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UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON D.C. 20460
OFFICE OF THE ADMINISTRATOR
SCIENCE ADVISORY
BOARD
READER NOTE:
The Background Materials for the Arsenic Review Panel's meetings on the draft arsenic
report consist of four documents. The documents are:
1. December 27, 2005 Draft Report - this is the "clean" draft report for ARP
discussion and editing. It reflects edits made to the first draft that was circulated to
members for comment on November 10, 2005.
2. December 27, 2005 Draft Report with Comments - this is the draft report (1
above) which embeds member questions and comments on that draft. This
document was circulated to members for information and additional comment/edits
on December 27, 2005.
3. Embedded Comment Summary - This is a summarization of the comments
embedded in the December 27, 2005 Draft Report With Comments (2 above).
4. Compilation of ARP Member Comments on the December 27, 2005 Draft
Report With Comments - this is a compilation of member comments received on
the Dec 27 2005 Draft report With Comments (2" above). These comments are not
contained in 1, 2, or 3 above.
THIS DOCUMENT IS NUMBER 2 IN THE ABOVE LIST
[Date]
EPA-SAB-ADV-06-xxx
The Honorable Stephen L. Johnson
Administrator
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, N.W.
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draft report does not represent EPA policy. December 27, 2005
Washington, D.C. 20460
Subject: Advisory on EPA's Assessments of Carcinogenic Effects of Organic
and Inorganic Arsenic: An Advisory Report of the US EPA Science Advisory
Board
Dear Administrator Johnson:
[First paragraph identifies client office and nature of advisory question],
[Next paragraph describes issues deserving the Administrator's attention and
SAB's advice as to actions, if any, that need to be taken by the Administrator]
[Middle paragraphs describe summary ("bottom line") advice in lay terms],
[Final paragraph offers future help and identifies follow-up activities SAB would
like to have with client office].
Sincerely,
/signed/ /signed/
Dr. M. Granger Morgan, Chair Dr. XXXX, Chair
EPA Science Advisory Board XXX Committee
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NOTICE
This report has been written as part of the activities of the EPA [Science Advisory
Board/Clean Air Scientific Advisory Committee/ Advisory Council on Clean Air
Compliance Analysis], a public advisory committee providing extramural scientific information
and advice to the Administrator and other officials of the Environmental Protection Agency. The
[Board/CASAC/Council] is structured to provide balanced, expert assessment of scientific
matters related to problems facing the Agency. This report has not been reviewed for approval
by the Agency and, hence, the contents of this report do not necessarily represent the views and
policies of the Environmental Protection Agency, nor of other agencies in the Executive Branch
of the Federal government, nor does mention of trade names or commercial products constitute a
recommendation for use. Reports of the EPA [Science Advisory Board/Clean Air Scientific
Advisory Committee/ Advisory Council on Clean Air Compliance Analysis] are posted on
the EPA Web site at: http://www.epa.gov/sab.
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U.S. Environmental Protection Agency
Science Advisory Board
Arsenic Review Panel
CHAIR
Dr. Genevieve Matanoski, Professor, Department of Epidemiology, Johns Hopkins University,
Baltimore, MD
MEMBERS
Dr. H. Vasken Aposhian, Professor, Department of Cell and Molecular Biology , The
University of Arizona, Tucson, AZ
Dr. Aaron Barchowsky, Associate Professor, Department of Environmental and Occupational
Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
Dr. David Brusick, Retired, Convance Labs, Vienna, VA
Dr. Kenneth P. Cantor, Senior Investigator, Occupational and Environmental Epidemiology
Branch, Division of Cancer and Epidemiology and Genetics, National Cancer Institute,
Bethesda, MD
Dr. John (Jack) Colford, Associate Professor, Division of Public Health, Biology &
Epidemiology, School of Public Health, University of California, Berkeley, CA
Dr. Yvonne P. Dragan, Director of the Division of Systems Toxicology (DST) and Chief of the
Center for Hepatotoxicology, National Center for Toxicological Research (NCTR), Food and
Drug Administration's (FDA), Jefferson, AR
Dr. Sidney Green, Associate Professor, Department of Pharmacology, College of Medicine,
Howard University, Washington, DC
Dr. Sioban Harlow, Professor, Department of Epidemiology, School of Public Health,
University of Michigan, Ann Arbor, MI
Dr. Steven Heeringa, Research Scientist and Director, Statistical Design Group, Institute for
Social Research (ISR), University of Michigan , Ann Arbor, MI
Dr. Claudia Marie Hopenhayn, Associate Professor, Department of Epidemiology,
Markey Cancer Control Program, College of Public Health, University of Kentucky, Lexington,
KY
it
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Dr. James E. Klaunig, Professor and Director, Department of Pharmacology and Toxicology,
School of Medicine , Indiana University , Indianapolis, IN
Dr. X. Chris Le, Professor, Department, of Public Health Sciences, Department of Chemistry &
Department of Laboratory Medicine & Pathology, University of Alberta, Edmonton, Alberta,
Canada
Dr. Michele Medinsky, Toxicology Consultant, Toxcon, Durham, NC
Dr. Kenneth Portier, Associate Professor. Institute of Food and Agricultural Sciences.
University of Florida. Gainsville, FL
Dr. Barry Rosen, Professor and Chairman, Department of Biochemistry and Molecular Biology,
School of Medicine, Wayne State University, Detroit, MI
Dr. Toby Rossman, Professor, Environmental Medicine, School of Medicine, New York
University, Tuxedo, NY
Dr. Miroslav Styblo, Research Associate Professor, Department of Nutrition, University of
North Carolina , Chapel Hill, NC
Dr. Justin Teeguarden, Senior Scientist, Pacific Northwest National Laboratory, Richland, WA
Dr. Michael Waalkes, Chief, Inorganic Carcinogenesis Section, Laboratory of Comparative
Carcinogenesis, National Cancer Institute, National Institute of Environmental Health Science,
RTP, NC
Dr. Janice Yager, Scientific Program Manager-Senior Research Manager, Electric Power
Research Institute, Palo Alto , CA
SCIENCE ADVISORY BOARD STAFF
Mr. Thomas Miller, Designated Federal Officer, EPA Science Advisory Board Staff Office
(1400F), 1200 Pennsylvania Avenue, NW, Washington, DC, 20460, Phone: 202-343-9982.
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U.S. Environmental Protection Agency
Science Advisory Board
CHAIR
Dr. [To be Determined], Affiliation, City, State
MEMBERS
Dr. [To be Determined], Affiliation, City, State
SCIENCE ADVISORY BOARD STAFF
Mr. Thomas Miller, Designated Federal Officer, EPA Science Advisory Board Staff Office
(1400F), 1200 Pennsylvania Avenue, NW, Washington, DC, 20460, Phone: 202-343-9982.
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TABLE OF CONTENTS
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ADVISORY ON EPA'S ASSESSMENTS OF CARCINOGENIC EFFECTS
OF ORGANIC AND INORGANIC ARSENIC: AN ADVISORY REPORT OF
THE US EPA SCIENCE ADVISORY BOARD
1. EXECUTIVE SUMMARY [optional]
[Provide short introductory paragraph, followed by bullets, derived from the text
boxes in each chapter. Organize document by charge question, if appropriate./
Check that the substance and tone of the Executive Summary is consistent with the
Administrator Letter]
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2. INTRODUCTION
2.1. Background
EPA's Office of Research and Development (ORD), in association with the EPA
Office of Water and the EPA Office of Pesticide Programs (USEPA, 2005a), requested
that the EPA Science Advisory Board (SAB) conduct a review of certain components of
its draft assessment of potential human carcinogenicity associated with arsenic, and
arsenic containing compounds. Generally, inorganic arsenic is found naturally in the
environment and it is typically present in soil and water at some determinate level.
Sources of human exposure to inorganic arsenic include drinking water, diet, air and
anthropogenic sources such as wood preservatives and industrial wastes. Additionally,
humans are exposed to organic arsenicals when they are used as pesticides.
Several laws require EPA to consider the human health risks associated with
arsenic and arsenic containing compounds. The Safe Drinking Water Act (SDWA)
directs EPA to establish national standards for arsenic containing compounds, among
other contaminants, in public drinking water supplies. EPA's Superfund and Resource
Conservation and Recovery Act (RCRA) programs evaluate exposure to arsenic
compounds at locations undergoing clean up or remediation. The Clean Air Act, requires
EPA to set air emissions standards for sources of arsenic. EPA's Office of Pesticide
Programs (OPP) evaluates the exposure and health risks associated with arsenicals used
as pesticides in the U.S. Under the mandate of the Food Quality Protection Agency
(FQPA), EPA must reevaluate arsenical, and other, pesticide food tolerances (the legal
limits of pesticides on/in food or animal feed) in the U.S. by August, 2006. Also, several
organic arsenic herbicides are undergoing reregi strati on and/or tolerance reassessment
including cacodylic acid (referred to as dimethylarsinic acid or DMAV), monosodium,
disodium, and calcium salts of methanearsonate acid (MSMA, DSMA, and CAMA,
collectively as referred as MMAV). In 2003, most residential uses of chromated copper
arsenate (CCA) as a wood preservative were cancelled.
Arsenic, and arsenic containing compounds, have been the focus of many EPA
assessments throughout EPA's existence, as the above statutory authorities might
suggest. In addition, the National Research Council of the National Academy of
Sciences has conducted comprehensive health sciences reviews of arsenic on at least two
occasions (NRC, 1999; NRC, 2001). EPA SAB Panels have considered inorganic arsenic
issues (USEPA SAB, 2000; USEPA SAB, 2001).
Since the 2001 NAS review, new information has been developed on the mode of
carcinogenic action, metabolism and toxicokinetics for arsenic and its methylated species,
and new epidemiology studies have been conducted on inorganic arsenic. EPA
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considered this new information in its hazard characterization for tolerance assessment of
DMAV and MMAV (USEPA OPP, 2005 and USEPA ORD, 2005). EPA also developed a
revised hazard and dose response assessment for inorganic Arsenic (USEPA OW, 2005)
which relies on the two NRC reviews and provides an updated human health effects and
dose-response assessment for inorganic arsenic.
In its Charge to the SAB (USEPA, 2005a), EPA asked for advice on the soundness of its
major science conclusions in the above cited documents developed by EPA during 2005. The
focus is on the carcinogenic assessments of DMAV and inorganic arsenic.
2.1.1. Metabolism and Toxic Responses of Arsenic Species
Al. Metabolism and pharmacokinetics: Please comment on how
pharmacokinetic processes are best considered regarding the use of data derived
from direct DMAV exposure versus direct iAs exposure for cancer risk
assessment.
A2. Response to mixtures of metabolites: Given the toxicological response
profiles observed following direct exposures to iAs versus MMAV and DMAV, and
the differences in human and rodent toxicologic responses to arsenicals, please
comment on the use of data derived from rodent exposures to the organic
arsenicals versus use of data derived from direct iAs human exposure, in the
DMAV assessment.
2.1.2. Modes of Carcinogenic Action for DMAV and Inorganic Arsenic
Bl. Mode of action of DMAV: Please comment on the sufficiency of
evidence to establish the animal mode of carcinogenic action for DMAV. Are the
scientific conclusions sound and consistent with the available evidence on DMAV
and the current state of knowledge for chemical carcinogenesis.
Please comment on whether the key events in DMA 's mode of action are
supported by the available data. Specifically comment on the role of: a) reactive
oxygen species in producing chromosomal damage and the strength of the
evidence supporting oxidative damage as a causal key event in DMAV/DMAIU s
mode of carcinogenic action versus an associative event or a secondary
consequence of cytotoxicity; b) cell proliferation and cytotoxicity and the
strength of the evidence as causal key events in DMAV/DMAUI s mode of
carcinogenic action versus associative or secondary events, and c) other
potential modes of action that have substantial scientific support that may be
contributing to the carcinogenicity of DMA.
B2. Human relevance of animal DMAV MOA: Please comment on the
relevance of the postulated key events (see Bl) to tumors in humans.
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Please comment on how, if at all, differences in the human population vs.
experimental animals should be accounted for in the risk assessment for DMAV.
Please comment on the Agency's conclusion that the young are likely to respond
like the adult to the formation of bladder tumors following exposure to DMA.
B3. Modes of carcinogenic action from exposure to inorganic arsenic:
Please comment on the conclusion that the available data support the hypothesis
that multiple modes of action may be operational following exposure to
inorganic arsenic.
2.1.3. Selection of Data for Dose-Response Assessment
CI. Use of animal data for DMAV : Please comment on the use of the
bladder tumor data from the DMAV rat bioassay as the most suitable dataset for
quantifying potential human cancer risk to DMAV, including the weight of
evidence to support this conclusion.
Please comment on whether the iAs epidemiology data can be used to inform the
DMAV dose-response assessment derived from rat data with DMAV. If so, please
discuss how such information might be used. (See Appendix).
C2. Use of human epidemiological data from direct iAs exposure: Does the
SAB agree that the Taiwanese dataset remains the most appropriate choice for
estimating cancer risk in humans? Please discuss the rationale for your
response.
Do these data provide adequate characterization of the impact of childhood
exposure to iAs? Please discuss the rationale for your response.
2.1.4. Approaches to Low-Dose Extrapolation for Inorganic Arsenic and
DMAV
Dl. Mode of carcinogenic action understanding for DMAV™ and implications
for dose response extrapolation to estimate human cancer risk: Please comment
on the scientific evidence and biological rationale in support of nonlinear versus
linear low dose extrapolation approaches, which approach is more consistent with
the available data on DMAV and current concepts of chemical carcinogenesis, and
how scientific uncertainty should most appropriately be incorporated into low-dose
extrapolation.
D2. Implementation of the recommendations of the NRC (2001): Does the panel
concur with the selection of a linear model following the recommendations of the
NRC (2001) to estimate cancer risk at this time? Please discuss your response in
light of the highly complex mode of action for iAs with its metabolites.
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D3. EPA re-implemented the model presented in the NRC (2001) in the
language R as well as in an Excel spreadsheet format. In addition, extensive
testing of the resulting code was conducted. Please comment upon precision and
accuracy of the re-implementation of the model.
D4. Available literature describing drinking water consumption rates for the
southwestern Taiwanese study population: What drinking water value does the
panel recommend for use in deriving the cancer slope factor for inorganic arsenic?
D5. Selection of an estimate of dietary intake of arsenic from food: What
background dietary intake (of arsenic) value does the panel recommend for both the
control population and study population of Southwestern Taiwan used in deriving the
cancer slope factor for inorganic arsenic?
2.2. Process for Developing this Report and the Structure of this Report
This advisory was conducted by a Science Advisory Board Ad Hoc Panel
composed of members of the chartered SAB and its committees, members of the FIRRA
Scientific Advisory Panel, and invited outside experts. A Federal Register notice on
February 23, 2005 requested nominations of candidates for membership on the Arsenic
Review Panel (see GPO, 2005a). Panel Members were selected following procedures for
panel formation at the EPA Science Advisory Board (USEPA SAB 2005a). The Arsenic
Review Panel held a public telephone conference meeting to plan for the review on
August 11, 2005 (see GPO 2005b). The Panel' review meeting was held on September
12-13, 2005 and concluded with the articulation of a series of recommendations in
response to each of the EPA Charge questions. These recommendations became the core
of this report. The Arsenic Review Panel held its final discussions of the report during a
telephone conference meeting on January 24, 2006 (GPO, 2005c; GPO, 2005d). The
chartered Science Advisory Board reviewed and approved the report in a meeting on
To Be Added
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3. RESPONSE TO THE CHARGE
3.1. Overview
The SAB Arsenic Review Panel is being asked to comment on several key
science issues concerning the i) toxicity/metabolic profile/bioavailability for different
arsenic species, ii) the Agency's understanding of the mode of action of arsenic
carcinogenesis and implications of that on dose response extrapolation for DMAV and
inorganic arsenic, and iii) the implications of newer epidemiology and the 2001 National
Research Council recommendations on modeling the human cancer slope factor for
inorganic arsenic.
{TR}(Dr. Rossman points out the need to scrub the document for "arsenic-
compound" naming conventions and settle on a consistent name for the same
compound throughout.}
3.2. Metabolism and Toxic Responses of Arsenic Species
3.2.1. Metabolism and pharmacokinetics
"Evidence from in vivo and in vitro metabolism and pharmacokinetic studies with
humans and laboratory animals suggests that the efficiency of the methylation
reaction(s) and cellular uptake varies based on which arsenical compound is
administered exogenously. Most available studies suggest that the metabolic
process in most mammals is primarily a one-way process and that following direct
exposure to DMAV significant amounts of iAs111, iAsv, MMAm, or MMAV at the
target tissue are not expected" (USEPA, 2005a).
Please comment on how pharmacokinetic processes are best considered
regarding the use of data derivedfrom direct DMA1 exposure versus
direct iAs exposure for cancer risk assessment.
Al. Metabolism and pharmacokinetics: Charge questions A1 and A2 address
exposure to and metabolic fate of DMAV from associated with organoarsenic-containing
herbicides. However, DMAV from these herbicides can be degraded by microorganisms,
both in the environment and in the intestinal tract, to yield a variety of methylated and
inorganic arsenic (As) species, which have specific metabolic fates and toxicities, ft
should be noted that the p The Panel's responses to questions Al and A2 do not take
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into consideration potential byproducts of the microbial degradation of DMAV in the
environment. This reflects statements from EPA representatives in the September, 2005
Panel meeting that the environmental conversion of DMAV from organoarsenic
pesticides and the risk associated with exposures to these conversion products will be
addressed by EPA in an independent document.)
{SG}(Once we say that we have not taken into consideration potential byproducts
of microbial degradation, should we not state why? It seems to beg the question.)
{MS}(The change in the preceding sentence reflects the comment from SG).
{BR}(Dr. Rosen suggests several articles that are relevant to the introductory
statement from the "Bugs and Drugs" perspective. What should we do in that
regard? See item 4 in this subsection for more.)
{MS} (Responded on 11-04-2005.. .not aware of any paper addressing metabolism
of dimethylarsine by E coli or by gut microflora. Also, I do not think that arsenic
in any form causes intestinal cancer(??). The article you sent us may be referring
to two papers by Endo's lab that found an unidentified cytotoxic metabolite in
urine and feces of rats exposed to DMAV. The same compound was found to be a
product of the metabolism of DMAV by E coli in presence of cysteine in an in
vitro experiment. It is possible that this metabolite is DMAIII alone or in complex
with cysteine.)
{JT}(Since the charge question is directed towards administered As, it is OK to
ignore environmental metabolism, but if intestinal metabolism is to be ignored,
some explanation regarding why it is not an important consideration for oral
studies should be provided.)
The panel agrees with the Agency's reasoning behind this question. In
mammalian (including human) tissues/cells, the metabolism of inorganic arsenic (iAs)
appears to be a one-way process in which iAs is converted to monomethyl-As (MMA),
dimethyl-As (DMA), and in some species to trimethyl-As (TMA TMA111,
trimethylarsine){TR}metabolites containing As in +3 or +5 oxidation states (Vahter,
1999; Thomas, et al., 2001). There is no evidence for demethylation of methylated As
species in either animal or human tissues. While the step-wise addition of methyl groups
is likely a one-way process, a cycling between +3 and +5 As species may occur at each of
the methylation steps due to a spontaneous oxidation of +3 species (Gong, et al., 2001;
Aposhian, et al., 2003) and non-enzymatic (Delnomdedieu, et al., 1994; Scott et al.,
1993) or enzymatic (Zakharyn and Aposhian, 1999; Radabaugh and Aposhian, 2000;
Waters et al., 2004) reduction of +5 species. Given the one-way character of As
methylation, we do not expect to find significant amounts of MMA or iAs as products of
DMAV metabolism in either rat or human tissues or urine.
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In contrast, exposure to iAs may result in the production, tissue retention, and
urinary excretion of all the above iAs and methylated As species. Both the uptake and
reduction of DMAV to DMA111 are apparently critical steps in the activation of exogenous
DMAV It is not clear, where and to what extent (if at all) these processes occur in
humans exposed to DMAV, although it appears that uptake may be the rate limiting for
further metabolism of DMAV {SHa} However, DMA111 is a major urinary metabolite in
individuals chronically exposed to iAs (Lo ot al., 2000; Valenzuela, et al., 2005),
{XCL}(Remove - Le et al 2000 showed the presence of DMAIII as a urinary
metabolite in individuals chronically exposed to iAs, but it did not show that it is
a "major" urinary metabolite. Therefore, I suggest removing this reference from
this context.}
indicating that the capacity to reduce DMAV to DMA111 exists in human tissues.
However, It should bo pointed out that even the conversion of a small amount/fraction of
exogenous DMAV to DMA111 is of toxicological significance due to the significant
toxicity of DMA111. Thus, strictly from the point of view of the metabolic pattern, data
derived from DMAV exposure (in the rat), not from iAs exposure, {CH}is better suited
should bo used for cancer risk assessment of DMAV However, thoro is uncertainty
associated with this approach is uncertain because of specific due to the following
metabolic differences, and other factors {CH}, that arc discussed in the following:
1. The uptake pathway or pathways for DMAV is/are unidentified. The expression
or properties of DMAV transporters may differ in rats and humans, leading to
differences in uptake of DMAV in tissues and organs.
2. Results of laboratory and epidemiological studies suggest that the pattern for
DMAV metabolism in rats is different from that in humans: Rat metabolize
DMAV to DMA111, trimethylarsine oxide (TMAvO) (Yoshida et al., 1997; Yoshida
et al., 1998; Cohen et al., 2002), and possibly, trimethylarsine (TMA111) (Waters et
al., 2004).
{BR}(Since TMAIII is volatile, it might be produced but expired through
the lungs rather than excreted in urine. I am not suggesting that this occurs
but just want to point out that absence of evidence is not evidence of
absence. The absence of TMAOV (and by association TMAIII) in human
urine is not evidence that they are not produced, and we should be
cautious about how we interpret negative data.}
DMAV, DMA111, and TMAvO are major urinary metabolites of DMAV in the rat.
In addition, TMAvO was also detected in urine of rats chronically exposed to iAs
(Yoshida et al., 1998). In contrast, little or no TMAvO was found in human urine
after a single dose of DMAV (Marafante et al, 1987; Buchet et al., 1981) or after
acute (Mahieu, et al., 1981; Apostoli et al., 1997; Benramdane et al., 1999) or
chronic exposures to iAs (Vahter, 1999; Thomas et al., 2001). These data suggest
that the capacity to produce TMAvO from iAs or DMAV or to excrete TMAvO in
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urine is limited in humans as compared to rats. Thus, while it is possible that the
urinary TMAV/In metabolites significantly affect the overall toxic or cancerous
outcomes in the bladder of rats exposed to DMAV, the relative lack of these
metabolites in human urine would suggest that the outcome in humans would not
be as severe as in rats.
3. Accumulation of DMA111 in rat erythrocytes (due to a high-affinity binding to
hemoglobin (Lu et al., 2004) contributes to a specific kinetic pattern for DMAV in
rats. It is not clear how and to what extent this factor affects the yield and
concentration of the active As species (e.g., DMA111, TMAvO, or TMAs111) in
urine or in target tissues of rats and how lower accumulation in human
erythrocytes would alter the kinetic pattern for DMAV and toxic/cancerous
outcomes of DMAV exposure in humans.
4. Microorganisms, including intestinal bacteria, have a capacity to either methylate
or demethylate arsenicals (Hall et al., 1997; Cullen et al., 1984; Cullen et al, 1989;
Lehr et al., 2003; Bently and chasten, 2002; Tamaki and Frankenberger, 1992;
Mukhopadhyay et al, 2002; Ridley et al., 1977). Although the pattern and extent
of DMAV metabolism by human intestinal microflora are not known, it is possible
that oral exposure to DMAV results in the absorption of a wide spectrum of As
metabolites produced by bacteria in the gastrointestinal tract of exposed
individuals. In contrast, bacterial metabolism would not affect the absorption of
DMAV after inhalation or dermal exposures. Thus, As species found in tissues
may differ with different routes of exposure. Interspecies differences in
endogenous intestinal bacteria may further complicate extrapolation from rats to
humans.
5. Additional factors may affect the metabolic profiles for DMAV in humans,
including co-exposures to other environmental contaminants, deficiencies of
specific nutrients (e.g., selenium) or malnutrition (poor nutrition) has been shown
to induce expression of aquaglyceroporin-9 (AQP9), an iAsin/MMAin transporter
(Liu et al., 2002; Liu et al., 2004; Liu et al., submitted), {BR} 60 20-fold (Carbrey
et al., 2003).
All the above concerns should be considered in the risk assessment of DMAV
exposure.
In their briefing documents the agency presented information on a physiologically
based pharmacokinetic (PBPK) model for As disposition and metabolism that is under
development. PBPK modeling might be a useful approach for integrating tissue and
excreta concentrations of As metabolites resulting from exposure to the various forms of
As, including DMAV, in laboratory animals and humans.
{JT} Some comment could be added in the paragraph above noting that the
experimental work conducted to support PBPK model development is an
investment in developing an understanding of the biochemical and other processes
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that influence As kinetics. That is, the work is not done for the sake of developing
a PBPK model, it is done to develop the understanding of the system we need to
understand the pharmacokinetic basis for risks across species whether or not we
use a PBPK model for dosimetry.)
At the present time the modeling work described by the agency is in the development
stages and is not considered sufficiently robust to conduct interspecies extrapolations.
However, the Panel agency is strongly encourages the Agency to proceed with PBPK
model development, including laboratory studies to obtain the kinetic constants needed to
describe rates of uptake, efflux, metabolism, and elimination of DMAV in both rats and
humans. When sufficiently validated, this model could simulate concentrations of active
(toxic or carcinogenic) metabolites in urine and bladder tissue following exposure to
DMAV This approach could be used for dose response analysis in cancer risk
assessment. Such models must be validated for predicting tissue concentrations of active
species regardless of the source of arsenic exposure.
{JT}(The last sentence should be modified to express the idea that the PBPK
model need not describe kinetics following exposure to As by any route, only
those routes necessary for interpreting animal studies (oral probably, dermal
maybe) and for human risk assessment (oral, maybe dermal).
3.2.2. Response to mixtures of metabolites
"Tumorigenic profiles vary based on which arsenical compound is
administered exogenously. In vivo and in vitro studies indicate that each of the
arsenical compounds exhibit similarities and differences in their profiles of
biological activities. Direct exposure to iAs111 or iAs v is expected to result in
more of a mixture of toxic metabolites than for direct exposure to DMAV; the
mixture of metabolites is expected to vary based on which chemical is
administered exogenously. The potential mixture of metabolites following direct
exposure to DMAV appears less complex as compared to iAs" (USEPA, 2005a).
Given the toxicological response profiles observed following direct
exposures to iAs versus MMAV and DMA1, and the differences in human
and rodent toxicologic responses to arsenicals, please comment on the use
of data derivedfrom rodent exposures to the organic arsenicals versus use
of data derivedfrom direct iAs human exposure, in the DMA1 assessment.
A2. Response to mixtures of metabolites: The answer to this charge question is
essentially linked to the answer to the charge question in section 3.2.1 above A-k The
metabolism of iAs yields a wide spectrum of metabolites some of which (iAsIII/v,
MMAIII/V) are apparently not produced during the metabolism of exogenous DMAV The
production of iAs and MMA metabolites may be associated with specific toxic or
cancerous endpoints that are absent in DMAV exposure in rats or humans unless there is a
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significant co-exposure to iAs from drinking water, food or the environment. Therefore,
data derived from human exposures to iAs are not suitable for DMAV risk assessment. It
should be noted that there are no published data on toxicological responses to DMAV in
humans. The toxic and carcinogenic effects of DMAV have been examined only in
rodents, mainly in rats. Thus, because there is no available alternative, this panel has no
choice, but to recommend that the data derived from rodent exposures to DMAV be used
for the risk assessment in DMAV exposure in humans.
{GMa} (The wording in the bold type has undertones that are difficult to
interpret. Are you objecting to the policy or what? Better wording might be:
"Because there are no available data derived from human exposure to DMAV, this
panel recommends that the data derived from rodent exposures be used for the
risk assessment of DMAV exposures in humans")
{SG}(In the next draft, I would suggest we delete the phrase, "this panel has no
choice". To me it seems an inappropriate phrase to use in a document of this
type.)
{TR}(This paragraph is difficult to understand because of the abbreviations used).
{MS} The phrase captures the deliberations which did not suggest in any way that
using rodent data is a good choice for evaluation of DMAV metabolism and
carcinogenesis in humans. It is the only choice we had. Perhaps others can
suggest more appropriate wording without loosing this perspective.)
{JT} I would urge the authors to add a paragraph assessing how sufficient the
data is. It is not very satisfying to end with a statement, as it now stands, that
there is no alternative to using the data. It will be important to convey how
good/bad we feel that approach is based on the sufficiency of the data.
However, a significant degree of uncertainty is associated with this approach due
to the metabolic differences between rats and humans and due to other factors, including
those listed in the response to the charge question in section 3.2.1 above A-k The
differences in the production and urinary excretion of TMAIII/V species that could affect
the toxic and cancerous outcomes of DMAV exposure are of a particular concern to this
panel. TMAvO is a hepatocarcinogen in rats (Shen et al., 2003). TMA111 is apparently
more potent than DMA111 in damaging {DB} purified DNA in in vitro systems (Andrews,
et al., 2003). On the other hand, both TMAvO and TMAs111 are less acutely toxic or
cytotoxic than DMA111 (Yamauchi et al., 1990; Cullen, 2005; Sakurai et al., 1998; Oochi
et al., 1994). The contribution of these two metabolites to cytotoxicity and
carcinogenesis in the urinary bladder of rats exposed to DMAV remains unclear. This
uncertainty should be properly addressed by the risk assessment analysis for DMAV
exposure in humans.
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{JT}(The authors make it clear that there are some important metabolism/kinetics
issues that are poorly understood and advise that the uncertainty is addressed in
the risk assessment. This is not easy to do and so I would urge the authors to
advise that the research be conducted to understand the processes. Only this will
eventually reduce or allow uncertainty to be addressed. The bar certainly is lower
than the unequivocally implicated...)
3.3. Modes of Carcinogenic Action for DMAV and Inorganic Arsenic
3.3.1. Mode of Action of DMAV:
"When relying on laboratory animal data, two critical assumptions are made: (i)
data on animal tumors are predictive of human cancer, and (ii) animal tumor
effects found at high experimental doses predict human risk at lower exposures.
An understanding of a chemical mode of carcinogenic action can help inform the
above assumptions. In the case of DMAV, mode of action (MOA) data are
available and were evaluated using the framework described in EPA's cancer
guidelines" (USEPA, 2005a).
Please comment on the sufficiency of evidence to establish the animal
mode of carcinogenic action for DMA1. Are the scientific conclusions
sound and consistent with the available evidence on DMA1 and the current
state of knowledge for chemical carcinogenesis.
Please comment on whether the key events in DMA's mode of action are
supported by the available data. Specifically comment on the role of: a)
reactive oxygen species in producing chromosomal damage and the
strength of the evidence supporting oxidative damage as a causal key
event in DMA1 DMA111 s mode of carcinogenic action versus an
associative event or a secondary consequence of cytotoxicity; b) cell
proliferation and cytotoxicity and the strength of the evidence as causal
key events in DMA1 DMA111 s mode of carcinogenic action versus
associative or secondary events, and c) other potential modes of action
that have substantial scientific support that may be contributing to the
carcinogenicity of DMA.
Bl. Mode of action of DMAV: The committee felt that there is adequate data to
support an MOA for bladder carcinogenesis induced by high doses of DMAV in the rat
that involves cytotoxicity to the bladder epithelium and increased, sustained regenerative
proliferation as key events. The urine of DMAv-treated rats contains DMA111 at levels
that cause necrotic cytotoxicity in vitro, so it is reasonable to postulate that DMA111 might
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mediate the necrotic cytotoxicity in the rat bladder. However, the rat (unlike the human)
metabolizes a significant fraction of exogenous DMAV to trimethylarsine oxide
(TMAvO) (Cohen et al., 2002; Yoshida et al., 1997, 1998) and possibly to trimethylarsine
(TMAs111) (Waters et al., 2004). Thus, these compounds cannot be excluded as additional
mediators of the necrotic cytotoxicity in bladder of rats exposed to DMAV
The committee {SHa} thought felt that there is insufficient data to invoke reactive
oxygen species (ROS)-induced DNA damage as a key event in the carcinogenic process
associated with exposures to DMAV or DMA111, although contributions from that
mechanism cannot be ruled out. Cytotoxic concentrations of DMA111 have been shown to
induce DNA damage in vitro and in intact cells (Mass et al., 2001), possibly via an ROS-
mediated mechanism (Yamanaka et al., 2003; Kitchin and Ahmad, 2003). However, this
mechanism has not been unequivocally implicated as a causative factor in bladder
cancers induced in rats by DMAV exposure. {JT}(This is a new topic and should start
another paragraph). Permanent genetic change is necessary for carcinogenesis, and it is
unlikely that increased proliferation alone in the absence of increased genomic instability
(increased mutation rate, aneuploidy, amplification, methylation changes, etc.) will result
in the 3 or more changes needed to transform a normal cell to a tumor cell. {CH} fe
addition, Chronic induction of cell proliferation, such as that seen with chloroform-
induced compensatory hyperplasia in the liver, is thought to induce genetic instability.
{JT}(The involvement of ROS in the mode of action is very important to how the
risk assessment is to be conducted. It will be heavily scrutinized. As such it is
important that the authors do more than(?) say that there is not enough evidence to
invoke ROS. We need to state what our criteria for enough evidence would be and
why the experimental data to date do not meet the criteria. Our analysis must be
more clear than it is now.)
{JT}(I encourage the authors to outline the MOA in more detail, as done in D1
either by cross referencing to D1 or taking it from D1 (we then would remove it).
We need to make sure that the MOA in D1 and B3 are in full agreement.)
{JT}( Understand that if the authors do not believe that increased cell proliferation
is not enough for carcinogenesis, they are arguing for the role of some other
processes, one involving gene tox, that will be low dose linear. The last line here,
that chloroform induced cytotoxicity and compensatory hyperplasia induces genetic
instability contradicts the first statement that more than cell proliferation is needed
for carcinogenesis.
Other sources
{JT} (Understand that the "other" sources of DNA damage you propose, at least as
written here, are as speculative as ROS is as a means of DNA damage. Again,
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dismissing ORS and eplacing it with speculations about what else could be involved
is not satisfying. We seem to allow ourselves the freedom to rely on speculation,
but don't accept speculation by the EPA regarding ROS. When we deal with mode
of action, we are always faced with putting forth the best hypothesis we can based
on available data.
of DNA damage exist (including spontaneous oxidative lesions) and arsenic may affect
the activity of enzymes that repair of oxidative and other DNA damage (reviewed in
Rossman, 2003). It is also possible that live cells exposed to the contents of necrotic cells
may experience DNA damage (e.g. via "clastogenic factors" or via inflammatory cells).
Although there is no direct evidence to support this mechanism, it is of interest that heat-
killed E. coli instilled into the bladder was found to increase bladder carcinogenesis by
MNU {BR: N-methyl-N-Nitrosourea} (Yamamoto et al., 1992), presumably by an
inflammatory mechanism.
There are known direct effects of trivalent arsenicals, including DMA111, on
protein thiols that can affect cytoprotection and cell signaling. These effects may
contribute not only to injury, but also to changes in gene expression and enhanced
proliferation. Further, generation of low levels of oxidants from enzymatic sources
(Smith et al., 2001) or possibly by uncoupling of mitochondrial oxidations
{JT}("uncoupling mitochondrial oxidations".. .would this not lead to ROS?)
(if DMAV can act in a manner similar to arsenate) may contribute to these effects on cell
signaling and transcriptional activation. Finally, effects of inorganic and methylated
arsenicals on thiols in tubulin and cytoskeletal proteins interfere with microfilament
function and cytoskeletal changes that contribute to mitotic arrest and genomic instability
(Li et al., 1992; Ling et al., 2002; Ochi et al., 1999). There is no evidence that hydroxyl
or peroxyl radicals play a significant role in these regulatory processes, especially at low
concentrations of arsenicals. Thus, there are too many highly plausible alternative
pathways through which arsenicals can affect the carcinogenic or tumorigenic processes
to commit to oxyradical generation and oxidative damages as a primary key event in the
toxicity of arsenicals. Other effects of trivalent arsenicals that may be applicable to
DMAV/In exposure include: alterations in DNA methylation, effects on DNA repair, and
induction of aneuploidy (reviewed in Rossman, 2003).
{JT}(Plausible alternative pathways are not an argument against a stated MOA.
Ruling out the influence from all plausible pathways will always be experimentally
beyond our reach, and it is therefore not a good argument for dismissing ROS. It is
fine to mention these, but much more attention is directed at pointing out the
alternatives to ROS than is directed at clearly articulating why the existing data are
not sufficient to support ROS. Is the existing data sufficient to rule it out? We need
to give everyone a framework for experimentally determining if ROS plays a role,
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not just give them a list of alternatives.) (The authors of this section should
consider taking p29 L5-18 from the answer to D1 [DFO NOTE: The original
document pagination is cited here]. Around this text the authors can expand on why
the ROS data are not sufficient and lay the foundation for conducting the necessary
experimental work to refine the MOA.
The tumor response in the rat bladder system is non-linear, as is the key event (i.e.
necrotic cytotoxicity). (Dr. Dragan: More on this please). (This statement really needs a
proper explanation + references) {TR} Since the MOA involves cytotoxicity, doses
below those causing cytotoxicity would not be expected to cause tumors.
{MS}(Forwarded on 11-28-2005 an artiacle on Drosophila (Rizki et al., 2005) - ".. .that
may be of interest for elucidating MOA.)
3.3.2. Human relevance of animal DMAV MOA:
"There are little or no scientific data to suggest that if sufficient DMA111 were
present, key precursor events and ultimately tumor formation would not occur in
humans directly exposed to DMAV" (USEPA, 2005a)
Please comment on the relevance of the postulated key events (see Bl) to
tumors in humans.
Please comment on how, if at all, differences in the human population v.v.
experimental animals should be accountedfor in the risk assessment for
DMA1'.
B2. Human relevance of animal DMAV MOA: If high enough (cytotoxic)
concentrations of DMAV or DMA111 were present in the human urine or bladder after
exposure to DMAV, it is plausible that a similar response (necrosis followed by
regenerative proliferation) would take place. However, no data are available to support or
reject this assumption. No studies have been carried out on DMAv-induced bladder
cancer in humans, so it is not known at this time whether there have been any cases.
Concentrations high enough to cause necrosis in the bladder might be achievable in an
industrial accident or deliberate poisoning. It is not clear whether a repeated or chronic
exposure to DMAV from the environment could produce cytotoxic concentrations of
critical metabolites in human urine. Even in the case of high exposure, the exposures
would probably have to be repeated often enough to produce {TR} persistent necrosis
and /or cancer in the bladder regeneration in order to cause cancer.
{TR}(Again, the confusion with TMAs exists in this paragraph and it appears that
there is an assumption that TMA111 is present in the rat bladder.) Already mentioned (in
charge Al) is the fact that DMAV is converted to TMAvO and possibly TMA111 more
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efficiently by rats than by humans. TMAvO is a hepatocarcinogen in rats (Shen et al.,
2003). TMAm is more potent than DMA111 in damaging DNA in in vitro systems
(Andrews et al, 2003). Thus, although acute toxicities of TMAvO and TMAs111 are lower
than that of DMA111 (Ochi et al., 1994; Sakurai and Kaise, 1998; Yamauchi et al., 1990),
these metabolites can contribute to the MOA for DMAv-induced bladder cancer in rats.
The extent of this contribution is unknown. However, it is possible that the rat data over-
estimates the human risk for bladder cancers from DMAV
There are no data to suggest that the young are at greater or lesser risk with regard
to DMAv-induced carcinogenesis. {GMa}{SHa}(The sentence is not clear about whether
there are no data because the effect on the young has not been tested or whether the tests
have not yielded clear results. Could we clarify?)
There are little to no chemical specific data regarding an increased susceptibility
of humans for bladder tumor development during different life stages. {CH}(The two
preceding short paragraphs could be integrated and or have more substance added.
Otherwise they could be deleted because they refer to a similar issue as discussed in the
last paragraph of 3.4.2, although the latter is not specific to bladder cancer. Also, what is
meant by "little to no chemical specific data. If there is little, then there is some, and
maybe it should be cited. If there are no data, then there is no data. And chemical
specific.. .does this refer to data specific to different chemical compounds of arsenic? It
isn't clear")
3.3.3. Modes of carcinogenic action from exposure to inorganic arsenic:
"Inorganic arsenic (iAs) undergoes successive methylation steps in humans,
resulting in the intermediate production of iAs111, MMAV, MMA111, DMAV, and
DMA111. Each arsenical metabolite exhibits its own toxicity" (USEPA, 2005a).
Please comment on the conclusion that the available data support the
hypothesis that multiple modes of action may be operational following
exposure to inorganic arsenic.
B3. Modes of carcinogenic action from exposure to inorganic arsenic: The
committee agrees that multiple modes of action may operate in carcinogenesis induced by
inorganic arsenic. This is because there is simultaneous exposure to multiple metabolic
products as well as multiple target organs. There are differences in metabolic capability
and probably transport into and out of different organs for different metabolic products,
so that the composition of the metabolites can differ in different organs as well. Each of
the metabolites has its own cytotoxic and genotoxic capability. In general, the
pentavalent compounds are less cytotoxic and genotoxic than are the trivalent
compounds. The primary genotoxic endpoint produced by both inorganic and organic
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arsenic compounds in vitro is chromosome breakage, most likely mediated by DNA
strand breaks resulting from cytotoxicity (Kligerman et al., 2003). DNA strand breakage,
sister chromatid exchange SCE induction and clastogenicity are limited almost
exclusively to trivalent species. {TR}There is little or no evidence of direct DNA
binding of any arsenical to DNA. ©r Point mutations occur at low levels in arsenite-
treated cells, and only at cytotoxic concentrations (Rossman 2003), from cither trivalent
or pentavalent arsenic compounds, except as a secondary result of genomic instability
(Mure et al., 2003). Genotoxic activity in vivo is limited to a small number of studies in
rodents. IP injections of high doses of DMA(DMAV) induced a slight but insignificant
increase in mutagenesis in the Muta™Mouse lung, but not in bladder or bone marrow.
Arsenite was also negative in this assay (Noda et al., 2002). Arsenite induced
micronuclei in mouse peripheral blood lymphocytes and in mouse bone marrow (Tinwell
et al., 1991; Noda et al., 2002). DMA did not induce micronuclei in mouse peripheral
blood lymphocytes (Noda et al., 2002), but did induce aneuploidy in mouse bone marrow
cells (Kashiwada et al., 1998). {CH}(Unless I am confused here, shouldn't the epi
studies that have found elevated micronuclei frequency in exfoliated bladder cells among
arsenic-exposed individuals be mentioned in the following sentences as evidence of
genotoxicity? E.g., Moore et al., papers). Genotoxic activity found in vivo is limited to a
small number of studies in rodents indicating that highly toxic doses of arsenic
compounds may induce micronuclei and/or aneuploidy in non-target tissues. {DBr} (the
sentence should be deleted - Andrews et al. 2003 shows TMA damages purified DNA in
vitro.) There is no gontoxicity data available for other arsenic compounds found in
rodents such as TMA. {GMa}(What arsenic compounds are the genotoxic and what
compounds are you referring to as having no data? The way it is currently written, it
looks like the arsenic compounds are both genotoxic and non-genotoxic.)
(TRi I would like to respond to the suggestion that we include the Epi studies
showing elevated micronuclei (MN) in exfoliated bladder epithelial cells. While I
believe that the data is real (it has been found in many studies and in many
places), it does not really help with MOA. I will quote from something I wrote a
short while ago:
"MN are defined as small round. DNA-containing cytoplasmic bodies formed
during cell division by loss of either acentric chromatin fragments or whole
chromosomes. The two basic phenomena leading to the formation of MN are
chromosome breakage (double strand breaks associated with clastogenesis) and
dysfunction of the mitotic apparatus (aneugeneis). Aneuploidy is defined as a
change in chromosome number from the normal diploid or haploid number other
than an exact multiple (polyploidy). MN as a result of clastogenesis contain
acentric chromosome or chromatid fragments and MN associated with aneuploidy
contain whole chromosomes that lag behind in anaphase and are left outside the
daughter nuclei in telophase. Lagging chromosomes cannot move to the poles,
because they are detached from the mitotic spindle.
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Because cell division is necessary for the generation of MN, the cytokinesis block
micronucleus (CBMN) assay is recommended for use with human lymphocytes
(Kirkland et al.. 2003). In this assay, cultures are treated with cvtochalasin B. an
inhibitor of actin polymerization. Cvtochalasin B prevents cytokinesis but allows
nuclear division, resulting in cells with multiple nuclei. It is thus possible to
identify cells that have divided once, because they contain two nuclei. By
restricting scoring of micronuclei only to cells with two nuclei, problems caused
by variations in cell division due to exposure to toxicants are eliminated.
In the past, several attempts have been made to distinguish between the aneugenic
and clastogenic action of test compounds. Currently, the most widespread and
reliable assays identify whole chromosomes in MN by labeling their kinetochores
or centromeres. Kinetochore proteins can be identified by immunofluorescence
with anti-kinetochore antibody (labeled MN are termed K+) while centromeric
DNA sequences can be identified by FISH using repetitive DNA sequence probes
(labeled MN are termed C+). However, only a few laboratories routinely use these
techniques because they are very costly. When these techniques are used, the in
vitro MN assay is considered a suitable alternative to in vitro chromosome
aberrations tests for detection of clastogenic and aneugenic agents.
It is recommended that this assay should be performed under conditions of high
survival (an increase of >90% in number of viable cells). It is also recommended
that markers for apoptosis and necrosis be included (Kirsch-Volders et al.. 2003).
At least 2000 cells should be scored per concentration (1000 per culture, in
duplicate)."
When MN are measured in Epi studies, there is not enough information to
determine whether the MN result from: 1) toxicity. 2) clastigenicitv. or 3) non-
dvsiunction (leading to aneuplodv). Thus, one cannot say that the MN result from
a genotoxic insult (i.e. clastogenesis). Aneuploidv is an event that has a threshold
(see papers by Kirsch-Volders). whereas many people assume that clastogenesis
does not (at least for ionizing radiation). Also. MN in cells is a trigger for
apoptosis. so many cells with MN will have no progeny.
Furthermore. Giri's studies on MN induction in India show that arsenic exposed
individuals have increased MN in bladder cells, lymphocytes and buccal cells,
with the greatest effect in lymphocytes. But arsenic exposure is not associated
with blood cancers or cancer of the mouth. Thus. MN does not help us to
understand bladder cancer.
Animal studies indicate that for some organs, transplacental carcinogenesis after
maternal exposure to inorganic arsenic occurs. This includes the formation in C3H mice
of tumors of the lung and liver, target sites of potential human relevance, after exposure
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to arsenic in ntero. In addition, in ntero arsenic induces tumors of the ovary and adrenal,
sites not observed in humans to date. The C3H mouse was selected in these studies
because it is, in general, sensitive to chemical carcinogenesis, although this strain shows
spontaneous tumor formation in several tissues. {TR} Other studies indicate that in fof
skin, inorganic arsenic compounds are not complete carcinogens, but act as enhancers
(cocarcinogens, sometimes mistakenly called "promoters") with other agents. Arsenite
acts as a cocarcinogen with solar UV light (Rossman et al 2001; Burns et al., 2004) and
arsenate is cocarcinogenic with 9,10 dimethyl 1-2-benzanthracene (Motiwale et al.,
2005). and not a complete carcinogen. This leaves open the possibility that a
cocarcinogenic MOA may also operate for other organs, but this remains to be tested
(only money is needed){StH, XCL, GMa}.
At this time One cannot dismiss the possibilities of hormesis effects in humans
exposed to low-dose arsenic or the essentiality of arsenic to humans {TR} (Snow et al,
2005). Evidence for essentiality of arsenic has been reported for a number of mammalian
species as well as for chickens (reviewed in Uthus, 1992). {BR: Could this be
reworded? I'm uncomfortable with the suggestion that we are supporting the essentiality
of arsenic, which I personally don't believe. For example, in chickens and other farm
animals, arsenicals may serve as antimicrobial agents that improve growth yields by
preventing infections, but this doesn't mean that arsenic is an essential element.}
These may explain some of the apparent low-dose benefits seen in a variety of systems.
For example, inorganic arsenic has both positive and negative effects on the growth and
function of blood vessel (Soucy et al., 2003, 2005; Kamat et al., 2005). Low
concentrations fuel angiogenesis, while higher concentrations injure endothelial cells and
promote the vessels dysfunction seen in ischemic diseases and peripheral vascular
diseases. Thus at low levels arsenic may provide improved vascularization and growth
of normal tissues, which could reduce cardiovascular risks. However, this process poses
a high risk for arsenic increasing the vascularization and growth of both atherosclerotic
lesions (Simeonova and Luster, 2004) and tumors from a secondary source (Kamat et al.,
2005). The potential for arsenicals to enhance tumorigenisis through enhanced
vascularization has been demonstrated in mice drinking 10-250 ppb iAs111 (Kamat et al.,
2005). However, arsenic at high doses has been used to destroy the tumor vasculature
(Griffin et al., 2003). {CH}(This entire section on essentiality is unclear and confusing. I
suggest deleting it here - the point about essentiality is in the preceding section.) If
arsenic is essential for humans and/or if epidemiological data could be strengthened at the
low-dose range to demonstrate either a low-dose benefit or no effect at low dose, then a
threshold is certain. However, at this time, the data are lacking or problematic with
regard to low-dose effects. This is an extremely important issue and should be
investigated.
{DB - The document references that there are insufficient experimental data
showing that cytotoxic effects from DMAIII/V exposure produce damage at animal dose
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levels associated with tumorigenic responses in the bladder. I believe that EPA should be
encouraged to investigate this area more thoroughly in order to fill gaps in the MOA as
proposed in the second paragraph of page 16. The EPA should want to resolve the issue
of the precise role of DNA in the MOA.}
3.4. Selection of Data for Dose-Response Assessment
3.4.1. Use of animal data for DMAV
"A number of different rodent bioassays (standard bioassay, transgenic animals,
susceptible rodent strains, initiation and promotion studies) are available on
DMAV" (USEPA, 2005a).
Please comment on the use of the bladder tumor data from the DMA1 rat
bioassay as the most suitable dataset for quantifying potential human
cancer risk to DMA1, including the weight of evidence to support this
conclusion
CI: Use of animal data for DMAV: The consensus of the panel is that the
bladder tumor data from the DMAV rat bioassay is the most suitable data set for
quantifying potential human cancer risk to DMAV Given the complex metabolic fates of
Arsenic and its various species, the use of human data from iAs exposure to predict risk
from DMAV is not recommended. In this case, reliance on interspecies extrapolation
using the rat bioassay data is the best alternative.
This question indirectly raises the issue as to the largest source of uncertainty for
DMAV risk assessment—conventional interspecies extrapolation or extrapolation across
various forms of arsenic. The available material suggests that extrapolation across
various forms of arsenic would lead to the greatest degree of uncertainty in a risk
assessment. Although the panel agreed that use of the rat bioassay data is the preferred
alternative, the panel also felt strongly that a discussion of the key uncertainties with
using data from testing in rats to conduct human risk assessment should be included in
EPA's "Science Issue Paper: Model of Carcinogenic Action for Cacodylic Acid
(Dimethylarsinic Acid, DMA1) and Recommendations for Dose Response
Extrapolation.". Issues that panel members consider important to discuss in EPA's
Science Issue Paper are discussed in more detail below. {XCL: Referring to Section
3.2.1 would be useful.} These issues relate to the toxicokinetic and toxicodynamic
differences between rats and humans in response to arsenic exposure, the use of rodent
bladder tumor models in general, and issues in the use of rodent data for human risk
assessment.
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Data illustrating the mode of action for DMAV as a bladder carcinogen in rats
seem quite convincing. However, rats are much more sensitive to DMAV in
carcinogenicity testing than the mouse (Rossman, 2003; Arnold, et al., 2003). Several
toxicokinetic and toxicodynamic differences between rats and humans have also been
reported after arsenic exposure. For example, arsenic methylation in rat liver hepatocytes
proceeds at a faster rate than in human hepatocytes; and rats have a considerably slower
whole body clearance of DMA than humans. This slower whole body clearance in rats is
because a significant portion of DMA is retained in the erythrocytes of rats (Vahter, et al.,
1984). There is a 15 to 20 fold higher binding of arsenic to rat hemoglobin than to human
hemoglobin (Lu, et al, 2004). Human bladder tumors are primarily transitional cell
carcinomas, and rat bladder tumors are reported to bear some similarity in pathology to
low-grade papillary tumors that occur in humans; however, they are not similar to
invasive human bladder tumors that display high grade malignancy (Cohen, 2002). The
foregoing, taken together, illustrate known substantial metabolic, pharmacokinetic and
pharmacodynamic differences between rats and humans and should be thoroughly
discussed in the final EPA documents as these data indicate that the rat is likely to be
considerably more sensitive to developing bladder cancer than humans after exposure to
DMAV. {MW: I do have an issue with the text on page 20 line 32-35—I think that the
distinction made between the rat urinary bladder tumors ("Low grade" transitional cell
papillomas) and human UB tumors associated with arsenic ("high grade" invasive
transitional cell carcinomas) in this text is not one of qualitative substance. First of all,
the majority of the rat tumors induced by DMA were diagnosed as transitional cell
carcinoma not low grade papilloma. So the rat and human UB tumors are the same cello
type and are both carcinoma (which by pathological definition has the quality of
invasiveness). The human bladder tumors in these third world countries are likely only
recognized when they cause overt symptoms and therefore at a late stage. The rat UB
tumors in the Fukishima study were discovered at the 2 year necropsy (mostly) in animals
intentionally killed at this time. Had the authors let the rats go until death these lesions
may well have progressed to "more" invasive carcinoma. — So this is largely an esoteric
argument concerning comparative pathology and tumor progression, not a major
qualitative difference. I think this text should be deleted or at least corrected to be in line
with the facts of this study. To say that these rat tumors "bear some similarity in
pathology to low grade papillary tumors" is a clear distortion. There may be biokinetic
and biodynamic issues but there are not real issues in UB tumor pathology.}
A second major uncertainty associated with using bladder tumor data from rats is
the lack of knowledge about levels of DMA111 produced in the human bladder upon
exposure to DMAV and how that compares to levels of DMA111 produced in rats exposed
toDMAv. The few human exposure studies that exist seem to indicate little if any
DMA— production takes place. {MS}(Preceding sentence needs to be reworded. There
are no studies on DMAIII formation in humans exposed to DMAV. In humans exposed
to iAs, DMAIII is the major urinary metabolite when fresh urines are analyzed (see
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responses to Al).) This is because DMAV is not absorbed well — -approximately 80% of
a dose of the parent compound is excreted in a short time after exposure (Buchet, et al.,
1981; Marafante, E., et al., 1987). Additionally rat urothelial cells are 3.5 times more
sensitive to DMA111 than are human urothelial cells in in vitro studies (Cohen, et al.,
2000).
These toxicokinetic and toxicodynamic factors should be taken into account in the
application of rat bladder tumor data to assess human bladder cancer risk. These factors
will impact the choice of uncertainty factors since the weight of evidence indicates that
the rat is considerably more sensitive to bladder tumor induction from direct exposure to
DMAV than are humans. {MS}(The preceding sentence needs to be reworded. There is
no evidence, per se, that rats are more sensitive to DMA carcinogenesis than humans,
although the urinary excretion of trimethyl-As metabolites that are not found in humans
may suggest so.) Although selection of a safety factor is the province of EPA's policy
choice, the Panel believes that in the case of the Food Quality Protection Act 10X safety
factor for this element of risk assessment, the science supporting a smaller factor could
lead EPA to choose to lower the factor for arsenic to some number less than 10. The
increased sensitivity of rats relative to humans could be taken into account. The Arsenic
Review Panel's analysis of the toxicokinetic data indicates that an uncertainty factor for
extrapolation from rat toxicokinetic data to human risk in this case is likely to be less than
one. The analysis of the toxicodynamic data indicates that the uncertainty factor may
also be lower than the default. The application of uncertainty factors has also been
addressed in the Panel's response to question Dl. {JT and MM: There is a question of
how the issue of the Safety Factor of 10 should be handled. This issue is in common with
the discussions here in 3.4.1 (i.e., CI) and 3.5.1 (i.e., Dl). The issue has been dealt with
in the two sections as having PD and PK components and there is a suggestion that the
Safety Factor can be reduced. There is an issue of whether to suggest some factor that
the components could be reduced to or just to suggest to EPA that they should consider
reducing the factor. The issue needs to be discussed at the Panel meeting. WE NEED TO
POINT OUT THIS IS A POLICY ISSUE THAT THE PANEL ADVISES UPON—
CROSS WALK TO Dl as WELL—SEE SECTION IN 3.5.1}
The Agency should also discuss in its Science Issue Paper, differences between
rats and humans in the development of bladder tumors, and how these differences impact
interspecies extrapolation. For example, urinary bladder tumors in rats occur very late in
life. {GMa} (I am not sure why the comment is frequently made that bladder cancers in
rodents occur very late. That is true of human cancers as well. Bladder cancer is usually
one of the latest occurring cancers in humans. However, the age of occurrence also may
relate to the age of first exposure. Therefore, this is a complicated issue in humans and it
hardly seems an appropriate reason to try to refute the use of animal data for human
extrapolation because of the age of onset of disease in rats.) Studies suggest that in rats
it takes two or more years of continuous high dose exposure to DMAV to induce these
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tumors. This would equate to a human being-developing cancer very late in life as well.
The Science Issue Paper should specifically discuss the similarities and differences in the
time for induction of DMAV related tumors in rats with the pattern observed with humans
and arsenic associated urinary bladder cancer.
EPA'S Science Issue Paper should also discuss general issues associated with rat
urinary bladder cancer. One such issue is the relationship between the non-specific
{TR}(What is meant by the non-specific induction of tumors and high concentrations...?)
induction of tumors and high concentrations of arsenic in the urine. Also, there is a need
to address evidence that simple enhancement of proliferation is not associated with
carcinogenesis in many tissues. Studies by Gur et al. (listed on page 97 of the DMA
MO A Science Issue Paper) on the carcinogenicity of DMAV were never published and
thus cannot be critically evaluated by the Panel. The Science Issue Paper notes that the
Gur studies in rats and mice are key bioassay studies. Reliance on these studies would be
stronger if the studies had the benefit of peer review.
EPA's Science Issue Paper is critical of the transplacental model for inorganic
arsenic carcinogenesis because the work was done in a sensitive strain of mouse (C3H)
that develops a significant background level of tumors in certain tissues. Implicit in this
criticism is the assumption that the presence of a high spontaneous tumor rate in the
organ of interest makes the interpretation of the animal data difficult. That difficulty
would extend to the ability to estimate the proportion of human tumors, if any, that could
be attributable to low exposure to a specific contaminant such as iAs However, it is well
known that all cancers in rodent and human tissues can occur spontaneously. Thus, it
could be argued that no rodent carcinogenesis studies could be used to assess human
carcinogenicity. Clearly, this is not the case as rodent studies are used routinely for
human risk assessment. The EPA's position on the issue of using a sensitive strain to
extrapolate to humans should be expanded and clarified in the Science Issue Paper
especially as it relates to arsenic. As part of this clarification, requirements for target site
concordance between human and rodents in order to validate a rodent bioassay and the
relative weight placed on fatal versus not fatal cancers should be discussed as they apply
to arsenic. {TR}(The issue is not that tumors can occur spontaneously. It is that the
strain of mouse used in the transplacental studies has a very high incidence of
spontaneous tumors. If these results cannot be reproduced in a more normal strain of
mouse, one must view the results as a kind of cocarcinogenesis (arsenic enhancing an
endogenous carcinogenic process). EPA's Science Issue Paper does not even address the
question of cocarcinogenesis of inorganic arsenic. It confuses tumors with paps and
promotion with cocarcinogenesis (p. 39) and Section 3.B (p. 40) contains numerous
errors as well.)
Please comment on whether the iAs epidemiology data can be used to
inform the DMA1 dose-response assessment derived ji'om rat data with
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DMA1. If so, please discuss how such information might be used. (See
Appendix).
C. 1 (B). :The panel consensus was that without more detailed information on
target tissue dosimetry of arsenic species the iAs epidemiology data would be of limited
use to inform the DMAV dose-response assessment derived from rat data with DMAV
Direct exposure to iAs elicits a different cascade of metabolite concentrations with
related differential kinetics compared to direct exposure to DMAV, therefore the iAs
epidemiology data cannot reasonably be used to inform the DMAV dose-response
assessment derived from rat data with DMAV In the absence of specific information on
target tissue levels, assumptions would have to be made regarding the proportion of the
iAs for human and DMAV for rodents that reaches the bladder tissue as the toxic DMA
species.
In principle, epidemiology data from iAs exposed humans could be used to
inform the DMA assessment to the extent that the data might be able to address the
appropriateness of interspecies extrapolation, specifically the relative sensitivities of rat
and human to bladder cancer following arsenic exposure. However, as noted above, in
order to be useful some information on target tissue dose of DMA following human
exposure to iAs and rodent exposure to DMAV would be necessary. With both tumor
indices (human and rodent) expressed in terms of the same tissue dose rather than iAs or
DMAV exposure levels, the relative sensitivities of the human and rodent could be
assessed.
3.4.2. Use of human epidemiological data from direct iAs exposure:
"Since the NRC (2001) report on iAs, an additional body of literature has
developed describing epidemiology data from populations in the US exposed to
iAs in drinking water" (USEPA, 2005a).
Does the SAB agree that the Taiwanese dataset remains the most
appropriate choice for estimating cancer risk in humans? Please discuss
the rationale for your response.
C2. Use of human epidemiological data from direct iAs exposure: The
Taiwanese dataset consists of population and mortality data from 42 villages in southwest
Taiwan for the years 1973-1986. Arsenic levels in wells from these villages were
measured in 1964-1966. The database is one of the largest that has been evaluated for
cancer risk relative to arsenic exposures. A total of almost 900,000 person years of
follow-up were included, with 1,152 cancer deaths (637 males, 515 females). Among the
cancer deaths were 181 due to bladder cancer (85 males, 96 females), 268 lung cancer
(147 males, 121 females), and several hundred due to other types of cancer. These data
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have been subject to several ecologic analyses, starting with the original publications by
Chen et al. (1988) and Wu et al. (1989), followed by further analyses by Morales et al.
(2000) and by the National Research Council (1999 and 2001).
Among the 42 villages, the arsenic concentration ranged from 10 to 934 ppb ((J-g/L).
Twenty of these 42 villages used one well. Among many of the 21 {GM}(Where is the 1
missing village in these counts? The next page has 22.}villages with multiple wells,
many had wide variability in the measured arsenic level in their wells. Analyses using
the full dataset give results comparable to results from a reduced dataset including only
the villages with single wells, providing some confidence in the stability of the overall
results (National Research Council, 1999). The Panel recognizes the limitations of the
southwest Taiwan database, including its ecologic character, lack of smoking
information, limited precision of exposure estimates, especially among villages with
multiple wells, and the possible issue of compromised nutrition among segments of the
exposed population. {GM}(Isn't the fact that the data sets from Taiwan have been
subjected to many years of peer review, as part of published studies, an important plus for
these data as well?) However, in view of the size and statistical stability of the database
relative to other studies, the reliability of the population and mortality counts, the stability
of residential patterns, and the reliability of the exposure assessment {GM}(You talk
about the "reliability of exposure" here but just above say it lacks precision. That needs
clarification ), it is the Panel's view that this database remains, at this time, the most
appropriate choice for estimating cancer risk among humans.
{JT}(I urge the panel to revise the ending of the paragraph to reflect the text that
follows describing the limitations of this data set. For example:
".. .this database remains, at this time, the most appropriate choice for estimating
cancer risks in humans, but given its limitations, alone it is not sufficient for
estimating risks to humans. Additional, work to test, validate and compare risk
estimates made using this data set must be completed, as suggested in the
following sections."
The Panel recommends that other epidemiologic databases from studies of
arsenic-exposed populations be used to scale the unit risks at high exposure levels that
emerge from the Taiwan data. Several of these studies had the advantage of data with
excellent exposure assessment. In addition, some populations likely differed from the
Taiwanese population with regard to their nutritional status. The accuracy and precision
of exposure assessment is a major issue in all environmental epidemiologic studies, and
in particular, in studies of arsenic in drinking water. Misclassification of exposure in
such studies (when non-differential) can have a profound effect in depressing the
magnitude of the observed risk. The excellence of exposure assessment is an especially
strong aspect of several studies from northern Chile, and the Panel recommends that the
findings of Smith et al. (1998) and of Ferreccio et al. (2000) be considered by EPA
{JT}(What does it mean "be considered by EPA." Be more specific, how should it be
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used?) In addition, arsenic exposures appear to be well characterized in cohort studies of
Chiou et al.(2001) of transitional cell carcinoma (mostly bladder cancers) and Chen et al.
(2004) of lung cancer, from arsenic-exposed cohorts in southwest and northeast Taiwan.
The latter study also provides data on the joint effects of arsenic and cigarette smoking in
the Taiwanese population. It should be possible to go through a complete risk assessment
using at least one other of these databases. {JT}("it should be possible" should be revised
to stronger language and expand the reason this is important: model and data set
validation, uncertainty assessment, sensitivity to data sets, etc.)
{JY}In contrast, problems in t The accuracy of estimated long-term exposures to
arsenic in some recent studies with individual data conducted in the United States and
elsewhere among populations exposed to levels is of concern for some recent studies
under 100 ppb. compromises This may compromise their overall utility of these data for
long term estimates of exposure (>20 years) in assessing concordance with risk estimates
obtained from the Taiwan study. The Panel suggests that results on bladder cancer risk
from published epidemiology studies of US and other populations chronically exposed
from 0.5 to 160 |ig/L inorganic arsenic in drinking water be critically evaluated. EPA
should determine regarding their potential utility in exploring overall concordance of the
cancer risk estimates derived from their data with risk estimates obtained from
extrapolation of the Taiwan data [Bates (1995), Lewis (1999), Steinmaus (2003),
Michaud (2004), Bates (2004)]. {SHa}(corss-reference this line with section 3.5.1.)
When reviewing these "low-level" studies, {JY} as well as the "high level"
studies, at least the following should be considered: The effect of exposure
misclassification on estimates of risk; temporal variability in assigning past arsenic levels
from recent measurements; the extent of reliance on imputed exposure levels; the number
of persons exposed at various estimated levels of waterborne arsenic; study
response/participation rates; estimates of exposure variability; and the resulting influence
of these factors on the magnitude and statistical stability of risk estimates. US and other
populations differ from the Taiwanese population of interest in genetic background,
dietary intake, and background exposure concentrations to inorganic arsenic, and if one
or more of these studies are shown to be of potential utility, comparative analyses of the
US and Taiwan data may lead to further insights into the possible influence of these
differences on population responses to arsenic in drinking water. For compounds such as
arsenic for which there are human data beyond the Taiwanese study on which human
cancer risk has been based, data from the other, {JY}loss robust, investigations at high
exposure levels (>150 ug/1) can be used to gauge the Taiwanese findings (REFERENCE).
All of these studies including those from Taiwan, Chile, Argentina and the U.S. as
described above should be judged by the same set of criteria, with the comparative
assessment of those criteria across studies clearly laid out in a tabular format. {JY} We
recommend that At least some the criteria be listed and described, have been listed in the
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previous paragraph, with t The relative strengths and weaknesses of each study spelled
etrt need to be described in relation to each criterion. The caveats and assumptions used
should be presented so that they are apparent to anyone who uses the data. Included in
the risk assessment background document should be a complete and transparent treatment
of variability within and among studies and how it affects risk estimates. The present
lack of transparency in the application of the criteria in the process of study selection was
pointed out by several panel members.
{JY Insertion}
As recommended in the preceding sections, aggregate results, particularly on bladder
cancer risk, from multiple published epidemiology studies of low level arsenic-exposed
populations need to be taken into consideration in a more formal secondary integrative
analysis and compared with the main analysis for concordance. Data from the
epidemiologic studies of relatively low exposure can be informative and need to be
formally evaluated beginning with a comparative analysis of strengths and weaknesses as
described above.
A sensitivity analysis to formally evaluate the potential impact of sources of bias (non-
random error) in the low level case control and cohort studies is recommended since non-
differential misclassification cannot be routinely assumed. These several recent arsenic
epidemiology studies have the advantage of data with exposure assessment at a range of
exposure levels relevant to those experienced by the US population—exposure levels in
these studies range from 0.5 to 160 |ig/L inorganic arsenic in drinking water (Bates et al.,
1995; Karagas et al., 2004; Lewis et al., 1999; Kurttio et al., 1999; Steinmaus et al., 2003;
Bates et al., 2004). Most of these populations have a nutritional and genetic background
similar to that of U.S. or were conducted in a U.S. population.
Precedents for formally integrating health outcome information from a number of
epidemiology studies are readily available. Although, ideally, one would prefer
individual measures of exposure to be available in all studies, it is recognized that the
Taiwan study of 42 villages herein recommended as the basis for arsenic cancer risk
estimation is an ecological study with uncertainty as to individual exposure levels.
Recommendations for assessing the range of uncertainty have been put forth in this report
in the section immediately following.
Arsenic epidemiological literature is an instance in which a number of quality (but not
ideal) epidemiology studies are available. Quantitative exposure-response modeling for
other compounds for which integrative risk analyses were carried out utilizing multiple
epidemiology studies have been conducted and health risks for defined outcomes
estimated. For example, NRC/NAS (2000) conducted an integrative analysis of three
studies of in utero exposure to methylmercury (MeHg) and a number of
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neurodevelopmental outcomes in children. Statistical power among studies was
examined and was found not to be principally accountable for observed study-to-study
differences in outcomes at similar exposure levels; likewise p values for outcomes were
not found to be particularly useful in comparing studies, but rather comparative dose-
response estimates (i.e., regression slopes) were chosen as the most optimum comparative
basis for integration. Likewise, four recent studies (Konig et al., 2005; Bouzan et al.,
2005; Cohen et al., 2005a; Cohen et al., 2005b) amply illustrate the conduct of integrative
exposure analyses and health outcome. In an integrative analysis of fish consumption
and coronary heart disease mortality, eight studies (29 exposure groups) were identified
that met pre-established study quality criteria, had quantified exposure (e.g., fish intake)
and had reported the precision of relative risk estimates (Konig et al., 2005). Averaged
relative risk results were weighted proportionately by precision. In another integrative
analysis, a quantitative exposure-response function for prenatal MeHg exposure and IQ
was developed using data from three different epidemiology studies (Cohen et al.,
2005a). Weights were assigned to measures of cognitive performance for each of seven
test domains; an integrated sensitivity analysis was conducted to assess the impact of
alternative assumptions on the final integrative study results.
Studies for inclusion in each integrative analysis were selected on the basis of a priori
established criteria. As previously stated, inclusive evaluation of all arsenic
epidemiology studies (both "low" and "high" exposure studies) by pre-set standard
criteria and presentation of results in tabular format has been recommended by this Panel.
This is the initial step in conducting an integrative analysis.
For most compounds of human health concern, epidemiologic data are generally not
available (see A2); but occasionally, as in the case of arsenic, one or perhaps a few
epidemiology studies will be available. To improve validity, it is important to support
human cancer risk estimates using the maximum available scientific information and
contemporary risk assessment methodology. The current cancer risk assessment
methodology for iAs relies on choosing a single epidemiological study to derive a cancer
slope factor that is then used to extrapolate health effects considerably below the
exposure levels observed in that study. There are a number of arsenic epidemiology
studies now available; there are published methods for quantitatively integrating results
from multiple studies (Coull et al., 2003; Ryan, 2005).
Integrative analyses result in improved statistical power and precision of the estimates
that represent an additional advantage of utilizing a larger dataset, as has been pointed out
for the Taiwan dataset. Although the "low" arsenic exposure epidemiology studies cannot
by themselves provide a basis for dose-response modeling because of lack of data at the
higher exposure levels (see D2), they do provide data on the relative risks of bladder
cancer for humans exposed at low levels. The Panel suggests, as described in detail in
this section that an effort be made to conduct a secondary integrative analysis applying
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similar approaches to those described above to assess concordance with exposure-
response models derived from the outcome of the primary analysis.
{JY} In response to Dr. Harlow's questions in her comments, Dr. Yager notes:
The charge to the committee states that we must address all questions AND
THEN WE ARE FREE TO COMMENT ON ANY OTHER ASPECT WE WISH.
These paragraphs were submitted in the latter vein as stated.
The suggestion being made in these paragraphs is that, in general, EPA needs to
consider at some point changing the paradigm of using just one epidemiology
study to conduct a risk analysis and consider methods to integrate results when
several epidemiology studies evaluated on the same set of criteria are available. It
appears that this suggestion is not particularly controversial. Of course, this Panel
cannot recommend EXACTLY how EPA should conduct an integrative analysis
for arsenic. As correctly pointed out by Sioban, that is outside the scope of this
Panel.
These paragraphs make very clear, however, that an integrative approach is being
suggested for future consideration by US EPA and is giving EXAMPLES (note
the term exemplify used in these paragraphs) of how integrative analyses have
been conducted for ANOTHER compound—methylmercury. NO WHERE is it
suggested in these paragraphs that EPA conduct an analysis for arsenic
EXACTLY as was carried out in the examples provided. The fact that these
integrative analyses and methods are published (and therefore referenced) verifies
the fact that the integrative approach is being applied; that this is not simply some
random idea that cannot be carried out in the real world. Again, referencing these
studies does NOT in any way specifically suggest that EPA follow these exact
examples.
It may very well be that the quality of current arsenic epidemiology studies in
general simply cannot meet the requirements for a reasonably rigorous integrative
analytical approach at this time. So be it. The point is to make the suggestion
that US EPA be considering such an approach in general, and at the very least in
this instance, compare ALL of the arsenic epidemiology studies currently in
existence by the same set of criteria.
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Regarding the southwest Taiwan data from \2 villages, the Panel suggests that EPA
conduct sensitivity analyses, using tho range of exposures in tho villages with more than
one well to provide a range of the risk.
(Note: The following is an adaptation of the response originally to D2):
{GMa}(This paragraph seems out of place where it is - do we need a lead in or
something?){CH}(This should be merged with the preceding paragraph. See following
changes) Given the concerns regarding the use of the median well water concentrations
in some of the 42 villages in Southwest Taiwan that have with- more than one weH-
measurement, the Panel recommends that EPA the Agency conduct a sensitivity
analysis. This should include the range of exposures in said villages to provide a range
of risk estimates, of the estimated model for arsenic exposure hazard to the assumption
that all village residents were exposed to tho median well water concentration in
communities served by multiple wells. One alternative (suggested in response to D-3)
is a full Monte Carlo analysis in which the individual well concentrations for 22
villages with multiple wells are taken into account. The Panel recognizes the difficulties
with this approach including the issue of how to allocate cases to wells within villages.
A simpler, but useful first approach would be to test the sensitivity of the model fitting
when arsenic concentrations for multiple-well villages are set to: 1) a low level
concentration from the range for the village ({SHa}minimum, 10th percentile, 20th
percentile); 2) the median (current procedure); and 3) a high level concentration from
the village range ({SHa} maximum, 90th percentile, 80th percentile).
Do these data provide adequate characterization of the impact of
childhood exposure to iAs? Please discuss the rationale for your
response.
The Taiwanese data are inadequate to characterize the impact of childhood
exposure to inorganic arsenic with respect to carcinogenesis. That is, it is not clear
whether children differ from adults with regard to their sensitivity to the carcinogenic
effects of arsenic in drinking water. More data are needed to fully characterize the impact
{CH rewords as follows} of transplacental exposures. However, data from the studies in
Southwestern Taiwan which include aftd childhood exposures in the calculation of
lifetime dose, show that in the population under 30 years of age there were no bladder
cancer cases, and only 5 lung cancer cases. , however tho Southwestern Taiwanese data
are as good as other studies in this regard and do have more information than most others.
In these data, no bladder and 5 lung cases were observed in population age <30 years.
Childhood exposures are included in the lifetime dose estimates. Smith et al (1998) report
the highest excessive risk for male lung cancer in the 30-39 year old age group,
suggesting the importance of childhood exposure and risk {JY} and perhaps smoking
behavior as young adults. For 533 women exposed to arsenic in drinking water from tube
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wells at greater than 50 |ig/L compared with those exposed at 50 |ig/L, or less, findings
suggest that there are significantly increased odds ratios for spontaneous abortion,
stillbirth and neonatal death (Milton et al., 2005). Another reproductive study in Chile,
which followed over 800 pregnancies, found that pregnant women drinking water
containing 40 ug/L gave birth to infants of lower birth weight than a comparable group
drinking water containing very low arsenic concentrations (<1 ug/L) (Hopenhayn et al,
2003). Thus maternal exposure at {CH}moderately high levels may have untoward
toxicity effects; the issue of childhood carcinogenic susceptibility has not been {JY} weH-
extensively addressed.
3.5. Approaches to Low-Dose Extrapolation for Inorganic Arsenic and DMAV
3.5.1. Mode of carcinogenic action understanding for DMAv/m and
implications for dose response extrapolation to estimate human cancer risk:
"The use of mode of action data in the assessment of potential carcinogens is a
main focus of EPA's 2005 cancer guidelines. As stated in these guidelines "The
approach to dose-response assessment for a particular agent is based on the
conclusion reached as to its potential mode(s) of action". Although a biological-
based model is the preferred approach to estimating cancer risk, there are
insufficient data on DMAV to support development of such a model" (USEPA,
2005a).
Please comment on the scientific evidence and biological rationale in
support of nonlinear versus linear low dose extrapolation approaches,
which approach is more consistent with the available data on DMA1 and
current concepts of chemical carcinogenesis, and how scientific
uncertainty should most appropriately be incorporated into low-dose
extrapolation.
Dl: Mode of carcinogenic action understanding for DMAv/m and
implications for dose response: (1) Please comment on the scientific evidence
and biological rationale in support of the nonlinear versus linear low dose
extrapolation approaches,
The committee felt that there are adequate data to support a MOA for bladder
carcinogenesis induced by high doses of DMAV in the rat {JT}(see B3). The MOA that
involves cytotoxicity of the bladder epithelium and increased, sustained regenerative
proliferation as a key events. {GMa}(Initially you mentioned that carcinogenesis needed
3 steps but here you aonly talk about the cytotoxicity and regeneration as a route to
cancer. Don't we need to clarify this relative to the previous statements?) The urine of
DMAv-treated rats contains DMA111 at levels that cause necrotic cytotoxicity in these
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cells in vitro, so it is reasonable to postulate that DMA111 might mediate the necrotic
cytotoxicity in the rat bladder. A role for other rat DMAV metabolites, trimethylarsine
oxide (TMAvne (TMAs111) (Waters, et al., 2004) cannot be excluded as contributors of
the necrotic cytotoxicity in rats exposed to DMAV
The committee felt that there are insufficient data to invoke ROS-induced DNA
damage as a key event in the carcinogenic process, associated with exposures to DMAV
or DMA111, although contributions from that mechanism cannot be ruled out. {BR: Can
we remove "although contributions from ruled out?" Almost nothing can be ruled out,
so this statement places undue emphasis on ROS.} {SG}(Here, and 6 paragraphs forward
— are we being inconsistent in our comments in these instances? It seems on the one hand
we don't think much of the ROS mechanism in relation to MO A, but on the other hand,
there is ample evidence that ROS can be involved in the MOA. Am I misinterpreting
something?)
The postulated revised MOA {JT} for DMAV is:
1. Reductive metabolism of DMAV to DMA111.
2. High concentrations of DMA111 in urine cause urothelial cytotoxicity.
3. DNA damage by an unknown mechanism unrelated to direct genotoxicity. The
clastogenic action of DMAIII/V is likely involved. {TR}(The fact that the bladder
contains increased 8-oxo-dG does not mean that DMA caused it. See Section B.)
4. Regenerative cell proliferation drives conversion of DNA damage into heritable
mutations and clonal expansion of altered cells.
5. Continuous exposure and persistent regenerative proliferation leads to production
of additional mutations, including those necessary for multistep carcinogenesis.
Neither the revised MOA nor those postulated by ORD or OPP (USEPA OPP,
2005; USEPA ORD, 2005b) contain key events expected to be a linear function of dose.
Reductive metabolism of DMAV is likely to be saturable and therefore non-linear. In
vitro, cytotoxicity of uroepithelial cells occurs {TR} in vitro only at concentrations
greater than 0.4 [xM DMA111 (Inferred from Dr Cohen's paper, but should be confirmed
with the author. The range of doses tested was not described PLEASE ADD THE
CITATION HERE){GMa}(Is the Cohen paper published?). In rats, cytotoxicity of the
uroepithelium occurred at the lowest tested dose (2 ppm in the diet), but the incidence
and severity increased, and the latency decreased significantly as a function of dose.
Statistically significant increases in regenerative cell proliferation only occur in rats at
DMAV doses greater than 40 ppm in rats, again, a non linear or apparent threshold
response. Even the production of ROS and its interaction with DNA, a key event in the
MOA postulated by OPP and ORD would be nonlinear functions of DMAV dose.
{TR}(This makes no sense to me. It completely leaves out DNA Repair!) Production of
ROS would likely be linear low dose, but nonlinear across a larger dose range if saturable
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metabolic processes are involved. Formation of heritable alterations in DNA by ROS is
believed to be nonlinear (sublinear) effect best represented by a quadratic function
(USEPA OPP, 2005). The formation rate is a function of the rate of DNA damage and
the rate of DNA misreplication (USEPA OPP, 2005). The latter being a function of cell
proliferation, which in the case of DMAV, is a highly nonlinear function of dose (USEPA
ORD, 2005). {TR}(This also leaves out DNA repair!)
It was therefore the consensus opinion that the available data support the
nonlinear approach for the low dose extrapolation.
The linear approach would be consistent with evidence for direct genotoxicity of
DMAIII/V There is no compelling data that DMAIII/V are directly genotoxic. It is generally
accepted that DMAV is not directly genotoxic (not DNA reactive). This conclusion is
well supported by the data presented in the "Science Issue Paper: Model of Carcinogenic
Action for Cacodylic Acid (Dimethylarsinic Acid, DMAV) and Recommendations for
Dose Response Extrapolation." While DMA111 may be indirectly genotoxic under some
circumstances, genotoxicity does not appear to be the driving factor in the mode of action
of DMA111. {JT} We summarize these data below.
Based on results from genotoxicity studies conducted DMAV and DMA111 appear
to lack significant reactivity directly with DNA. These studies are discussed in the
Science Issue Paper (pages 52 to 59) and summarized in Table B4 (with references). The
panel agrees with the conclusion in the Science Issue Paper that DMAV is only genotoxic
at concentrations producing cytotoxicity or cytolethality. For example, DMAV was not
mutagenic in the Ames assay (Kligerman, et al., 2003) or the transgenic "Muta" mouse
assay (Noda, et al., 2002); DMAV exposure did not result in micromuclei formation
(Noda, et al, 2002). In the mouse lymphoma assay a low frequency of mutations were
seen only at concentrations that were cytolethal (Moore, et al, 1997). Chromosome
aberrations in human lymphocytes were only seen at cytotoxic levels (Moore et al, 1997).
In contrast, there is some evidence that DMA111 is clastogenic in vitro at concentrations
below those that are cytotoxic. For example, in Chinese hamster ovary cells low
concentrations of DMA111 (1 to 5 micromolar) resulted in micronuclei, well below
cytolethal concentrations (Dopp, et al., 2004). {TR}(l-5 micromolar DMAIII is NOT A
LOW CONCENTRATION, BUT IS LETHAL. The Dopp et al. paper makes an error in
using Trypan blue exclusion to assay cytotoxicity. This is an extremely poor choice, as is
shown in Komissarova et al., 2005.) However, the induction of chromosomal damage in
vitro and in non target cell types is not necessarily related to cytotoxicity in bladder cells
or genotoxicity in bladder cells.
Overall, there is a critical mass of data from in vitro studies with DMAV/In in
animal tissue that supports the types of mechanisms typically associated with indirect
(i.e., threshold) types of carcinogens. {GMa}(The section that follows does not seem to
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be a sentence). For example, production of reactive oxygen species and DNA disruption
(nicks and breaks) formed in association with toxic levels of DMA species, inhibition of
some DNA repair processes, DNA-protein cross4inks, and altering the expression of
pathways associated with the production of tumors (e.g., p53 and telomerase proteins).
Data that might argue for a linear, non-threshold mode of action such as DNA binding
and point mutation induction have not been produced. {SG}(Here, and 6 paragraphs
back — are we being inconsistent in our comments in these instances? It seems on the one
hand we don't think much of the ROS mechanism in relation to MO A, but on the other
hand, there is ample evidence that ROS can be involved in the MOA. Am I
misinterpreting something?)Other studies in vivo that show induction of DNA strand
breaks and the formation of oxidative DNA species also support secondary effects on the
DNA. While there are studies which show in vivo clastogenicity with inorganic arsenic
compounds, no solid evidence of in vivo chromosome damage exists for DMAv/ra.
Thus, data produced with animal cells and tissues points strongly to a secondary mode of
action for DMA v/m.
{GMa}(Didn't we also recommend looking at the dose consistency using other
studies?")
{JT}(Suggests striking this paragraph. It seems redundant.)
The Science Issue Paper states that the limited ability of DMA111 to induce sister
chromatid exchanges coupled with its clastogenicity and cytotoxicity are features of a
genotoxin whose mode of action is likely via the production of reactive oxygen species
(ROS). However, the Panel was not in agreement that ROS play a role in the mechanism
of action of DMA. Although in vitro studies with isolated DNA have shown oxidative
DNA adducts and damage, these results do not necessarily mean that resulting
chromosomal or DNA mutational events will occur in vivo. Oxidative DNA adduct
formation is readily repaired in mammalian cells and unless there is direct evidence for
the formation of oxidative DNA adducts resulting in the induction of mutational events in
the bladder, the relationship between these two events are associative ed at best and
probably not related to each other in the context of bladder cancer in the rat following
DMA treatment. In contrast, the induction of oxidative damage and oxidative stress
following cytotoxicity, however, is well documented. This frequently is the result of
necrotic events in the target tissue resulting in the sequelae of inflammatory events.
{JT}(This text.. .the whole paragraph, should be a part of the answer to charge
question B3. Around this text the authors can expand on why the ROS data are
not sufficient and lay the foundation for conducting the necessary experimental
work to refine the MOA.)
(2)...which approach is more consistent with the available data on DMA1 and
current concepts of chemical carcinogenesis,
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The non-linear approach is more consistent with the available data and current
concepts of chemical carcinogenesis (See (1), above).
(3)... how [should] scientific uncertainty should most appropriately be
incorporated into low-dose extrapolation
After some discussion, we viewed this question from the perspective of the EPA's
RfC guidelines (EPA 1994). Similar guidelines for the derivation of chemical specific
uncertainty factors have been developed by the International Program for Chemical
Safety (IPCS 2001). These guidelines provide an approach for incorporating uncertainty
into risk assessments in the form of uncertainty factors. Uncertainties in the dose-
response assessment can be broadly grouped into a) those related to interspecies
differences in pharmacokinetics, b) those related to interspecies differences in {JT}
pharmacodynamics, to which we add, c) those related to misspecification of the MOA. In
the case of the latter, the dose response would change significantly only if evidence
became available that DMAIII/V caused DNA damage through direct reactivity with DNA.
The low dose extrapolation would then become linear. This appears unlikely at this time
and the panel concludes that conducting the low-dose extrapolation using the linear
assumption to allow evaluation of uncertainty in the MOA by comparison to the non
linear approach is not an appropriate way to address this uncertainty. {JT} The preferred
approach is to conduct additional research (an outline is found in B3).
{MM—Asks whether for EPA we should use pharmacokinetics or
toxicokinetics throughout the document?}
{MM—the following is MM's revision to reflect both the policy issue
and the crosswalk. Also, we need to decide whether to call these
"uncertainty" factors or "safety" factors". Section CI calls them
safety factors, although the rest of the para refers to uncertainty
factors. It is probably a policy convention, so let's do whatever the
agency usually does.}
Although selection of uncertainty factors is the province of EPA's policy choice, the
Panel believes that in the case of the Food Quality and Protection Act 10X safety factor
for this element of risk assessment, the science supporting a smaller factor could lead
EPA to choose to lower the factor for arsenic to some number less than 10. As a result of
the Arsenic Review Panel's analysis of the data for the key toxicodynamic response,
uroepithelial cell cytotoxicity, the consensus was the EPA could assemble a case for
toxicodynamic equivalency between the test species, rats, and humans from existing
experimental data. In the context of EPA and IPCS guidelines, this finding could be
incorporated in the assessment as a reduction of the toxicodynamic component of the
interspecies uncertainty factor, which is 3, to a value of one. The application of
uncertainty factors has also been addressed in the Panel's response to question CI. Fof
the key pharmacodynamic response, uroepithelial cell cytotoxicity, the consensus was the
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EPA could assemble a case for pharmacodynamic equivalency between the test species,
rats, and humans from existing oxporimontal data. In tho context of EPA and IPCS
guidelines, this finding could be incorporated in the assessment as a reduction of the
pharmacodynamic component of tho interspecies uncertainty factor, which is 3, to a value
of one.
[{JT and MM: There is a question of how the issue of the Safety Factor of 10
should be handled. This issue is in common with the discussions here in 3.5.1
(i.e., Dl) and 3.4.1 (i.e., CI). The issue has been dealt with in the two sections as
having PD and PK components and there is a suggestion that the Safety Factor
can be reduced. There is an issue of whether to suggest some factor that the
components could be reduced to or just to suggest to EPA that they should
consider reducing the factor. The issue needs to be discussed at the Panel
meeting. AGAIN, WE NEED TO POINT OUT THIS IS A POLICY ISSUE
THAT THE PANEL ADVISES UPON—CROSS WALK TO CI --SEE
SECTION IN 3.4.1 FOR HOW THAT WAS DONE],
While it was the opinion that rats might deliver a higher dose of the proximate
toxicant, DMA111, to the bladder for a given dose of DMAV than humans, the committee
recognized that there was insufficient data on the comparative dosimetry for these species
to make any conclusive statements about species differences in pharmacokinetics. There
appears to be emerging data on DMAV kinetics which might be brought to bear on the
question and the agency is encouraged to consider these data with respect to
pharmacokinetic differences between the species and the characterization of this
component of uncertainty in the dose response assessment.
{MM}(The conclusion drawn in this paragrpha seems to be somewhat at odds with
the panel conclusions in Al, A2 and CI as I read it. It is also somewhat at odds with
the discussion of safety factors in CI. Basically, it boils down to whether or not the
panel believes that the scientific data points to humans' metabolism of As leading to
less toxic species, and as such putting them at less risk than rats. If that is the case the
safety factor could be reduced. I think this either needs to be resolved, and the two
sections brought into harmony, or if there is not consensus then this needs to be
stated. What I think would be a mistake is to have one section (CI) saying to reduce
the safety factor for toxicokinetics ad another section (Dl) saying that there is not
sufficient data to do this.
3.5.2. Implementation of the recommendations of the NRC (2001)
"EPA has determined that the most prudent approach for modeling cancer risk
from exposure to iAs is to use a linear model because there are significant
remaining uncertainties regarding which of the metabolite(s) may be the ultimate
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carcinogenic moiety and whether or not mixtures of toxic metabolites interact at
the site(s) of action" (USEPA, 2005A).
Does the panel concur with the selection of a linear model following the
recommendations of the NRC (2001) to estimate cancer risk at this time?
Please discuss your response in light of the highly complex mode of action for
iAs with its metabolites.
D2: Implementation of the recommendations of the NRC (2001): There is a
lack of adequate human data at the lower range of iAs due to limitations in
epidemiologic studies conducted to date. These studies have been discussed in
response to charge question C-2. In summary, there have been a number of studies in
different populations across different countries that seem to support a possible linear
dose-response between exposure from drinking water and internal cancer risks
(particularly in Taiwan, Chile and Argentina). However, the dose-response
relationships are observed at higher exposure levels (>100 ppb). Although some
recent studies have included populations with exposures in the lower range (<100
ppb), they are not appropriate for using in dose-response analysis for lower exposure
levels since they have problems related to study design, exposure assessment and
statistical power. Estimations of low dose risk based on studies in populations with
only low dose exposure are unstable with high uncertainty and studies are
underpowered (Lamm et al, 2004; Bates et al, 2003; Steinmaus et al, 2003). For
example, in the Lamm el al. (2004) [PLEASE PROVIDE A FULL CITATION FOR
THIS LAMM 2004] ecological study, exposure assessment is not only highly
problematic given that a single median county-level exposure value is assigned to all
the person-years contributed by each county in the analysis, but 82% of the 133
counties are assigned exposure levels of 3-5 ug/L with only 6 counties assigned
values between 15 and 60 ug/L. A recent follow-up of the Taiwanese cohort reports a
monotonic trend in lung cancer risk for exposure to arsenic levels ranging from <10
to 700 ug/L, however this study also has limited power to examine the form of the
dose-response relationship within the 10-100 ug/L range (Chen et al 2004). There is
no human data available that is adequate to characterize the shape of the dose
response curve below a given point of departure.
At present the experimental evidence on mode of action of inorganic arsenic
supports a possible non-linear dose-response at low exposure levels yet there is no
clear indication of what shape a non-linear dose-response would take for application
to human cancer risks at low exposures (<50 or 100 ppb). In examining the dose-
response relationships of arsenicals in inducing mutagenic responses (including
effects thought to be clastogenic in nature), it is clear that effects are only seen at
doses that induce cytotoxicity. This implies a threshold (Rossman, T.G. 2003).).
Until more is learned about the complex properties and MO As of iAs and its
metabolites there is insufficient justification for the choice of a specific non-linear
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form of the dose-response relationship. Under these circumstances, the EPA's 2005
Guidelines for Cancer Risk Assessment are clear that linear extrapolation below the
point of departure is the method to be used.
Although the EPA has chosen a linear model for the arsenic dose component of
the hazard model for lung and bladder cancer, the Panel encourages the Agency to
test the sensitivity of the assumption of linearity by comparing its corresponding
estimate of excess life risk to an alternative hazard model that has a dose contribution
that is multiplicative and quadratic in form. The following equation is the form of the
model that NRC (2001) found to have best fit to the data based on the Akaike
Information Criterion (AIC):
[Corrected equation follows:]
c = exp(a] + a2 ¦ agej + a;, ¦ age~) • exp(j3() + (3X ¦ dose + j32 ¦ dose2)
Summary—F In summary, the Panel recognizes the potential for a highly complex
mode of action of iAs and its metabolites, but until more is learned about the complex
PKPD properties of iAs and its metabolites there is insufficient justification for the
choice of a specific nonlinear form of the dose-response relationship. Based on this
and the EPA's 2005 Guidelines for Cancer Risk Assessment, the final
recommendation of NRC (2001) to base current risk assessments on a linear dose
response model that includes the SW Taiwan population as a comparison group
seems the most appropriate approach. However, the Panel also recommends a)
performing a sensitivity analysis with different exposure metrics with the subgroup of
villages with more than one well measurement; b) using a multiplicative model that
includes a quadratic term for dose, as performed by NRC (2001).
3.5.3. EPA Model Re-implementation
"EPA re-implemented the model presented in the NRC (2001) in the language R
as well as in an Excel spreadsheet format. In addition, extensive testing of the
resulting code was conducted" (USEPA, 2005a).
Please comment upon precision and accuracy of the re-implementation of
the model.
Question D.3 EPA re-implemented the model presented in the NRC(2001) in
the language R as well as in EXCEL spreadsheet format. In addition, extensive testing
of the resulting code was conducted. "Please comment on the precision and accuracy
of the re-implementation of the model."
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Pre-meeting Comments/Clarifications on the Question
Question D-3 suggests that the estimation of the dose-response model and the
hazard assessment were originally programmed in the R language. Page 63 of the issue
paper indicates that the Poisson hazard model was originally estimated in the R language
(optim routine) but neither the main text of the paper nor its appendices provided any
additional information. A clarifying question from the panel through the Designated
Federal Officer:
" The reference to the implementation in R in question D.3 is outdated, and should
have been removed. This was an oversight on EPA's part. The model
implementation in Excel is oar implementation of record, and was used to
prepare the results in the draft toxicological review. We would ask the Panel to
please review and comment only on the implementation in Excel. (Background:
EPA did originally implement its model in R. However we found that version to
be not very transparent, and hard to debug. We then re-implemented the model in
Excel, found and corrected some errors, and used that corrected version to
prepare the tox review. While Excel may not be the best choice fi'om the
standpoint of numerical accuracy, it is greatly superior in the transparency of the
implementation, and is powerful enough to perform the entire model calculation
from start to finish, even including the nonlinear optimization. Once the Panel is
satisfied that the implementation in Excel is correct and appropriate, then the
model can be re-implemented in R or some other numerically superior
language.) "
The Agency staff is to be commended for deciding to test its original R-language
version of the model program through a separate implementation in EXCEL. The
EXCEL version serves as a check of programming performed in alternative systems (e.g.
R, SPlus ) and provides transparency for review by non-specialists. For the calculations
of hazard and excess risk implemented in this model, the EXCEL computations will
provide sufficient numerical accuracy. If the EPA returns to another programming
environment, it should begin with the original model formulas and not simply transcribe
the EXCEL model program. As a debugging and error-checking tool, comparisons of
intermediate results from the two model implementations should be performed to verify
the equivalence of the models.
Overview of the EXCEL spreadsheet implementation of the model: The EXCEL
model implementation is described in Appendix B (pages 105-106) of the Issue Paper.
The Issue Paper (page 65) referenced a URL, www.epa.gov/waterscience.sab that proved
to be not available. EPA staff notified the panel of the correct address,
http://epa.gov/waterscience/sab/. The Issue Paper suggests that a listing is provided of
the variable and parameter input fields in Table B-3 but the current draft of the Issue
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Paper did not include this table. The fields in the spreadsheet model were interpreted by
the Panel based on the description provided in the text of the Issue Paper and general
understanding of the model fitting procedure employed.
The spreadsheet model requires two Excel files and associated macros. The first
of these is MCCancerfit.XLS. This workbook consists of eight worksheets in four pairs
(e.g. fblad and MC fblad for female bladder cancer) that cover the two cancers of interest
(lung and bladder) and gender (male, female). The initial worksheet (e.g. fblad) in each
of the four cancer/gender pairs contains the input data for fitting the hazard model. The
first step in the model fitting algorithm is to employ the EXCEL Solver to find initial
values of al,a2,a3 and P (Cells G2:G5) that maximize the Poisson likelihood under the
following model:
[Corrected equation follows]
c = exp(flj + a2 • agei + a;, ¦ age~ )•(!+/?• dose)
This is the model described by the EPA in the Issue Paper and is one of two models that
appeared to provide best fit to the data based on the Akaike Information Criterion (NRC,
2001).
The second worksheet in each the four disease/gender pairs (e.g. MC fblad) is
used in conjunction with the initial starting values, generated by Solver and stored in Cell
N2, to simulate the empirical Bayes posterior distribution of the model parameters based
on a set of 1000 random perturbations of the coefficient vector (al,a2,a3, P) about the
maximum likelihood estimates found using Solver. The perturbation involves
independent, random, and uniformly distributed deviations of the coefficient estimates in
a relative range of +/- 10% about the point estimates. Parameter draws outside this range
were not performed since the posterior likelihood takes on a near zero value outside the
+/- 10% of MLE boundaries. The corresponding macro (e.g. mcfblad) is then invoked
and uses the observed data and the set of perturbed coefficient values to predict values of
the posterior log4ikelihood for each of the 1000 draws. The empirical Bayes estimate of
the slope parameter and its lower confidence limit are then estimated based on the mean
and standard deviation of the simulated posterior distribution using the following
equations.
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2"j
L,
b =
j=i
L„
1000
I
L,-
1L*
sd(b) = sqrt
1000
y
iooo
999
with,
UCL(b) = b +2- sd(b)
L,
L.
(b, ~b)'
z
L,.
j-1 ^max
The estimated UCL(b) is then copied to the Bier.xls spreadsheet which implements
the BIER.IV computations of excess lifetime risk.
Based on its review, the Panel noted that for the given data inputs, the empirical
Bayes estimation algorithm programmed in the MCCancerFit.xls spreadsheet does match
the model form and general description of the parameter fitting algorithm outlined in the
Issue Paper.
The Panel recommends that the EPA verify the data on "person years of
exposure" for the male and female controls (Southwestern Taiwan). There is no
particular evidence that these values are in error but they exhibit a demographic
relationship that suggests a check on the accuracy of the data inputs is prudent. As
presently input, female person years of exposure for five year age groups are generally
less than that for males up to about age 60, a fact that is not consistent with general adult
population structures and dynamics. These EPA data inputs agree with Morales, et al.
(2000) for the reference population but the question of the gender balance in these data
should be investigated to be confident that these inputs correspond to the correct
population values. In general, the panel recommends that all tables of model data inputs
be published in appendices to the Issue Paper so that reviewers can independently
reference and verify the critical inputs to the hazard and excess risk analysis.
{GMa}(Maybe we should not emphasize the problem of male/female
imbalance compared to other countries. I've looked at World Bank data several
years ago and found more male children than female. I'm not sure that occurred
because of biology or other reasons. However, if true in Taiwan as in mainland
China then it would set the stage for more males than females. Certainly a check
is worthwhile.)
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{SHa}(This gender differential may be a result of high female
mortality associated with high maternal death rates - without information
to the contrary for this subpopulation I would temper the statements. I
can't get data on line for relevant time periods but what's there suggests
very high maternal mortality was likely. Perhaps add .population
structures and dynamics in the absence of high maternal mortality.")
The MCCancerft.xls spreadsheet includes an adjustment of 50 |ig/day of arsenic
from food intake. Based on the formula provided on page 103 of the Issue Paper, the
current model assumes a combined daily intake of 2 liters/day of cooking and drinking
water. The Issue Paper suggests that the current analysis uses 30 (j,g/day of arsenic from
this source. Although the Issue Paper notes the NRC (2001) finding that dietary intake
had no significant effect on the estimated cancer slope factor, the apparent discrepancy
between the value of 30 (j,g/day cited in the Issue Paper and the 50 (j,g/day value used in
the spreadsheet model should be resolved. The model does not allocate an arsenic food
input for the control population. This decision presumes food-based intake of arsenic
originates from cooking water only and is an assumption that should be subjected to a
sensitivity analysis.
The second EXCEL workbook in the risk assessment model employs estimates of
the dose response model parameter, p, and its upper bound to evaluate excess lifetime
risk under the Bier-IV formula. The Bier.xls workbook includes four worksheets, one for
each cancer type by gender combination (flung, mlung, fblad, mblad). The estimates of
the linear dose response parameter and its estimated 95% UCL (see above) are manually
input using the value obtained from the corresponding worksheet in MCCancerFit.xls.
The excess risk is computed in cell T15. Solver can be applied to the dose value in Cell
Til (not U10 as indicated on Page 105 in the Issue Paper) to establish the dose level
requirements for user-specified values of excess risk (i.e., ED0i).
The notation on Page 102 in the Issue Paper does not distinguish between total
survivorship (Si) and survivorship adjusted for the added risk of cancer. However, the
spreadsheet implementation of the model decomposes survival into the product of
baseline survival and a survival factor that reflects excess cancer deaths due to arsenic
exposure in prior years. The version of the spreadsheet downloaded from the Office of
Water website has calculation of cancer-specific survival (Row 13) appearing to
incorporate mortality through time I, not time 1-1 as indicated in the Issue Paper. This
should be checked. {StH} , but in general t The calculation of baseline survival appears
to be correct with survival at time I including only mortality through the end of time
period 1-1. Other than this exception, calculation of Excess Risk follows the Bier IV
formula.
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The Bier.xls spreadsheet implementation of the Bier.IV excess risk calculation
includes a 3-fold divisor which is assumed included to allow transforming of the risk to a
U.S. population base (based on the assumption that exposure per kg is 3-fold higher in
the SW Taiwanese population compared to the US population). This scaling occurs in
the calculation of the age-specific cancer hazard (Row 11). This multiplier should be
documented and included as a factor in future sensitivity studies. Since this is truly a
model parameter it should be identified as a distinct input on the spreadsheet interface
and not simply embedded in the calculations.
Following the series of checks and minor corrections to the model listed above,
the Panel encourages the Agency to extend its testing of the model's sensitivity to
alternative models forms and model assumptions. Specific areas where the Panel felt
additional sensitivity testing is warranted include:
• A Monte Carlo analysis in which the individual well concentrations for 22
villages with multiple wells are taken into account. The Panel recognizes the
difficulties with this approach including the issue of how best to allocate cases to
wells for those villages having multiple wells. {StH} A practical approach to this
sensitivity analysis has been described in the Panel's response to Question 3.4.2
(above).
• MCCancerFit.xls :
o Examine the sensitivity of the model to the choice of the reference
population (SW Taiwan),
o Examine the sensitivity of model results to the assumption that the
reference population has 0 intake of arsenic via food.
{JY} This recommendation needs some expansion,
o A contrast of results for the linear dose model employed in this program to
an alternative hazard model that has a dose contribution that is
multiplicative and quadratic in form. This is the form of the model that
NRC(2001) found to have best fit to the data based on the Akaike
Information Criterion (AIC):
[Corrected equation follows]
c = exp(a] + a2 ¦ agej + a;, ¦ age~) • exp(j3() + (3X ¦ dose + j32 ¦ dose2)
• Bier.xls
o The Panel recommends a sensitivity analysis in which the age groupings
used to estimate the baseline hazard and excess lifetime risk are altered. A
logical choice is to test the sensitivity of the model results to using 10-year
groupings (e.g. 20-29, 30-39) in both spreadsheets.
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The exposure/kg parameter used to transfer the dose/response model from
the original SW Taiwanese population to a U.S. general population should
be a major driver in the computation of excess lifetime risk. In preparing
its final risk assessment, the EPA should conduct a sensitivity analysis to
determine how the choice of 3 for the conversion factor impacts the final
estimates of excess lifetime risk.
3.5.4. Available literature describing drinking water consumption rates for
the southwestern Taiwanese study population:
"NRC (2001) stated that the drinking water consumption rate, as well as
variability of that rate in both US and Taiwanese populations, are important
factors to consider. In calculating risk estimates for U.S. populations exposed to
arsenic through drinking water, NRC used a drinking water consumption rate of 1
L/day for the US population and two possible consumption rates for the
Taiwanese population: 1 L/day (identical to the US population) and 2.2 L/day
with little or no supporting rationale. Since publication of NRC 2001, a number
of new studies have become available and are summarized in the Cancer Slope
Factor Workgroup Issue Paper. Agency reviews of the relevant literature suggests
that the mean drinking water (for the Taiwanese study population) consumption
rate is between 1 to 4.6 L/day. EPA's current cancer modeling includes water
intake adjustments for 2.0 and 3.5 L/day" (USEPA, 2005a).
What drinking water value does the panel recommendfor use in deriving
the cancer slope factor for inorganic arsenic?
GENERAL COMMENTS:
{SHa}(.. .1 do think that we need to consider whether we really want to
recommend analyses based on extremes measured in populations (whether of
water consumption, food consumption or arsenic levels in water). Scientifically,
we probably do not, and consistency in recommending high and low values that
are reflective of a measure of standard deviations would be encouraged.)
D4. Available literature describing drinking water consumption rates for
the southwestern Taiwanese study population: Assumptions about water
consumption levels in the US and in Taiwan have a substantial impact on the risk
assessment. Relative to US consumption, overestimating water consumption in Taiwan
decreases risk estimates and underestimating consumption increases risk estimates.
Evidence for sex differences in consumption is limited, but considerable within-
population variability in consumption occurs (NRC, 2001).
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US water consumption data are obtained from comprehensive US surveys
including surveys by USD A and as part of NHANES (as cited in EPA 2005), among
others. These studies provide information on tap water consumption as well as water
consumption attributable to other beverage consumption and food preparation. Estimates
of mean daily drinking water consumption and total water consumption (including water
used in food preparation) range from 1.0 to 2.8 and from 1.2 to 3.2 respectively.
In comparison, information on water-consumption in Taiwan derives from a small study
by Yang and Blackwell and an EPA informal, anecdotal assessment (as cited in EPA
2005) that include only information on drinking water consumption. Information on
water consumption in South Asia, another world region with high arsenic levels in the
water supply, is available from a large population based survey in India (Chowdhury et
al., 2001 cited in EPA 2005) and a small study from Bangladesh (Watanabe et al., 2004).
The South Asian studies include information on water consumption associated with food
preparation. Although similar in socioeconomic characteristics, the diet and climate differ
in Taiwan and South Asia, with temperatures higher in South Asia. These studies report
mean daily drinking water intake of 1 to 3.5 L, with an additional 1 L associated with
food preparation.
We recommend that:
a) the EPA incorporate variability parameters for individual water consumption in
their analysis for the Taiwanese population as they have done for the US population
as per NRC recommendation;
b) given that assumptions about water consumption are an important source of
variability in the risk estimates, that the EPA conduct sensitivity analyses of the
impact of using a range of consumption values for the Taiwanese population.
c) Data on sex differences in consumption in Taiwan are limited, and a better
justification for assuming different consumption levels by sex is needed, particularly
given lack of sex difference in consumption in US and observed in studies from other
countries (Watanabe et al., 2004). In the absence of such a justification, the panel
recommends an additional sensitivity analysis to examine the impact of equalizing the
sex-specific consumption level.
d) The source of data for intake from other beverages and cooking water needs to be
more fully discussed and documented. Specifically, the document should more clearly
articulate how different sources of water intake are incorporated into the risk model
including beverages other than water (e.g. green tea) and water used in food
preparation. Clarification of both the assumed consumption level and how water
consumption and consumption variability is introduced within the model is needed.
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3.5.5. Selection of an estimate of dietary intake of arsenic from food:
"The issue of intake of arsenic from food (e.g., dry rice, sweet potatoes) has been
distinguished from the issue of intake of arsenic from drinking water. The NRC
addressed the issue of arsenic in food by determining how sensitive the
calculation of ED0i was to the consumption rate. NRC found that changing the
consumption rate from 50 |ig/day to 30 |ig/day did not change the calculated ED0i
significantly (about 1% difference). Since the publication of NRC 2001, a
number of new studies have become available, summarized in the Cancer Slope
Factor Workgroup Issue Paper. EPA's current cancer modeling includes dietary
intake adjustments for 0, 10, 30, and 50 |ig/day" (USEPA, 2005a).
What background dietary intake (of arsenic) value does the panel
recommend for both the control population and study population of
Southwestern Taiwan used in deriving the cancer slope factor for
inorganic arsenic?
Question D5. Three studies summarizing arsenic consumption per day derived from
food in areas of high arsenic intake are listed in Table 4(1). Based on NRC
recommendations, US EPA used a range of 30-50 |ig per day arsenic intake from dry rice
(uncooked) and dried yams in the diet of Southeastern Taiwan that also was based on the
work of Schoof et al., 1998 (2) as listed in this table. In materials presented and
submitted to the committee (3), Dr. Schoof, however, affirmed that these 1998 data were
obtained during the dry season in Taiwan when arsenical pesticides were not in use.
Findings in the soil (5 ppm) indicated that arsenical pesticides had not been applied at
this time even though it is known that arsenic was applied to soil (and taken up in food
crops) during the wetter season. Thus these data may underestimate the dietary arsenic
intake from food in this population. Daily intake of arsenic from food obtained by
Chowdhury et al (2001) and Watanabe et al., (2004) suggest arsenic intakes of from 120
to 285 |ig/day from food in Bangladesh and Indian populations exposed to high levels of
naturally occurring arsenic. Although these data are not derived specifically from the
area of Taiwan studied, they indicate along with ancillary information presented here and
elsewhere that dietary exposure from food may be somewhat higher than previously
thought. Raw rice, a staple of the area, has been shown in other studies to contain among
the highest iAs values in food (4). In comparison, daily total intake of iAs at the 10th and
90th percentiles in the US are estimated to be 1.8 to 11.4 |ig/day for males and 1.3 to 9.4
|ig/day for females (5). It is clear that the adjustment for background Asi intake from
food, given that the total exposure dose does matter in terms of toxicity and cancer
induction, is extremely important.
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Sensitivity Analyses. It is recommended that a range of values from at least 50
|ig/day up to perhaps as high as 100 200 |ig/day for males and perhaps somewhat lower
{SHa}—(The data do not support 200 for women or child/young adult exposures,
and baed on the data represents a most extreme value)
for females, be run in a sensitivity analysis to assess the impact of this range of dietary
intakes on risk of lung and bladder cancer from exposure via drinking water in this
population.
{SHa}(Re: the following sentences in the paragraph - "It is important not to insert
too many presumptions where we have no data. Although, it is reasonable to
assume that men had the "best" diet - it is much more difficult to understand how
that translated into arsenic consumption. Women may well have had less fish but
also considerably less total food. Thus it is not possible to assess quantitatively
the implications of "relatively more rice" in terms of its impact on women's
arsenic consumption.—She suggests the following deletion:)
With regard to selection of the highest value to run in the sensitivity analysis, it is of note
that according to information presented from Yang and Blackwoll, Taiwanese males in
the study population were afforded the "best" diet (presumably higher in protein) thus
women and perhaps children may have ingested relatively more rice and loss protein
thereby perhaps also exposing them to relatively high levels of total arsenic levels from
diet The cancer risk model {SHa}(Clarify this sentence with edits shown) thus needs to
be weighted with a wider range of iAs food values above 50 |ig/day to determine if there
is a change in slope as a result
{SHa}(Clarify what "in slope" is expected in the model here).
{SHa}(Given the lack of data on consumption in Taiwan and absolutely no
information on variability in consumption by village, I think this line should be
struck—It would be excellent to do if there were any relevant data - but none
have been presented.)
In addition, if possible, an analysis needs to be considered to determine the impact of
differences in iAs background (from dietary sources) for each village in the Taiwan
study.
Such a sensitivity analysis of the impact of dietary arsenic uptake using a range of
data from high arsenic-exposed populations is unlikely to introduce larger uncertainty
than the myriad dietary differences - protein deficiency, Se, Zn, folate deficiency etc. -
between this Taiwanese population and the US population
It is known that fish contain some portion of iAs further pointing to the need for
the sensitivity analysis described above. Seafood may also contain DMA that may also
contribute to background exposure from food relative to water sources (Huang, et al.,
2003).
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Much greater rigor needs to be applied in discussing and presenting documented
data sources and making clear the basis on which assumptions are being made and the
relative strength of those assumptions. Comparisons of the impact of differing levels of
iAs intake from food between the exposed and reference population (if one is used in the
analysis) need to be made on the basis of absolute risk as well as relative risk.
{CH}(I suggest either deleting the last sentence, or expanding to explain what is
meant by "on the basis of absolute risk as well as relative risk")
An awareness and discussion of methodological issues {JY} around related to
reported arsenic concentrations in food, that These are likely somewhat dependent upon
differential extraction processes and different analytical procedures used in different
laboratories on different food stuffs, noods to bo included. Further, laboratory extraction
procedures are not usually designed, however, to equate with that portion of arsenic in
food that may be bioavailable. The bioavailability issue is an important area for
research. Additionally, a clearer statement of the limited data on daily dietary intake is
needed.
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advice or recommendations of the SAB, nor has it been reviewed or approved by the Chartered SAB. This
draft report does not represent EPA policy. December 27, 2005
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advice or recommendations of the SAB, nor has it been reviewed or approved by the Chartered SAB. This
draft report does not represent EPA policy. December 27, 2005
Dopp, E., L. M. Hartmann, et al. (2004). "Uptake of inorganic and organic derivatives of
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advice or recommendations of the SAB, nor has it been reviewed or approved by the Chartered SAB. This
draft report does not represent EPA policy. December 27, 2005
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advice or recommendations of the SAB, nor has it been reviewed or approved by the Chartered SAB. This
draft report does not represent EPA policy. December 27, 2005
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advice or recommendations of the SAB, nor has it been reviewed or approved by the Chartered SAB. This
draft report does not represent EPA policy. December 27, 2005
Meacher DM, DB Menzel, MD Dillencourt, LF Bic, RA Schoof, LJ Yost, JC Eickhoff,
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advice or recommendations of the SAB, nor has it been reviewed or approved by the Chartered SAB. This
draft report does not represent EPA policy. December 27, 2005
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Do Not Cite or Quote - This draft report is a work in progress that does not reflect final consensus
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Do Not Cite or Quote - This draft report is a work in progress that does not reflect final consensus
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Do Not Cite or Quote - This draft report is a work in progress that does not reflect final consensus
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draft report does not represent EPA policy. December 27, 2005
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Do Not Cite or Quote - This draft report is a work in progress that does not reflect final consensus
advice or recommendations of the SAB, nor has it been reviewed or approved by the Chartered SAB. This
draft report does not represent EPA policy. December 27, 2005
4. ACRONYM TABLE
[Explain all acronyms used in a table format]
ACRONYM EXPLANATION
iAS Inorganic Arsenic
Crosswalk of Charge Questions with
Report Sections
Charge Question
Report Section
A1
3.2.1
A2
3.2.2
B1
3.3.1
B2
3.3.2
B3
3.3.3
CI
3.4.1
C2
3.4.2
D1
3.5.1
D2
3.5.2
D3
3.5.3
D4
3.5.4
D5
3.5.5
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