plantinga et al., 1997). For this reason, measures of human infant development generally involve
29 adjustment of a child's "test age" if he or she had a gestational age of fewer than 38 weeks, often
30 by subtracting weeks premature from the age measured from birth (Wilson and Cradock, 2004).
31 When this type of adjustment is made to the Burbacher et al. (2004b; 1999b) VDR data, the
32 dose-response trend for males only remains unacceptable (p = 0.448) and, while the dose-
33 response trend for the females only remains adequate (p = 0.009), the variance in the data could
34 not be modeled adequately. Thus, only the unadjusted VDR response for females only exhibited
35 a dose-response that could be adequately modeled (see Appendix D).
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1 At 190-210 days of age, the Pagan Test of infant intelligence was conducted. The
2 paradigm makes use of the infant's proclivity to direct more visual attention to novel stimuli
3 rather than familiar stimuli. The test measures the time infants spend looking at familiar versus
4 novel items. Deficits in the Pagan task can qualitatively predict deficits in intelligence quotient
5 (IQ) measurements assessed in children at later ages (Pagan and Singer, 1983). Control monkey
6 infants in the Burbacher et al. (2004b; 1999b) study spent more than 62% ± 4% (mean for both
7 cohorts) of their time looking at novel versus familiar monkey faces, while the treated monkeys
8 did not display a statistically significant preference for the novel faces (59% ± 2%, 54% ± 2%
9 and 59% ± 2% in 200, 600 and 1,800 ppm groups, respectively). Unlike the VDR results
10 discussed previously, results of this test did not appear to be gender specific and were neither
11 statistically significant (ANOVA/? = 0.38) nor related to exposure concentration. The findings
12 indicated a cohort effect which appeared to reduce the statistical power of this analysis. The
13 authors' exploratory analysis of differences in outcomes between the 2 cohorts indicated an
14 effect of exposure in the second cohort and not the first cohort due to higher mean performance
15 in controls of cohort 2 (70% ± 5% versus 55% ± 4% for cohort 1). In addition, this finding could
16 reflect the inherent constraints of this endpoint. If the control group performs at the 60% level
17 and the most impaired subjects perform at approximately the 50% chance level (worse than
18 chance performance would not be expected), the range over which a concentration-response
19 relationship can be expressed is limited. Because of the longer latency between assessment and
20 birth, these results would not be confounded with the postulated methanol-induced decrease in
21 gestation length of the exposed groups of this study. Negative results were obtained for the
22 remaining seven tests that evaluated early reflexes, gross motor development, spatial and concept
23 learning and memory, and social behavior. Infant growth and tooth eruption were unaffected by
24 methanol exposure.
4.4.3. Neurotoxicity Studies Employing i.p. and in vitro Methanol Exposures
25 Table 4-14 describes three i.p. injection studies that attempt to determine the biochemical
26 changes associated with the effects of repeat methanol exposures on the brain, retina, optic nerve
27 (Rajamani et al., 2006; Gonzalez-Quevado et al., 2002) and the hypothalamus-pituitary-adrenal
28 (HPA) axis of the neuroendocrine system (Parthasarathy et al., 2006b). The goal of the Gonzalez-
29 Quevado et al. (2002) study was to determine whether a sustained increase in formate levels,43 at
30 concentrations below those known to produce toxic effects from acute exposures, can induce
43 Formate levels were increased by treating test rats with methotrexate (MTX), which depletes folate stores by
interfering with tetrahydrofolate (THF) regeneration (Dorman et al.. 1994).
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1 biochemical changes in the retina, optical nerve, or certain regions of the brain. 44 The amino
2 acids aspartate, glutamate, asparagine, serine, histidine, glutamine, threonine, glycine, arginine,
3 alanine, hypotaurine, gamma-aminobutyric acid (which is also a neurotransmitter), and tyrosine
4 were measured in blood, brain, and retinal regions.
5 The increased level of aspartate in the optic nerve of animals treated with MTX-methanol
6 and Tau-MTX-methanol may indicate a relation to formate accumulation. The authors note that
7 L-aspartate is a major excitatory amino acid in the brain and that increased levels of excitatory
8 amino acids can trigger neuronal cell damage and death (Albin and Greenamyre, 1992).
9 Increased levels of aspartate and glutamine in the hippocampus could provide an explanation for
10 some of the CNS symptoms observed in methanol poisonings on the basis of their observed
11 impact on cerebral arteries (Huang et al., 1994). The observation that these increases resulted
12 primarily from methanol without MTX could be significant in that it indicates methanol can
13 cause excitotoxic effects without formate mediation. The neurotransmitters serotonin (5-HT) and
14 dopamine (DA) and their respective metabolites, 5-hydroxyindolacetic acid (5-HIAA) and
15 dihydroxyphenylacetic acid (DOPAC), were also measured in various brain regions. The levels
16 of these monoamines were not affected by formate accumulation, as the only increases were
17 observed for 5-HT and 5-HIAA following methanol-only exposure. DA and DOPAC levels were
18 not altered by the treatments in any of the areas measured. The posterior cortex did not show any
19 changes in monoamine levels for any treatment group.
20 Rajamani et al. (2006) examined several oxidative stress parameters in male Wistar rats
21 following methotrexate-induced folate deficiency. The optic nerve, retina, and brain were
22 collected and the brain was dissected into the following regions: cerebral cortex, cerebellum,
23 mid-brain, pons medulla, hippocampus, and hypothalamus. Each region was examined for
24 indicators of oxidative stress including increases in the free radical scavengers: superoxide
25 dismutase (SOD), CAT, glutathione peroxidase (GPx); and reduced GSH levels. The levels of
26 protein thiols, protein carbonyls, and amount of lipid peroxidation were also measured. More
27 recently, investigators from the same laboratory measured increased methanol blood levels and
28 corresponding increases in these indicators of oxidative stress in discrete regions of the brain in
29 Wistar strain albino rats exposed to 75 mg/kg/day aspartame (lyyaswamy and Rathinasamy,
30 2012). Overall, the results reported in these studies suggest that folate-deficient rats exposed to
31 methanol exhibit signs of oxidative stress (e.g., increased SOD, GPx and CAT activity and
32 decreased levels of GSH and protein thiol) in discrete regions of the brain, retina, and optic
33 nerve.
44 A subset of exposed rats were also exposed to taurine, which plays an important role in the retina and optical
nerve, to explore its possible protective effect (Gonzalez-Quevado et al.. 2002).
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1 To determine the effects of methanol on the HPA axis, Parthasarathy et al. (2006b)
2 evaluated a combination of oxidative stress, immune and neurobehavioral parameters following
3 methanol exposure. Oxidative stress parameters examined included SOD, CAT, GSH peroxidase,
4 GSH, and ascorbic acid (Vitamin C). Plasma corticosterone levels were measured, and lipid
5 peroxidation was measured in the hypothalamus and the adrenal gland. An assay for DNA
6 fragmentation was conducted in tissue from the hypothalamus, the adrenal gland and the spleen.
7 Immune function tests conducted included the footpad thickness test for delayed type
8 hypersensitivity (DTH), a leukocyte migration inhibition assay, the hemagglutination assay
9 (measuring antibody titer), the neutrophil adherence test, phagocytosis index, and a nitroblue
10 tetrazolium (NET) reduction and adherence assay used to measure the killing ability of
11 polymorphonuclear leukocytes (PMNs). The open field behavior test was used to measure
12 general locomotor and explorative activity during methanol treatment in the 30-day treatment
13 group, with tests conducted on days 1, 4, 8, 12, 16, 20, 24, and 28.
14 The results for this study shown in Table 4-14 suggest that exposure to methanol-induced
15 oxidative stress, disturbs HPA-axis function, altering corticosterone levels and producing effects
16 in several nonspecific and specific immune responses.
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Table 4-14 Intraperitoneal injection neurotoxicity studies.
Species/Strain/N Dose & Duration
Effect Relative to Control
Reference
Rat/Sprague-
Dawley/
(5-7 per group;
100-150 g)
Control: tap water (wk 1);
saline s.c. (wks 2-4)
MeOH: tap water (wk 1);
s.c. saline (wk 2);
2 g/kg-day MeOH i.p.
(wks 3-4)
Increased blood formate (<2-fold); Increased aspartate,
glutamine and Tau in hippocampus; Increased 5-HT
and 5-HIAA in hippocampus; Increased 5-HT in retina
MTX: tap water (wk 1);
0.2 mg/kg-day MTX s.c.
(wk 2);
0.1 mg/kg-day MTX s.c. &
saline i.p. (wks 2-4)
No change in blood formate or any other measured
parameter
MTX-MeOH: tap water
(wk 1);
0.2 mg/kg-day MTX s.c.
(wk 2);
0.1 mg/kg-day MTX s.c. &
2 g/kg -day MeOH i.p.
(wks 3-4)
Increased blood formate (>3-fold); Increased aspartate
in optic nerve; Increased aspartate and Tau in Gonzalez-
hippocampus Quevado
et al. (2002)
Tau: 2% Tau in DW
(wks 1-4);
saline s.c. (wks 2-4)
No change in blood formate; Increased blood histidine
and Tau
Tau-MTX-MeOH: 2% Tau
in DW (wks 1-4);
0.2 mg/kg-day MTX s.c.
(wk 2);
0.1 mg/kg-day MTX s.c. &
2 g/kg-day MeOH i.p.
(wks 3-4)
Increased blood formate (>3-fold) and Tau; Increased
aspartate in optic nerve; Increased aspartate, glutamine
and Tau in hippocampus
Rat/Wistar/
6 per group
Control: saline i.p. (day 8)
MTX: 0.2 mg/kg-day MTX
(wk 1);
saline i.p. (day 8)
Increased SOD, CAT, GSH peroxidase, oxidized GSH,
protein carbonyls and lipid peroxidation in all brain
regions; Decreased GSH and protein thiols in all brain
regions; Increased HSP70 in hippocampus
MTX-MeOH: 0.2 mg/kg-
day MTX (wk 1);
3 g/kg-day MeOH i.p.
(day 8)
Increased SOD, CAT, GSH peroxidase, oxidized GSH,
protein carbonyls and lipid peroxidation in all brain
regions over control and MTX group; Decreased GSH
and protein thiols in all brain regions over control and
MTX group; Increased HSP70 in hippocampus
Rajamani
et al. (2006)
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Species/Strain/N Dose & Duration Effect Relative to Control Reference
Rat/Wistar/ 0 or 2.37 g/kg-day MeOH All antioxidants increased at 1-day, but decreased at 15
6 per group i.p. for 1, 15 or 30 days and 30 days; Increased lipid peroxidation in
hypothalamus and adrenal gland at 1, 15, and 30 days;
Increased leukocyte migration and antibody liter at all
time points; Decreased footpad thickness at 15 and
30 days; Decreased neutrophil adherence at 1 and
30 days. Decreased NET reduction and adherence in _ _,, ^
„„/ ^ __ , ™,TKT ^i^j T-V • Parthasarathy
PMNs at 30-days versusPMNs at 15-days; Decrease in ^ , ,„„„,,•;
u i *• t ^u j T-. • • j etal. (2006b)
ambulation from 4th day on; Decrease in rearing and
grooming from 20th day on. Increase in immobilization
from 8th day on; Increase fecal bolus from 24th day on;
Increase in corticosterone levels at 1 and 15 days;
Decrease in corticosterone levels at 30 days;
Fragmentation of DNA from hypothalamus, adrenal
gland, and spleen at 30 days.
wk = week; MeOH = methanol; s.c. = subcutaneous injection; i.p.= intraperitoneal injection; MIX = methotrexate; Tau = taurine;
DW = drinking water ad libitum exposure
1 There is some experimental evidence that the presence of methanol can affect the activity
2 of acetylcholinesterase (Tsakiris et al., 2006). Although these experiments were carried out on
3 erythrocyte membranes in vitro, the apparent compound-related changes may have implications
4 for possible impacts of methanol and/or its metabolites on acetylcholinesterase at other centers,
5 such as the brain. Tsakiris et al. (2006) prepared erythrocyte ghosts from blood samples of
6 healthy human volunteers by repeated freezing-thawing. The ghosts were incubated for 1 hour at
7 37°C in 0, 0.07, 0.14, 0.6 or 0.8 mmol/L methanol, and the specific activities of
8 acetylcholinesterase monitored. Respective values (in change of optical density units/minute-mg
9 protein) were 3.11 ± 0.15, 2.90 ± 0.10, 2.41 ± 0.10 (p < 0.05), 2.05 ± 0.11 (p < 0.01), and
10 1.81 ± 0.09 (p < 0.001). More recently, Simintzi et al. (2007) carried out an in vitro experiment
11 to investigate the effects of aspartame metabolites, including methanol, on 1) a pure preparation
12 of acetylcholinesterase, and 2) the same activity in homogenates of frontal cortex prepared from
13 the brains of (both sexes of) Wistar rats. The activities were measured after incubations with 0,
14 0.14, 0.60, or 0.8 mmoles/L (0, 4.5, 19.2, and 25.6 mg/L) methanol, and with methanol mixed
15 with the other components of aspartame metabolism, phenylalanine and aspartic acid. After
16 incubation at 37°C for 1 hour, the activity of acetylcholinesterase was measured
17 spectrophotometrically. As shown in Table 4-15, the activities of the acetylcholinesterase
18 preparations were reduced dose dependently after incubation in methanol. Similar results were
19 also obtained with the other aspartame metabolites, aspartic acid, and phenylalanine, both
20 individually or as a mixture with methanol. While the implications of this result to the acute
21 neurotoxicity of methanol are uncertain, the authors speculated that methanol may bring about
22 these changes through either interactions with the lipids of rat frontal cortex or perturbation of
23 proteinaceous components.
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Table 4-15 Effect of methanol on Wistar rat acetylcholinesterase activities.
,.„,,, , ,. Acetylcholinesterase activity (AOD/min-mg)
Methanol concentration _ —
(mmol/L) Frontal cortex Pure enzyme
Control 0.269 ±0.010 1.23 ±0.04
0.14 0.234 ±0.007a 1.18 ±0.06
0.60 0.223 ±0.009b 1.05±0.04b
0.80 0.204 ± 0.008b 0.98 ± 0.05b
ap<0.01.
V< 0.001.
Values are means ± SD for four experiments. The average value of each experiment was derived from three determinations of
each enzyme activity.
Source: Simintzi et al. (2007).
4.5. Immunotoxicity
1 Parthasarathy et al. (2005b) provided data on the impact of methanol on neutrophil
2 function in an experiment in which 6 male Wistar rats/group were given a single i.p. exposure of
3 2,370 mg/kg methanol mixed 1:1 in saline. Another group of 6 animals provided blood samples
4 that were incubated with methanol in vitro at a methanol concentration equal to that observed in
5 the in vivo-treated animals 30 and 60 minutes postexposure. Total and differential leukocyte
6 counts were measured from these groups in comparison to in vivo and in vitro controls.
7 Neutrophil adhesion was determined by comparing the neutrophil index in the untreated blood
8 samples to those that had been passed down a nylon fiber column. The cells' phagocytic ability
9 was evaluated by their ability to take up heat-killed Candida albicans. In another experiment,
10 neutrophils were assessed for their killing potential by measuring their ability to take up then
11 convert NET to formazan crystals.45 One hundred neutrophils/slides were counted for their total
12 and relative percent formazan-positive cells.
13 The blood methanol concentrations 30 and 60 minutes after dosing were 2,356 ±162 and
14 2,233 ±146 mg/L, respectively. The mean of these values was taken as the target concentration
15 for the in vitro methanol incubation. In the in vitro studies, there were no differences in total and
16 differential leukocyte counts, suggesting that no lysis of the cells had occurred at this methanol
17 concentration. This finding contrasts with the marked difference in total leukocytes observed as a
18 result of methanol incubation in vivo, in which, at 60 minutes after exposure, 16,000 ± 1,516
45 Absence of NET reduction indicates a defect in some of the metabolic pathways involved in intracellular
microbial killing.
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1 cells/mm3 were observed versus 23,350 ± 941 in controls (p < 0.001). Some differences in
2 neutrophil function were observed in blood samples treated with methanol in vitro and in vivo.
3 These differences are illustrated for the 60-minute postexposure samples in Table 4-16.
Table 4-16 Effect of methanol on neutrophil functions in in vitro and in vivo studies in
male Wistar rats.
In vitro studies (60 minutes)
Parameter Control
Phagocytic index (%) 89.8 ±3.07
Avidity index 4.53 ± 0.6
NET reduction (%) 3 1.6 ± 4.6
Adherence (%) 50.2 ±5.1
ap<0.01.
V< o.ooi.
Values are means ± SD for six animals.
Source: Parthasarathy et al. (2005b).
Parthasarathy et al. (2005b)
Methanol
81.6±2.2a
4.47 ±0.7
48.6±4.3b
39.8±2.4a
observed differences
In vivo studies (60 minutes)
Control
66.0 ±4.8
2.4 ±0.1
4.6 ±1.2
49.0 ±4.8
in the neutrophil
Methanol
84.0 ± 7.0b
3.4±0.3a
27.0 ± 4.6b
34.6±4.0b
functions of cells
4
5 exposed to methanol in vitro versus in vivo, most notably in the phagocytic index that was
6 reduced in vitro but significantly increased in vivo. However, functions such as adherence and
7 NET reduction showed consistency in the in vitro and in vivo responses. The authors noted that,
8 by and large, the in vivo effects of methanol on neutrophil function were more marked than those
9 in cells exposed in vitro.
10 Another study by Parthasarathy et al. (2005a) also exposed 6 male Wistar rats/group i.p.
11 to methanol at approximately 1/4 the LD50 (2.4 g/kg). The goal was to further monitor possible
12 methanol-induced alterations in the activity of isolated neutrophils and other immunological
13 parameters. The exposure protocol featured daily injections of methanol for up to 30 days in the
14 presence or absence of sheep RBCs. Blood samples were assessed for total and differential
15 leukocytes, and isolated neutrophils were monitored for changes in phagocytic and avidity
16 indices, NET reduction, and adherence. In the latter test, blood samples were incubated on a
17 nylon fiber column, then eluted from the column and rechecked for total and differential
18 leukocytes. Phagocytosis was monitored by incubating isolated buffy coats from the blood
19 samples with heat-killed C. albicans. NET reduction capacity examined the conversion of the
20 dye to formazan crystals within the cytoplasm. The relative percentage of formazan-positive cells
21 in each blood specimen gave a measure of methanol's capacity to bring about cell death. As
22 tabulated by the authors, there was a dose-dependent reduction in lymphoid organ weights
23 (spleen, thymus, and lymph node) in rats exposed to methanol for 15 and 30 days via i.p.
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1 injection, irrespective of the presence of sheep RBCs. Methanol also appeared to result in a
2 reduction in the total or differential neutrophil count. These and potentially related changes to
3 neutrophil function are shown in Table 4-17.
Table 4-17 Effect of intraperitoneally injected methanol on total and differential leukocyte
counts and neutrophil function tests in male Wistar rats.
Parameter
Without
Control
sheep red blood
15-day
methanol
cell treatment
30-day
methanol
With sheep
Control
red blood cell
15-day
methanol
treatment
30-day
methanol
Organ weights (mg)
Spleen
Thymus
Lymph node
1,223 ± 54
232 ± 12
32 ±2
910±63a
171 ±7a
24±3a
696 ± 83a'b
121 ± 10a'b
16 ± 2a'b
1,381 ±27
260 ±9
39 ±2
1,032 ±39a
172 ± 10a
28±la
839 ± 35^
130 ± 24a'b
23 ± la'b
Leukocyte counts
Total leukocytes
% neutrophils
% Lymphocytes
Neutrophil function
Phagocytic
index (%)
Avidity index
NET reduction
(%)
Adherence (%)
23,367
±946
24 ±8
71±7
tests
91.0 ±2.0
2.6 ±0.3
6.3 ±2.0
49.0 ±5.0
16,592
± l,219a
21±3
76 ±3
80.0±4.0a
3.2±0.5a
18.2±2.0a
44.0 ±5.0
13,283
± 2,553a'b
16±3a
79 ±5
79.0±2.0a
3.2±0.1a
15.0±1.0a'b
29.5 ± 5.0**
18,633
± 2,057
8±3
89 ±4
87.0 ±4.0
4.1±0.1
32.0 ±3.3
78.0 ±9.2
16,675
± 1,908
23±4a
78.5 ±4a
68.0±3.0a
2.6±0.3a
22.0±3.0a
52.0±9.0a
14,067
± 930^
15 ± 5a'b
82 ±6
63.0±4.0a
2.1±0.3a
19.0±2.4a
30.0 ± 4.3a'b
"p < 0.05 from respective control.
bp < 0.05 between 15-and 30-day treatment groups.
Values are means ± SD (n = 6).
Source: Parthasarathy et al. (2005a).
4 The study provided data that showed altered neutrophil functions following repeated
5 daily exposures of rats to methanol for periods up to 30 days. This finding is indicative of a
6 possible effect of methanol on the immunocompetence of an exposed host.
7 Parthasarathy et al. (2006a) reported on additional immune system indicators as part of a
8 study to determine the effects of methanol intoxication on the HPA axis. As described in
9 Section 4.4.3, immune function tests conducted included the footpad thickness test for DTH, a
10 leukocyte migration inhibition assay, the hemagglutination assay (measuring antibody titer), the
11 neutrophil adherence test, phagocytosis index, and a NET reduction and adherence assay used to
12 measure the killing ability of PMNs.
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1 Leukocyte migration and antibody titer were both significantly increased over controls
2 for all time points, while footpad thickness was significantly deceased in 15- and 30-day treated
3 animals. Neutrophil adherence was significantly decreased after 1 and 30 days of exposure. A
4 significant decrease in the NET reduction and adherence was found when comparing PMNs from
5 the 30-day treated animals with cells from the 15-day methanol-treated group.
6 Parthasarathy et al. (2007) reported the effects of methanol on a number of specific
7 immune functions. As before, 6 male Wistar rats/group were treated with 2,370 mg/kg methanol
8 in a 1:1 mixture in saline administered intraperitoneally for 15 or 30 days. Animals
9 scheduled/designated for termination on day 15 were immunized intraperitoneally with 5 x 109
10 sheep RBCs on the 10th day. Animals scheduled for day 30 termination were immunized on the
11 25th day. Controls were animals that were not exposed to methanol but immunized with sheep
12 RBCs as described above. Blood samples were obtained from all animals at sacrifice and
13 lymphoid organs including the adrenals, spleen, thymus, lymph nodes, and bone marrow were
14 removed. Cell suspensions were counted and adjusted to 1 x 108 cells/mL. Cell-mediated
15 immune responses were assessed using a footpad thickness assay and a leukocyte migration
16 inhibition (LMI) test, while humoral immune responses were determined by a hemagglutination
17 assay, and by monitoring cell counts in spleen, thymus, lymph nodes, femoral bone marrow, and
18 in splenic lymphocyte subsets. Plasma levels of corticosterone were measured along with levels
19 of such cytokines as TNF-a, IFN-y, IL-2, and IL-4. DNA damage in splenocytes and thymocytes
20 was also monitored using the Comet assay.
21 Table 4-18 shows decreases in the animal weight/organ weight ratios for spleen, thymus,
22 lymph nodes and adrenal gland as a result of methanol exposure. However, the splenocyte,
23 thymocyte, lymph node, and bone marrow cell counts were time-dependently lower in methanol-
24 treated animals.
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Table 4-18 Effect of methanol exposure on animal weight/organ weight ratios and on cell
counts in primary and secondary lymphoid organs of male Wistar rats.
Immunized
Organ Control 15 days 30 days
Animal weight/organ weight ratio
Spleen 3.88 ±0.55 2.85±0.36a 2.58±0.45a
Thymus 1.35 ±0.29 0.61 ±0.06" 0.63 ±0.04a
Lymph node 0.10 ±0.01 0.08 ±0.01" 0.06 ± 0.02a
Adrenal 0.14 ±0.01 0.15 ±0.01 0.12±0.01a'b
Cell counts
Splenocytes (x 108) 5.08 ±0.06 3.65±0.07a 3.71±0.06a
Thymocytes (x 108) 2.66 ±0.09 1.95±0.03a 1.86±0.09a
Lymph node (x 107) 3.03 ±0.04 2.77±0.07a 2.20±0.06a'b
Bone marrow (x 107) 4.67 ±0.03 3.04±0.09a 2.11±0.05a'b
Values are means ± six animals, "p < 0.05 versus control groups. bp < 0.05 versus 15-day treated group.
Source: Parthasarathy et al. (2007).
1 Parthasarathy et al. (2007) also documented their results on the cell-mediated and
2 humoral immunity induced by methanol. Leukocyte migration was significantly increased
3 compared to control animals, an LMI of 0.82 ± 0.06 being reported in rats exposed to methanol
4 for 30 days. This compares to an LMI of 0.73 ± 0.02 in rats exposed for 15 days and 0.41 ± 0.10
5 in controls. By contrast, footpad thickness and antibody titer were decreased significantly in
6 methanol-exposed animals compared to controls (18.32 ± 1.08, 19.73 ± 1.24, and 26.24 ± 1.68%
7 for footpad thickness; and 6.66 ± 1.21, 6.83 ± 0.40, and 10.83 ± 0.40 for antibody titer in 30-day,
8 15-day exposed rats, and controls, respectively).
9 Parthasarathy et al. (2007) also provided data in a histogram that showed a significant
10 decrease in the absolute numbers of Pan T cells, CD4, macrophage, major histocompatibility
11 complex (MHC) class II molecule expressing cells, and B cells of the methanol-treated group
12 compared to controls. The numbers of CDS cells were unaffected. Additionally, as illustrated in
13 the report, DNA single strand breakage was increased in immunized splenocytes and thymocytes
14 exposed to methanol versus controls. Although some fluctuations were seen in corticosterone
15 levels, the apparently statistically significant change versus controls in 15-day exposed rats was
16 offset by a decrease in 30-day exposed animals. Parthasarathy et al. (2007) also tabulated the
17 impacts of methanol exposure on cytokine levels; these values are shown in Table 4-19.
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Table 4-19 The effect of methanol on serum cytokine levels in male Wistar rats.
Cytokines (pg/mL)
IL-2
IL-4
TNF-a
IFN-y
Control
1,810 ±63.2
44.8 ±2.0
975 ± 32.7
1,380 ±55.1
Immunized
15 days
1,303.3 ±57.1a
74.0 ± 5. la
578.3 ± 42.6a
961.6 ±72.7a
30 days
1,088.3 ± 68.8a'b
78.8±4.4a
585 ± 45a
950±59.6a
a/> < 0.05 versus control groups.
bp < 0.05 versus 15-day treated group.
Values are means ± six animals.
Source: Parthasarathy et al.(2007).
1 Drawing on the results of DNA single strand breakage in this experiment, the authors
2 speculated that methanol-induced apoptosis could suppress specific immune functions such as
3 those examined in this research report. Methanol appeared to suppress both humoral and cell-
4 mediated immune responses in exposed Wistar rats.
4.6. Synthesis of Major Noncancer Effects
4.6.1. Summary of Key Studies in Methanol Toxicity
5 A substantial body of information exists on the toxicological consequences to humans
6 who consume or are acutely exposed to large amounts of methanol. Neurological and
7 immunological effects have been noted in adult human subjects acutely exposed to as low as
8 200 ppm (262 mg/m3) methanol (Mann et al.. 2002: Chuwers et al.. 1995). Nasal irritation effects
9 have been reported by adult workers exposed to 459 ppm (601 mg/m3) methanol. Frank effects
10 such as blurred vision and bilateral or unilateral blindness, coma, convulsions/tremors, nausea,
11 headache, abdominal pain, diminished motor skills, acidosis, and dyspnea begin to occur as
12 blood levels approach 200 mg methanol/L, and 800 mg/L appears to be the threshold for
13 lethality. Data for subchronic, chronic, or in utero human exposures are very limited.
14 Determinations regarding longer term effects of methanol are based primarily on animal studies.
15 An end-point-by-end-point survey of the primary noncancer effects of methanol in
16 experimental animals is given in the following paragraphs. Tabular summaries of the principal
17 toxicological studies that have examined the noncancer effects of methanol when experimental
18 animals were exposed to methanol via the oral or inhalation routes are provided in Tables 4-20
19 and 4-21. Figures 4-1 and 4-2 graphically depict the oral and inhalation exposure-response
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1 information from these studies, illustrating the relationship between NOAELs and LOAELs that
2 have been identified. Most studies focused on developmental and reproductive effects. A large
3 number of the available studies were performed by routes of exposure (e.g., i.p.) that are less
4 relevant to the assessment. The data are summarized in separate sections that address oral
5 exposure (Section 4.6.1.1) and inhalation exposure (Section 4.6.1.2).
Table 4-20 Summary of noncancer effects reported in repeat exposure and developmental
studies of methanol toxicity in experimental animals (oral).
Species, strain,
number/sex
Rat
Sprague-Dawley
30/sex/group
Rat
Sprague-Dawley
100/sex/group
Mouse
Swiss
NOAEL
Dose/duration (mg/kg-day)
0, 100, 500, and
2,500 mg/kg-day for 500
13 wk
0, 500, 5,000, or
20,000 ppm (v/v) in
drinking water, for
104 wk. Doses were
approx. 0, 46.6, 466, ND
and 1,872 mg/kg-day
(male) and 0, 52.9,
529, and 2, 101
mg/kg-day (female)
560, 1,000 and 2,100
mg/kg/day (female)
and 550, 970, and
1,800 mg/kg/day ^/" i,uuu
(male), 6 days/wk for
life
LOAEL
(mg/kg-day) Effect
Reduction of brain
weights, increase in the
2,500 serum activity of ALT
and AP. Increased liver
weights
No noncancer effects
were reported
Increased incidence of
1,800-2,100 liver parenchymal cell
necrosis
Reference
TRL (1986)
Soffritti et al.
(2002)
Apaja (1980)
Reproductive/developmental toxicity studies
Rat
Long-Evans
10 pregnant
females/group
Mouse
CD-I
8 pregnant
females and 4
0 and 2,500 mg/kg-
day on either x T .
NA
GD15-GD17 or
GD17-GD19.
4 g/kg-day in 2 daily .
dosesonGD6-GD15
Neurobehavioral
, ,„„ deficits (such as
homing behavior,
suckling ability
Increased incidence of
totally resorbed litters,
. „„„ cleft palate and
exencephaly. A
decrease in the number
of live fetuses/litter
Infurna and
Weiss (1986)
Rogers et al.
(1993b)
NA = Not applicable; ND = Not determined; M= male, F=female.
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Table 4-21 Summary of repeat exposure and developmental studies of methanol toxicity in
experimental animals (inhalation exposure).
Species, strain,
number/sex
Monkey
M. fascicularis,
1 or 2 animals/group
Dog (2)
Rat
Sprague-Dawley
5 males/ group
Rat
Sprague-Dawley
5 males/ group
Rat
Sprague-Dawley
5/sex/group
Monkey
M. fascicularis
3/sex/group
Rat
Sprague-Dawley
10/sex/group
Rat
Sprague-Dawley
1 5/sex/group
Monkey
M. fascicularis
2 or 3 animals/
group/time point
Rat
F344
20/sex/group
Mouse
B6C3FJ
30/sex/group
Mouse
B6C3FJ
52-53/sex/group
Dose/duration
0, 3,000, 5,000, 7,000,
or 10,000 ppm, 21
hr/day, for up to 14
days
10,000 ppm for 3 min,
8 times/day for 100
days
0, 200, 2000, or
10,000 ppm, 8 hr/day,
5 days/wk for up to 6
wk
0, or 200 ppm,
6 hr/day, for either 1
or 7 days
0, 500, 2,000, or
5,000 ppm, 5 days/wk
for 4 wk
0, 500, 2,000, or
5,000 ppm, 5 days/wk
for 4 wk
0,300, or 3,000 ppm,
6 hr/day, 5 days/wk
for 4 wk
0 or 2,500 ppm, 6
hr/day, 5 days/wk for
4wk
0, 10, 100, or
1,000 ppm, 21 hr/day
for either 7, 19, or 29
mo
0, 10, 100, or
1,000 ppm, 20 hr/day,
for 12 mo
0, 10, 100, or
1,000 ppm, 20 hr/day,
for 12 mo
0, 10, 100, or
1,000 ppm, 20 hr/day,
for 18 mo
NOAEL LOAEL
(ppm) (ppm)
ND NDa
NA NA
NA 200
NA 200
5,000 NA
5,000 NA
NA 300
NA 2,500
ND NDa
NA NA
NA NA
100 1,000 b
Effect
Clinical signs of toxicity, CNS
changes, including degeneration
of the bilateral putamen, caudate
nucleus, and claustrum. Edema of
cerebral white matter.
None
Transient reduction in plasma
testosterone levels
Transient reduction in plasma
testosterone levels
No compound-related effects
No compound-related effects
Reduction in size of thyroid
follicles
Reduction of relative spleen
weight in females,
histopathologic changes to the
liver, irritation of the upper
respiratory tract
Limited fibrosis of the liver;
Possible myocardial and renal
effects; ; Fibrosis of responsive
stellate cells in the brain
No compound-related effects
No clear-cut compound-related
effects
Increase in absolute kidney and
spleen weight, decrease in
absolute and relative testis weight
Reference
NEDO
(1987)
Sayers et al.
(1944)
Cameron et
al. (1984)
Cameron et
al. (1985)
Andrews et
al. (1987)
Poon et al.
(19941
Poon et al.
(19951
NEDO
•(19871
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Species, strain,
number/sex
Rat
F344
52/sex/group
Rat
Sprague-Dawley
15/pregnant
females/group
Rat
Sprague-Dawley
36/pregnant
females/group
Rat
Sprague-Dawley
FI and F2 generations
of a two-generation
study
Rat
Sprague-Dawley
Follow-up study of
brain weights in FI
generation of
10-14/sex/group inFi
generation
Mouse
CD-I
30-1 14 pregnant
females/group
Mouse
CD-I
12-17 pregnant
females/group
Dose/duration
0, 10, 100, or
1,000 ppm, -20 hr/day
for 2 yr
0, 5,000, 10,000, or
20,000 ppm, 7 hr/day
on either GDI -GDI 9
orGD7-GD15.
0, 200, 1,000, or
5,000 ppm,
22.7 hr/day, on
GD7-GD17
0, 10, 100, or
1,000 ppm, 20 hr/day;
FI- birth to end of
mating (M) or
weaning (F); F2- birth
to 8 wks
0, 500, 1,000, and
2,000 ppm; GDO
through F! 8 wks
0, 1,000, 2,000, 5,000,
7,500, 10,000, or
15,000 ppm, 7 hr/day
onGD6-GD15.
0 and 10,000 ppm
7 hr/day, 2
consecutive days
during GD6-GD 13 or
on one day during
GD5-GD9
NOAEL LOAEL
(ppm) (ppm) Effect
fluctuations in urinalysis,
100 1,000 b hematology, and clinical
chemistry parameters
Reduced fetal body weight,
increased incidence of visceral
5,000 10,000 and skeletal abnormalities,
including rudimentary and extra
cervical ribs
Late-term resorptions, reduced
fetal viability, increased
1,000 5,000 frequency of fetal malformations,
variations and delayed
ossifications.
Reduced weight of brain,
1 00 1 000 Pituitary, and thymus at 8, 16 and
24 wk postnatal in F! and at 8 wk
inF2
Reduced brain weight at 3 wk and
^™ ! ™« 6 wk (males only). Reduced brain
500 1,000 , ,, • w *0 i
and cerebrum weight at 8 wk
(males only)
Increased incidence of extra
cervical ribs, cleft palate,
1,000 2,000 exencephaly; reduced fetal weight
and pup survival, Delayed
ossification
Cleft palate, exencephaly, skeletal
malformations
Reference
Nelson et al.
(19851
NEDO
(19871
Rogers et al.
(1993b)
Rogers and
Mole (19971
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Species, strain,
number/sex
Rat
Long-Evans
6-7 pregnant
females/group
Rat
Long-Evans
10-12 pregnant
females/group
Monkey
M. fascicularis
12 monkeys/group
Dose/duration
0 or 15,000 ppm,
7 hr/day on
GD7-GD19
0 or 4,500 ppm from
GD10toPND21.
0, 200, 600, or
1,800 ppm, 2.5 hr/day,
7 days/wk, during
premating, mating and
gestation
NOAEL LOAEL
(ppm) (ppm) Effect
NA 15,000 Reduced pup weight
NA 4,500 Subtle cognitive deficits
Shortened period of gestation;
may be related to exposure (no
dose-response),
ND ND ° neurotoxicological deficits
including reduced performance in
the VDR test; may be related to
premature births.
Reference
Stanton et al.
(19951
Weiss et al.
(19961
Burbacher et
al. (2004a;
2004b;
1999a:
1999b)
a Effects in the brain and other organs were noted at exposures as low as 100 ppm (131 mg/m3), but due to substantial
uncertainties associated with these results, EPA was not able to identify a NOAEL or LOAEL from this study.
b A LOAEL of 1,000 ppm was identified by the authors of these studies, but the weight-of evidence is low (see Section 4.2.2.3).
0 Lhe shortened gestation period was noted dams exposed to as low as 200 ppm (263 mg/m3) and signs of possible developmental
neurotoxicity were noted in the offspring of dams exposed to as low as 600 ppm (789 mg/m3). However, because of uncertainties
associated with these results, including the lack of a clear dose-response, EPA was not able to identify a NOAEL or LOAEL
from this study.
ND = Not determined due to study limitations such as small number of animals /time point/ exposure level
NA = Not applicable.
Exposure Concentration
(Oral, mg/kg-day)
_•* P
-* o o o
-I 0 0 0 0
1 Low Dose T High Dose A NOAEL V LOAEL
2-9 Gestation Days
Mouse
T *
1 2
91-Day Suberonie
Rat
T T
3 4
Lifespan
Mouse Rat
V
5 6
1= developmental neurobehavioral deficits (Infurna and Weiss. 1986)
2 = resorbed litters, fetal death, cleft palate, exencephaly (Rogers etal.. 1993b)
3 = reduced brain weight (TRL. 1986)
4 = increased liver weight and serum activity of ALT/AP (TRL. 1986)
5 = parencymal cell necrosis (Apaja. 1980)
6 = (cancer study): no noncancer effects were reported (Soffritti et al.. 2002)
Figure 4-1 Exposure response array for noncancer effects reported in animals from repeat
exposure and developmental studies of methanol (Oral).
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Monkey Mouse
I 10,000 , r \
1 1 i 1 \
g °" 1,000 , I -»— I
Ł •§ 100 ,
3 f :
UJ 10 !
1 Low Dose T High Dose NOAEL T LOAEL
1. y. 1 ll 'ID • HNL) 10 *il"JJy. -il'li 1'nu !i,,y.
Rat
1 : 1 2 345
Rat
•w
6 r
Monkey Rat
T Ą
89 10 11 12
Monkey Mouse Rat
-^ -Ą-
13 14 15
Note: Oval shapes in the array indicate principal studies used in reference value determinations.
Effects (bolded effects from principal studies were used in reference value determinations):
1= reproductive (shortened gestation) and developmental neurotoxicity (delayed VDR) (Burbacher et al.. 2004b: Burbacher et al.. 1999b);
N(L)OAEL not determined
2 = extra cervical ribs, cleft palate, excencephaly, reduced fetal weight & pup survival, delayed ossification (Rogers and Mole. 1997; Rogers et
al.. 1993b);
3 = reduced fetal weight, visceral and skeletal abnormalities, including rudimentary and extra cervical ribs (Nelson et al.. 1985);
4 = late-term resorptions, reduced fetal viability, fetal malformations, variations and delayed ossifications (NEDO. 1987);
5 = reduced pup weight (Stanton et al.. 1995)
6 = reduced weight of brain, pituitary, and thymus at 3, 6, 8, 16 and 24 wk postnatal in Fl and at 8 wk in F2 generation (NEDO. 1987)
7 = subtle cognitive deficits (Weiss et al.. 1996)
8 = clinical signs of toxicity, CNS changes in bilateral putamen, caudate nucleus, and claustrum. edema of cerebral white matter (NEDO. 1987)
9 = no methanol-related effects (Andrews et al.. 1987)
10 = transient reduction in plasma testosterone levels (Cameron et al.. 1985; Cameron et al.. 1984)
11 = no methanol-related effects (Andrews et al.. 1987)
12 = reduction in size of thyroid follicles (Poonetal.. 1995; Poonetal.. 1994)
13 = limited fibrosis of the liver, possible myocardial and renal effects; fibrosis of responsive stellate cells in the brain (NEDO. 1987)
14 = increased absolute kidney, spleen weight; decreased relative testes weight (NEDO. 1987); tentative LOAEL due to low weight-of-evidence.
15 = fluctuations in urinalysis, hematology, and clinical chemistry parameters (NEDO. 1987); tentative LOAEL due to low weight-of-evidence..
Figure 4-2 Exposure response array for noncancer effects reported in animals from repeat
exposure and developmental studies of methanol (Inhalation).
4.6.1.1. Oral
1 There have been very few subchronic, chronic, or in utero experimental studies of oral
2 methanol toxicity. In one such experiment, an EPA-sponsored 90-day gavage study in Sprague-
3 Dawley rats suggested a possible effect of the compound on the liver (TRL, 1986). In the
4 absence of gross or histopathologic evidence of toxicity, fluctuations on some clinical chemistry
5 markers of liver biochemistry and increases in liver weights at the highest administered dose
6 (2,500 mg/kg-day) justify the selection of the mid-dose level (500 mg/kg-day) as a NOAEL for
7 this effect under the operative experimental conditions. That the bolus effect may have been
8 important in the induction of those few effects that were apparent in the subchronic study is
9 suggested by the outcome of lifetime drinking water study of methanol that was carried out in
10 Sprague-Dawley rats by Soffritti et al. (2002). According to the authors, no noncancer
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1 toxicological effects of methanol were observed at drinking water concentrations of up to
2 20,000 ppm (v/v). Based on default assumptions on drinking water consumption and body
3 weight gain assumptions, the high concentration was equivalent to a dose of 1,780 mg/kg-day in
4 males and 2,177 mg/kg-day in females. In the stated absence of any changes to parameters
5 reflective of liver toxicity in the Soffritti et al. (2002) study, the slight impacts to the liver
6 observed in the subchronic study (TRL, 1986) at 2,500 mg/kg-day suggest the latter dose to be a
7 minimal LOAEL. Logically, the true but unknown threshold would at the high end of the range
8 from 500 (the default NOAEL) to 2,500 mg/kg-day for liver toxicity via oral gavage.
9 Two studies have pointed to the likelihood that oral exposure to methanol is associated
10 with developmental neurotoxicity or developmental deficits. When Infurna and Weiss (1986)
11 exposed pregnant Long-Evans rats to 2% methanol in drinking water (providing a dose of
12 approximately 2,500 mg/kg-day), they observed no reproductive or developmental sequelae
13 other than from 2 tests within a battery of fetal behavioral tests (deficits in suckling ability and
14 homing behavior). In the oral section of the Rogers et al. (1993b) study, such teratological effects
15 as cleft palate and exencephaly and skeletal malformations were observed in fetuses of pregnant
16 female mice exposed to daily gavage doses of 4,000 mg/kg methanol during GD6-GD15.
17 Likewise, an increase in totally resorbed litters and a decrease in the number of live fetuses/litter
18 appear likely to have been an effect of the compound. Similar skeletal malformations were
19 observed by Rogers and Mole (1997), Rogers et al.(1993b), and Nelson et al. (1985) following
20 inhalation exposure.
4.6.1.2. Inhalation
21 Some clinical signs, gross pathology, and histopathological effects of methanol have been
22 seen in experimental animals including adult nonhuman primates exposed to methanol vapor.
23 Results from an unpublished study (NEDO, 1987) of M. fascicularis monkeys, chronically
24 exposed to concentrations as low as 10 ppm for up to 29 months, resulted in histopathological
25 effects in the liver, kidney, brain and peripheral nervous system. These results were generally
26 reported as subtle or transient. However, brain effects, such as responsive stellate cells in
27 cerebral white matter, were observed as many as 11 months after the cessation of exposure.
28 Confidence in the methanol-induced findings of effects in adult nonhuman primates is limited
29 because this study utilized a small number (2-3) of animals/dose level/time of sacrifice and
30 inadequately reporting of results (e.g., limited details on materials and methods, lack of clear
31 documentation of a concurrent control group). Due to these concerns NOAEL and LOAEL
32 values could not be identified and the NEDO (1987) monkey studies have limited utility in
33 derivation of an RfC.
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1 A number of studies have examined the potential toxicity of methanol to the male
2 reproductive system (Lee et al., 1991; Cameron et al., 1985; Cameron et al., 1984). The data
3 from Cameron et al. (1985; 1984) showed a transient but not necessarily dose-related decrease in
4 serum testosterone levels of male Sprague-Dawley rats. Lee et al. (1994) reported the appearance
5 of testicular lesions in 18-month-old male Long-Evans rats that were exposed to methanol for
6 13 weeks and maintained on folate-deficient diets. Taken together, the Lee et al. (1994) and
7 Cameron et al. (1985; 1984) study results could indicate chemically-related strain on the rat
8 system as it attempts to maintain hormone homeostasis. However, the available data are
9 insufficient to definitively characterize methanol as a toxicant to the male reproductive system.
10 When Sprague-Dawley rats were exposed to methanol, 6 hours/day for 4 weeks, there
11 were some signs of irritation to the eyes and nose. Mild changes to the upper respiratory tract
12 were also described in Sprague-Dawley rats that were exposed for 4 weeks to up to 300 ppm
13 methanol (Poon et al., 1995). Other possible effects of methanol in rats included a reduction in
14 size of thyroid follicles (Poon et al., 1994), panlobular vacuolation of the liver, and a decrease in
15 spleen weight (Poon et al., 1995). NEDO (1987) reported dose-related increases in moderate
16 fatty degeneration in hepatocytes of male mice exposed via inhalation for 12 months, but this
17 finding was not observed in the NEDO (1987) 18-month mouse inhalation study. Nodes reported
18 in the liver of mice from the 18-month study may have been precancerous, but the 18-month
19 study duration was not of sufficient duration to make a determination.
20 One of the most definitive and quantifiable toxicological impacts of methanol when
21 administered to experimental animals via inhalation is related to the induction of developmental
22 abnormalities in fetuses exposed to the compound in utero. Developmental effects have been
23 demonstrated in a number of species, including monkeys, but particularly rats and mice. Most
24 developmental teratological effects appear to be more severe in the latter species. For example,
25 in the study of Rogers et al. (1993b) in which pregnant female CD-I mice were exposed to
26 methanol vapors on GD6-GD15 at a range of concentrations, reproductive and fetal effects
27 included an increase in the number of resorbed litters, a reduction in the number of live pups, and
28 increased incidence of exencephaly, cleft palate, and the number of cervical ribs. While the
29 biological significance of the cervical rib effect has been the subject of much debate (See
30 discussion of Chernoff and Rogers (2004) in Section 5), it appears to be the most sensitive
31 indicator of developmental toxicity from this study, with a NOAEL of 1,000 ppm (1,310 mg/m3).
32 In rats, however, the most sensitive developmental effect, as reported in the NEDO (1987)
33 two-generation inhalation studies, was a postnatal reduction in brain weight at 3, 6 and 8 weeks
34 postnatally, which was significantly lower than controls when pups and their dams were exposed
35 to 1,000 ppm (1,310 mg/m3) during gestation and throughout lactation. The NOAEL reported in
36 this study was 500 ppm (655 mg/m3).
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1 Rogers and Mole (1997) addressed the question of which period of gestation was most
2 critical for the adverse developmental effects of methanol in CD-I rats. Such malformations and
3 anomalies as cleft palate, exencephaly, and a range of skeletal defects, appeared to be induced
4 with a greater incidence when the dams were exposed on or around GD6. These findings were
5 taken to indicate that methanol is most toxic to embryos during gastrulation and in the early
6 stages of organogenesis. However, NEDO (1987) gestation-only and two-generation studies
7 showed that significant reductions in brain weight were observed at a lower exposure levels
8 when pups and their dams were exposed during lactation as well as gestation, indicating that
9 exposure during the later stages of organogenesis, including postnatal development, can
10 significantly contribute to the severity of the effects in this late-developing organ system.
11 In comparing the toxicity (NOAELs and LOAELs) for the onset of developmental effects
12 in mice and rats exposed in utero, there is suggestive evidence from the above studies that mice
13 may be more susceptible to methanol than rats. Supporting evidence for this proposition has
14 come from in vitro studies in which rat and mouse embryos were exposed to methanol in culture
15 (Andrews et al., 1993). Further evidence for species-by-species variations in the susceptibility of
16 experimental animals to methanol during organogenesis has come from experiments on monkeys
17 (Burbacher et al., 2004a: 2004b: 1999a: 1999b). In these studies, exposure of monkeys to
18 methanol during premating, mating, and throughout gestation resulted in a shorter period of
19 gestation in dams exposed to as low as 200 ppm (263 mg/m3). Though statistically significant,
20 the finding of a shortened gestation length may be of limited biological significance. Gestational
21 age, birth weight and infant size observations in all exposure groups were within normal ranges
22 for M. fascicularis monkeys, and other "signs of possible difficulty in the maintenance of
23 pregnancy" reported , such as vaginal bleeding, are considered normal within 1-4 days of
24 delivery and do not necessarily imply a risk to the fetus [as cited in NTP-CERHR (2004)]. As
25 discussed in Section 4.4.2, there is also evidence from this study that methanol caused
26 neurobehavioral effects in exposed monkey infants that may be related to the gestational
27 exposure. However, the data are not conclusive, and a dose-response trend is not robust. There is
28 insufficient evidence to determine if the primate fetus is more or less sensitive than rodents to
29 methanol teratogenesis. The use of a cohort design necessitated by the complexity of this study
30 may have limited its power to detect effects. Because of the uncertainties associated with these
31 results, including the lack of a clear dose-response for decreased in gestational length and
32 neurological effects, EPA was not able to identify a definitive NOAEL or LOAEL from this
33 study. This study does support the weight of evidence for developmental neurotoxicity in the
34 hazard characterization of low-level methanol exposure.
35 Weiss et al. (1996) and Stanton et al. (1995) evaluated the developmental and
36 developmental neurotoxicological effects of methanol exposure on pregnant female Long-Evans
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1 rats and their progeny. In the latter study, exposure of dams to 15,000 ppm (19,656 mg/m3),
2 7 hours/day on GD7-GD19 resulted in reduced weight gain in pups, but produced little other
3 evidence of adverse developmental effects. The authors subjected the pups to a number of
4 neurobehavioral tests that gave little if any indication of compound-related changes. This study,
5 while using high exposure levels, was limited in its power to detect effects due to the small
6 number of animals used. In the Weiss et al. (1996) study, exposure of pregnant female Long-
7 Evans rats to 0 or 4,500 (0 and 5,897 mg/m3) methanol from GD6 to PND21 likewise provided
8 fluctuating and inconsistent results in a number of neurobehavioral tests that did not necessarily
9 indicate any compound-related impacts. The finding of this study indicated subtle cognitive
10 defects not on the learning of an operant task but in the reversal learning. This study also
11 reported exposure-related changes in neurodevelopmental markers of NCAMs on PND4.
12 NCAMs are a family of glycoproteins that is needed for migration, axonal outgrowth, and
13 establishment of the pattern for mature neuronal function.
14 Taking all of these findings into consideration reinforces the conclusion that the most
15 appropriate endpoints for use in the derivation of an inhalation RfC for methanol are associated
16 with developmental neurotoxicity and developmental toxicity. Among an array of findings
17 indicating developmental neurotoxicity and developmental malformations and anomalies that
18 have been observed in the fetuses and pups of exposed dams, an increase in the incidence of
19 cervical ribs of gestationally exposed mice (Rogers et al., 1993b) and a decrease in the brain
20 weights of gestationally and lactationally exposed rats (NEDO, 1987) appear to be the most
21 robust and most sensitive effects.
4.7. Noncancer MOA Information
22 There is controversy over the possible roles of the parent compound, metabolites, reactive
23 oxygen species (from methanol metabolism competitively inhibiting other catalase activity) and
24 folate deficiency (potentially associated with methanol metabolism) in the developmental
25 toxicity of methanol. Experiments that have attempted to address these issues are reviewed in the
26 following paragraphs.
4.7.1. Role of Methanol and Metabolites in the Developmental Toxicity of
Methanol
27 Dorman et al. (1995) conducted a series of in vitro and in vivo studies that provide
28 information for identifying the proximate teratogen associated with developmental toxicity in
29 CD-I mice. The studies used CD-I ICR BR (CD-I) mice, HPLC grade methanol, and
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1 appropriate controls. PK and developmental toxicity parameters were measured in mice exposed
2 to sodium formate (750 mg/kg by gavage), a 6-hour methanol inhalation (10,000 or 15,000 ppm),
3 or methanol gavage (1.5 g/kg). In the in vivo inhalation study, 12-14 dams/ group were exposed
4 to 10,000 ppm methanol for 6 hours on GD8,46 with and without the administration of
5 fomepizole to inhibit the metabolism of methanol by ADH1. Dams were sacrificed on GD10, and
6 fetuses were examined for neural tube patency. As shown in Table 4-22, the incidence of fetuses
7 with open neural tubes was significantly increased in the methanol group (9.65% in treated
8 versus 0 in control) and numerically but not significantly increased in the group treated with
9 methanol and fomepizole (7.21% in treated versus 0 in controls). Rodents metabolize methanol
10 via both ADH1 and CAT (as discussed in Section 3.1) which, when coupled with the Dorman et
11 al. (1995) observation that maternal formate levels in blood and decidual swellings (swelling of
12 the uterine lining) did not differ in dams exposed to methanol alone or methanol and fomepizole,
13 suggest that the role of ADH1 relative to CAT and nonenzymatic methanol clearance is not of
14 great significance in adult rodents.
Table 4-22 Developmental outcome on GD10 following a 6-hour 10,000 ppm
(13,104 mg/m3) methanol inhalation by CD-mice or formate gavage
(750 mg/kg) on GD8.
Treatment
Air
Air/fomepizole
Methanol
Methanol/fomepizole
Water
Formate
No. of litters
14
14
12
12
10
14
Open neural tubes (%)
2.29 ± 1.01
2.69 ±1.19
9.65±3.13a
7.21 ±2.65
0
2.02 ± 1.08
Head length (mm)
3. 15 ±0.03
3.20 ±0.05
3.05 ±0.07
3.01 ±0.05
3.01 ±0.07
2.91 ±0.08
Body length (mm)
5. 89 ±0.07
5. 95 ±0.09
5.69 ±0.13
5.61±0.11
5.64 ±0.11
5.49 ±0.12
*p < 0.05, as calculated by the authors.
Values are means ± SD
Source: Dorman et al. (1995) (adapted).
15 The data in Table 4-22 suggest that the formate metabolite is not responsible for the
16 observed increase in open neural tubes in CD-I mice following methanol exposure. Formate
17 administered by gavage (750 mg/kg) did not increase this effect despite the observation that this
18 formate dose produced the same toxicokinetic profile as a 6-hour exposure to 10,000 ppm
19 methanol vapors (48.33 mg/L formate in maternal blood and 2.0 mM formate/kg in decidual
20 swellings). However, the data are consistent with the hypotheses that the formaldehyde
46 Dorman et al. (1995) state that GD8 was chosen because it encompasses the period of murine neurulation and the
time of greatest vulnerability to methanol-induced neural tube defects.
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1 metabolite of methanol may play a role. Both CAT and ADH1 activity are immature at days past
2 conception (DPC)8 (Table 4-23). If fetal ADH1 is more mature than fetal CAT, it is conceivable
3 that the decrease in the open neural tube response observed for methanol combined with
4 fomepizole (Table 4-22) may be due to fomepizole having a greater effect on the metabolism of
5 fetal methanol to formaldehyde than is observed in adult rats. Unfortunately, the toxicity studies
6 were carried out during a period of development where ADH1 expression and activity are just
7 starting to develop (Table 4-23); therefore, it is uncertain whether any ADH1 was present in the
8 fetus to be inhibited by fomepizole.
Table 4-23 Summary of ontogeny of relevant enzymes in CD-I mice and humans.
CD-I Mouse
Days Past Conception (DPC)
6.5 7.5 8.5 9.5
Somites (8-12) (13-20) (21-29)
Human
Trimesters
123
CAT
mRNA
activity3
embryo 1 10 20
VYS 10 15 20
N/A N/A N/A
ADH1
mRNA - -
activity3
embryo 320 460 450
VYS 240 280 290
+ + +
ADH3
mRNA + + +
activity3
embryo 300 490 550
VYS 500 500 550
- - +
"Activity of CAT and ADH1 are expressed as nmol/minute/mg and pmol/minute/mg, respectively.
Source: Harris et al. (2003).
9 Dorman et al. (1995) provide additional support for their hypothesis that methanol's
10 developmental effects in CD-I mice are not caused by formate in an in vitro study involving the
11 incubation of GD8 whole CD-I mouse embryos with increasing concentrations of methanol or
12 formate. Developmental anomalies were observed on GD9, including cephalic dysraphism,
13 asymmetry and hypoplasia of the prosencephalon, reductions of brachial arches I and II,
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1 scoliosis, vesicles on the walls of the mesencephalon, and hydropericardium (Table 4-24). The
2 concentrations of methanol used for embryo incubation (0-375 mM or 0-12,000 mg/L) were
3 chosen to be broadly equivalent to the peak methanol levels in plasma that have been observed
4 (approximately 100 mM or 3,200 mg/L) after a single 6-hour inhalation exposure to 10,000 ppm
5 (13,104 mg/m3). As discussed above, these exposure conditions induced an increased incidence
6 of open neural tubes on GD10 embryos when pregnant female CD-I mice were exposed on GD8.
7 (Table 4-22). Embryonic lesions such as cephalic dysraphism, prosencephalic lesions, and
8 brachial arch hypoplasia were observed with 250 mM (8,000 mg/L) methanol and 40 mM
9 (1,840 mg/L) formate. The study authors noted that a formate concentration of 40 mM
10 (1,840 mg/L) greatly exceeds blood formate levels in mice inhaling 15,000 ppm methanol
11 (0.75 mM = 35 mg/L), a teratogenic dose.
Table 4-24 Dysmorphogenic effect of methanol and formate in neurulating CD-I mouse
embryos in culture (GD8).
Live embryos
Cephalic
dysraphism
Concentration No.
Treatment (mg/L) Total abnormal Severe
Vehicle
Methanol
Formate
1,984
4,000
5,984
8,000
12,000
184
368
552
920
1,840
20
13
14
13
15
12
12
13
9
16
16
3
1
5
7
7
7
2
5
5
7
14a
0
0
1
2
2
6a
0
1
0
2
10a
Mode-
rate
2
0
0
4
5
5
0
5
5
5
4
Prosencephalic lesions
Total Hypoplasia
2
0
2
6
7
lla
0
6
5
7
14a
2
1
2
3
7a
9a
2
4
1
2
3
Asymmetry Total 1
0
0
2
1
1
1
0
2
2
1
5a
2
1
4
4
8
10a
2
6
3
3
8
Brachial
arch
lypoplasia
0
0
1
1
6a
8a
1
0
0
1
13a
a/> < 0.05, as calculated by the authors.
Source: Dorman et al. (1995) (adapted).
12 As discussed in Section 4.3.3, a series of studies by Harris et al. (2004; 2003) also
13 provide evidence as to the moieties that may be responsible for methanol-induced developmental
14 toxicity. Harris et al. (2004) have shown that among methanol and its metabolites, viability of
15 cultured rodent embryos is most affected by formate. In contrast, teratogenic endpoints (of
16 interest to this assessment) in cultured rodent embryos are more sensitive to methanol and
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1 formaldehyde than formate. Data from these studies indicate that developmental toxicity may be
2 more related to formaldehyde than methanol, as formaldehyde-induced teratogenicity occurs at
3 several orders of magnitude lower than methanol (Table 4-12) (Hansen et al., 2005; Harris et al.,
4 2004). It should also be noted that CAT, ADH1, and ADH3 activities are present in both the rat
5 embryo and VYS at stages as early as 6-12 somites (Harris et al., 2003): thus, it is presumable
6 that in these ex vivo studies methanol is metabolized to formaldehyde and formaldehyde is
7 subsequently metabolized to S-formylglutathione.
8 Studies involving GSH depletion have been offered as support for the hypothesis that
9 formaldehyde is a key proximal teratogen, and for the role of ROS (see Section 4.7.3). Inhibition
10 of GSH synthesis with butathione sulfoximine (BSO) has little effect on developmental toxicity
11 endpoints, yet treatment with BSO and methanol or formaldehyde increases developmental
12 toxicity (Harris et al., 2004). Among the enzymes involved in methanol metabolism, only ADH3-
13 mediated metabolism of formaldehyde is GSH dependent. While "depletion of GSH, as the
14 major cellular antioxidant, will also increase the accumulation of reactive oxygen species
15 (ROS)."This hypothesis that ADH3-mediated metabolism of formaldehyde is important for the
16 amelioration of methanol's developmental toxicity is also supported by the diminished ADH3
17 activity in the mouse versus rat embryos, which is consistent with the greater sensitivity of the
18 mouse to methanol developmental toxicity (Harris et al., 2003) (Section 4.3.3).
19 Without positive identification of the actual moiety responsible for methanol-induced
20 teratogenicity, MOA remains unclear. If the moiety is methanol, then it is possible that
21 generation of NADH during methanol oxidation creates an imbalance in other enzymatic
22 reactions. Studies have shown that ethanol intake leads to a >100-fold increase in cellular
23 NADH, presumably due to ADH1-mediated reduction of the cofactor NAD+ to NADH
24 (Cronholm, 1987; Smith and Newman, 1959). This is of potential importance because, for
25 example, ethanol intake has been shown to increase the in vivo and in vitro enzymatic reduction
26 of other endogenous compounds (e.g., serotonin) in humans (Svensson et al., 1999; Davis et al.,
27 1967). In rodents, CAT-mediated methanol metabolism may obviate this effect; in humans,
28 however, methanol is primarily metabolized by ADH1.
29 If the teratogenic moiety of methanol is formaldehyde, then reactivity with protein
30 sulfhydryls and nonprotein sulfhydryls (e.g., GSH) or DNA protein cross-links may be involved.
31 Metabolic roles ascribed to ADH3, particularly regulation of S-nitrosothiol biology (Foster and
32 Stamler, 2004), could also be involved in the MOA. Recently, Staab et al. (2008) have shown
33 that formaldehyde alters other ADH3-mediated reactions through cofactor recycling and that
34 formaldehyde alters levels of cellular S-nitrosothiol, which plays a key role in cellular signaling
35 and many cellular functions and pathways (Hess et al., 2005).
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1 Studies such as those by Harris et al. (2004; 2003) and Dorman et al. (1995) suggest that
2 formate is not the metabolite responsible for methanol's teratogenic effects. The former
3 researchers suggest that formaldehyde is the proximate teratogen, and provide evidence in
4 support of that hypothesis. However, questions remain. As has been discussed, the capacity for
5 the metabolism of methanol to formaldehyde is likely lower in the fetus and neonate versus
6 adults (Section 3.3). Further, researchers in this area have not yet reported using a sufficient array
7 of enzyme inhibitors to conclusively identify formaldehyde as the proximate teratogen. Studies
8 involving other inhibitors or toxicity studies carried out in genetically engineered mice, while not
9 devoid of confounders, might further inform regarding the methanol MOA for developmental
10 toxicity.
11 Even if formaldehyde is ultimately identified as the proximate teratogen, methanol would
12 likely play a prominent role, at least in terms of transport to the target tissue. The high reactivity
13 of formaldehyde would limit its unbound and unaltered transport as free formaldehyde from
14 maternal to fetal blood (Thrasher and Kilburn, 2001). However, methanol can be metabolized to
15 formaldehye in situ by multiple organ systems (Jelski et al., 2006; Motavkin et al., 1988; Buhler
16 et al., 1983) and dose-dependent increases of formaldehyde DNA adducts derived from
17 exogenous methanol exposure have been observed in multiple tissues such as liver, lung, spleen,
18 thymus, bone marrow, kidney, and WBC (exogenous adduct levels were less than 10% of
19 endogenous adduct levels for most organ systems; embryonic tissue was not examined) of rats
20 (Luetal., 2012).
4.7.2. Role of Folate Deficiency in the Developmental Toxicity of Methanol
21 As discussed in Sections 3.1 and 4.1, humans and other primates are susceptible to the
22 effects of methanol exposure associated with formate accumulation because they have lower
23 levels of hepatic tetrahydrofolate-dependent enzymes that help in formate oxidation.
24 Tetrahydrofolate-dependent enzymes and critical pathways that depend on folate, such as purine
25 and pyrimidine synthesis, may also play a role in the developmental toxicity of methanol. Studies
26 of rats and mice fed folate-deficient diets have identified adverse effects on reproductive
27 performance, implantation, fetal growth and developmental defects, and the inhibition of folate
28 cellular transport has been associated with several developmental abnormalities, ranging from
29 neural tube defects to neurocristopathies such as cleft-lip and cleft-palate, cardiac septal defects,
30 and eye defects (Antony, 2007). Folate deficiency has been shown to exacerbate some aspects of
31 the developmental toxicity of methanol in mice (see discussion of (Fuet al., 1996), and
32 (Sakanashi et al., 1996), in Section 4.3.1) and rats (see discussion of (Aziz et al., 2002), in
33 Section 4.4.1).
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1 The studies in mice focused on the influence of FAD on the reproductive and skeletal
2 malformation effects of methanol. Sakanashi et al. (1996) showed that dams exposed to
3 5 g/kg-day methanol on GD6-GD15 experienced a threefold increase in the percentage of litters
4 affected by cleft palate and a 10-fold increase in the percentage of litters affected by exencephaly
5 when fed a FAD (resulting in a 50% decrease in liver folate) versus a FAS diet. They speculated
6 that the increased methanol effect from FAD diet could have been due to an increase in tissue
7 formate or a critical reduction in conceptus folate concentration immediately following the
8 methanol exposure. The latter appears more likely, given the high levels of formate needed to
9 cause embryotoxicity (Section 4.3.3) and the decrease in conceptus folate that is observed within
10 2 hours of GD8 methanol exposure (Dorman et al., 1995). Fu et al. (1996) confirmed the findings
11 of Sakanashi et al. (1996) and also determined that the maternal FAD diet had a much greater
12 impact on fetal liver folate than maternal liver folate levels.
13 The rat study of Aziz et al. (2002) focused on the influence of FAD on the developmental
14 neurotoxicity of methanol. Experiments by Aziz et al. (2002) involving Wistar rat dams and pups
15 exposed to methanol during lactation provide evidence that methanol exposure during this
16 postnatal period affects the developing brain. These effects (increased spontaneous locomotor
17 activity, decreased conditioned avoidance response, disturbances in dopaminergic and
18 cholinergic receptors and increased expression of GAP-43 in the hippocampal region) were more
19 pronounced in FAD as compared to FAS rats. This suggests that folic acid may play a role in
20 methanol-induced neurotoxicity. These results do not implicate any particular proximate
21 teratogen, as folate deficiency can increase levels of both methanol, formaldehyde and formate
22 (Medinsky et al., 1997). Further, folic acid is used in a number of critical pathways such as
23 purine and pyrimidine synthesis. Thus, alterations in available folic acid, particularly to the
24 conceptus, could have significant impacts on the developing fetus apart from the influence it is
25 presumed to have on formate removal.
26 Another problem with the hypothesized folate deficiency MOA is that an explanation for
27 this greater mouse sensitivity is not readily apparent. Mouse livers actually have considerably
28 higher hepatic tetrahydrofolate and total folate than rat or monkey liver (Johlin etal., 1987).
4.7.3. Methanol-induced Formation of Free Radicals, Lipid Peroxidation, and
Protein Modifications
29 Oxidative stress in mother and offspring has been suggested to be part of the teratogenic
30 mechanism of a related alcohol, ethanol. Certain reproductive and developmental effects (e.g.,
31 resorptions and malformation rates) observed in Sprague-Dawley rats following ethanol
32 exposure were reported to be ameliorated by antioxidant (Vitamin E) treatment (Wentzel et al..
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1 2006; Wentzel and Eriksson, 2006). A number of studies have examined markers of oxidative
2 stress associated with methanol exposure.
3 McCallum et al. (2011 a: 201 Ib) treated adult male CD-I mice, DNA repair deficient
4 oxoguanine glycosylase (Oggl) knockout mice, NZW rabbits and cynomolgus monkeys
5 (Macacafascicularis) with a single i.p. injection of 2 g/kg methanol and measured 8-hydroxy-2'-
6 deoxyguanosine (8-oxodG), as an indicator of tissue oxidative DNA damage, 6 hours post-
7 injection in the lung, liver, kidney, bone marrow and spleen. They also examined these organs for
8 8-oxodG in adult male CD-I mice injected daily for 15 days with 2 g/kg methanol. They reported
9 no evidence of methanol-dependent increases in 8-oxodG in any of the species and organ
10 systems tested.
11 Miller and Wells (2011) exposed mouse embryos expressing human catalase (hCat) or
12 their wild-type controls, and acatalasemic (aCat)-expressing mouse embryos or their wild-type
13 controls for 24 hours to 4 mg/mL methanol or vehicle on gestational day 9. They observed higher
14 methanol-induced teratogenicity in catalase deficient embryos, and interpreted this as an
15 indication that ROS is involved in the embryopathic mechanism of methanol. However,
16 contradictory results were obtained from subsequent in-vivo studies performed by the same
17 laboratory using the same mouse strains. Siu et al. (2013) treated pregnant hCat and aCat mice
18 and their wild-type (WT) controls with 4 g/kg of methanol (i.p.) or saline on GD 8. Although
19 catalase activities were confirmed to be substantially increased in the hCat maternal livers and
20 embryos, increases in fetal ophthalmic abnormalities and cleft palate, similar to those reported
21 for C57BL/6J mice by Rogers et al. (2004), were observed in methanol-exposed hCat mice and
22 their WT controls but not in methanol-exposed aCat mice or their WT controls. The authors
23 indicated that the relative resistance of aCat mice to the embryotoxic effects of methanol could
24 not be explained by differences in methanol metabolism because similar peak and AUC levels of
25 methanol and its formic acid metabolite were observed for male aCat and hCat mice and their
26 WT controls, but this would need to be verified with pharmacokinetic data for the female mice
27 and their affected embryos. Siu et al. (2013) suggest that the apparent discrepancy between their
28 in-vivo results and the Miller and Wells (2011) in-vitro results could be due to yet to be
29 determined maternal factors associated with metabolism and membrane transport and/or a
30 requirement for high catalase activity in the hCat mice, but acknowledge that it may also be an
31 indication that ROS does not play an important embryopathic role in vivo.
32 Skrzydlewska et al. (2005) provided inferential evidence for the effects of methanol on
33 free radical formation, lipid peroxidation, and protein modifications, by studying the protective
34 effects of N-acetyl cysteine and the Vitamin E derivative, U83836E, in the liver of male Wistar
35 rats exposed to the compound via gavage. Forty-two rats/group received a single oral gavage
36 dose of either saline or 50% methanol. This provided a dose of approximately 6,000 mg/kg, as
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1 calculated by the authors. Other groups of rats received the same concentration of methanol, but
2 were also injected intraperitoneally with either N-acetylcysteine or U-83836E. N-acetylcysteine
3 and U-83836E controls were also included in the study design. Animals in each group were
4 sacrificed after 6, 14, and 24 hours or after 2, 5, or 7 days. Livers were rapidly excised for
5 electron spin resonance (ESR) analysis, and 10,000 x g supernatants were used to measure GSH,
6 malondialdehyde, a range of protein parameters, including free amino and sulfhydryl groups,
7 protein carbonyls, tryptophan, tyrosine, and bityrosine, and the activity of cathepsin B. They
8 reported (1) an ESR signal (thought to be indicative of free radical formation) at g = 2.003 in
9 livers harvested 6 and 12 hours after methanol exposure, (2) a significant decrease in GSH levels
10 that was most evident in rats sacrificed 12 and 24 hours after exposure; (3) increased
11 concentrations in the lipid peroxidation product, malondialdehyde (by a maximum of 44% in the
12 livers of animals sacrificed 2 days after exposure); (4) increased specific concentrations of
13 protein carbonyl groups and bityrosine; but (5) reductions in the specific level of tryptophan.
14 Given the ability of N-acetylcysteine and U83836E to oppose these changes, at least in part, the
15 authors speculated that methanol-induced free radical formation and lipid peroxidation are
16 involved. However, it is unclear whether or not the metabolites of methanol, formaldehyde,
17 and/or formate, were involved in any of these changes.
18 Rajamani et al. (Rajamani et al., 2006) examined several oxidative stress parameters in
19 male Wistar rats following methotrexate-induced folate deficiency. Compared to controls, the
20 levels of free radical scavengers SOD, CAT, GSH peroxidase, oxidized GSH, protein carbonyls,
21 and lipid peroxidation were elevated in several regions of the brain, with greater increases
22 observed in the MTX-methanol-treated animals than in the MTX-alone group. The level of GSH
23 and protein thiols was decreased in all regions of the brain, with a greater decrease observed in
24 the MTX-methanol-treated animals than MTX-treated animals.
25 Dudka (2006) measured the total antioxidant status (TAS) in the brain of male Wistar rats
26 exposed to a single oral gavage dose of methanol at 3 g/kg. The animals were kept in a nitrous
27 oxide atmosphere (N2O/O2) throughout the experiment to reduce intrinsic folate levels, and
28 various levels of ethanol and/or fomepizole (as ADH antidotes) were administered i.p. after
29 4 hours. Animals were sacrificed after 16 hours, the brains homogenized, and the TAS
30 determined spectrophotometrically. As illustrated graphically by the author, methanol
31 administration reduced TAS in brain irrespective of the presence of ADH antidotes. The author
32 speculated that, while most of the methanol is metabolized in the liver, some may also reach the
33 brain. Metabolism to formate might then alter the NADH/NAD+ ratio resulting in an increase in
34 xanthine oxidase activity and the formation of the superoxide anion.
35 Parthasarathy et al. (2006b) investigated the extent of methanol-induced oxidative stress
36 in rat lymphoid organs. Six male Wistar rats/group received 2,370 mg/kg methanol (mixed 1:1
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1 with saline) injected i.p. for 1, 15 or 30 days. A control group received a daily i.p. injection of
2 saline for 30 days. At term, lymphoid organs such as the spleen, thymus, lymph nodes, and bone
3 marrow were excised, perfused with saline, then homogenized to obtain supernatants in which
4 such indices of lipid peroxidation as malondialdehyde, and the activities of CAT, SOD, and GSH
5 peroxidase were measured. Parthasarathy et al. (2006b) also measured the concentrations of GSH
6 and ascorbic acid (nonenzymatic antioxidants) and the serum concentrations of a number of
7 indicators of liver and kidney function, such as ALT, AST, blood urea nitrogen (BUN), and
8 creatinine.
9 Table 4-25 shows time-dependent changes in serum liver and kidney function indicators,
10 which resulted from methanol administration. Treatment with methanol for increasing durations
11 resulted in increased serum ALT and AST activities and the concentrations of BUN and
12 creatinine.
Table 4-25 Time-dependent effects of methanol administration on serum liver and kidney
function, serum ALT, AST, BUN, and creatinine in control and experimental
groups of male Wistar rats.
Methanol administration (2,370 mg/kg)
Parameters Control Single dose 15 days 30 days
ALT (umoles/min-mg) 29.0 ±2.5 31.4±3.3 53.1±2.3a 60.4±2.8a
AST (umoles/min-mg) 5.8 ±0.4 6.4 ±0.3 9.0±1.2a 13.7±1.2a
BUN(mg/L) 301 ±36 332 ±29 436±35a 513±32a
Creatinine (mg/L) 4.6 ±0.3 4.8 ±0.3 5.6±0.2a 7.0±0.4a
"p < 0.05 versus controls.
Values are means ± SD of 6 animals.
Source: Parthasarathy et al. (2006b) (adapted).
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Table 4-26 Effect of methanol administration on male Wistar rats on malondialdehyde
concentration in the lymphoid organs of experimental and control groups and
the effect of methanol on antioxidants in spleen.
Methanol administration (2,370 mg/kg)
Parameters
Malondialdehyde in lymphoid
Spleen
Thymus
Lymph nodes
Bone marrow
Control
organs
2.62 ±0.19
3.58 ±0.35
3. 15 ±0.25
3. 14 ±0.33
Single dose
4.14±0.25a
5.76±0.36a
5.08±0.24a
4.47±0.18a
15 days
7.22 ± 0.3 la
9.23±0.57a
8.77±0.57a
7.20 ± 0.42a
30 days
9.72±0.52a
11.6±0.33a
9.17±0.67a
9.75±0.56a
Antioxidant levels in spleen
SOD (units/mg protein)
CAT (umoles H2O2
consumed/min-mg protein
GPx (ug GSH
consumed/min-mg protein)
GSH (ug/mg protein)
Vitamin C (ug/mg protein)
2.40 ±0.16
35.8 ±2.77
11.2 ±0.60
2.11±0.11
0.45 ±0.04
4.06±0.19a
52.5±3.86a
20.0±1.0a
3.75±0.15a
0.73 ± 0.05a
1.76±0.09a
19.1±1.55a
7.07±0.83a
1.66±0.09a
0.34±0.18a
1.00±0.07a
10.8±1.10a
5.18±0.45a
0.89±0.04a
0.11±0.03a
"p < 0.05, versus controls.
Values are means ± SD of six animals.
Source: Parthasarathy et al. (2006b) (adapted).
1 Table 4-26 gives the concentration of malondialdehyde in the lymphoid organs of control
2 and experimental groups, and, as an example of all tissue sites examined, the levels of enzymatic
3 and nonenzymatic antioxidants in spleen. The results show that malondialdehyde concentrations
4 were time-dependently increased at each tissue site and that, in spleen as an example of all the
5 lymphoid tissues examined, increasing methanol administration resulted in lower levels of all
6 antioxidants examined compared to controls. Parthasarathy et al. (2006b) concluded that
7 exposure to methanol may cause oxidative stress by altering the oxidant/antioxidant balance in
8 lymphoid organs in the rat.
4.7.4. Exogenous Formate Dehydrogenase as a Means of Detoxifying the
Formic Acid that Results from Methanol Exposure
9 In companion reports, Muthuvel et al. (2006a; 2006b) used 6 male Wistar rats/group to
10 test the ability of exogenously-administered formate dehydrogenase (FD) to reduce the serum
11 levels of formate that were formed when 3 g/kg methanol was administered i.p. to rats in saline.
12 In the first experiment, purified FD (from Candida boitimf) was administered by i.v. conjugated
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1 to the N-hydroxysuccinimidyl ester of monomethoxy polyethylene glycol propionic acid
2 (PEG-FD) (Muthuvel et al., 2006b). In the second, rats were administered FD-loaded
3 erythrocytes (Muthuvel et al., 2006a). In the former case, some groups of rats were made folate
4 deficient by means of a folate-depleted diet; in the latter, folate deficiency was brought about by
5 i.p. administration of methotrexate. In some groups, the rats received an infusion of an equimolar
6 mixture of carbonate and bicarbonate (each at 0.33 mol/L) to correct the formate-induced
7 acidosis. As illustrated by the authors, methanol-exposed rats receiving a folate-deficient diet
8 showed significantly higher levels of serum formate than those receiving a folate-sufficient diet.
9 However, administration of native or PEG-FD reduced serum formate in methanol-receiving
10 folate-deficient rats to levels seen in animals receiving methanol and the folate-sufficient diet.
11 In the second report, Muthuvel et al. (2006a) carried out some preliminary experiments to
12 show that hematological parameters of normal, reconstituted but unloaded, and reconstituted and
13 FD-loaded erythrocytes, were similar. In addition, they showed that formate levels of serum were
14 reduced in vitro in the presence of FD-loaded erythrocytes. Expressing blood formate
15 concentration in mmol/L at the 1-hour time point after carbonate/bicarbonate and enzyme-loaded
16 erythrocyte infusion via the tail vein, the concentration was reduced from 10.63 ±1.3
17 (mean ± SD) in methanol and methotrexate-receiving controls to 5.83 ± 0.97 (n = 6). This
18 difference was statistically significant at the/? < 0.05 level. However, FD-loaded erythrocytes
19 were less efficient at removing formate in the absence of carbonate/bicarbonate. Effective
20 elimination of formate appears to require an optimum pH for the FD activity in the enzyme-
21 loaded erythrocytes.
4.7.5. Summary and Conclusions Regarding MOA for Developmental Toxicity
22 Data from experiments carried out by Dorman et al. (1995) indicate that formate is not
23 the probable proximate teratogen in pregnant CD-I mice exposed to high concentrations of
24 methanol vapor. This conclusion is based on the observation that there appeared to be little, if
25 any, accumulation of formate in the blood of methanol-exposed mice, and exencephaly did not
26 occur until formate levels were grossly elevated. In addition, treatment of pregnant mice with a
27 high oral dose of formate did not induce neural tube closure defects at media concentrations
28 comparable to those observed in uterine decidual swelling after maternal exposure to methanol.
29 Lastly, methanol- but not formate- induced neural tube closure defects in mouse embryos in vitro
30 at media concentrations comparable to the levels of methanol detected in blood after a
31 teratogenic exposure.
32 Harris and colleagues (Hansen et al., 2005; Harris et al., 2004; Harris et al., 2003) carried
33 out a series of physiological and biochemical experiments on mouse and rat embryos exposed to
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1 methanol, formaldehyde and formate, concluding that the etiologically important substance for
2 embryo dysmorphogenesis and embryolethality was likely to be formaldehyde rather than the
3 parent compound or formate. Specific activities for enzymes involved in methanol metabolism
4 were determined in rat and mouse embryos during the organogenesis period of 8-25 somites
5 (Harris et al., 2003). The experiment was based on the concept that differences in the metabolism
6 of methanol to formaldehyde and formic acid by the enzymes ADH1, ADH3, and CAT may
7 contribute to hypothesized differences in species sensitivity that were apparent in toxicological
8 studies. A key finding was that the activity of ADH3 (converting formaldehyde to formate) was
9 lower in mouse VYS than that of rats throughout organogenesis, consistent with the greater
10 sensitivity of the mouse to the developmental effects of methanol exposure. Another study
11 (Harris et al., 2004) which showed that the inhibition of GSH synthesis increases the
12 developmental toxicity of methanol also lends support to this hypothesis because ADH3-
13 mediated metabolism of formaldehyde is the only enzyme involved in methanol metabolism that
14 is GSH-dependent. These findings provide inferential evidence for the proposition that
15 formaldehyde may be the ultimate teratogen through diminished ADH3 activity. This concept is
16 further supported by the demonstration that the LOAELs for the embryotoxic effects of
17 formaldehyde in rat and mouse embryos were much lower than those for formate and methanol
18 (Hansen et al., 2005). The findings from both sets of experiments (Hansen et al., 2005; Harris et
19 al., 2004; Harris et al., 2003) suggest that the lower capacity of mouse embryos to transform
20 formaldehyde to formate (by ADH3) could explain the increased susceptibility of mouse versus
21 rat embryos to the toxic effects of methanol.
22 Recent studies suggest that mouse embryo tissue may have a high sensitivity to oxidative
23 damage relative to other species following methanol exposure (Miller and Wells, 2011; Sweeting
24 et al., 2011). Sweeting et al. (2011) postulated that one possible explanation for this sensitivity
25 may be a strong reliance of mice on catalase over ADH to metabolize embryonic methanol. A
26 low ADH activity in mouse embryo relative to rats [(Harris et al., 2003), Section 4.3.3],
27 combined with a preference of catalase to metabolize methanol over hydrogen peroxide
28 (Sweeting et al., 2011), could lead to a reduction in catalase activity and a higher level of ROS in
29 mouse versus rat embryos, partially explaining the higher sensitivity of mice to the embryotoxic
30 effects of methanol. If an appreciable portion of methanol's teratogenicity in sensitive mouse
31 strains can be explained by this mode of action, and if this mode of action is not applicable to
32 human fetuses, then sensitive mouse strains may not adequately reflect human risk. However, the
33 evidence for this mode of action remains limited. Further, as discussed in Section 3.3, there is
34 reason to believe that human infants can metabolize methanol via a mechanism other than ADH,
35 and that this alternative mechanism could involve catalase (Tran et al., 2007).
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1 While studies such as those by Harris et al. (2004; 2003) and Dorman and colleagues
2 (Dorman and Wei sch, 1996; Dorman et al., 1995) strongly suggest that formate is not the
3 metabolite responsible for methanol's teratogenic effects, there are still questions regarding the
4 relative involvement of parent methanol, formaldehyde and ROS. However, both the proposed
5 formaldehyde and ROS MO As require methanol to be present at the target site. Methanol can be
6 metabolized to formaldehye in situ by multiple organ systems and the high reactivity of
7 formaldehyde would limit its unbound and unaltered transport as free formaldehyde (see
8 discussion in Section 4.7.1), and the ROS MOA would require the presence of methanol to alter
9 embryonic catalase activity.
4.8. Evaluation of Carcinogenicity
10 Carcinogenicity will be addressed in a separate document.
4.9. Susceptible Populations and Life Stages
4.9.1. Possible Childhood Susceptibility
11 Studies in animals have identified the fetus as being more sensitive than adults to the
12 toxic effects of methanol; the greatest susceptibility occurs during gastrulation and early
13 organogenesis (NTP-CERHR, 2004). Table 4-23 summarizes some of the data regarding the
14 relative ontogeny of CAT, ADH1, and ADH3 in humans and mice. Human fetuses have limited
15 ability to metabolize methanol as ADH1 activity in 2-month-old and 4-5 month-old fetuses is
16 3-4% and 10% of adult activity, respectively (Pikkarainen and Raiha, 1967). ADH1 activity in
17 9-22 week old fetal livers was found to be 30% of adult activity (Smith et al., 1971). Likewise,
18 ADH1 activity is -20-50% of adult activity during infancy (Smith et al., 1971; Pikkarainen and
19 Raiha, 1967). Activity continues to increase until reaching adult levels at 5 years of age
20 (Pikkarainen and Raiha, 1967). However, no difference between blood methanol levels in 1-year-
21 old infants and adults was observed following ingesting the same doses of aspartame, which
22 releases 10% methanol by weight during metabolism (Stegink et al., 1983). Given that the
23 exposure was aspartame as opposed to methanol, it is difficult to draw any conclusions from this
24 study vis-a-vis ontogeny data and potential influences of age differences in aspartame
25 disposition. With regard to inhalation exposure, increased breathing rates relative to adults may
26 result in higher blood methanol levels in children compared to adults (NTP-CERHR, 2004). It is
27 also possible that metabolic variations resulting in increased methanol blood levels in pregnant
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1 women could increase the fetus' risk from exposure to methanol. In all, unresolved issues
2 regarding the identification of the toxic moiety increase the uncertainty with regards to the extent
3 and pathologic basis for early life susceptibility to methanol exposure.
4 The prevalence of folic acid deficiency has decreased since the United States and Canada
5 introduced a mandatory folic acid food fortification program in November 1998. However, folate
6 deficiency is still a concern among pregnant and lactating women, and factors such as smoking, a
7 poor quality diet, alcohol intake, and folic antagonist medications can enhance deficiency (NTP-
8 CERHR, 2004). Folate deficiency could affect a pregnant woman's ability to clear formate,
9 which has also been demonstrated to produce developmental toxicity in rodent in in vitro studies
10 at high-doses (Dorman et al., 1995). It is not known if folate-deficient humans have higher levels
11 of blood formate than individuals with adequate folate levels. A limited study in folate-deficient
12 monkeys demonstrated no formate accumulation following an endotracheal exposure of
13 anesthetized monkeys to 900 ppm methanol for 2 hours (Dorman et al., 1994). The situation is
14 obscured by noting that folic acid deficiency during pregnancy by itself is thought to contribute
15 to the development of severe congenital malformations (Pitkin, 2007).
4.9.2. Possible Gender Differences
16 There is limited information on potential differences in susceptibility to the toxic effects
17 of methanol according to gender. One study (n=12) reported a higher background blood
18 methanol level in human females versus males (Batterman and Franzblau, 1997), but a larger
19 study (n=35) did not observe gender differences (Sarkola and Eriksson, 2001). In rodents, fetuses
20 exposed in utero were found to be the most sensitive subpopulation. One study suggested a
21 possible increased sensitivity of male versus female rat fetuses and pups. When rats were
22 exposed to methanol pre- and postnatally, 6- and 8-week-old male progeny had significantly
23 lower brain weights at 1,000 ppm, compared to those in females that demonstrated the same
24 effect only at 2,000 ppm (NEDO, 1987). In general, there is little evidence for substantial
25 disparity in the level or degree of toxic response to methanol in male versus female experimental
26 animals or humans. However, it is possible that the compound-related deficits in fetal brain
27 weight that were evident in the pups of FI generation Sprague-Dawley rats exposed to methanol
28 in the NEDO (1987) study may reflect a threshold neurotoxicological response to methanol. It is
29 currently unknown whether higher levels of exposure would result in brain sequelae comparable
30 to those observed in acutely exposed humans.
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4.9.3. Genetic Susceptibility
1 Polymorphisms in enzymes involved in methanol metabolism may affect the sensitivity
2 of some individuals to methanol. For example, as discussed in Section 3, data summarized in
3 reviews by Agarwal (200IX Burnell et al. (19891 Bosron and Li (19861 and Pietruszko (1980)
4 discuss genetic polymorphisms for ADH. Class IADH, the primary ADH in human liver, is a
5 dimer composed of randomly associated polypeptide units encoded by three genetic loci
6 (ADH1 A, ADH1B, and ADH1C). Polymorphisms are observed at the ADH1B (ADH1B*2,
7 ADH1B*3) and ADH1C (ADH1C*2) loci. The ADH1B*2 phenotype is estimated to occur in
8 -15% of Caucasians of European descent, 85% of Asians, and less that 5% of African
9 Americans. ADH1C* 1 is also highly prevalent in Asians, but has only been examined in a few
10 studies of Chinese and Korean samples (Eng et al., 2007). Fifteen percent of African Americans
11 have the ADH1B*3 phenotype, while it is found in less than 5% of Caucasian Europeans and
12 Asians. The only reported polymorphisms in ADH3 occur in the promoter region, one of which
13 reduces the transcriptional activity in vitro nearly twofold (Hedberg et al., 2001). While
14 polymorphisms in ADH3 are described in more than one report (Cichoz-Lach et al., 2007;
15 Hedberg et al., 2001), the functional consequence(s) for these polymorphisms remains unclear.
16 Although racial and ethnical differences in the frequency of the occurrence of ADH
17 alleles in different populations have been reported, ADH enzyme kinetics (Vmax and Km) have not
18 been reported for methanol. There is an abundance of information pertaining to the kinetic
19 characteristics of the ADH dimers to metabolize ethanol in vitro. Methanol blood concentrations
20 of 2.62 ± 1.33 mg/L (Table 3-1) in 18 Korean males ( Woo et al., 2005) were considerably higher
21 than the sample U.S. background distribution estimated of 1.36 mg/L and 0.77 mg/L estimated in
22 Section 5.3.6. However, the functional and biological significance is not well understood due to
23 the lack of data documenting metabolism and disposition of methanol or ethanol in individuals of
24 known genotype. Thus, while potentially significant, the contribution of ethnic and genetic
25 polymorphisms of ADH to the interindividual variability in methanol disposition and metabolism
26 cannot be reliably quantified at this time.
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5.DOSE-RESPONSE ASSESSMENTS
5.1. Inhalation Reference Concentration (RfC)47
1 In general, the RfC is an estimate (with uncertainty spanning perhaps an order of
2 magnitude) of a continuous inhalation exposure to the human population (including sensitive
3 subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime.
4 It is derived from a POD, generally an estimated 95 percent lower confidence limit on the BMD
5 (i.e., BMDL), with uncertainty factors applied to reflect limitations of the data used. The
6 inhalation RfC considers toxic effects for both the respiratory system (portal-of-entry) and
7 systems peripheral to the respiratory system (extra-respiratory or systemic effects). It is generally
8 expressed in mg/m3.
9 This assessment uses BMD modeling to identify the POD.48 The suitability of these
10 methods to derive a POD is dependent on the nature of the toxicity database for a specific
11 chemical. Details of the BMD analyses are found in Appendix D. The use of the BMD approach
12 for identifying the POD is preferred over the NOAEL/LOAEL approach because the BMD
13 approach includes consideration of the shape of the dose-response curve, is less dependent on
14 experimental dose selection, and estimates uncertainty pertaining to the modeled dose response.
15 Other limitations and uncertainties associated with the methanol database that influence
16 derivation of the RfC, such as uncertainties associated with human variability, animal-to-human
17 differences, and limitations in the database, are addressed through the use of rat and human
18 PBPK models and uncertainty factors.
5.1.1. Choice of Principal Study and Critical Effect(s)
5.1.1.1. Key Inhalation Studies
19 While a substantial body of information exists on the toxicological effects in humans
20 exposed to high concentrations of methanol for short durations, none of these studies are suitable
21 for quantification of subchronic, chronic, or in utero effects of methanol exposure. Table 4-21 in
22 the previous section summarizes the available experimental animal inhalation studies of
47 The RfC discussion precedes the RfD discussion in this assessment because the inhalation database ultimately
serves as the basis for the RfD. The RfD development would be difficult to follow without prior discussion of the
inhalation database and PK models used for the route-to-route extrapolation.
48 Use of BMD modeling involves fitting mathematical models to dose-response data and using the results to
estimate a POD that is associated with a selected benchmark response (BMR), such as a percentage increase in the
incidence of a particular lesion or a percentage decrease in body weight gain (see Section 5.1.2.2).
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1 methanol. Several of these studies, including monkey chronic (NEDO, 1987) and developmental
2 (Burbacher et al., 2004a: 2004b: 1999a: 1999b) studies, male rat reproductive studies (Lee et al.,
3 1991; Cameron et al., 1985; Cameron et al., 1984), and 4-week rat studies (Poonetal., 1994), are
4 lacking in key attributes (e.g., existence of a dose response, documented controls, and adequate
5 duration of exposure) necessary for use in the derivation of a chronic RfC. As discussed in
6 Section 4.6, the most appropriate endpoints for use in the derivation of an inhalation RfC for
7 methanol are associated with developmental toxicity. From the studies listed in Table 4-21, the
8 reproductive/developmental studies that were adequately documented and of the appropriate size
9 and design for use in the derivation of an RfC were selected and are described in Table 5-1.
5.1.1.2. Selection of Critical Effect(s)
5.1.1.2.1. Developmental Skeletal Abnormalities
10 Skeletal defects following methanol exposure have been observed in developmental
11 studies of rats (Weiss etal., 1996: NEDO, 1987: Nelson etal., 1985) and mice (Rogers and Mole,
12 1997: Bolonetal., 1993: Rogers etal., 1993b). The findings of Bolon et al. (1993) and Rogers
13 and Mole (1997) indicate that methanol is toxic to mouse embryos in the early stages of
14 organogenesis, on or around GD7. In the study by Rogers et al. (1993b), in which pregnant
15 female CD-I mice were exposed to methanol vapors (at concentrations of 1,000, 2,000, and
16 5,000 ppm) on GD6-GD15, reproductive and fetal effects included an increase in the number of
17 resorbed litters, a reduction in the number of live pups, and increased incidences of exencephaly,
18 cleft palate, and extra cervical ribs. The authors identified a NOAEL of 1,000 ppm (1,310
19 mg/m3) and a LOAEL of 2,000 ppm (2,620 mg/m3) based on the increased incidence of extra
20 cervical ribs, with 49.6% per litter in the 2,000 ppm dose group versus 28.0% per litter in the
21 control group. An increased incidence of extra cervical ribs was also observed in the rat
22 organogenesis study by NEDO (1987), with the 5,000 ppm dose group exhibiting an incidence of
23 65.2% per litter versus 0% in the control group, indicating that this endpoint is consistent across
24 species.
25 The biological significance of the cervical rib endpoint has been the subject of much
26 debate (Chernoff and Rogers, 2004). Previous studies have classified this endpoint as either a
27 malformation (birth defect of major importance) or a variation (morphological alteration of
28 minor significance). Evidence exists that incidence of supernumerary ribs (including cervical
29 ribs) is not just the addition of extraneous, single ribs, but rather is related to a general alteration
30 in the development and architecture of the axial skeleton as a whole. For example, in CD-I mice
31 exposed during gestation to various types of stress, food and water deprivation, and the herbicide
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1 dinoseb, supernumerary ribs were consistently associated with increases in the length of the 13th
2 rib (Branch et al., 1996). This relationship was present in all fetal ages examined in the study.
3 The authors concluded that these findings are consistent with supernumerary ribs being one
4 manifestation of a basic alteration in the differentiation of the thoraco-lumbar border of the axial
5 skeleton. The biological significance of this endpoint is further strengthened by the association of
6 supernumerary ribs with adverse health effects in humans. The most common effect associated
7 with the presence of extra cervical ribs is thoracic outlet disease (Nguyen et al., 1997; Fernandez
8 Noda et al., 1996; Henderson, 1914). Thoracic outlet disease is characterized by numbness
9 and/or pain in the shoulder, arm, or hands. Vascular effects associated with this syndrome include
10 cerebral and distal embolism (Beam et al.. 1993: Connell et al.. 1980: Short. 1975). while
11 neurological symptoms include extreme pain, migraine, and symptoms similar to Parkinson's
12 disease (Evans, 1999: Saxton et al., 1999: Fernandez Noda et al., 1996). Furthermore,
13 Schumacher et al. (1992) observed 242 rib anomalies in 218 children with tumors (21.8%) and
14 11 (5.5%) in children without malignancy, a statistically significant (p < 0.001) difference that
15 suggests an association between the presence of extra cervical ribs and childhood cancers. In
16 conclusion, the mouse cervical rib endpoint is biologically significant and potentially relevant to
17 humans, and thus appropriate for use in the derivation of a human health toxicity value (RfC or
18 RfD).
5.1.1.2.2. Developmental Neurotoxicity
19 NEDO (1987) reported reduced brain, pituitary, and thymus weights in FI and F2
20 generation Sprague-Dawley rats exposed to 1,000 ppm methanol. In a follow-up study of the FI
21 generation brain weight effects, NEDO (1987) reported decreased brain, cerebellum, and
22 cerebrum weights in FI males exposed to 1,000 ppm methanol from GDO through the FI
23 generation.49 The methanol exposure levels used in these studies are difficult to interpret because
24 dams were exposed prior to gestation, as well as during gestation and lactation, while pups were
25 exposed during gestation (in utero) and lactation. However, the results from NEDO (1987)
26 clearly show that postnatal methanol exposure increases the magnitude of brain weight
27 reduction. In another experiment by NEDO (1987) referenced in the previous section, rats
28 exposed to methanol only during organogenesis (GD7-GD17) exhibited decreases in brain
29 weights in offspring at 8 weeks of age that were less severe than in rat pups in the studies in
30 which methanol exposure was continued postnatally. This finding is not unexpected, given that
31 the brain undergoes tremendous growth beginning early in gestation and continuing into the
49 For the interpretation of the dose-response data, EPA did not rely on the statistics reported by NEDO (1987)
which were based on inappropriate t-test methods but, instead, relied on the results of the benchmark dose analyses
described in Appendix D.
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1 postnatal period. Rats are considered altricial (i.e., born at a relatively underdeveloped stage),
2 and thus many of their neurogenic events occur postnatally (Clancy et al., 2007). Brain effects
3 from postnatal exposure are also relevant to humans given that, in humans, gross measures of
4 brain growth increase for at least 2-3 years after birth, with the growth rate peaking
5 approximately 4 months after birth (Rice and Barone, 2000).
6 Change in brain weight is considered to be a biologically significant effect (U.S. EPA,
7 1998a). This holds true regardless of whether changes in body weight occur simultaneously
8 because brain weight is generally conserved even during malnutrition or weight loss, unlike
9 many other organs or tissues (U.S. EPA, 1998a). Thus, change in absolute brain weight is an
10 appropriate measure of effects on this critical organ. Decreases in brain weight have been
11 associated with simultaneous deficits in neurobehavioral and cognitive parameters in animals
12 exposed during gestation to various solvents, including toluene and ethanol (Gibson et al., 2000;
13 Coleman et al.. 1999: Hassetal., 1995). NEDO (1987) reported that brain, cerebellum, and
14 cerebrum weights decreased in a dose-dependent manner in male rats exposed to methanol
15 throughout gestation and the FI generation. While brain weight reduction has been observed in
16 adult rats exposed to methanol (TRL, 1986), it has not been observed in other developmental
17 bioassays of methanol. This lack of consistency across developmental studies may be due to the
18 fact that brain weight is not an endpoint that has been extensively measured in other
19 developmental studies of methanol [e.g., Rogers et al. (1993b)1.
20 Developmental neurobehavioral effects associated with methanol inhalation exposure
21 have also been investigated in monkeys. Burbacher et al. (2004a; 2004b: 1999a: 1999b) exposed
22 M fascicularis monkeys to 0, 200, 600, or 1,800 ppm (0, 262, 786, and 2,359 mg/m3) methanol,
23 2.5 hours/day, 7 days/week during premating/mating and throughout gestation (approximately
24 168 days). There appeared to be neurotoxicological deficits in methanol-exposed offspring. VDR
25 was significantly reduced in the 600 ppm (786 mg/m3) methanol group for males and in the
26 1,800 ppm (2,359 mg/m3) methanol group for both sexes. However, a dose-response trend for
27 this endpoint was only exhibited for females. In fact, the VDR response in females is the only
28 effect reported in the Burbacher et al. (2004a; 2004b: 1999a: 1999b) studies for which a
29 significant dose-response trend is evident. As discussed in Section 4.4.2, confidence in these
30 results may have been increased by statistical analyses that adjusted for multiple comparisons
31 (NTP-CERHR, 2004). However, the dose-response trend for VDR in females remained
32 significant both with (p = 0.009) and without (p = 0.0265) an adjustment for the shortened
33 gestational periods. In addition, VDR is a measure of functional deficits in sensorimotor
34 development that is consistent with other early developmental CNS effects (i.e., brain weight
35 changes discussed above) that have been observed in rats exposed to methanol.
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1 Another test performed by Burbacher et al. (2004a; 2004b: 1999a: 1999bX the Pagan test
2 of infant intelligence, indicated small, but non-significant, deficits of performance (decreased
3 time spent looking at novel faces versus familiar faces) in treated monkeys. Although not
4 statistically significant nor quantifiable, the results of this test should be considered, in
5 conjunction with the VDR test results and brain weight changes noted in the NEDO (1987) rat
6 study, as a possible indication of CNS effects. As discussed in Section 4.6.1.2, the monkey data
7 are not conclusive, and there is insufficient evidence to determine if the primate fetus is more or
8 less sensitive than rodents to methanol-induced teratogenesis. Taken together, however, the
9 results of the NEDO (1987) rat study and the Burbacher et al. (2004a; 2004b: 1999a: 1999b)
10 monkey studies suggest that prenatal exposure to methanol can result in adverse effects on
11 developmental neurology and function, which can be exacerbated by continued postnatal
12 exposure to methanol.
5.1.1.2.3. Reproductive Effects
13 In the Burbacher et al. (2004a; 2004b: 1999a: 1999b) studies, exposure of monkeys to
14 methanol levels ranging from 200 ppm (263 mg/m3) to 1,800 ppm (2,359 mg/m3) during
15 premating, mating, and throughout gestation resulted in no changes in reproductive parameters
16 other than a shorter period of gestation in all exposure groups that did not appear to be dose
17 related. As discussed in Section 4.6.1.2, although statistically significant relative to controls, the
18 biological significance of this shortened gestation finding is uncertain given the absence of a
19 dose-response relationship. Other developmental parameters, such as fetal crown-rump length
20 and head circumference, were unaffected by methanol exposure.
21 A number of studies described in Section 4.3.2 and summarized in Section 4.6.1.2 have
22 examined the potential toxicity of methanol to the male reproductive system (Lee et al., 1991;
23 Cameron et al., 1985; Cameron et al., 1984). Some of the observed effects, including a transient
24 decrease in testosterone levels, could be the result of chemically related strain on the rat
25 hormonal system. However, the data are insufficient to definitively characterize methanol as a
26 toxicant to the male reproductive system.
5.1.1.2.4. Selected Critical Effects
27 The studies considered for use in the derivation of an RfC for methanol are summarized
28 in Table 5-1. As discussed in Sections 5.1.3.1 and 5.3.1, there is uncertainty associated with the
29 selection of a critical effect from the methanol database for use in the derivation of an RfC.
30 Although monkeys may represent the more relevant species, the available monkey studies are not
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1 adequate for dose-response analysis. Taking into account the advantages and limitations of the
2 studies available for quantification purposes and the relative sensitivities for the effects observed,
3 two developmental effects were chosen as candidate critical effects for the purpose of dose-
4 response assessment, cervical rib anomalies in fetal CD-I mice (Rogers et al., 1993b) and
5 decreased brain weight in male Sprague-Dawley rats exposed throughout gestation and lactation
6 (NEDO, 1987). These endpoints can be reliably quantified and represent adverse effects in two
7 separate sensitive organ systems at key periods of development. RfC derivations based on these
8 two endpoints using different dose-response options are described in Appendix D and
9 summarized below.
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Table 5-1 Summary of studies considered most appropriate for use in derivation of an
RfC.
Reference Species (strain)
NEDO (1987) Rat
Teratology Sprague-Dawley
study
NEDO (1987) Rat
Two- Sprague-Dawley
generation
study
NEDO (19871
Follow-up
study, FI
generation
Rogers et al. Mouse
(1993b) CD-I
Burbacher et Monkey
al. (2004a; M. fascicularis
2004b;
1999a;
1999fr)
Number/
dose group
10-12/sex/ group
Not specified -
F! and F2
generation
10-147 sex/
group- F!
generation
30- 114 pregnant
dams/
group
12 pregnant
monkeys/group
Exposure
Duration
GD7-GD17
F! -Birth to end
of mating (M)
or weaning (F);
F2-birth to 8 wk
GDO through Fj
generation
GD6-GD15
2.5 hr/day,
7 days/wk,
during
premating,
mating and
gestation
NOAEL
Critical Effect (ppm)
Prenatal: increase in late- 1,000
term resorptions,
decrease in live fetuses,
reduced fetal weight, and
increased frequency of
litters with fetal
malformations,
variations, and delayed
ossifications
Postnatal: Reduced
brain, pituitary, thyroid,
thymus, and testis
weights at 8 wk
Reduced weight of brain, 100
pituitary, and thymus at
8, 16, and 24 wk
postnatal in F! and at 8
wk in F2
Reduced brain weight at 500
3 wk and 6 wk (males
only). Reduced brain and
cerebrum weight at 8 wk
(males only)
Increased incidence of 1,000
extra cervical ribs, cleft
palate, exencephaly;
reduced fetal weight and
pup survival, delayed
ossification
Shortened period of -
gestation; may be related
to exposure (no dose
response),
neurotoxicological.
deficits including
reduced performance in
the VDR test
LOAEL
(ppm)
5,000
1,000
1,000
2,000
a
aGestational exposure resulted in a shorter period of gestation in dams exposed to as low as 200 ppm (263 mg/m ). However,
because of uncertainties associated with these results, including the lack of a clear dose-response, EPA was not able to identify a
definitive NOAEL or LOAEL from this study.
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5.1.2. Methods of Analysis for Identifying the POD—Application of PBPK and
BMD Models
1 Potential PODs for use in deriving the RfC, as described in Appendix D, have been
2 identified via the use of PBPK models, summarized in Section 3.4 and further described in
3 Appendix B. The administered doses used in the experimental animal studies were converted to
4 an internal dose metric that was deemed most appropriate for the endpoint being considered. The
5 PBPK models are capable of estimating several internal dose metrics for methanol, including the
6 following:
7 • Cmax - The peak concentration of methanol in the blood during the exposure period;
8 • AUC - Area under the curve, which represents the cumulative product of
9 concentration and time for methanol in the blood; and
10 • Total metabolism - The production of metabolites of methanol, namely formaldehyde
11 and formate.
12 Because uncertainty exists surrounding identification of the proximate teratogen of
13 importance (methanol, formaldehyde, formate or ROS), the dose metric chosen for derivation of
14 an RfC was based on blood methanol levels, either Cmax or AUC, rather than total metabolism.
15 As discussed in Section 4.7, this decision was primarily based on a determination that (1) the
16 toxic moiety for developmental effects from methanol exposure is not likely to be the formate
17 metabolite and (2) methanol is an adequate dose metric, even if formaldehyde or ROS are
18 determined to have a significant role in the teratogenicity of methanol. The former determination
19 has been endorsed by other organizations (NTP-CERHR, 2004) and is supported by evidence
20 that formate blood levels do not correlate well with the developmental toxicity observed
21 following methanol exposure. The latter determination is based on evidence that (1) methanol
22 can be metabolized to formaldehye in situ by multiple organ systems, (2) the high reactivity of
23 formaldehyde would limit its unbound and unaltered transport as free formaldehyde and (3) the
24 hypothesized ROS MO A would require the presence of methanol to alter embryonic catalase
25 activity (see further discussion in Sections 4.7.1, 4.7.3 and 4.7.5).
26 Employing BMD modeling, a BMDL was then estimated using the selected internal dose
27 metric. Finally, after application of UFs (see Section 5.1.3.2) to this BMDL, the adjusted BMDL
28 was converted to a HEC via the use of a PBPK model parameterized for humans. The next
29 section describes the BMD modeling approach that was used to estimate the BMDL.
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5.1.2.1. Application of the BMD/BMDL Approach
1 Several developments over the past few years impact the derivation of the RfC: (1) EPA
2 has developed BMD assessment methods (U.S. EPA, 2012, 1995) and supporting software (U.S.
3 EPA, 2011) to improve upon the previous NOAEL/LOAEL approach; (2) MOA studies have
4 been carried out that can give more insight into methanol toxicity; and (3) EPA has refined PBPK
5 models for methanol on the basis of the work of Ward et al. (1997) (see Appendix B for a
6 description of the EPA models). The EPA PBPK models provide estimates of HECs from test
7 animal exposures that are supported by pharmacokinetic information available for rodents,
8 monkeys and humans. The following sections describe how the BMD/BMDL approach, along
9 with the EPA PBPK models, are used to obtain PODs for use in the derivation of an RfC and
10 RfD for methanol consistent with current BMD technical guidance (U.S. EPA, 2012).
11 The BMD approach attempts to fit models to the dose-response data for a given endpoint.
12 It has the advantage over the NOAEL/LOAEL approach of taking more of the dose-response
13 data into account when determining the POD, as well as estimating the dose at which an effect
14 may have a specific probability of occurring. The BMD approach also accounts, in part, for the
15 quality of the study by estimating a BMDL, the 95% lower confidence limit on the BMD. Larger
16 studies (i.e., those with more test subjects) and studies with a low background response (i.e., with
17 more test subjects for which a relationship between dose and response can be evaluated)
18 generally yield narrower confidence intervals (BMDL estimates closer to their corresponding
19 BMD estimates) than smaller studies and studies with a high background response. For this
20 reason and because the BMDL approach will take into account, in part, a study's power, dose
21 spacing, and the steepness of the dose-response curve, it is generally preferred over the
22 NOAEL/LOAEL approach.
23 Even though the BMD approach is preferred over the NOAEL/LOAEL approach,
24 uncertainties are still associated with its use. As indicated above, the BMD approach fits several
25 models to the dose-response data to determine which model exhibits the best fit.50 In the absence
26 of an established MOA or a biological basis for why one model should be preferred, model
27 selection is based on which exhibits the best fit to the experimental data. Model fit is evaluated
50USEPA's BMDS 2.2 (U.S. EPA. 2011) was used for this assessment as it provides data management tools for
running multiple models on the same dose-response data set. At this time, BMDS offers over 30 different models
that are appropriate for the analysis of dichotomous, continuous, nested dichotomous and time-dependent response
data. Results from all models include a reiteration of the model formula and model run options chosen by the user,
goodness-of-fit information, the BMD, and an estimate of the 95 percent lower-bound on the BMD (i.e., the
BMDL).
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1 through use of goodness-of-fit diagnostics (i.e., overall %2, AIC, and ^ residuals for individual
2 dose groups), as well as visual inspection, consistent with EPA guidance (U.S. EPA, 2012).51
3 When performing a BMD analysis, it is important to choose a reliably measured or
4 estimated dose metric that has a close relationship to the health effect under consideration. For
5 the BMD analysis of the mouse cervical rib endpoint, peak (Cmax) internal methanol blood
6 concentrations were used as the dose metric [from the dams in each dose group at GD6, reported
7 by Rogers et al.(1993b)]. For the BMD analysis of the rat brain weight endpoint following
8 gestational exposure only (GD7-GD17), PBPK model estimates of Cmax methanol in blood for
9 the dams in each dose group were used as the dose metric. Cmax of methanol in blood (in mg/L)
10 was chosen as the appropriate internal dose metric for these two gestational exposure studies
11 because the magnitude of exposure is believed to be more important for these effects under these
12 study conditions than the duration of exposure, particularly for the cervical rib endpoint, which
13 has been shown to have a short gestational window of susceptibility (Rogers and Mole, 1997;
14 Bolonetal.. 1993)
15 For the BMD analysis of the rat brain weight endpoint following both gestational and
16 lactational exposure, PBPK model estimates of AUC methanol in blood for the dams in each
17 dose group were used as the dose metric. The results of NEDO (1987), described in Section 4.4.2
18 and shown in Table 4-13, indicate that there is no obvious cumulative effect from ongoing
19 methanol exposure on brain-weight decrements in rats exposed postnatally. That is, the dose
20 response in terms of percent of control is about the same at 3 weeks postnatal as at 8 weeks
21 postnatal in rats exposed throughout gestation and the FI generation. However, there does appear
22 to be a greater brain-weight effect in rats exposed postnatally versus rats exposed only during
23 organogenesis (GD7-GD17), suggesting a cumulative effect of methanol exposure. Specifically,
24 in male rats exposed during organogenesis only, there is no statistically significant decrease in
25 brain weight at 8 weeks after birth at the 1,000 ppm exposure level. Conversely, in male rats
26 exposed to the same concentration of methanol throughout gestation and the FI generation, there
27 was an approximately 5% decrease in brain weights (statistically significant at the/? < 0.01
28 level). Also, male rats exposed to 5,000 ppm methanol only during organogenesis experienced a
29 smaller decrease in brain weight at 8 weeks postnatal than male rats exposed to 2,000 ppm
30 methanol throughout gestation and the 8 week postnatal period (10% versus 13%). Further, brain
31 weight reductions have been observed in adult rats that were exposed to methanol for 90 days
32 with exposure beginning no earlier than 30 days of age (TRL, 1986). These results demonstrate
33 that brain weight is susceptible to both the magnitude and duration of exposure, and thus suggest
51Akaike's Information Criterion (AIC) (Akaike. 1973) is used for model selection and is defined as -2L + 2P where
L is the log-likelihood at the maximum likelihood estimates for the parameters and P is the number of model degrees
of freedom.
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1 that a dose metric that incorporates a time component would be most appropriate. For these
2 reasons, and because AUC is more typically used in internal-dose-based assessments as well as
3 better reflecting total exposure within a given day, daily AUC (measured for 22 hours
4 exposure/day) was chosen as the most appropriate dose metric for modeling the effects of
5 methanol exposure on brain weights in rats exposed throughout gestation and continuing into the
6 FI generation.
5.1.2.2. BMD Approach Applied to Brain Weight Data in Rats
7 The NEDO (1987) teratology study reported decreases in brain weights in fetal rats and
8 rat pups exposed during gestation only (GD7-GD17) and the developmental study performed as
9 a follow-up to the NEDO (1987) two generation rat study reported decreases in brain weights in
10 rat pups exposed during gestation and up to 8 weeks postnatally (see Section 4.4.2). Because of
11 the biological significance of decreases in absolute brain weight in the developing rat and
12 because this endpoint was not evaluated in other peer-reviewed studies, BMD analysis was
13 performed using dose-response data from both of these studies (see Appendix D for details).
14 Decreased brain weights observed in male rats at 8 weeks of age after gestation-only exposure
15 were not used for RfC derivation because the decreases seen were lower in magnitude at the
16 same dose level (1,000 ppm) compared to the decreases observed in rats exposed during both
17 gestation and postnatally. For the purpose of deriving an RfC for methanol, decreases in rat brain
18 weight at 6 weeks of age in the more sensitive gender, males, exposed throughout gestation and
19 continuing into the FI generation (both through lactation and inhalation routes) were used.
20 Decreases in brain weight observed at 6 weeks, rather than those seen at 3 and 8 weeks, were
21 chosen as the basis for the RfC derivation because they resulted in lower estimated BMDs and
22 BMDLs.
23 The first step in the BMD analysis is to convert the administered inhalation doses, given
24 as concentrations in air in ppm, to an internal dose metric using the EPA PBPK model (see
25 Appendix B for a detailed description of the PBPK models developed for methanol). Application
26 of the EPA methanol PBPK model is complicated by the exposure regimen used in the NEDO
27 (1987) developmental studies. The neonatal rats in the developmental study performed as a
28 supplement to the NEDO (1987) two-generation rat study were exposed to methanol in utero
29 before parturition (as well as via lactation and inhalation after parturition). Because data on
30 lactational transfer and early postnatal inhalation exposures to methanol are limited, the PBPK
31 model developed by EPA only estimates internal dose metrics for methanol exposure in non-
32 pregnant adult rats. Experimental data indicate that blood methanol kinetics following inhalation
33 exposures to non-pregnant (NP) mice and pregnant mice on GD6-GD10 are similar (Dorman et
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1 al.. 1995: Perkins et al.. 1995b: Rogers etal.. 1993a: Rogers etal.. 1993b). In addition,
2 experimental data indicate that the maternal blood:fetal partition coefficient for mice and rats is
3 approximately 1 up to GD 20 (see Sections 3.2 and 3.4.1.2). Assuming that these findings also
4 apply for rats later in pregnancy, the data indicate that PBPK estimates of PK and blood dose
5 metrics for NP rats are better predictors of fetal exposure during gestation than would be
6 obtained from default extrapolations from external exposure concentrations. However, as is
7 discussed in Section 5.1.3.2.2, the additional routes of exposure to the pups in this study (via
8 both lactation and inhalation) present uncertainties in that the average blood levels in pups are
9 likely to be greater than those of their dams. The assumption made in this assessment is that, if
10 such differences exist between human mothers and their offspring, they are not significantly
11 greater than that which has been postulated for rats. Assuming this is true, the PBPK model -
12 estimated adult blood methanol level is considered to be an appropriate dose metric for the
13 purpose of this analysis and the estimation of a human equivalent concentration (HEC).
14 The predicted AUC blood methanol values (adjusted for background) for rat dams
15 exposed to methanol in air at 0, 500, 1,000, or 2,000 ppm are presented in the second column of
16 Table 5-2. These AUC values are then used as the internal dose metric for the BMD analysis of
17 the response data (i.e., mean male brain weight of pups at 6 weeks of age) shown in the third
18 column of Table 5-2.52 The full details of this BMD analysis are provided in Appendix D.
19 Further details concerning the PBPK modeling are presented in Section 3.4 and Appendix B.
52A11 BMD assessments in this review were performed using BMDS version 2.2 (U.S. EPA. 2011).
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Table 5-2 The EPA PBPK model estimates of methanol blood levels (AUC) adjusted for
background (control) levels in rat dams following methanol inhalation
exposures and reported mean brain weights of 6-week-old male pups.
Exposure level
(ppm)
0
500
1,000
2,000
Blood methanol AUCa - control AUCa
(mg-hr/L)a in rat dams
0
547
2,310
17,500
Mean male rat (Fi generation)
brain weight at 6 weeksb
1.78 ±0.07
1.74 ±0.09
1.69±0.06C
1.52±0.07d
N
12
12
11
14
aAUCs were obtained by simulating 22 hr/day exposures for 5 days and calculated for the last 24 hours of that period; AUCs
above background were obtained by subtracting the estimated AUC for controls of 72 mg-hr/L.
bExposed throughout gestation and FI generation. Values are means ± SD
°p<0.01
dp < 0.001, as calculated by the authors.
Source: NEDO (1987).
1 The EPA's BMD technical guidance (U.S. EPA, 2012) suggests that, in the absence of
2 knowledge as to what level of response to consider adverse, a change in the mean equal to one
3 standard deviation (SD) from the control mean can be used as a benchmark response (BMR) for
4 continuous endpoints. However, it has been suggested that other BMRs, such as 5% change
5 relative to the estimated control mean, also be considered when performing BMD analyses on
6 developmental endpoints, such as fetal weight change (Kavlock et al., 1995). Therefore, both a
7 one SD change from the control mean and a 5% change relative to the estimated control mean
8 were considered as BMRs in the current analysis (see Appendix D for RfC derivations using
9 alternative BMRs).
10 As described in Appendix D and consistent with the EPA's BMD Technical Guidance
11 (U.S. EPA, 2012), the BMDL from the Hill model was selected as the most appropriate POD
12 from which to derive an RfC derivation because this model yields the lowest BMDL from among
13 a broad range of BMDLs and also provides a superior fit in the low dose region of the dose-
14 response nearest the BMD. The fit of the Hill model to the dose-response data for mean brain
15 weight in male rats is presented in Figure 5-1, with the response plotted against the chosen
16 internal dose metric of methanol AUC in blood of rats, adjusted for background. The BMDLiso
17 was estimated to be 858 mg-hr/L and the BMDLos was estimated to be 1,183 mg-hr/L.
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Hill Model with 0.95 Confidence Level
cc.
c
CD
1.85
1.8
1.75
1.7
1.65
1.6
1.55
1.5
1.45
Hill
\
BMDL
BMD
10:25 10/052011
0 2000 4000 6000 8000 10000 12000 14000 16000 18000
dose
Figure 5-1 Fit of the Hill model to decreased mean brain weight in male rats at 6 weeks
age using estimated AUC of methanol in blood (adjusted for background) as
the dose metric. The BMD is estimated based on a BMR of one SD change from
the control mean.
5.1.2.3. BMD Approach Applied to Cervical Rib Data in Mice
1 For the purpose of deriving an RfC for methanol based on a developmental endpoint in
2 mice, extra cervical rib incidence data were evaluated from Rogers et al. (1993b). Although the
3 teratology portion of the NEDO study (1987) also reported fetal malformations, including
4 increases in extra cervical rib incidence, in Sprague-Dawley rats, the Rogers et al. (1993b) study
5 was chosen for dose-response modeling because these effects were seen at lower doses, the study
6 was peer-reviewed and published in the open literature, and data on individual animals were
7 available, yielding a more statistically robust analysis utilizing nested models in BMDS 2.2 (U.S.
8 EPA. 2011).
9 For cervical rib anomalies, Cmax of methanol in blood (in mg/L) was chosen as the
10 appropriate internal dose metric because studies that have identified a small gestational window
11 of susceptibility (Rogers and Mole, 1997; Bolonetal., 1993) suggest that the magnitude of
12 exposure is more important than the duration of exposure. Because the critical window for
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1 methanol induction of cervical rib malformations in CD-I mice is thought to be between GD6
2 and GD7 (Rogers and Mole, 1997; Rogers et al., 1993a), the measured Cmax plasma methanol
3 levels at GD6 from the Rogers et al. (1993b) study are used after adjusting for background (i.e.,
4 1.6 mg/L).53 Cmax values for methanol in the blood of mice at GD6 from Rogers et al. (1993a) are
5 summarized in Table 5-3. These Cmax values are then used as the internal dose metric for the
6 BMD analysis of the litter-specific incidence of extra cervical ribs. The average incidence of
7 extra cervical ribs/litter (expressed as %) reported by Rogers et al. (1993b) is shown in Table 5-3,
8 but litter-specific response data from this study of 170 litters obtained from John Rogers (via
9 personal communication) was used for the nested BMD analysis described in Appendix D. Due
10 to high mortality, the high-dose (15,000 ppm) group consisting of 5 litters was excluded from the
11 analysis. The individual animal response data for the four dose groups shown in Table 5-3 are
12 displayed in the Appendix D BMD model output file.
Table 5-3 Maximum methanol blood levels (Cmax) adjusted for background, in mice
following inhalation exposures to methanol along with the corresponding
incidence of extra cervical ribs observed.
Exposure (ppm)
0
1,000
2,000
5,000
aCmax was adjusted for baclq
Blood methanol Cmax - control Cmax
(mg/L)a in mouse dams
0
61.4
485
2,120
'round by subtracting the Cmax
for controls reported by
Mean Incidence of Extra
Cervical Ribs/Litter (%)
28
33.6
49.6
74.4
Rogers et al. (1993b) of 1.6 mg/L.
Source: Rogers et al. (1993b)
13 Both 10% and 5% extra risk BMRs were considered for this endpoint. A 10% extra risk
14 BMR is adequate for most traditional bioassays using 50 animals per dose group. A smaller BMR
15 of 5% extra risk is sometimes justified for developmental studies such as Rogers et al. (Rogers et
16 al., 1993b) depending on the size of the study and the severity of the effects observed. As
17 described in Appendix D, the best model fit to these data (from visual inspection and comparison
18 of AIC values) was obtained using the NLogistic model. The fit of the NLogistic model to the
19 dose-response data for increased incidence of extra cervical ribs in fetal mice is presented in
53 Given that methanol inhalation dosimetry appears to be not significantly affected by the stage of pregnancy, data
from the later gestation days could be viewed simply as additional measurements in female GDI mice. Therefore the
BMD modeling results of using weighted concentration averages for all three gestation days measured were
compared with EPA's primary approach (using only the GD6 data). The results are not substantially different, and
the model fits were not as good as the model fits to the data using the GD6 blood levels. Thus, EPA has decided that
the use of the GD6 data as the dose metric is appropriate for this analysis.
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1 Figure 5-2. From this model, the BMDLos was estimated to be 43.10 mg/L and the BMDLio was
2 estimated to be 90.9 mg/L, expressed in terms of the Cmax above background for methanol in
3 blood.
Nested Logistic Model with 0.95 Confidence Level
0.8
0.7
0.6
0.5
0.4
0.3
0.2
10:56 12/16 2011
2000
Source: Rogers et al. (1993b).
Figure 5-2 Fit of the nested logistic (NLogistic) model- to the incidence of extra cervical
rib in fetal mice versus Cmax adjusted for background of methanol in blood
from a GD6-GD15 inhalation study in mice. The BMD is estimated based on a
BMR of 0.05 extra risk.
5.1.3. RfC Derivation - Including Application of Uncertainty Factors
5.1.3.1. Derivation of Candidate RfCs
4 Four potential PODs based on two developmental endpoints , cervical rib abnormalities
5 in mice and decreased brain weight in rats, each with two possible BMRs were considered for
6 the derivation of an RfC for methanol (see Appendix D for BMD modeling details). These
7 PODs, along with applied UFs (see Section 5.1.3.2 for details) and the estimated candidate RfCs
8 (obtained from PBPK models described in Appendix B) are presented in Table 5-4. This
9 information is presented so that comparisons can be made across the different endpoints (i.e.,
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1 cervical rib abnormalities and decreased brain weight) and BMRs employed. Each approach for
2 RfC derivation has its strengths and limitations, but when considered together, this comparison
3 allows for a more informed determination of the RfC for methanol.
Table 5-4 Summary of PODs for critical endpoints, application of UFs and conversion to
candidate RfCs using PBPK modeling.
BMDL = PODmtemal
RfCmtemai = PODmtemal/UFsa
JRfC (mg/m3)b
Rogers et al. Q993b)
mouse cervical rib Cmax
10% BMR 5% BMR
90.9mg/L 43.1mg/L
0.909 mg/L 0.43 mg/L
41.8 20.0
NEDO (1987)
rat brain weight AUC
5% BMR 1 SD BMR
1 , 1 83 mg-hr/L 858 mg-hr/L
11.85 mg-hr/L 8.58 mg-hr/L
24.5 17.8
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
aLTFA =3; UFD = 3; UFH = 10;LTFS = 1;UFL = 1; product of all UFs = 100; see Sections. 1.3.2 belowfor details.
bEach candidate RfC is the inhalation exposure concentration predicted to yield a blood concentration equal to its corresponding
RfCinternal, using the human PBPK model with an background blood concentration of 2.5 mg/L, which corresponds to the
estimated maximum background exposure rate for a diet including fruits and vegetables of 1600 mg/day (COT, 2011) in a 70-kg
person (see discussion in Section 5.3.6); the final RfC is rounded to one significant figure.
As described in Section 5.1.3.2 and shown in Table 5-4, the internal BMDL (PODinternai)
values were divided by a total UF of 100 (UFH of 10, UFA of 3 and a UFD of 3) to yield an
RfCmtemai, which was converted to a candidate RfC using the human PBPK model described in
Appendix B.54 Candidate RfCs estimated from the Rogers et al. (1993b) study based on extra
cervical rib incidence in mice employing Cmax as the dose metric were 41.8 and 20.0 mg/m3 using
BMRs of 10% and 5%, respectively. Candidate RfCs estimated from the NEDO (1987) study
based on decreases in brain weight at 6 weeks of age in male rats exposed during gestation and
throughout the FI generation employing AUC as the dose metric were 24.5 and 17.8 mg/m3 using
BMRs of 5% change relative to control mean and one SD from the control mean, respectively.
Because a one SD decrease in brain weight in male rats at 6 weeks (postnatal) resulted in the
lowest of the candidate RfC estimates and, therefore, the most likely to be protective against
other effects of methanol exposure, it was chosen as the critical endpoint for use in the RfC
derivation.
2X101 mg/m3
RfC = 858 mg-hr/L - 100 = 8.58 mg-hr/L
(rounded to 1 significant figure)
54 An algebraic equation provided near the end of Appendix B approximates the PBPK model predicted relationship
between methanol AUC and Cmax blood levels above background and the HEC in ppm.
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5.1.3.2. Application of UFs
1 UFs are applied to PODs to account for recognized uncertainties in extrapolation from
2 experimental conditions to the assumed human scenario (i.e., chronic exposure over a lifetime).
3 According to EPA guidance (U.S. EPA, 2002, 1994b), UFs used in deriving reference values are
4 generally applied to FEC or FED estimates. However, as described in Appendix B (Section
5 B.2.7, Table B-6), the human PBPK model developed for methanol is considered uncertain above
6 inhalation concentrations of 500 ppm (655 mg/m3) or oral ingestions of 50 mg/kg-day, since the
7 blood levels predicted rise above those for which there are model calibration data. The FEC
8 values (1,042 to 1,604 mg/m3) and FED values (133 to 220 mg/kg-day) predicted by the human
9 PBPK model for BMDLs from the candidate principal studies are well above these exposure
10 levels. Consequently, the standard EPA practice of applying a human PBPK model to derive
11 FEC or FED values prior to dividing by UFs (U.S. EPA. 2002. 1994b) would add considerable
12 model uncertainty. In order to avoid the uncertainty associated with applying the model to
13 exposure levels that are above the levels for which the model was calibrated and to account for
14 possible non-linearities in the external versus internal dose relationships at high doses, EPA has
15 applied the UFs to the internal BMDL (PODinternai) prior to FEC (and FED) derivation to obtain
16 an RfCintemai (and RfDintemai). This approach results in more scientifically reliable model
17 predictions by lowering the BMDLs to within the more linear, calibrated range of the human
18 PBPK model.
5.1.3.2.1. Interindividual variation UFH
19 A factor of 10 was applied to account for variation in sensitivity within the human
20 population (UFH). The UFH of 10 is commonly considered to be appropriate in the absence of
21 convincing data to the contrary. The data from which to determine the potential extent of
22 variation in how humans respond to chronic exposure to methanol are limited, given the complex
23 nature of the developmental endpoint employed and uncertainties surrounding the importance of
24 metabolism to the observed teratogenic effects. Susceptibility to methanol is likely to involve
25 intrinsic and extrinsic factors. Some factors may include alteration of the body burden of
26 methanol or its metabolites, sensitization of an individual to methanol effects, or augmentation of
27 underlying conditions or changes in processes that share common features with methanol effects.
28 Additionally, inherent differences in an individual's genetic make-up, diet, gender, age, or
29 disease state may affect the pharmacokinetics and pharmacodynamics of methanol, influencing
30 susceptibility intrinsically (see Sections 3.3 and 4.9). Co-exposure to a pollutant that alters
31 metabolism or other clearance processes, or that adds to background levels of metabolites may
32 also affect the pharmacokinetics and pharmacodynamics of methanol, influencing susceptibility
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1 extrinsically. The determination of the UF for human variation is supported by several types of
2 information, including information concerning background levels of methanol in humans,
3 variation in pharmacokinetics revealed through human studies and from PBPK modeling,
4 variation of methanol metabolism in human tissues, and information on physiologic factors
5 (including gender and age), or acquired factors (including diet and environment) that may affect
6 methanol exposure and toxicity.
7 Sensitivity analyses of the human PBPK models were performed (see Appendix B), and
8 the results suggest that parameter variability is not likely to result in methanol blood level
9 estimates that vary more than 3-fold, the toxicokinetic portion of the 10-fold UFH. However, one
10 needs to also consider the variation in background levels of methanol (Table 3-1), because that
11 can be a factor governing the impact of an exogenous methanol exposure. From the data in Table
12 3-1, it can be seen that the reported background levels of methanol in blood have ranged
13 considerably, from 0.25 to 5.2 mg/L. Overall, the extent of human interindividual variation in
14 (endogenous and exogenous) methanol toxicokinetics and toxicodynamics would be very
15 difficult to quantify given the significant uncertainties that exist regarding background levels and
16 methanol's mode of action.
17 The candidate effects for RfC derivation have been observed in a potentially susceptible
18 and sensitive fetal/neonatal subpopulation. However, there is also variability across fetuses and
19 neonates that need to be taken into account. Children vary in their ability to metabolize and
20 eliminate methanol and in their sensitivity to methanol's teratogenic effects. There is information
21 on PK and pharmacodynamic factors suggesting that children can have differential susceptibility
22 to methanol toxicity (see Section 4.9.1). Thus, there is uncertainty in children's responses to
23 methanol that should be taken into consideration for derivation of the UF for human variation
24 that is not available from either measured human data or PBPK modeling analyses. The enzyme
25 primarily responsible for metabolism of methanol in humans, ADH, has been reported to be
26 reduced in activity in newborns. Differences in pharmacokinetics include potentially greater
27 pollutant intake due to greater ventilation rates, activity, and greater intake of liquids in children.
28 In terms of differences in susceptibility to methanol due to pharmacodynamic considerations, the
29 substantial anatomical, physiologic, and biochemical changes that occur during infancy,
30 childhood, and puberty suggest that there are developmental periods in which the endocrine,
31 reproductive, immune, audiovisual, nervous, and other organ systems may be especially
32 sensitive.
33 There are limited data from short-term exposure studies in humans and animal
34 experiments that suggest differential susceptibility to methanol on the basis of gender. Gender
35 can provide not only different potential targets for methanol toxicity, but also differences in
36 methanol pharmacokinetics and pharmacodynamics. NEDO (1987) reported that in rats exposed
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1 to methanol pre- and postnatally, 6- and 8-week-old male progeny had significantly lower brain
2 weights at 1,000 ppm, whereas females only showed decreases at 2,000 ppm. In general, gender-
3 related differences in distribution and clearance of methanol may result from the greater muscle
4 mass, larger body size, decreased body fat, and increased volumes of distribution in males
5 compared to females.
5.1.3.2.2. Animal-to-human Extrapolation UFA
6 A factor of 3 was applied to account for uncertainties in extrapolating from rodents to
7 humans (UFA). Application of a full UF of 10 would depend on two areas of uncertainty:
8 toxicokinetic and toxicodynamic. The rodent-to-human toxicodynamic uncertainty is addressed
9 by a factor of 3, as is the practice for deriving RfCs (U.S. EPA, 1994b). In this assessment, the
10 toxicokinetic component of uncertainty is addressed by the determination of a HEC through the
11 use of PBPK modeling. Use of PBPK-estimated maternal blood methanol levels for the
12 estimation of HECs allows for the use of data-derived extrapolations rather than standard
13 methods for extrapolations from external exposure levels. Although PBPK model uncertainties
14 exist, for reasons discussed below, the toxicokinetic uncertainty is reduced to a value of 1 for
15 both of the candidate principal studies.
16 There is uncertainty surrounding the identification of the proximate teratogen of
17 importance (methanol, formaldehyde, or formate) for PBPK modeling, but it is not considered to
18 be substantial enough to warrant a higher uncertainty factor. A review of the reproductive and
19 developmental toxicity of methanol by a panel of experts concluded that methanol, not its
20 metabolite formate, is likely to be the proximate teratogen and that blood methanol level is a
21 useful biomarker of exposure (NTP-CERHR. 2004: Dormanetal.. 1995). The NTP-CERHR
22 Expert Panel based their assessment of potential methanol toxicity on an assessment of
23 circulating blood levels (NTP-CERHR, 2004). EPA has chosen to use blood methanol levels as
24 the dose metric for RfC derivation primarily based on evidence that the toxic moiety is not likely
25 to be the formate metabolite of methanol (NTP-CERHR, 2004). While in vitro evidence indicates
26 that formaldehyde is more embryotoxic than methanol and formate (Harris et al., 2004: 2003),
27 the high reactivity of formaldehyde would limit its unbound and unaltered transport as free
28 formaldehyde from maternal to fetal blood (Thrasher and Kilburn, 2001) (see discussion in
29 Section 3.3). Thus, even if formaldehyde is ultimately identified as the proximate teratogen,
30 methanol would likely play a prominent role, at least in terms of transport to the target tissue.
31 Further discussions of methanol metabolism, dose metric selection, and MOA issues are in
32 Sections 3.3 and 4.7.
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1 There is uncertainty regarding whether the rat and human PBPK models adequately
2 characterize species differences. However, given the chosen dose metrics (AUC or Cmax for
3 methanol in blood), uncertainties in the PBPK modeling of methanol are not expected to be
4 substantially greater for one species than another. Specifically, the analysis of parameter
5 sensitivity and uncertainty for the PBPK modeling performed with human and rat data gave
6 similar results as to how well the model fit the available data (Appendix B). Thus, the human and
7 rat PBPK model performed similarly using these dose metrics for comparisons between species.
8 HEC predictions from the models can vary depending on the dose metric selected (e.g.,
9 AUC or Cmax), but this is not a major source of uncertainty for the following reasons. In the case
10 of the mouse cervical rib endpoint, the choice of the Cmax dose metric was well justified based on
11 studies that show a narrow gestational window of susceptibility for this endpoint (Rogers and
12 Mole, 1997; Bolon et al., 1993). In the case of the rat brain weight endpoint, the choice of the
13 AUC dose metric was well justified based on studies which show an exacerbation of the effect
14 from cumulative exposure (NEDO, 1987; TRL, 1986). Study conditions that involved nearly 24
15 hours of exposure, resulted in an HEC estimate that was not significantly different (-10% lower)
16 than the HEC estimate that would be obtained using Cmax as the dose metric.
17 For estimation of an HEC from the NEDO (1987) rat study, uncertainty that could result
18 in the underestimation of toxicity exists regarding the use of maternal blood levels because of
19 possible species differences in the relation of maternal blood levels estimated by the model to
20 fetal and neonatal blood levels that would be obtained under the gestational, postnatal and
21 lactational exposure scenario. Young animals have different metabolic and physiological profiles
22 than adults. This fact, coupled with multiple routes of exposure, complicate the prediction of
23 internal dose to the offspring.55 Further, methanol dosimetry data are not available for rat pups,
24 human infants, lactating rat dams, nor lactating human mothers (particularly, amounts in breast
25 milk). Given the high aqueous solubility of methanol, it may be reasonable to assume that
26 concentrations expressed in breast milk equal those in maternal blood. However dosimetry in the
27 developing infant would depend on when and to what extent metabolic capacity develops in rat
28 pups versus human infants. So while it would be possible to extrapolate the existing adult models
29 to those life-stages, such extrapolations, for the infant in particular, would be quite speculative
30 and uncertain. However, it is reasonable to assume that the ratio of the difference in blood
31 concentrations between a human infant and mother would be similar to and not significantly
32 greater than the difference in blood concentrations between a rat pup and their rat dam. This
33 assumption is based largely on the fact that key parameters and factors which determine the ratio
55Stern et al. (1996) reported that when rat pups and dams were exposed together during lactation to 4,500 ppm
methanol in air, methanol blood levels in pups from GD6-PND21 were approximately 2.25 times greater than those
of dams. It is reasonable to assume that similar differences in blood methanol levels would be observed in the
NEDO (1987) FI study, as the exposure scenario is similar to that of Stern et al. (1996).
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1 of fetal or neonatal versus maternal methanol blood levels in humans either do not change
2 significantly with age (partition coefficients, relative blood flows) or scale in a way that is
3 common across species (allometrically). While there is uncertainty surrounding this assumption,
4 it is not likely to have a major impact given that health-effects data indicate that most of the
5 effects of concern are due to in utero exposure, with a relatively small influence due to postnatal
6 exposures.
5.1.3.2.3. Database UFD
7 For determining the application of the database UF (UFo), EPA's guidance (U.S. EPA,
8 2002) states, "In addition to identifying toxicity information that is lacking, review of existing
9 data may also suggest that a lower reference value might result if additional data were
10 available." Based upon this guidance, a UFD of 3 was applied to account for deficiencies in the
11 toxicity database that may result in a lower reference value. While the database for methanol
12 toxicity is extensive in terms of the laboratory species and study design coverage, consisting of
13 chronic and developmental toxicity studies in rats, mice, and monkeys, a two-generation
14 reproductive toxicity study in rats, and neurotoxicity and immunotoxicity studies, there still
15 remains some uncertainty with respect to the potency, importance and relevance of reproductive,
16 developmental and chronic effects observed in monkeys. With regard to potency, uncertainty is
17 warranted given evidence that these effects have been observed in monkeys with average blood
18 levels that are close to, and in one case as little as 0.5 mg/L higher than, the range of
19 uncontaminated background levels in humans (see Figure 5-4 and discussion in Sections 5.3.6
20 and 5.3.7). Also, uncertainty regarding the potency, importance and relevance of these effects has
21 been expressed in the external peer review of this assessment (e.g., Appendix A external review
22 comments in response to Charge D3) and in three independent peer reviews of the individual
23 monkey studies (discussed below).
24 As discussed in Section 5.1.1.1, the available monkey studies are considered inadequate
25 or inferior to the candidate principal rodent studies for the purposes of RfC/D derivation. As has
26 been suggested by one of the peer reviewers who questioned the need for a 3-fold UFo (e.g.,
27 Appendix A external review comments in response to Charge B4), this deficiency in the dose-
28 response data would not normally warrant a UFo given the scope of the existing database and the
29 qualitative value of the chronic and developmental monkey studies for hazard identification.
30 However, this deficiency is of particular concern for methanol given (1) metabolic similarities
31 that suggest monkeys should most closely represent the potential for effects in humans (see
32 Section 3.1) and (2) uncertainties regarding the importance and relevance of the monkey effects
33 mentioned above and discussed further below.
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1 The reproductive effects (discussed in Section 4.3.2) and the developmental
2 neurobehavioral effects (discussed Section 4.4.2) reported by Burbacher et al. (2004a; 2004b:
3 1999a: 1999b) were independently peer reviewed by HEI (Burbacher et al., 2004a: 2004b:
4 1999a: 1999b) and NTP-CERHR (2004. 2003). The NEDO (1987) acute and chronic studies
5 were also independently peer reviewed (ERG, 2009). All three of these independent peer reviews
6 concluded that these studies identified effects of potential relevance but uncertain adversity that
7 warrant further research. For example, with respect to the Burbacher et al. (2004a; 2004b: 1999a:
8 1999b) CERHR (2004) stated that "the Panel could not determine whether or not the possible
9 effects observed in late gestation were treatment-related" and that the positive findings in DNT
10 tests provide "... evidence of subtle, but not definitive, adverse effects that are ... important from
11 a qualitative perspective" and suggested specific additional research topics to help resolve these
12 uncertainties. With respect to NEDO (1987) monkey studies, peer reviewers (ERG, 2009) noted
13 the small dose group sizes and profound data gaps in the report (e.g., materials and methods,
14 statistical methods, data), and also suggested additional research to improve both the qualitative
15 and quantitative interpretation of the NEDO (1987) findings.
16 In contrast to the data on chronic and reproductive toxicity, the developmental
17 neurotoxicity data are comparable across the two species and, of the uncertain effects observed in
18 monkeys, the results of the visually directed reaching (VDR) test are likely to be the most
19 reliable, discernible and relevant (see discussion in Section 4.4.2 and the BMD analysis in
20 Appendix D). Also, EPA's guidance (U.S. EPA, 2002) places particular emphasis on database
21 deficiencies in the area of developmental toxicity, stating that "If data from the available
22 toxicology studies raise suspicions of developmental toxicity and signal the need for
23 developmental data on specific organ systems (e.g., detailed nervous system, immune system,
24 carcinogenesis, or endocrine system), then the database factor should take into account whether
25 or not these data are available and used in the assessment and their potential to affect the POD
26 for the particular duration RfD or RfC under development." Table 5-5 provides a comparison of
27 the lowest methanol blood LOAELs (excluding background) observed in rodent and monkey
28 developmental neurotoxicity studies. Even after using EPA's rat PBPK and monkey PK models
29 to convert external doses to internal blood levels (to account for toxicokinetic differences), the
30 rodent LOAEL blood level is 12-fold higher than the monkey LOEL blood level. Some of this
31 12-fold difference may be due to differences in species sensitivity, for which the UFA of 3-fold is
32 intended to account, but some of the difference may be due to other factors, including whether
33 appropriate and comparable endpoints were examined and whether appropriate study designs and
34 quality control measures were used. To account for these additional factors, a 3-fold UFD is
35 applied.
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Table 5-5 Comparison of the lowest rodent and monkey methanol blood LOAELs
(excluding background) observed in developmental neurotoxicity studies.
Reference
NEDO (1987) Follow-up
study, FI generation
Burbacher et al. (2004a:
2004b; 1999a; 1999b)
Rodent:MonkeyMethanol
Strain/ Exposure
Rat, S-D
GDO through FI generation
Monkey, M. fascicularis
2.5 hr/day, 7 days/wk;
premating, mating and
gestation
Blood Level Ratio
Effect
Reduced brain
weight
Neurotoxicology
. deficits
(reduced VDR
test results)
LOAEL" (ppm; mg/L
1,000 ppm;
115 mg/L
600 ppm;
10 mg/L
12
bloodb)
5.1.3.2.4. Extrapolation from subchronic to chronic UFs
1 A UF of 1 was used for extrapolation from less than chronic results because
2 developmental toxicity (extra cervical rib incidence and decreased brain weight) was used as the
3 critical effect. The developmental period is recognized as a susceptible lifestage where exposure
4 during certain time windows is more relevant to the induction of developmental effects than
5 lifetime exposure (U.S. EPA. 1991).
5.1.3.2.5. LOAEL-to-NOAEL extrapolation UFs
6 A UF of 1 was used for LOAEL to NOAEL (UFL) because the current approach is to
7 address this extrapolation as one of the considerations in selecting a benchmark response (BMR)
8 for BMD modeling. In this case, the endpoint and benchmark response level employed for the
9 RfD/C derivation is appropriate for use in deriving the RfD/C under the assumption that it
10 represents a minimal biologically significant change.
5.1.3.3. Confidence in the RfC
11 The confidence in the RfC is medium to high. Confidence in the Rogers et al. (1993b)
12 study is high and confidence in the NEDO (1987) developmental studies is medium. The Rogers
13 et al. (1993b) study was well designed, as it included large sample sizes, and was well
14 documented, peer reviewed and published. While there are issues with the lack of detail
15 regarding methods and results in the NEDO (1987) report, the observed effect (brain weight
16 reduction) is a relevant endpoint that has been reproduced in an oral study of adult rats (TRL,
17 1986), and the exposure regimen involving pre- and postnatal exposures addresses a potentially
18 sensitive human subpopulation. Confidence in the database is medium. Though skeletal and
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1 brain effects have been demonstrated and corroborated in multiple animal studies in rats, mice,
2 and monkeys, some study results were not quantifiable, thus there is uncertainty regarding which
3 is the most relevant test species, and there is limited data regarding reproductive or
4 developmental toxicity of methanol in humans. There is also uncertainty regarding the potential
5 active agent—the parent compound, methanol, formaldehyde, formate or some other (e.g.,
6 reactive oxygen species) agent. There are deficiencies in the knowledge of the metabolic
7 pathways of methanol in the human fetus during early organogenesis, when the critical effects
8 can be induced in animals. Thus, the medium-to-high confidence in the critical studies and the
9 medium confidence in the database together warrant an overall confidence descriptor of medium
10 to high.
5.1.4. Previous RfC Assessment
11 The health effects data for methanol were assessed for the IRIS database in 1991 and
12 were determined to be inadequate for derivation of an RfC.
5.2. Oral Reference Dose (RFD)
13 In general, the RfD is an estimate of a daily exposure to the human population (including
14 susceptible subgroups) that is likely to be without an appreciable risk of adverse health effects
15 over a lifetime. It is derived from a POD, generally the 95 percent lower bound confidence limit
16 on the BMD, with uncertainty factors applied to reflect limitations of the data used. The RfD is
17 expressed in terms of mg/kg-day of exposure to a substance and is derived by a similar
18 methodology as is the RfC. Ideally, studies with the greatest duration of exposure and conducted
19 via the oral route of exposure give the most confidence for derivation of an RfD. For methanol,
20 the oral database is currently more limited than the inhalation database. With the development of
21 PBPK models for methanol, the inhalation database has been used to help bridge gaps in the oral
22 database to derive an RfD. As for the RfC, limitations and uncertainties associated with the
23 derivation of the RfD are addressed through the use of the BMD modeling approach, rat and
24 human PBPK models and uncertainty factors.
5.2.1. Choice of Principal Study and Critical Effect-with Rationale and
Justification
25 No studies have been reported in which humans have been exposed subchronically or
26 chronically to methanol by the oral route of exposure and thus, would be suitable for derivation
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1 of an oral RfD. Data exist regarding effects from oral exposure in experimental animals, but they
2 are more limited than data from the inhalation route of exposure (see Sections 4.2, 4.3, and 4.4).
3 Only two oral studies of 90 days duration or longer in animals have been reported
4 (Soffritti et al.. 2002: TRL. 1986) for methanol.U.S. EPA CTRL. 1986) reported that there were
5 no differences in body weight gain, food consumption, or gross or microscopic evaluations in
6 Sprague-Dawley rats gavaged with 100, 500, or 2,500 mg/kg-day methanol versus control
7 animals. Liver weights in both male and female rats were increased, although not significantly, at
8 the 2,500 mg/kg-day dose level, suggesting a treatment-related response despite the absence of
9 histopathologic lesions in the liver. Brain weights of high-dose group males and females were
10 significantly less than control animals at terminal (90-day) sacrifice. The data were not reported
11 in adequate detail for dose-response modeling and subsequent BMD estimation. Based primarily
12 on the qualitative findings presented in this study, the 500 mg/kg-day dose was deemed to be a
13 NOAEL.56
14 The only lifetime oral study available was conducted by Soffritti et al. (2002) in Sprague-
15 Dawley rats exposed to 0, 500, 5,000, 20,000 ppm (v/v) methanol, provided ad libitum in
16 drinking water. Based on default, time-weighted average body weight estimates for Sprague-
17 Dawley rats (U.S. EPA. 1988). average daily doses of 0, 46.6, 466, and 1,872 mg/kg-day for
18 males and 0, 52.9, 529, 2,101 mg/kg-day for females were reported by the study authors. All rats
19 were exposed for up to 104 weeks, and then maintained until natural death. The authors report no
20 substantial changes in survival nor was there any pattern of compound-related clinical signs of
21 toxicity. The authors did not report noncancer lesions, and there were no reported compound-
22 related signs of gross pathology or histopathologic lesions indicative of noncancer toxicological
23 effects in response to methanol.
24 Five oral studies investigated the reproductive and developmental effects of methanol in
25 rodents (Aziz et al.. 2002: Fuetal.. 1996: Sakanashi et al.. 1996: Rogers etal.. 1993b: Infurna
26 and Weiss, 1986), including three studies that investigated the influence of folic acid diets on the
27 effects of methanol exposures (Aziz et al., 2002: Fu et al., 1996: Sakanashi et al., 1996). Infurna
28 and Weiss (1986) exposed pregnant Long-Evans rats to methanol at 2,500 mg/kg-day in drinking
29 water on either GDIS-GDI? or GD17-GD19. Litter size, pup birth weight, pup postnatal weight
30 gain, postnatal mortality, and day of eye opening were no different in treated animals versus
31 controls. Mean latency for nipple attachment and homing behavior (ability to detect home
32 nesting material) were different in both methanol treated groups, and these differences were
33 significantly different from controls. Rogers et al. (1993b) exposed pregnant CD-I mice via
34 gavage to 4 g/kg-day methanol, given in 2 equal daily doses. Incidence of cleft palate and
56 U.S. EPA [TRL (1986)1 did not report details required for a BMD analysis such as standard deviations for mean
responses.
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1 exencephaly was increased following this maternal exposure to methanol. Also, an increase in
2 totally resorbed litters and a decrease in the number of live fetuses per litter were observed.
3 Aziz et al. (2002), Fu et al. (1996), and Sakanashi et al. (1996) investigated the role of
4 folic acid in methanol-induced developmental neurotoxicity. Like Rogers et al. (1993b), the first
5 2 studies observed that an oral gavage dose of 4-5 g/kg-day methanol during GD6-GD15 or
6 GD6-GD10 resulted in an increase in cleft palate in mice fed sufficient folic acid diets, as well as
7 an increase in resorptions and a decrease in live fetuses per litter. Fu et al. (1996) also observed
8 an increase in exencephaly in the folic acid sufficient (FAS) group. Both studies found that an
9 approximately 50% reduction in maternal liver folate concentration resulted in an increase in the
10 percentage of litters affected by cleft palate (as much as threefold) and an increase in the
11 percentage of litters affected by exencephaly (as much as 10-fold). Aziz et al. (2002) exposed rat
12 dams throughout their lactation period to 0, 1, 2, or 4% v/v methanol via drinking water,
13 equivalent to doses of approximately 480, 960 and 1,920 mg/kg-day.57 Pups were exposed to
14 methanol via lactation from PND1-PND21. Methanol treatment at 2% and 4% was associated
15 with significant increases in activity (measured as distance traveled in a spontaneous locomotor
16 activity test) in the FAS group (13 and 39%, respectively) and most notably, in the folic acid
17 deficient (FAD) group (33 and 66%, respectively) when compared to their respective controls. At
18 PND45, the condition avoidance response (CAR) in FAD rats exposed to 2% and 4% methanol
19 was significantly decreased by 48% and 52%, respectively, relative to nonexposed controls. In
20 the FAS group, the CAR was only significantly decreased in the 4% methanol-exposed animals
21 and only by 22% as compared to their respective controls.
5.2.1.1. Route-to-Route Extrapolation
22 Developmental effects are considered the most sensitive effects of methanol exposure
23 (see Section 5.1.1). EPA has derived an RfD by using developmental response data from the
24 candidate principal inhalation studies through route-to-route extrapolation employing the EPA
25 PBPK model (see Sections 3.4 and 5.1). Several factors support use of route-to-route
26 extrapolation for methanol. The oral database has significant limitations, including the limited
27 reporting of noncancer findings in the subchronic (TRL, 1986) and chronic studies (Soffritti et
28 al., 2002) of rats, and the use of high dose levels in the rodent oral developmental studies. In
29 addition, the limited data from oral studies indicate similar effects as reported via inhalation
30 exposure (e.g., the brain and fetal skeletal system are targets of toxicity). Further, methanol has
31 been shown to be rapidly and well-absorbed by both the oral and inhalation routes of exposure
57 Assuming that Wistar rat drinking water consumption is 60 mL/kg-day (Rogers et al.. 2002X 1% methanol in
drinking water would be equivalent to 1% x 0.8 g/mL x 60 mL/kg-day = 0.48 g/kg-day = 480 mg/kg-day.
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1 (NTP-CERHR. 2004: Kavet and Nauss. 1990). Once absorbed, methanol distributes rapidly to all
2 organs and tissues according to water content, regardless of route of exposure.
3 As with the species-to-species extrapolation used in the development of the RfC, the dose
4 metric used for species-to-species and route-to-route extrapolation of inhalation data to oral data
5 is the Cmax (in the case of the mouse cervical rib endpoint) or AUC (in the case of the rat brain
6 weight endpoint) of methanol in blood. Simulations of human oral methanol exposure were
7 conducted using the model parameters as previously described for human inhalation exposures,
8 with human oral kinetic/absorption parameters from Sultatos et al. (2004) (i.e., kas = 0.2, ks; =
9 3.17, and ka; = 3.28). Human oral exposures were assumed to occur during six drinking episodes
10 during the day, at times 0, 3, 5, 8, 11, and 15 hours from the first ingestion of the day. For
11 example, if first ingestion occurred at 7 a.m., the six episodes would be at 7 a.m., 10 a.m.,
12 12 noon, 3 p.m., 6 p.m., and 10 p.m. Each ingestion event was treated as occurring over 3
13 minutes, during which the corresponding fraction of the daily dose was infused into the stomach
14 lumen compartment. The fraction of the total ingested methanol simulated at each of these times
15 was 25%, 10%, 25%, 10%, 25%, and 5%, respectively. Six days of exposure were simulated to
16 allow for any accumulation (visual inspection of plots showed this to be finished by the 2nd or
17 3rd day), and the results for the last 24 hours were used. Dividing the exposure into more and
18 smaller episodes would decrease the estimated peak concentration, but have little effect on AUC.
19 This dose metric was used for dose-response modeling to estimate the BMDL or PODinternai-
5.2.2. RfD Derivation-Including Application of Uncertainty Factors
5.2.2.1. Derivation of Candidate RfDs
20 Inhalation studies considered in the derivation of the RfC are used to supplement the oral
21 database through use of route-to-route extrapolation, as previously described. As for the RfC,
22 BMD approaches were applied to the existing inhalation database, and the EPAPBPK model was
23 used for species-to-species extrapolations. Table 5-6 presents the candidate RfDs based on the
24 selected developmental endpoints, the BMD modeling approaches employed (see Appendix D
25 for details), and the applied UFs (see Section 5.2.2.2) using route-to-route extrapolation
26 (obtained from PBPK models described in Appendix B). Like the RfC derivation, the internal
27 BMDL (PODimemai) values are divided by a total UF of 100 (UFH of 10, UFA of 3 and a UFD of 3)
28 to yield an RfDinternai, which is converted to a candidate RfD using the human PBPK model
29 described in Appendix B.58 Candidate RfDs estimated from the Rogers et al. (1993b) study for
58 An algebraic equation is provided near the end of Appendix B that approximates the PBPK model predicted
relationship between methanol AUC above background and the HED in mg/kg-day.
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1 extra cervical rib incidence in mice employing Cmax as the dose metric were 4.1 and 1.9 mg/kg-
2 day using BMRs of 10% and 5%, respectively. Candidate RfDs estimated from the NEDO
3 (1987) study based on decreases in brain weight at 6 weeks of age in male rats exposed during
4 gestation and throughout the FI generation employing AUC as the dose metric were 5.4 and
5 4.0 mg/kg-day for BMRs of 5% change relative to control mean and one SD from the control
6 mean, respectively. Because the cervical rib endpoint resulted in the lowest of the candidate RfD
7 estimates, it was chosen as the critical endpoint for use in the RfD derivation.
8 RfD = 43.1 mg/L + 100 = 0.43 mg/L =^>PBPK^> 2 mg/kg-day
9 (rounded to 1 significant figure)
Table 5-6 Summary of PODs for critical endpoints, application of UFs and conversion to
candidate RfDs using PBPK modeling.
Rogers et al. Q993b)
(mouse cervical rib Cmax)
10% BMR 5% BMR
BMDL = PODmtemai 90.9 mg/L 43.1 mg/L
RfDmtemai = PODmtemal/UFsa 0.909 mg/L 0.43 mg/L
\RfD (mg/kg/day)b 3.9 1.9
NEDO (1987)
(rat brain wt. AUC)
5% BMR 1 SD BMR
1,183 mg-hr/L 858 mg-hr/L
1 1.83 mg-hr/L 8.58 mg-hr/L
7.1 5.2
aLTFA =3; LTFD = 3; LTFH = 10; LTFS = 1; LTFL = 1; product of all UFs = 100 ; see Section 5.2.2.2 below for details.
bEach candidate RfD is the oral dose predicted to yield a blood concentration equal to its corresponding RfDintemai, using
the human PBPK model described in Appendix B, with a background blood concentration of 2.5 mg/L, which corresponds
to an estimated maximum background exposure rate for a diet including fruits and vegetables of 1600 mg/day in a 70-kg
person (see discussion in Section 5.3.6); the final RfC is rounded to one significant figure.
5.2.2.2. Application of UFs
10 Because the same studies, endpoints, BMD methods and PBPK models used to derive the
11 candidate RfCs were also used to calculate the candidate RfDs, the RfD derivation uses the same
12 values for uncertainty factors as are described for the RfC derivation (Section 5.1.3.2).
13 Consistent with the RfC derivation, in order to avoid the uncertainty associated with applying the
14 human PBPK model to exposure levels that are above the levels for which the model was
15 calibrated and to account for possible non-linearities in the external versus internal dose
16 relationships at high doses, EPA applied the UFs to the internal BMDL (PODinternai) prior to HED
17 derivation to obtain an RfDinternai (see Table 5-6).
18
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5.2.2.3. Confidence in the RfD
1 The confidence in the RfD is medium to high. Despite the relatively high confidence in
2 the critical studies, all limitations to confidence as presented for the RfC also apply to the RfD.
3 Confidence in the RfD is slightly lower than for the RfC due to the lack of adequate oral studies
4 for the RfD derivation, necessitating a route-to-route extrapolation.
5.2.3. Previous RfD Assessment
5 The previous IRIS assessment for methanol included an RfD of 0.5 mg/kg-day that was
6 derived from a U.S. EPA [(TRL, 1986)1 subchronic oral study in which Sprague-Dawley rats
7 (30/sex/dose) were gavaged daily with 0, 100, 500, or 2,500 mg/kg-day of methanol. Elevated
8 levels of serum glutamic pyruvic transaminase (SGPT), serum alkaline phosphatase (SAP), and
9 increased, but not statistically significant, liver weights in both male and female rats suggest
10 possible treatment-related effects in rats dosed with 2,500 mg methanol/kg-day, despite the
11 absence of supportive histopathologic lesions in the liver. Brain weights of both high-dose group
12 males and females were significantly less than those of the control group. Based on these
13 findings, 500 mg/kg-day of methanol was considered a NOAEL in this rat study. Application of a
14 1,000-fold UF (interspecies extrapolation, susceptible human subpopulations, and subchronic to
15 chronic extrapolation) yielded an RfD of 0.5 mg/kg-day.
5.3. Uncertainties in the Inhalation RfC and Oral RfD
16 The following is a more extensive discussion of the uncertainties associated with the RfC
17 and RfD for methanol beyond that which is addressed quantitatively in Sections 5.1.2, 5.1.3, and
18 5.2.2. A summary of these uncertainties is presented in Table 5-7.
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Table 5-7 Summary of uncertainties in methanol noncancer assessment.
Consideration
Choice of
study/endpoint
Potential Impact
Minimal impact. RfD
and RfC estimates
from candidate
principal studies were
extremely close to one
another.
Decision
RfC is based on brain
weight reduction in
rats NEDO (1987) ;
RfD is based on
cervical rib anomalies
in mice Rogers et al.
(1993b)
Justification
The chosen endpoints were observed in
adequate studies, have been observed in
other rodent studies, are considered
biological significant and relevant to
humans, and were the most sensitive of the
quantifiable endpoints for their respective
route of exposure.
Choice of model for
BMDL estimation
BMDLs from
adequately fitting
models differed by 5-
foldfortheRfC,
indicating high model
dependence, and were
within 25% of each
other for the RfD,
indicating little model
dependence.
Hill model was chosen
for derivation of the
POD for the RfC and
NLogistic model was
chosen for derivation
of the POD for the
RfD.
Hill model was chosen because it resulted
in the lowest BMDL from among a wide
range (>3-fold) of BMDL estimates from
adequately fitting models. NLogistic
model was the best fitting model in
accordance with U.S. EPA (2012) criteria.
Route-to-Route
Extrapolation method
Raises the RfD 7-fold Human PBPK model Rogers et al. (1993b) study was a high
above 1988 methanol was used to estimate quality study, measured a sensitive and
RfD of 0.5 mg/kg-day HED from blood levels relevant endpoint, provided measured
based on oral study by reported in Roger et al. blood concentrations that could be
TRL (1986) (1993b) study. converted to oral doses with the EPA
human PBPK model.
Statistical uncertainty
at POD (sampling
variability due to
bioassay size)
POD would be-50%
higher if BMD were
used
A BMDL was used as
the POD
The BMDL is the lower limit of a one-
sided 95% confidence interval on the
BMD.
Choice of
species/gender
PODs for the RfC and
RfD estimates based
on rat and mouse data
are similar; POD
estimates based on
monkey data would be
-30-50% lower
RfC and RfD were
based on the most
sensitive of relevant
and quantifiable
endpoints in the most
sensitive species and,
in the case of the RfC,
also in the most
sensitive gender.
Mouse and rat studies gave similar results
forRfC/D. Qualitative evidence from
NEDO (1987). Burbacher et al. (2004b)
and Burbacher et al. (2004a) suggest that
monkeys may be a sensitive species, but
data are not as reliable for quantification.
No gender differences were noted by
Rogers et al. (1993b). but NEDO (1987)
reported slightly greater brain weight
changes in male offspring.
Relationship of the
RfC and RfD to
Background Blood
Levels and Blood
Levels In Monkeys
Associated with
Unquantifiable Effects
Adverse effects may
result if RfC and RfD
are too large.
RfD and RfCs are
deemed adequately
protective and
reasonable.
RfD and RfC would cause an appreciable
increase in the number of individuals with
blood levels above 2.5 mg/L, the high end
of the range of background methanol blood
levels associated with a diet that includes
fruits and vegetables.
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5.3.1. Choice of Study/Endpoint
1 As discussed in Sections 5.1.1 and 5.2.1, developmental effects observed in two
2 candidate principal studies were considered for the purposes of RfC/D derivation. Brain weight
3 reduction in rats (NEDO, 1987) and cervical rib anomalies in mice (Rogers et al., 1993b) were
4 selected as the endpoints reported in these studies that are most appropriate for RfC/D derivation.
5 Candidate RfCs derived based on these endpoints ranged from 17.8 to 41.8 mg/m3 (Table 5-4).
6 Candidate RfDs derived using route-to-route extrapolation and based on the same endpoints as
7 the candidate RfCs ranged from 1.9 to 5.4 mg/kg-day (Table 5-6).
8 Uncertainties associated with the Rogers (1993b) study results are primarily with respect
9 to the relevance of developmental studies in rodents to humans, which is discussed in Sections
10 5.1.1.2.1 and 5.3.5. There is less uncertainty associated with the Rogers et al. (1993b) study
11 methods and reporting because it has undergone independent peer review, is well documented,
12 used robust group sizes, and reports effects that have been observed by other laboratories. In
13 addition individual animal data were made available by the authors (see Appendix D).
14 Uncertainties in the NEDO (1987) developmental study are primarily associated with the
15 reproducibility of the brain weight endpoint and the level and quality of study documentation.
16 Neonatal reduction in brain weight is not as well documented across laboratories and across
17 species and strains of test animals as is the fetal cervical rib endpoint. However, this is not a
18 major concern given that reduced brain weight following methanol gavage exposure was
19 reported in adult S-D rats by another laboratory (TRL, 1986). and in two other NEDO (1987) S-
20 D rat developmental inhalation studies, including in another teratogenicity study and in both
21 generations of a two generation study. In addition, CNS effects have been reported in inhalation
22 studies of monkeys, including abnormal brain histopathology following chronic methanol
23 exposure (NEDO, 1987) and delayed neurological development following gestational methanol
24 exposure (Burbacher et al., 2004a: 2004b: 1999a: 1999b). Further, the primary reason that the
25 developmental brain weight effect has not been identified in other species could be that it has not
26 been the focus of other laboratory research. More important is the uncertainty associated with the
27 lack of documentation in the NEDO (1987) supplementary developmental study that formed the
28 basis for EPAs benchmark dose analysis. The three primary reporting deficiencies in this study,
29 identified during external peer review (ERG, 2009), were: (1) lack of information on the number
30 and health of pregnant dams, (2) not reporting the body weight of the offspring, and (3) lack of a
31 statistical analysis of response data. While the methods employed in this supplementary study
32 were not adequately described, the methods used in the parent two-generation study were
33 adequately described. Because these two studies were conducted in the same laboratory, it is
34 reasonable to assume that the supplementary study was performed under the same protocol as the
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1 two-generation study, starting with a number of F0 parents appropriate for a one-generation
2 developmental study.59 While data related to maternal or gestational outcomes in the
3 supplementary study were not provided, signs of overt maternal toxicity were not reported in the
4 two-generation study at similar exposure levels, and thus it is reasonable to assume that they did
5 not occur, and would have been reported had they been observed, in the supplementary study.
6 With respect to the second source of documentation-related uncertainty, the NEDO
7 supplementary study only reported means and standard deviations for absolute brain weight
8 change and did not report body weight data for the offspring. However, body weight data
9 reported in the parent two-generation study did not indicate a body weight effect in the exposed
10 FI or p2 generation pups. Further, EPA neurotoxicity guidelines (U.S. EPA, 1998a) state that a
11 "change in brain weight is considered to be a biologically significant effect," and further states
12 that "it is inappropriate to express brain weight changes as a ratio of body weight and thereby
13 dismiss changes in absolute brain weight." The third source of documentation-related uncertainty
14 noted by the external peer reviewers of the NEDO supplementary study, was that the
15 investigators did not report the results of a more appropriate (e.g., ANOVA) test for statistical
16 significance. This is not a significant source of uncertainty because EPA did not rely on the
17 NEDO statistical tests, but instead performed its own more definitive trend test benchmark dose
18 analysis of the data (see Appendix D). In summary, while there are uncertainties concerning the
19 NEDO (1987) supplementary study that forms the basis of the RfC, particularly with respect to
20 reporting deficiencies, there is sufficient ancillary evidence to offset these concerns and allow for
21 the consideration the this study as a basis for RfC or RfD derivation.
22 The use of reproductive and neurotoxicity endpoints reported in developmental
23 (Burbacher et al.. 2004a: 2004b: 1999a: 1999b) and chronic (NEDO. 1987) monkey studies
24 would potentially result in lower reference values, but significant uncertainties associated with
25 the reported dose-response data (e.g., an absent or questionable dose-response relationship)
26 preclude their use as the basis for an RfC. Burbacher et al. (2004a; 2004b: 1999a: 1999b)
27 exposedM. fascicularis monkeys to 0, 200, 600, or 1,800 ppm (0, 262, 786, and 2,359 mg/m3)
28 methanol 2.5 hours/day, 7 days/week during premating/mating and throughout gestation
29 (approximately 168 days). They observed a slight, but statistically significant, shortening of
30 gestation period in all exposure groups. As discussed in Sections 4.3.2 and 5.1.1.2, there are
59 The number of F0 parents in the supplemental experiment was not reported, but the number of pups per dose
group was presented, and it is reasonable to assume that, consistent with the culling protocol used for the two-
generation study (NEDO. 1987 pages 185 and 189 ), each dose group pup came from a different litter (to avoid
"litter correlation" issues). EPA developmental neurotoxicity guidelines (U.S. EPA. 1998b) require that "on
postnatal day 11, either 1 male or 1 female pup from each litter (total of 10 males and 10 females per dose group)
should be sacrificed." Hence, by examining more than 10 male and 10 female litter-specific pups per dose group at
three time points (3, 6 and 8 wks), the NEDO supplementary study would exceed EPA recommendations for this
type of study.
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1 questions concerning this effect and its relationship to methanol exposure. In these studies,
2 neurobehavioral function was assessed in infants during the first 9 months of life. Two tests out
3 of nine returned positive results that were possibly related to methanol exposure. The Fagan test
4 of infant intelligence indicated small, but non significant deficits of performance (decreased time
5 spent looking at novel faces versus familiar faces) in treated infants. Also, VDR performance
6 was reduced in all treated male infants, and was significantly reduced in the 1,800 ppm
7 (2,359 mg/m3) group for both sexes and in the 600 ppm (786 mg/m3) group for males. However,
8 as discussed in Appendix D, an overall dose-response trend for this endpoint was not apparent in
9 males and was only marginally significant in females, which had a larger overall sample size
10 across dose groups than males (21 females versus 13 males). A benchmark dose analysis was
11 done for the VDR effect in female monkeys using Cmax (adjusted for background blood
12 methanol) as the dose metric (results detailed in Appendix D.3). The BMDL was estimated to be
13 19.6 mg/L. While there are significant concerns regarding the dose-response relationship for this
14 VDR endpoint, this BMDL (based on Cmax) is consistent with the BMDLs (based on Cmax and
15 AUC) estimated from the rodent studies and represents a measure of functional deficit in
16 sensorimotor development that is possibly consistent with developmental CNS effects (i.e., brain
17 weight changes) that have been observed in rats (NEDO, 1987). Although the VDR test results
18 suggest that prenatal exposure to methanol can result in neurotoxicity to the offspring, the use of
19 such statistically borderline dose-response data is not warranted in the derivation of the RfC or
20 RfD, given the availability of better dose-response data in other species.
21 NEDO (1987) examined the chronic neurotoxicity of methanol in monkeys (M.
22 fascicularis) exposed to 0, 10, 100, or 1,000 ppm (13.1, 131, or 1,310 mg/m3) methanol for up to
23 29 months. Multiple effects were noted at 131 mg/ m3, including slight myocardial effects
24 (negative changes in the T wave on an EKG), degeneration of the inside nucleus of the thalamus,
25 and abnormal pathology within the cerebral white tissue in the brain. The results support the
26 identification of 10 ppm (13.1 mg/m3) as the NOAEL for neurotoxic effects in monkeys exposed
27 chronically to inhaled methanol. However, as discussed in Section 4.2.2.3, there exists
28 significant uncertainty in the interpretation of these results and their utility in deriving an RfC for
29 methanol. These uncertainties include lack of appropriate control group data and the limited
30 nature of the reporting of the neurotoxic effects observed. Thus, while the NEDO (1987) study
31 suggests that monkeys may be a more sensitive species to the neurotoxic effects of chronic
32 methanol exposure than rodents, the deficiencies in the reporting of data preclude the use of this
33 study for the derivation of an RfC.
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5.3.2. Choice of Model for BMDL Estimation
1 As discussed in Section 5.1.2.1, in the absence of an established MOA or a biological
2 basis for why one model should be preferred, the choice of model for a dose-response analysis is
3 based on which model exhibits the best mathematical fit to the experimental data. There is
4 uncertainty inherent in this approach with respect to how well the selected model reflects the true
5 dose-response relationship. This uncertainty is increased when there is no biologically basis for
6 model selection and the dose-response data demonstrate a high degree of model dependence
7 (e.g., BMDL results vary widely for all models employed). This is the case for the BMD analysis
8 of the NEDO (1987) rat brain weight endpoint. As described in Appendix D, the BMDL from the
9 Hill model was selected as the most appropriate model for derivation of an RfC from this
10 endpoint, in accordance with EPA BMD Technical Guidance (U.S. EPA, 2012) , because it
11 yielded the lowest BMDL from among a broad range of BMDLs and provided a superior fit in
12 the low dose region nearest the BMD. If another adequately fitting model had been chosen, the
13 BMDL would have been as much as 5-fold higher. With respect to the mouse cervical rib
14 endpoint, model uncertainty is somewhat reduced because the nested Logistic (NLogistic) model
15 employed has some biological basis, in that it accounts for possible litter-specific covariates and
16 correlations, and BMDL results from the three nested models employed were within a relatively
17 small, 1.3-fold range. Therefore, in accordance with EPA BMD Technical Guidance (U.S. EPA,
18 2012), the NLogistic model was selected a as the most appropriate model for derivation of an
19 RfC because it yielded the lowest AIC and exhibited a superior fit in the low dose region nearest
20 the BMD.
5.3.3. Route-to-Route Extrapolation
21 To identify a POD from which to derive an RfD based on cervical rib anomalies in mice,
22 a route-to-route extrapolation was performed using the POD from which the RfC was derived.
23 One way to characterize the uncertainty associated with this route-to-route extrapolation is to
24 compare the responses observed in the critical inhalation study to responses observed in similar
25 oral developmental studies. As discussed in Section 5.2.1, Rogers et al. (1993b) conducted both
26 an inhalation and oral developmental studies of methanol in CD-I mice. The oral study involved
27 a single dose of 4,000 mg/kg-day methanol and resulted in effects (i.e., cleft palate and
28 exencephaly) consistent with the skeletal abnormalities observed in the inhalation developmental
29 studies in CD-I mice (Rogers and Mole, 1997; Rogers et al., 1993b). Brain weight reductions
30 observed in rats in the other candidate principal developmental study (NEDO, 1987) have been
31 observed in an oral study in adult rats exposed to 2,500 mg/kg-day methanol (TRL, 1986) .
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1 While the oral doses associated with adverse effect in the Rogers et al. (1993b) and TRL (1986)
2 oral studies were 11- to 30-fold higher than the 133-220 mg/kg-day human equivalent oral doses
3 estimated for BMDLs from the candidate inhalation studies (see Section 5.3.1.2), the observation
4 of similar effects in the same species following oral and inhalation exposure to methanol reduces
5 some of the uncertainty associated with a route-to-route extrapolation.
5.3.4. Statistical Uncertainty at the POD
6 Uncertainty in the BMD used to derive the POD for the RfC/D can be assessed through
7 confidence intervals. For the Hill and NLogistic models applied to the data for decreased brain
8 weight in rats and cervical rib anomalies in mice, respectively, there is a degree of uncertainty in
9 the BMD estimate at the BMR reflected by a 40-50% difference between the 95% one-sided
10 lower confidence limit (BMDL) and the maximum likelihood estimate of the BMD. Thus, the
11 POD for the RfC and RfD would be approximately 50% higher if the BMD were used instead of
12 the BMDL.
5.3.5. Choice of Species/Gender
13 The RfC derivation was based on decreased brain weight at 6 weeks (postnatal) in male
14 (the gender most sensitive to this effect) S-D rats (NEDO, 1987) and the RfD was based on
15 cervical rib anomalies in male and female CD-I mice (Rogers et al., 1993b). If the decreased
16 brain weight in female rats had been used instead, the RfC would have been approximately 66%
17 higher than the RfC based on the male data. As discussed in Section 5.3.1, while existing
18 developmental and chronic studies suggest that monkeys may be the more sensitive and relevant
19 species, these studies were not chosen for RfC or RfD derivation due to substantial deficiencies
20 in the NEDO (1987) monkey study and uncertainties in the dose-response data reported in the
21 Burbacher et al. (2004b: 1999b) study.
22 Researchers at the University of Toronto (Miller and Wells, 2011; Sweeting et al., 2011)
23 have suggested that developmental studies in rodents may not be suitable for assessing human
24 developmental toxicity. Their hypothesis that mouse studies are not relevant to humans is based
25 on a series of assumptions, as follows:
26 1) mouse embryos have a higher reliance on catalase over ADH to metabolize
27 embryonic methanol,
28 2) catalase has a higher affinity for methanol than reactive oxygen species,
29 3) due to this affinity, embryonic methanol competitively inhibits catalase
30 antioxidant activity,
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1 4) this competitive inhibition results in an increase in embryonic ROS activity, and
2 5) this increased embryonic ROS activity is the primary MOA responsible for the
3 teratogenic effects observed in mice following methanol exposure.
4 The validity of the first of these assumptions is uncertain given the complexity of enzyme
5 kinetics in humans, the limited knowledge of how a human fetus/infant metabolizes methanol,
6 existing evidence that a human fetus/infant can metabolize methanol via a mechanism(s) other
7 than ADH, and the possibility that this alternative mechanism could involve catalase (Tran et al.,
8 2007). The second assumption has greater validity as it is based on published reports of catalase
9 affinity (Km) for methanol (Perkins et al., 1995a: Ward et al., 1995) and hydrogen peroxide
10 (Vetrano et al., 2005). However, there is limited and conflicting evidence on the validity of
11 assumptions 3 and 4 (i.e., that catalase affinity for methanol can lead to an increase in embryonic
12 ROS). In order for assumptions 3 and 4 to be true, catalase affinity for methanol would need to
13 be strong enough to overcome the extremely high reaction rate between catalase and ROS60, and
14 other enzymes (e.g., glutathione and superoxide dismutase) can also protect against ROS. Miller
15 and Wells (2011) point out that methanol radicals have been detected by electron spin resonance
16 spectrometry in methanol intoxicated rats (Skrzydlewska et al., 2000), and methanol derived
17 adducts have been observed in the bile and urine of rats exposed to methanol and a free radical
18 spin trapping agent (Mason and Kadi ska, 2003). However, these observations do not answer the
19 question of whether methanol's impact on catalase activity can cause an overall increase in
20 embryonic ROS, and evidence to the contrary exists for adult organ systems. For instance, no
21 increase in a general indicator of tissue oxidative DNA damage [8-hydroxy-2'-deoxyguanosine
22 (8-oxodG)] was observed in the lungs, livers, bone marrow and spleen of male CD-I mice, DNA
23 repair deficient knockout mice, NZW rabbits and cynomolgus monkeys given a single i.p.
24 injection of 2 g/kg methanol and male CD-I mice injected daily for 15 days with 2 g/kg
25 methanol (McCallum et al., 2011 a: 2011b). With respect to the validity of the fifth assumption, it
26 has been suggested that in vitro studies that report an enhancement of methanol-induced
27 embryopathies in glutathione-depleted rat embryos (Harris et al., 2004) provide support for a
28 ROS-mediated mode of action for methanol developmental toxicity. However, as discussed in
29 Section 4.7.1, the impact of glutathione depletion on the methanol-induced embryopathies has
30 also been attributed to a decreased ability to metabolize formaldehyde (Harris et al., 2004). It has
31 also been suggested that the enhancement of methanol-induced embryopathies in acatalasemic
32 (aCat; low catalase activity) mouse embryos supports a ROS-mediated mode of action (Miller
33 and Wells, 2011). However, in vivo studies from the same laboratory using the same strains of
34 mice as the Miller and Wells (2011) study observed enhanced fetal effects in the hCat mice
60 The interaction rate of catalase with hydrogen peroxide (Kcat) is roughly 40,000,000/second (Garrett and Grisham.
2010).
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1 similar to those observed in mice by Rogers et al. (2004) and no enhancement of fetal effects in
2 aCat mice (Siu et al., 2013). Siu et al. (2013) acknowledge that their in vivo results imply no
3 ROS involvement in the embryopathology of methanol-induced fetal effects in mice. While ROS
4 may yet be determined to play a role in the pathological progression of methanol-induced fetal
5 effects in rodents, available information is not consistent or adequate to conclude this or that the
6 rodent developmental studies are not relevant in the assessment of human developmental toxicity
7 from methanol exposure.
8 Sweeting et al. (2011) have suggested that rabbits would be a more appropriate test
9 species than mice because rabbits may largely metabolize methanol via alcohol dehydrogenase
10 and more accurately reflect primate methanol and formic acid pharmacokinetic profiles. They
11 further state that rabbits are resistant to methanol teratogenicity. A developmental study in rabbits
12 via an appropriate route of exposure would be of interest, particularly if it involved an
13 investigation of effects over a broad set of gestational days. However, more research is needed
14 before it can be stated that a rabbit developmental study would be more relevant to humans than
15 rodent developmental studies and that rabbits are resistant to methanol teratogenicity. The
16 Sweeting et al. (2011) study assumes that the gestational window of susceptibility for
17 developmental effects in rabbits following methanol exposure is at or close to that for mice.
18 While the gestational window of susceptibility for developmental effects in mice is well studied
19 and documented (Degitz et al., 2004a: Degitz et al., 2004b: Rogers et al., 2004; Rogers and
20 Mole, 1997; Dorman and Welsch, 1996; Fuetal., 1996; Dorman etal., 1995; Andrews et al.,
21 1993; Bolonet al., 1993; Rogers et al., 1993a: Rogers etal., 1993b), no studies have been done
22 to identify the gestational window of susceptibility for methanol exposures in rabbits. As mouse
23 studies have shown, missing the true gestational window of susceptibility for a species/strain can
24 make a marked difference in the developmental effects observed (Rogers and Mole, 1997; Bolon
25 etal.. 1993).
5.3.6. Relationship of the RfC and RfD to Background Levels of Methanol in
Blood
26 The available data on methanol blood levels (small numbers of studies and individuals,
27 differing results by study) do not support a precise estimate of a population distribution of blood
28 methanol levels. However, for the purpose of examining the relationship of the RfC and RfD to a
29 representative sample background of methanol blood levels, EPA has derived a sample
30 lognormal distribution that is consistent with data from relevant study groups in Table 3-1. The
31 arithmetic means and standard deviations reported in Table 3-1 across six study groups that did
32 not involve substantial dietary restrictions other than alcohol, Batterman and Franzblau (1997),
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1 Batterman et al. (1998). Lee et al. (1992). Sarkola and Eriksson (2001). Turner et al.(2006) and
2 Woo et al. (2005), were converted to log geometric means (|i) and log geometric standard
3 deviation (o) using the formulas given by Johnson and Kotz (Johnson and Kotz, 1970). Then
4 simulated methanol values derived for the studies were used to fit an overall lognormal
5 distribution.61 The mean and SD for this sample background distribution are 1.36 mg/L and 0.77
6 mg/L. The UK Food Standards Agency estimates that endogenous methanol production ranges
7 from 300 to 600 mg/day (Lindinger et al., 1997) (4.3 to 8.6 mg/kg-day) and that diet can
8 contribute up to an additional 1,000 mg/day (14.3 mg/kg-day), principally from fruits and
9 vegetables (COT, 2011). Thus the upper bound of the combined endogenous and dietary
10 exposures estimated in the UK is 23 mg/kg-day. The methanol blood level predicted by EPA's
11 PBPK model for this 23 mg/kg-day maximum exposure rate is 2.5[4] mg/L, which is slightly
12 below EPA's sample background distribution mean + 2xSD of 2.9 mg/L. A small percentage
13 (-7%) of the EPA sample background population is predicted to have methanol blood levels
14 above 2.5 mg/L.
15 Figure 5-3 illustrates the shift in EPA's sample background methanol blood level
16 distribution that would be associated with exposing every individual to methanol at the RfC or
17 the RfD. This analysis assumes that a RfC or RfD exposure would increase each individual's
18 methanol blood level by the same amount.62 According to this analysis, the RfC and RfD
19 exposures would result in approximately 85% and 94% increases, respectively, in the number of
20 individuals with peak methanol blood levels at or above 2.5 mg/L. These estimates are not
21 precise and do not account for interindvidual variability. However, they illustrate that the
22 increase in individuals with higher than 2.5 mg/L methanol blood levels (i.e., higher than the
23 upper range of background methanol blood levels associated with a diet that includes fruits and
24 vegetables) following a RfD or RfC exposure would not be negligible.
61Studies were weighted according to the extent to which they represent the U.S. population. The Sarkola and
Eriksson (2001) restricted alcohol consumption for one week prior to blood testing and was therefore given a weight
of 0.48, commensurate with the percentage of US population that are not regular drinkers (CDC. 2011). Woo et al.
(2005) studied Korean subjects, a unique population prone to having more than one variant of the gene coding for
alcohol dehydrogenase, which causes them to metabolize alcohol at a much higher efficiency than other gene
variants (EngetaL 2007). and was therefore given a weight of 0.036, commensurate with the Asian fraction of the
US population (SSDAN CensusScope. 2010). The other four studies were assigned a weight of one. Using these
weights and assuming that the distribution of each individual study and the overall distribution are both
log-normally distributed, the following simulation was performed: (1) studies were picked at random according to
the weights assigned to form a new combination of six studies; (2) methanol blood levels were randomly generated
from the lognormal distribution characterized by the \i and o estimated for each of the six randomly picked studies;
(3) the n and o for the overall lognormal distribution associated with these blood values were estimated by the
maximum likelihood estimation method; (4) the steps (1) to (3) were repeated 2,000 times and the mean of the 2,000
H and o estimates were used as the final parameters of the overall lognormal distribution.
62 In actuality this quantity will have relevant variability due to interindividual differences. However, we do not have
PK results to predict variability for blood levels for methanol exposures at the RfC/D. If the model predictions are
central estimates of blood levels from exposures, then adding in population variability can be expected to lead to
higher upper percentile estimates for the blood methanol levels in the environmentally exposed population.
July 2013 5-39 Draft - Do Not Cite or Quote
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1 EPAs PBPK model predicts that a continuous daily methanol inhalation exposure
2 equivalent to the RfC would raise the methanol blood level of an individual with a high end
3 normal background methanol blood level of 2.5 mg/L by 0.43 mg/L. The model also predicts that
4 a daily oral exposure to methanol at the RfD (distributed as six bolus doses) would raise this
5 potentially susceptible individual's methanol blood level by a daily peak value of 0.46 mg/L and
6 by a daily average of approximately 0.19 mg/L. Section 5.3.7 discusses the relationship of these
7 increases to levels that have been reported in monkey studies to be associated with effects of
8 uncertain, but potential adversity.
9
Sample Background Blood Level Distribution
. Sample Background + Peak RfD
S:. Sample Background + RfC
\,
V
\.
\.
vRfD/C i
Ij
1;
1:
1:
I!
Estimated high end of
uncontaminated
background blood levels
r
«^=?\,
X \.
\^v
0.5
1.5 2 2.5 3 3.5 4
mg Methanol/Liter Blood (mg/L)
4.5
5.5
*For the exposure regimen assumed (Section B.2.7), daily increases for an RfD vary between O.Of and 0.44 mg/L (Appendix B,
Figure B-f 7).
Figure 5-3 Projected impact of daily peak RfD and RfC exposures on sample background
methanol blood levels (mg MeOH/Liter [mg/L] blood) in humans.
10
11
5.3.7. Relationship of the RfC and RfD to Methanol Blood Levels In Monkeys
Associated with Unquantifiable Effects of Uncertain Adversity
As discussed in Section 5.1.3.2.3, EPA believes that the existing methanol database
provides an incomplete characterization of methanol's potential to cause reproductive effects,
July 2013
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1 developmental neurotoxicity, and chronic neurotoxicity. NTP-CERHR (2003) reported "minimal
2 concern" that up to 10 mg/L of methanol in blood would result in reproductive or developmental
3 toxicity in humans. However, based on an evaluation of the methanol blood levels corresponding
4 to effects observed in the Burbacher et al. (2004b; 1999b) reproductive and developmental
5 monkey study using the EPA monkey PK model, EPA believes there may be some uncertainty
6 associated with the NTP-CERHR (2003) conclusion. Further, the NTP-CERHR (2003) report
7 focused on the reproductive and developmental effects of methanol, and did not assess the
8 potential for effects from chronic exposure.
9 In the Burbacher et al. (2004b; 1999b) study, statistically significant shortened pregnancy
10 duration was observed in monkeys exposed to 200 ppm methanol, and statistically significant
11 VDR delay was observed in male monkey infants exposed to 600 ppm methanol for 2 hours
12 per day (see Section 4.3.2). EPA estimates that these two exposures resulted in peak methanol
13 blood levels in these monkeys of approximately 5 and 12 mg/L, respectively (including a
14 background level of 2 mg/L; see Appendix D, Table D-10). Also, NEDO (1987) observed
15 potential signs of CNS effects (minimal fibrosis of "responsive stellate cells" of the brain, likely
16 astrocytes) in histopathology in monkeys exposed chronically to 100 ppm for 21 hours per day
17 (see Section 4.4.2), which is estimated by EPA's monkey PK model to be associated with an
18 increase in methanol blood levels over background levels of approximately 1 mg/L,
19 corresponding to total methanol blood levels of roughly 3 mg/L (assuming a background in these
20 monkeys of 2 mg/L; see Appendix B, Table B-8). The significance of this stellate cell/astrocyte
21 response is uncertain at this time. However, the slight neurological effects (Chuwers et al., 1995)
22 and increased subclinical biomarkers for inflammation (Mann et al., 2002) in humans acutely
23 exposed to 200 ppm (262 mg/m3) methanol were associated with just over twice this methanol
24 blood level, 6.5 mg/L. Further, stellate astroglia are believed to play a key role in the
25 pathogenesis of CNS disorders and in response to tissue injury and inflammation. Thus, with
26 further research this endpoint could prove to be an important CNS effects associated with
27 methanol exposure.
28 As discussed in Sections 4.3.2 and 4.4.2, EPA could not derive a NOAEL or LOAEL
29 from the studies which reported these reproductive and neurotoxicity endpoints. However, as
30 discussed in Section 5.1.3.2.3, these effects were important considerations with respect to the
31 determination of the database uncertainty factors. Figure 5-4 illustrates how methanol blood
32 level distributions for RfD and RfC exposures to the EPA sample background distribution
33 compares with the blood levels that have been associated with these uncertain, but potentially
34 adverse effects in monkeys. As discussed in the previous section, a RfC or RfD exposure is
35 expected to raise the methanol blood level of an individual with a high end normal background
July 2013 5-41 Draft - Do Not Cite or Quote
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1 methanol blood level of 2.5 mg/L to just under 3 mg/L, the lowest methanol blood level that has
2 been associated with these uncertain, but potentially adverse effects.
Sample Background Blood Level Distribution
Sample Background + Peak RfD
Sample Background + RfC
Estimated high end of
uncontaminated
background blood levels
NEDO(1987)
Chronic monkey study; 100 ppm;
21 hrs/day; Minimal fibrosis of
"responsive stellate cells;"
astrocytes (ERG 2009)
V
•s..
-x.
V.
Burbacher et al. (2004)
Pregnant monkeys;
200 ppm; 2 hrs/day;
Shortened pregnancy
duration
0.5
1.5
2 2.5 3 3.5 4
mg Methanol/Liter Blood (mg/L)
4.5
5.5
Figure 5-4 Relationship of monkey blood levels associated with effects of uncertain
adversity with projected impact of daily peak RfC and RfD exposures on
sample background methanol blood levels (mg MeOH/Liter [mg/L] blood) in
humans.
5.4. Cancer Assessment
3 A cancer assessment was not conducted for this document. However, the Agency is
4 currently reviewing the literature on methanol carcinogenicity and will develop a cancer
5 assessment for methanol at a later date.
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