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TOXICOLOGICAL REVIEW

 

OF 

ACRYLONITRILE

(CAS No. 107-13-1)

 

 

In Support of Summary Information on the 

Integrated Risk Information System (IRIS)

January, 2010

NOTICE

This document is an Interagency Science Consultation draft. This information is distributed 

solely for the purpose of pre-dissemination peer review under applicable information quality 

guidelines. It has not been formally disseminated by EPA. It does not represent and should not 

be construed to represent any Agency determination or policy. It is being circulated for review 

of its technical accuracy and science policy implications. 

 

U.S. Environmental Protection Agency 

Washington, DC
ii DRAFT - DO NOT CITE OR QUOTE 

DISCLAIMER

 This document is a preliminary draft for review purposes only. This information is 

distributed solely for the purpose of pre-dissemination peer review under applicable information 

quality guidelines. It has not been formally disseminated by EPA. It does not represent and 

should not be construed to represent any Agency determination or policy. Mention of trade 

names or commercial products does not constitute endorsement or recommendation for use. 
iii DRAFT - DO NOT CITE OR QUOTE 

CONTENTS —TOXICOLOGICAL REVIEW OF ACRYLONITRILE 

(CAS No. 107-13-1) 

LIST OF TABLES................................................................................................................... vii 

LIST OF FIGURES ................................................................................................................ xvi 

LIST OF ABBREVIATIONS AND ACRONYMS ............................................................. xviii 

FOREWORD ......................................................................................................................... xxii 

AUTHORS, CONTRIBUTORS, AND REVIEWERS ........................................................ xxiii 

1. INTRODUCTION .................................................................................................................1 

2. CHEMICAL AND PHYSICAL INFORMATION ...............................................................3 

3. TOXICOKINETICS ..............................................................................................................5 

3.1. ABSORPTION ...................................................................................................................5 

3.1.1. Studies in Humans .....................................................................................................5 

3.1.2. Studies in Animals .....................................................................................................5 

3.2. DISTRIBUTION ................................................................................................................7 

3.3. METABOLISM................................................................................................................14 

3.3.1. Oxidation of AN to CEO .........................................................................................15 

3.3.2. Interaction of AN with GSH ....................................................................................23 

3.3.3. Covalent Binding of AN and Its Metabolites to Subcellular Macromolecules........28 

3.4. ELIMINATION................................................................................................................34 

3.4.1. Studies in Humans ...................................................................................................34 

3.4.2. Studies in Animals ...................................................................................................34 

3.4.2.1. Exhalation ....................................................................................................... 34 

3.4.2.2. Fecal Excretion ............................................................................................... 35 

3.4.2.3. Urinary Excretion............................................................................................ 35 

3.5. PHYSIOLOGICALLY BASED TOXICOKINETIC MODELS .....................................40 

4. HAZARD IDENTIFICATION............................................................................................53 

4.1. STUDIES IN HUMANS—EPIDEMIOLOGY AND CASE REPORTS.........................53 

4.1.1. Oral Exposure ..........................................................................................................53 

4.1.2. Inhalation Exposure .................................................................................................53 

4.1.2.1. Acute Exposure............................................................................................... 53 

4.1.2.2. Chronic Exposure............................................................................................ 55 

4.1.3. Dermal Exposure ...................................................................................................115 

4.1.3.1. Acute Exposure............................................................................................. 115 

4.1.3.2. Chronic Exposure.......................................................................................... 117 

4.1.4. Ocular Exposure.....................................................................................................117 

4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 

ANIMALS—ORAL AND INHALATION..................................................................120 

4.2.1. Oral Exposure ........................................................................................................121 

4.2.1.1. Subchronic Studies........................................................................................ 121 

4.2.1.2. Chronic Studies............................................................................................. 127 
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4.2.2. Inhalation Exposure ...............................................................................................156 

4.2.2.1. Subchronic Studies........................................................................................ 156 

4.2.2.2. Chronic Studies............................................................................................. 157 

4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL AND INHALATION..164 

4.3.1. Studies in Humans .................................................................................................164 

4.3.2. Studies in Animals .................................................................................................167 

4.3.2.1. Oral Studies................................................................................................... 167 

4.3.2.2. Inhalation Exposure ...................................................................................... 175 

4.3.2.3. Intraperitoneal Administration...................................................................... 177 

4.3.3. In Vitro Studies ......................................................................................................179 

4.4. OTHER DURATION- OR ENDPOINT-SPECIFIC STUDIES ....................................180 

4.4.1. Acute Toxicity Data...............................................................................................180 

4.4.1.1. Effects of AN on the GI Tract....................................................................... 184 

4.4.1.2. Effects of AN on the Kidney......................................................................... 186 

4.4.1.3. Effects of AN on the Adrenal Gland............................................................. 186 

4.4.1.4. Neurotoxic Effects of AN ............................................................................. 187 

4.4.1.5. Effects on Hearing ........................................................................................ 188 

4.4.2. Immunotoxicity of AN...........................................................................................191 

4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUPPORT OF THE MODE OF 

ACTION .......................................................................................................................196 

4.5.1. Mode-of-Action Studies.........................................................................................196 

4.5.1.1. Noncancer Endpoints .................................................................................... 196 

4.5.1.2. Cancer Effects............................................................................................... 210 

4.5.2. Genotoxicity Studies..............................................................................................223 

4.5.2.1. Studies in Humans ........................................................................................ 223 

4.5.2.2. In Vivo Tests in Mammals............................................................................ 227 

4.5.2.3. Short-term Tests: Bacteria, Fungi, Drosophila, Others................................ 230 

4.5.2.4. Mammalian Cell Short-term Tests................................................................ 235 

4.6. SYNTHESIS AND EVALUATION OF MAJOR NONCANCER EFFECTS AND 

MODE OF ACTION—ORAL AND INHALATION ..................................................255 

4.6.1. Oral ........................................................................................................................255 

4.6.2. Inhalation ...............................................................................................................259 

4.6.3. Mode-of-Action Information .................................................................................263 

4.6.3.1. GI Effects ...................................................................................................... 263 

4.6.3.2. Neurotoxicity ................................................................................................ 264 

4.6.3.3. Reproductive/Developmental Effects ........................................................... 266 

4.6.3.4. Hematological Effects................................................................................... 267 

4.6.3.5. Immunotoxicity............................................................................................. 268 

4.6.3.6. Covalent Binding to Sulfhydryl Groups ....................................................... 268 

4.7. EVALUATION OF CARCINOGENICITY—SYNTHESIS OF HUMAN, ANIMAL, 

AND OTHER SUPPORTING EVIDENCE, CONCLUSIONS ABOUT HUMAN 

CARCINOGENICITY, AND LIKELY MODE OF ACTION.....................................269 

4.7.1. Summary of Overall Weight of Evidence..............................................................269 

4.7.2. Synthesis of Human, Animal, and Other Supporting Evidence.............................269 

4.7.3. Mode-of-Action Information .................................................................................272 

4.7.3.1. Hypothesized Mode of Action: Direct Mutagenic Mode-of-Action............ 273 

4.7.3.2. Experimental Support for the Hypothesized Mode of Action ...................... 273 

4.7.3.3. Other Possible Modes of Action ................................................................... 284 

4.7.3.4. Possible Modes of Action for Forestomach Tumors .................................... 292 
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4.7.3.5. Possible Modes of Action for Hepatomas..................................................... 293 

4.7.3.6. Possible Modes of Action for Tumors of Intestines, Tongue, Zymbal Gland, 

and Harderian Gland..................................................................................... 294 

4.7.3.7. Possible Modes of Action for Lung Cancer.................................................. 294 

4.8. SUSCEPTIBLE POPULATIONS AND LIFE STAGES...............................................294 

4.8.1. Possible Childhood Susceptibility .........................................................................294 

4.8.2. Possible Geriatric Susceptibility............................................................................297 

4.8.3. Possible Gender Differences..................................................................................298 

4.8.4. Genetic Polymorphisms .........................................................................................301 

4.8.4.1. CYP450......................................................................................................... 301 

4.8.4.2. Glutathione S-transferases ............................................................................ 302 

4.8.4.3. EH ................................................................................................................. 302 

5. DOSE-RESPONSE ASSESSMENTS...............................................................................304 

5.1. ORAL REFERENCE DOSE (RfD) ...............................................................................304 

5.1.1. Choice of Principal Study and Critical Effect........................................................304 

5.1.2. Methods of Analysis—Including Use of PBTK Modeling....................................308 

5.1.2.1. PBTK Modeling............................................................................................ 308 

5.1.2.2. BMD Modeling............................................................................................. 309 

5.1.3. RfD Derivation—Including Application of Uncertainty Factors (UFs) ................314 

5.1.4. Oral Data Array for Noncancer Endpoints ............................................................315 

5.1.5. Previous RfD Assessment......................................................................................318 

5.2. INHALATION RfC........................................................................................................318 

5.2.1. Choice of Principal Study and Critical Effect........................................................318 

5.2.2. Methods of Analysis ..............................................................................................321 

5.2.3. RfC Derivation—Including Application of UFs....................................................322 

5.2.4. Inhalation Data Array for Noncancer Endpoints ...................................................323 

5.2.5. Previous Inhalation Assessment.............................................................................325 

5.3. UNCERTAINTIES IN THE ORAL RfD AND INHALATION RfC............................325 

5.4. CANCER ASSESSMENT .............................................................................................327 

5.4.1. Choice of Study/Data—with Rationale and Justification ......................................327

5.4.2. Dose-Response Data ..............................................................................................328 

5.4.2.1. Human Occupational Data............................................................................ 328 

5.4.2.2. Rat Oral Data ................................................................................................ 329 

5.4.2.3. Rat Inhalation Data ....................................................................................... 333 

5.4.3. Dose-Response Modeling ......................................................................................334 

5.4.3.1. Human Occupational Data............................................................................ 334 

5.4.3.2. Rat Oral Data ................................................................................................ 335 

5.4.3.3. Rat Inhalation Data ....................................................................................... 342 

5.4.4. Cancer Risk Values................................................................................................345 

5.4.4.1. Oral CSFs...................................................................................................... 345 

5.4.4.2. Inhalation Unit Risk...................................................................................... 347 

5.4.4.3. Quantitative Analysis of Early Life Exposure Scenarios.............................. 349 

5.4.5. Uncertainties in Cancer Risk Values ......................................................................359 

5.4.5.1. Oral Cancer Assessment ............................................................................... 359 

5.4.5.2. Inhalation Cancer Assessment ...................................................................... 365 
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6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSE 

RESPONSE......................................................................................................................369 

6.1. HUMAN HAZARD POTENTIAL ................................................................................369 

6.2. DOSE-RESPONSE ........................................................................................................371 

6.2.1. Oral RfD.................................................................................................................371 

6.2.2. Inhalation RfC........................................................................................................372 

6.2.3. Oral CSF ................................................................................................................374 

6.2.4. Cancer Inhalation Unit Risk...................................................................................375 

7. REFERENCES ..................................................................................................................376 

APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC 

COMMENTS AND DISPOSITION............................................................................... A-1 

APPENDIX B. BENCHMARK DOSE CALCULATIONS .................................................B-1 

APPENDIX B-1. NONCANCER ORAL DOSE-RESPONSE ASSESSMENT (RfD): 

BENCHMARK DOSE MODELING RESULTS EMPLOYING THE INCIDENCE OF 

FORESTOMACH LESIONS (HYPERPLASIA AND HYPERKERATOSIS) IN 

MALE AND FEMALE SPRAGUE-DAWLEY RATS, F344 RATS, AND B6C3F1

MICE CHRONICALLY EXPOSED ORALLY TO AN FOR 2 YEARS....................B-1 

APPENDIX B-2. NONCANCER INHALATION DOSE-RESPONSE ASSESSMENT 

(RfC): BMD MODELING RESULTS EMPLOYING THE INCIDENCE DATA FOR 

NONNEOPLASTIC NASAL LESIONS IN RATS EXPOSED TO AN BY 

INHALATION FOR 2 YEARS (TABLES B-6 THROUGH B-9) ..........................B-116 

APPENDIX B-3. CANCER ORAL DOSE-RESPONSE ASSESSMENT: BMD DOSE 

MODELING RESULTS FOR TUMOR INCIDENCE DATA FROM RATS

CHRONICALLY EXPOSED TO AN IN DRINKING WATER.............................B-123 

APPENDIX B-4. CANCER INHALATION DOSE-RESPONSE ASSESSMENT: BMD 

MODELING RESULTS FOR TUMOR INCIDENCE DATA FROM RATS

CHRONICALLY EXPOSED TO AN VIA INHALATION....................................B-246 

APPENDIX B-5. ANALYSIS TO ASSESS COMBINING TUMOR INCIDENCE DATA 

FROM TWO CANCER BIOASSAYS EMPLOYING SPRAGUE-DAWLEY 

RATS ........................................................................................................................B-283 

APPENDIX B-6. ESTIMATION OF COMPOSITE CANCER RISK FROM EXPOSURE 

TO AN BY COMBINING RISK ESTIMATES ACROSS MULTIPLE TUMOR 

SITES........................................................................................................................B-289 

APPENDIX B-7. STATISTICAL ANALYSIS OF BLAIR ET AL. (1998) ....................B-293 

APPENDIX C. PBPK MODEL DESCRIPTIONS AND SOURCE CODE .........................C-1 

APPENDIX D. UNCERTAINTIES ASSOCIATED WITH CHEMICAL-SPECIFIC 

PARAMETERS EMPLOYED IN THE PBPK MODEL FOR AN DOSIMETRY 

IN HUMANS .................................................................................................................. D-1 
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LIST OF TABLES 

3-1. Recovery of radioactivity from male Sprague-Dawley rats exposed to 5 or 100 ppm 

[1-14C]-AN for 6 hours via inhalation.................................................................................... 6

3-2. Recovery of radioactivity after a single gavage dose of 0.1 or 10 mg/kg [1-14C]-AN to 

male Sprague-Dawley rats ..................................................................................................... 6

3-3. Percentage recovery of radioactivity in tissues of male Wistar rats following a single 

oral dose of radiolabeled AN ................................................................................................. 9

3-4. Apparent kinetic parameters of CEO formation from AN in B6C3F1 mice, F344 rats, 

and humans .......................................................................................................................... 20

3-5. Apparent kinetic parameters for glutathione conjugation of AN and CEO at pH 6.5.......... 26

3-6. Glutathione conjugation of AN and CEO with or without microsomal or cytosolic GST 

from rat, mouse, and human liver preparations ................................................................... 26

3-7. Urinary excretion of thioethers derived from AN ................................................................ 38

4-1. Clinical signs in 144 subjects accidentally exposed to AN.................................................. 54

4-2. Distribution of select incidence and mortalities among wage workers and all workers 

at an AN plant ...................................................................................................................... 56

4-3. Distribution of select incidence and mortalities among wage workers and all workers 

at an AN plant ...................................................................................................................... 59

4-4. Distribution of select incidence and mortalities among wage and salary workers at 

an AN plant.......................................................................................................................... 61

4-5. Distribution of select mortalities among exposed workers in two AN plants...................... 63

4-6. Distribution of select mortalities among exposed workers .................................................. 64

4-7. Crude and adjusted hazard ratio estimates for 100 ppm-year increase in cumulative 

exposure ............................................................................................................................... 65

4-8. Hazard ratio estimated for select cancer mortality by lagged cumulative exposure for 

100 ppm-year increase in cumulative exposure................................................................... 66

4-9. Distribution of select mortalities among AN-exposed and unexposed workers .................. 73

4-10. Lung cancer mortality of AN-exposed workers stratified by cumulative dose 

and latency.......................................................................................................................... 74

4-11. Distribution of select mortalities among AN-exposed and unexposed workers ................ 80
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4-12. Distribution of select mortalities among AN-exposed and unexposed workers ................ 83

4-13. Distribution of mortality among AN-exposed workers...................................................... 87

4-14. Summary of relative regression analyses for cancer of the bronchus, trachea, 

and lung .............................................................................................................................. 88

4-15. Distribution of observed lung cancer deaths among AN-exposed workers, using 

regional rates for comparison............................................................................................. 89

4-16. ORs of lung cancer for AN exposure ................................................................................. 93

4-17. Derived all-cancer SMRs for major cohort studies on AN exposure................................. 96

4-18. Derived lung cancer SMRs for major cohort studies on AN exposure .............................. 98

4-19. Industrial AN exposure, levels of AN and thiocyanate in urine, and prevalence of 

physical signs of adverse effects in workers exposed to AN at six acrylic fiber 

factories in Japan .............................................................................................................. 102

4-20. Comparison of reproductive outcomes in wives of exposed and control males at a 

chemical fiber plant .......................................................................................................... 108

4-21. Comparison of reproductive outcomes between exposed and control females at a 

chemical fiber plant .......................................................................................................... 108

4-22. Epidemiology studies of noncancer outcomes among cohorts of workers exposed 

to AN ................................................................................................................................ 117

4-23. Effect on SCV in male Sprague-Dawley rats exposed to AN via gavage for 

12 weeks ........................................................................................................................... 124

4-24. Incidence of nonneoplastic lesions in Sprague-Dawley rats exposed to AN in 

drinking water for 2 years ................................................................................................ 129

4-25. Selected tumor incidences in response to AN administered to Sprague-Dawley rats 

in drinking water for up to 2 years ................................................................................... 130

4-26. Histopathologic location of astrocytomas in the CNS of male Sprague-Dawley rats 

administered AN in drinking water for 2 years................................................................ 132

4-27. Incidence of nonneoplastic lesions in Sprague-Dawley rats exposed to AN in 

drinking water for 2 years ................................................................................................ 134

4-28. Selected tumor incidences in Sprague-Dawley rats exposed to AN in drinking water 

for up to 2 years................................................................................................................ 136
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4-29. Incidence of nonneoplastic lesions in Sprague-Dawley rats exposed to AN by gavage 

for 20 months.................................................................................................................... 138

4-30. Cumulative incidence of tumors in response to AN administered to Sprague-Dawley 

rats by gavage for up to 2 years........................................................................................ 139

4-31. Incidences of nontumorous lesions in F344 rats exposed to AN in drinking water for 

2 years............................................................................................................................... 143

4-32. Selected tumor incidences in F344 rats exposed to AN in drinking water for 2 years .... 144

4-33. Incidence and severity of nonneoplastic lesions in B6C3F1 mice exposed by gavage 

to AN for 2 years .............................................................................................................. 146

4-34. Incidences of selected neoplastic lesions in B6C3F1 mice exposed by gavage to AN 

for 2 years......................................................................................................................... 147

4-35. Incidence of tumors in female Sprague-Dawley rats exposed to AN in drinking 

water for up to 46 weeks .................................................................................................. 151

4-36. Summary of chronic oral toxicity studies of AN: noncancer effects in rats 

and mice ........................................................................................................................... 151

4-37. Summary of chronic oral toxicity studies of AN: cancer effects in rats and mice .......... 153

4-38. Effect on SCV in male Sprague-Dawley rats exposed to AN via inhalation for 

24 weeks ........................................................................................................................... 156

4-39. Incidence of histopathological lesions of the nasal turbinates in Sprague-Dawley 

rats exposed to AN via inhalation for 2 years .................................................................. 158

4-40. Incidence of dose-related noncancerous histopathological lesions in Sprague-Dawley 

rats exposed to AN via inhalation for 2 years .................................................................. 159

4-41. Cumulative incidence of tumors in Sprague-Dawley rats exposed to AN via 

inhalation for up to 2 years............................................................................................... 160

4-42. Comparison of carcinogenic effects of chronic exposure to AN at 60 ppm starting 

either in utero or in adulthood, in Sprague-Dawley rats .................................................. 162

4-43. Incidence of fetal abnormalities among litters of Sprague-Dawley rats following 

maternal exposure to AN on GDs 6–15 ........................................................................... 168

4-44. Morphological alterations in GD 12 fetuses of Sprague-Dawley rats exposed to 

100 mg/kg AN on GD 10 ................................................................................................. 169

4-45. Group-specific reproductive indices in three generations of Sprague-Dawley rats 

receiving AN in drinking water........................................................................................ 172
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4-46. Group-specific pup weights in three generations of Sprague-Dawley rats receiving 

AN in drinking water........................................................................................................ 173

4-47. Incidence of fetal malformations among litters of Sprague-Dawley rats exposed to 

AN by inhalation .............................................................................................................. 175

4-48. Effects of AN on organ weight, clinical chemistry, and biochemical parameters 

when administered to male Wistar rats via inhalation ..................................................... 182

4-49. Time course of the effect of AN administration on [3H]-thymidine uptake into 

mouse splenocytes under the influence of different mitogens in vitro............................. 193

4-50. Summary of immunotoxicity studies of AN..................................................................... 194

4-51. Effect of AN on RBC metabolic intermediates following a single oral dose................... 196

4-52. Detection of N7

-(2-oxoethyl)guanine after i.p. administration of 50 mg/kg AN or 

CEO to male F344 rats ..................................................................................................... 212

4-53. Summary of studies on the mutagenicity/genotoxicity of AN ......................................... 239

4-54. Formation of 8-oxodG in DNA from tissues of male Sprague-Dawley and F344 rats 

exposed to AN in drinking water for 21 days .................................................................. 251

4-55. Summary of studies on the indirect mutagenicity or genotoxicity of AN........................ 253

4-56. Noncancer effects in animals repeatedly exposed to AN by the oral route...................... 235

4-57. Noncancer effects in human workers and animals repeatedly exposed to AN 

by inhalation ..................................................................................................................... 259

4-58. 8-OxodG in brain DNA and brain tumor incidence in male F344 rats exposed to 

AN in drinking water........................................................................................................ 287

4-59. 8-OxodG in brain DNA and brain tumor incidence in male Sprague-Dawley rats 

exposed to AN in drinking water ..................................................................................... 288

5-1. Incidences of forestomach lesions (hyperplasia or hyperkeratosis) in Sprague-Dawley and 

F344 rats exposed to AN in drinking water for 2 years..................................................... 305

5-2. Incidences of forestomach lesions (hyperplasia or hyperkeratosis) in 

male and female B6C3F1 mice administered AN via gavage for 2 years.......................... 306

5-3. Candidate RfDs based on BMD modeling of the incidence of nonneoplastic 

forestomach lesions (hyperplasia or hyperkeratosis) in male and female 

Sprague-Dawley rats exposed to AN in drinking water for 2 years .................................. 310
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5-4. Candidate RfDs based on BMD modeling of the incidence of nonneoplastic 

forestomach lesions (hyperplasia or hyperkeratosis) in male and female F344 rats 

exposed to AN in drinking water for 2 years..................................................................... 311

5-5. Candidate RfDs based on BMD modeling of the incidence of nonneoplastic 

forestomach lesions (hyperplasia or hyperkeratosis) in male and female 

B6C3F1 mice exposed to AN via gavage for 2 years......................................................... 312

5-6. Results of dose-response analyses of incidence data for selected nasal lesions in 

male and female Sprague-Dawley rats exposed by inhalation to AN for 2 years ............. 321

5-7. Incidence of CNS tumors in Sprague-Dawley and F344 rats exposed to AN in 

drinking water for 2 years.................................................................................................. 329

5-8. Incidence of mammary gland tumors in F344 and Sprague-Dawley rats exposed to 

AN in drinking water for 2 years ....................................................................................... 330

5-9. Tumor incidences Sprague-Dawley and F344 in rats exposed to AN in drinking water 

for 2 years .......................................................................................................................... 331

5-10. Incidences of intestinal, CNS, Zymbal gland, tongue, and mammary gland tumors 

in Sprague-Dawley rats exposed to AN via inhalation for 2 years .................................. 333

5-11. Four different dose metrics, two external and two internal, based on doses 

employed in studies of Sprague-Dawley and F344 rats exposed to AN in 

drinking water for 2 years ................................................................................................ 335

5-12. BMD modeling results using tumor incidence data from male and female 

Sprague-Dawley and F344 rat studies in which animals were exposed to AN in 

drinking water for 2 years ................................................................................................ 336

5-13. Site-specific oral CSFs for AN based on BMD modeling of tumor incidence data in 

rats and predicted CEO levels in blood (AUC/24 hours) of rats and humans 

assuming episodic exposure to AN .................................................................................. 338

5-14. Site-specific oral CSFs for AN based on BMD modeling of tumor incidence data 

in rats and predicted AN levels in blood (AUC/24 hours) of rats and humans 

assuming episodic exposure to AN .................................................................................. 339

5-15. Site-specific oral CSFs for AN based on BMD modeling of tumor incidence 

data in rats and BW scaling to the 3⁄4 power to convert from rat to human 

administered doses ........................................................................................................... 340

5-16. Two different dose metrics, one external and one internal, based on administered 

air concentrations of AN employed in a 2-year bioassay in Sprague-Dawley rats.......... 341

5-17. BMD modeling results using tumor incidence data from male and female 

Sprague-Dawley rats exposed to AN via inhalation for 2 years and CEO 

concentration in blood predicted from an EPA-modified PBTK model .......................... 342
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5-18. Site-specific IURs for AN based on BMD modeling of tumor incidence data in 

Sprague-Dawley rats and PBTK modeling of CEO levels in blood (AUC/24 hours) 

of rats and humans............................................................................................................ 343

5-19. Site-specific IURs for AN based on BMD modeling of tumor incidence data in 

Sprague-Dawley rats exposed to AN via inhalation ........................................................ 343

5-20. Estimated human equivalent oral CSFs for composite risk based on tumor 

incidence in AN-exposed rats and predicted CEO-AUC levels in blood......................... 345

5-21. Estimated human equivalent composite IURs based on tumor incidence in 

AN-exposed rats and predicted CEO-AUC levels in blood............................................. 347

5-22. Tumor incidences in Sprague-Dawley rats following inhalation exposure to 

60 ppm AN for 104 weeks, starting either in utero (GD 12) or as adults at 

13 wks of age.................................................................................................................... 350

5-23. Tumor incidences in female Sprague-Dawley rats exposed to AN in drinking water 

for approximately 46 weeks, starting either in utero or at 5 weeks of age....................... 353

5-24. Overall extra risks of multiple tumor incidence, for chronic exposure beginning 

either in early-life or in adulthood; based on Sprague-Dawley rats exposed to AN........ 355

5-25. Application of ADAFs for estimating human cancer risk from 70-year oral or 

inhalation exposures to AN from ages 0 to 70 ................................................................. 357

5-26. Summary of uncertainty in the AN oral cancer risk assessment ...................................... 359

5-27. Summary of uncertainty in the AN inhalation cancer risk assessment ............................ 364

B-1. Incidences of forestomach lesions (hyperplasia or hyperkeratosis) in Sprague-Dawley and 

F344 rats exposed to AN in drinking water for 2 years..................................................... B-1

B-2. Incidences of forestomach lesions (hyperplasia or hyperkeratosis) in male and female 

B6C3F1 mice administered AN via gavage for 2 years ..................................................... B-3

B-3. Summary of the BMD modeling results based on the incidence of forestomach lesions 

(hyperplasia or hyperkeratosis) in male and female 

Sprague-Dawley rats exposed to AN in drinking water for 2 years .................................. B-4

B-4. Summary of the BMD modeling results based on the incidence of forestomach lesions 

(hyperplasia or hyperkeratosis) in male and female F344 rats 

exposed to AN in drinking water for 2 years................................................................... B-52

B-5. Summary of the BMD modeling results based on the incidence of forestomach lesions 

(hyperplasia or hyperkeratosis) in male and female B6C3F1 mice exposed to AN via 

gavage for 2 years ............................................................................................................ B-83
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B-6. Incidence data for selected nasal lesions in Sprague-Dawley rats exposed by 

inhalation to AN for 2 years........................................................................................... B-116

B-7. A summary of BMDS (version 1.3.2) modeling results based on incidence of 

hyperplasia of mucus-secreting cells in male Sprague-Dawley rats exposed to 

AN via inhalation for 2 years......................................................................................... B-117

B-8. A summary of BMDS (version 1.3.2) modeling results based on incidence of 

flattening of respiratory epithelium in female Sprague-Dawley rats exposed to 

AN via inhalation for 2 years......................................................................................... B-120

B-9. Incidence of forestomach (nonglandular) tumors in Sprague-Dawley rats exposed to 

AN in drinking water for 2 years ................................................................................... B-124

B-10. Summary of BMD modeling results based on incidence of forestomach 

(nonglandular) tumors in Sprague-Dawley rats exposed to AN in drinking water 

for 2 years..................................................................................................................... B-124

B-11. Incidence of CNS tumors in Sprague-Dawley rats exposed to AN in drinking water 

for 2 years..................................................................................................................... B-139

B-12. Summary of BMD modeling results based on incidence of CNS tumors in 

Sprague-Dawley rats exposed to AN in drinking water for 2 years............................. B-139

B-13. Incidence of Zymbal gland tumors in Sprague-Dawley rats exposed to AN 

in drinking water for 2 years ........................................................................................ B-154

B-14. Summary of BMD modeling results based on incidence of Zymbal gland 

tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years ............ B-154

B-15. Incidence of tongue tumors in Sprague-Dawley rats exposed to AN in drinking 

water for 2 years ........................................................................................................... B-169

B-16. Summary of BMD modeling results based on incidence of tongue tumors in 

Sprague-Dawley rats exposed to AN in drinking water for 2 years............................. B-169

B-17. Incidence of mammary gland tumors in Sprague-Dawley rats exposed to AN in 

drinking water for 2 years ............................................................................................ B-184

B-18. Summary of BMD modeling results based on incidence of mammary gland 

tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years ............ B-184

B-19. Incidence of forestomach (nonglandular) tumors in F344 rats exposed to AN in 

drinking water for 2 years ............................................................................................ B-192

B-20. Summary of BMD modeling results based on incidence of forestomach 

(nonglandular) tumors in F344 rats exposed to AN in drinking water for 2 years ...... B-193
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B-21. Incidence of CNS tumors in F344 rats exposed to AN in drinking water for 

2 years........................................................................................................................... B-208

B-22. Summary of BMD modeling results based on incidence of CNS tumors in 

F344 rats exposed to AN in drinking water for 2 years ............................................... B-208

B-23. Incidence of Zymbal gland tumors in F344 rats exposed to AN in drinking water 

for 2 years..................................................................................................................... B-223

B-24. Summary of BMD modeling results based on incidence of Zymbal gland tumors in 

F344 rats exposed to AN in drinking water for 2 years ............................................... B-223

B-25. Incidence of mammary gland tumors in F344 rats exposed to AN in drinking water 

for 2 years..................................................................................................................... B-238

B-26. Summary of BMD modeling results based on incidence of mammary gland tumors 

in F344 rats exposed to AN in drinking water for 2 years ........................................... B-238

B-27. Incidence of intestinal tumors in Sprague-Dawley rats exposed to AN in air for 

2 years........................................................................................................................... B-247

B-28. Summary of BMD modeling results based on incidence of intestinal tumors in 

Sprague-Dawley rats exposed to AN in air for 2 years................................................ B-247

B-29. Incidence of CNS tumors in Sprague-Dawley rats exposed to AN in air for 

2 years........................................................................................................................... B-253

B-30. Summary of BMD modeling results based on incidence of CNS tumors in 

Sprague-Dawley rats exposed to AN in air for 2 years................................................ B-253

B-31. Incidence of Zymbal gland tumors in Sprague-Dawley rats exposed to AN in air 

for 2 years..................................................................................................................... B-262

B-32. Summary of BMD modeling results based on incidence of Zymbal gland tumors 

in Sprague-Dawley rats exposed to AN in air for 2 years............................................ B-262

B-33. Incidence of tongue tumors in Sprague-Dawley rats exposed to AN in air for 

2 years........................................................................................................................... B-272

B-34. Summary of BMD modeling results based on incidence of tongue tumors in SpragueDawley rats exposed to AN in air for 2 years .............................................................. B-272

B-35. Incidence of mammary gland tumors in Sprague-Dawley rats exposed to AN in air 

for 2 years..................................................................................................................... B-278

B-36. Summary of BMD modeling results based on incidence of mammary gland tumors 

in Sprague-Dawley rats exposed to AN in air for 2 years............................................ B-278
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B-37. Summary of PODs for composite cancer risk associated with episodic oral 

exposure to AN, using CEO-AUC levels in blood as dose metric and multiple 

tumor incidence data in rats.......................................................................................... B-291

B-38. Summary of PODs for composite cancer risk associated with inhalation exposure 

to AN, based on multiple tumor incidence data in rats and CEO-AUC levels 

in blood......................................................................................................................... B-291

B-39. Estimated human oral CSFs for AN based on multiple tumor incidence data in 

rats and CEO-AUC levels in blood .............................................................................. B-292

B-40. Estimated human IURs for AN based on multiple tumor incidence data in rats and 

CEO-AUC levels in blood............................................................................................ B-292

C-1. Rat and human PBPK model parameter values ................................................................. C-2

D-1. Tissue:blood PCs ............................................................................................................... D-2 

D-2. Impact of method of estimation of PCs on the peak AN and CEO model predictions ..... D-3

D-3. PBPK mass balance predictions for an 8-hour human exposure to 2 ppm AN................. D-6

D-4. Sensitivity of AN and CEO metrics for continuous inhalation exposure.......................... D-9

D-5. Sensitivity of AN and CEO metrics for continuous oral exposure.................................. D-10

D-6. Estimated CVs for AN and CEO metrics ........................................................................ D-12

D-7. Parameter contributions to overall CVs for inhalation exposure..................................... D-13

D-8. Parameter contributions to overall CVs for oral exposure .............................................. D-14
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LIST OF FIGURES 

2-1. Chemical structure of AN....................................................................................................... 3

3-1. Scheme for the metabolic transformation of AN.................................................................. 14

3-2. Structure of the PBTK model for AN and CEO................................................................... 41

3-3. Intravenous exposure, dosimetry, and model fits................................................................. 46

3-4a. Inhalation exposure, CEO concentrations .......................................................................... 47

3-4b. Inhalation exposure, AN concentrations ............................................................................ 48

3-5a. Oral exposure, CEO concentrations.................................................................................... 49

3-5b. Oral exposure, AN concentrations...................................................................................... 50

3-5c. Oral exposure, urinary excretion, and Hb binding.............................................................. 51

5-1. Comparison of LOAELs for noncancer effects across target organs following oral 

exposure to AN in animals.................................................................................................. 316

5-2. Comparison of LOAELs for noncancer effects in human workers following inhalation 

exposure to AN ................................................................................................................... 323

5-3. Comparison of tumor responses to inhalation exposure of acrylonitrile, by age at start 

of exposure (offspring at GD 12, adults at 13 weeks), sex, and length of exposure, for 

Sprague-Dawley rats (Maltoni et al., 1988)........................................................................ 351

5-4. Comparison of composite oral CSFs derived from tumor incidence data in four 

different sex/strain/species of rats exposed chronically to AN. For each 

sex/strain/species combination, two different dose metrics were employed: 

(1) CEO concentration in blood, and (2) human equivalent administered dose................. 360

5-5. Comparison of Composite IURs derived from: (1) tumor incidence data in male and 

female Sprague-Dawley rats exposed chronically to AN, and (2) neurological effects 

in humans exposed to AN occupationally. In deriving the animal-based IURs, two 

different dose metrics were employed: (1) predicted CEO concentration in blood, and 

(2) human equivalent administered AN concentration in air.............................................. 365

C-1. Human inhalation exposure level vs. internal AN concentration ...................................... C-5

C-2. Human inhalation exposure level vs. internal CEO concentrations .................................. C-6

C-3. Human oral exposure level vs. internal AN concentration for continuous exposure ........ C-8

C-4. Human oral exposure level vs. internal CEO concentration for continuous exposure ...... C-8
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C-5. Human oral exposure level vs. internal AN concentration for episodic exposure............. C-9

C-6. Human oral exposure level vs. internal CEO concentration for episodic exposure .......... C-9
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LIST OF ABBREVIATIONS AND ACRONYMS 

ABS AN butadiene styrene 

ABT 1-aminobenzotriazole 

ADAF age-dependent adjustment factor 

ADUR AN-derived undialyzable radioactivity 

AIC Akaike’s Information Criterion 

ALT alanine aminotransferase 

AMAP amplitude of the motor action potential 

AN acrylonitrile 

ASAP amplitude of the sensory action potential 

AST aspartate aminotransferase 

ATP adenosine triphosphate 

ATPase adenosine triphosphatase 

ATSDR Agency for Toxic Substances and Disease Registry 

AUC area under the curve 

BAL broncho alveolar lavage 

BMC benchmark concentration 

BMCL 95% lower bound of the BMC 

BMD benchmark dose 

BMDL 95% lower confidence limit of benchmark dose 

BMDS benchmark dose software 

BMR benchmark response 

BrdU bromodeoxyuridine 

BSO buthionine sulfoximine 

BUN blood urea nitrogen 

BW body weight 

CA chromosomal aberration 

CAIII carbonic anhydrase III 

CAP compound action potential 

CASRN Chemical Abstracts Service Registry Number 

CEMA 2-cyanoethyl mercapturic acid 

CEO 2-cyanoethylene oxide 

CEVal N-(2-cyanoethyl)valine 

CF correction factor 

CHL Chinese hamster lung 

CHO Chinese hamster ovary 

CI confidence interval 

CNS central nervous system 

con-A concanavalin-A 

CSF cancer slope factor 

CV coefficient of variation 

CYP450 cytochrome P450 

DEM diethylmaleate 

DEX dexamethasone 

dGMP deoxyguanosine-5′-monophosphate 

DMSO dimethyl sulfoxide 

DNA deoxyribonucleic acid 
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DPOAE distortion product otoacoustic emission 

DTH delayed-type hypersensitivity 

EC exposure concentration 

ECG electrocardiogram 

EH epoxide hydrolase 

ERK extracellular signal-regulated kinase 

EROD ethoxyresorufin-O-deethylase 

FISH fluorescence in situ hybridization 

FSH follicle stimulating hormone 

GAPDH glyceraldehyde-3-phosphate dehydrogenase 

GD gestation day 

GEI gastric erosion severity index 

GI gastrointestinal 

GJIC gap junction intercellular communications 

GSH reduced glutathione 

GSSG glutathione disulfide 

GST glutathione-S-transferase 

GSTM GST of the μ subclass 

γ-GTP γ-glutamyl transpeptidase 

Hb hemoglobin 

HbCO carboxyhemoglobin 

HbO oxyhemoglobin 

HEC human equivalent concentration 

HED human equivalent dose 

HMPA hexamethylphosphoramide 

HPLC high performance liquid chromatography 

hprt hypoxanthine guanine phosphoribosyl transferase 

IC50 median inhibitory concentration

Ig immunoglobulin

i.p. intraperitoneal 

IPCS International Programme on Chemical Safety 

IRIS Integrated Risk Information System 

IUR inhalation unit risk 

i.v. intravenous 

KCN potassium cyanide 

LC50 median lethal concentration 

LD50 median lethal dose 

LDH lactate dehydrogenase 

LEC 95% lower bound of exposure concentration 

LH luteinizing hormone 

LOAEL lowest-observed-adverse-effect level 

LPS lipopolysaccharide 

MCMC Markov chain Monte Carlo 

MCV motor conduction velocity 

MDA malondialdehyde 

mEH microsomal epoxide hydrolase 

MEK mitogen-activated/ERK-activating kinase 

MEL melatonin 

MetHb methemoglobin 
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MN micronucleus, micronuclei 

MNU methylnitrosourea 

MP microsomal protein 

4MP 4-methylpyrazole 

NAC N-acetylcysteine 

NADP(H) nicotinamide adenine dinucleotide phosphate (reduced) 

NAS National Academy of Sciences 

NCI National Cancer Institute 

NCTB Neurobehavioral Core Test Battery 

NHA normal human astrocyte 

NIHL noise-induced hearing loss 

NIOSH National Institute for Occupational Safety and Health 

NMR nuclear magnetic resonance 

NOAEL no-observed-adverse-effect level 

NRC National Research Council 

NTP National Toxicology Program 

OBN octave band of noise 

OHC outer hair cell 

OR odds ratio 

OTC L-2-oxothiazolidine-4-carboxylic acid 

8-oxodG 8-oxodeoxyguanosine, also referred to as 8-oxo-7,8-dihydro2′deoxyguanosine and 8-hydroxy-2′-deoxyguanosine 

PB phenobarbital 

PBN phenyl-N-tertiary-butylnitrone 

PBPK physiologically based pharmacokinetic 

PBTK physiologically based toxicokinetic 

PC partition coefficient 

PCR polymerase chain reaction 

PH phorone 

PHA phytohemagglutinin 

PK protein kinase 

PMA phorbol 12-myristate 13-acetate 

PND postnatal day 

POD point of departure 

PRL prolactine 

RBC red blood cell 

RfC reference concentration 

RfD reference dose 

RLC rat liver cell 

RNA ribonucleic acid 

ROS reactive oxygen species 

RR relative risk 

SAED serially additive expected dose 

s.c. subcutaneous 

SCE sister chromatid exchange 

SCV sensory conduction velocity 

SD standard deviation 

SDH sorbitol dehydrogenase 

SEER Surveillance, Epidemiology and End Results 
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SG USEPA Supplemental Guidance for Assessing Susceptibility from EarlyLife Exposure to Carcinogens 

SGPT serum glutamate pyruvate transaminase 

SHE Syrian hamster embryo 

SIR standardized incidence ratio 

SMR standardized mortality ratio 

SOD superoxide dismutase 

SRBC sheep red blood cell 

STS sodium thiosulfate 

TAU taurine 

TBARS thiobarbituric acid-reactive substances 

TCPO 1,1,1-trichloropropane-2,3-oxide 

6-TG 6-thioguanine 

TNF-α tumor necrosis factor 

TPO 3,3,3-trichloropropylene oxide 

TRX trolox 

TWA time-weighted average 

UCL upper confidence limit 

UDS unscheduled DNA synthesis 

UF uncertainty factor 

U.S. EPA U.S. Environmental Protection Agency 

v/v volume/volume 

WBC white blood cell 

WHO World Health Organization 

WT wild-type
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FOREWORD 

The purpose of this Toxicological Review is to provide scientific support and rationale 

for the hazard and dose-response assessment in IRIS pertaining to chronic exposure to

acrylonitrile. It is not intended to be a comprehensive treatise on the chemical or toxicological 

nature of acrylonitrile. 

The intent of Section 6, Major Conclusions in the Characterization of Hazard and Dose 

Response, is to present the major conclusions reached in the derivation of the reference dose, 

reference concentration and cancer assessment, where applicable, and to characterize the overall 

confidence in the quantitative and qualitative aspects of hazard and dose response by addressing 

the quality of data and related uncertainties. The discussion is intended to convey the limitations 

of the assessment and to aid and guide the risk assessor in the ensuing steps of the risk 

assessment process. 

For other general information about this assessment or other questions relating to IRIS, 

the reader is referred to EPA’s IRIS Hotline at (202) 566-1676 (phone), (202) 566-1749 (fax), or 

hotline.iris@epa.gov (email address). 
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AUTHORS, CONTRIBUTORS, AND REVIEWERS 

CHEMICAL MANAGER 

Diana Wong, Ph.D., DABT 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

AUTHORS

Diana Wong, Ph.D., DABT 

Ted Berner, MS 

John Fox 

Rosemarie Hakim, Ph.D. 

Karen Hogan, MS 

Amanda Persad, Ph.D. 

Leonid Kopylev, Ph.D. 

Paul Schlosser, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

Roglio Tornero-Valez, Ph.D. 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

CONTRACTOR SUPPORT 

Lutz W.D. Weber, Ph.D., DABT (First Draft) 

George Holdsworth, Ph.D. (First Draft) 

Janusz Z. Byczkowski, Ph.D., D.Sc., DABT (First Draft) 

Donna Cragle, Ph.D. (First Draft) 

Virginia H. Sublet, Ph.D. (First Draft) 

Oak Ridge Institute for Science and Education 

Oak Ridge Associated Universities 

Oak Ridge, TN 

Margaret Fransen, Ph.D. (Second Draft) 

Michael Lumpkin, Ph.D. (Second Draft) 

Jennifer Rhoades, B.S. (Second Draft) 

Peter McClure, Ph.D., DABT (Second Draft) 

Environmental Science Center 

SRC, Inc. 

North Syracuse, NY 
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INTERNAL EPA REVIEWERS 

James Allen, Ph.D. 

NHEERL 

Office of Research and Development 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Dave Bayliss, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

Jerry Blancato, Ph.D. 

NERL 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Anthony DeAngelo, Ph.D. 

NHEERL 

Office of Research and Development 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Rob Dewoskin, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Lynn Flowers, Ph.D., DABT 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

Kate Guyton, Ph.D., DABT 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

Karl Jensen, Ph.D. 

NHEERL 

Office of Research and Development 
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U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Jennifer Jinot 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

Channa Keshava, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

John Lipscomb, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Cincinnati, OH 

Robert MacPhail, Ph.D. 

NHEERL 

Office of Research and Development 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Jeff Ross, Ph.D. 

NHEERL 

Office of Research and Development 

U.S. Environmental Protection Agency 

Research Triangle Park, NC 

Cheryl Scott 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 

Lawrence Valcovic, Ph.D. 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 
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John Whalan 

National Center for Environmental Assessment 

Office of Research and Development 

U.S. Environmental Protection Agency 

Washington, DC 
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1. INTRODUCTION 

This document presents background information and justification for the Integrated Risk 

Information System (IRIS) Summary of the hazard and dose-response assessment of acrylonitrile 

(AN). IRIS Summaries may include oral reference dose (RfD) and inhalation reference 

concentration (RfC) values for chronic and other exposure durations, and a carcinogenicity 

assessment. 

The RfD and RfC, if derived, provide quantitative information for use in risk assessments 

for health effects known or assumed to be produced through a nonlinear (presumed threshold) 

mode of action (MOA). The RfD (expressed in units of mg/kg-day) is defined as an estimate 

(with uncertainty spanning perhaps an order of magnitude) of a daily exposure to the human 

population (including sensitive subgroups) that is likely to be without an appreciable risk of 

deleterious effects during a lifetime. The inhalation RfC (expressed in units of mg/m3

) is 

analogous to the oral RfD, but provides a continuous inhalation exposure estimate. The 

inhalation RfC considers toxic effects for both the respiratory system (portal of entry) and for 

effects peripheral to the respiratory system (extrarespiratory or systemic effects). Reference 

values are generally derived for chronic exposures (up to a lifetime), but may also be derived for 

acute (≤24 hours), short-term (>24 hours up to 30 days), and subchronic (>30 days up to 10% of 

lifetime) exposure durations, all of which are derived based on an assumption of continuous 

exposure throughout the duration specified. Unless specified otherwise, the RfD and RfC are 

derived for chronic exposure duration. 

The carcinogenicity assessment provides information on the carcinogenic hazard 

potential of the substance in question and quantitative estimates of risk from oral and inhalation 

exposure may be derived. The information includes a weight-of-evidence judgment of the 

likelihood that the agent is a human carcinogen and the conditions under which the carcinogenic 

effects may be expressed. Quantitative risk estimates may be derived from the application of a 

low-dose extrapolation procedure. If derived, the oral slope factor is a plausible upper bound on 

the estimate of risk per mg/kg-day of oral exposure. Similarly, an inhalation unit risk is a 

plausible upper bound on the estimate of risk per μg/m3 air breathed. 

Development of the hazard identification and dose-response assessments for AN has 

followed the general guidelines for risk assessment as set forth by the National Research Council 

(NRC, 1983). U.S. Environmental Protection Agency (U.S. EPA) Guidelines and Risk 

Assessment Forum Technical Panel Reports that may have been used in the development of this 

assessment include the following: Guidelines for the Health Risk Assessment of Chemical 

Mixtures (U.S. EPA, 1986a), Guidelines for Mutagenicity Risk Assessment (U.S. EPA, 1986b), 

Recommendations for and Documentation of Biological Values for Use in Risk Assessment (U.S. 

EPA, 1988), Guidelines for Developmental Toxicity Risk Assessment (U.S. EPA, 1991), Interim 
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Policy for Particle Size and Limit Concentration Issues in Inhalation Toxicity (U.S. EPA, 

1994a), Methods for Derivation of Inhalation Reference Concentrations and Application of 

Inhalation Dosimetry (U.S. EPA, 1994b), Use of the Benchmark Dose Approach in Health Risk 

Assessment (U.S. EPA, 1995), Guidelines for Reproductive Toxicity Risk Assessment (U.S. EPA, 

1996), Guidelines for Neurotoxicity Risk Assessment (U.S. EPA, 1998a), Science Policy Council 

Handbook: Risk Characterization (U.S. EPA, 2000a), Benchmark Dose Technical Guidance 

Document (U.S. EPA, 2000b), Supplementary Guidance for Conducting Health Risk Assessment 

of Chemical Mixtures (U.S. EPA, 2000c), A Review of the Reference Dose and Reference 

Concentration Processes (U.S. EPA, 2002), Guidelines for Carcinogen Risk Assessment (U.S. 

EPA, 2005a), Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to 

Carcinogens (U.S. EPA, 2005b), Science Policy Council Handbook: Peer Review (U.S. EPA, 

2006a), and A Framework for Assessing Health Risks of Environmental Exposures to Children

(U.S. EPA, 2006b). 

The literature search strategy employed for this compound was based on the Chemical 

Abstracts Service Registry Number (CASRN) and at least one common name. Any pertinent 

scientific information submitted by the public to the IRIS Submission Desk was also considered 

in the development of this document. The relevant literature was reviewed through June 2009. 
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2. CHEMICAL AND PHYSICAL INFORMATION 

 AN (CASRN 107-13-1) is a three-carbon alkene carrying a nitrile substituent group as 

part of the terminal carbon atom (carbon 1) (Figure 2-1). Synonyms for the compound include 

vinyl cyanide, propenenitrile, and cyanoethylene, and there are a variety of trade names. AN is a 

colorless, flammable, and volatile liquid with a weakly pungent onion- or garlic-like odor. Some 

physical and chemical properties are shown below (NLM, 2003; IPCS, 2002; ATSDR, 1990). 

Figure 2-1. Chemical structure of AN. 

 

 Formula: C3H3N 

 Molecular weight: 53.06 

 Melting point: –83°C 

 Boiling point: 77.4°C 

 Density: 0.806 g/mL (at 20°C) 

 Log KOW: –0.92 

 Log KOC: –0.07 

 Vapor pressure: 100 mm Hg at 22.8°C 

 Henry’s law constant: 8.8 × 10-5 atm-m3/mol 

 Conversion factors: 1 ppm = 2.17 mg/m3

 1 mg/m3

 = 0.46 ppm 

 AN is a commercially important chemical with a wide range of uses in the chemical 

industry. It is used in the production of acrylic and modacrylic fibers, plastics (AN butadiene 

styrene [ABS] and AN-styrene resins), and nitrile rubbers and as an intermediate in the 

production of other important chemicals, such as adiponitrile and acrylamide. AN is used in the 

plastics industry in the formation of surface coatings and adhesives. It is a chemical intermediate 

in the synthesis of antioxidants, pharmaceuticals, and dyes and, in general, for processes 

requiring the introduction of a cyanoethyl group into a molecule (NLM, 2003). AN is also used 

in clinical practice in the form of dialysis tubing (Mulvihill et al., 1992). AN was used 

occasionally as a fumigant insecticide for stored grain. A measure of the commercial importance 

of AN may be judged by the amount produced in a given year. The Agency for Toxic 

Substances and Disease Registry (ATSDR, [1990]) reports that 1,112,754 metric tons of AN 

were produced in the United States in 1987. Production had increased to 1,455,735 metric tons 

C

C

C

N

H

H

H
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by 1995 (ACS, 2003). Exposure of the general public to AN can potentially occur through 

migration of residual monomer in polymeric products via contact with food or water. Exposure 

to airborne AN is possible among members of the general population living in the vicinity of 

emission sources such as acrylic fiber or chemical manufacturing plants or waste sites (ATSDR, 

1990). In addition, smokers are expected to be exposed to AN, which has been detected in 

cigarette smoke at levels of 3.2–15 mg per cigarette (IARC, 1999). 
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3. TOXICOKINETICS 

 Although only limited information on the toxicokinetics of AN in exposed humans is 

available, a substantial body of evidence has accumulated on the absorption, distribution, 

metabolism, and excretion of AN in experimental animals. The overall conclusion that can be 

drawn is that AN is rapidly and nearly completely absorbed, widely distributed among the 

tissues, and biochemically transformed into several discrete metabolic products that are excreted 

in the urine and, to a much lesser extent, in feces and expired air. Characterization of the 

excretory products of AN, with support from in vitro and in vivo kinetic data on its 

biotransformation, has contributed to a picture of how AN is rearranged into a series of 

metabolic products. Two primary processes appear to be involved: (1) interaction with reduced 

glutathione (GSH) and (2) cytochrome P450 (CYP450) 2E1-mediated formation of 

2-cyanoethylene oxide (CEO). Each product of these processes can undergo further metabolic 

transformations. For example, CEO can be hydrolyzed to cyanide with further transformation to 

thiocyanate. Alternatively, CEO can itself interact with GSH, resulting in the formation of a 

number of metabolites, several of which have been identified in the urine of experimental 

animals. 

 Important data elements that have contributed to the EPA's current understanding of the 

toxicokinetics of AN are summarized in the following sections. 

3.1. ABSORPTION 

3.1.1. Studies in Humans 

 There are few data on the absorption of AN in humans. However, Jakubowski et al. 

(1987) provided some information on the topic by administering AN via inhalation to six male 

volunteers for 8 hours at concentrations of either 5 or 10 mg/m3

 from a chamber. Lung 

ventilation and retention of AN in the lungs of these individuals were measured by determining 

the concentrations of AN in the inhaled and expired air. A respiratory retention of 52% was 

estimated, based on 90 minutes to 8 hours of observation. 

3.1.2. Studies in Animals 

Most of the available information on the absorption of AN has come from studies in 

experimental animals. Young et al. (1977) carried out a series of experiments in which 

[1-14C]-AN was administered to male Sprague-Dawley rats via the oral, inhalation, or 

intravenous (i.v.) route. Semiquantitative evidence of extensive absorption of AN has come 

from an inhalation experiment of Young et al. (1977) in which four rats/group were exposed 

nose only to 5 or 100 ppm AN vapor for 6 hours. Following the exposure, the animals were kept 

in metabolism cages and excreta were collected for 220 hours. Total recovered doses estimated 
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from total recovered radioactivity for the low and high exposure levels were 0.7 and 10.2 mg/kg 

[1-14C]-AN, respectively. Substantial amounts of the recovered dose were found in urine, feces, 

and tissues, which indicated that AN has the capacity to be absorbed via the inhalation route 

(Table 3-1). 

Table 3-1. Recovery of radioactivity from male Sprague-Dawley rats 

exposed to 5 or 100 ppm [1-14C]-AN for 6 hours via inhalation 

5 ppm 100 ppm 

Site of recovery Percentage of recovered dose (mean ± standard deviation [SD]) 

Urine 68.50 ± 9.38 82.17 ± 4.21 

Feces 3.94 ± 0.97 3.15 ± 0.82 

14CO2 6.07 ± 1.58 2.60 ± 0.83 

Body 18.53 ± 4.68 11.24 ± 2.85 

Cage wash 2.95 ± 3.95 0.85 ± 0.58 

Total dose (mg/kg) 0.7 10.2 

Source: Young et al. (1977). 

 In the gavage experiments of Young et al. (1977), animals were kept in metabolic cages 

after a single dose of either 0.1 or 10 mg/kg [1-14C]-AN (vehicle not stated), and the fate of the 

radiolabel was monitored for 72 hours. As shown in Table 3-2, only about 5% of the 

administered radiolabel was recovered in the feces after 72 hours. By contrast, most of the 

administered radiolabel was recovered in the urine, carcass, and skin, with smaller fractions of 

the administered radiolabel expired as 14CO2. These data suggest that at least 95% of 

administered AN was absorbed. 

Table 3-2. Recovery of radioactivity after a single gavage dose of 0.1 or 

10 mg/kg [1-14C]-AN to male Sprague-Dawley rats 

0.1 mg/kg 10 mg/kg 

Recovery site Percent of dose 

Urine 34.22 ± 6.26 66.68 ± 10.6 

Feces 5.36 ± 1.43 5.22 ± 1.17 

Expired CO2 4.56 ± 1.82 3.93 ± 1.79 

Carcass 24.24 ± 5.02 16.04 ± 1.87 

Skin 12.78 ± 1.17 10.57 ± 4.55 

Total recovery 81.2 102.4 

Source: Young et al. (1977). 

 Ahmed et al. (1983) administered a single oral dose of 46.5 mg/kg AN to male SpragueDawley rats in distilled water, using 50 μCi/kg of either [2,3-14C]- or [1-14C]-AN as a tracer. 
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Only 8–10% of administered radioactivity from the [2,3-14C]-AN dose had been excreted in 

feces 72 hours after dosing, compared with 2% from orally administered [1-14C]-AN during the 

same period. Thus, AN was readily absorbed at the gastrointestinal (GI) tract. The time course 

of radioactivity released from feces showed a major spike of [2,3-14C]-AN-derived radiolabel 

after 72 hours. The delayed release suggests that at least a portion of this released radioactivity 

may have resulted from biliary elimination of absorbed AN. The major peak of released 

radiolabel from [1-14C]-AN was at 24 hours postexposure, possibly indicative of a different 

metabolic fate for the nitrile portion of the molecule. 

 Kedderis et al. (1993a) administered [2,3-14C]-AN orally to male F344 rats (0.09–

28.8 mg/kg) and male B6C3F1 mice (0.09–10 mg/kg). Three to five percent of the administered 

dose was recovered in the feces of rats after 72 hours. Between 2 and 8% of the dose was 

recovered in the feces of male B6C3F1 mice. These data indicated the near-complete absorption 

of the compound when administered via the oral route. 

3.2. DISTRIBUTION 

 The toxicokinetic experiments of Young et al. (1977) provided data on the deposition of 

radiolabel when male Sprague-Dawley rats were exposed to [1-14C]-AN via inhalation, gavage, 

or i.v. injection. As shown in Table 3-1, an average of 11.24% of total recovered dose 

(10.2 mg/kg [1-14C]-AN) was obtained in the tissues when a group of four rats were exposed to 

100 ppm of [1-14C]-AN for 6 hours via inhalation, and excreta were collected for 220 hours. 

Another group exposed to 5 ppm [1-14C]-AN had an average of 18.53% of the recovered 

radiolabel (0.7 mg/kg [1-14C]-AN) deposited in the tissues. When the fate of radiolabel 

administered by gavage was monitored, combining the recoveries of the administered 

radioactivity in carcass and skin gave a value of 37% for tissue deposition at the lower AN 

concentration (0.1 mg/kg) vs. 27% at the higher concentration (10 mg/kg) (Table 3-2), indicating 

possible metabolic saturation at the higher dose. The percentage of expired CO2 was lower for 

the high-dose group than the low-dose group (3.93 vs. 4.56%), providing support for possible 

metabolic saturation. 

Young et al. (1977) examined the distribution of the radiolabel among the major organs 

and tissues after oral and i.v. administration of [1-14C]-AN. Radioactivity was detected at a 

range of tissues, including lungs, liver, kidneys, stomach, intestines, skeletal muscle, heart, 

spleen, brain, thymus, testes, skin, carcass, and blood cells. Of these, the stomach, red blood 

cells (RBCs), and skin appeared to be the most important deposition sites for radiolabeled AN or 

its metabolites, regardless of the route of administration, dose level, or time. Radioactivity found 

in the stomach was highest after either oral or i.v. route and was not due to unabsorbed AN since 

similar results were obtained with either i.v. or oral dosing. 

In a follow-up time course experiment, Young et al. (1977) administered 10 mg/kg 

[1-14C]-AN intravenously via the tail vein to three male Sprague-Dawley rats and examined the 
 DRAFT - DO NOT CITE OR QUOTE 8 

distribution of radioactivity to the stomach and adrenal glands. The level of radioactivity in the 

stomach and its contents increased from 5 minutes to 24 hours postinjection. On the other hand, 

radioactivity was high in the adrenal gland at 5 minutes but decreased 13-fold in 24 hours. 

Radioactivity was observed in the bile of a single bile-duct-cannulated rat, indicating biliary 

excretion. Maximal radioactivity in bile was observed after 15 minutes but declined at later time 

points. 

 When both sexes of adult Sprague-Dawley rats (including some pregnant animals) and 

two cynomolgus monkeys were exposed orally (26 mg/kg) or intravenously (13 mg/kg) to single 

doses of [1-14C]-AN, whole-body autoradiography from 20 minutes after injection primarily 

showed radioactivity in the bile, intestinal contents, and urine (Sandberg and Slanina, 1980). 

Other organs showing accumulation of isotope in the autoradiogram were blood, liver, kidney, 

lung, and adrenal cortex, in which the activity declined slowly during 24 hours. There also was 

uptake of the label in the stomach mucosa and hair follicles. Distribution of radioactivity in fetal 

tissue following i.v. and oral administration to pregnant rats was uniform and showed a low 

uptake compared to maternal tissue. An exception was found in the eye lens, in which the 

radioactivity exceeded that of the maternal blood (Sandberg and Slanina, 1980). 

 Jacob and Ahmed (2003a) used whole-body autoradiography to examine the distribution 

of 11.5 mg/kg [2-14C]-AN administered orally or intravenously to male F344 rats 5 minutes and 

8, 24, and 48 hours postexposure. Levels of radioactivity per gram of tissue were highest 

5 minutes after oral dosing for stomach lumen and mucosa, small intestine lumen and mucosa, 

liver, nasal mucosa, spleen, and kidney; other tissues (including the lung, brain, spinal cord, 

thyroid, and testis) had peak levels at 8 hours. Covalently bound radioactivity was detected 

48 hours later in stomach mucosa, blood, and hair follicles. Five minutes following i.v. 

administration, the highest levels of radioactivity per gram of tissue were detected in the lung, 

liver, spleen, small intestine lumen, kidney, epididymis, and adrenal gland. At 24 hours, tissues 

that showed peak levels included bone marrow, brain, lacrimal gland, and testis. Tissues with 

the highest level at 24 hours included the lung, liver, and bone marrow. The levels of covalent 

bound radioactivity (nCi/g) were higher 48 hours after i.v. exposure compared with oral 

exposure, with bound radioactivity retained in liver, spleen, bone marrow, lung, kidney, and 

adipose tissue ranging from 2.5 to 23 times higher following i.v. exposure. The only organs that 

retained higher levels of covalently bound radioactivity 48 hours following oral exposure were 

the stomach mucosa (3×) and heart blood (5.7×). The total radioactive dose retained in animals 

after i.v. and oral exposures were 70 and 38%, respectively. Jacob and Ahmed (2003a) 

concluded that the metabolism and distribution of AN is greatly influenced by the portals of 

entry, with a higher amount of AN metabolized and excreted following oral exposure compared 

with exposure by i.v. injection. Rapid delivery of AN after i.v. treatment resulted in fast 

conjugation and/or covalent interaction of the parent compound with biological molecules, 

resulting in minimal metabolism and excretion in urine or feces. 
 DRAFT - DO NOT CITE OR QUOTE 9 

 Sapota (1982) administered 40 mg/kg AN in saline, containing either 40 μCi/kg 

[1,2-14C]-AN or [1-14C]-AN to male Wistar rats, either via gavage or intraperitoneally. Tissue 

distribution of radioactivity as measured by liquid scintillation counting after intraperitoneal 

(i.p.) and oral administration showed that the highest specific radioactivity in tissue (nCi/g) was 

found in RBCs, liver, and kidneys. Tissue-wide recovery of the radiolabel from either 

[1,2-14C]-AN or [1-14C]-AN at 2, 8, and 24 hours after a single oral dose is shown in Table 3-3. 

Statistically significant differences were observed in the distribution of radioactivity from the 

two forms of labeled AN in RBCs, plasma, liver, and kidney at 8 and 24 hours after 

administration. More rapid loss of tissue radioactivity in the liver, kidneys, and brain was also 

observed after oral administration of [1-14C]-AN than [1,2-14C]-AN. These results suggested 

different pathways for disposition and biotransformation of the cyano and vinyl moieties of the 

AN molecule. 

Table 3-3. Percentage recovery of radioactivity in tissues of male Wistar 

rats following a single oral dose of radiolabeled AN 

Recovered radioactivity (percent of dose in tissue)

Distribution from [1-14C]-AN Distribution from [1,2-14 Target organ/ C]-AN 

tissue 2 h 8 h 24 h 2 h 8 h 24 h 

RBCs 5.36 4.82a 5.45 5.31 7.27a 6.72 

Plasma 2.63 4.00a 0.50a 1.93 1.92a 1.70a 

Liver 6.13 1.21a 1.00a 7.00 5.98a 2.67a 

Kidney 1.17 0.27a 0.15a 0.82 0.77a 0.30a 

Spleen 0.22 0.10 0.08 0.14 0.17 0.10 

Lung 0.36 0.25 0.25 0.30 0.27 0.11 

Brain 0.25 0.12a 0.09 0.24 0.25a 0.12 

Total 16.1 10.8 7.5 15.7 16.6 11.7 

a

p < 0.05; significant difference between [14CN]-AN and [1,2-14C]-AN at the same time point. 

Source: Sapota (1982). 

In an in vivo study on the interaction of orally administered 46.5 mg/kg [1-14C]-AN or 

5 mg/kg K14CN with rat blood, Farooqui and Ahmed (1982) reported that up to 94% of 14C from 

AN in RBCs was covalently bound to cytoplasmic and membrane proteins. On the other hand, 

90% of the radioactivity from K14CN in erythrocytes was bound to the heme fraction of 

hemoglobin (Hb), indicating that CN– liberated from potassium cyanide (KCN) interacted with 

heme. In addition, distribution of 14C from erythrocytes of rats treated with [1-14C]-AN showed 

that more than 40% of total radioactivity was localized in membrane residue, 20–35% in the 

globin fraction, and 11–25% in the heme fraction. In contrast, 70% of 14C from K14CN in red 

cells was localized in the heme fraction, 14–25% in globin, and 5–10% in cell membrane. The 

study authors concluded that KCN interacted with rat blood mainly through liberation of CN–

,
 DRAFT - DO NOT CITE OR QUOTE 10 

which was bound to heme. Since AN was found to be mainly covalently bound to cell 

membranes, AN might cause damage to RBCs by mechanisms other than the release of CN–

. 

 In male Wistar rats that received 40 mg/kg AN (about half the median lethal dose [LD50]) 

by gavage in water, peak blood levels of AN (2 μg/mL) were detected 1.5 hours after dosing 

(Shibata et al., 2004). By 2.5 hours after dosing, blood levels of AN had dropped to less than 

0.2 μg/mL. Ten hours after dosing, AN was still detectable in blood at 50 ng/mL. 

 Ahmed et al. (1983, 1982) studied the distribution of AN administered to male SpragueDawley rats by gavage with a dose equivalent to one-half the LD50 (46.5 mg/kg). In the first 

experiment (Ahmed et al., 1982), the dose additionally contained 50 μCi/kg [1-14C]-AN. In the 

second experiment (Ahmed et al., 1983), both [2,3-14C]-AN (both carbons in the vinyl moiety 

were radiolabeled) and [1-14C]-AN were studied in rats administered an oral dose of 46.5 mg/kg. 

Radioactivity from both forms of labeled AN or its metabolites initially was sequestered 

mainly in the stomach and stomach content, followed by the rest of the GI tract, including small 

and large intestines. The GI tract contained the highest levels of radioactivity up to 72 hours 

before beginning to decline, suggesting that AN or its metabolites were re-secreted in the 

stomach (Ahmed et al., 1983). In addition, radioactivity became widely distributed in all tissues 

within 1–6 hours after dosing, with liver, kidney, and blood showing higher radioactivity than 

muscle, fat, and bone (Ahmed et al., 1983, 1982). Heart, spleen, brain, and thymus showed 

maximum concentrations between 3 and 6 hours. By 24 hours after administration, the levels of 

radioactivity found in liver, kidney, and lung began to decline, resulting in 10- to several 

100-fold reductions from peak concentrations over the course of the 10-day experiment. 

However, in several tissues, the decline of radioactivity was much lower: at 10 days postdosing, 

radiolabel concentrations had declined only 2.4-fold in skin, 2.9-fold in blood, 3.8-fold in spleen, 

and 4.9-fold in eyes, as compared with peak levels. 

Two differently labeled AN preparations were administered to rats to elucidate potential 

differences in distribution and metabolism between the cyano and vinyl groups. One important 

finding of these studies was that radioactivity in blood was predominantly in the RBCs, 

especially for radioactivity from [2,3-14C]-AN. Radioactivity from [1-14C]-AN in plasma was 

higher than that from [2,3-14C]-AN. For radioactivity from [1-14C]-AN in RBCs, 40% was 

localized in membrane residue, 20–35% in the globin fraction, and 11–25% in the heme fraction. 

In contrast, 50% of radioactivity from [2,3-14C]-AN was in the membrane fraction, 45% in the 

globin fraction, and only a trace amount in the heme fraction. 

 In addition, compared to [1-14C]-AN administered to animals, the percentage of covalent 

binding of [2,3-14C]-AN to proteins was significantly higher even 72 hours after dosing. 

Subcellular distribution of radioactivity from [2,3-

14C]-AN was also different from that derived 

from [1-14C]-AN. For [2,3-14C]-AN, the cytosol fraction attained the lowest covalent protein 

binding in tissues. The percentage of covalently bound radioactivity in tissues relative to the 

total increased four- to fivefold over that of the 1-hour level. At 72 hours after administration, 
 DRAFT - DO NOT CITE OR QUOTE 11 

the highest bound radioactivity was in the mitochondrial fractions of kidney, spleen, lung, and 

heart. However, in liver, the microsomal fraction contained the highest radioactivity (Ahmed et 

al., 1983). 

 For [1-14C]-AN, covalent binding to macromolecules in tissues remained unchanged over 

time. Cytosol contained the highest levels of total radioactivity in the six tissues (liver, kidney, 

spleen, brain, lung, and heart) selected for the study of subcellular distribution. Twenty to 40% 

of total radioactivity was bound to nuclear, mitochondrial, or microsomal fractions. Only 6–14% 

of total radioactivity was bound to cytosol over 6 hours (Ahmed et al., 1982). 

Farooqui and Ahmed (1983a) demonstrated the irreversible binding of radiolabel from 

[2,3-14C]-AN to proteins and nucleic acids in vivo. AN was administered by gavage as a bolus 

dose of 46.5 mg/kg (one-half LD50) in distilled water to male Sprague-Dawley rats (3–4/group). 

Proteins were extracted by chloroform-isoamyl alcohol-phenol, and ribonucleic acid (RNA) and 

deoxyribonucleic acid (DNA) were isolated by hydroxyapatite chromatography. Protein binding 

at 1 hour after dosing was highest in spleen and stomach, followed by liver, brain, and kidney. 

Protein binding in spleen and stomach declined after 1 hour, whereas binding in liver, kidney, 

and brain increased. At 6 hours after dosing, protein binding fell to lower values in spleen and 

stomach but increased in other tissues. Binding plateaued in all tissues between 6 and 48 hours, 

with levels in spleen > liver > stomach > kidney > brain. Binding to RNA was highest in liver, 

stomach, and brain, with liver attaining a maximum by 6 hours and stomach and brain by 

24 hours. The subsequent decline until 48 hours was also slow. DNA binding did not reach a 

maximum until 24 hours after dosing, with levels in brain > stomach > liver. Again, the decline 

of DNA-bound radioactivity during the following 24 hours was slow. Binding of AN to DNA in 

brain, stomach, and liver was 56, 45, and 5 μmol AN per mol DNA, respectively, at 24 hours. 

The study authors also calculated a covalent binding index for DNA, defined as the ratio of 

(μmol AN bound per mol DNA) to (mmol AN applied per kg body weight [BW]). The values 

for brain, stomach, and liver were 65, 52, and 6, respectively. 

 Silver et al. (1987) examined the distribution of 100 mg [1-14C]-AN in female SpragueDawley rats after i.v. injection to investigate why this procedure induced acute hemorrhagic 

necrosis of the adrenal gland 2 hours after administration and why this damage was more 

prominent with i.v. injection than with oral administration. Total radioactivity was found to be 

highest in the blood, liver, kidney, duodenum, and adrenals 15–90 minutes following i.v. 

injection of the radiolabeled compound. (This result was largely in agreement with the wholebody autoradiographic findings of Sandberg and Slanina [1980] in rats and monkeys.) Total 

radiolabel in blood increased over this time period, whereas the total radiolabel in other organs 

remained constant or decreased with time. The level of covalently bound radiolabel in the 

adrenals was lower than that observed in blood, liver, kidney, forestomach, and glandular 

stomach. 
 DRAFT - DO NOT CITE OR QUOTE 12 

Silver et al. (1987) also administered the same dose of [1-14C]-AN in water by gavage to 

female Sprague-Dawley rats (four/group) and investigated the distribution of radiolabel up to 

24 hours after dosing. Total radioactivity was highest during the first 8 hours after dosing in the 

blood, GI tract, liver, and kidney. At 24 hours after dosing, the highest total radioactivity was 

found in the blood, forestomach, and glandular stomach. The highest level of covalently bound 

radioactivity was found in these same tissues during the first 8 hours after dosing and remained 

highest in the blood and forestomach at 24 hours after dosing. The study authors concluded that 

their observations would not support a role of covalent binding in the hemorrhagic effect of AN 

on the adrenals. Rather, the initial high concentrations of radiolabel from AN might play a role 

in the action of AN on the adrenal gland. However, it should be noted that in both studies, the 

cyano carbon, not the vinyl carbons, was labeled. 

 The rapidity with which AN was biotransformed and distributed to the brain as its 

epoxide metabolite, CEO, was reported in two studies (Kedderis et al., 1993b; Roberts et al., 

1991). Roberts et al. (1991) administered 4 mg/kg AN to male F344 rats and B6C3F1 mice 

(three/group) and measured CEO levels in blood at 0.5, 1, 4, or 24 hours after dosing. Higher 

levels of CEO were found in rat blood than in mouse blood. In addition, CEO was cleared from 

mouse blood in 4 hours, but was cleared in rat blood in 24 hours. The dose dependence of CEO 

concentrations in blood was also evaluated. Blood CEO was measured 0.5 hours after oral 

dosing in F344 rats given either 0, 1, 4, 10, or 30 mg/kg AN and in B6C3F1 mice given either 0, 

1, 4, 8, or 10 mg/kg AN. Blood CEO concentrations increased with dose in rats and mice but at 

higher concentrations in rats at the same doses. 

In the first experiment by Kedderis et al. (1993b), three male F344 rats and three male 

B6C3F1 mice were administered 10 mg/kg AN in water by gavage. The rats were sacrificed 

10 minutes after dosing, while the mice were sacrificed 5 minutes after dosing. CEO 

concentrations from blood and brains of rats and mice were measured. Higher CEO 

concentrations were found in the blood and brains of rats than in mice (13% higher in blood and 

23% higher in brain). In addition, CEO concentration in rat blood 10 minutes after oral 

administration was about twice the concentration previously reported by Roberts et al. (1991) at 

30 minutes after oral dosing of 4 mg/kg AN to three male F344 rats. On the other hand, CEO 

concentration in mice 5 minutes after oral administration was about 10 times higher than that 

reported at 30 minutes after oral dosing of 4 mg/kg AN to three male B6C3F1 mice (Roberts et 

al., 1991). These results suggested that CEO was rapidly cleared in both rats and mice and that 

the clearance of CEO in mice was more rapid than in rats. 

Kedderis et al. (1993b) also administered 3 mg/kg [2,3-14C]-CEO orally to F344 rats and 

B6C3F1 mice to determine the tissue distribution of radioactivity from labeled CEO after 2 and 

24 hours. Radioactivity from labeled CEO was widely distributed in major organs of rats and 

mice 2 hours after administration, with the highest level of radioactivity found in the stomach 

and intestines of rats and mice. However, radioactivity detected in the stomach and intestines of 
 DRAFT - DO NOT CITE OR QUOTE 13 

mice was only about 15 and 40%, respectively, of that detected in rats, suggesting that mice 

absorbed CEO more rapidly than rats (Kedderis et al., 1993b). By 24 hours, radioactivity 

decreased by 71–90% in all tissues, including the brain, liver, and lung. Stomach and intestines 

continued to retain the highest level of radioactivity, probably due to covalent binding of CEO to 

macromolecules in these organs. 

 Burka et al. (1994) monitored the tissue distribution of radiolabel derived from 

[2-14C]-AN after oral dosing at 0.87 mmol/kg (46 mg/kg) to untreated, phenobarbital 

(PB)-pretreated, or SKF 525A pretreated male F344 rats (three/group). PB induces a number of 

CYP450 isozymes, including CYP2B1 and CYP2B2, whereas SKF 525A is a general inhibitor 

of CYP450. After 24 hours, about 10% of the administered dose in untreated rats was present in 

the blood with a further 4% sequestered in the tissues. In PB-pretreated rats, a 40% increase in 

AN-derived radioactivity was found in both the liver and glandular stomach when compared 

with rats treated with AN alone, with no changes in other tissues. However, AN-derived 

radioactivity in most tissues of SKF 525A pretreated rats were up to 278% higher, suggesting the 

involvement of CYP450 metabolism in the disposition of AN and/or its metabolites. (AN reacts 

more rapidly with tissue nucleophiles than CEO; hence, decreasing its oxidative metabolism to 

CEO would increase tissue binding of radiolabel.) Because PB pretreatment had little effect on 

tissue distribution, the isoforms of CYP450 induced by PB are probably not the ones involved in 

the metabolism of AN. It is known that AN is metabolized by CYP2E1, not CYP2B1 or 

CYP2B2, to CEO (see Section 3.3). PB might increase AN-derived radioactivity in the liver and 

stomach by inducing other enzymes, such as nicotinamide adenine dinucleotide phosphate 

(NADPH)-cytochrome CYP450 reductase. 

 Ahmed et al. (1996a) monitored the tissue distribution of AN-derived radioactivity in 

F344 rats (four/group) up to 48 hours following i.v. injection of 11.5 mg/kg of [2-14C]-AN 

(50 μCi/kg). The study authors used whole-body autoradiography to chart a time course of tissue 

deposition and obtained the highest levels of activity in lung (998 nCi/mg), intestinal contents 

(752 nCi/mg), liver (713 nCi/mg), and spleen (539 nCi/mg) 5 minutes after dosing. Other tissues 

with high radiolabel at this time point were the kidney (283 nCi/mg), epididymis (266 nCi/mg), 

adrenal gland (241 nCi/mg), intestinal mucosa (245 nCi/mg), heart-blood (166 nCi/mg), bonemarrow (178 nCi/mg), thyroid (121 nCi/mg), adipose tissue (169 nCi/mg), and lacrimal gland 

(122 nCi/mg), while the brain, spinal cord, and testis had the lowest levels of radioactivity. At 

8 hours after dosing, the contents of the large intestine, especially the cecum, had the highest 

level of radioactivity (852 nCi/mg). Radioactivity in brain (92 nCi/mg), lacrimal gland 

(294 nCi/mg), and thyroid (211 nCi/mg) peaked at 24 hours after dosing, while radioactivity 

level in bone marrow (698 nCi/mg) peaked at 48 hours. Covalent bound radioactivity, as 

determined after acid-extraction techniques on freeze-dried sections, was observed in the spleen, 

liver, bone marrow, and lung. 
 DRAFT - DO NOT CITE OR QUOTE 14 

3.3. METABOLISM 

A proposed scheme for the metabolic pathways of AN in mammals is shown in 

Figure 3-1. The scheme has been developed as a result of studies on the identification of urinary 

metabolites following acute exposure (Fennell and Sumner, 1994; Kedderis et al., 1993a; Fennell 

et al., 1991; Turner et al., 1989; Müller et al., 1987; Tardiff et al., 1987; Gut et al., 1985; 

Kopecky et al., 1980; Langvardt et al., 1980), measurements of the in vivo modulation of 

AN-induced toxicological and biochemical changes by enzyme inhibitors or inducers (Wang et 

al., 2002; Sumner et al., 1999; Burka et al., 1994; Kedderis et al., 1993c; Pilon et al., 1988a, b; 

Ghanayem and Ahmed, 1986; Ahmed and Abreu, 1981; Abreu and Ahmed, 1980), determination 

1996a), and analysis of metabolites formed in vitro by subcellular fractions of liver, lung, and 

kidney in response to AN administration (Mostafa et al., 1999; Kedderis et al., 1995; Kedderis 

and Batra, 1993; of the subcellular distribution of metabolic products of AN (Nerland et al., 

2001; Ahmed et al., Roberts et al., 1991, 1989; Hogy, 1986; Geiger et al., 1983; Ahmed and 

Abreu, 1981; Guengerich et al., 1981; Abreu and Ahmed, 1980). 

CH2 CH

O

CN

H2C CH C N

CYP2E1

Acrylonitrile

RSCH2CH2CN

GS CH2CH2CN

S CH2CH2CN

HOOC CH2 S CH2CH2CN

N-acetyl-S-(2-cyanoethyl)cysteine

OH

CHO

+ CN- SCNThiocyanate

rhodanese

GS CHCN

CH2OH

S CHCN

CH2OH

N-acetyl-S-(1-cyano-2-hydroxyethyl)cysteine

GSH

GS CH2 CHCN

OH

Cyanohydrin

CN- SCNThiocyanate

rhodanese

GS CH2CHO

S-2-oxoethylglutathione

GSH

Cys S CH2COOH

S CH2COOH

S-(carboxymethyl)cysteine

N-acetyl-S-(carboxymethyl)cysteine

S CH2CH2OH

N-acetyl-S-(2-hydroxyethyl)cysteine

HOOC CH2 S

O

CH2COOH

Thionyldiacetic acid

CH2 O

H

NC

Cyanoacetaldehyde

spontaneous

rearrangement

CH2 O

OH

NC

Cyanoacetic acid

CH2

NC

H

H

OH

Cyanoethanol

CH2

GSH

Cyanide

Cyanide

Ac-N-Cys

Ac-N-Cys

Ac-N-Cys

Glycol

epoxide aldehyde

hydrolase

glutathione

S-transferase

Ac-N-Cys

2-Cyanoethylene

 oxide

S-(2-cyanoethyl)thioacetic acid

S-(2-cyanoethyl)glutathione

Source: National Toxicology Program (NTP) (2001). 

Figure 3-1. Scheme for the metabolic transformation of AN. 
 DRAFT - DO NOT CITE OR QUOTE 15 

 Primary components of the scheme are formation of CEO by the action of mixed function 

oxidases (predominantly CYP4502E1), detoxification of AN by interaction with GSH, and 

covalent binding of AN reactive metabolite to other biological macromolecules. 

In rats, CYP2E1 is present in the liver and widespread among other tissues. This isoform 

can be induced in the tongue, esophagus, forestomach squamous epithelia (Shimizu et al., 1990), 

and intestinal mucosa (Subramanian and Ahmed, 1995). It is present, albeit at levels 10–

20 times lower than in liver, in such tissues as kidney and lung. It is also present in the brain 

(Geng and Strobel, 1993; Sohda et al., 1993). The formation of CEO has important implications 

for the toxicity of AN, because the intermediate has been proposed as the principal carcinogenic 

metabolite of AN. However, CEO can undergo a number of further transformations. These 

include the interaction with GSH to form a series of cysteine or N-acetyl cysteine derivatives and 

the production of cyanide via the action of epoxide hydrolase (EH). Subsequent detoxification 

of cyanide to thiocyanate is thought to occur under the action of rhodanese (Kopecky et al., 

1980). 

3.3.1. Oxidation of AN to CEO 

 Evidence for the oxidation of AN to CEO and its subsequent transformations came from 

a number of studies. Abreu and Ahmed (1980) studied the in vitro conversion of AN to cyanide 

in subcellular fractions of liver from Sprague-Dawley rats (also reported in Ahmed and Abreu 

[1981]). The metabolic activity was localized in the microsomal fraction and required NADPH, 

MgCl2, and oxygen for maximal activity. Determination of the kinetic parameters (Km and Vmax)

of the transformation of AN to cyanide pointed to a higher affinity and faster rate of product 

formation in microsomes from rats pretreated with CYP450-inducing agents, such as 

Aroclor 1254 and PB. (Six AN concentrations ranging from 10 to 300 mM were used for each 

preparation.) The Km values calculated for the PB and Aroclor 1254 preparations were 54.8 and 

40.9 mM, respectively, and were lower than the control (190 mM). Pretreatment of rats or 

addition to incubation mixtures with agents that inhibit CYP450 activity, such as SKF 525A or 

cobalt chloride, reduced the amount of cyanide formed by rat liver microsomes. 

 Abreu and Ahmed (1980) studied the effect on cyanide formation when 1,1,1-trichloropropane-2,3-oxide (TCPO), a specific inhibitor of EH, was added to the microsomal incubation 

mixtures. Production of cyanide was dose-dependently reduced to 19% of control levels at 

TCPO concentration of 1 × 10-2 M. Abreu and Ahmed (1980) also tested the effect of sulfhydryl 

compounds on microsomal metabolism of AN, as measured by the rate of cyanide formation. 

Only cysteamine decreased cyanide formation; other sulfhydryl compounds, including GSH and 

cysteine, enhanced the rate of cyanide formation from AN. 

Abreu and Ahmed (1980) suggested that probably more than one step was involved in the 

enzymatic conversion of AN to cyanide. The study authors proposed the initial product of AN 

oxidation to be CEO, which could then undergo a number of alternative transformations, one of 
 DRAFT - DO NOT CITE OR QUOTE 16 

which would be non-enzymatic conversion to cyanide. That another transformation might 

involve EH was indicated by the decrease in cyanide formation following administration of the 

inhibitor TCPO. Because cyanide production was enhanced in the presence of sulfhydryl 

compounds, such as GSH, chemical interaction of CEO with GSH could lead to formation of 

cyanohydrin. Rearrangement of this cyanohydrin to an aldehyde could result in the release of 

cyanide. Cysteamine might diminish cyanide formation due to its inhibition of CYP450-

dependent metabolism (Buckpitt et al., 1979). 

Geiger et al. (1983) studied the conversion of AN to its metabolic products in isolated rat 

hepatocytes and demonstrated the formation of CEO and its hydrolysis to cyanide, which itself 

was transformed and detected as thiocyanate. 

In vitro incubation of AN with liver microsomes isolated from male F344 rats pretreated 

with inhibitors or inducers of specific members of the CYP450 family of mixed function 

oxidases indicated that CYP2E1 is the major catalyst in the oxidation of AN to CEO (Kedderis et 

al., 1993c). The rate (Vmax) at which rat liver microsomes oxidized AN to CEO was increased 

more than fivefold from Vmax of 366 pmol CEO/minute-mg for untreated rats following acetone 

pretreatment, although Km was increased from 11 to 19 μM. Because acetone is a potent inducer 

of CYP2E1, the data suggest that this isoform is a primary catalyst of AN epoxidation in rats. 

Treatment with β-naphthoflavone to induce CYP1A1 and CYP1A2 or with dexamethasone 

(DEX) to induce the CYP3A enzymes increased Vmax only less than twofold, but Km was 

increased by 3.5 and 5.2-fold, respectively, for AN epoxidation in these two pretreatment 

systems. Treatment with PB to induce CYP2B1 and CYP2B2 slightly decreased the Vmax but 

increased the Km in microsomes from rats. These studies demonstrated that other forms of 

CYP450 (CYP2B1, CYP2B2, and the 3A enzymes) can oxidize AN but with specific activities 

much lower than CYP2E1. 

 The effect of a number of CYP450 inhibitors on epoxidation of 1.2 mM AN by rat 

hepatic microsomes was investigated (Kedderis et al., 1993c). Neither SKF 525A nor 

metyrapone were effective inhibitors, retaining 87% of control activity. After treatment of rats 

with DEX or PB, SKF 525A became a more effective inhibitor, retaining 45 and 47% of control 

activity. Metyrapone also became a more effective inhibitor of epoxidation of AN after DEX 

treatment. The CYP450 ligand, 1-phenylimidazole, was a potent inhibitor of AN epoxidation 

(4% of control activity). Chlorzoxazone (27%), ethanol (42%), and diethyldithiocarbamate 

(17%) also inhibited this pathway. The changes in the degree of inhibition of epoxidation of AN 

following DEX and PB treatments could be interpreted as multiple CYP450 enzymes from rat 

hepatic microsomes were capable of oxidizing AN. 

Antibodies to CYP2E1 (sheep or goat anti-rabbit CYP2E1) inhibited more than 85% of 

AN epoxidation in liver microsomes from untreated or acetone-treated rats but only 40 and 60% 

inhibition following DEX and PB treatment, respectively (Kedderis et al., 1993c), suggesting 

that CYP450 enzymes other than CYP2E1 might participate in the epoxidation. However, it 
 DRAFT - DO NOT CITE OR QUOTE 17 

should be noted that the AN concentration in these in vitro studies was high (1 mM). Forms of 

CYP450 enzymes other than CYP2E1 might have been recruited to AN metabolism. 

Kedderis et al. (1993c) also investigated the kinetics of the epoxidation of 1.2 mM AN by 

using human hepatic microsomes. Km and Vmax values for oxidation of AN by liver microsomes 

from six uninduced individuals ranged from 12 to 18 μM and from 129 to 315 pmol/minute-mg, 

respectively. Antibodies to CYP2E1 produced 58–70% inhibition of AN epoxidation catalyzed 

by the six human liver microsomal preparations. This suggests that, while CYP2E1 was the 

major catalyst of AN epoxidation in humans, other isoforms of CYP450 may also be involved. 

Sumner et al. (1999) investigated the role of CYP450 in the metabolism of AN in mice. 

Three male wild-type (WT) mice and three to four male CYP450 2E1-null mice were treated 

orally with either 2.5 mg or 10 mg/kg of [1,2,3-13C] AN. Urinary metabolites in samples 

collected over 24-h were characterized using 13C nuclear magnetic resonance (NMR). In WT 

mice, urinary metabolites of CEO predominated, with metabolites derived from GSH 

conjugation at the 3-carbon of CEO accounting for 67–71%. Metabolites from GSH conjugation 

at the 2-carbon accounted for about 13%. Metabolites from direct GSH conjugation with the 

parent compound, AN, accounted for 15–21%. In the urine of CYP2E1-null mice, however, 

only metabolites from direct GSH conjugation were detected. Sumner et al. (1999) interpreted 

their data as indicating that CYP2E1 may be the only CYP450 involved in the metabolism of AN 

in mice. 

 Subramanian and Ahmed (1995), attempting to characterize the specific intestinal 

toxicity of AN, incubated microsomes isolated from male Sprague-Dawley rat intestinal mucosa 

in vitro with AN in the presence of NADPH. AN metabolism to cyanide was enhanced by the 

addition of sulfhydryl compounds such as GSH, cysteine, and D-penicillamine. AN metabolism 

to cyanide was also enhanced following the induction of microsomal proteins (MPs) by treating 

rats with PB (inducer of CYP2B1), β-naphthoflavone (inducer of CYP1A1), and 

4-methylpyrazole (inducer of CYP2E1). AN metabolism to cyanide was inhibited to 8 and 20% 

of control, respectively, when dimethyl sulfoxide (DMSO) or ethanol (competitive inhibitors of 

CYP2E1) was added to the incubation mixtures. 

Subramanian and Ahmed (1995) showed that the intestinal CYP450 isoform had a high 

affinity for AN, with a Km of 1.1 μM and a Vmax of 1,250 pmol/mg protein/minute. Addition of 

DMSO in varying concentrations (final 30 mM) increased the Km of the reaction to 10 μM, but 

Vmax remained unchanged. Since DMSO is a specific substrate and competitive inhibitor for 

CYP2E1, these studies indicated that CYP2E1 was the main CYP450 isoform that bio-activates 

AN in the intestine. In addition, anti-P450 3a immunoglobulin (Ig)G (which cross-reacts with rat 

CYP2E1) caused a concentration-dependent inhibition of the metabolism of AN to cyanide in the 

ethanol-induced intestinal microsomes (Subramanian and Ahmed, 1995). These results showed 

that CYP2E1 was the main intestinal mucosa enzyme metabolizing AN to cyanide. 
 DRAFT - DO NOT CITE OR QUOTE 18 

 Similarly, Abdel-Aziz et al. (1997) demonstrated the metabolism of AN to cyanide when 

AN was incubated in vitro with NADPH and a microsomal fraction prepared from SpragueDawley rat testis. The Vmax of this reaction was 65 pmol CN–

/mg protein/minute, and the Km

was 88.6 μM AN. Addition of SKF 525A or benzimidazole (competitive inhibitors of CYP450) 

to the incubation mixture inhibited the formation of cyanide, whereas microsomes obtained from 

PB-treated rats increased activation of AN to cyanide. Thus, AN was metabolized in rat testis 

via CYP450 mixed function oxidase. Addition of GSH, L-cysteine, D-penicillamine, or 

2-mercaptoethanol also enhanced the release of cyanide from AN. 

The capability of rat kidney to metabolize AN to cyanide was demonstrated by Mostafa 

et al. (1999) in an in vitro study that investigated the mechanism by which AN caused renal 

toxicity. In renal subcellular fractions from Sprague-Dawley rats, the metabolism of AN to 

cyanide was highest in the microsomal fraction. An NADPH-generating system in the presence 

of magnesium ions was required for maximal activity. The Vmax of this reaction was 118 pmol 

CN–/mg protein/minute, and the Km was 160 μM AN. Metabolism of AN to cyanide was 

increased when microsomes were obtained from PB-, ethanol-, 4-methylpyrazole-, and 

3-methylcholanthrene-treated rats. On the other hand, addition of SKF 525A or benzimidazole 

to the incubation mixture inhibited AN metabolism. These data suggested that AN was 

metabolized in the kidney via a CYP450-dependent mixed function oxidase system. Addition of 

GSH, L-cysteine, cysteamine, D-penicillamine, or 2-mercaptoethanol to the incubation mixture 

enhanced AN metabolism. 

Ahmed and Patel (1981) carried out a series of single-dose gavage experiments on male 

Sprague-Dawley rats and male Swiss mice at fractions of the LD50 values of AN and KCN. (The 

LD50 of AN is 93 mg/kg in rats and 27 mg/kg in mice; the LD50 of KCN is 10 mg/kg in rats and 

8.5 mg/kg in mice.) Cyanide was measured and detected in blood, liver, kidney, and brain of 

both rats and mice 1 hour after administration in a dose-dependent manner. However, cyanide 

concentrations from metabolism of one LD50 AN in blood and tissues of rats were significantly

lower than those produced from one LD50 of KCN. On the other hand, comparable 

concentrations of cyanide in blood and tissues were observed after one LD50 AN or KCN was 

administered to mice. Blood and liver contained higher amounts of cyanide per unit volume than 

kidney and brain (the other two organs evaluated). 

Observed signs of toxicity were also different in rats and mice administered an LD50 of

AN. Rats developed severe cholinomimetic signs including salivation, lacrimation, diarrhea, 

wheezing on expiration, and peripheral vasodilatation within 10 minutes after administration of 

93 mg/kg AN. These signs were not observed in rats treated with KCN. Severe central nervous 

system (CNS) effects such as depression, convulsions, and asphyxia were observed in rats 10–

20 minutes after treatment with 10 mg/kg KCN (LD50). These CNS signs of cyanide toxicity 

were observed in AN-treated rats 2–3 hours after dosing. No physiological adverse effects were 

observed in rats receiving 0.25 LD50 AN. Mild salivation, diarrhea, and vasodilation were 
 DRAFT - DO NOT CITE OR QUOTE 19 

observed after one-half LD50 AN in rats. However, in mice treated with equitoxic dose (LD50

27 mg/kg) AN, CNS signs identical to those observed after KCN was administered were 

observed. These results demonstrated species differences in the toxicity and metabolism of AN. 

Moreover, Ahmed and Patel (1981) showed that pretreatment of rats with Aroclor 1254 

and PB increased AN metabolism to cyanide in rats, and pretreatment of rats with CoCl2 or SKF 

525A decreased blood cyanide concentrations. These results showed that the AN 

transformations demonstrated by Abreu and Ahmed (1980) in vitro also could take place in vivo. 

In addition, increased metabolism of AN to cyanide would increase CNS effects. However, 

acute AN toxicity was also manifested as cholinomimetic signs, which were not from cyanide. 

 Shibata et al. (2004) employed headspace gas chromatography to simultaneously measure 

blood levels of AN and its metabolite, hydrogen cyanide, following oral administration to rats. 

Plasma and urinary thiocyanate concentrations were also measured by the colorimetric method. 

Male Wistar rats that received 40 mg/kg AN (about half the LD50) by gavage in water showed 

toxic signs such as tachycardia 1 hour later. Peak blood levels of AN (2 μg/mL) and cyanide 

(0.7 μg/mL) were detected 1.5 hours after dosing. By 2.5 hours after dosing, blood levels of AN 

had dropped to less than 0.2 μg/mL and blood levels of cyanide decreased to 0.1 μg/mL; at that 

time, thiocyanate was detected in plasma (20 μg/mL). Plasma thiocyanate concentrations rose 

over time, peaking at 5 hours (31.3 μg/mL). At the same time, excretion of thiocyanate in urine 

began to increase significantly. Ten hours after dosing, AN was still detectable in plasma at 

50 ng/mL, but cyanide had decreased to a background level of about 5 ng/mL. The cumulative 

urinary elimination of thiocyanate gradually increased, and at 10 hours, about 1.2 mg thiocyanate 

was excreted into the urine. This amount was calculated to be 7% of the total administered AN. 

Urinary AN level was not measured. 

The capacity for formation of CEO from AN has been demonstrated in F344 rat liver 

microsomes, lung microsomes, and isolated lung cells. The rate of CEO formation in rat lung 

was cell specific, with the Clara cell-enriched fraction having a rate of CEO formation 7 times 

greater than other cell fractions (Roberts et al., 1989). The overall rate of CEO formation was 

about 15 times greater in the livers than the lungs (Roberts et al., 1989). 

Roberts et al. (1991) provided data on the kinetics of CEO formation in liver and lung 

microsomes isolated from male F344 rats, B6C3F1 mice, and humans (Table 3-4). While CEO 

was produced in vitro by lung and liver microsomes in both rats and mice, the metabolite was 

produced at a greater rate in liver compared with lung and in mice vs. rats. These data 

potentially implicated the liver as the primary site of CEO formation after oral challenge with 

AN but suggested differences in the kinetics of CEO formation between species. The rate of 

CEO formation in microsomes isolated from human livers was comparable to that of F344 rats, 

but about 4 times lower than that of B6C3F1 mice. The average rate of CEO formation in liver 

microsome samples from six human donors was 501 ± 112 pmol/minute-mg protein. (The 

almost eightfold variation in enzymatic activity among these human samples appeared to 
 DRAFT - DO NOT CITE OR QUOTE 20 

correlate with the amount of CYP450 in each preparation.) However, after oral administration of 

AN, the concentration of CEO in mouse blood was about one-third that in rat blood at all doses 

and time points tested. Thus, blood CEO concentration did not correlate with rate of microsomal 

CEO formation, suggesting that species differences in detoxification of CEO might play a role in 

determining CEO concentrations in blood. The single human lung microsome sample tested in 

the study formed 0.55 pmol CEO/minute-mg protein, which was much lower than that for rat 

liver or lung microsomes. 

Table 3-4. Apparent kinetic parameters of CEO formation from AN in 

B6C3F1 mice, F344 rats, and humans 

Tissue Species Vmax (pmol/min-mg protein) Km (μM)a

Mouse 2,801a 67 

Rat 667a 52 

Liver 

Human 501b

 Not available 

Mouse 570a 1,229 

Rat 45a 1,854 

Lung 

Human 0.55c

 Not available 

aValues are the mean of eight replicates. 

bValue is the mean of six human donors. 

cValue is from one human donor. 

Source: Roberts et al. (1991). 

 Guengerich et al. (1981) used a reconstituted enzyme system containing purified rat liver 

CYP450 and NADPH-P450 reductase and a NADPH-generating system to oxidize AN in vitro 

to a metabolite that they identified colorimetrically as CEO. The extent of CEO accumulation 

was decreased by the addition of purified rat liver EH to the incubation medium. When 0.5 mM 

CEO was incubated with 30 μg/mL purified EH, the rate that CEO was hydrolyzed was 

5.5 nmol/minute. The rate of disappearance of CEO (due to nonenzymatic hydrolysis) was 

1.7 nmol/minute in the absence of EH or in the presence of inactivated EH. HCN was released at 

a rate of 1.5 nmol/minute during the hydrolysis of CEO by EH. (The rate of HCN release was 

0.2 nmol/minute in the absence of EH.) The study authors suggested that the reason the HCN 

release was not stoichiometric with epoxide disappearance might be due to a finite level of 

cyanohydrin existing in solution. A Km of 0.8 mM and a Vmax of 300 nmol/minute-mg based on 

disappearance of CEO was estimated for the hydrolysis of CEO by purified rat liver microsomal 

EH. The half-life of CEO in 0.1 M potassium phosphate was estimated to be about 2 hours at 

37°C (Guengerich et al., 1981). 

Kopecky et al. (1980) also investigated the role of EH and the generation of hydrogen 

cyanide from AN metabolism. AN was incubated in vitro with liver microsomes isolated from 

female Wistar rats, with and without cofactors (NADP, Mg2+, etc.) for 60 minutes. After the 
 DRAFT - DO NOT CITE OR QUOTE 21 

incubation, the mixtures were adjusted to either pH 1.8 (acidic processing) or 6.3 (alkaline 

processing). Cyanide released, in the presence of cofactors, was found to be fourfold higher 

under alkaline processing condition than acidic processing condition. The role of EH in AN 

metabolism in rats was supported by the increase in cyanide released after alkaline processing, 

indicating the existence of a cyanohydrin intermediate (glycolaldehyde cyanohydrin) in the 

biotransformation of AN. (Cyanohydrins generally decompose spontaneously to hydrogen 

cyanide and a carbonyl compound at pH higher than 7.) Moreover, when 3,3,3-trichloropropylene oxide (TPO), a potent inhibitor of EH, was added to the incubation mixture, the 

conversion of AN to cyanide was decreased by 70%. This result also provided evidence for the 

participation of the cyanohydrin in AN metabolism because the hydration of CEO to 

glycolaldehyde cyanohydrin was significantly inhibited by TPO. 

Kedderis and Batra (1993) compared the rates of CEO hydrolysis, enhanced by liver 

cytosol and microsomes from rats, mice, and humans, to the background rate of non-enzymatic 

hydrolysis displayed by the chemical. [2,3-14C]-CEO was incubated at pH 7.3 and 37°C for 

5 minutes with liver cytosol or microsomes. [2,3-14C]-CEO and its hydrolysis products were 

separated by high performance liquid chromatography (HPLC). The identity of the hydrolysis 

products could not be determined and did not correspond to aldehydes. Human hepatic 

microsomes enhanced the formation of hydrolysis products of CEO, whereas both human hepatic 

cytosol and liver cytosol and microsomes from F344 rats and B6C3F1 mice had no effect on 

hydrolysis product formation from CEO. The study authors concluded that rodent hepatic 

microsomal and cytosolic EHs were not active toward CEO, contrary to conclusions developed 

by Guengerich et al. (1981) on rat purified microsomal EH and the conclusions by Kopecky et al. 

(1980). 

One possible explanation that EH activity was not observed by Kedderis and Batra 

(1993) in microsomes from rats and mice was that their enzymatic reactions had not been 

optimized. No cofactors were used in the incubation mixture, and the incubation duration was 

only for 5 minutes. Both Kopecky et al. (1980) and Guengerich et al. (1981) used an NADPHgenerating system in their incubation mixture. 

Kedderis and Batra (1993) also showed that the heat-labile human EH activity was 

inhibited by the specific inhibitor, 1,1,1-trichloropropene oxide (median inhibitory concentration 

[IC50] of 23 μM), indicating that EH was the catalyst in the hydrolysis of CEO. The half-life of 

CEO in sodium phosphate buffer (pH 7.3), as estimated from hydrolysis by human liver 

microsomes, was 99 minutes. Estimated Km using liver microsomes from six individuals ranged

from 0.6 to 3.2 mM. Vmax ranged from 8.3 to 18.8 nmol hydrolysis products/minute-mg protein. 

The affinity of the human liver microsomal EH for CEO was relatively low, suggesting that the 

contribution of the hydrolysis pathway to the clearance of CEO would be small at low substrate 

concentrations. Increase in microsomal hydrolysis was observed after treatment of mice and rats 
 DRAFT - DO NOT CITE OR QUOTE 22 

with PB or acetone, suggesting that CEO hydrolysis is inducible. However, treatment of rats and 

mice with AN did not induce hepatic EH activity towards CEO (Kedderis and Batra, 1993). 

Studies that demonstrated that EH is present in rats and humans are also available. 

Immunoblot analysis of MPs was used by de Waziers et al. (1990) to measure EH in different 

organs and tissues of rats and humans. They reported that EH occurred in rat liver microsomes 

at 165 μg/mg protein and in human liver microsomes at 170 μg/mg protein. Therefore, the 

concentrations of EH in MP are similar in rats and humans. Guengerich et al. (1979) also 

reported that multiple forms of EH exist in rats and humans. 

EH activity was demonstrated in mice in a recent study, contrary to the conclusion by 

Kedderis and Batra (1993). El Hadri et al. (2005) demonstrated that microsomal EH was present 

in WT mice, which metabolized AN administered by gavage to cyanide in a dose- and timedependent manner. Blood cyanide levels in microsomal EH-null mice treated with a gavage 

dose of 0.047–0.38 mmol/kg AN were lower than levels in similarly treated WT mice. Blood 

cyanide level was also largely abolished in CYP2E1-null mice and in WT mice pretreated with a 

nonselective CYP inhibitor, 1-aminobenzotriazole (ABT), confirming that CYP2E1 was the key 

enzyme for the epoxidation of AN and the subsequent formation of cyanide. AN-treated 

CYP2E1- and mEH-null mice showed less severe symptoms of cyanide poisoning (labored 

breathing, lethargy, and trembling) than similarly treated WT mice (El Hadri et al., 2005). 

Significantly higher levels of AN-derived blood cyanide levels were observed in male mice than 

in female mice, suggesting gender-related differences in toxicity. Western blot analysis also 

demonstrated that expression of soluble EH was greater in male than female mice. 

 Detection and identification of urinary metabolites of AN from male F344 rats or B6C3F1

mice exposed orally to [1,2,3- 13C]-AN (10 or 30 mg/kg for rats, 10 mg/kg for mice), using 

13C NMR spectroscopy, also offered more information of its possible metabolic interactions 

(Fennel and Sumner, 1994; Fennel et al., 1991). As detailed in Section 3.4, some of the 

hypothetical metabolites of AN shown in Figure 3-1 were detected in the urine of animals 

exposed to AN. A major urinary metabolite in rats was N-acetyl-S-(2-cyanoethyl)cysteine, from 

conjugation of AN with GSH. Other metabolites, formed following oxidation of AN to CEO and 

subsequent conjugation to GSH, were identified as N-acetyl-S-(2-hydroxyethyl)cysteine, 

thiodiglycolic acid, S-carboxylmethylcysteine, and thionyldiacetic acid, all derived from addition 

of GSH to the 3-position of CEO. Thiocyanate was detected in urine as a metabolite of released 

cyanide. Moreover, N-acetyl-S-(1-cyano-2-hydroxyethyl)cysteine was formed after addition of 

GSH to the 2-position of CEO (Fennel and Sumner, 1994). These metabolites were also found in 

mouse urine. 

 Species differences in the extent of AN metabolism via oxidation to CEO, and 

subsequent conjugation of CEO with GSH, may exist. Fennell et al. (1991) and Fennell and 

Sumner (1994) noted differences in the relative abundance of these urinary metabolites in mice 

compared with rats. After oral administration of 10 mg/kg AN to mice, 80% of the urinary 
 DRAFT - DO NOT CITE OR QUOTE 23 

metabolites were derived from CEO, most notably thiodiglycolic acid and S-(carboxymethyl)-

cysteine. By contrast, these metabolites made up only 60% of metabolites in the urine from rats 

administered orally with 10 or 30 mg/kg AN. This difference indicated that more CEO was 

produced in the mouse than in rats. In addition, the ratio of metabolites derived from glutathione 

conjugation of CEO at the 2- and 3-positions determined the amount of cyanide released, since 

cyanide is released from CEO metabolites conjugated at the 3-position. This ratio was 0.43 in 

rats and 0.21 in mice, indicating that a greater percentage of the CEO produced in mice was 

metabolized to release cyanide. Thus, mice were likely to be exposed to a higher cyanide level 

produced from CEO, possibly accounting for the greater acute toxicity of AN in the mouse 

(Fennel and Sumner, 1994). 

Wang et al. (2002) confirmed the central role of CYP2E1 in the metabolism of AN to 

cyanide via CEO. Male WT and CYP2E1-null mice were dosed by gavage with 0, 2.5, 10, 20, or 

40 mg/kg AN, and cyanide was measured in blood and tissues. Expression of CYP2E1 and EH 

was monitored concurrently using Western blot techniques. Cyanide concentrations in blood and 

tissues of AN-treated WT mice increased dose dependently but remained at background levels in 

CYP2E1-null mice or control WT mice. Results from Western blots showed CYP2E1 to be well 

expressed in the liver, kidney, and lung of WT mice and not detected in tissues of CYP2E1-null 

mice. EH was equally expressed in both WT and CYP2E1 mice, supporting the hypothesis that 

CYP2E1-mediated oxidation of AN is an early step in the metabolism of AN to cyanide. The 

role of cyanide in the acute toxicity of AN was confirmed by the lack of acute symptoms of AN 

toxicity in CYP2E1-null compared with WT mice. Pretreatment of WT mice with a universal 

CYP450 inhibitor, ABT, likewise blocked cyanide formation and abolished the symptoms of 

acute toxicity. Wang et al. (2002) concluded that the metabolism of AN to CEO was exclusively 

catalyzed by CYP2E1. 

3.3.2. Interaction of AN with GSH 

 A succession of research findings showed that AN conjugates with GSH, both nonenzymatically or by being catalyzed by glutathione transferase. Young et al. (1977) suggested 

that since the toxicity of AN was due to the parent compound (AN) or its oxidative metabolites, 

the cyanoethylation of sulfhydryl-containing compounds, such as GSH or cysteine, by AN 

represented a detoxification mechanism. This metabolic pathway was shown indeed to play a 

role in the detoxification of AN (Ghanayem and Ahmed, 1986; Ghanayem et al., 1985; Appel et 

al., 1981). The toxicity of AN would be expected to increase in severity as the GSH level 

becomes depleted (Benz et al., 1997a). 

 Kopecky et al. (1980) administered 0.75 mmol/kg AN or 0.5 mmol/kg [1-14C]-AN to 

female Wistar rats by different routes (oral, i.p., subcutaneous [s.c.], and i.v.) and measured 

radioactivity and thiocyanate excreted in the urine. “Non-thiocyanate” metabolites excreted in 

urine constituted about two-thirds of the administered dose. Paper chromatography of the 
 DRAFT - DO NOT CITE OR QUOTE 24 

metabolites in urine identified AN mercapturic acid as the key metabolite. Kopecky et al. (1980) 

proposed that there were at least two pathways for AN metabolism. The minor route was 

oxidative metabolism to cyanide, which was further metabolized to thiocyanate and other “nonthiocyanate” metabolites. The major route was conjugation with glutathione, catalyzed by 

glutathione S-alkenetransferases, to N-acetyl-S-(2-cyanoethyl)cysteine. 

Further support for this proposition came from Geiger et al. (1983), who studied AN 

metabolism in isolated F344 rat hepatocytes. GSH levels and AN-protein binding were 

measured after incubating rat hepatocytes with [1-14C]- or [2,3-14C]-AN. GSH-adduct levels 

were determined by chromatographic procedures of aliquots of the trichloroacetic acid 

supernatant. Exposure to AN at 5 or 10 mM resulted in decrease of GSH levels to 15–20% of 

controls within 10 minutes. The primary radiolabeled product was S-(2-cyanoethyl)glutathione, 

and not S-(2-oxoethyl)GSH (the compound formed by reaction of CEO with GSH in the 

presence of purified GSH transferase). 

Indirect evidence for the involvement of GSH in the metabolism of AN was provided by 

Langvardt et al. (1980, 1979), who used gas chromatography-mass spectrometry and gas 

chromatography-infrared spectroscopy to identify urinary components in male Sprague-Dawley 

rats 16 hours after exposure to [1-14C]- or [2,3-14C]-labeled AN by gavage. They identified two 

major components: the first was N-acetyl-S-(2-cyanoethyl)cysteine, which they assumed to be a 

product of AN conjugation with GSH, and the other was thiocyanate. A third metabolite, 

N-acetyl-S-(2-cyanoethyl)cysteine, was tentatively identified and was proposed by Langvardt et 

al. (1980) to have resulted from the action of GSH on the epoxide intermediate. The authors 

speculated that the detoxification of AN likely involved conjugation with GSH, and the toxicity 

of AN was likely affected by the status of GSH pools in target tissues, since a rapid and dosedependent decrease in GSH stores in the liver, lungs, kidney, and adrenals was observed by 

Szabo et al. (1977) after i.v. injection of 1–15 mg/100 g AN to Sprague-Dawley rats. A sharp 

decrease in cerebral GSH concentrations occurred between 5 and 15 mg/100 g AN and correlated 

with the occurrence of mortality. On the other hand, oral dosing of 0.002–0.05% AN to rats for 

21 days resulted in up to 25% increase in hepatic GSH and might represent a rebound 

phenomenon (Szabo et al., 1977). 

 Benz et al. (1997a) studied the time and dose dependence of the depletion of tissue GSH 

and tissue cyanide and the covalent binding to tissue after s.c. injection of 0, 20, 50 (LD10), 

80 (LD50), or 115 mg/kg (LD90) AN to male Sprague-Dawley rats. GSH levels in liver were the 

most sensitive marker of AN exposure and were depleted by 50% at 20 mg/kg, a dose without 

overt toxicity. At 50 mg/kg, the threshold dose for overt toxicity, GSH was depleted by ≥85% 

and followed by a rapid recovery of 60% at 4 hours. Liver GSH was depleted almost completely 

within 30 minutes when rats were injected with 80 mg/kg AN. The depletion was sustained 

through 120 minutes and followed by 40% recovery through the end of study period of 4 hours. 

Blood and brain GSH were more resistant to the GSH depleting effects of AN and were depleted 
 DRAFT - DO NOT CITE OR QUOTE 25 

less extensively in a dose-dependent manner as the doses were in the toxic range. (The highest 

dose of 115 mg/kg depleted only 40% brain GSH at 2 hours.) In addition, brain GSH levels 

showed little capacity for recovery during the study period, unlike liver and kidney. Glandular 

and forestomach GSH were also dose-dependently depleted by AN treatment and were unable to 

recover within the study period. 

GSH depletion was accompanied by a dose-dependent increase of cyanide in the blood 

and brain during the first 60 minutes. At the lowest dose of 20 mg/kg, blood and brain cyanide 

declined after 60 minutes. At the higher doses, blood and brain cyanide continued to increase to 

120 minutes and then declined. Covalent binding of AN to tissue protein increased in all tissues 

rapidly during the first 30 minutes at all doses. At 20 mg/kg, covalent binding reached a plateau 

at 30 minutes. At the three higher doses, covalent binding continued to increase after 30 minutes 

and reached a plateau level by 2–4 hours. Benz et al. (1997a) concluded that when liver GSH 

was depleted, detoxification of AN was terminated. Acute AN toxicity became apparent, and a 

sustained increase in covalent binding to tissue protein was observed. 

 Further experiments by Ahmed and coworkers (Ahmed et al., 1983, 1982; Ghanayem and 

Ahmed, 1982) confirmed the involvement of hepatic GSH in AN metabolism. For example, 

when bile was collected from male Sprague-Dawley rats given a single oral dose of 46.5 mg/kg 

AN containing 12 μCi/kg [1-14C]-AN, four metabolites were isolated and characterized in biliary 

extracts at 6 hours after treatment. The two main metabolites were S-cyanoethyl glutathione and 

N-acetyl-S-(2-cyanoethyl)cysteine (Ghanayem and Ahmed, 1982). Both were glutathione 

conjugates of AN. Pretreatment of rats with diethyl malate (a glutathione-depleting agent) 

significantly decreased or abolished all of the metabolites in the bile. The study authors 

proposed GSH conjugation as a major pathway of AN metabolism, probably catalyzed by 

glutathione transferases. The product, S-cyanoethyl glutathione, is further metabolized to 

N-acetyl-S-(2-cyanoethyl)cysteine. Nearly 27% of the administered dose was excreted in the 

bile after 6 hours (Ahmed et al., 1982). 

 Kedderis et al. (1995) compared the kinetics of AN and CEO interaction with GSH in 

vitro by measuring the formation of conjugates when [2,3-14C]-labeled AN or CEO were 

incubated for a very short time (20 seconds for mice, 30 seconds for rats) with [glycine2-3H]-GSH in the presence of microsomal and cytosolic subcellular fractions of human, rat, or 

mouse liver. Because of the rapid non-enzymatic reaction of AN and CEO with GSH at pH 7.3, 

the steady-state kinetics of GSH conjugation were determined at pH 6.5. HPLC-mass 

spectrometry was used to separate and identify the conjugates, which included S-(2-cyanoethyl)-

glutathione from AN; and S-(1-cyano-2-hydroxyethyl)glutathione and S-(2-cyano-2-hydroxyethyl)-glutathione from CEO. The apparent kinetic parameters for the conjugation reactions 

(Vmax app and Km app) were estimated by fitting the Michaelis-Menten equation to the data, giving 

estimates of Vmax app for the conjugation reactions catalyzed by mouse cytosolic enzymes that 

were four to six times greater than those for rat cytosolic enzymes at pH 6.5 (Table 3-5). These 
 DRAFT - DO NOT CITE OR QUOTE 26 

data suggest that mouse liver cytosolic glutathione-S-transferase (GST) has a greater capacity for 

conjugating AN and CEO than do rat liver enzymes. Initial velocity studies were also carried out 

with microsomes and cytosol from human liver, providing data to suggest that GSH conjugation 

of AN with human liver cytosol was broadly similar to that of rodent liver cytosol (Table 3-6). 

Table 3-5. Apparent kinetic parameters for glutathione conjugation of AN 

and CEO at pH 6.5 

Fixed substrate Species Vmax app (μmol/min-mg)a Km app (GSH) (mM)a

Rat 3.32 ± 0.29 17.47 ± 3.60 AN 

Mouse 21.68 ± 1.75 23.39 ± 3.99 

Rat 2.00 ± 0.20 9.36 ± 2.27 CEO 

Mouse 8.34 ± 0.75 15.12 ± 2.84 

aValues are the means ± SDs of three determinations.

Source: Kedderis et al. (1995). 

Table 3-6. Glutathione conjugation of AN and CEO with or without 

microsomal or cytosolic GST from rat, mouse, and human liver 

preparations 

Nanomoles of product 

Speciesa Substrate Non-enzymatic Microsomal Cytosolic 

Rat 32.6 ± 1.9b 36.1 ± 3.0b

Mouse 31.3 ± 1.2b 36.6 ± 1.4b

Human 

AN 25.5 ± 2.0 

19.5–24.5c 25.2–34.4c

Rat 16.6 ± 1.1 25.2 ± 1.1b

Mouse 18.9 ± 1.0b 25.9 ± 3.7b

Human 

CEO 15.5 ± 1.3 

11.2–14.3c 12.6–14.5c

aRodent values are means ± SDs of three determinations. 

b

Statistically significantly greater than the non-enzymatic reaction (p < 0.05) as calculated by the authors. 

cRange of values for subcellular fractions prepared from six human subjects. 

Source: Kedderis et al. (1995). 

 In the same report, Kedderis et al. (1995) described the determination of the initial 

velocities of non-enzymatic vs. enzymatic GSH conjugation of AN and CEO at pH 7.3 in the 

absence or presence of GST (Table 3-6). Both substrates reacted rapidly with GSH in a nonenzymatic reaction, and addition of hepatic microsomes or cytosol from rats and mice 

statistically significantly enhanced the rate of product formation from AN (p < 0.05). Initial 

velocities indicated that AN conjugated more effectively with GSH than did CEO. Hepatic 

cytosol enhanced the rate of product formation from CEO to a greater extent (up to 52% higher) 

than did microsomes, suggesting that rodent cytosolic GST is more active toward CEO than 
 DRAFT - DO NOT CITE OR QUOTE 27 

microsomal GST. Under physiological conditions (pH 7.3), addition of liver cytosol from four 

out of six individuals similarly enhanced GSH conjugation with AN but not CEO. Human liver 

microsomes did not enhance the velocity of CEO or AN conjugation with GSH, suggesting that 

human microsomal GST forms do not catalyze this reaction (Table 3-6). 

Similarly, Guengerich et al. (1981) studied the reaction of AN and CEO with glutathione 

in vitro. The pseudo first-order rate constant for disappearance of GSH at pH 7.7 (37°C) was 

0.28/minute, when 0.5 mM was mixed with 0.1 M AN. The rate constant for the disappearance 

of GSH in the presence of 0.1 mM CEO was 0.11/minute. 

 Guengerich et al. (1981) also incubated [1-14C]-AN or -CEO with GSH at pH 6.5 in the 

presence of cytosolic fraction from rat liver, human liver, or rat brain to determine GST activity. 

Rat liver cytosol showed GSH S-transferase activity towards AN, with a Km of 33 mM and a 

Vmax of 57 nmol/minute-mg protein. Human liver and rat brain cytosolic fraction had no activity 

towards AN. Rat liver also showed activity towards CEO, with activity in rat brain more than an 

order of magnitude lower. 

 The importance of sulfhydryl compounds in the detoxification of AN was shown in a 

number of studies, particularly by the demonstration that treatment with exogenous sulfhydryl 

compounds could protect the organism from the harmful effects of AN. Appel et al. (1981) 

reported that sulfhydryl compounds such as cysteine were effective antidotes for both orally and 

intraperitoneally administered lethal doses of AN in rats. N-acetyl-cysteine was ineffective 

when given intraperitoneally and less effective than cysteine when administered orally. The 

GSH-depleting effect of a single s.c. dose of AN administered to male Sprague-Dawley rats and 

the subsequent GI bleeding and gastric mucosal necrosis could be blocked by pretreatment with 

sulfhydryl-containing agents such as L-cysteine or cysteamine (Ghanayem and Ahmed, 1986; 

Ghanayem et al., 1985). 

 Benz et al. (1990) studied the effectiveness of D- or L-cysteine and N-acetyl-D-cysteine 

or N-acetyl-L-cysteine in the detoxification of acutely administered AN by determining the s.c. 

LD50 of AN in male Sprague-Dawley rats either administered AN alone or in combination with 

individual antidotes. The LD50 of AN alone was determined to be 74.7 mg/kg. The LD50 of AN 

when combined with other antidotes ranged from 93.3 mg/kg (with N-acetyl-D-cysteine) to 

151.4 mg/kg (with L-cysteine). The antidote protective index ranged from 1.25 for N-acetyl-Dcysteine to 2.03 for L-cysteine. Thus, N-acetyl-D-cysteine was less effective than other antidotes 

in reducing acute lethality. Measurement of urinary N-acetyl-S-cyanoethyl cysteine, which was 

derived from conjugation with GSH pathway, following s.c. injection of 50 mg/kg AN alone or 

AN plus an antidote, indicated that none of the antidotes significantly increased the excretion of 

this metabolite. 

Blood cyanide levels were also measured in rats at 0.5, 1, 2, 4, and 6 hours following s.c. 

injection of 50 mg/kg AN or AN plus an antidote. Benz et al. (1990) showed that all of the 

antidotes, except N-acetyl-D-cysteine, lowered blood cyanide levels. Since N-acetyl-D-cysteine 
 DRAFT - DO NOT CITE OR QUOTE 28 

was the least effective antidote, the antidotal effectiveness of these cysteine enantiomers was 

related to their cyanide detoxification mechanism. Discussing these findings, Borak (1992) 

pointed out that, because both D- and L-cysteine provided equivalent protection against AN 

poisoning but only L-cysteine could be incorporated into GSH, the antidotal effects of these 

compounds may be unrelated to GSH repletion. In fact, since the potency of each antidote was 

proportional to their ability to lower cyanide levels, Borak (1992) suggested that their effects 

may be due to the ability of cysteine derivatives to serve as sulfur donors for the detoxification of 

cyanide via rhodanese-mediated transformation of cyanide to thiocyanate. The protection 

provided by these antidotes for cyanide poisoning from AN exposure, however, does not 

necessarily extend to other forms of AN-induced toxicity. 

3.3.3. Covalent Binding of AN and Its Metabolites to Subcellular Macromolecules 

 When isolated hepatocytes from male F344 rats were incubated with 1 mM [2,3-14C]-AN 

for 2 hours (Hogy, 1986; Geiger et al., 1983), a radiolabeled protein adduct was formed that 

could be characterized after the removal of residual AN and other low molecular weight products 

by dialysis. Analysis of the hydrolyzed non-dialyzable fraction indicated that about 75% of the 

radioactivity was contained in a single major peak that was chromatographically identified as 

S-(2-carboxyethyl)cysteine, the hydrolysis product of S-(2-cyanoethyl)cysteine, indicating direct 

cyanoethylation of cysteinyl residues by AN. When isolated hepatocytes were incubated with 

2 mM [2,3-14C]-AN for 60 minutes, Geiger et al. (1983) estimated the level of irreversible 

binding to protein to be 8.1 nmol/mg protein, a level of alkylation corresponding to modification 

of 1 in every 900 amino acid residues or roughly 1 of every 20 cysteine groups. In contrast to 

AN-protein binding, detection of binding of [2,3-14C]-AN-derived radiolabel to DNA and RNA 

in hepatocytes was limited by the low level of radioactivity that could be incorporated into 

[

14C]-AN because of polymerization and microsynthesis problems and by the high level of 

protein binding. Therefore, hepatocytes were incubated with 2 mM [2,3-14C]-AN for 60 minutes 

in the presence of extracellular calf thymus DNA (0.5 mg/mL) (Hogy, 1986; Geiger et al., 1983). 

RNA and both intracellular and extracellular DNA were isolated. The isolated RNA contained 

53 pmol AN metabolites per mg RNA of which 9 pmol/mg RNA could be attributed to the 

contaminating protein. The isolated extracellular DNA contained 47 pmol AN adducts per mg 

DNA, of which 30 pmol/mg DNA could be attributed to protein. A portion of incubated 

extracellular DNA was further purified; alkylation of extracellular DNA was not observed at a 

detection limit at 3.5 × 105 bases (Geiger et al., 1983). 

 Hogy and Guengerich (1986) treated an F344 rat intraperitoneally with 0.6 mg/kg 

[2,3-14C]-CEO to assess macromolecular binding in liver and brain 1 hour after treatment. DNA 

and RNA in liver and brain were isolated, and the amounts were estimated. Bound radioactivity 

was estimated by liquid scintillation counting. Covalent binding of CEO-derived radioactivity 

was detected in both liver and brain protein at rates of 1.1 and 1.0 alkylations per 106 amino 
 DRAFT - DO NOT CITE OR QUOTE 29 

acids, respectively. However, no covalent binding to DNA or RNA could be detected at the 

level of 0.3 alkylations per 106 bases in liver and brain. 

In another experiment by Hogy and Guengerich (1986), liver and brain DNA were 

isolated from three rats 2 hours after treatment with 50 mg/kg AN i.p. or 6 mg/kg CEO i.p. 

Using thin layer chromatography with fluorescent plates, the study authors were able to detect 

N

7

-(2-oxoethyl)guanine at 0.014 and 0.032 alkylations per 106 DNA bases in liver for rats treated 

with CEO and AN, respectively. This DNA adduct was apparently derived from CEO, 

consistent with its recovery after AN and CEO treatment. The apparent lineage of this DNA 

adduct was different from the protein adduct, S-(2-cyanoethyl)cysteine, described previously, 

which was derived from AN. 

N

7

-(2-oxoethyl)guanine was only at the level of detection in rat brain DNA. In addition, 

1,N6-ethenoadenosine or 1,N6-ethenodeoxyadenosine were not detected in liver DNA, using 

HPLC with fluorescence detector in the analyses of these two adducts. Binding of AN and/or 

CEO to DNA is also discussed in Section 4.5.1.2.1. 

As discussed in Section 3.3.2, when 0, 20, 50, 80, or 115 mg/kg [2,3-14C]-AN was 

injected subcutaneously into male Sprague-Dawley rats, GSH became almost completely 

depleted (>95%) in liver at 80 mg/kg within 30 minutes, while blood and brain GSH were more 

resistant to the depleting effect of AN. Brain and blood GSH were not affected at 20 mg/kg. 

The amount of cyanide in blood and brain increased dose dependently in the first hour after 

dosing (Benz et al., 1997a). Covalent binding to tissue proteins increased in a dose-dependent 

fashion during the first 30 minutes at all doses, with binding to blood proteins being 3–4 times 

greater than in any other tissue. Benz et al. (1997a) suggested that GSH depletion in liver was 

related to AN toxicity and covalent binding. 

 The effect of GSH depletion on the irreversible binding of AN to tissue macromolecules 

has been studied in male F344 rats exposed to 4 mg/kg [2,3-14C]-AN either by inhalation (Pilon 

et al., 1988a) or gavage (Pilon et al., 1988b). Binding of radiolabel to tissue macromolecules 

was evaluated in control rats or rats depleted of GSH by an i.p. injection of phorone (PH)/

buthionine sulfoximine (BSO) about 30 minutes prior to AN exposure. GSH contents in control 

rats were as follows: liver (17.3 μmol/g), kidney (4.5 μmol/g), lung (3.1 μmol/g), stomach 

(5.3 μmol/g), brain (3.9 μmol/g), and blood (4.2 μmol/g). A significant depletion of GSH was 

produced in liver (43%), kidney (42%), and lung (22%) after PH/BSO treatment. No significant 

depletion of GSH was observed in blood, brain, or stomach 30 minutes after a combined 

PH/BSO treatment. 

In the inhalation studies (Pilon et al., 1988a), three rats were exposed to initial AN 

concentrations of 0, 25, 50, 100, 500, or 750 ppm in a closed-circuit inhalation chamber for 

240 minutes. AN was not replenished during the exposure, and the decrease in chamber AN 

concentration was monitored by taking samples every 10 minutes during the exposure. Uptake 

of AN vapor by control rats showed two distinct phases: an initial, rapid phase that lasted about 
 DRAFT - DO NOT CITE OR QUOTE 30 

60 minutes, followed by a slower phase. An uptake rate of 4.82 mg/kg-hour was estimated for a 

concentration of 100 ppm using the uptake curve for the rapid phase. In GSH-depleted rats, the 

mortality rate was higher. The rate of AN uptake was increased in the rapid phase but decreased 

at 500 and 750 ppm. In the slow phase, uptake was similar to that in control rats for 

concentrations below 200 ppm, but was elevated at 500 and 750 ppm. 

Radioactivity irreversibly associated with tissue macromolecules was measured in control 

rats 1, 2, 4, 6, 12, or 24 hours after the AN dose. In GSH-depleted rats, radioactivity was 

measured 1, 6, or 24 hours postexposure. In most tissues, the concentration of AN-derived 

undialyzable radioactivity (ADUR) reached a maximum in ≤1 hour in both control and 

GSH-depleted rats. (In the brain, ADUR levels reached a maximum in 2 hours.) The time 

course of ADUR levels showed a plateau from 1 to 6 hours in studied organs of control rats, 

followed by a decrease thereafter during the next 6 hours. This was then followed by an increase 

between 12 and 24 hours in the lung and kidney (but not in the brain, stomach, and liver). The 

time course of ADUR levels in blood showed high level 1 hour after AN administration, 

decreased from 6 to 12 hours, and increased from 12 to 24 hours, resulting in a maximum level at 

24 hours. 

Total radioactivity recovered from brain, stomach, liver, kidney, and blood decreased by 

54% in GSH-depleted rats compared with controls at both 1 and 24 hours. In GSH-depleted rats, 

ADUR levels remained constant in all organs evaluated throughout the 24-hour postexposure 

period and were lower than those in controls. The kidney was the most affected organ, with an 

average 52% decrease in ADUR levels, followed by the liver (44%). ADUR levels in the brain, 

stomach, and lung of GSH-depleted rats were 31% lower when compared with controls. Blood 

ADUR levels were decreased by 50% in GSH-depleted rats. 

Irreversible binding of ADUR with total nucleic acids (RNA + DNA) of brain, stomach, 

and liver was also evaluated in control and GSH-depleted rats 1 hour after an inhalation dose of 

4 mg/kg (40 μCi) AN vapor. In control rats, ADUR in total nucleic acids was found to be 

highest in the brain (63 pmol AN equivalents/mg), followed by that in the stomach (20 pmol AN 

equivalents/mg) and the liver (12 pmol AN equivalents/mg). In GSH-depleted rats, ADUR in 

nucleic acids in the brain was about 50% lower than that in controls, but no change was detected 

in stomach or liver. ADUR in DNA could not be detected in any tissue of control or 

GSH-depleted rats. The study authors suggested that ADUR in DNA was not detected because 

the analytical method used was not sensitive enough to detect radiolabel bound to DNA. 

Nevertheless, a preferential binding of ADUR with brain RNA was observed in both control and 

GSH-depleted rats, with ADUR in brain RNA about 50% lower in GSH-depleted rats. 

It is unlikely that the observed decrease in radiolabel binding in GSH-depleted rats 

treated with PH/BSO was due to treatment effect on CYP2E1. BSO is a selective inhibitor of 

GST; PH depletes GSH in liver, kidney, and lung but not in the blood or brain by conjugation 
 DRAFT - DO NOT CITE OR QUOTE 31 

with GSH. PH was reported not to affect the hepatic microsomal mixed-function oxidase system 

(Younes et al., 1986). 

In the oral studies on male F344 rats, total radioactivity recovered in the tissues examined 

was similar in control and GSH-depleted rats at both 1 and 24 hours. However, significantly 

higher recovered radioactivity was found in stomach, lung, and blood of GSH-depleted rats than 

of control rats 1 hour after dosing, while the radioactivity in kidney was lower in GSH-depleted 

rats (Pilon et al., 1988b). 

The concentration of ADUR in brain reached a maximum in ≤1 hour for both control and 

GSH-depleted rats and remained constant for 24 hours. In GSH-depleted rats, 60–80% increase 

in ADUR was measured in brain at 1, 6, and 24 hours after dosing. The highest ADUR level was 

found in stomach and increased with time in control rats. ADUR levels in liver and kidney of 

control rats was characterized by an increase over the first 6 hours and a decrease between 5 and 

24 hours. GSH-depletion resulted in an increase in ADUR levels in liver, lung, kidney, stomach, 

blood, and brain between 6 and 24 hours after the dose. 

GSH depletion also caused a significant increase in ADUR levels in total nucleic acid 

(DNA + RNA) in both brain and stomach (one and a half- and threefold, respectively) 6 hours 

after the dose. No change was found in liver. ADUR associated with DNA was detected in 

stomach tissue of control rats only. Pilon et al. (1988b) suggested that ADUR levels reflected 

the relative concentration of covalently bound radioactivity in control and GSH-depleted rats and 

that the reaction of AN with protein and other macromolecules was responsible for the rapid 

increase in ADUR at ≤1 hour. The slower increase in ADUR in metabolically competent organs 

(liver, kidney, and lung) of control rats and all organs of GSH-depleted rats might represent the 

binding of CEO to macromolecules. Urinary excretion of thiocyanate, a final metabolite from 

the epoxide pathway of AN metabolism, was increased twofold in GSH-depleted rats. Since 

urinary thiocyanate is indicative of CEO formation, Pilon et al. (1988a) interpreted their results 

as indicating that more CEO was formed after GSH-depletion. 

Farooqui and Ahmed (1983a) also reported covalent binding of [2,3-14C]-AN to protein, 

DNA, and RNA of tissues of male Sprague-Dawley rats treated with a single oral dose of 

46.5 mg/kg. DNA from tissue homogenate was isolated by extraction with chloroform/isoamyl 

alcohol/phenol and application of the aqueous extract to hydroxyapatite chromatography. DNA 

alkylation was higher in brain and stomach than that in the liver, with highest levels of covalent 

binding in the brain. The covalent binding indices for the liver, stomach, and brain at 24 hours 

after dosing were 5.9, 51.9, and 65.3, respectively. 

Ahmed et al. (1992a) demonstrated the covalent binding of radiolabel from [2,3-14C]-AN 

to testicular DNA after a single gavage of radiolabeled AN (46.5 mg/kg) to male SpragueDawley rats. In a time course study, bound activity was shown to be greatest after 30 minutes 

(8.93 ± 0.80 μmol AN bound per mol nucleotide). Using an identical experimental protocol, 

Ahmed et al. (1992b) demonstrated the capacity of AN to bind covalently to DNA in the lung. 
 DRAFT - DO NOT CITE OR QUOTE 32 

Binding was associated with a 28–41% decrease in replicative DNA synthesis at time points up 

to 24 hours after dosing. 

 Jacob and Ahmed (2003a) used whole-body autoradiography to examine the distribution 

of [2-14C]-AN administered orally or intravenously to male F344 rats. Two days after oral 

dosing, covalently bound radioactivity was retained at higher levels in the gastric mucosa, blood, 

and hair follicles. After i.v. injection, covalently bound radioactivity was retained in liver, 

spleen, bone marrow, adipose tissue, and lung. The amount of radioactivity associated with 

covalent binding was lower for oral dosing than for i.v. injection, which was consistent with the 

higher recovery of radioactivity excreted following oral dosing compared with injection (see 

Section 3.4.2). 

Covalent binding of [2,3-14C]-AN to tissue protein and globin was also studied in male 

Sprague-Dawley rats after a single s.c. injection of 1.2–115 mg/kg (Benz et al., 1997b). 

Covalent binding to tissue protein reached completion in 1–4 hours and was linear in the low 

dose range (1.2–50 mg/kg), with the relative order (in descending order) as follows: blood > 

kidney = liver > forestomach = brain > glandular stomach > muscle. Covalent binding to globin 

followed a similar dose-response curve. Benz et al. (1997b) also measured an N-(2-cyanoethyl)-

valine (CEVal) adduct of globin at this dose range. This adduct was formed by reaction of AN 

with the NH2-terminal residue of globin (Osterman-Golkar et al., 1994) and represented only 

0.2% of total AN binding to globin. However, regression of tissue protein binding vs. globin 

total covalent binding or globin CEVal adduct indicated that both globin biomarkers could be 

used as surrogates for the amount of AN bound to tissue protein. 

 Using a similar dosing regimen, Nerland et al. (2001) employed sodium dodecyl sulfatepolyacrylamide gel electrophoresis to separate labeled proteins isolated from subcellular 

fractions of liver from treated rats. Binding of AN was found to be associated preferentially with 

GST of the μ subclass (GSTM). Within this subclass, GSTM1 was labeled about seven times 

more strongly than GSTM2, while, from the α-subclass, only GSTA3 was labeled (at about 

1/35 the strength of GSTM1). No label was associated with GSTA1 or GSTA2. The site of 

binding was identified as exclusively cysteine 86. Since this particular cysteine residue in 

rGSTM1 appeared to have been targeted specifically, the study authors hypothesized that high 

reactivity at cysteine 86 was due to its potential interaction with histidine residue at position 84, 

which would lower the pka of cysteine 86, increasing reactivity towards sulfhydryl reagents. 

These data would suggest that tissue proteins containing cysteine residues with an abnormally 

low pka value would be likely targets for AN. In an in vivo experimental approach, Nerland et 

al. (2003) demonstrated that subcutaneously administered AN preferentially bound to the 

cysteine 186 residue of carbonic anhydrase III (CAIII) in rat liver. 

 A considerable body of evidence demonstrated the ability of AN to bind to intercellular 

proteins, in particular to Hb. Osterman-Golkar et al. (1994) reported a method for quantifying an 

N-terminal cyanoethyl-valine adduct, CEVal, the product of reaction between AN and the 
 DRAFT - DO NOT CITE OR QUOTE 33 

N-terminal valine of Hb. The method was based on the N-alkyl Edman procedure involving the 

derivatization of globin with pentafluorophenyl isothiocyanate and gas chromatography-mass 

spectrometry analysis. Osterman-Golkar et al. (1994) showed that the method was applicable to 

experimental animals exposed to AN in drinking water and to humans exposed to AN in tobacco 

smoke. Hb from smokers (10–20 cigarettes/day) with a daily intake of 0.5–5 μg AN per kg BW 

contained about 90 pmol CEVal/g, whereas adduct levels in the Hb of nonsmokers were below 

the detection limit of about 20 pmol/g Hb. This utility was confirmed by Tavares et al. (1996) 

for occupationally exposed workers and for smokers. 

A subsequent study by Bergmark (1997) showed that the Hb of smokers contained 

adducts of ethylene oxide and acrylamide as well as AN. In nonsmokers, the CEVal Hb adduct 

of AN was below the detection limit of <2 pmol/g of globin. In the 10 smokers studied, the 

levels of this adduct ranged from 25 to 178 pmol/g (mean 106 pmol/g) and correlated with the 

number of cigarettes smoked per day (correlation coefficient = 0.94). 

Fennell et al. (2000) determined CEVal from blood samples of 16 nonsmokers and 

32 smokers and reported that CEVal Hb adducts increased with increased cigarette smoking. 

The estimated CEVal level from smoking was 170 fmol per mg Hb per pack-day. Two 

participants in a smoking cessation program showed a gradual reduction of CEVal levels (Perez 

et al., 1999). Thus, the use of the Hb adduct CEVal may have utility as a biomarker to assess 

low-level exposure to AN (in the region of 50 ppb), even in a complex mixture of toxicants, 

although smoking would be a confounding variable. Fennell et al. (2000) also reported that the 

null genotypes for GSTM1 or GSTT1 had little effect on CEVal levels when compared to active 

genotypes. 

 Borba et al. (1996) measured CEVal as a marker of AN exposure in occupationally 

exposed workers in an acrylic fiber factory. The values for CEVal among the subjects were 8.5–

70.5 pmol/g globin in controls, 635.2–4,603.5 pmol/g globin for continuous polymerization 

workers, and 93.9–4,746 pmol/g globin for maintenance workers. These findings pointed to the 

ready formation of AN adducts with Hb in an occupational setting. 

 CEVal Hb adduct was also used as a follow-up dose monitor after accidental exposure of 

four cleaning workers to AN in an AN-containing tank wagon (Bader and Wrbitzky, 2006). On 

day 25 after exposure, CEVal adduct levels in Hb ranged from 640 (blood sample partly 

hemolyzed) to 2,020 pmol/g globin for the three smokers and was 566 pmol/g globin for the 

nonsmoker, indicating residual AN adducts from the accidental exposure. On day 175, CEVal 

adduct levels were 81–276 pmol/g globin for the smokers and 2 pmol/g globin for the nonsmoker 

and represented background CEVal of the study participants according to their smoking status. 

For both the smokers and nonsmoker, the adduct concentrations in blood declined linearly with 

time. Linear regression analysis of the data estimated a total elimination interval of 148 days, 

longer than the standard lifespan of 126 days of erythrocytes. Linear regression analysis also 

allowed estimation of the initial adduct levels of the workers on the day of the accident and 
 DRAFT - DO NOT CITE OR QUOTE 34 

estimation of the exposed AN concentrations based on the correlation from the former German 

exposure equivalent that 3 ppm AN yields 17,200 pmol/g globin. 

3.4. ELIMINATION 

3.4.1. Studies in Humans 

 In an inhalation study of six male volunteers exposed to 7.8–10 mg/m3

 AN for 8 hours 

(Jakubowski et al., 1987), 44–58% (mean = 52%) of the inhaled AN was absorbed, of which 

about 22% of absorbed AN was metabolized and excreted in the urine over 31 hours from the 

start of exposure as N-acetyl-S-(2-cyanoethyl)-L-cysteine (2-cyanoethyl mercapturic acid 

[CEMA]). Elimination followed first-order kinetics, with a half-life of about 8 hours. The 

authors concluded that individual urinary CEMA levels were not a useful measure for exposure 

to AN. 

3.4.2. Studies in Animals 

 Three pathways are involved in the elimination of AN from an organism: exhalation, 

urinary excretion, or fecal excretion. 

3.4.2.1. Exhalation 

In a study by Young et al. (1977), male Sprague-Dawley rats were exposed to [1-14C]-AN 

via inhalation (5 or 100 ppm) or a single oral dose (0.1 or 10 mg/kg). Exhalation of AN as CO2

within 6 hours after dosing decreased with increasing dose, from 6.1 to 2.6% of the dose 

following inhalation exposure and from 4.6 to 3.9% after gavage (see Tables 3-1 and 3-2). 

When Ahmed et al. (1983) administered a single oral dose of 46.5 mg/kg AN to male 

Sprague-Dawley rats in distilled water, using 50 μCi/kg of either [2,3-14C]- or [1-14C]-AN as 

tracer, the recovery of total dose in expired 14CO2 varied from 2% for [2,3-14C]-AN to 12% for 

[1-14C]-AN 24 hours after dosing. Burka et al. (1994) administered 0.87 mmol/kg (46.2 mg/kg) 

[2-14C]-AN by gavage to male F344 rats. About 2% of the dose was expired as volatile organic 

components, predominantly unchanged AN, while 11% was liberated as 14CO2 24 hours after 

dosing. 

 Jacob and Ahmed (2003a) compared excretion of 11.5 mg/kg [2-14C]-AN administered 

orally or intravenously to male F344 rats. In the 48 hours after oral dosing, 61% of the 

radioactive dose was excreted, with 4% in exhaled CO2, 4% in urine, and 53% in feces. 

Following i.v. administration, 30% of the dose was eliminated over 48 hours, with 2% in expired 

air, 8% in urine, and 21% in feces. In the 8 hours after oral dosing, 3% of the radioactive dose 

was in exhaled CO2, 2% in urine, and 48% in feces. Following i.v. administration, 2% of the 

dose was in exhaled CO2, 3% in urine, and 0.2% in feces. Jacob and Ahmed (2003a) concluded 

that these results indicated a significant difference in biological fate of AN following i.v. or oral 

treatment. 
 DRAFT - DO NOT CITE OR QUOTE 35 

3.4.2.2. Fecal Excretion 

 Young et al. (1977) also investigated the fecal excretion of AN in male Sprague-Dawley 

rats. This route of excretion showed little dependence on the route of administration, amounting 

to 3–4% of the dose following inhalation exposure and about 5% following gavage within 

6 hours of dosing. Young et al. (1977) also investigated the possibility of biliary excretion with 

subsequent reabsorption from the intestines in one male rat. A cannula was inserted between the 

common bile duct and the duodenum for sampling of bile, and [14C]-AN was given 

intravenously. Based on the concentrations of radioactivity in bile, urine, RBCs, and plasma as a 

function of time, the rate of elimination from the bile was found to be faster than from other 

fluids during the first 6 hours after dosage. The initial half-life for excretion of radioactivity via 

bile was estimated to be about 15 minutes. One unidentified metabolite was excreted in the bile 

and underwent enterohepatic circulation to the GI tract, contributing partially to 5% of the dose 

excreted in feces. 

Kedderis et al. (1993a) estimated that 3–5% of AN doses were excreted in feces of F344 

rats (0.09–28.8 mg/kg orally), while 2–8% of the dose were recovered from the feces of B6C3F1

mice (0.09–10 mg/kg orally). In either species, the differences in fecal excretion were not 

related to the administered dose. Farooqui and Ahmed (1982) administered a single oral dose of 

46.5 mg/kg [1-14C]-AN to male Sprague-Dawley rats, the highest percentage of 14C excreted in 

feces (2%) occurred between 12 and 24 hours after dosing. At the end of 10 days, 2.5% of the 

dose was excreted in feces. In another study, male Sprague-Dawley rats were given a single 

gavage dose of 46.5 mg/kg [1-14C]-AN; four radioactive peaks were identified in biliary extracts 

at 6 hours after treatment. The two major metabolites in bile were GSH conjugates of AN: 

S-cyanoethyl glutathione and N-acetyl-S-(2-cyanoethyl)cysteine (Ghanayem and Ahmed, 1982). 

Nearly 27% of the dose appeared in the bile after 6 hours (Ghanayem and Ahmed, 1982; Ahmed 

et al., 1982). The GI tract contained the highest level of radioactivity up to 72 hours, suggesting 

resecretion of AN metabolites to the stomach or binding of metabolites to the stomach mucosa 

(Ahmed et al., 1982). 

3.4.2.3. Urinary Excretion 

 A substantial number of studies demonstrated the rapid urinary elimination of AN or its 

metabolites when AN was administered to experimental animals via the oral or inhalation routes 

(Burka et al., 1994; Fennell and Sumner, 1994; Kedderis et al., 1993a; Ahmed et al., 1983, 1982; 

Young et al., 1977). For example, when Young et al. (1977) exposed male Sprague-Dawley rats 

to radiolabeled AN via inhalation (5 or 100 ppm) or a single oral dose (0.1 or 10 mg/kg), most of 

the radiolabel was recovered in the urine, with much lower proportions of the initial dose in feces 

or expired air (see Table 3-1 and 3-2). Urinary excretion increased with dose, from 69 to 82% of 
 DRAFT - DO NOT CITE OR QUOTE 36 

the dose following inhalation exposure and from 34 to 67% after gavage (Tables 3-1 and 3-2). 

Excreted dose in urine was mostly unidentified metabolites. 

 In another study, Sapota (1982) administered 40 mg/kg AN, containing either 40 μCi/kg 

[1,2-14C]- or [1-14C]-AN, in saline to male Wistar rats, either via gavage or intraperitoneally. In 

parallel to the depletion of radiolabel in tissues at 24 hours postexposure, 82–93% of the dose 

was eliminated from the body in the urine, with 3–7% exhaled unchanged in the breath in 

24 hours, independent of the route of administration and the position of the radiolabel. However, 

when Farooqui and Ahmed (1982) administered an oral dose of 46.5 mg/kg [1-14C]-AN to male 

Sprague-Dawley rats, 40% of the radioactivity was excreted in urine over 24 hours after dosing. 

At the end of 10 days, 61% of the total dose was excreted in urine. Similarly, when Ahmed et al. 

(1983) gave a single oral dose of 46.5 mg/kg AN to male Sprague-Dawley rats in distilled water, 

using 50 μCi/kg of either [2,3-14C]- or [1-14C]-AN as tracer, 40% of the radioactivity from 

[1-14C]-AN but 60% of [2,3-14C]-AN-derived radiolabel were detected in the urine in the initial 

24 hours. Neither of the two studies provided details that might explain the discrepancy. 

However, the observed discrepancy might indicate the impact of different strains used in the 

studies. 

 The single gavage dose experiment of Burka et al. (1994), in which male F344 rats were 

placed in metabolic cages after receiving 0.87 mmol/kg (46.2 mg/kg) [2-14C]-AN, resulted in 

67% of the load being voided to the urine after 24 hours. This proportion of the recovered load 

was similar to the 55–56% value obtained when male F344 rats or B6C3F1 mice were orally 

exposed to [1,2,3-13C]-AN (Fennell and Sumner, 1994). However, Ahmed et al. (1996a) 

recovered only about 4% of the counts in 48-hour urine samples when F344 rats were injected 

intravenously with 11.5 mg/kg [2-14C]-AN. About 27% of the load was eliminated via all routes 

combined. In this study, much higher levels of tissue binding were observed than in other 

studies. 

 Identification of the urinary metabolites derived from AN metabolism was attempted in 

several studies. Langvardt et al. (1980) administered [2,3-14C]- and [1-14C]-AN orally to male 

Sprague-Dawley rats, thereby specifically tracing the fate of the vinyl and cyano groups of AN. 

Two main urinary metabolites, thiocyanate and N-acetyl-S-(2-cyanoethyl)cysteine, were 

identified. Thiocyanate, formed from the epoxide metabolite CEO, was the predominant urinary 

metabolite following oral dosing with 30 mg/kg of [1-14C]-AN and accounting for 54% of the 

injected radioactivity within 16 hours after dosing. On the other hand, thiocyanate only 

accounted for 1% of the urinary radioactivity after dosing with [2,3-14C]-AN. The second 

metabolite, N-acetyl-S-(2-cyanoethyl)cysteine, a mercapturic acid derived from direct 

conjugation between AN and GSH, constituted 18% of the radiolabel derived from [1-14C]-AN 

and 28% from [2,3-14C]-AN. Another metabolite, tentatively identified as N-acetyl-3-carboxy5-cyanotetrahydro-1,4-2H-thiazine, constituted 19% of the label from [1-14C]-AN and 35% from 

[2,3-14C]-AN. Evidently, this metabolite was formed from conjugation of CEO with GSH. 
 DRAFT - DO NOT CITE OR QUOTE 37 

Langvardt et al. (1980) found another four minor metabolites that were not identified 

structurally. 

 Tardiff et al. (1987) monitored the urinary metabolites of AN-treated male SpragueDawley rats 24 hours after i.v. or i.p. single doses (0.6, 3, or 15 mg/kg) or inhalation exposure to 

4, 20, and 100 ppm for 6 hours. Three major metabolites were measured: thiocyanate, N-acetylS-(2-hydroxyethyl)cysteine, and N-acetyl-S-(2-cyanoethyl)cysteine, that were also detected by 

Langvardt et al. (1980). These three excreted metabolites represented 50–54% of the 

administered dose in urine within 24 hours, independent of the dose. Tardiff et al. (1987) found 

that following i.p. or i.v. administration of AN, N-acetyl-S-(2-hydroxyethyl)cysteine and 

thiocyanate each represented between 5 and 10% of the urinary metabolites; the major 

metabolite was N-acetyl-S-(2-cyanoethyl)cysteine, representing 74–78% of the urinary 

metabolite when AN was administered intraperitoneally or intravenously. However, following 

inhalation exposure of AN, only 8% of the dose was excreted as N-acetyl-S-(2-cyanoethyl)-

cysteine, and the major urinary metabolite was thiocyanate at 20 and 100 ppm. Moreover, 

N-acetyl-S-(2-hydroxyethyl)cysteine was excreted in larger amounts than N-acetyl-S-(2-cyanoethyl)cysteine. These results also showed that the percentage of dose excreted as urinary 

thiocyanate increased with dose when AN was administered by inhalation. The study authors 

concluded that the route of administration of AN had an important influence on the pattern of 

metabolic excretion. 

 Shibata et al. (2004) investigated the urinary excretion of thiocyanate in male Wistar rats 

that received 40 mg/kg AN (about half the LD50) by gavage in water. Urinary excretion of 

thiocyanate became measurable at the time of peak plasma thiocyanate levels, 5 hours after 

dosing. Excretion of urinary thiocyanate gradually increased so that at 10 hours after dosing, 

about 1.2 mg thiocyanate (7% of administered dose) had been excreted into urine. 

 Gut et al. (1981) administered [1-14C]-AN to male Wistar rats (dose not given) by the 

oral, i.v., i.p., and s.c. routes. Total excretion of radioactivity after 48 hours was reported to be

close to 100% following oral administration but 75–84% following the other routes of 

administration. The patterns of urinary radioactivity elimination were also different: after 

parenteral administrations, elimination of radioactivity was highest within the first 4 hours after 

dosing, with much smaller amounts for the remaining 44 hours. After oral dosing, between 

6 and 8% of the dose was eliminated in urine for the time periods 4, 8, and 12 hours after dosing 

with much lower amounts thereafter. However, the major difference was found to be urinary 

thiocyanate elimination: 23% during the 48 hours after oral dosing and 4% following i.p., 4.6% 

following s.c., and 1.2% following i.v. administration. 

In another study (Gut et al., 1985), male Wistar rats were exposed via inhalation to 57, 

125, or 271 mg/m3

 AN for 12 hours. A constant ratio between thiocyanate and the sum of 

thioether compounds (AN mercapturic acids) in urine was found throughout the three doses. 

Average total amounts of thioethers excreted in urine during 12 hours of exposure were 24, 63, 
 DRAFT - DO NOT CITE OR QUOTE 38 

or 83 μmol/kg for 57, 125, or 271 mg/m3

 AN, respectively. Average total amounts of 

thiocyanate excreted were 14, 24, and 49 μmol/kg for 57, 125, and 271 mg/m3 AN, respectively. 

The ratio of thioethers to thiocyanate was about 2:4 during the 12 hours of exposure and was 

similar to that from oral exposure to AN. Thus, thioethers, not thiocyanate, were the major 

urinary metabolites following inhalation and oral exposure. These results were different from 

those reported by Langvardt et al. (1980) and Tardiff et al. (1987). 

 Müller et al. (1987) quantified four urinary metabolites and unchanged AN following 

inhalation exposure of male Wistar rats to 1–100 ppm of AN for 8 hours (thiocyanate was not 

measured). At 24 hours postexposure, N-acetyl-S-(2-cyanoethyl)cysteine was the primary 

urinary metabolite, followed by N-acetyl-S-(2-hydroxyethyl)cysteine, thiodiglycolic acid (also 

known as thiodiacetic acid), S-carboxyethyl-L-cysteine, and unchanged AN. The excretion 

pattern of AN and its metabolites was dependent on the inhalation exposure concentrations. The 

study authors proposed cyanoethyl mercapturic acid was the most sensitive indicator metabolite 

of AN exposure at levels of 5 ppm. 

Fennell et al. (1991) also measured GSH-derived metabolites, but not thiocyanate, in the 

urine of male F344 rats (10 or 30 mg/kg) and male B6C3F1 mice (10 mg/kg), following oral 

administration of [1,2,3-13C]-AN. The results of this study are shown in Table 3-7. N-acetylS-(2-cyanoethyl)cysteine was formed by conjugation of AN with GSH, whereas the other 

metabolites were from reaction of CEO with GSH. The results support the finding that rats and 

mice differ in the way they metabolize AN, and mice evidently metabolize more AN through the 

CYP2E1-mediated formation of CEO. 

Table 3-7. Urinary excretion of thioethers derived from AN 

Rat (30 mg/kg) Mouse (10 mg/kg) 

Metabolite (see Figure 3-2) Percent of total metabolites 

N-acetyl-S-(2-cyanoethyl)cysteine 42.8 ± 4.8 20.5 ± 2.0 

N-acetyl-S-(2-hydroxyethyl)cysteine 26.7 ± 1.8 22.3 ± 1.2 

N-acetyl-S-(1-cyano-2-hydroxyethyl)cysteine 17.4 ± 2.2 13.9 ± 3.2 

N-acetyl-S-(carboxymethyl)cysteine and thiodiacetic acid 7.4 ± 2.9 43.2 ± 3.5 

Thionyldiacetic acid 5.7 ± 0.21 Not detected 

Source: Fennell et al. (1991). 

Kedderis et al. (1993a) studied the dose dependence of the urinary excretion of AN 

metabolites in male F344 rats and male B6C3F1 mice. In rats during the 72 hours following oral 

doses of 0.09–28.8 mg/kg [2,3-14C]-AN, 73–99% of the dose was excreted in urine, while 3–5% 

was found in feces. In mice receiving 0.09–10 mg/kg [2,3-14C]-AN, 83–94% of the dose was 

excreted in urine and 2–8% in feces. Excretion of radioactivity by both routes was not dose 

dependent in either species. 
 DRAFT - DO NOT CITE OR QUOTE 39 

The position of the radiolabel did not allow detection of thiocyanate. Radiochromatograms of urine from rats or mice identified five major peaks, two of which contained more than 

one compound. Following administration of [2,3-14C]-CEO, two of the five peaks were not 

found, indicating that those peaks were derived from direct conjugation of AN without metabolic 

activation to CEO. The sum of the percent of total radioactivity from CEO conjugate-derived 

peaks was higher than that from the AN conjugate-derived peaks in both rats and mice. None of 

the metabolites appeared to be glucuronides. Kedderis et al. (1993a) detected four of the five 

metabolites shown in Table 3-7, but could not identify thionyldiacetic acid. In addition, 

S-(2-cyanoethyl)-thioacetic acid was detected in mouse urine only, likely a degradation product 

of N-acetyl-S-(2-cyanoethyl)cysteine. 

The excretion of metabolites derived from CEO was approximately linear with the AN 

dose in both rats and mice. However, the urinary excretion of N-acetyl-S-(2-cyanoethyl)cysteine 

increased nonlinearly with increasing dose of AN, an effect that was much more pronounced in 

rats than in mice. This probably indicated the presence of a competing pathway, namely, 

epoxidation of AN, with the conjugation of AN with GSH. The fraction of the total dose 

recovered as metabolite from CEO was 0.5 in rats and 0.67 in mice. The study authors estimated 

that the ratio of AN epoxidation to GSH conjugation ranged from 4.8 to 1.3 as the AN dose 

increased in rats and from 5.7 to 2.7 as the dose increased in mice. Kedderis et al. (1993a) also 

pointed specifically to the species differences detected in this study—a roughly 10-fold higher 

excretion of thiodiglycolic acid (thiodiacetic acid) in mice as compared with rats and measurable 

excretion of S-(2-cyanoethyl)thioacetic acid in mice. This urinary metabolite could not be 

detected in rats at all. 

 Sumner et al. (1999) treated three male WT and four male CYP2E1-null mice 

(C57BL/GN × Sv129) orally to 0, 2.5, or 10 mg/kg [1,2,3-13C]-AN and used NMR spectroscopy 

to characterize AN metabolites in urine samples collected over 24 hours. WT mice excreted 

metabolites derived from CEO (80–85% of total excreted) and from direct GSH conjugation with 

AN (15–21% of total excreted), with the largest percentage of metabolites from conjugation of 

GSH with the 3-carbon of CEO. CYP2E1-null mice displayed only metabolites derived from 

direct GSH conjugation with AN in their urine following administration of 2.5 or 10 mg/kg 

[1,2,3-13C]-AN. This confirmed the role of CYP2E1in the oxidation of AN to CEO and its 

subsequent transformation to a range of other products. Since CYP2E1-null mice did not excrete 

metabolites that would be produced by oxidation by other CYP450s, CYP2E1 may be the only 

CYP450 enzyme involved in the metabolism of AN. In addition, CYP2E1-null mice excreted 

about the same percentage of administered dose as the WT mice, indicating CYP2E1-null mice 

compensated for the CYP2E1 deficiency by producing more metabolites from direct conjugation 

of AN with GSH. 

 Taken together, the animal data indicate that AN can be exhaled as parent compound at a 

low percentage of the administered dose, probably increasing at high doses (e.g., 10 mg/kg). 
 DRAFT - DO NOT CITE OR QUOTE 40 

Fecal excretion amounts to about 5% of a given dose. The biliary pathway leading to fecal 

excretion has not been well characterized. To a small extent, similar to fecal excretion, AN is 

metabolized completely and exhaled as CO2. Both pathways appear to be quite independent of 

the administered dose. Urinary excretion of AN metabolites has been well characterized but is 

not without contradictory findings. There appears to be little doubt that mice metabolize more 

AN via the CYP2E1-mediated oxidative pathway than do rats. To what extent this pathway is 

likely to be overcome by large doses, or what contribution the GSH conjugation makes with 

varying doses of AN and different species exposed, is not known.

3.5. PHYSIOLOGICALLY BASED TOXICOKINETIC MODELS 

 A physiologically based toxicokinetic (PBTK) model for AN was previously developed 

in rats (Kedderis et al., 1996; Gargas et al., 1995) and extended to describe the dosimetry of both 

AN and CEO in humans (Sweeney et al., 2003). The PBTK model structure consists of two 

parallel modules, one for AN and one for CEO, interlinked by the rate of oxidative metabolism 

of AN to CEO in the liver, essentially as described by Gargas et al. (1995). Each module 

consists of seven dynamic tissue compartments representing the lung, slowly perfused tissues, 

fat, well-perfused tissues, brain, stomach, and liver (Figure 3-2). All perfusion-limited tissue 

compartments are linked through blood flow, following an anatomically accurate, typical, 

physiologically based description (Andersen, 1991). 
 DRAFT - DO NOT CITE OR QUOTE 41 

Source: Sweeney et al. (2003). 

Figure 3-2. Structure of the PBTK model for AN and CEO. 

Because AN and CEO are retained by the tissue in each compartment according to their 

tissue/blood partition coefficients (PCs) (which were measured in vitro), the concentrations of 

both chemicals in venous blood (leaving the tissue) are lower than those in arterial blood during 

the equilibration phase (except CEO in the liver). Therefore, the rate of change in the amounts 

of both chemicals in each tissue compartment is given by the difference between concentration in 

blood entering and exiting the tissue multiplied by the blood flow. Simple differential equations 

for each compartment, corrected for the non-enzymatic conjugation with GSH, are integrated 

over time, giving the amounts of AN and CEO present in the tissue (Kedderis et al., 1996) (see 

equation below). Therefore, knowing (from the literature) the actual volume of each tissue, 

concentrations of AN and CEO in each tissue can be calculated over time. 
 DRAFT - DO NOT CITE OR QUOTE 42 

 dAi/dT = Qi(CA–CVi)–(KSO × CVi × GSH) × Vi

where 

Qi

 = blood flow rate to the target tissue (i) 

CA = concentration of AN in arterial blood 

CVi = concentration of AN in venous blood 

KSO = rate constant for the conjugation of AN with glutathione (GSH) 

Vi

 = volume of the target tissue (i) 

For the lung compartment, with two mass inputs (mixed venous blood and inhaled air) 

and two outputs (arterial blood and exhaled air), the amount of either chemical in alveolar air is 

in equilibrium with the amount in lung blood at the steady state. Thus, concentrations of AN and 

CEO in arterial blood can be calculated from simple mass balance equations. Such calculations 

take into account the alveolar ventilation rate and the rate of blood flow through the lung, a 

parameter made equal to cardiac output (both known from the literature) and corrected for 

binding to Hb and blood sulfhydryls. 

 For the liver compartment, with mass input from blood and two outputs (venous blood 

and metabolism, excluding biliary excretion that was not considered), the chemical mass transfer 

is given by the difference between concentrations in portal and venous blood multiplied by 

hepatic blood flow and corrected for: (1) metabolism of AN to yield CEO (calculated from the 

Michaelis-Menten equation, subtracted from the mass of AN, and added to the mass of CEO), 

(2) enzymatic hydrolysis of CEO (also described by the Michaelis-Menten equation), and (3) the 

first-order conjugation with GSH. A simplified scheme of the mass flow in the PBTK model for 

AN and CEO is shown in Figure 3-2 (Sweeney et al., 2003). 

 The model was initially calibrated in rats for three routes of AN administration—oral, i.v. 

(bolus), and inhalation (Kedderis et al., 1996)—by manually adjusting the metabolic parameters 

Vmax and Km for AN oxidation, first-order constants for AN- and CEO-GSH conjugation, and 

first-order constant for absorption of AN from the GI tract, guided by the approximate statistical 

likelihood calculation of SimuSolv. Absorption through the skin, which has been estimated at 

about 1% of that through the lung (Rogaczewska, 1975), was not considered in this model. 

Chemical-specific modeling parameters were either: (1) measured in vitro in rats (PC [Teo et al., 

1994]; macromolecular interaction constants [Gargas et al., 1995]), (2) fitted to the experimental 

data by the model (metabolism parameters: Vmax and Km), or (3) estimated from the literature 

(CEO elimination constants). 

 The model assumed that rats do not have EH activity, based on data from Kedderis and 

Batra (1993). As discussed previously in Section 3.3.1, this assumption is probably incorrect, 

based on data from de Waziers et al. (1990), Guengerich et al. (1981), and Kopecky et al. (1980). 

This PBTK model did not scale allometrically EH activity to humans, whose liver microsomes 

display EH activity toward CEO (Kedderis and Batra, 1993). Instead, Kedderis (1997) estimated 
 DRAFT - DO NOT CITE OR QUOTE 43 

this activity in humans in vivo based on the ratio of EH to CYP450 activity in subcellular hepatic 

fractions multiplied by the CYP450 activity in vivo. In addition, the human blood-to-air PC for 

AN was determined experimentally (Kedderis and Held, 1998). Because no in vivo 

pharmacokinetic data were available to validate the human model, human in vitro data were 

scaled to experimental data obtained from rats by using a “parallelogram approach.” 

 The model by Kedderis et al. (1996) overestimates the oral exposure of venous blood 

CEO concentration by 3- to 10-fold. This is a systematic bias, which suggests that the model 

parameters need to be reevaluated or that the model is not capturing an important kinetic process 

for CEO clearance. In particular, for all tissues except the liver, the measured rise in CEO 

concentration for the first 10–15 minutes after oral and i.v. exposures is much slower than 

predicted by the model, and the model continues to overpredict the oral data for all measured 

time points, with the overprediction in the brain being the worst. Kedderis et al. (1996) 

suggested that the overestimation of CEO concentration in blood at early time points is “most 

likely due to a large intrahepatic first-pass effect.” This hypothesis has not been further 

evaluated, but, even if correct, the model structure has not been revised to simulate this 

phenomenon. The model continues to overestimate CEO levels in blood (albeit to a lesser 

degree) at later time points when the hypothesized first-pass effect would be less of a 

contributing factor. 

 It should also be noted that Kedderis et al. (1996) did not compare their model 

predictions to data on the urinary elimination of AN-GSH and CEO-GSH conjugates and on total 

activity bound to Hb, as was done in a previous version of the model (Gargas et al., 1995). 

While fits to those data may have informed the parameters reported by Kedderis et al. (1996), 

this is clearly not the case in this instance. Also, the blood and tissue time-course data shown by 

Kedderis et al. (1996) do not include all of the points shown in the previous publication. 

 Since Kedderis and colleagues (1996) did not include EH activity in their rat model (but 

other evidence strongly indicates significant CEO hydrolysis be EH), did not perform a more 

global, numerical optimization of their parameters, may not have included the urinary and Hb 

data, and the subsequent model fits consistently overpredicted CEO pharmacokinetics in blood 

and brain to a large extent, the model parameterization was revised to hopefully improve the 

model characterization of the rat pharmacokinetic data and provide a more sound footing for 

human-rat dosimetry comparisons and hence risk extrapolation, at least making the results 

numerically reproducible. Guengerich et al. (1981) measured CEO hydrolysis with purified rat 

EH and obtained a Vmax of 0.3 μmol/minute-mg protein and a Km of 800 μM. Since the highest 

blood levels observed for CEO were ~2 μM (0.1 μg/mL), to a good approximation hydrolysis 

can then be described using a first-order rate constant of 0.3/800 = 3.75 × 10-4 L/minute-mg EH 

protein. The EH content of rat liver was measured by de Waziers et al. (1990), who found 

0.165 mg EH/mg MP and a value of 40 mg MP/g liver from Ploemen et al. (1997) can be 

applied. 
 DRAFT - DO NOT CITE OR QUOTE 44 

Finally, the liver fraction for the rat as used in the model 40 g/kg BW was applied, 

assuming a standard 0.25 kg rat. The rate constant for a standard rat would then be kEH = 

(3.75 × 10-4 L/minute-mg EH) × (0.165 mg EH/mg MP) × (40 mg MP/g liver) × (40 g liver/kg 

BW) × (0.25 kg BW) × (60 minutes/hour) = 1.49 L/hour. Because kEH is effectively the ratio, 

Vmax/Km, for EH, and a Vmax is expected to scale with BW across species while Km is not 

expected to scale with BW, kEH is expected to scale in the same way as a Vmax. In particular, 

since kEH is a total activity (rather than an activity per unit volume of liver), it is expected to 

scale as BW0.7. Therefore, as for Vmax values in general, one derives a scaled constant, kEHC = 

kEH/(0.25 kg)0.7 = 3.92 L/h-kg0.7. Based on similar in vitro (Krause et al., 1997) and in vivo 

(Kemper et al., 2001) EH activity data for butadiene mono-epoxide, it is suspected that the in 

vivo enzymatic hydrolysis of CEO is also similar to in vitro values, further supporting this direct 

extrapolation. 

 Because of the close dose spacing used in the protein kinase (PK) studies and the limited 

data on metabolite disposition, we found that not all of the remaining parameters were readily 

identifiable from the in vivo PK data. Therefore, a value of Km for AN oxidation to CEO from in 

vitro experiments with rat liver microsomes from Roberts et al. (1991) will be used: 

52 μM × 0.05306 mg AN/μmol = 2.76 mg/L. 

While the model predictions of AN and CEO blood levels after oral exposures tended to 

either match or exceed the measured levels, the model predictions of the Hb-binding data were 

below the measured levels, indicating that the corresponding binding constants that had been 

determined in vitro were too low. Since the data are only for total binding to Hb (AN plus 

CEO), the ratio of the AN:CEO binding constants from in vitro was held constant, but the 

absolute value of the constants was allowed to vary. 

Given the values for Km and the kEHC obtained above, the parameters varied during model 

fitting were Vmax (AN oxidation), kFC (GST activity towards AN), kFC2 (GST activity towards 

CEO), kA (oral absorption), and kH (AN-Hb binding constant, with the CEO-Hb binding 

constant, kH2, varied in direct proportion, so that kH/kH2 remained equal to the ratio of the values 

measured in vitro). An approximate log likelihood function as described by Cole et al. (2001) 

was used as a measure of goodness of fit. During initial optimizations, it was assumed that the 

heteroscedasticity values for AN and CEO were distinct but that the same value held for each 

compound among all three tissues sampled (brain, liver, and blood). However, examination of 

the standard deviations (SDs) noted in the data of Kedderis et al. (1996) and Gargas et al. (1995) 

indicated that measurement error was approximately proportional to the signal strength, so the 

heteroscedasticities were set to two. 

 Initial attempts to fit the model to the entire data set by varying other model parameters 

were not satisfactory. While the results are not shown here in detail, a possible reason that the 

model could not entirely fit the data is that it assumes constant GSH levels in each tissue, while 

previous studies (e.g., Benz et al., 1997a) have shown significant GSH depletion at dose levels in 
 DRAFT - DO NOT CITE OR QUOTE 45 

the range of those used in the PK studies. Since GSH depletion will be least significant at the 

lowest doses used, and the most interest is in the low-dose range for extrapolation, it was decided 

to reestimate the model parameters by using only the lowest concentration pharmacokinetic data: 

the oral doses at or below 3 mg/kg, i.v. dose of 3.4 mg/kg, and inhalation concentration of 

186 ppm. Also, of the data used to estimate parameters, it was determined that the last AN blood 

measurement from both the 3 mg/kg oral data and the 3.4 mg/kg i.v. data appeared to be outliers 

since they were well above the otherwise log-linear clearance curve defined by the preceding 

data, so they too were not used in the estimation. (Model simulations of all exposure 

concentrations and doses will be shown as compared with the data, but only the data for the 

exposure values stated two sentences above were used for fitting.) 

 The following figures show the model fits obtained with the parameters of Kedderis et al. 

(1996) as compared with the EPA's revised parameters. (All parameter values are listed in Table 

C-1 of Appendix C.) The term “fits” is used here to describe the closeness of model simulations 

to the data, recognizing that only a subset of the data, as described in the preceding paragraph 

and indicated in the figure legends, was actually used in parameter estimation.) The most 

remarkable aspect of the revised fits is how close they are to identical to the original model fits. 

Results are nearly identical for most of the i.v., inhalation, and oral (Figures 3-3 to 3-5a) bloodand tissue-time-course data. The revised fits to the CEO blood- and tissue-time-course data after 

oral dosing are slightly worse than in the original model (Figure 3-6b), but then the fits to the 

urine and especially the Hb-binding data (Figure 3-6c) are considerably better than those 

obtained with the parameters of Kedderis et al. (1996). Since only a few of the fits were 

degraded slightly, while others were improved, the revised model parameters are considered to 

represent the overall data set at least as well as the original. The fact that the revised parameters

are specifically defined by the low-dose data, which are closest to the range where the model will 

be applied and are obtained using an objective criteria and numerically reproducible methods 

(the approximate likelihood function with numerical optimization), gives further support for their 

use. 
 DRAFT - DO NOT CITE OR QUOTE 46 

Note: Only 3.4 mg/kg data were used to estimate revised parameters, with circled 

point excluded. 

Figure 3-3. Intravenous exposure, dosimetry, and model fits. 

CEO in blood
 DRAFT - DO NOT CITE OR QUOTE 47 

Note: Only 186 ppm data were used to estimate revised parameters. 

Figure 3-4a. Inhalation exposure, CEO concentrations. 

CEO in brain
 DRAFT - DO NOT CITE OR QUOTE 48 

Note: Only 186 ppm data were used to estimate revised parameters.

Figure 3-4b. Inhalation exposure, AN concentrations. 

AN in blood
 DRAFT - DO NOT CITE OR QUOTE 49 

Note: Only 3 mg/kg data were used to estimate revised parameters. 

Figure 3-5a. Oral exposure, CEO concentrations. 

CEO in blood

CEO in blood
 DRAFT - DO NOT CITE OR QUOTE 50 

Note: Only 3 mg/kg data were used to estimate revised parameters. 

Figure 3-5b. Oral exposure, AN concentrations. 
 DRAFT - DO NOT CITE OR QUOTE 51 

Note: points are data; lines are model fits or simulations. Only data for doses 

≤2 mg/kg were used to estimate revised parameters. 

Figure 3-5c. Oral exposure, urinary excretion, and Hb binding. 

Since the human metabolic parameters were extrapolated from in vitro measurements by 

using the relationship between in vitro measured and in vivo estimated values from the rat 

(Sweeney et al., 2003), it is appropriate to update the human metabolic parameters and model in 

parallel with the EPA's update of those in the rat. For EH, Sweeney et al. (2003) used the in 

vivo:in vitro relationship for the CYP450-mediated metabolism, since there had been no parallel 

relationship for hydrolysis. As we are now choosing to extrapolate the rat EH from in vitro to in 

CEO-GSH in urine
 DRAFT - DO NOT CITE OR QUOTE 52 

vivo based only on enzyme content, microsomal content, liver fraction, and BW, a parallel 

approach for the human would be to do the same, rather than using a correction factor based on a 

different class of enzymes. In the case of humans, Kedderis and Batra (1993) measured EH 

activity in vitro by using hepatic microsomes, so we do not need to use the amount of enzyme 

per mg MP in the calculation. Kedderis and Batra (1993) determined a Vmax and Km EHmediated hydrolysis of CEO using liver samples from six individual humans. The lowest 

estimated Km in the group was 600 μM, so again, we choose to describe the metabolism as first 

order, using the ratio of Vmax/Km. The ratio of Vmax/Km was first calculated for each individual 

since Vmax and Km tend to be statistically correlated due to the way they are estimated, and an 

average value for the ratio was then determined to be 7.02 × 10-6 L/minute-mg MP. We can then 

apply the value of 56.9 mg MP per g liver from Lipscomb et al. (2003), the liver fraction of 

25.7 g/kg BW, and the standard value of 70 kg for a human. The rate constant for a standard 

human is then kEH = (7.02 × 10-6 L/minute-mg MP) × (56.9 mg MP/g liver) × (25.7 g liver per kg 

BW) × (70 kg BW) × (60 minutes/hour) = 43.1 L/hour, assuming it also scales as BW0.7, kEHC = 

kEH/(0.70 kg)0.7 = 2.20 L/hour-kg0.7. Recall that the value for rats was estimated to be 

3.92 L/hour-kg0.7. 

The original PBTK model for humans was assessed for its sensitivity to changes in key 

input parameters, and the expected variability in CEO concentrations in humans under different 

AN exposure scenarios was estimated (Sweeney et al., 2003). In addition to updating the CEO 

hydrolysis rate constant for the human model (and using a first-order equation for that reaction) 

as previously discussed, the ratio of Vmax for the oxidation step as estimated in vivo vs. measured 

in vitro for the rat was used to estimate the human in vivo VmaxC, and the enzymatic GSH 

conjugation rate constants for AN (kFC) was likewise estimated from the rat estimated in vivo vs. 

measured in vitro ratio (kFC2 was unchanged during the reestimation). Since the rat values for 

VmaxC and kFC were revised, and these values were each one leg of the metabolic extrapolation 

“parallelogram,” the human in vivo values should be accordingly varied. The result is that the 

ratio of revised/original human values for each of these constants is simply equal to the 

respective revised/original in vivo values for the rat constants; the revised human values are 

VmaxC = 22.1 mg/hour-kg0.7 and kFC = 77 kg0.3/hour. Finally, since the original model 

extrapolation assumed that the oral absorption constant, kA, and the Hb-binding constants, kH and 

kH2, were the same in humans as in rats, these assumptions were retained, updating the human 

parameters appropriately. 

 Appendix C provides model source codes written in acsXtreme (AEgis Technologies, 

Huntsville, AL) and Matlab (The Mathworks, Inc., Natick, MA) that were used to model 

AN/CEO pharmacokinetics with the PBTK models of Kedderis et al. (1996, as revised) and 

Sweeney et al. (2003) in this evaluation. 
 DRAFT - DO NOT CITE OR QUOTE 53 

4. HAZARD IDENTIFICATION 

4.1. STUDIES IN HUMANS—EPIDEMIOLOGY AND CASE REPORTS 

4.1.1. Oral Exposure 

 No studies were identified that addressed the exposure of human beings to AN via the 

oral route. 

4.1.2. Inhalation Exposure 

4.1.2.1. Acute Exposure 

 In a study on six male volunteers, a single 8-hour inhalation exposure of 5–10 mg/m3

 AN 

produced no subjective symptoms, such as headache, nausea, or general weakness (Jakubowski 

et al., 1987). 

 A report by Chen et al. (1999) collated 144 acute AN poisoning cases that had occurred 

between 1977 and 1994 in China. Each case involved a brief workplace accidental exposure to a 

high concentration of AN. There were few reliable data on the levels of exposure in these cases, 

although transient concentrations of AN were thought to range from 40 to 560 mg/m3

 (18–

258 ppm) for 60 cases and may have been over 1,000 mg/m3

 for the remaining 84 cases. All but 

9 of the 144 subjects were males, ranging in age from 18 to 53 years old. Forty-two of the cases 

were considered to have resulted in severe acute AN poisoning, while the rest fell into the mild 

acute category. 

 Table 4-1 summarizes the incidence of symptoms and signs of toxicity that were evident 

in the 144 cases. Other changes in monitored biochemical or physiological parameters included 

transient increases in peripheral white blood cell (WBC) count to greater than 10 × 109

/L in 

66 cases and a number of apparent fluctuations in clinical chemistry parameters. Out of 

120 subjects whose liver function was monitored, seven subjects showed abnormal increases in 

alanine aminotransferase (ALT) (slight), aspartate aminotransferase (AST), and cholylglycine 

(i.e., glycocholic acid). Up to 23 times the normal serum concentration of the latter compound 

was detected. The seven subjects with abnormal liver functions were poisoned at low 

concentrations in air (40–79 mg/m3 [18–36 ppm]) but for a comparatively long duration of acute 

exposure (36 hours). Blood levels of GSH were depressed up to 50% in the severe cases, and 

urine thiocyanate was increased up to fourfold. 
 DRAFT - DO NOT CITE OR QUOTE 54 

Table 4-1. Clinical signs in 144 subjects accidentally exposed to AN 

Symptoms Cases (%) Symptoms Cases (%) 

Dizziness 144 (100) Congestion of pharynx 105 (73) 

Headache 144 (100) Hoarseness 13 (9) 

Feebleness 144 (100) Pallor 108 (75) 

Sore throat 87 (60) Profuse diaphoresis 95 (66) 

Chest tightness 144 (100) Rough breathing sound 18 (13) 

Cough 16 (11) Rapid heart rate 36 (25) 

Dyspnea 118 (82) ECG abnormalitiesa 15 (10) 

Nausea 133 (92) High blood pressure 20 (13) 

Vomiting 95 (66) Low blood pressure 5 (4) 

Abdominal pain 97 (68) Liver tenderness 9 (7) 

Numbness of the limbs 50 (40) Hepatomegaly and splenomegaly 7 (5) 

Fainting 104 (72) Coma 7 (5) 

Convulsion 46 (32) Hyperactive knee jerk 137 (95) 

aAll 15 instances of electrocardiogram (ECG) abnormalities occurred in cases of severe poisoning. 

Source: Chen et al. (1999). 

These changes disappeared after poisoned subjects were removed from the accident site 

and underwent treatment that included amyl nitrite via inhalation and an i.v. injection of 3% 

sodium nitrite followed by 50% sodium thiosulfate (STS). Other treatments included infusion 

with glucose, adenosine triphosphate (ATP), coenzyme A, and DEX along with oxygen 

inhalation to prevent the development of cerebral edema and to protect brain and liver cells. 

 In a study that was possibly reflective of combined inhalation and dermal exposure to 

AN, Wilson et al. (1948) reported that workers exposed to AN vapors at 16–100 ppm (35–

217 mg/m3) for periods of 20–45 minutes while involved in cleaning operations in polymerizer 

facilities complained of dull headache, fullness in the chest, irritation of all mucous membranes 

(eyes, nose, and throat), and a feeling of apprehension and nervous irritability. Some workers 

also complained of intolerable itching of the skin but had no clinically demonstrable dermatitis. 

Workers who had direct skin contact with AN displayed a sequence of symptoms, including skin 

irritation and erythema, followed by bleb formation and then desquamation with slow healing 

(Wilson et al., 1948). An earlier report by Wilson (1944) reported the onset of nausea, vomiting, 

weakness, headache, fatigue, diarrhea, and an “oppressive feeling” in the upper respiratory 

passages following exposure to “mild concentrations” of the compound. Several cases of 

reversible mild jaundice and one case of slow-to-reverse severe jaundice were identified and 

associated with occasional liver tenderness and low-grade anemia, but it was unclear whether 

they were related to inhalation or dermal contact exposures to only AN or to a combination of 

AN with other industrial rubber manufacturing chemicals such as butadiene and styrene. 
 DRAFT - DO NOT CITE OR QUOTE 55 

4.1.2.2. Chronic Exposure 

4.1.2.2.1. Cancer epidemiology

Cohort studies 

A retrospective cohort study involving workers at a DuPont textile fibers plant in 

Camden, South Carolina, was the first epidemiologic study addressing the potential 

carcinogenicity of AN (O’Berg, 1980). Shortly thereafter, reports from other cohorts of 

AN-exposed workers, based in Germany, the Netherlands, the United Kingdom, and the United 

States, were published. Other smaller-scaled occupational cohorts have also been utilized to 

better assess the association between AN exposure and adverse human health effects. 

Early studies did not utilize quantitative measures of exposure nor were they able to 

control for smoking (an important consideration when lung cancer is an outcome of interest). 

These factors were being taken into account by the late 1980s. The following section provides a 

summary of some of the major cohort studies conducted both within and outside the United 

States. 

The DuPont studies 

Researchers from DuPont conducted a series of studies among male workers potentially 

exposed to AN (Symons et al., 2008; Wood et al., 1998; Chen et al., 1987; O’Berg et al., 1985; 

O’Berg, 1980). The original study was conducted in South Carolina, with a follow-up study a 

few years later. A second DuPont plant, located in Virginia, was the site for another cohort 

study. Finally, Wood et al. (1998) combined the cohorts from South Carolina and Virginia to 

further investigate the relationship between AN exposure and cancer. Most recently, Symons et 

al. (2008) updated this combined cohort, adding 11 years of follow-up for a total follow-up 

period of over 50 years. 

The first epidemiologic study addressing the potential carcinogenicity of AN (O’Berg, 

1980) examined cancer incidence and mortality in a cohort of 1,345 male workers from a DuPont 

textile plant who were potentially first exposed to AN between 1950 and 1966. The cohort was 

chosen from a larger group of more than 10,000 workers, based on examination of work history 

(wage roll employees and some salaried employees), recollection of plant supervisors (wage roll 

maintenance employees and salaried employees), and survey of salaried employees (salary roll 

employees). No individual or area exposure monitoring data were available during the period of 

study. Several surrogate measures of potential exposure were utilized in the analyses, including 

job title, initial period of first exposure, length of exposure, and payroll (assuming that wage roll 

employees have higher potential exposure than supervision or salary roll employees). 

Workers were followed through the end of 1976, thus allowing a latency period of at least 

10 years for all surviving members of the cohort. Cancer incidence was ascertained for all 

cohort members who were diagnosed during their employment, and cause of death was 

determined for all cohort members who died either while employed or after termination. 
 DRAFT - DO NOT CITE OR QUOTE 56 

Comparison rates for cancer incidence and mortality were derived from similarly collected data 

in a company-wide cancer incidence and mortality registry system. Additional mortality 

information was supplied by the Social Security Administration, and death certificates were 

obtained for all known deaths. Other standard comparison rates were also utilized and presented; 

however, the company-wide data represented the most comparable control group. 

After observing only one incident case of cancer in the 217 employees with <6 months of 

exposure, examination of the incidence data was concentrated on the 1,128 employees who had 

more than 6 months of exposure. Among this group, cancer incidence was stratified by interval 

of diagnosis: 1956–1964, 1965–1969, and 1970–1976. The cancer incidence was statistically 

significantly elevated only in the last interval with 19 cases observed compared to 10.1 expected 

(standardized incidence ratio [SIR] = observed ÷ expected = 1.88, 95% confidence interval [CI] 

= 1.17–2.88, p < 0.01), based on company-wide rates. Seventeen of the 19 cases were among 

wage roll employees, the remaining two were salary roll employees. The difference between the 

observed and expected number of cases among the wage employees was statistically significant 

(SIR = 2.05, 95% CI = 1.23–3.21, p < 0.01) (Table 4-2). 

Table 4-2. Distribution of select incidence and mortalities among wage 

workers and all workers at an AN plant 

 Wage workers All workers 

Cause of 

disease/death 

Observed 

cases 

SIRa

(CI) 

Observed 

deaths 

SMRa

(CI) 

Observed 

cases 

SIRa

(CI) 

Observed

deaths 

SMRa

(CI) 

Less than 6 months of exposure 

All cancers 1 0.77 

(0.04–3.19)

3 1.30 

(0.33–3.55)

1 0.67 

(0.03–3.29)

3 1.25 

(0.32–3.40)

Respiratory cancer 0 0.00 1 1.11 

(0.06–5.48)

0 0.00 1 1.11 

(0.06–5.48)

Greater than 6 months of exposure 

All cancers 

(1956–1976) 

20 1.30 

(0.82–1.97)

15 1.16 

(0.68–1.87)

24 1.26 

(0.82–1.85)

17 1.13 

(0.68–1.78)

All cancers 

(1970–1976) 

17 2.05b

(1.23–3.21)

11 1.41 

(0.74–2.45)

19 1.88b

(1.17–2.88)

13 1.44 

(0.80–2.41)

Respiratory cancer 

(1956–1976) 

8 2.35b

(1.09–4.47)

6 1.30 

(0.53–2.71)

8 1.95 

(0.91–3.71)

7 1.35 

(0.59–2.66)

Respiratory cancer 

(1970–1976) 

6 2.86b

(1.16–5.94)

5 1.61 

(0.59–3.57)

6 2.40b

(0.97–4.99)

6 1.71 

(0.69–3.57)

a

SIR and SMR standardized against company-wide rates. 

b

Statistically significant (p < 0.05). 

SMR = standardized mortality ratio 

Source: Amended from O’Berg et al. (1980). 
 DRAFT - DO NOT CITE OR QUOTE 57 

Eight incident respiratory cancer cases were observed in the cohort of 1,345 workers. All 

eight of the respiratory cancers occurred in the group of employees who had >6 months of 

exposure, and all were among wage roll employees. Six of the eight respiratory cancers occurred 

in the 1970–1976 time interval compared to 2.1 expected based on company-wide rates (SIR = 

2.86, 95% CI = 1.16–5.94, p < 0.05) (Table 4-2). The numbers were too small to perform any 

other cancer-specific analyses.

In order to consider the effects of latency and level of exposure, further analyses were 

performed looking at the group of workers who had first been exposed between 1950 and 1952, 

when AN was first used at the plant and when exposures were known to have been highest. 

Statistically significant differences between the number of observed and expected cases were 

found among the wage roll employees in the diagnosis interval from 1970 to 1976, with 

17 cancers observed and 5.6 expected (SIR = 3.04, 95% CI = 1.83–4.78), with six of these cancer 

cases being respiratory cancers with an expected value of 1.5 (SIR = 4.0, 95% CI = 1.62–8.32). 

This group is presumed to have the longest latency and highest exposures to AN. 

Other factors related to significant differences in cancer incidence between observed and 

expected cases among the wage roll employees during the time period 1970–1976 were: 

(1) being a mechanic (10 observed vs. 3.7 expected), (2) duration of exposure of more than 

10 years (9 observed vs. 2.8 expected), and (3) exposure above “low level” (13 cancers observed 

vs. 5.5 expected), low level not defined. Similar relationships were found among respiratory 

cancers except for duration of exposure of more than 10 years. 

Incidence data among wage roll employees were examined by duration of exposure, 

excluding exposures of <6 months. The duration categories were <5, 5–9, and ≥10 years. The 

SIRs for all cancers in these three duration of exposure categories were 0.7 (95% CI = 0.23–

1.79), 1.2 (95% CI = 0.49–2.50), and 2.3 (95% CI = 1.18–4.14), respectively. 

A total of 89 deaths was observed in the entire cohort of 1,345 workers by the end of 

1976. The mortality analyses using company-wide rates for comparison did not show any large 

deviations between observed and expected numbers for all cancers or for respiratory cancers 

alone. Observed and expected numbers of cancer deaths between 1970 and 1976 for the wage 

roll employees with ≥6 months of exposure were not markedly different, with 11 cancers 

observed vs. 7.8 expected (standardized mortality ratio [SMR] = 1.41, 95% CI = 0.74–2.45) and 

5 respiratory cancers observed vs. 3.1 expected (SMR = 1.61, 95% CI = 0.59–3.57) (Table 4-2). 

The excess mortality observed is of interest, since statistical significance may have been 

hindered by the small sample size. 

The use of company-wide rates as a comparison may be problematic because the 

company-wide rates are based on other plants where exposure to carcinogenic agents may be 

possible. Additionally, company-wide rates include both exposed and unexposed workers, thus 

weakening the ability to observe increased risk among the exposed workers. The use of this 

population-based referent may hide true associations between AN and cancer. Additionally, the 
 DRAFT - DO NOT CITE OR QUOTE 58 

number of incident cancer cases and cancer-specific mortalities was too small for further 

analysis. However, the fact that the cancer/respiratory cancer comparisons appeared to be 

stronger for workers with longer latency, longer exposure, jobs with higher exposure, and work 

during the early years of observation when exposures were highest added to the weight of the 

evidence. 

Another potential limitation of this study was under-ascertainment of incident lung cancer 

cases. Two confirmed lung cancer cases that should have been included in the cohort were 

omitted because of clerical error. A validity check of a subsample of 465 employees revealed 

five more omissions, suggesting that a problem existed with ascertainment of lung cancer cases. 

The omission of these cases may have resulted in the underestimation of the risk estimate for the 

incidence of lung cancer. Also, subjective exposure assessment could have resulted in 

misclassification of exposure. If the exposure misclassification was random, it would bias the 

risk ratio toward the null value. If it was nonrandom because those assessing AN exposure 

believed it could cause illness, the effect on the risk estimate is unpredictable. However, other 

metrics used in this study, including duration of exposure, time of diagnosis, and job category, 

had internal validity and supported the finding of an association between AN exposure and 

cancer. Another limitation is the indication that workers may have been exposed to other 

chemicals in addition to AN. Lastly, there was no adjustment for smoking. The EPA AN health 

assessment (U.S. EPA, 1983) adjusted the results of this analysis based on smoking rates in the 

plant and among U.S. blue-collar workers, estimating that the expected number of cancer cases 

would be 15% higher and would reduce, but not eliminate, the association between AN and 

cancer in this study. Finally, the small sample size and limited follow-up restricted the ability to 

detect most cancers. 

A second DuPont study extended the follow-up of the above cohort through 1983 for 

cancer incidence and 1981 for cancer mortality, adding 7 and 5 years of follow-up, respectively 

(O’Berg et al., 1985). The exposure assessment was not updated, and case ascertainment and 

calculation of expected incidence and mortality were unchanged from the above study. To 

evaluate dose-response relationships and latency, cumulative exposure was categorized into three 

groups (<2, 2–12, and ≥13 years), and latency was dichotomized into “less than 20 years” or 

“20 or more years.” Men with <6 months of exposure were included in the analyses. As with 

the earlier study, DuPont cancer registry data were used as a comparison for the cancer incidence 

rates observed in the exposed cohort. DuPont and U.S. death rates were used as a comparison 

for the mortality data in the exposed cohort. 

There were 43 incident cancer cases, including 10 lung cancer cases and 6 prostate cancer 

cases (Table 4-3). The authors did not comment on the problems with ascertainment of incident 

lung cancer cases described in the O’Berg (1980) study. Two additional cases of lung cancer 

were identified. No significant differences between observed all-cancer incidence or even lung 

cancer incidence and expected values were found among workers (Table 4-3). There was a 
 DRAFT - DO NOT CITE OR QUOTE 59 

statistically significant association between AN exposure and prostate cancer incidence (SIR = 

6 observed ÷ 1.8 expected = 3.3, 95% CI = 1.35–6.93). All prostate cancer cases were observed 

among wage workers who had at least 20 years of latency. No other significant relationship 

between latency and cumulative exposure was detected. 

Table 4-3. Distribution of select incidence and mortalities among wage 

workers and all workers at an AN plant 

Wage workers All workers 

Cause of 

disease/death

Observed 

cases 

SIRa,b 

(CI) 

Observed 

deaths 

SMRa 

(CI) 

Observed 

cases 

SIRa,b 

(CI) 

Observed 

deaths 

SMRa 

(CI) 

All causes – – 139 1.18 

(1.00–1.39)

– – 155 1.15 

(0.98–1.34)

All cancers 37 1.25 

(0.89–1.70)

31 1.15 

(0.79–1.61)

43 1.17 

(0.86–1.56)

36 1.14 

0.81–1.56) 

Lung cancer 10 1.67 

(0.85–2.97)

12 1.17 

(0.63–2.00)

10 1.39 

(1.41–4.95)

14 1.21 

(0.69–1.98)

Prostate 6 4.00c

(1.62–8.32)

1 1.11 

(0.05–5.48)

6 3.33c

(1.35–6.93)

1 1.00 

(0.05–4.93)

a

SIR and SMR standardized against company-wide rates. 

bCalculated based on observed and expected values provided. 

c

Statistically significant (p < 0.05). 

Source: Amended from O’Berg et al. (1985).

A total of 155 deaths was reported, 36 of which were attributed to cancer. No significant 

differences between observed and expected deaths were reported among either wage workers or 

salary workers (Table 4-3). Twelve lung cancer deaths were observed vs. 10.2 expected (SMR = 

1.17, 95% CI = 0.63–2.00), and 1 prostate cancer death was observed vs. 0.9 expected (SMR = 

1.11, 95% CI = 0.05–5.48). The mortality comparisons were less elevated than the morbidity 

comparisons, indicating that a longer follow-up period may be needed. The observation that 

prostate cancer was elevated in the incidence data but not in the mortality data could reflect the 

fact that prostate cancer has a relatively high 5-year survival rate. 

In summary, O’Berg et al. (1985) added approximately 7 years of follow-up to the 

previous DuPont cohort but did not aid in refining knowledge about the potential for a 

relationship between AN exposure and lung-cancer incidence. The population was exposed to 

chemicals other than AN, and these additional exposures were not accounted for in the analyses. 

The small number of lung cancer and prostate cancer cases made the interpretation of the 

stratified analyses difficult, and the observed numbers of cases were not different from expected 

numbers of cases in either the highest cumulative exposure group or the longest latency group. 

This study shares the same limitations as the O’Berg (1980) study. Smoking status, which was 

not available in O’Berg et al. (1985), may have acted as a confounder. As the numbers of 
 DRAFT - DO NOT CITE OR QUOTE 60 

incident cases and cancer-specific deaths are small, and concomitant exposure to other chemicals 

is a potential limitation, this study does not provide a substantial basis for the evaluation of the 

relationship between AN exposure and cancer incidence. 

Chen et al. (1987) assembled a cohort of 1,083 mostly white male workers from a 

DuPont plant in Waynesboro, Virginia, that produced the acrylic fiber Orlon®

. The 

manufacturing process was similar to that at the Camden plant except there was greater distance 

between the process areas at the Waynesboro facility (Wood et al., 1998). Workers employed at 

the plant between 1944 and 1970 who had a potential for AN exposure were included. The 

cohort consisted of 805 wage roll employees and 278 salary roll employees. Potential exposure 

was based on the review of work histories. No quantitative information was available for 

exposure levels to AN; however, each job was classified as having either low, moderate, or high 

levels of AN exposure. Because data prior to 1957 were not available, the investigators analyzed 

only deaths between 1957 and 1981. 

As with previous DuPont cohort studies, morbidity in the exposed cohort was compared 

with company-wide cancer incidence rates, while mortality was compared with company-wide 

rates and national rates. A total of 92 deaths was observed, with 21 attributed to cancer. For 

both wage workers and salary workers, the number of observed deaths was significantly lower 

than expected (Table 4-4). No excess of observed cancer deaths was observed in either worker 

category. Among the wage workers, the five observed lung cancer deaths were not statistically 

different than expected based on U.S. rates (SMR = observed ÷ expected = 0.59, 95% CI = 0.22–

1.32). The significant deficit in observed deaths likely indicates, at least in part, the presence of

a healthy worker effect, incomplete cohort identification, and possibly incomplete ascertainment 

of mortality data. It should be noted that death information was gathered for active and 

pensioned employees, and names of terminated employees were submitted to the Social Security 

Administration for identification of vital status. Vital status for 20 people (1.8%) was unknown. 

No lung cancer deaths were observed among the salary workers. As for other cause-specific 

deaths, no significant trends were detected among either wage or salary workers by time period 

or duration of exposure. Analyses by the level of AN exposure and cumulative exposure did not 

show significant differences between observed deaths and expected values. 
 DRAFT - DO NOT CITE OR QUOTE 61 

Table 4-4. Distribution of select incidence and mortalities among wage and 

salary workers at an AN plant 

Wage workers Salary workers Total 

Cause of 

disease/death

Observed 

deaths 

SMRUS

a

(CI) 

SMRDuPont

a

(CI) 

Observed 

deaths 

SMRUS

a

(CI) 

SMRDuPont

a,b

(CI) 

Observed 

cases 

SIRDuPont

a,b

(CI) 

All causes 68 0.57b

(0.44–0.78)

0.77b

(0.61–0.98)

24 0.41b

(0.27–0.60)

0.66b

(0.43–0.97) 

– – 

All cancers 18 0.75 

(0.44–1.16)

0.88 

(0.54–1.37)

3 0.24b

(0.06–0.66)

0.31b

(0.08–0.85) 

37 1.01 

Lung cancer 5 0.59 

(0.22–1.32)

0.66 

(0.24–1.46)

0 Not 

determined

Not 

determined 

5 0.72 

(0.26–1.61)

Prostate 

cancer 

1 1.11 

(0.06–5.48)

1.11 

(0.06–5.48)

1 2.0 

(0.03–2.47)

2.0 

(0.03–2.47) 

5 2.63 

(0.96–5.83)

aCalculated based on observed and expected values provided. 

b

Statistically significant (p < 0.05). 

SMRDuPont = SMR based on DuPont Registry; SMRU.S. = SMR based on U.S. statistics 

Source: Amended from Chen et al. (1987). 

Analyses of cancer incidence or morbidity reported 37 incident cancers in the cohort 

(Table 4-4). Twenty-seven were among the wage roll employees (vs. 26.0 expected) and 

10 were among the salary roll employees (vs. 10.5 expected). No increase was noted in lung 

cancer incidence, with 5 cases observed in the total group vs. 6.9 expected (SIR = observed ÷ 

expected = 0.72, 95% CI = 0.26–1.61). The incidence of prostate cancer was increased, with 

5 observed cases compared to 1.9 expected based on the company-wide database (SIR = 2.63, 

95% CI = 0.96–5.83). 

In summary, no statistically significant observed excess in overall cancer incidence or 

mortality was found among AN workers, but the presence of a healthy worker effect is likely. 

An increase in prostate cancer incidence was noted. As there is a general high rate of survival 

for prostate cancer cases, cancer incidence rather than mortality should be considered in the 

evaluation of AN exposure and disease. Some of the study’s disadvantages that limit the 

interpretation of the results include the small sample size and number of cancer cases, subjective 

exposure assessment, lack of smoking information, and lack of stratification by latency and dose 

in the data analysis. There was the possibility of under-ascertainment of cases, particularly 

prostate cancer cases, by relying on the DuPont Cancer Registry as the source of information on 

cancer incidence. The results of this study support the findings of an excess in prostate cancer by 

O’Berg et al. (1985), but the aforementioned study limitations may have hindered the 

observation of an association between lung cancer and AN. 

Wood et al. (1998) combined the Virginia and South Carolina cohorts described above 

(Chen et al., 1987; O’Berg et al., 1985) and analyzed 2,428 male workers with an added decade 

of follow-up. The exposure assessment was updated, taking into account plant histories, 
 DRAFT - DO NOT CITE OR QUOTE 62 

descriptions of manufacturing processes, and changes that would affect exposures, a matrix of 

job titles, and work area names, documentation of personal protective equipment use, personal 

and area air sampling data from 1975, and descriptions of working conditions by long-term 

employees. Environmental air samples confirmed changes in plant processes, engineering, and 

ventilation. Exposure levels for the period before 1975 were estimated from information 

provided by a panel of “knowledgeable employees.” Wood et al. (1998) estimated peak AN 

exposure in parts per million for a 40-hour workweek for each job title/work area combination 

and averaged this over a year. Peak exposure level categories, reported as the interval averages, 

were low (0.11 ppm), moderate (1.1 ppm), high (11 ppm), and very high (30 ppm). Other 

exposure variables analyzed included latency (<20 and ≥20 years of observation), duration of 

exposure (<5, 5–9, and ≥10 years), and cumulative exposure (<10, ≥10–<50, ≥50–<100, and 

≥100 ppm-years). There was no information on exposure to other chemicals or on smoking 

status of the subjects. 

The cohort included all employees who worked in exposed areas in either plant until the 

plants were closed. The DuPont Cancer Registry was used to identify incident cases of cancer 

among employees during employment. Thus, incident cancer cases occurring after tenure at 

DuPont would not have been identified. Vital status of past employees was determined through 

a review of the National Death Index (1979–1991) and the Social Security Administration (all 

years). Vital status of living employees was confirmed through pension records, motor vehicle 

records, and credit bureau reports. Expected numbers of deaths were derived from the DuPont 

mortality files and the U.S. population. The period of follow-up was extended through 1991 in 

the South Carolina plant and 1990 in the Virginia plant. At the end of the follow-up period, 

approximately 18% of the cohort was deceased (n = 454). The entire cohort had a total of 

72,083 person-years of follow-up for the mortality analyses and 29,461 person-years for the 

morbidity analyses. More than half of the study population was born before 1930, and 82% were 

first exposed before 1971, thus allowing adequate follow-up to examine latency and adequate 

attained age to examine most cancer outcomes. A total of 37% of the population had a 

cumulative exposure level estimated at 50 or more ppm-years. 

The SMR analysis revealed that the 454 deaths observed in the cohort were significantly 

below the expected number of deaths based on U.S. rates (SMR = 0.69, 95% CI = 0.62–0.75). 

There were 126 deaths from cancer, which include 46 lung cancer deaths, 27 digestive cancer 

deaths, and 11 prostate cancer deaths (Table 4-5). The SMR for all cancers was also 

significantly lower than expected (SMR = 0.78, 95% CI = 0.64–0.93), indicating a possible 

healthy worker effect. Incomplete ascertainment of the endpoint of death may have also played a 

role in the low SMR value, as only 18% of the cohort was deceased at the time of the follow-up. 

Among the site-specific cancer mortalities, an excess number of prostate cancer deaths was 

reported (SMR = 1.29, 95% CI = 0.64–2.30). A comparison of the cohort death rates with those 

derived from the DuPont mortality registry showed SMRs that were slightly different than those 
 DRAFT - DO NOT CITE OR QUOTE 63 

derived from the U.S. data but did not provide any definitive differences. For all comparisons, 

there was no evidence of a relationship with any measure of exposure. For respiratory cancer, a 

nonsignificant excess of observed deaths was noted for the highest exposure level within the 

stratified analysis (SMR = 1.23 based on 23 observed deaths, 95% CI = 0.80–1.85). 

Cancer incidence in the cohort was compared with company-wide incidence rates derived 

from the DuPont Cancer Registry. There were no significant elevations reported in any cancerspecific category (Table 4-5), although an excess in prostate cancer cases was reported. There 

were sufficient deaths in several categories to allow examination of the patterns of incidence by 

the four measures of exposure utilized in the mortality analyses. Specifically, all cancers, 

digestive organ cancers, respiratory system cancer, and prostate cancer were examined in the 

exposure analyses. There was no evidence of a relationship with any measure of exposure for all 

cancers, respiratory cancer, or digestive organ cancers. 

Table 4-5. Distribution of select mortalities among exposed workers in two 

AN plants 

South Carolina cohort Virginia cohort Combined cohort 

Cause of 

disease/death

Observed

deaths 

SMRa

(CI) 

Observed

deaths 

SMRa

(CI) 

Observed 

deaths 

SMRa

(CI) 

Observed 

cases 

SIRa

(CI) 

All causes 271 0.76b

(0.67–0.85)

185 0.60 

(0.51–0.69)

454 0.69b

(0.62–0.75)

– – 

All cancers 77 0.88 

(0.69–1.10)

50 0.66 

(0.49–0.87)

126 0.78b 

(0.64–0.93)

101 0.97 

(0.79–1.18)

Lung cancer 35 1.06 

(0.74–1.47)

11 0.40b

(0.20–0.71)

46 0.76 

(0.56–1.02)

17 0.81 

(0.48–1.28)

Digestive 

cancer 

12 0.57b

(0.29–0.99)

15 0.81 

(0.45–1.33)

27 0.69 

(0.45–1.00)

22 0.89 

 (0.56–1.34)

Prostate 

cancer 

5 1.23 

(0.40–2.86)

6 1.32 

(0.48–2.88)

11 1.29 

(0.64–2.30)

12 1.58 

 (0.82–2.76)

a

SIR and SMR standardized against company-wide rates. 

b

Statistically significant (p < 0.05). 

Source: Amended from Wood et al. (1998). 

In summary, this study provided better exposure assessment than previous studies of this 

group of workers. Additional follow-up and the combination of two small cohorts enhanced the 

information available for inclusion; however, the apparent healthy worker effect may have 

masked a relationship between AN exposure and death from or incidence of lung cancer or other 

cancers. 

Symons et al. (2008) provided an update based on the combined Virginia and South 

Carolina cohorts from Wood et al. (1998), adding 11 years of follow-up. The exposure 

assessment was the same as described in Wood et al. (1998) with exposure being based on a job-
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exposure matrix, documentation of personal protective equipment use, personal and area air 

sampling data, and descriptions of working conditions by long-term employees. Vital statistics 

were obtained through the DuPont Epidemiology Registry and verified by the National Death 

Index. New in this update was the assignment of mean intensity values based on estimated 

intensity categories ranging from <0.2 to >20 ppm. These intensity categories were coupled with 

duration of employment to determine cumulative exposure. For SMR calculations, the expected 

number of deaths were derived both the U.S. population and regional DuPont employees. To 

reduce potential bias associated with the healthy worker effect, the Occupational Mortality 

Analysis Program (OC-MAP) was utilized for SMR calculations. For the estimation of relative 

mortality risk via a hazard ratio, a log linear model for AN exposure was assumed for all-cause 

and cause-specific outcomes. 

Of the 2,559 workers from Wood et al. (1998), 11 workers were found to be exposed to 

AN for <6 months and thus were excluded from the cohort in Symons et al. (2008). A total of 

839 deaths (32%) were observed in this updated cohort of 2,548 male workers. Of these, 

240 deaths were due to cancer, with 88 deaths being specific to lung cancer (Table 4-6). One 

quarter of the updated cohort were found to be in the mean intensity exposure group of 

<2.0 ppm, while, two-thirds were in the 2.0–19.9 ppm mean intensity exposure category. The 

number of deaths, especially cause-specific deaths, in these exposure groups was not reported. 

Table 4-6. Distribution of select mortalities among exposed workers 

Cause of death South Carolina cohort Virginia cohort Combined cohort

Observed

deaths

SMRa 

(95% CI)

Observed

deaths

SMRa 

(95% CI)

Observed

deaths

SMRa 

(95% CI)

SMRb 

(95% CI)

All causes 481 0.98 

(0.89–1.07) 

358 0.85c

(0.76–0.95) 

839 0.92c

(0.86–0.98) 

0.69c

(0.64–0.74) 

All cancers 144 1.00 

(0.84–1.18) 

96 0.81c

(0.67–0.99) 

240 0.92 

(0.81–1.04) 

0.73c

(0.64–0.82) 

Lung cancer 61 1.14 

(0.88–1.49) 

27 0.64c

(0.42–0.93) 

88 0.92 

(0.75–1.14) 

0.74c

(0.60–0.91) 

Prostate cancer 12 0.93 

(0.48–1.63) 

13 1.12 

(0.60–1.92) 

25 1.02 

(0.66–1.51) 

0.91 

(0.59–1.35) 

aBased on company regional rates. 

bBased on U.S. population rates. 

c

Statistically significant (p < 0.05). 

Source: Amended from Symons et al. (2008). 

Symons et al. (2008) also reported hazard ratio estimates for 100-ppm years increase in 

cumulative exposure (Table 4-7). In addition to the variable ‘exposure term’ used in the crude 

model, the adjusted model utilized in generating hazard ratio estimates included ‘birth period’ 

(6-decade ordinal variable) and ‘employment in South Carolina start-up group’ (binary 
 DRAFT - DO NOT CITE OR QUOTE 65 

indicator). The authors noted a slight significant increase in all-cause mortality associated with 

increasing cumulative exposure to AN in the crude model but did not find any other statistically 

significant findings. Colorectal and brain cancers had elevated hazard ratios but were not 

statistically significant in either the crude or adjusted models. 

Table 4-7. Crude and adjusted hazard ratio estimates for 100 ppm-year 

increase in cumulative exposure 

Crude Adjusteda

Cause of death Hazard ratio 95% CI Hazard ratio 95% CI

All causes 1.12b 1.04–1.21 1.05 0.97–1.14 

All cancers 1.07 0.92–1.24 1.00 0.86–1.17 

Lung cancer 1.04 0.81–1.33 0.95 0.73–1.23 

Prostate cancer 0.81 0.48–1.35 0.78 0.46–1.32 

Colorectal cancer 1.13 0.74–1.71 1.16 0.75–1.81 

Brain and CNS 1.37 0.59–3.16 1.03 0.38–2.78 

aModel includes exposure term, birth period, and employment in South Carolina start-up group. 

b

Statistically significant (p < 0.05). 

Source: Amended from Symons et al. (2008). 

Hazard ratios estimates were also derived based on lagged cumulative exposure. 

Increasing exposure lags resulted in decreasing hazard ratios for all cancers, lung cancer, and 

colorectal cancer. However, an increase in hazard ratio estimates over lagged cumulative 

exposure was observed for brain and CNS cancer and lymphatic and hematopoietic cancer. It 

should be noted that the number of events for these cancers were small (Table 4-8). 
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Table 4-8. Hazard ratio estimated for select cancer mortality by lagged 

cumulative exposure for 100 ppm-year increase in cumulative exposure 

5-Yr lag 

(n = 2,224) 

10-Yr lag 

(n = 2,066) 

15-Yr lag 

(n = 1,907) 

Cause of death Events 

Hazard ratio 

(95% CI) Events 

Hazard ratio 

(95% CI) Events 

Hazard ratio 

(95% CI) 

All cancers 210 1.03 

(0.87–1.23) 

199 0.98 

(0.80–1.20) 

179 0.94 

(0.74–1.19) 

Lung 75 0.95 

(0.70–1.28) 

72 0.84 

(0.59–1.19) 

63 0.80 

(0.53–1.22) 

Prostate 22 0.86 

(0.48–1.53) 

19 0.98 

(0.50–1.92) 

15 0.95 

(0.41–2.22) 

Colorectal 26 1.06 

(0.64–1.76) 

24 0.90 

(0.49–1.66) 

23 0.81 

(0.40–1.66) 

Brain and CNS 4 1.38 

(0.43–4.47) 

4 1.55 

(0.44–5.47) 

4 1.96 

(0.49–7.84) 

Lymphatic and 

hematopoietic 

16 1.09 

(0.59–2.01) 

14 1.29 

(0.66–2.54) 

13 1.27 

(0.57–2.86) 

Source: Amended from Symons et al. (2008). 

In summary, Symons et al. (2008) followed workers for over 50 years and, among the 

33% mortality in the cohort, reported that no statistically significant observed excess in overall 

mortality was found among AN workers. Unlike the previous studies based on the DuPont 

cohort, Symons et al. (2008) did not provide cancer incidence data or address previous issues 

with this cohort such as smoking status and concomittent exposure to other chemicals. This 

update did attempt to reduce potential bias from the healthy worker effect with specialized 

statistical program. Differences between U.S. population-based SMRs and regional workerbased SMR indicated that there may still be a strong healthy worker effect. Although Symons et 

al. (2008) categorized workers in different mean intensity exposure and cumulative exposure 

groups, the authors did not report the observed number of cause-specific deaths in these 

categories or provide cause-specific SMR estimates. In deriving hazard ratio estimates, Symons 

et al. (2008) adjusted for workers ‘employment in South Carolina start-up group.’ Based on 

O’Berg (1980), it appears that workers in the South Carolina start-up group may have had higher 

levels of exposure to AN. Additionally, the metric derived by quantitation of AN exposure and 

SMR derivation of this subgroup would have been helpful for better assessing the relationship 

between AN exposure and lung cancer. 

Overall summary 

 The DuPont cohort studies were the first to hypothesize an association between AN 

exposure and cancer, specifically lung and prostate cancer. It should be noted that the DuPont 

cohort studies are limited to male workers and lack appropriate unexposed worker comparison 
 DRAFT - DO NOT CITE OR QUOTE 67 

groups to better assess the risk of developing cause-specific diseases, namely cancer. Even in 

the most recent cohort study by Symons et al. (2008), smoking and concomitant exposures were 

not adequately addressed in any of the DuPont cohort studies. Interestingly, the prostate cancer 

findings in the Wood et al. (1998) study revealed a closer association to duration of employment 

rather than exposure. This observation is echoed with brain and CNS cancer and lymphatic and 

hematopoietic cancer in Symons et al. (2008). 

Excluding Symons et al. (2008), the DuPont cohort studies are the only studies that 

evaluate the association between AN exposure and cancer incidence rather than relying on a 

surrogate marker such as cause-specific death. For cancer incidence, the cohort studies appeared 

to only focus on data from the DuPont cancer registry rather than including data from state or 

national tumor registries that have known quality assurance and quality control procedures for 

diagnoses. 

 Symons et al. (2008) assessed risk based on mortality. As with the other DuPont studies, 

the reliance on mortality statistics from the U.S. population as a comparison group is less 

desirable given the potential for bias from the healthy worker effect. Symons et al. (2008) 

attempted to address this issue by employing DuPont regional workers as a comparison group 

instead of using company-wide statistics as in other DuPont studies. Information regarding other 

chemical exposures among regional workers would aid in reducing the uncertainty of exposure 

to other potential carcinogens in this comparison group. 

As with its predecessor, Wood et al. (1998), the most recent DuPont cohort study Symons 

et al. (2008) may also suffer from exposure misclassification, as no exposure monitoring existed 

prior to 1975. This lack of information on exposure potential and level may also subject the 

studies to recall bias. However, given the shortcomings of each of the individual DuPont studies, 

there is still suggestive evidence that there may be an association between AN exposure and the 

incidence of cancer. 

American Cyanamid Company 

Collins et al. (1989) conducted a retrospective cohort study of 2,671 men who worked at 

two American Cyanamid Company plants in Louisiana and Florida from start-up (1951 for the 

Louisiana plant, 1957 for the Florida plant) through December 1973. One facility manufactured 

AN and other materials, and the other facility utilized large quantities of AN in the 

manufacturing of acrylic fiber. All 2,671 study subjects were followed through the end of 

1983 for mortality, thus allowing at least 10 years of follow-up for the cohort. According to 

Collins et al. (1989) for exposure estimation, industrial hygiene monitoring, which began in 

1977, was considered representative of previous exposure levels, with adjustments made for 

changes in practices and engineering controls. Any actual measurements that were available 

were also used to tailor job-specific exposure. The investigators created four exposure 

categories: 0–<0.01, 0.01–0.7, 0.7–7.0, and >7 ppm/year. Exposed workers were defined as 
 DRAFT - DO NOT CITE OR QUOTE 68 

having a cumulative exposure of >0.01 ppm/year. Smoking information was only available for 

58% of the workers. Each person in the cohort was coded as smoker (smoked for ≥3 months), 

nonsmoker (smoked for <3 months), or unknown (information not available). The authors used 

an internally standardized method of adjustment for age (<45, 45–54, 55–64, 75+ years), race 

(white, nonwhite), smoking status (smoker, nonsmoker, unknown), latency (<10, 10–19, 

20+ years), and time period (<1965, ≥1965). In the calculation of the SMR, the expected number 

of cause-specific deaths was derived from U.S. general population data on men. 

More than 50% of the exposed workers in this study were followed for at least 20 years. 

By the end of the study, a total of 237 deaths (92 from the unexposed group and 145 from the 

exposed group) were observed, and death certificates were located for 224 of these workers. 

From both groups combined, there were 65 cancers, including 23 respiratory cancers, of which 

22 were lung cancers. For lung cancer, there was no significant elevation in the SMR for either 

the exposed or unexposed group (SMR in unexposed group = 1.08, 95% CI = 0.69–1.61; SMR in 

exposed group = 1.01, 95% CI = 0.74–1.35). A similar pattern was observed among the lung 

cancer deaths, with no significant elevations reported (SMR in unexposed group = 1.01, 95% CI 

= 0.44–2.01 [7 cancer deaths]; SMR in exposed group = 1.00, 95% CI = 0.58–1.61 [15 cancer 

deaths]). The SMRs for the AN exposure categories for lung cancer were 1.09 (95% CI = 0.51–

2.08), 0.63 (95% CI = 0.10–2.06), 0.64 (95% CI = 0.20–1.53), and 1.41 (95% CI = 0.68–2.58) 

for categories 0–<0.01, 0.01–0.7, 0.7–7.0, and >7 ppm/year, respectively. Using an internally 

standardized method that adjusted for smoking, race, latency, age, and time period, the SMRs 

were 1.11 (95% CI = 0.52–2.11), 0.72 (95% CI = 0.12–2.36), 0.71 (95% CI = 0.23–1.72), and 

1.22 (95% CI = 0.59–2.23), respectively, for the above exposure categories. None of these risk 

estimates or subsequent trend tests was statistically significant. No additional information was 

provided with regard to the nature of the trend test. 

The inclusion of an analysis for the unexposed group compared to the U.S. population 

was helpful and allowed an evaluation of whether elevations in cancer rates in the exposed group 

were also observed in the unexposed group and thus were not likely to be related to exposure. It 

should be noted that indirect standardization (the use of age-specific mortality rates from the 

standard U.S. population to derive regional expected deaths) was used, thus hindering the ability 

to compare SMRs across groups. This study attempted to quantify exposure levels and control 

for smoking history. The study did allow for approximately 50% of the exposed cohort to have 

at least 20 years of follow-up, thus strengthening the possibility that a health effect might be 

detected. However, since the endpoint marker used was death, as recorded on the death 

certificates, and with less than 10% of the study cohort deceased by the end of the study, the 

study may have been premature in attempting to link AN exposure to cancer deaths. This study 

may have had insufficient power as portrayed by the observation of only 15 lung cancer deaths in 

the exposed group. It should also be noted that this study, as with many other cohorts assembled 

to assess the relationship between AN and cancer, consists of only men. 
 DRAFT - DO NOT CITE OR QUOTE 69 

Because the results presented were adjusted by latency, duration of exposure, and time 

since exposure, relative risks (RRs) in these strata could not be readily compared with the results 

of the studies of Symons et al. (2008), Benn and Osborne (1998), Blair et al. (1998), Swaen et al. 

(1998), Wood et al. (1998), O’Berg et al. (1985), and O’Berg (1980). Unlike other studies that 

assumed early exposure levels were higher, Collins et al. (1989) assumed that AN exposure 

levels in 1977 were representative of the time frame prior to that date. This assumption may 

have led to exposure misclassification, resulting in a flattening of the dose-response gradient. 

Other limitations included low statistical power to evaluate lung or rarer cancers, particularly in 

subgroup analyses, incomplete smoking information, and use of SMRs rather than comparable 

unexposed controls. In summary, this study may have been premature in assessing the 

relationship between AN exposure to cancer deaths. 

Synthetic chemical plant in the U.S. 

Waxweiler et al. (1981) examined the mortality rates in a cohort of 4,806 chemical plant 

workers who were exposed to many potential carcinogens, including AN. The cohort was 

identified as all workers at the synthetic chemicals plant who were first employed between 

1942 and 1973. These workers were followed through the end of 1973. Since the majority of 

the cohort (63%) were actually hired before 1954, this allowed for at least 20 years of latency 

and follow-up for the majority of the workers. However, it should be noted that some workers 

had less than 1 year of follow-up, latency, or exposure. The cohort was described as young, with 

only 30% of live workers being over 55 years of age. 

Mortality rates in the plant cohort were compared to those derived from the U.S. white 

male population. Under the assumption that all workers were considered at risk from the first 

day of employment, no difference was noted between the observed deaths and the expected 

deaths (556 observed deaths vs. 550.2 expected deaths, SMR = 1.01, 95% CI = 0.93–1.10). The 

number of observed cancer deaths was higher than expected (109 observed vs. 92.5 expected, 

SMR = 1.18, 95% CI = 0.97–1.42). Upon stratification of cancer deaths, higher numbers of 

respiratory system and CNS cancers were observed among the workers (respiratory cancer SMR 

= 1.49, 95% CI = 1.09–1.99; CNS cancer SMR = 2.09, 95% CI = 1.02–3.84). 

A secondary analysis was performed among workers who had at least 10 years of 

exposure. Waxweiler et al. (1981) noted similar findings, though actual values were not 

reported. The authors did note that there were 39 observed deaths from cancers of the 

respiratory system compared to 25 expected (SMR = 1.56, 95% CI = 1.12–2.11). A similar 

elevation had been observed by the authors in a previous publication (Waxweiler et al., 1976) 

that focused on the workers with high vinyl chloride monomer exposure; thus, the authors 

concluded that the excess lung cancer risk may not solely be due to exposure to a single 

chemical. 
 DRAFT - DO NOT CITE OR QUOTE 70 

Serially additive expected dose (SAED) modeling was performed to determine whether 

exposure to chemicals, including AN, was associated with excess lung cancer risk. Job histories 

were used to assess the potential for exposure to 19 chemicals routinely used at the plant. Each 

job was assigned a qualitative exposure rating (from 0 for no exposure to 5 for intimate contact 

on the skin or high inhalation potential) for each year of the study. Thirty-five of the 80 (56%) 

job categories ranked had no exposure to AN, with another 30% reporting minimal to low levels 

of exposure. An exposure score was derived for each chemical for all workers by summing each 

exposure rating for each year. The exposure score for each cohort member dying from 

respiratory system cancers was compared to the score for a group of workers with a similar birth 

year and year of first hire (the “subcohort” from which the case arose). Scores in the 

nonrespiratory death subcohorts (expected scores) were subtracted from the observed scores in 

the respiratory cancer deaths to obtain an observed-minus-expected cumulative dose difference 

per lung-cancer case. For AN, this calculation resulted in a negative unit, reflecting that 

expected cumulative dose greatly exceeded the observed cumulative dose. No significant 

differences with regard to AN exposure were observed in this analysis. 

While this study showed significant increased risks of death from lung and CNS cancer in 

a cohort of workers exposed to multiple carcinogens, limitations with the study design hindered 

the ability to assess the relationship between the observed deaths and exposure to AN. The 

population of workers was potentially exposed to multiple carcinogens, so any effect of exposure 

to AN may have been impossible to measure. 

Rubber manufacturing plant 

Delzell and Monson (1982) analyzed the mortality among workers from a rubber 

manufacturing plant in order to determine if potential exposure to AN might be associated with 

excess deaths. The study included 327 white males who had been employed at the plant for at 

least 2 years between January 1940 and July 1971. These employees were selected from over 

15,000 workers because they worked in departments where AN exposure was most likely. 

Mortality information was gathered on both active and pensioned workers through July 1978, 

allowing at least 7 years of follow-up for most workers in the cohort. Workers without a record 

of death were assumed to be alive. Mortality rates were compared with the white male subset of 

the U.S. general population rates, stratifying by cause of death, age, and calendar time. 

By mid-1978, a total of 74 deaths (~ 22%) were observed, 22 of which were from various 

types of cancers. The differences between the observed and expected deaths for all-cause and for 

cancer mortality were not statistically significant, with SMRs of 0.8 (95% CI = 0.7–1.0) and 

1.2 (95% CI = 0.8–1.9), respectively. Nine lung cancer deaths were observed as compared to the 

5.9 expected (SMR = 1.5, 95% CI = 0.7–2.9). The ability to detect statistical significance may 

have been hindered by the small number of deaths. The numbers of deaths from bladder, 

lymphatic, and hematopoietic cancers exceeded the expected values, but the number of deaths 
 DRAFT - DO NOT CITE OR QUOTE 71 

were small. Lung cancer deaths were examined by duration of employment and latency. No 

trends were noted, and there were no deaths in the group employed for ≥15 years. However, 

7 lung cancer deaths were observed as compared to the 4.1 expected in the group with 15 or 

more years of latency since first exposure. 

This study was based on a small number of study participants, with less than a quarter 

reaching the study endpoint of death. The study provides no quantitative assessment as to the 

level of AN exposure. Mixed exposure is also an issue, since it is noted that butadiene, styrene, 

and vinyl pyridine were utilized at the plant during the exposure time frame. However, there is 

no information in the study as to whether the study participants were potentially exposed to these 

other agents. Finally, though lung cancer was specifically analyzed, no mention of data 

collection or adjustment for smoking history was reported. These shortcomings limit the weight 

that this study carries with regard to assessing the relationship between AN exposure and cancer 

mortality. 

The Netherlands cohort 

Three successive papers (Swaen et al., 2004, 1998, 1992) reported mortality analyses of a 

Dutch cohort consisting of 2,842 male workers employed ≥6 months from 1956 to 1979 in eight 

companies that produced AN, latex polymer, acrylic fiber, AN polymers, resins, or acrylamide. 

This cohort was compared to 3,961 workers at a neighboring plant during the same time frame 

who were not exposed to any known carcinogens in the normal work setting. Use of this 

reference population aided in minimizing the impact of a potential healthy worker effect. 

In the original study (Swaen et al., 1992), exposure assessment for most companies was 

conducted using a job matrix model and air AN samples collected in 1978–1979. The exposure 

assessment took into account changes in the production process, industrial hygiene control 

measures, and work procedures over time. Potential for exposure misclassification was 

enhanced by the extrapolation of exposure monitoring data from one plant to the other seven 

plants, for which there were no exposure monitoring data. For all of the companies involved, 

most jobs were classified in the following ranges: 0–0.5, 0.5–1, 1–2, and 2–5 ppm. However, 

for some jobs, only two categories could be distinguished: 0–2 and 2–5 ppm. For all exposed 

workers in the study, a cumulative measure of exposure was derived by multiplying the average 

concentration for a particular exposure class by the number of years in that class. Although 

workers were characterized by duration of exposure and duration of follow-up, these variables 

were not used in the evaluation of the relationship between AN and cancer deaths. 

Both the exposed and the unexposed groups were compared with national Dutch death 

rates to generate SMRs. No direct comparison of rates in the exposed and unexposed groups was 

followed for ≥20 years after entry into the cohort. Almost 24% of the exposed cohort was 

categorized in the highest category of cumulative exposure of ≥10 ppm-years, a cutoff higher 

than the ≥8 ppm used in the Blair et al. (1998) study. 
 DRAFT - DO NOT CITE OR QUOTE 72 

Mortality information was collected for both groups through the end of 1987, allowing at 

least 8 years of follow-up for all surviving study members. A total of 134 deaths was observed 

in the exposed group (SMR = 0.78, 95% CI = 0.65–0.92) and 572 deaths in the unexposed group 

(SMR = 0.77, 95% CI = 0.71–0.84), undertaken, with the authors citing differences in age and 

calendar time between the groups as the rationale. Nearly half of the exposed group worked with 

AN for at least 5 years, and 26% of the unexposed group was both observations significantly 

lower than expected. As both exposed and unexposed workers were compared to a national rate, 

the lower observed deaths may be attributable to the healthy worker effect. Among the workers 

exposed to AN, no significant differences were noted between the number of observed and 

expected cancer deaths (i.e., 42 observed deaths vs. 50.8 expected, SMR = 0.83, 95% CI = 0.60–

1.10). Analyses of site-specific cancer deaths in this group did not reveal any significant 

differences between the observed cancer deaths and the expected values. However, among the 

unexposed workers, the number of observed deaths from cancer of the trachea and lung was 

significantly lower than expected (i.e., 67 observed deaths vs. 93.3 expected deaths, SMR = 0.72, 

95% CI = 0.56–0.90), likely indicating, at least in part, the presence of a healthy worker effect. 

Among exposed workers in the highest exposure category, the number of observed lung cancer 

deaths exceeded the number expected (SMR = 1.11, 95% CI = 0.48–2.19). Compelling evidence 

of the healthy worker effect is provided by the fact that the observed number of deaths among 

the unexposed group, regardless of disease category, is significantly lower than the expected 

estimates derived from the national population statistics. 

In an updated analysis by Swaen et al. (1998), an additional 8 years of follow-up yielded 

156 more deaths in the exposed cohort and 411 more deaths in the unexposed group, bringing the 

total number of observed deaths to 290 and 983, respectively. The exposure assessment was not 

updated because more recent exposures were considered to be negligible. For both groups, the 

total number of cancers observed was lower than expected. The exposed group had 97 deaths 

from neoplasms observed vs. 110.8 expected (SMR = 0.88, 95% CI = 0.71–1.06) and the 

unexposed group had 332 deaths observed vs. 400.4 expected (SMR = 0.83, 95% CI = 0.74–

0.92). With the increased follow-up time, slight, but mainly statistically nonsignificant, 

increases in cancer of the brain, large intestine, prostate, and all leukemias for the exposed group 

were observed that were not previously evident. While these increases were based on small 

numbers, it is noteworthy that intestinal tract and brain are cancer target organs in rat studies. 

The association between AN exposure and mortality, all-cancer mortality, and lung 

cancer mortality was examined by the following exposure variables: latency, peak exposure, 

cumulative exposure, respirator use, and exposure to other carcinogens. Overall, among workers 

exposed to AN, the number of observed deaths did not differ greatly from expected. 

Swaen et al. (2004) revisited this cohort of AN workers and added 5 years of follow-up to 

the analysis, for a minimum of 22 years of follow-up. This updated study added 142 new deaths 

for the exposed cohort and 360 deaths to the unexposed cohort, bringing the total number of 
 DRAFT - DO NOT CITE OR QUOTE 73 

observed deaths for 432 and 1,343, respectively. The number of deaths was 2.5-fold higher than 

in the original cohort study and accounted for over a quarter of the original study population. 

The exposure assessment was not updated from the first study. 

SMR analyses were conducted for both the exposed and unexposed cohorts, using the 

Dutch general population rates as a comparison. The observed number of cancer deaths in the 

exposed group was not significantly different from the expected value (Table 4-9). The study 

found that number of respiratory cancer deaths in this group was higher than expected, 

67 observed vs. 62.5 expected (SMR = 1.07, 95% CI = 0.83–1.36). Analyses by peak exposure, 

respirator use, and possible exposure to cocarcinogens were also performed, yielding no 

indication for elevated site-specific cancer risks in any of the subgroups. Additional analyses 

were performed by examining the SMRs for lung cancer by various measures of dose and 

latency (Table 4-10). An increasing SMR was noted with increasing levels of exposure (i.e., 

0.92, 1.06, and 1.15 for low, medium, and high exposure, respectively). 

Table 4-9. Distribution of select mortalities among AN-exposed and 

unexposed workers 

Exposed workers Unexposed workers 

Cause of death Observed Expected SMR 95% CI Observed Expected SMR 95% CI 

All causes 432 467.8 0.92 0.84–1.01 1,343 1,545.2 0.87 0.82–0.92a

All cancers 146 164.5 0.89 0.75–1.04 447 519.8 0.86 0.78–0.94a

Lung and 

trachea cancer 67 62.5 1.07 0.83–1.36 160 203.8 0.78 0.67–0.92a

a

Statistically significant (p < 0.05). 

Source: Amended from Swaen et al. (2004). 
 DRAFT - DO NOT CITE OR QUOTE 74 

Table 4-10. Lung cancer mortality of AN-exposed workers stratified by 

cumulative dose and latency 

 All cancer mortality Lung cancer mortality 

Dose Observed Expected SMR 95% CI Observed Expected SMR 95% CI 

Low (<1 ppm/yr) 

<10 Yrs latency 0 1.9 – – – 0.7 – – 

10–20 Yrs latency 7 7.5 0.93 0.37–1.91 3 2.9 1.03 0.21–2.97

≥20 Yrs latency 10 11.3 0.88 0.42–1.62 4 4.0 1.00 0.27–2.53

Total 17 20.7 0.82 0.48–1.31 7 7.6 0.92 0.37–1.89

Moderate (1–10 ppm/yr) 

<10 Yrs latency 8 8.4 0.95 0.41–1.87 1 3.2 0.31 0.40– 1.58

10–20 Yrs latency 31 32.1 0.96 0.66–1.37 16 12.4 1.29 0.74–2.09

≥20 Yrs latency 39 49.4 0.79 0.56–1.08 19 18.2 1.04 0.63–1.63 

Total 78 89.9 0.87 0.69–1.08 36 33.8 1.06 0.75–1.47 

High (>10 ppm/yr) 

<10 Yrs latency 8 6.0 1.33 0.57–2.62 3 2.5 1.20 0.24–3.44 

10–20 Yrs latency 25 21.1 1.18 0.77–1.75 12 8.4 1.43 0.74–2.49 

≥20 Yrs latency 18 26.3 0.68 0.40–1.08 9 10.0 0.90 0.41–1.70 

Total 51 53.4 0.95 0.71–1.26 24 20.9 1.15a 0.75–1.68a

aCalculated based on reported data. 

Source: Amended from Swaen et al. (2004). 

In summary, as with previous analyses of this cohort, the interpretation of the results 

from this study is limited by the following: potential misclassification of AN exposure because 

of the use of current measures to derive past exposures and the use of subjective information 

about exposure, use of a population-based control group, pooling of data from factories with 

different kinds of AN production and exposures without adjusting for this, and lack of 

information on smoking. 

Epidemiology studies based on this Dutch cohort provided better exposure assessment 

than studies using the SAED method or similar extrapolation tools. Here, exposure categories 

represented estimates based, in part, on actual measurements rather than ordinal ranking. The 

number of lung cancer deaths observed among the AN-exposed workers was higher than 

expected. However, the following biases regarding the Dutch cohort studies are possible: 

potential misclassification of AN exposure because of the use of current measures to estimate 

past exposures and the use of subjective information about exposure, use of a population-based 

control group, pooling of data from factories with different kinds of AN production and 

exposures without appropriate adjustment, and bias based on the lack of smoking information 

available. The low SMRs observed indicate the presence of a potential healthy worker effect, 

making it more difficult to detect an association with AN. 
 DRAFT - DO NOT CITE OR QUOTE 75 

The Dutch studies cohort utilized an unexposed worker cohort for a “comparison” group. 

The use of this unexposed group was not fully explored by developing rates by age and calendar 

time in the unexposed group to be used as a basis for developing expected rates in the exposed 

group. Instead, the unexposed group was compared to national rates and then used as a 

“standard” to see if the patterns of SMRs generated in the exposed cohort looked similar to those 

generated in the unexposed cohort. Therefore, the true comparison group used in these studies 

was the national population. It should be noted that the lung cancer SMR among workers 

exposed to AN was found to be higher than that among unexposed workers. Direct comparison 

between the exposed and unexposed workers in terms of an RR was not derived, as the 

demographics between the exposed and unexposed workers may have differed. Though no 

explicit details were provided, it is noted that the number of person-years and crude mortality 

rate are higher in the unexposed workers (recruited from a different plant) than in the exposed 

workers. Thus, the expected number of deaths for each group, on which the SMRs are based, 

would be dependent on different distributions or standards, a situation in which comparing the 

SMRs between the exposed and unexposed groups would not be recommended. Additional 

support is provided with the increasing SMR with level of exposure; a progressive increase of 

0.92 in the low exposure group to 1.15 in the high exposure group was reported. 

Finally, the statistical measure used in all the Dutch cohort studies was the SMR. This 

statistic allows for the comparison of cause-specific deaths and not the incidence of disease. 

Using deaths as a surrogate for disease may underestimate the true relationship between AN 

exposure and cancer, especially when the majority of the cohort population is not deceased. As 

with other studies that evaluate AN exposure using SMRs, these Dutch studies were focused on 

determining if AN exposure may lead to an excess of cause-specific deaths; however, these 

studies lack the appropriate design to address the issue of AN exposure and the incidence of 

disease, namely site-specific cancers. 

BASF plants in Germany 

A mortality study was conducted among workers from 12 BASF plants in Germany 

(Thiess et al., 1980). Though none of these plants manufactured AN, this substance, along with 

styrene and butadiene, was used in many of their processes. The number of employees in each 

plant varied, ranging from 30 to 334 employees. The first uses of AN at these plants did not 

occur simultaneously but rather over a course of 14 years, from 1954 to 1968. A total of 

1,469 active and former employees who had worked for >6 months processing AN were 

identified for mortality follow-up. The cohort was followed through May 15, 1978, and death 

certificates were obtained and coded for cause of death. There were 1,081 German workers in 

the cohort, and the vital status was traced for 98% of these workers. Tracing was less successful 

for the 388 foreign workers in the cohort, with only 56% follow-up. 
 DRAFT - DO NOT CITE OR QUOTE 76 

No measurements of levels of AN exposure were available for use in this study. It was 

noted that prior to 1976, AN was handled manually, and as a result, there may have been 

increased exposure during that time (Thiess et al., 1980). In later years, closed systems were 

utilized, leading to reduced exposures. Although measurements were not available, this study 

assumed that workers were occasionally exposed to levels of ≥20 ppm for short periods, based 

on the manual handling of AN at specific work sites prior to 1976. Several other known 

carcinogens were used at some of the facilities and could have presented a confounding effect in 

terms of cancer outcomes. One plant (Plant 5) was subsequently excluded from the analysis 

because of the potential for concurrent exposure to β-naphthylamine. 

The comparison rates used for the majority of the analyses were derived from mortality 

rates for the Federal Republic of Germany. The 1,469 workers accounted for a total of 

15,350 person-years of follow-up. A total of 89 deaths were observed, a value lower than the 

99 predicted deaths based on rates for the Federal Republic of Germany (SMR = 0.90, 95% CI = 

0.72–1.10). A total of 27 cancer deaths was observed for the entire cohort, compared to the 

20.5 expected deaths (SMR = 1.32, 95% CI = 0.89–1.89). 

In the analysis that excludes Plant 5, the number of observed deaths dropped to 74, with 

the expected deaths at 78.8 (SMR = 0.94, 95% CI = 0.74–1.17). Among these deaths, 20 were 

attributed to cancer, with a calculated expected value of 16.1 deaths (SMR = 1.24, 95% CI = 

0.78–1.88). In both analyses, the number of cancer deaths exceeded expected estimates, but the 

small sample size might have hindered the observation of statistically significant findings. When 

cause-specific cancer deaths were examined, a significant difference was noted between the 

observed and expected bronchial carcinoma (lung cancer) deaths, regardless of the inclusion of 

Plant 5 in the analysis (i.e., 11 observed deaths vs. 5.7 expected in the full cohort and 9 observed 

vs. 4.4 expected in the cohort without Plant 5). 

Neoplasms of the lymphatic and hematopoietic organs were also observed to be elevated, 

but not significantly (i.e., 4 observed vs. 1.7 expected in the full cohort and 4 observed vs. 

1.4 expected in the cohort without Plant 5). Because of the small number of deaths in this 

category, further stratification or examination was precluded. It should be noted that two of the 

four deaths in this category were from Hodgkin’s disease, which is significantly different from 

the 0.3 deaths expected. 

Analyses were conducted, excluding Plant 5, for the group of workers who were followed 

for at least 5 years before death or loss to follow-up. This comprised 944 workers, with only 

seven bronchial carcinomas reported. These carcinoma deaths were stratified by duration of 

exposure into three categories: 0–4, 5–9, and ≥10 years. There were no bronchial carcinomas in 

the 0–4 year exposure category, four in the 5–9-year exposure category and three in the highest 

exposure category. For the latter two categories, the observed number of deaths was higher than 

expected (SMR4–9 years = 3.86, 95% CI = 1.23–9.31; SMR≥10 years = 2.23, 95% CI = 0.57–6.07). 
 DRAFT - DO NOT CITE OR QUOTE 77 

The study of BASF workers showed a significant excess in lung-cancer deaths in workers 

potentially exposed to AN. The follow-up time was not specifically quantified; however, 

examination of the exposure (1954–1968) and follow-up (5/15/1978) dates indicates that most 

workers in the cohort were followed for at least 9 years. The study is limited by the fact that 

only 6% of the study cohort was recorded as deceased; this observation is important since death 

certificates were used to determine if an association between AN exposure and certain cancers 

existed. An additional limitation of this study is the fact that the cohort was assembled from 

12 different plants and some of the plants were acknowledged to have concurrent exposures to 

known carcinogens such as β-naphthylamine, vinyl chloride, or solvents. The study did not 

indicate when these overlaps in exposures could have occurred and how many workers at the 

plant could have been possibly exposed, and no information on the level of exposure was 

provided. This limitation coupled with a lack of ability to characterize the workers by job or 

exposure level makes this study less informative in trying to assess the relationship between 

cancer mortality and AN exposure. 

Six factories in the United Kingdom 

There have been two successive studies evaluating the mortality rates in a cohort of male 

workers potentially exposed to AN at six United Kingdom polymerization and spinning factories 

(Benn and Osborne, 1998; Werner and Carter, 1981). For both studies, workers were included if 

they were employed for at least 1 year between 1950 and 1968. Werner and Carter (1981) 

examined the mortality rates in a cohort of 1,111 men drawn from six factories in England, 

Wales, Scotland, and Northern Ireland. This cohort was followed through the end of 1978, 

allowing for a minimum 10-year follow-up for all surviving workers. The workers included in 

the study were deemed to have the potential for the highest level of AN exposure, since they 

were involved in either the AN polymerization process or spinning of acrylic fiber. However, no 

exposure monitoring data were available for the period of the study. Additionally, there was 

potential for concomitant exposure to styrene and butadiene in the work environment. 

Each worker in the cohort was classified according to the length of time spent in a highexposure job. This categorization resulted in 934 workers with ≥1 years and 177 workers with 

<1 year of potential for high exposure to AN. The remainder of the analyses focused on the 

934 workers with ≥1 year in a job with potential for high exposure. Examination of the personyears distribution by age group in these 934 workers revealed that <2% of the person-years was 

observed in persons over age 65, while 65% of the person-years was observed in the 15–44-year 

age range. Thus, the follow-up time for this cohort may be inadequate to detect excess cancer 

deaths. 

Among the 934 workers, 68 deaths were observed compared to the 72.4 expected based 

on mortality rates for the total male population of England and Wales (SMR = 0.93, 95% CI = 

0.73–1.18). Of these observed deaths, 21 were attributed to cancer, with 9 specifically attributed 
 DRAFT - DO NOT CITE OR QUOTE 78 

to cancer of the trachea, bronchus, and lung. The SMRs for all malignant neoplasms and cancer 

of the trachea, bronchus, and lung are 1.10 (95% CI = 0.72–1.70) and 1.20 (95% CI = 0.58–

2.17), respectively. Incidentally, the number of observed stomach cancer deaths was 

significantly higher than expected (5 observed vs. 1.9 expected, SMR = 2.63, 95% CI = 0.96–

5.83). 

The distribution of cancer deaths was also examined by age at death (age groups: 15–44, 

45–54, 55–64, and ≥65 years). No significant differences between the number of observed and 

expected all-cause deaths were found in any of the age groups. Of the 14 deaths observed in the 

15–44-year age group, 3 deaths were attributed to cancer of the trachea, bronchus, and lung, a 

significant increase over the 0.7 expected value (SMR = 4.28, 95% CI = 1.09–11.66). No 

significant differences between observed and expected cancer-specific deaths were noticed in 

any of the other age groups. 

All-cause deaths were also stratified based on the year of first exposure to determine if 

cancer risks were higher for those who were exposed in the early years of the factories’ 

operations (usually a surrogate for longer and often higher exposure and longer latency) 

compared with more recent hires. Three time periods were examined: 1950–1958, 1959–1963, 

and 1964–1968, with the observed number of deaths being 35, 21, and 12, respectively. No 

significant differences between the number of observed and expected deaths were found. 

Observed and expected deaths from all cancer types, including cancer of the trachea, bronchus, 

and lung, were similar in all three time periods, with only a slight increase in the most recent 

time period (i.e., 1964–1968) (all-cancer SMR = 1.36, 95% CI = 0.55–2.83; cancer of the 

trachea, bronchus, and lung SMR = 1.87, 95% CI = 0.48–5.10). 

In order to further examine latency, an analysis of cancer deaths by length of time since 

first exposure was performed. No increases in cancers of the stomach or cancers of the trachea, 

bronchus, and lung were noted with increasing time since first exposure. Similarly, the observed 

increases in cancers of the stomach and of the trachea, bronchus, and lung could not be related to 

duration of exposure, year of first exposure, or latency. It should be noted that the study power 

to examine these parameters was quite limited. Furthermore, 25% of the cohort (foreign 

workers, who may have had the highest exposure) were lost to follow-up, potentially introducing 

a bias resulting from an under-ascertainment of deaths. Another shortcoming of this study was 

that the comparison group selected to derive the expected values may not have been 

representative of the other regions and the comparisons may have been biased downwards by the 

healthy worker effect. This study was also limited by the short length of follow-up and small 

number of deaths observed. Aside from the shortcomings of this study, if an effect of AN were 

to be observed, one would expect cancer rates to be elevated in the group with the earliest years 

of first exposure, which represents the workers with the highest potential for greater exposure, 

longest follow-up, and longest latency. The fact that increases were observed in the most recent 

group (i.e., those first exposed between 1964 and 1968) weakens the argument that there was an 
 DRAFT - DO NOT CITE OR QUOTE 79 

exposure effect demonstrated in this study, because the latter group probably had lower exposure 

levels and fewer than 15 years latency and follow-up. 

In the update of the above study, Benn and Osborne (1998) expanded the sample to 

include workers employed in the same six AN polymerization and acrylic fiber spinning 

factories from 1969 to 1978 and extended follow-up through 1991, allowing for at least 13 years 

of follow-up. Added to the study were craftsmen with possible AN exposure, control laboratory 

workers, other possibly exposed workers, and unexposed workers. The sample size was 

2,763 men employed for ≥1 year. The exposure assessment in this study was based on a 

threshold limit enacted by the British government in 1981, a few measurements from the late 

1970s, and an exposure estimated for the period 1958–1977 by a chemist at one of the factories. 

The available exposure measurements were found to be lower than the calculated 8-hour timeweighted average (TWA) (0.4–2.7 vs. 20 ppm, respectively). Job titles were collapsed into three 

AN exposure categories: polymer workers and spinners—“high”; craftsmen, control laboratory 

workers, and others with possible AN exposure—“other or medium”; and all others into the 

“little or no” AN exposure group. No details were provided on how these categories were based 

on the previously described exposure estimates. Unlike the earlier study by Werner and Carter 

(1981), death rates for England and Wales were used to calculate expected deaths for the 

factories that were located in England and Wales. Scottish rates were used for the factories 

located in Scotland and Northern Ireland (rates for Northern Ireland were not available). 

The 13 years of follow-up resulted in a total 409 observed deaths, a value significantly 

lower than the expected (SMR = 0.84, 95% CI = 0.76–0.93). This result demonstrates a likely 

healthy worker effect. Stratifying by cause of death, no significant differences were noted 

between observed and expected deaths (Table 4-11), except in the case of all-circulatory 

diseases, in which the number of observed deaths was significantly lower than expected (SMR = 

0.86, 95% CI = 0.75–0.99). Upon stratification by the level of AN exposure, no significant 

excess in cause-specific mortality was observed (Table 4-11); however, an excess of lung, 

trachea, and bronchial cancers in the highest exposure group was found. In addition, linear 

regression analysis found a significant increasing trend between level of AN exposure and 

stomach cancer mortality. The distribution of cause-specific deaths was also examined by age of 

death, with age categorized in the same manner as by Werner and Carter (1981). No significant 

difference was found between the observed number of deaths in each age category and the 

expected value. This observation was also noted when all-cancer mortality was stratified by age 

group. Interestingly, among the youngest cohort of AN-exposed workers, the number of 

observed deaths from respiratory cancers was significantly higher than expected (5 observed vs. 

0.8 expected, SMR = 6.10, 95% CI = 2.23–13.51). 
 DRAFT - DO NOT CITE OR QUOTE 80 

Table 4-11. Distribution of select mortalities among AN-exposed and 

unexposed workers 

 Exposure level 

Cause of death High Possible Little or none Total 

 Oa Ea SMR Oa E

a

 SMR Oa Ea SMR Oa Ea SMR 

All causes 170 181.2 0.94 

(0.80–1.09)

97 124.7 0.78b

(0.63–

0.94) 

142 179.6 0.79b

(0.67–

0.93) 

409 485.5 0.84b

(0.76–0.93)

All cancers 58 50.1 1.16 

(0.89–1.49)

22 35.9 0.61b

(0.39–

0.91) 

41 51.1 0.80 

(0.58–

1.08) 

121 137.1 0.88 

(0.74–1.05)

Lung, tracheal, 

bronchial 

cancer 

27 19.1 1.41 

(0.95–2.03)

7 13.3 0.52 

(0.23–

1.04) 

19 19.1 0.99 

(0.62–

1.52) 

53 51.5 1.03 

(0.78–1.34)

Stomach 

cancerc

7 4.2 1.66 

(0.73–3.30)

3 2.9 1.03 

(0.26–

2.81) 

1 4.3 0.23 

(0.01–

1.15) 

11 11.4 0.96 

(0.51–1.68)

Circulatory 

disease 

81 86.9 0.93 

(0.74–1.15)

49 59.1 0.83 

(0.62–

1.09) 

70 86.2 0.81 

(0.64–

1.02) 

200 232.2 0.86b

(0.75–0.99)

aO = observed deaths; E = expected deaths. 

b

Statistically significant (p < 0.05). 

c

Statistically significant trend (p < 0.05). 

Source: Amended from Benn and Osborne (1998). 

Data were also analyzed by stratifying by year of first exposure, time since first exposure, 

and length of exposure. The latter variables were divided into the following groups: <5, 5–10, 

10–15, and >15 years. When cause-specific deaths, including all cancers and respiratory 

cancers, were examined within these categories, no significant differences were noted between 

observed and expected values. However, a significant increasing trend was noted for all deaths 

and circulatory diseases based on time since first exposure but not with length of exposure. The 

analysis that focused on cause-specific mortality and the year of first exposure differed from the 

previous study by Werner and Carter (1981) in that workers were divided into the following 

three groups: pre-1960, 1960–1968, and post-1968. No differences in all-cause or cancer deaths 

were noted between the observed and expected values, but a significant increase in respiratory 

cancer deaths was noted in the subgroup of workers that were exposed post-1968 (7 observed 

deaths vs. 2.6 expected deaths, SMR = 2.70, 95% CI = 1.18–5.32). 

This study increased the number of observed deaths sixfold as compared with the number 

of deaths reported in the previous study by Werner and Carter (1981). The number of cancer 

deaths, including deaths from lung cancer, also rose proportionally. However, the number of 

observed deaths only represented less than 15% of the studied cohort and thus may have 

contributed to not finding an overall statistically significant association between lung cancer and 
 DRAFT - DO NOT CITE OR QUOTE 81 

exposure to AN. As seen in the initial study, cancers of the trachea, bronchus, and lung 

(respiratory cancers) were elevated in the youngest age group. While significant, this statistic 

was based on five subjects in the younger age group. Also noted was the fact that there was a 

significant elevation of deaths from cancers of the trachea, bronchus, and lung in the workers 

who were first exposed in 1969 and later, rather than those first exposed prior to that year. 

Smoking history, an important confounder when assessing cause-specific lung cancer, was not 

addressed. The analyses on the high-exposure group included fewer than 800 workers from the 

total cohort; therefore, power to detect trends and excess deaths was limited in this part of the 

publication. Although not statistically significant, an increased SMR for lung, tracheal, and 

bronchial cancers was observed in the high exposure group (SMR = 1.41, 95% CI = 0.95–2.03, 

n = 27). The finding of an increase in stomach cancer in the high exposure group is interesting, 

but the small total number of stomach cancer deaths (n = 11) makes rigorous analysis difficult. 

This study had no quantitative AN levels, use of a population reference group could have 

masked associations, and statistical power needed to detect rare cancers such as stomach cancer 

was low. There was no evidence of a dose-related trend between increasing AN exposure and 

respiratory cancer, which is not surprising given study deficiencies and the lack of quantitative 

exposure data. 

Acrylic fiber factory in Italy 

A retrospective cohort study was conducted with 671 male workers who had at least 

12 months of exposure to AN (or mixed exposure to AN and dimethylacetamide) at an acrylic 

fiber factory in Venezia, Italy (Mastrangelo et al., 1993). Mortality patterns were examined to 

determine whether excess cancer cases were related to these exposures. Occupational exposure 

to AN occurred between 1959 and the end of 1988, with mortality tracked until the end of 1990, 

thus allowing at least 2 years of follow-up for every person in the cohort. Workers with past 

exposure to vinyl chloride or benzidine were excluded from the study cohort. Study participants 

were categorized based on their level of AN exposure as follows: (1) high exposure to AN only, 

(2) low exposure to AN plus exposure to dimethylacetamide, and (3) episodic exposure to AN 

plus exposure to dimethylacetamide. SMRs were calculated based on the observed deaths and 

the expected number of deaths in the general population. The expected death rate took into 

account age, gender, year, cause, and person-time. 

No significant difference in all-cause mortality was observed during 1959–1990, with 

only 32 deaths (4.7% of total cohort) being reported. A total of 12 deaths from cancer was 

observed in the total cohort. This observation was slightly, but not significantly, higher than the 

8.73 expected cancer deaths. None of these cancer deaths was observed among the 100 workers 

who were only exposed to high levels of AN. Of the 12 cancer cases, there were 2 lung cancer 

cases and 4 intestinal cancer cases. The lung cancer cases were observed among the 272 workers 

who had discontinuous but episodic exposure to AN and dimethylacetamide, and the number was 
 DRAFT - DO NOT CITE OR QUOTE 82 

not significantly different than the expected number of lung cancer cases. The intestinal and 

colon cancer cases were equally distributed between the groups that had concomitant exposure to 

dimethylacetamide and were significantly higher than expected in both groups. 

When analyses were stratified by duration of exposure and time since first exposure, no 

relationship was found with regard to all-cause mortality or all cancers. Among individuals 

exposed for 1–4 years, significant differences were noted between the number of observed 

testicular, rectal, intestinal, and colon cancer deaths and the expected values. However, the 

number of cancer-specific deaths was small, with only one or two deaths being attributed to the 

above cancer types. 

In addition to questions about the comparison group, the ability of this study to greatly 

inform an assessment of the relationship between AN and cancer is quite limited due to its small 

sample size. The follow-up time is also short, as reflected by the fact that less than 5% of the 

cohort was deceased by the end of the follow-up period. These factors combined may contribute 

to the study’s lack of sufficient power to determine if AN exposure is associated with cancer. 

National Cancer Institute (NCI) cohort study 

 Many studies have investigated the relationship between AN exposure and cause-specific 

death using a cohort assembled by the NCI (Starr et al., 2004; Marsh et al., 2001, 1999; Blair et 

al., 1998). The studies were found to differ by the types of analyses used, comparison groups, 

cohort subsets, or years of follow-up. 

Blair et al. (1998) assembled a cohort of 25,460 workers (18,079 white males, 

4,293 white females, 2,191 nonwhite males, and 897 nonwhite females) who were employed in 

AN production or use beginning in the 1950s through 1983. The cohort included workers who 

were employed prior to 1984 and after the start-up of AN operations (between 1952 and 1965) at 

one of eight plants located in Alabama, Florida, Louisiana, Ohio, Texas, and Virginia. This 

method allowed for the examination of both AN-exposed workers and unexposed workers. 

Workers were followed through the end of 1989, allowing ≥6 years of follow-up. 

Exposure was assessed for each plant by developing a quantitative estimate for each job, 

department, and time period. Sources used to develop the estimates were walk-through surveys, 

personal and area monitoring data, and interviews with longtime workers. The exposure 

assessment for this study was more detailed (Stewart et al., 1998) than for any previously 

published study. More than 10,000 estimates were developed for 3,662 job, department, and 

plant combinations for a 30-year period of time. Individual worker exposure estimates were 

developed, including estimates for workers whose exposures were difficult to estimate because 

of their movement through all areas of a plant (i.e., maintenance workers). The estimation 

methods were compared with actual data for validation. 

SMR analyses were performed to compare observed mortality in both the exposed and 

unexposed groups to expected numbers of deaths based on U.S. race- and gender-specific death 
 DRAFT - DO NOT CITE OR QUOTE 83 

rates. Subsequent analyses used the unexposed worker rates to develop internal comparison rate 

ratios adjusted for birth year, plant, calendar time, race, gender, wage, and salary status. These 

comparisons alleviate the healthy worker effect that is expected when using external general 

population rates. Smoking history was obtained on a sample of workers by using a case-cohort 

design to allow statistical adjustment for risk estimates calculated for known smoking-related 

cancers, such as lung cancer. A 10% sample of living workers was chosen at random to be 

interviewed regarding their smoking history. A 10% sample of persons deceased prior to 

1983 was chosen, and next-of-kin interviews were attempted. Also, all brain and lung cancer 

deaths that were not chosen in the 10% sample of deceased persons were also selected for nextof-kin interview. 

At the end of the study, the total person-years for the exposed workers was 

348,642, while the person-years for the unexposed workers tallied 196,727. More than 66% of 

the members of the cohort had at least 20 years of follow-up. A total of 1,217 exposed workers 

and 702 unexposed workers were known to be deceased. For all-cause mortality, significant 

lower numbers of observed deaths than expected were reported for both AN-exposed and 

unexposed groups (Table 4-12). This pattern is also noted for all-cancer mortality among 

exposed workers; however, no statistically significant difference between observed and expected 

deaths was found among the unexposed workers. A similar observation was made for lung and 

tracheal cancer death, with SMR values for AN-exposed and unexposed workers being 0.9 (95% 

CI = 0.8–1.1) and 0.8 (95% CI = 0.6–1.1), respectively (Table 4-12). Interestingly, among the 

exposed workers, the numbers of observed deaths from pancreatic cancer, lymphosarcoma, and 

reticulosarcoma, as well as noncancer deaths like diabetes, cerebrovascular disease, and liver 

cirrhosis, were significantly lower than expected values. Upon comparison of the exposed 

workers to the unexposed workers, a small excess in lung and tracheal cancer deaths was 

observed (see RR in Table 4-12). 

Table 4-12. Distribution of select mortalities among AN-exposed and 

unexposed workers 

Exposed workers Unexposed workers 

Cause of death Observed SMR 95% CI Observed SMR 95% CI 

RR 

(95% CI) 

All causes 1,217 0.7 0.6–0.7a 702 0.7 0.7–0.8a 0.9 (0.8–1.0)

All cancers 326 0.8 0.7–0.9a 216 0.9 0.8–1.0 0.8 (0.7–1.0)

Lung and tracheal cancer 134 0.9 0.8–1.1 59 0.8 0.6–1.1 1.2 (0.9–1.6)

Pancreatic cancer 10 0.5 0.3–0.9a 13 1.2 0.7–2.1 0.4 (0.2–1.0)

Cerebrovascular disease 37 0.5 0.4–0.7a 23 0.5 0.4–0.8a 0.9 (0.5–1.6)

a

Statistically significant (p < 0.05). 

Source: Amended from Blair et al. (1998). 
 DRAFT - DO NOT CITE OR QUOTE 84 

Data were stratified by time since first exposure (<10, ≥10–20, and ≥20 years) to examine 

any evidence of latency effects. Using the unexposed group for comparison, no significant 

increases in cancer deaths were observed among AN exposed workers in any of the latency 

intervals examined. The RRs for lung cancer mortality were increased for the longer latency 

periods; however, these RRs and the overall trend were not statistically significant. The RRs 

were 0.4, 1.6, and 1.3 in the <10-years exposure group, the ≥10–20-years group, and the 

≥20 years group, respectively. 

Cumulative exposure was examined by stratifying the data into five exposure groups: 

<0.13, ≥0.13–0.57, ≥0.57–1.5, ≥1.5–8.0, and ≥8.0 ppm-years. There was no evidence of a doseresponse effect across the quintiles of exposure when death rates for all cancers combined were 

examined. Similarly, lung cancer death rates did not increase across the exposure categories 

with rate ratios of 1.1, 1.3, 1.2, 1.0, and 1.5, respectively. A sufficient number of lung cancer 

deaths were available to analyze the relationship between latency and cumulative exposure. 

Among the lung cancer deaths that occurred within 10 years since first exposure to AN, there 

was no significant increase in deaths with increasing exposure. This observation is also noted for 

lung cancer deaths occurring 11–19 years after first exposure to AN. For the workers with 

≥20 years since first exposure, a statistically significant rate ratio of 2.1 (95% CI = 1.2–3.8) was 

reported in the highest cumulative exposure quintile; however, there was not a significant 

exposure-response trend (p = 0.11). 

The risk of lung cancer mortality was also analyzed by other exposure variables, 

including duration, intensity, frequency of peak exposures, and cumulative exposures, 

considering different lag periods and adjustment factors. Most exposure variables showed a 

nonsignificant increase in lung cancer deaths among workers with the highest level of AN 

exposure, but none yielded a strong exposure-response gradient or statistically significant 

exposure-response trend. No exposure-response patterns were observed for duration of exposure 

at any intensity level. 

Additional analyses focused on the workers with 20 or more years since first exposure in 

order to examine the factors that might contribute to increased risk of lung cancer at the highest 

cumulative exposure level in this group. The increased risk was not observed when analyses 

were restricted to workers first employed between 1960 and 1969. This could be because 

workers who were first employed between 1960 and 1969 would have at least 10 fewer years of 

follow-up than those hired before 1960 and would tend to be younger. Also, having a later hire 

date would allow workers in this group less time to work and accumulate exposure, so they 

would be less likely to be included in the highest quintiles of exposure. This is confirmed by the 

fact that 42 lung cancer cases were observed in the two highest quintiles for those first hired 

before 1960, and 9 were observed in the two highest quintiles for those first hired between 

1960 and 1969. The increase in risk in the highest exposure quintile was evident in both wage 

and salary employees and for both fiber and nonfiber plants for this group that was followed for 
 DRAFT - DO NOT CITE OR QUOTE 85 

20 or more years after first exposure. None of the trend tests for cumulative exposure in workers 

with 20 or more years since first exposure was significant. 

Smoking history was sought on a 10% sample of study subjects. A total of 2,655 workers 

was identified for interview, and 1,890 (71%) of this group were interviewed. For lung cancer 

deaths, 64 next-of-kin interviews were conducted. Additional analyses were performed by 

controlling for smoking status. These analyses did not change previous results, although they did 

result in a slight reduction in the risk ratios in the highest quintile of exposure. Blair et al. (1998) 

stated that they assumed that if smoking data were available for the full cohort, then the smoking 

adjustment would yield the same proportion of effects in the full cohort as in the subcohort. 

In summary, the sample size and follow-up time in this study were likely large enough to 

detect any substantial elevation of cause-specific cancer deaths. For lung and tracheal cancer 

deaths, an elevated RR of 1.2 (95% CI = 0.9–1.6) was observed in AN-exposed workers 

compared to the unexposed worker population. With lung cancer deaths as the surrogate for the 

development of lung cancer and less than 10% of the worker population being deceased at the 

time of the study evaluation, lung cancer risk may have been underestimated. The study authors 

state that increased risk with latency or cumulative exposure in separate analyses was not 

demonstrated. This observation could be attributable to the reduced level of power in the 

subgroup analyses. However, a statistically significant RR of 2.1 (95% CI = 1.2–3.81) was 

observed in the highest cumulative exposure quintile among workers with ≥20 years since first 

exposure. Overall, this study provides suggestive evidence with regard to AN exposure and lung 

cancer. 

Marsh et al. (1999) added 7 years of follow-up and focused on analyzing a subset of the 

original cohort of Blair et al. (1998). The subcohort was comprised of 992 white male workers 

who had worked for ≥3 months between 1960 and 1996 at a chemical plant in Ohio. Analyses 

included the calculation of SMRs and RRs for categories of exposure and latency for lung cancer 

and the calculation of SMRs (based on regional mortality rates) and RRs for stomach, prostate, 

large intestine, and lymphohematopoietic cancers by cumulative exposure level. 

Exposure assessment in this cohort mirrored that of the original cohort study by Blair et 

al. (1998) with the following modifications. A panel of industrial hygienists used all of the 

exposure data collected to assign calendar time-specific categories to each job title. The 

following categories were designated: <0.2, ≥0.2–2.0, 2.1–20.0, and >20.0 ppm. Job titles were 

also assessed for the potential for exposure to nitrogen products in a qualitative manner 

(potential, no potential). Marsh et al. (1999) mentioned that other known potential occupational 

hazards at the plant included asbestos, 1,3-butadiene, and depleted uranium; exposure to these 

chemicals was not assessed. However, in the exposure assessment by Stewart et al. (1998) on 

this cohort, these chemicals were not singled out as impactful potential occupational hazards. 

For AN exposure, the quantitative evaluations for each job title were used to compute three timedependent measures of exposure for each worker who held any job where AN exposure was 
 DRAFT - DO NOT CITE OR QUOTE 86 

possible. These measures included duration of exposure, cumulative exposure, and average 

intensity of exposure. Cumulative exposure was recorded in ppm-years, with workers being 

assigned to one of the following categories: >0–0.139, 0.14–0.579, 0.58–1.509, 1.51–

7.999 ppm-years, and ≥8.000 ppm-years. Unlike the study by Blair et al. (1998), which 

measured person-year accumulation from the first day of employment at the plant to the end of 

1989 or date of death or last date known to be alive, Marsh et al. (1999) extended their 1960–

1988 job exposure matrix to include new job categories and monitoring data through 1996. 

Thus, the exposure assessment by Marsh et al. (1999) covers all jobs held from the beginning of 

the plant operation (1960) through the end of 1996.

The total cohort of 992 workers included 474 workers who never worked in a job where 

AN exposure was possible and 518 workers who were potentially exposed to AN in at least one 

of their jobs. A total of 110 deaths was observed in the cohort through the end of 1996. 

Smoking history was collected for 90.3% of the total cohort and 93.2% of the AN-exposed 

group. The prevalence of smokers was similar between the two groups with 58% of the 

unexposed workers being smokers and 62.5% of the exposed workers being smokers. However, 

the prevalence of smoking in the exposed group was associated with the level of cumulative AN 

exposure and increased with increasing levels of exposure. 

Of the 110 deaths observed, 43 deaths were attributed to cancer. The observed number of 

cancer deaths did not differ from expected values based on the U.S. mortality rates or the 

regional death rates, with SMRs of 0.98 (95% CI = 0.71–1.32) and 0.97 (95% CI = 0.70–1.31), 

respectively. Fifteen of the observed cancer deaths were attributed to respiratory cancers, which 

showed a similar pattern of nonsignificant SMRs <1 (Table 4-13). With the exception of bladder 

tumors, none of the other site-specific cancers evaluated showed a significant difference between 

observed and expected values using either the U.S. mortality rates or the regional mortality rates. 

The number of bladder cancer deaths among workers was significantly higher than expected 

(SMR = 4.5, 95% CI = 1.23–11.53); however, all the deaths occurred among workers not 

exposed to AN. 
 DRAFT - DO NOT CITE OR QUOTE 87 

Table 4-13. Distribution of mortality among AN-exposed workers 

Exposed workers Unexposed workers Overall cohort 

Cause of death Ob 

SMR 

(95% CI) Ob 

SMR 

(95% CI) Ob 

SMRUS

(95% CI) 

SMRregional

(95% CI) 

RR 

(95% CI) 

All causes 41 0.58a

0.42–0.79 

69 0.78b

0.60–0.98 

110 0.64a 

0.53–0.77 

0.69a

0.57–0.83 

0.74 

0.5–1.1 

All cancers 17 0.88 

0.52–1.42 

26 1.04 

0.68–1.53 

43 0.98 

0.71–1.32 

0.97 

0.70–1.31 

0.87 

0.4–1.7 

Respiratory 

cancer 

9 1.28 

0.58–2.42 

6 0.64 

0.24–1.40 

15 0.88 

0.49–1.43 

0.92 

0.51–1.51 

1.98 

0.6–6.9 

Bladder and 

other urinary 

cancer 

0 – 

0.00–8.23 

4 7.01a

1.91–17.96 

4 4.50a

1.23–11.53 

3.93a

1.07–10.06 

Not 

determined

a

Statistically significant (p < 0.05). 

Ob = observed deaths 

Source: Amended from Marsh et al. (1999). 

For respiratory cancers, there were nine observed deaths in the exposed group and six in 

the unexposed group, leading to a risk ratio of 1.98 (95% CI = 0.6–6.9) (Table 4-13). This 

indicates that there was nearly 2 times the rate of lung cancer deaths in the exposed group as in 

the unexposed group. Respiratory cancer deaths were further examined using RR regression 

models that were able to adjust for age and calendar time as well as one other potential 

confounding factor, such as year of hire or smoking. Two variables were marginally associated 

with lung cancer risk in the total cohort (exposed and unexposed workers): duration of 

employment and time since first exposure. Smoking was not related to lung cancer risk; 

therefore, it is probable that there was misclassification of this risk variable, and use of smoking 

information in models of time-related exposure variables to control for a smoking effect was not 

possible. Regression analyses performed using categories of duration of exposure, cumulative 

exposure, and average exposure compared to no exposure were not more informative than 

previous analyses that compared exposed to unexposed rates. For each analysis, the exposed 

worker RR was approximately 2 times that for unexposed workers across all categories of 

exposure (Table 4-14). The risk ratios, derived in the regression analysis, increased with 

exposure level and time since first exposure, though the small numbers of observed deaths may 

have hindered the observation of a statistically significant increasing trend. 
 DRAFT - DO NOT CITE OR QUOTE 88 

Table 4-14. Summary of relative regression analyses for cancer of the 

bronchus, trachea, and lung 

Exposure measure Category Observed deaths RR 95% CI

Unexposed 6 1.00 

>0–4.9 3 1.71 0.25–8.94 

5.0–13.9 3 2.28 0.35–11.38 

Duration (yrs) 

14.0+ 3 2.15 0.34–10.70 

Unexposed 6 1.00 

>0–7.9 2 1.96 0.81–12.04 

Cumulative exposure 

(ppm-yrs) 

8.0+ 7 2.07 0.58–7.58 

Unexposed 6 1.00 

>0–7.9 2 1.97 0.18–12.10 

8.0–109.9 4 2.15 0.43–9.33 

Cumulative exposure 

(ppm-yrs) 

110.0+ 3 1.97 0.31–9.42 

Unexposed 6 1.00 

>0–4.9 3 1.97 0.31–9.54 

5.0–11.9 3 1.70 0.26–8.26 

Average exposure (ppm) 

12.0+ 3 2.64 0.42–12.67 

Source: Amended from Marsh et al. (1999). 

The risk ratio for all-cancer mortality and AN exposure derived by Marsh et al. (1999) 

was similar to the risk ratio derived in the larger-scale study by Blair et al. (1998). Despite the 

limitations of the small number of observed deaths and the focus on only white males, this study 

does indicate that there may be an association between AN exposure and increased risk in 

respiratory cancer deaths. 

Marsh et al. (2001) performed a sensitivity analysis on data from the original cohort of 

Blair et al. (1998), examining dependency of lung cancer RR estimates on selection of referent 

populations. Exposure categorization from the Blair et al. (1998) study was retained for this 

analysis, but the comparison groups differed. Mortality analyses were performed using U.S. 

mortality rates and local county rates. SMRs were calculated for both AN-exposed and 

unexposed workers. 

Upon comparison with U.S. and regional mortality rates, both exposed and unexposed 

workers were found to have significantly lower rates of all-cause mortality. Using the U.S. 

morality rates, the SMRs for the unexposed group and the exposed group were 0.75 (based on 

702 deaths, 95% CI = 0.7–0.8) and 0.66 (based on 1,217 deaths, 95% CI = 0.6–0.7), respectively. 

The SMRs for all-cause mortality utilizing regional rates were nearly identical to those using 

U.S. rates. Additionally, the number of lung cancer deaths observed among workers, both 

exposed and unexposed, was significantly lower than regional estimates, with SMRs for each 

group of workers being 0.74 (95% CI = 0.6–0.9) and 0.68 (95% CI = 0.5–0.9), respectively, 

compared with U.S. population rates. These findings indicate a potential healthy worker effect. 
 DRAFT - DO NOT CITE OR QUOTE 89 

Observed lung-cancer deaths were stratified by the cumulative exposure to AN and time since 

first exposure to derive RRs and regional-mortality-rate-based SMRs (Table 4-12). Workers 

with the highest cumulative exposures and at least 20 years of exposure were twice as likely to 

have lung cancer as unexposed workers (RR = 2.1, 95% C.I = 1.2–3.8). The numbers of 

observed and expected deaths in this highest exposure, longest duration category were about the 

same using external comparisons (SMR = 1.07, 95% CI = 0.7–1.6). This illustrates how the use 

of an external comparison population can mask an apparent association; the discrepancy is most 

likely attributable, at least in part, to the healthy worker effect. There was no evidence of a 

linear exposure-response relationship for lung cancer, based on the categories used to assess time 

since first exposure. SMRs in each category did appear to increase with increasing cumulative 

exposure category (Table 4-15). 

Table 4-15. Distribution of observed lung cancer deaths among AN-exposed 

workers, using regional rates for comparison 

Time since first exposure 

Less than 10 yrs 10–19 Yrs At least 20 yrs 

Cumulative 

exposure 

(ppm-yrs) Ob RR (CI) SMR (CI) Ob RR (CI) SMR (CI) Ob RR (CI) SMR (CI)

>0–0.13 7 0.4 

(0.2–1.2) 

0.72 

(0.3–1.5) 

9 0.5 

(0.5–3.2) 

0.71 

(0.3–1.4) 

11 1.1 

(0.6–2.2) 

0.56 

(0.3–1.0) 

0.13–0.57 3 0.4 

(0.1–1.4) 

0.63 

(0.1–1.8) 

12 2.6a

(1.2–5.7) 

1.18 

(0.6–2.1) 

11 1.0 

(0.6–2.2) 

0.57 

(0.3–1.0) 

0.57–1.50 2 0.4 

(0.1–1.6) 

0.70 

(0.1–2.5) 

10 2.0 

(0.9–4.8) 

1.01 

(0.5–1.8) 

16 1.2 

(0.5–2.1) 

0.71 

(0.4–1.2) 

1.50–8.00 2 0.4 

(0.1–2.0) 

0.87 

(0.1–3.1) 

7 1.2 

(0.5–3.1) 

0.66 

(0.3–1.4) 

18 1.2 

(0.6–2.2) 

0.61 

(0.4–1.0) 

≥8.00 1 0.4 

(0.1–3.1) 

0.81 

(0.02–4.5) 

4 0.9 

(0.3–1.2) 

0.54 

(0.2–1.4) 

21 2.1a

(1.2–3.8) 

1.07 

(0.7–1.6) 

a

Statistically significant (p < 0.05). 

Ob = observed deaths 

Source: Amended from Marsh et al. (2001). 

To look for plant-specific risks, the lung-cancer deaths in each of the eight study plants 

were analyzed separately by cumulative level of exposure. Only one plant showed an increased 

risk of lung-cancer deaths among the exposed workers, with the highest level of exposure (i.e., 

≥8 ppm-years) having an SMR of 2.68 (based on 10 deaths, 95% CI = 1.3–4.9). There was no 

comparison of process differences in the plants, thus raising uncertainty as to whether workers at 

this plant were exposed to other potential carcinogens or if these findings were due to chance. In 

addition, the small number of observed lung-cancer deaths in the plant-specific exposure 

categories lowers the level of power this study had to discern trends in SMRs that might provide 

more information on the association between AN exposure and cancer. 
 DRAFT - DO NOT CITE OR QUOTE 90 

In summary, Marsh et al. (2001) focused on external comparison groups rather than the 

available unexposed worker cohort. The use of an external comparison group, rather than a 

cohort more comparable to the exposed population (i.e., internal comparison group), may subject 

the relationship between exposure and lung cancer to biases such as the healthy worker effect. 

Internal comparison groups are generally preferred since they tend to be less influenced by the 

healthy worker effect, other sources of selection bias, and confounding (Checkoway et al., 1989). 

Marsh et al. (2001) mentioned potential occupational hazards such as asbestos, 1,3-butadiene, 

and depleted uranium not being assessed. Stewart et al. (1998) conducted an exposure 

assessment for the cohort of workers exposed to AN. Exposure to 340 substances other than AN 

was assessed qualitatively. 1,3-Butadiene and depleted uranium were not among the chemicals 

with exposures of >20,000 person-years. Additionally, Blair et al. (1998) did not observe any 

deaths from asbestosis or mesotheliomas, which would have been indicative of asbestos 

exposure. The reanalysis by Marsh et al. (2001), particularly the RR results, does support the 

association, found by Blair et al. (1998), between AN exposure and increased lung cancer 

mortality risk among workers with the highest exposure level, but the healthy worker effect, 

small sample sizes within subcategories, use of external controls, and short follow-up may limit 

the detection of stronger support for such an association. 

Data from this cohort were reanalyzed employing semiparametric Cox regression models 

with time-dependent covariates to estimate additional risk of death from lung cancer for several 

different AN occupational exposure scenarios (Starr et al., 2004). The “cumulative exposure 

estimate” was a time-dependent covariate, and “plant worked” was a time-independent covariate. 

The analysis focused on the largest race-sex group (18,079 white males) from the original Blair 

et al. (1998) study. The Cox models allowed for the calculation of the cumulative risk of dying 

from a disease by a certain age. The outcome measurement used was the risk of dying from lung 

cancer by age 70 years. Baseline rates were developed for the unexposed worker population and 

for three different AN exposure scenarios: (1) early intense exposure, (2) long moderate 

exposure, and (3) late intense exposure. All scenarios provided 50 ppm-years of cumulative 

exposure by age 55 years. The increased number of lung cancers per 1,000 workers that would 

develop by age 70 was calculated as 0.77–1.56, 0.74–1.50, and 0.68–1.56, respectively (the 

ranges reflect the use of different plant-specific baseline rates). The upper bound of additional 

risk was in the range of 7.5–15.1 per 1,000 workers with the upper bound on the exposure 

parameter being 0.0048 per ppm-working year. It is important to note that this study analysis did 

not control for smoking. Also, based on the extent of exposure misclassification, any exposureresponse association may have been underestimated. 

In summary, the study by Blair et al. (1998) reported an elevated risk of lung cancer 

deaths among AN-exposed workers as compared to the unexposed workers, particularly among 

workers in the highest cumulative exposure quintile with ≥20 years since first exposure (RR = 

2.1, 95% C.I. = 1.2–3.8). However, the short follow-up may have contributed to the study’s 
 DRAFT - DO NOT CITE OR QUOTE 91 

inability, overall, to demonstrate an increased risk associated with latency or cumulative 

exposure. Similar to Blair et al. (1998), Marsh et al. (1999) found an increased risk of lung 

cancer deaths among AN-exposed workers as compared to the unexposed workers, though the 

point estimate of 1.98 was not statistically significant. However, Marsh et al. (1999) only 

focused on a small subset of the NCI cohort. Though the small sample size and the study 

inclusion of only white males reduces the statistical power and generalizability of the study, the 

observation of the excess lung cancer risk in Marsh et al. (1999) does provide some weight with 

regard to hazard inferences. 

Marsh et al. (2001) utilized primarily an external comparison group and, while they 

provide better stability of comparison rates than internal controls as used by Blair et al. (1998), a 

limitation of external controls as the referent population is the risk of having potential 

associations masked by a healthy worker effect or other factors that may be more similar within 

an occupational cohort than between the cohort and the general population. The results from 

Marsh et al. (2001) indicate the presence of such an effect dampening the observation of an 

association between AN and cancer. 

Though the studies by Marsh et al. (2001) and Blair et al. (1998) have a relatively large 

cohort size, the number of observed deaths is small. These studies, though they rely on cancerspecific mortality ratios rather than cancer incidence as in the Wood et al. (1998) study, have 

several advantages to the Wood et al. (1998) study. The low SMR for overall mortality reported 

by Wood et al. (1998) suggests the potential presence of a number of biases, including the 

healthy worker effect, incomplete cohort identification, and incomplete ascertainment of the 

outcome measure. Furthermore, Blair et al. (1998) provide a better job exposure matrix than 

Wood et al. (1998). Although cancer incidence is typically preferred, mortality rates do serve as 

a good surrogate for incidence for some cancers like lung cancer. On the other hand, these 

mortality studies may miss associations with treatable cancers such as prostate cancer. 

The small percentage of deaths in the NCI cohort suggest a young mean age, which can 

impact statistical power. Thus, the observation of a statistically significant elevation in SMR 

among those with the longest latency and high cumulative exposure is noteworthy. Additional 

follow-up of this cohort may be useful to further assess the association between AN exposure 

and cancer suggested by the excess in lung cancer deaths that has been observed among workers 

exposed to high levels of AN. 

Case-control studies 

A large case-control study conducted in seven European countries investigated the 

association between occupational exposure to vinyl chloride, AN, and styrene and the risk of 

lung cancer (Scélo et al., 2004). The study included new cases of lung cancer occurring between 

1998 and 2002 in 15 centers in six Central and Eastern European countries and in Liverpool in 

the United Kingdom. Controls, consisting of subjects hospitalized in general public hospitals in 
 DRAFT - DO NOT CITE OR QUOTE 92 

the same areas as cases, were frequency matched to cases based on age and gender. Controls had 

to have been hospitalized within 3 months of diagnosis of the case and could not have cancer or 

any tobacco-related diseases. A total of 3,403 cases and 3,670 controls met the study inclusion 

criteria; after exclusions and refusals to participate, the final study group included 2,861 cases 

and 3,118 controls. 

In order to ascertain exposure and lifestyle information, such as tobacco consumption, 

each study participant was interviewed using a standard questionnaire. Exposure assessment was 

obtained from the work history portion of the questionnaire, where information was collected for 

each job held at ≥1 year. Experts evaluated the frequency and intensity of exposure to AN, 

among other agents, for each job held by each study subject. The following exposure models 

were constructed for analysis: (1) duration of exposure, (2) weighted duration of exposure 

(which considered both duration and frequency), and (3) cumulative exposure in ppm-years. 

Models included age, gender, center, tobacco consumption, and other occupational factors. 

A total of 10,555 jobs were held by the 2,861 study participants with lung cancer, and a 

total of 11,174 jobs were held by the 3,118 controls. AN exposure was associated with 48 jobs 

held by the cases and 26 jobs held by the controls. Thirty-nine of the 2,861 cases and 20 of the 

3,118 controls were characterized as being exposed to AN, resulting in a significant odds ratio 

(OR) of 2.20 (95% CI = 1.11–4.36) (i.e., cases were 2 times more likely to be exposed to AN 

than controls). However, it was found that more than half of the study participants that were 

exposed to AN were also exposed to styrene. Further analysis was conducted on individuals not 

exposed to styrene (17 cases and 10 controls). This resulted in a similar OR estimate but with a 

wider CI due to the smaller sample size (OR = 2.08, 95% CI = 0.82–5.27). Increasing linear 

trends for lung cancer were noted for both weighted duration of exposure (p = 0.05) and 

cumulative exposure (p = 0.06) (Table 4-16). Additional analyses employed a 20-year lag for 

exposures, which did not change the results appreciably. The authors reported an increased risk 

of exposure among lung cancer cases diagnosed before the age of 60 (43% of the cases), where 

the OR for ever being exposed was 2.79 (95% CI = 1.01–7.70), while the OR for ever being 

exposed among those over 60 years was 1.02 (95% CI = 0.35–2.92). An age-exposure 

interaction test yielded nonsignificant results. 
 DRAFT - DO NOT CITE OR QUOTE 93 

Table 4-16. ORs of lung cancer for AN exposure 

Exposure measure Cases Controls OR 95% CI 

Weighted duration of exposure (yrs) 

Not exposed 2,822 3,098 1.00 

0.01–1.00 13 9 2.03 0.72–5.73 

1.01–2.25 9 5 2.73 0.73–10.20 

>2.25 17 6 2.91 0.87–9.79 

Linear trend: p = 0.05

Cumulative exposure (ppm-yrs) 

Not exposed 2,822 3,098 1.00 

0.01–0.46 13 9 2.03 0.72–5.73 

0.47–1.61 10 4 2.76 0.68–11.22 

>1.61 16 7 2.87 0.85–9.66 

Linear trend: p = 0.06

Source: Amended from Scélo et al. (2004).

Because of the personal interviews conducted with each case and control, this study was 

able to provide an in-depth assessment of potential confounding factors, such as smoking history 

and lifestyle factors. The exposure assessment, though different than for the recent generation of 

cohort studies where actual plant measurements were possible, utilized reasonable and 

standardized methods to assign various levels of AN exposure to different jobs. As a multiindustry study, the possibility of exposure misclassification in this study was probably greater 

than in single-industry studies, though exposure misclassification is probably nondifferential 

with respect to disease and therefore would serve to lessen the outcome measures (ORs) 

calculated. The key observation in this study is the fact that, even after adjustment for 

confounding factors such as smoking history, an association between AN exposure and lung 

cancer incidence was observed. This observation adds to the weight of evidence in support of an 

association between AN and cancer. 

Cross-sectional studies 

A detailed cross-sectional study was conducted among workers at a Hungarian AN 

factory in June 2000 (Czeizel et al., 2004). Of the 888 employees, 72 employees did not work 

during the study time frame and 33 refused to participate. The remaining 783 employees were 

interviewed, with information gathered on demographics, lifestyle and habits, occupational 

exposures, and history of general and occupational diseases, among other factors. Medical 

records aided in the validation of the workers’ responses. Workers were categorized into three 

groups based on level of contact with AN (i.e., direct exposure, indirect or sporadic exposure, 

and no exposure). Since the interviews were done with living current workers, cancer 
 DRAFT - DO NOT CITE OR QUOTE 94 

information for any worker who had left the plant or died before the study was conducted was 

anecdotal. 

It is known that 12 former workers from the factory had died from cancer between 

1990 and 1999, and none of these deaths was due to lung cancer. Of the 783 workers 

interviewed, 12 workers were found in the interview sample that had cancer. Of these, only one 

lung-cancer case was identified. This worker, categorized as having direct exposure to AN, 

started working at the plant in 1973 and was diagnosed 15 years later. Five of the 12 cancer 

cases were among the group (n = 452) thought to have the highest level of exposure to AN, while 

4 cancer cases were noted among workers with no exposure to AN. No significant association 

between AN exposure and the development of cancer was observed. The study mentioned three 

of its shortcomings: persons with serious disorders who died or had premature pensions were 

not included, updated information on occupational exposures was unavailable, and there was 

difficulty in identifying appropriate controls. It should be noted that workers were not exposed 

exclusively to AN but to a mixture of other chemicals as well. The small number of cancer 

incidences and the identified shortcomings hinder the reliability of this study in evaluating the 

association between AN exposure and the development of cancer. 

Other supporting studies

In 2006, the Ohio Department of Health assessed the burden of cancer among residents of 

Addyston, Hamilton County, Ohio, who lived near a thermoplastics manufacturing plant that 

emitted AN and 1,3-butadiene into the environment (Ohio Department of Health, 2006). The 

study population consisted of invasive cancer cases identified through the Ohio Cancer Incidence 

Surveillance System between 1996 and 2003. The incidence of site-specific cancer was 

compared to the expected number of cases, the latter being derived from national background 

cancer incidence rates from NCI’s Surveillance, Epidemiology and End Results (SEER) program 

in 1998–2002 and region-specific cancer incidence rates from 1993 to 2003. A total of 

55 invasive cancer cases were identified among the 1,010 residents in the area, with an SIR = 1.8 

(95% C.I. = 1.3–2.3) based on the 1998–2002 SEER age-specific incidence rates. Cancer of the 

lung and bronchus was the most common cancer identified (13 cases, 23.6%), followed by 

colorectal cancer (10 cases, 18.2%). The number of observed cancer cases in both instances was 

higher than expected (lung and bronchus SIR = 3.2, 95% C.I. = 1.7–5.4; colon and rectum SIR = 

3.0, 95% C.I. = 1.5–5.6). SIRs based on the region-specific cancer incidence yielded similar 

results. Although cancer incidence in this cohort was higher than expected, the association 

between AN exposure and the incidence of lung cancer may be confounded by other risk factors, 

such as smoking, that were acknowledged but not controlled in the analyses. 
 DRAFT - DO NOT CITE OR QUOTE 95 

Overall summary of epidemiology data 

The early DuPont studies found potential increases in incidence and/or death from lung 

cancer and prostate cancer among persons possibly exposed to AN. These studies were the 

impetus for generating several additional studies spanning more than 20 years after the first 

publication. Exposure assessment was not fully explored until recently, though older studies did 

examine qualitative distributions of exposure. The cohorts ranged from a few hundred workers 

to over 25,000 workers. The follow-up period for many of the studies was short, not allowing 

half of the population to reach a terminal endpoint so that a health outcome such as cancer could 

be observed. However, over time, the cohort studies increased in power by increasing the 

number of workers, length of follow-up, and sophistication of the exposure assessment. 

A composite of the major cohort studies reviewed, along with all-cancer SMRs, is 

provided in Table 4-17. Table 4-18 summarizes SMRs for lung cancer, a cancer type that has 

been assessed in most of the epidemiology studies reviewed. In both tables, the SMRs are based 

on the cohort population most likely to be exposed to AN, as the actual cohort sample size in 

many cases included an unexposed worker group. As in most studies, the number of deaths on 

which the SMRs are based is a fraction (≤33%) of the actual cohort studied; thus, the actual

cohort size may not reflect the relative number of deaths in the SMR calculation. These SMRs 

were evaluated by the size of the exposed cohort, number of observed deaths, percentage of 

observed deaths within each study, and year of publication to determine if any of these factors 

was associated with increased SMR values. For both all-cancer mortality and lung-cancer 

mortality, no discernable association was observed between increased SMRs and the size of the 

exposed cohort, number of observed deaths, percentage of observed deaths within each study, or 

year of publication (data not shown). 
96 DRAFT - DO NO

Table 4-17. Derived all-cancer SMRs for major cohort studies on AN exposure 

Reference Study population Comparison group 

Potentially exposed 

cohort 

DuPont 

O’Berg (1980) Male workers exposed to AN between 1950 and 1966 at a 

DuPont Plant in South Carolina and followed through 1976. 

DuPont Registry 1,128

b 

O’Berg et al. (1985) As above but updated extended to 1983 DuPont Registry 1,345 Chen et al. (1987) Male workers exposed to AN between 1944 and 1970 at 

DuPont Plant in Virginia and followed through 1983.

White male subset of U.S. population 

1,083 

Chen et al. (1987) As above. DuPont Registry 1,083 Wood et al. (1998) Combined O’Berg et al. (1985) and Chen et al. (1987) U.S. general population 2,559 Wood et al. (1998) As above. DuPont Registry 2,559 Symons et al. (2008) Update from Wood et al. (1998) with 11 yrs of follow-up Regional Dupont workers 2,548 Symons et al. (2008) As above. U.S. general population 2,548 

NCI 

Blair et al. (1998) Workers employed in eight AN-producing facilities from 

1950s to 1983, followed through 1989. 

U.S. general population 25,460 

Blair et al. (1998) As above. Unexposed workers 25,460 Marsh et al. (1999) Subset of Blair et al. (1998). County mortality rates 518 Marsh et al. (1999) As above. Unexposed workers 518 Marsh et al. (2001) Same as Blair et al. (1998) Regional mortality rates 25,460 

American Cyanamid Company 

Collins et al. (1989) Male workers at two plants employed between 1951 to 1973, 

followed through1983. 

White male subset of U.S. population 

1,774 

Synthetic chemical plant 

Waxweiler et al. (1981) Chemical plant workers employed between 1942 and 1973, 

followed through 1973. 

White male subset of U.S. population 

4,806 
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Table 4-17. Derived all-cancer SMRs for major cohort studies on AN exposure 

Reference Study population Comparison group 

Potentially exposed 

cohort 

Table 4-17. Derived all-cancer SMRs for major cohort studies on AN exposure 

Reference Study population Comparison group 

Potentially 

exposed cohort 

Rubber industry 

Delzell and Monson (1982) White male rubber chemical plant workers employed for at 

least 2 yrs between 1940 and mid-1971, followed through mid-1978. 

White male subset of U.S. population 

327 

Netherlands cohort 

Swaen et al. (1992) Male workers exposed to AN in eight factories for 

≥6 mos 

before mid-1979, followed through 1987. 

Dutch general population 2,842 

Swaen et al. (1998) As above, but followed through 1995. Dutch general population 2,842 Swaen et al. (2004) As above, but followed through 2000. Dutch general population 2,842 

BASF (Germany) 

Thiess et al. (1980) Male workers from 12 plants followed through mid-1978. German mortality rates 1,469 

Six factories (U.K.) 

Werner and Carter (1981) Male workers employed for at least 1 yr in one of six 

factories from 1950 to 1968, followed through 1978.

Male mortality rates in England and Wales 

934 

Benn and Osborne (1998) As above but employed from 1969 to 1978, followed through 

1991. 

Mortality rates from different European countries 

2,963 

Acrylic fiber factory (Italy) 

Mastrangelo et al. (1993) General population 671 aSMR may be calculated from article based on available data. bOnly workers employed for 

≥6 mos. 

cBased only on wage workers. dStatistically significant (p < 0.05). 
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Table 4-18. Derived lung cancer SMRs for major cohort studies on AN exposure 

Reference Study population Comparison group Potentially exposed cohort Obser

cance

 DuPont 

O’Berg (1980) Male workers exposed to AN between 1950 and 

1966 at a DuPont Plant in South Carolina and followed through 1976. 

DuPont Registry 1,128

b 

O’Berg et al. (1985) As above, but updated and extended to 1983. DuPont Registry 1,345 Chen et al. (1987) Male workers exposed to AN between 1944 and 

1970 at DuPont Plant in Virginia and followed through 1983. 

White male subset of U.S. population 

1,083 

Chen et al. (1987) As above. DuPont Registry 1,083 Wood et al. (1998) Combined O’Berg et al. (1985) and Chen et al. 

(1987). 

U.S. general population 2,559 

Wood et al. (1998) As above. DuPont Registry 2,559 Symons et al. (2008) Update from Wood et al. (1998) with 11 yrs of 

follow-up 

Regional Dupont workers 2,548 

Symons et al. (2008) As above. U.S. general population 2,548 

NCI 

Blair et al. (1998) Workers employed in eight AN-producing facilities 

from 1950s to1983, followed through 1989. 

U.S. general population 25,460 

Blair et al. (1998) As above. Unexposed workers 25,460 Marsh et al. (1999) Subset of Blair et al. (1998). County mortality rates 518 Marsh et al. (1999) As above. Unexposed workers 518 Marsh et al. (2001) Same as Blair et al. (1998). Regional mortality rates 25,460 

American Cyanamid Company 

Collins et al. (1989) Male workers at two plants employed between 

1951 and 1973, followed through 1983. 

White male subset of U.S. population 

1,774 
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Table 4-18. Derived lung cancer SMRs for major cohort studies on AN exposure 

Reference Study population Comparison group Potentially exposed cohort Obser

cance

Table 4-18. Derived lung cancer SMRs for major cohort studies on AN exposure 

Reference Study population Comparison group Potentially exposed cohort Obse

canc

 Synthetic chemical plant 

Waxweiler et al. (1981) Chemical plant workers employed between 1942 and 

1973, followed through 1973. 

White male subset of U.S. population 

4,806 

 Rubber industry 

Delzell and Monson (1982) 

White male rubber chemical plant workers employed for at least 2 yrs between 1940 and mid-1971, followed through mid-1978. 

White male subset of U.S. population 

327 

 Netherlands cohort 

Swaen et al. (1992) Male workers exposed to AN in eight factories for 

≥6 mos before mid-1979, followed through 1987. 

Dutch general population 2,842 

Swaen et al. (1998) As above, but followed through 1995. Dutch general population 2,842 Swaen et al. (2004) As above, but followed through 2000. Dutch general population 2,842 

BASF (Germany) 

Thiess et al. (1980) Male workers from 12 plants followed through mid1978. German mortality rates 1,469 

Six factories (U.K.) 

Werner and Carter (1981) Male workers employed for 

≥1 yr in one of six 

factories from 1950 to 1968, followed through 1978.

Male mortality rates in England and Wales 

934 

Benn and Osborne (1998) As above but employed from 1969 to 1978, followed 

through 1991. 

Mortality rates from different European countries 

2,963 

Acrylic fiber factory (Italy)

Mastrangelo et al. (1993) General population 671 aSMR may be calculated from article based on available data. bOnly workers employed for 

≥6 mos. 
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Table 4-18. Derived lung cancer SMRs for major cohort studies on AN exposure 

Reference Study population Comparison group Potentially exposed cohort Obser

cance

cBased only on wage workers. dStatistically significant (p < 0.05). 
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To date, the largest cohort assessed in determining the relationship between AN and 

cancer is the NCI cohort. The NCI/National Institute for Occupational Safety and Health 

(NIOSH) cohort study of Blair et al. (1998) provides the strongest evidence for carcinogenicity, 

although this evidence is not conclusive. This study of 25,460 subjects in eight plants was 

designed to evaluate a relationship between AN exposure and site-specific cancer, including lung 

cancer, an a priori hypothesis. Both AN-exposed and unexposed subjects showed a favorable 

all-cause mortality rate compared to the all-cause mortality rate of the U.S. population. 

Although only 5% of the cohort had died, this study has a large number of observed deaths that 

could be analyzed. The study addressed known problems occurring with earlier studies by 

quantifying exposures, estimating the effect of smoking, and using an internal control group of 

unexposed workers. 

The study by Blair et al. (1998) is of particular interest because a possible association 

between AN exposure and death from lung cancer was observed among workers in the highest 

level of AN exposure. Specifically, workers with at least 20 years since first exposure and 

exposed to a high level of AN were 2 times more likely to die of lung cancer than unexposed 

workers. However, though significance was found among workers exposed to high levels of 

AN, as with other studies, the exposure-response analysis in the Blair et al. (1998) study did not 

provide strong or consistent evidence for a causal association. 

The observations of Swaen et al. (2004) of AN-exposed workers in the Netherlands and 

of Benn and Osborne (1998) of AN-exposed workers in the United Kingdom support the 

findings of Blair et al. (1998) and provide some evidence for carcinogenicity, although lung 

cancer SMRs in these studies were not statistically significant. Other supporting evidence comes 

from the observation that SMRs for lung cancer among subjects with the highest exposure (as 

compared to national mortality rates) were not only >1, but also larger than the SMRs for low- or 

no-exposed groups. Furthermore, the statistically significant increased OR for AN exposure in 

the lung-cancer case control study of Scélo et al. (2004) provides weight for this association. 

This study adjusted for effects related to individual smoking history and to a number of potential 

coexposures found in a subject’s occupational setting. The finding of lung-cancer risk increasing 

with increasing exposure duration or with increasing cumulative exposure provides further 

evidence of an association with AN. 

Within the body of epidemiologic literature examining a potential relationship between 

exposure to AN and cancer in occupational cohorts, the following shortcomings are noted: low 

power from small numbers of exposed subjects, lack of quantitative exposure information on 

individual study subjects leading to a greater potential for exposure misclassification bias, 

assessment of an insensitive outcome, and insufficient follow-up period for cancer latency. In 

addition, many of the studies used external comparison groups, and their results were subject to a 

downward bias from the healthy worker effect. 
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 An alleged shortcoming of the Blair et al. (1998) study has been the observation that the 

AN-exposed workers experienced a lower rate of lung-cancer deaths than in the general 

population; however, this is likely a manifestation of the healthy worker effect. The use of 

internal controls by Blair et al. (1998) was to draw inferences about AN risks. With cancer 

mortality being used as a surrogate for developing cancer associated with AN exposure and with 

a low percentage of the cohort having died, there may be an underestimate of the risk associated 

with AN exposure. In addition, Selikoff and Seidman (1992) showed based on histopathological 

analysis of a comparably large industrial cohort (17,800 asbestos workers) that as much as 13.7% 

of lung cancer cases are misdiagnosed on death certificates, both as neoplasms and nonmalignant 

diseases, with about 3% as asbestos only diseases (mesothelioma and asbestosis). Therefore, 

Blair cohort may have as much as 10% of internal controls that are actually lung cancers. That 

would cause a strong bias against finding a statistically significant relationship. Finally,

mortality data may be inadequate for assessing treatable cancers that could result from AN 

exposure. The earlier studies based on the DuPont cohort utilized cancer incidence as well as 

cancer mortality data. In these studies, although a better outcome measurement (i.e., cancer 

incidence) is used, observed rates are compared through an SIR with company-wide or national 

population statistics rates, rather than rates from an internal control group. Thus, a strong 

healthy worker effect may hinder the observation of a cancer effect of AN exposure. Even in the 

most recent DuPont cohort study (Symons et al. 2008) where an attempt was made to reduce the 

bias due to healthy worker effect, there may be bias from the health worker effect. It should be 

noted that unlike the other DuPont cohort studies, Symons et al. (2008), with over 50 years of 

follow-up, did not report cancer incidence. Though the outcome measure of mortality in the 

Blair et al. (1998) study is not as sensitive, this study has a relatively large number of lungcancer deaths and does compare cause-specific deaths between exposed and unexposed workers 

as well as the general population. The resulting risk ratio may not achieve statistical significance 

(as mentioned above, several factors may have caused bias to the null), but the point estimate 

does indicate a potential excess in lung-cancer deaths among workers exposed to AN. 

Furthermore, the observed RR in the group of workers with the highest cumulative exposure and 

the longest time since first exposure was statistically significantly increased. 

4.1.2.2.2. Epidemiological studies of AN in humans (noncancer effects). Sakurai et al. (1978) 

performed a cross-sectional health examination of 102 male workers exposed to AN in six 

acrylic fiber manufacturing factories in Japan in 1976. Also examined were 62 nonexposed 

matched control workers from polyester fiber manufacturing plants, power supply plants, or 

finishing branches of the acrylic fiber plants. The workers were selected by a random sampling 

process. By experimental design, all exposed subjects were shift workers who had been exposed 

to AN in the workplace for at least 5 years but had no history of exposure to other chemicals. 

All subjects underwent medical examinations, and blood and urine samples were collected for 
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chemical analysis. Clinical chemistry analyses included urinary protein and other parameters, 

including Hb, total cholesterol, AST, ALT, alkaline phosphatase, cholinesterase, γ-glutamyl 

transpeptidase (γ-GTP), and lactate dehydrogenase (LDH). Parameters that measured liver 

injury were a focus of the clinical examinations because a previous epidemiological study of 

576 Japanese acrylic fiber manufacturing workers exposed to <5 or <20 ppm AN between 1960 

and 1970 had reported an increase in subjective symptoms and mild injury to the liver in exposed 

workers (Sakurai and Kusumoto, 1972). AN and thiocyanate concentrations in urine were also 

measured to evaluate individual exposure levels. 

 Levels of AN in the air (Sakurai et al., 1978) were measured as 8-hour TWA from “spot” 

samples (from stationary air samplers) and from exposed subjects wearing personal samplers. 

As shown in Table 4-19, the factories and exposed workers were classified into three groups (A, 

B, and C), according to their level of AN exposure. SDs for the means and ranges of the 

exposure concentrations were not reported. Mean exposure durations for workers in the three 

groups of factories were 10.3 years (SD = 4.5) for group A, 10.8 years (SD = 4.4) for group B, 

and 12.6 years (SD = 2.1) for group C. 

Table 4-19. Industrial AN exposure, levels of AN and thiocyanate in urine, 

and prevalence of physical signs of adverse effects in workers exposed to AN 

at six acrylic fiber factories in Japan 

Mean 8-hr TWA AN 

concentration (ppm) 

Percentage of exposed vs. control workers 

Factory with physical signs of adverse effects 

group 

(n = number 

of factories)

Spot 

samples 

Personal 

samples 

AN in urine 

(μg/L) 

Thiocyanate 

in urine 

(μg/L) 

Reddening of 

pharynx or 

conjunctiva 

Palpable 

liver 

Rashes or 

pigmentation 

of skin 

A (n = 2) 2.1 

(n = 116) 

0.1 

(n = 11) 

3.9 

(n = 35) 

4.50 

(n = 19) 

19.4 (n = 31) 

vs. 

18.2 (n = 22)

16.1 (n = 31) 

vs. 

9.1 (n = 22) 

9.7 (n = 31) 

vs. 

9.1 (n = 22) 

B (n = 3) 7.4 

(n = 394) 

0.5 

(n = 37) 

19.7 

(n = 51) 

5.78 

(n = 58) 

11.3 (n = 53) 

vs. 

10.0 (n = 30)

15.1 (n = 53) 

vs. 

10.0 (n = 30)

3.8 (n = 53) 

vs. 

0 (n = 30) 

C (n = 1) 14.1 

(n = 98) 

4.2 

(n = 14) 

359.6 

(n = 22) 

11.41 

(n = 14) 

50.0 (n = 18) 

vs. 

30.0 (n = 10)

38.9 (n = 18) 

vs. 

30.0 (n = 10)

11.0 (n = 18)

vs. 

0 (n = 10) 

Control – – 0 

(n = 22) 

4.00 

(n = 52) 

– – –

Source: Sakurai et al. (1978). 

 Although there were some differences in mean age between the groups (38.1 years for 

group C, 33.9 years for group B, and 30.5 years for group A), the age distributions of exposed 

and control subjects were broadly similar (Sakurai et al., 1978). No statistically significant 

differences in mean clinical chemistry parameters were found between exposed workers and 

controls. Medical histories of exposed workers and controls suggested a transient AN-related 
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increase in such symptoms as irritation of the conjunctiva and upper respiratory tract, runny 

nose, and skin irritation (for example, at the scrotum). Physical examination of subjects 

suggested a slight increase in the incidence of palpable liver, reddening of the conjunctiva and 

pharynx, and occurrence of skin rashes (see Table 4-19). However, the incidences of these 

findings among the groups did not rise to the level of statistical significance. Likewise, there 

were no AN-related changes in blood pressure or neurological findings. 

 EPA determined 4.2 ppm (average 8-hour TWA from the high exposure group) as an 

equivocal lowest-observed-adverse-effect level (LOAEL) for physical signs of eye or throat 

irritation, liver enlargement, or skin irritation in male workers with average durations of 10–

12 years of occupational exposure to airborne AN. Limitations to this LOAEL are that 

workplace air concentrations across the 10–12 years of exposure were not available, workers 

who underwent medical examinations were not necessarily the same as those whose air and urine 

were sampled, and no survey of self-reported symptoms was conducted. 

 A later study of Japanese acrylic fiber workers by some of the same investigators (Muto 

et al., 1992) included a survey of self-reported symptoms. A strength of the LOAEL is the 

concurrence between the urinary biomarkers of exposure and the measured air concentrations 

(see Table 4-19). 

 Muto et al. (1992) performed another cross-sectional health examination of male workers 

in seven Japanese acrylic fiber manufacturing plants in 1988. The seven factories included the 

six factories studied in the 1976 cross-sectional health examination of Japanese acrylic fiber 

workers (Sakurai et al., 1978). Exposed workers selected for the study were 157 male shift 

workers with at least 5 years of experience on production lines. The mean years of exposure for 

these workers was 17 ± 6.6 years. A nonexposed control group consisted of 537 male shift 

workers in polyester fiber plants, power supply plants, or finishing branches in the acrylic fiber 

plants. Controls were similar to exposed workers in average age (42.2 years, controls; 

41.9 years, exposed), percentage who drank alcohol (76.5%, controls; 77.1%, exposed), and 

percentage who smoked (58.1%, controls; 58.6%, exposed). Subjects underwent a medical 

examination that documented past illnesses, work history, exposure to AN, smoking and 

drinking habits, subjective symptoms, physical condition, urinalysis, hematology, liver function 

blood variables (total bilirubin, AST, ALT, and γ-GTP), and chest X-rays. Prevalences of 

workers with abnormal values for the medical examination parameters were analyzed 

statistically (protein, sugar, or urobilinogen in urine; blood specific gravity >1.055, Hb <14 g/dL, 

hematocrit >40%, and RBC count <103/mm3; and bilirubin >1.0 mg/dL, AST >40 enzyme 

activity units, ALT >35 units, and γ-GTP >80 units). Exposure of workers (reported as 8-hour 

TWA concentrations) was assessed by data from workplace area air samples and from personal 

air samples collected over a 2-day period for 142 of the 157 exposed workers. Overall, the mean 

AN exposure concentrations for the exposed workers were 0.53 ± 0.52 ppm (range, 0.01–

2.80 ppm) based on stationary air samples and 0.62 ± 0.90 ppm (range, 0.01–5.70 ppm) based on 
105 DRAFT - DO NOT CITE OR QUOTE 

personal air samples. The mean AN exposure measurements were lower than the exposure 

measurements made in 1976 (see Table 4-19), suggesting that workplace air concentrations in 

the plants had declined over the 12-year period between the studies. 

 Prevalences of subjective symptoms that were statistical significantly different between 

the exposed and control groups included “heaviness in stomach” and decreased libido, with the 

symptom described as heaviness in stomach as most significant (Muto et al., 1992). Reported 

prevalences for heaviness of stomach were 29.3% in the exposed group vs. 18.7% in the control 

group. No significant differences were found in prevalences for other GI effects such as 

anorexia, nausea, vomiting, heartburn, or stomachache. 

When workers were grouped into those from factories with mean TWA AN 

concentrations below 0.3 ppm (four factories; mean stationary and personal air concentrations of 

0.27 and 0.19 ppm, respectively; Group A) or above 0.3 ppm (three factories; mean stationary 

and personal air concentrations of 0.84 and 1.13 ppm, respectively; Group B), statistically 

significant increased prevalences for the following symptoms (compared with controls) were 

found for the workers in the factories with higher exposure levels (Group B): decreased libido 

(54.9 vs. 40.2% for controls), poor memory (76.1 vs. 64.0% for controls), irritability (35.2 vs. 

24.1% for controls), reddening of conjunctiva (21.1 vs. 11.7% for controls), and eye pain or 

lacrimation (32.4 vs. 19.2% for controls). There were no statistically significant differences 

between the exposed and control groups in the prevalences of clinically observed physical signs 

(skin rashes or reddening of conjunctiva) or abnormal findings in urinalytic, hematological, liver 

function, or blood pressure variables. Prevalences of chest X-ray abnormalities were likewise 

not different between exposed and control groups. 

 The mean 8-hour TWA personal air concentration of workers in the Group B factories, 

1.13 ppm, was judged by EPA to be a LOAEL for small but statistically significant increased 

prevalences of several subjectively reported symptoms (e.g., poor memory and irritability) in the 

absence of statistically significant increases in the prevalences of physical signs or abnormal 

values for a number of urinalytic, hematological, liver function, or blood pressure variables 

(Muto et al., 1992). The average 8-hour TWA personal air concentration in the Group A 

factories, 0.19 ppm, was judged to be a no-observed-adverse-effect level (NOAEL). Like the 

NOAEL identified in the earlier cross-sectional health examination of Japanese acrylic fiber 

workers (Sakurai et al., 1978), a limitation to the Muto et al. (1992) NOAEL is that the exposure 

assessments were cross-sectional in nature. Historical measurements of air concentrations were 

not available. 

 Kaneko and Omae (1992) performed a cross-sectional health questionnaire study of 

exposed and nonexposed workers from seven acrylic fiber manufacturing plants in Japan. The 

questionnaire for surveying subjective symptoms was administered to 1,220 exposed male 

workers and 757 nonexposed male workers who were either from the same factory or a close-by 

factory of the same company. The selected study population included 504 exposed individuals 
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and 249 unexposed controls. Subjects who were excluded from the study were workers with 

administrative or nonshift jobs, a history of exposure to other chemicals, ages not able to be 

matched, or incomplete information on the questionnaire. Workplace air concentrations of AN 

were measured on 2 consecutive days in each factory by using a portable gas chromatograph. 

Factories were grouped into three exposure groups with the following mean workplace air 

concentrations: Group L = 1.8 ppm, Group M = 7.4 ppm, and Group H = 14.1 ppm. Further 

information on the exposure measurements was not reported (e.g., SD of means, ranges of 

values, or whether or not the reported concentrations represented 8-hour TWA concentrations). 

Mean durations of exposure in the three groups were 5.6, 7.0, and 8.6 years for the L, M, and 

H groups, respectively. All subjects filled in a detailed questionnaire (232 questions in all) that 

was intended to detect neurological condition and subjective symptoms. 

The neurological statuses, as assessed with two different analytical methods 

(Fukamachi’s criteria and Cornell Medical Index profiles), of the AN-exposed workers were 

slightly higher than those of control workers, although the differences were not statistically 

significant. Subjective symptoms with significantly higher prevalences in the L, M, and 

H groups, compared with the nonexposed groups, included headaches, tongue trouble, choking, 

lump in throat, fatigue, general malaise, heavy arms, and heavy sweating. The numbers of 

subjective symptoms that were significantly more prevalent in exposed workers were as follows: 

8 in group L, 19 in group M, and 14 in group H. Only the prevalence of one subjective 

symptom, “often feel a choking lump in the throat,” had a tendency to increase with increasing 

length of exposure to AN in all factories and in group L. EPA identified 1.8 ppm as an equivocal 

LOAEL (Group L mean air concentration) for statistically significantly increased prevalences of 

subjective symptoms. 

 In a translated study from China, Chen et al. (2000) examined the health effects of 

occupational exposure to AN in 224 workers at an acrylic fiber plant. The exposed group 

consisted of 180 males and 44 females, with an average age of 38.6 years (range 19–57 years) 

and an average of 13 years of service. The average AN concentration in the work areas at the 

plant was reported to be 1.04 mg/m3

 (0.48 ppm). All subjects were given a physical 

examination. The results of these investigations and of subjects’ hematological and clinical 

chemistry parameters were compared with those of unexposed controls. Reported symptoms that 

had significantly higher incidence in exposed subjects than in unexposed controls included 

headache and dizziness (41 vs. 21%), poor memory (30 vs. 13%), feelings of choking in the 

chest (13 vs. 8%), and loss of appetite (13 vs. 7%). However, of the other parameters evaluated 

in this study, all hematological data and all but one of the clinical chemistry parameters gave 

closely similar values to those of controls. The exception was the serum activity of γ-GTP that 

was significantly higher (p < 0.05) in exposed subjects than in controls (44.32 ± 32.21 vs. 

40.22 ± 31.06 IU/L). The study authors identified 0.48 ppm as a LOAEL for statistically 

significantly increased prevalences of subjective symptoms (including headache, dizziness, poor 
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memory, and loss of appetite) in workers employed in an acrylic fiber manufacturing plant for an 

average of 13 years, without significant changes in most hematological and clinical chemistry 

variables except for γ-GTP activity. 

 Lu et al. (2005a) employed the World Health Organization (WHO)-recommended 

Neurobehavioral Core Test Battery (NCTB), which includes seven components, to evaluate 

neurobehavioral effects of workers exposed to AN in a Chinese plant. The subjects included 

81 workers (68 males and 13 females) in the AN-monomer department, 94 workers (67 males 

and 27 females) in the acrylic fibers department, and 174 workers (130 males and 44 females) in 

the administrative or embroidery departments with no AN exposure. The monomer and fiber 

workers represented 96% of the eligible exposed workers in the two departments. Periodic 

short-term area sampling between 1997 and 1999 indicated that the geometric means of AN 

exposure were 0.11 ppm (range 0.00–1.70 ppm for 390 samples) in the monomer department and 

0.91 ppm (range 0.00–8.34 ppm for 570 samples) in the fiber department; no personal sampling 

data were collected. As categorized by duration of employment, 23% of monomer workers were 

exposed for 1–10 years, 42% for 11–20 years, and 35% for more than 20 years; and 47% of fiber 

workers were exposed for 1–10 years, 23% for 11–20 years, and 30% for more than 20 years. 

Mean durations of employment were not reported for the exposed groups. Monomer workers 

were also potentially exposed to cyanide and fiber workers to methyl methacrylate and heat, but 

levels of exposure to these possible confounders were not monitored. The exposed workers were 

frequency matched on age (within 5 years) and years of education (within 1 year) with the 

unexposed workers. Exposed workers (mean age 40.8 years; range 25–53) were slightly older 

than unexposed workers (mean age 36.4 years; range 21–53); the percentage of females and 

years of education were roughly similar across groups. All subjects were interviewed for 

demographic data, general health status, and lifestyle. All tests were conducted by three 

specially trained physicians using a Chinese operational guide of the NCTB. 

 Results of the analysis revealed that exposure to AN had adverse effects for some 

components of the NCTB, indicating neuropsychological impairment; scores from the following 

tests were statistically significantly different (p < 0.05) from controls in analyses of covariance 

that took into account age, sex, and education level. In the Profile of Mood States test, all scores 

for negative moods (anger, confusion, depression, fatigue, and tension) were significantly higher 

in the exposed groups than in the unexposed group and higher for monomer workers (41–68% 

higher than controls) than for fiber workers (20–44% higher than controls). Simple Reaction 

Time, a test of attention and visual response speed, was longer in the two exposed groups than in 

the unexposed group: 16% longer for monomer workers and 10% longer for fiber workers. 

Exposed workers performed more poorly (by 21% for monomer workers and 24% for fiber 

workers) in the backward sequence of the Digit Span test, a measure of auditory memory, but 

fiber workers had better performance in the forward sequence than unexposed workers. Both 

groups of exposed workers also had a 4% poorer performance in the Benton Visual Retention 
108 DRAFT - DO NOT CITE OR QUOTE 

test, a measure of visual perception and memory; scores in the Pursuit Aiming II test, which 

assesses fine motor skills and perceptual speed, were 14% lower for monomer workers and 10% 

lower for fiber workers compared with controls. Exposure to AN had no significant effect on 

scores for manual dexterity in the Santa Ana test or for perceptual speed in the Digital Symbol 

test. In examining effects by duration of AN exposure, there was no statistical relationship for 

mood scores and duration of exposure. However, there was an insignificant decrease in Simple 

Reaction performance with duration of exposure for both monomer and fiber workers. Inverse 

relationships were found between performance and duration in both the Digital Symbol test and 

total scores of the Digit Span test in the two exposed groups. Decreased performance with 

duration of exposure was also found in the Pursuit Aiming II test for exposed monomer workers. 

 Lu et al. (2005a) mentioned several limitations of this study. One was that the cited 

exposure data represented estimates of previous exposure levels and no contemporaneous 

personal monitoring data were available. Furthermore, as the NCTB was developed for 

populations in Europe and North America, it is not known to what extent cultural differences 

may have affected results of the Profile of Mood States test, shown to be sensitive to cultural 

differences. In addition, the study authors could not rule out the possibility that examiner drift 

may have affected the results. Selection bias among volunteers in different groups was 

mentioned as a possible confounding effect, but was discounted on the basis that the 

participation among exposed workers was so high. Moreover, largest measures of 

neurobehavioral effect occurred on the acrylic fiber workers, who had lower average exposure 

level. 

 EPA determined the results from this study were consistent with the designation of the 

average exposure levels for the monomer workers, 0.11 ppm, and the fiber workers, 0.91 ppm, as 

LOAELs for small deficits in neurobehavioral tests of mood, attention and response speed, 

auditory memory, and motor steadiness but not in tests of manual dexterity or perceptual motor 

speed. 

 The toxicity of AN in an occupational setting has been the subject of a number of other 

reports from China, which were collectively submitted to the U.S. EPA as a Toxic Substances 

Control Act Test Submissions report (Acrylonitrile Group, 2000). While these studies are 

discussed below for hazard identification purposes, some reports lack sufficient detail to support 

reported findings of AN-related toxicity. For example, Wang et al. (2000) reported on the 

disease incidence of 1,121 AN-exposed workers compared with 489 unexposed controls in a 

university in the same area. Subjects in the exposed group were stated to have a higher incidence 

of disease of the digestive system (16.95 vs. 8.28%) and the liver (8.12 vs. 1.84%) than in the 

control group. The highest prevalence rate of 12.5% for liver disease was found in workers 

exposed to AN over 20 years. The prevalence rate of chronic disease also increased with 

duration of exposure. However, the report contained no diagnostic information on these 

conditions and no information on the levels of AN to which the subjects had been exposed. 
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 Dong and Pan (1995) surveyed reproductive outcomes in 150 male and 105 female 

workers at a chemical fiber plant in China. The concentration of AN in the air in work areas of 

the plant ranged from 0.53 to 15.5 mg/m3 (0.24–7.1 ppm; midpoint = 3.7 ppm). Controls in the 

study were 110 male and 121 female workers who had not been exposed to AN. The report 

compared the reproductive outcomes for the wives of male workers to the wives of male controls 

(Table 4-20) and for all female workers at the plant vs. female controls (Table 4-21). As shown 

in Table 4-20, the rates of premature delivery, spontaneous abortion, threatened abortion, 

stillborn fetuses, and sterility in the wives of male exposed workers all were higher than those in 

wives of male controls, with some differences achieving statistical significance. 

Table 4-20. Comparison of reproductive outcomes in wives of exposed and 

control males at a chemical fiber plant 

Parameter Exposed groupa (n = 150) Controlsa (n = 110)

Average age 20.97 ± 6.85b 30.04 ± 3.37 

Average working yrs 3.19 ± 5.35 8.53 ± 3.89 

Pregnancies 168 113 

Sterility (%) 9 (5.00)c 2 (1.82) 

Life births 159b 113 

Normal births 141 104 

Premature deliveries (%) 18 (10.71d)

c

 4 (3.54) 

Late deliveries (%) 6 (3.57) 4 (3.54) 

Spontaneous abortion (%) 8 (4.76)c 1 (0.88) 

Threatened abortion (%) 5 (2.98)c 1 (0.88) 

Stillborn fetuses (%) 4 (2.38) 0 (0) 

Low birth weight 5 (3.14) 4 (3.84) 

aNumbers in parentheses are in %. 

bGiven as 7.74 in the report. 

c

Significantly different from controls (p < 0.05 by Fisher’s exact test), as calculated by U.S. EPA. 

d

Significantly different from controls (p < 0.001 by Student’s t-test), as calculated by U.S. EPA. 

Source: Dong and Pan (1995). 

Table 4-21. Comparison of reproductive outcomes between exposed and 

control females at a chemical fiber plant 

Outcome Exposed groupa (n = 105) Control groupa (n = 151)

Average age 29.36 ± 5.12b 20.68 ± 4.05 

Average number of working yrs 10.19 ± 8.22 10.12 ± 4.34 

Number of pregnancies 112 124 

Number of alive newborns 105 125 

Normal births 101 113 

Immature deliveries (%) 8 (7.14) 5 (4.03) 

Late deliveries (%) 8 (7.14) 6 (4.84) 
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Table 4-21. Comparison of reproductive outcomes between exposed and 

control females at a chemical fiber plant 

Outcome Exposed groupa

 (n = 105) Control groupa (n = 151)

Spontaneous abortions (%) 1 (0.89) 0 (0) 

Threatened abortions (%) 3 (2.68) 5 (4.03) 

Stillborn fetuses (%) 5 (4.46)c 0 (0) 

Mortality of newborns (%) 3 (2.86) 0 (0) 

Sterility (%) 3 (2.86) 1 (0.83) 

aNumbers in parentheses are in %. 

b

Significantly different from controls (p < 0.001 by Student’s t-test). 

c

Significantly different from controls (p < 0.05), as calculated by the study authors. 

Source: Dong and Pan (1995). 

 Effects on the reproductive outcome in exposed female workers at the plant were not as 

striking as in males, when compared with controls (Table 4-21) (Dong and Pan, 1995). 

However, the rate of stillborn fetuses in the exposed group was far higher than that of the control 

group (5/112 vs. 0/124, p < 0.05). It is unclear how much these differences may be related to the 

fact that in the first comparison (Table 4-20), the exposed males were significantly younger than 

the controls (p < 0.001 by Student’s t-test, as calculated by the reviewers), whereas in the second 

case (Table 4-21), the exposed childbearing females were significantly older than the controls 

(p < 0.001). The results from this study identify the midpoint of the range of average workplace 

air concentrations of AN, 3.7 ppm, as a LOAEL for increased prevalences of adverse 

reproductive outcomes in male and female workers employed for averages of about 3 and 

10 years, respectively. The adverse outcomes showing statistically significantly increased 

prevalences compared with controls were premature deliveries (18/150 vs. 4/110 in controls), 

threatened abortion (5/150 vs. 1/110 in controls), and sterility (9/150 vs. 2/110 in controls) for 

the male exposed workers and their wives and increased prevalence of stillborn fetuses in female 

exposed workers (4/105 vs. 0/151 in controls). 

 In a follow-up to the study by Dong and Pan (1995), Dong et al. (2000b) expanded the 

cohort to include the years 1994 and 1995, resulting in 548 exposed male workers (496 controls) 

and 391 exposed female workers (427 controls). Average employment durations for the exposed 

males and females were 11.0 ± 4.5 and 10.4 ± 3.8 years, respectively. The average ages of the 

male and female workers were 33.8 and 32.4 years, respectively. The age, length of service, and 

lifestyle of the controls were similar to the exposed workers. 

The reported range of AN concentrations in the workplace air, 0.11–15.5 mg/m3

 (0.05–

7.14 ppm, midpoint = 3.6 ppm), was not markedly different from that reported in the initial 

study. In the follow-up study, however, Dong et al. (2000b) also evaluated birth defects. The 

general trend of results was a slightly higher percentage of abnormal findings in the exposed 

cohort, as compared with the initial study, and an incidence of 15.7% birth defects, as compared 
111 DRAFT - DO NOT CITE OR QUOTE 

with 6.1% in controls. This difference was not statistically significant. There were, however, 

some statistically significant findings in the reproductive outcome of exposed females. In the 

initial study, Dong and Pan (1995) had reported a significant increase in stillbirths (4.5% in 

exposed vs. 0% in controls). In the expanded cohort, this value was lower, 2.7 vs. 0.68%, but 

still statistically significant at the p < 0.05 level. There was also a significantly (p < 0.05) 

increased incidence of birth defects (21.3 vs. 4.8%), decreased incidence of low birth weights 

(3.5 vs. 4.8%), and highly significant (p < 0.01) increase in premature deliveries (8.2 vs. 3.9%). 

The results from the follow-up study identify the midpoint of the range of workplace air 

concentrations, 3.6 ppm, as a LOAEL for statistically significantly increased prevalences of 

adverse reproductive outcomes (increased stillbirths, birth defects, and premature deliveries) in 

female exposed workers employed for an average of 11 years. 

 Dong et al. (2000a) also carried out an industrial hygiene survey of 68 male and 

25 female workers at a Chinese chemical plant, as compared with 58 male and 38 female 

workers who had not been exposed to AN. The average age of exposed subjects was 27.9 years, 

and their years of employment at the plant ranged from 1 to 15 years. The average age of 

controls was 32.3 years. All subjects in the study answered lifestyle questions, including 

medical and occupational history, smoking and drinking history, and subjective symptoms. They 

also were given a physical examination, including clinical examinations, chest X-rays, liver and 

gallbladder ultrasound, electrocardiogram (ECG), clinical chemistry, and blood and urine tests. 

Air samples were collected from two workplace areas over a 3-year period and analyzed for AN, 

HCN, and acetonitrile concentrations. Annual average AN concentration was not provided in the 

report, but measured AN concentrations were over 2 mg/m3 at all times, with the highest 

concentration reaching 22.79 mg/m3. 

 Exposed workers reported the occurrence of headache, dizziness, sleeping disorders, and 

a feeling of choking in the chest at a significantly higher prevalence than nonexposed workers. 

Without presenting details, Dong et al. (2000a) referred to ultrasound tests of six individuals in 

the exposed group, which appeared to show diffuse changes in the liver. In this group, there was 

also a higher incidence of trembling of eyes, face, and fingers than in controls. However, all of 

the blood pressure, hematological, and clinical chemistry parameters under evaluation (including 

liver function tests) for exposed subjects were within the normal range and closely similar to 

those of controls. Although the results indicated that increased prevalences of symptoms were 

reported by exposed workers compared with nonexposed workers, the reported exposure 

information was inadequate to designate a LOAEL for this study. 

 Li (2000) surveyed reproductive outcomes in 379 female workers in a Chinese AN 

manufacturing company and in 511 unexposed control workers from a bed sheet factory and a 

biological research institute in 1991. The average age and duration of employment of the (20.8 

vs. 7.14%), premature deliveries (11.62 vs. 4.72%), and congenital defects (25.4 vs. 4.2 exposed 

workers were 33.95 years (22.75–54.83 years) and 14.10 years (3.25–34.45 years), respectively. 
112 DRAFT - DO NOT CITE OR QUOTE 

Average age and employment duration of the control workers were reported to be similar to the 

exposed group. Monthly workplace air concentration data for 1989 and 1990 were provided by 

the factory. The average AN air concentration was reported as 16.35 mg/m3 (7.5 ppm, range = 

0–152.88 mg/m3 [0–70 ppm]). Statistically significant increased prevalences of the following 

reproductive outcomes were found, compared with controls: sterility (2.64 vs. 0.78%), 

pregnancy complications %). Li (2000) also divided the exposed group into female workers with 

and without exposed male partners. Prevalence rates for several adverse reproductive outcomes 

(pregnancy complications, premature delivery, late delivery, stillbirths, and congenital deficits) 

were statistically significantly elevated in females with exposed partners, compared with those 

with nonexposed partners. This study identifies the average workplace AN air concentration, 7.5 

ppm, as a LOAEL for increased prevalences of adverse reproductive outcomes in female AN 

manufacturing workers employed for an average of 14 years. 

 Xiao (2000a) reported on the fasting serum activities of serum glutamate pyruvate 

transaminase (SGPT, also known as ALT) in 372 workers exposed to AN for 1–31 years in a 

chemical factory in China and compared the levels with those in 186 unexposed workers. 

Individuals with SGPT level ≥19 μmol/L-minute were considered positive. The percentage of 

individuals with SGPT activity exceeding the benchmark level was compared between the 

groups. Significantly higher percentage of positive individuals were found in the exposed group 

compared with controls (41.13 vs. 4.8%), with exposed males being more severely affected than 

exposed females (50.23 vs. 27.82%). No data were provided on the level of AN exposure. 

 Xiao (2000b) also reported on the levels of whole blood cholinesterase in 237 workers 

exposed to AN in a chemical factory in comparison with those in 184 unexposed workers. AN 

measurements were provided for three separate workshops, although it is not evident from the 

report whether the measurements were taken as spot samples or from personal samplers. A 

colorimetric method was used to measure cholinesterase activity. The average AN 

concentrations in air for the three workshops were 7, 3.3, and 3 ppm, respectively. The authors 

reported that the levels of whole blood cholinesterase in AN-exposed workers from the three 

workshops were more than 50% lower than in controls. Health examination results showed there 

was also an apparent increase in the incidence of symptoms related to lowered cholinesterase 

activity in exposed subjects compared with controls. These symptoms included neurological 

disorder, excessive sweating, trembling, and discomfort in the chest. 

 In an article published in a Chinese journal, Ding et al. (2003) evaluated mitochondrial 

DNA damage in a group of 47 Chinese workers randomly selected from 1,020 active workers in 

the chemistry department of a petrochemical company. These workers were exposed to AN at a 

geometric mean concentration of 0.25 mg/m3 (0.11 ppm) (median 0.36 mg/m3 [0.17 ppm], range 

0–3.70 mg/m3) for an average of 17.3 ± 3.8 years. An unexposed control group of 47 persons 

was selected from the teachers and staff of a college, with an average length of employment of 

18.7 ± 4.1 years. DNA was extracted from peripheral blood samples from each subject and 
113 DRAFT - DO NOT CITE OR QUOTE 

evaluated using the polymerase chain reaction (PCR) with specific primer pairs to detect 

deletions in mitochondrial DNA. Deletions in mitochondrial DNA were detected in 

8/47 exposed workers compared with 0/47 nonexposed workers. A deletion rate of 0.00225 ± 

0.00171 was calculated based on optical densities from gel scans of the deletion fragment 

compared with a fragment synthesized by using primer pairs to a conserved region of 

mitochondrial DNA; this deletion rate was statistically significantly different (p < 0.05) from the 

rate of 0 for the controls. For studying the effects of aging, a group of 12 healthy nonexposed 

retirees from governmental organizations (average age 79.15 ± 3.80 years) and a group of 

12 healthy nonexposed high school students (average age 14.23 ± 1.52 years) were also 

examined. Deletion fragments were detected in 3/12 elderly subjects and 0/12 young subjects. 

The deletion rate for the elderly was calculated as 0.00193 ± 0.00086, which was not 

significantly different from that calculated for AN-exposed workers. The study authors 

suggested that exposure to AN might have an effect on the molecular process(es) of aging. 

Limitations of this study included the lack of reporting for the criteria of selection for the 

controls and the gender composition of each group. The results identified the mean workplace 

AN air concentration, 0.11 ppm, as a LOAEL for increased prevalence of workers with deletions 

in peripheral blood mitochondrial DNA compared with controls. 

 Ivanescu et al. (1990) used a radioimmunoassay to measure serum levels of testosterone 

in three groups of male workers exposed to AN in a chemical factory. Blood samples were taken 

from 39 subjects in May 1975, from 109 subjects in March 1976, and from 149 subjects in May 

1977. Subjects were between 19 and 40 years old and had been employed at the facility from 

6 months to 10 years. Controls in the study consisted of 145 unexposed men. The three groups 

of exposed subjects had average serum testosterone concentrations ranging from 3.5 to 

4.1 ng/mL. This compared with average values ranging from 5.4 to 7.3 ng/mL in different 

subsets of the 145 control subjects. Although the time of blood sampling during the day was 

variable in this study and the circadian rhythm of testosterone was unknown, testosterone 

concentrations in sera of exposed groups were much lower than in control groups of the same 

month. However, no data were presented in the report on the level of exposure to AN or other 

chemicals. 

 An epidemiological report by Czeizel et al. (2000, 1999) examined the incidence of 

congenital abnormalities and indicators of germinal mutations in the vicinity of an AN-using 

factory in Hungary. The study used the incidence of congenital abnormalities from the 

Hungarian Congenital Abnormality Registry in 46,326 infants born between 1980 and 1996 in 

30 settlements within a 25-km radius of an AN-using factory. A number of time-space-specific 

clusters of abnormalities were identified among the subjects, including pectus excavatum in the 

Tata community between 1990 and 1992 (OR = 78.5, 95% CI = 8.4–729.6), undescended testis 

in Nyergesujfalu between 1980 and 1983 (OR = 8.6, CI = 1.4–54.3) and at Esztergom between 
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1981 and 1982 (OR = 4.2, CI = 1.3–13.5), and clubfoot in Tata between 1980 and 1981 (OR = 

5.5, CI = 1.5–20.3). 

 The relationship between the findings of clusters of abnormalities and AN exposure was 

uncertain because there were no exposure data in the report. Consequently, it was not known by 

how much the mothers of affected infants were exposed to the compound, if at all. Furthermore, 

when the incidence of congenital abnormalities was considered for infants born throughout the 

entire duration of the study, there were no increased incidences of congenital abnormalities 

compared with infants born throughout Hungary. 

 The study authors stated that there was a technological change at the AN factory in 1984 

that resulted in greater environmental protection, implying that releases of AN to the 

environment were lower than before the change. This suggests that the cluster of pectus 

excavatum obtained at Tata between 1990 and 1992 was unlikely to have been due to AN 

exposure. However, the high incidence of undescended testis in Nyergesujfalu between 1980 

and 1983 may have been an environmental phenomenon, because the region-wide incidence of 

this congenital abnormality appeared to decrease with increasing distance from the factory. In 

general, however, it is difficult to draw conclusions about a link between maternal exposure to 

AN and the incidence of congenital abnormalities from the data in this study because of a lack of 

exposure data. 

 Wu et al. (1995) (in the English translation of the abstract of an article in Chinese) 

reported findings on 477 female workers exposed to AN and 527 controls studied using the 

retrospective cohort method. Statistically significant increases in the incidence of pernicious 

vomiting, anemia, preterm delivery, and birth defects were found in exposed women. However, 

the authors also emphasized several confounding factors in their study, such as illness, medicine 

taking, and X-ray exposure during pregnancy. 

 Other reports of chronic occupational exposure to AN described additional health effects. 

Babanov et al. (1959) (as cited in IPCS, 1983) reported nonspecific changes in skin and pale 

mucous membranes in addition to vocal cord inflammation in workers exposed to 0.6–6.0 mg/m3

(0.3–3 ppm) AN in air for approximately 3 years. 

 Depression, lowered arterial pressure, diffuse dermographia, and increased sweating in 

AN production workers was described by Ageeva (1970) (as cited in IPCS, 1983). Stamova et 

al. (1976) (as cited in IPCS, 1983) reported that workers in a polyacrylic fiber plant showed 

increased incidence of skin diseases when exposed to air concentrations of 10–25 mg/m3

 (5–

12 ppm) AN. An increase in other “neurasthenic” complaints and diseases was also reported. 

However, the presence of other industrial chemicals and uncertainty in the length of exposure 

were potential confounding factors in these responses. 

 Borba et al. (1996) measured CEVal-Hb adducts as a marker of AN exposure in three 

groups of occupationally exposed workers in an acrylic fiber factory in Portugal. The groups 

comprised 20 administrative workers who were not exposed to AN in the same plant, 
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14 individuals employed in the continuous polymerization department, and 10 equipment 

maintenance workers. Considered a measure of the biologically effective dose, CEVal values 

were 8.5–70.5 pmol/g Hb in controls, 635.2–4,603.5 pmol/g Hb for continuous polymerization 

workers, and 93.9–4,746 pmol/g Hb for maintenance workers. These findings pointed to the 

ready formation of AN adducts with Hb in exposed workers. Unfortunately, the report lacked 

critical information about the levels and duration of exposure to AN undergone by the workers of 

the different groups and whether such exposure and the adduct formation that resulted were 

associated with symptoms of ill health. 

 Borba et al. (1996) also monitored several internal exposure markers for the three groups 

of workers. The induction of CYP450 species was determined by the excretion of D-glucaric 

acid (an end product of the glucuronic pathway) in the urine, and formation of malondialdehyde 

(MDA) (a final product of lipid peroxidation) in RBCs was determined as a surrogate measure of 

oxidative stress. The study authors found no indication of AN-induced CYP450 induction, but a 

significant increase was seen for the oxidative stress marker in the group of maintenance 

workers. Smoking had no influence on these metrics. Borba et al. (1996) also investigated 

markers for genotoxicity (viz., gene reversion activity of urine extracts, chromosomal aberrations 

(CAs), and sister chromatid exchanges [SCEs]). These are discussed in the genotoxicity section 

(Section 4.5.2). 

4.1.3. Dermal Exposure 

4.1.3.1. Acute Exposure 

 A case report by Vogel and Kirkendall (1984) described a 24-year-old ship’s officer who 

was accidentally sprayed with AN when a valve burst while he was unloading the chemical. 

Because the man’s face, eyes, and body were covered with AN, it is likely that he was exposed 

via the oral and inhalation routes as well as to the skin and eyes. Immediate responses to 

exposure included dizziness, flushing, and nausea with vomiting. During hospitalization, acute 

toxicological impacts included a rapid pulse rate (100 beats/minute) and a respiratory rate of 

16/minute. The subject displayed erythema and mild conjunctivitis, tachycardia, and striking 

hematological changes (WBC count of 26,400 cells/cm3

, of which 76% was polymorphonuclear 

leukocytes, 10% lymphocytes, and 7% each basophiles and monocytes). Methemoglobin 

(MetHb) concentration was 10.3% on admission. The patient received nitrite/thiosulfate 

treatment, underwent dialysis, and, overall, showed steady recovery over his 5-day 

hospitalization. 

 There are a number of additional case studies of the toxic effects of AN resulting from 

acute exposure after accidental spillage in the workplace. These support the designation of AN 

as a skin irritant. In several cases, erythemas were shown to result from direct dermal contact 

with solutions of AN (Davis et al., 1973 [as cited in IPCS, 1983]; Zeller et al., 1969; Wilson et 

al., 1948; Dudley and Neal, 1942). The lesions were followed by delayed blistering and burns, 
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typically 1 or 2 days following exposure (Davis et al., 1973 [as cited in IPCS, 1983]; Zeller et al., 

1969; Babanov et al., 1959; Dudley and Neal, 1942). In some cases, clinically diagnosed 

dermatitis was associated with irritation (Bakker et al., 1991; Davis et al., 1973 [as cited in IPCS, 

1983]). For example, Davis et al. (1973) (as cited in IPCS, 1983) reported a wide range of 

dermal effects from AN contact, including skin dermatitis, local irritation, erythema, swelling, 

blistering, and burns. However, dermatitis has not always resulted from AN-induced skin 

irritation (Zeller et al., 1969; Babanov et al., 1959; Wilson et al., 1948; Dudley and Neal, 1942). 

 When Dudley and Neal (1942) investigated the effects of AN exposures to laboratory 

animals, an accident in their laboratory resulted in a case of occupational exposure. Symptoms 

similar to those described later by Wilson et al. (1948) were reported for a male laboratory 

worker who spilled small quantities of liquid AN on his hands. Diffuse erythema on hands and 

wrists was evident after 24 hours, with subsequent blistering on the fingertips on day 3. Both 

hands became slightly swollen, erythematous, itching, and painful. By day 10 after exposure, the 

skin of the fingers had cracked and peeled and the skin was dry and scaly with large areas of 

tender new skin. 

 Zeller et al. (1969) identified 137 cases of accidental exposure to nitriles when reviewing 

industrial hygiene data from Germany on accidental exposures to chemical agents in an 

occupational setting over a 15-year period. Of the 137 cases, 66 cases related to AN exposure, of 

which 50 cases resulted from direct skin contact and the remaining 16 to inhalation or exposure 

to AN vapors. All 66 cases were judged to be minor and did not require hospitalization. 

However, up to 3 weeks of recuperation was required as a result of direct skin contact with the 

compound. Typically, the first symptoms appeared between 5 minutes to 24 hours after initial 

dermal contact with AN. For the most part, the workers complained of burning sensations of the 

skin, followed by reddening of the exposed area and the formation of blisters at any point during 

the first 24 hours. In one case, AN was thought to have diffused through the leather of a shoe on 

which it was spilled, resulting in a delay before blisters appeared and delayed healing. There 

was no indication of resorptive damages from the dermal exposure in any of the 50 cases. 

 In another study (Babanov et al., 1959), blistering was also observed on workers’ legs 

within 6–8 hours of contact with spilled AN, while a diluted (5%), heated (50°C) solution of AN 

caused serious skin burns. 

 A fatal case of dermal contact exposure with AN was described by Lorz (1950), when 

application of a delousing agent containing AN resulted in the death of a 10-year-old girl. 

Following dermal application of the delousing agent to the scalp, the girl’s head was wrapped in 

a cloth and she went to bed. Symptoms of nausea, headaches, and dizziness were followed by 

repeated vomiting and coma. Cramps and increasing cyanosis were followed by death 4 hours 

after application. A similar case of fatal poisoning was reported by Grunske (1949) in which a 

3-year-old girl died after reentry into a home that had been treated with an AN-containing 
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fumigant. In both of these cases, exposure was likely to have occurred via inhalation as well as 

the dermal route. 

4.1.3.2. Chronic Exposure 

 In addition to the known skin irritation effects of acute exposures to high-concentration 

liquids and vapors, various chronic dermal exposure effects were reported. There was limited 

evidence that skin sensitization resulted in dermal allergies to AN. Therefore, an intrinsic 

capacity of AN to act as a skin sensitizing agent was suggested. 

 The abstract of a Japanese language report by Hashimoto and Kobayasi (1961) discussed 

the case of a chemical laboratory worker who developed skin lesions through contact with AN. 

Although much of the detail remained uncertain, including period and duration of exposure and 

the influence of other chemicals on the subject’s condition, the lesions apparently spread across 

the subject’s body from the contact site, consistent with a direct contact allergic reaction. 

 Bakker et al. (1991) reported that 10 employees at an acrylic fiber factory complained of 

skin irritation. While five of the subjects developed irritant dermatitis, the other five subjects 

gave positive patch tests with AN, suggesting an allergic reaction. This finding also supported 

the designation of AN as a sensitizing agent. 

 Prolonged dermal contact for 6 weeks to methyl methacrylate, a copolymer of AN, 

resulted in an allergic skin sensitization reaction in the case of a 27-year-old man who had his 

finger splinted for a torn ligament (Balda, 1975). The unpolymerized AN of the Plexidur 

copolymer resulted in strong skin irritation response, with erythema and formation of scaly skin 

and scattered blisters. Patch testing confirmed that the allergic sensitization was to AN and not 

to a copolymer or the polymerization catalyst, benzoyl peroxide. A contributing factor may have 

been the man’s prior hyperhydrosis episode of the hands that led to blister formation. 

 Very few studies hinted at a possible desensitization or adaptive effect for prolonged 

chronic exposures. Based on investigations carried out over a period from 1965 to 1971, Zotova 

(1975) reported complaints of poor health, which included skin irritation, in workers at an AN 

manufacturing facility. Gincheva et al. (1977) (as cited in IPCS, 1983) did not find changes in 

the health status of a group of 23 men exposed to 4.2–7.2 mg/m3

 (2–3.3 ppm) of AN for 

exposure durations of 3–5 years. Details of the study were not provided. 

4.1.4. Ocular Exposure 

 Secondary routes of exposure to AN include ocular exposure to either AN liquid or 

vapor. For example, in the Wilson et al. (1948) study, subjects exposed to AN at concentrations 

varying from 16 to 100 ppm (35–217 mg/m3) for 20–45 minutes demonstrated irritation of all 

mucous membranes, including the eyes, nose, and throat. In other studies, blepharoconjunctivitis 

was reported in workers exposed to the compound (Delivanova et al., 1978). Of 302 workers 
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examined over 2 years (138 in 1976 and 164 in 1978), 42 had severe cases of 

blepharoconjunctivitis related to AN exposure. 

 In the case report by Vogel and Kirkendall (1984), the mucous membranes of the eyes of 

the 24-year-old man had been sprayed with AN. Among other symptoms, mild conjunctivitis but 

no apparent corneal clouding was observed. Eye irritations and nasal discharge also were 

reported in workers exposed to relatively high levels of AN at an acrylic fiber plant (Sakurai, 

2000; Sakurai et al., 1978). 

 A synopsis of noncancer outcomes of exposure to AN is provided in Table 4-22. 

Table 4-22. Epidemiology studies of noncancer outcomes among cohorts of 

workers exposed to AN 

Reference Study population Exposure assessment Toxic effects/outcome

Muto et al. (1992) 157 Male workers 

employed in seven 

Japanese acrylic fiber 

plants with average of 

17 yrs employment; 

537 unexposed controls 

Mean 8-hr TWAs: 

Group A factories = 

0.19 ppm; Group B 

factories = 1.13 ppm 

Increased prevalences of subjective 

symptoms in Group B factories, such as 

heaviness of the stomach, decreased libido, 

poor memory, irritability, conjunctival 

reddening, and eye irritation; not in Group 

A; no significantly increased prevalences 

of physical signs or abnormal values in 

urinalytic, hematological, liver function, or 

blood pressure variables in Group A or B 

compared with control 

Sakurai et al. 

(1978) 

102 Male workers in six 

Japanese acrylic fiber 

plants with averages of 

10–12 yrs of employment; 

62 matched controls 

Mean 8-hr TWAs: 

Group A factories = 

0.1 ppm; Group B 

factories = 0.5 ppm; 

Group C factories = 

4.2 ppm 

Statistically insignificant increase in the 

incidence of palpable liver, reddening of 

the conjunctiva and pharynx, and skin 

rashes compared with controls; survey of 

subjective symptoms not performed 

Kaneko and 

Omae (1992) 

502 Male workers in 

seven Japanese acrylic 

fiber plants with averages 

of 5.6, 7.0, and 8.6 yrs of 

employment at low-, 

medium-, and high-level 

workplace exposure; 

249 unexposed matched 

controls 

Group L factories = 

1.8 ppm; Group M 

factories = 7.4 ppm; 

Group H factories = 

14.1 ppm: air 

concentrations reported 

as “means” without 

other information 

Statistically significant increased 

prevalences of subjective symptoms, such 

as headaches, tongue trouble, choking lump 

in chest, fatigue, general malaise, heavy 

arms, and heavy sweating in workers in 

Groups L, M, and H factories, compared 

with controls 

Chen et al. (2000) 224 Workers (180 males 

and 44 females) in an 

acrylic fiber plant with 

average of 13 yrs of 

employment; 

224 unexposed controls 

0.48 ppm Statistically significant increased 

prevalences of subjective symptoms, such 

as headache, dizziness, poor memory, 

choking feeling in the chest, and loss of 

appetite, compared with controls; increase 

in serum γ-GTP but not in other clinical 

chemistry or hematological variables 
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Table 4-22. Epidemiology studies of noncancer outcomes among cohorts of 

workers exposed to AN 

Reference Study population Exposure assessment Toxic effects/outcome

Lu et al. (2005a) Chinese acrylic fiber 

workers: 81 monomer 

workers (68 male and 

13 female); 94 fiber 

workers (67 male and 

27 female); 

174 unexposed workers 

Mean 8-hr TWAs: 

Monomer work areas = 

0.11 ppm (0–1.7 ppm); 

fiber manufacture work 

areas = 0.91 ppm (0–

8.34 ppm) 

Small but statistically significant deficits in 

tests of neurobehavior in monomer and 

fiber workers compared with controls; 

significant deficits in tests of mood 

(increased scores for anger, confusion, 

depression, fatigue, and tension), attention 

and response speed, auditory memory, and 

motor steadiness; not in tests of manual 

dexterity or perceptual motor speed 

Dong and Pan 

(1995) 

255 Workers in a Chinese 

chemical fiber plant 

(150 males and 

105 females) with 

averages of 3.2 and 

10.2 yrs of employment; 

231 unexposed controls 

Workplace air 

concentrations = 0.24–

7.1 ppm; 

midpoint = 3.7 ppm 

Statistically significant increased 

prevalences of adverse reproductive 

outcomes (premature delivery [10.7 vs. 

3.5%, wives of exposed males], stillbirths 

[4.5 vs. 0%, exposed females], and sterility 

[5.0 vs. 1.8%, exposed males]) compared 

with controls 

Dong et al. 

(2000b) 

548 Male and 391 female 

workers in a Chinese 

chemical fiber plant with 

averages of 11.0 and 

10.4 yrs of employment; 

496 male and 427 female 

unexposed controls 

Workplace air 

concentrations = 0.05–

7.14 ppm; midpoint = 

3.6 ppm 

Statistically significantly increased 

prevalences of adverse reproductive 

outcomes (increased stillbirths [2.7 vs. 

0%], birth defects [21.3 vs. 4.8%], and 

premature deliveries [8.2 vs. 3.9%]) in 

female workers compared with controls 

Dong et al. 

(2000a) 

93 Workers at a Chinese 

chemical fiber plant; 

96 unexposed controls 

Unclear presentation of 

exposure data 

Increased prevalences of subjective 

symptoms (headache, dizziness, sleeping 

disorders, and a feeling of choking in the 

chest) compared with controls 

Li (2000) 379 Female AN 

manufacturing workers 

employed an average of 

14 yrs; 511 unexposed 

controls 

Average workplace air 

concentration = 

7.5 ppm; range = 0–

70 ppm 

Statistically significant increased 

prevalences of adverse reproductive 

outcomes (sterility [2.6 vs. 0.8%], 

pregnancy complications [20.8 vs. 7.1%], 

premature deliveries [11.6 vs. 4.7%], and 

congenital defects [25.4 vs. 4.2%]) in 

female exposed workers compared with 

controls 

Xiao (2000a) 372 Workers exposed to 

AN in a chemical factory; 

186 unexposed controls 

No data Increase in the serum ALT activity 

Xiao (2000b) 237 Workers exposed to 

AN in a chemical factory; 

184 unexposed controls 

Workshop A = 7 ppm; 

workshop B = 3.3 ppm; 

workshop C = 3 ppm 

Reduction in whole blood cholinesterase 

activity; subjective symptoms such as 

neurological disorder, sweating, trembling, 

and discomfort in the chest 

Ivanescu et al. 

(1990) 

39 Subjects (May 1975), 

109 subjects (March 

1976), 149 subjects (May 

1977) 

No data Reduced serum testosterone 

Czeizel et al. 

(2000, 1999) 

Case control study of 

babies born with 

congenital abnormalities 

in the vicinity of an 

AN-using factory 

No data Incidence of undescended testis possibly 

related to proximity to the AN-using 

facility 
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Table 4-22. Epidemiology studies of noncancer outcomes among cohorts of 

workers exposed to AN 

Reference Study population Exposure assessment Toxic effects/outcome

Wu et al. (1995) 477 Female AN workers; 

527 workers 

No data Increased vomiting, anemia, preterm 

delivery, and birth defects in pregnant 

females 

Babanov et al. 

(1959) 

Unstated number of 

exposed subjects 

0.3–3.0 ppm Changes to skin and mucous membranes, 

vocal cord inflammation 

Ageeva (1970) 

(as cited in IPCS, 

1983) 

Unstated number of 

exposed workers 

No data Diffuse dermographia and increased 

sweating 

Stamova et al. 

(1976) (as cited in 

IPCS, 1983) 

Unstated number of 

exposed AN workers 

5–12 ppm Skin reactions 

Delivanova et al. 

(1978) 

302 Exposed workers No data Blepharoconjunctivitis 

4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN 

ANIMALS—ORAL AND INHALATION 

AN has been demonstrated to be a multiple-site carcinogen in rat and mouse bioassays. 

Chronic oral exposure to AN-induced tumors in the brain or spinal cord, Zymbal gland in the ear 

canal, the forestomach, and, to a lesser degree and less consistently, in the female mammary 

gland and the tongue in several oral bioassays with F344 rats (Johannsen and Levinskas, 2002b; 

Bigner et al., 1986; Biodynamics, 1980b) and Sprague-Dawley rats (Johannsen and Levinskas, 

2002a; Quast, 2002; Biodynamics, 1980a, b; Quast et al., 1980a). In addition, oral exposure for 

up to 46 weeks led to increases in brain astrocytomas and Zymbal gland in female SpragueDawley rats (Friedman and Beliles, 2002; Litton Bionetics, 1992). Lifetime inhalation 

cancer bioassays with Sprague-Dawley rats found exposure-related increased incidences of brain 

tumors, Zymbal gland tumors, intestinal tumors, malignant mammary gland tumors, and tongue 

tumors (Dow Chemical Co., 1992a; Maltoni et al., 1988, 1977; Quast et al., 1980b). In mice, a 

single gavage lifetime bioassay identified the forestomach and the Harderian gland as sites of 

tumor development, but elevated incidences of brain, Zymbal gland, or mammary gland tumors 

were not found (NTP, 2001). Thus, consistent target organs for the carcinogenicity of AN 

include the forestomach, CNS, and Zymbal gland in rats and the forestomach and ocular 

Harderian gland in mice. Exposure-related increased incidences of tongue and mammary gland 

tumors have been observed, but the responses have not been observed as consistently across 

studies as the responses in the forestomach, CNS, and Zymbal gland in rats. 

 Evidence from two studies of exposure to AN starting in early-life suggests increased 

susceptibility to the carcinogenicity of AN compared with chronic exposure during adulthood 

only. The evidence for carcinogenicity in these studies, a three-generation reproductive/

developmental study of AN in drinking water (Friedman and Beliles, 2002) and an inhalation 
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bioassay (Maltoni et al., 1988), is presented in Sections 4.2.1.2.8. and 4.2.2.2, respectively. The 

evidence for early-life susceptibility is discussed in Section 4.8.1. 

 Oral toxicity studies in rats and mice identified the forestomach as the most sensitive 

target organ for the noncancer toxicity of oral exposure to AN. Hyperplasia of the forestomach 

epithelium occurred at lower oral doses than doses producing other noncancer effects. Increases 

in other nonneoplastic lesions were observed in the kidney, Harderian gland, and ovary. 

Available data include results from several oral toxicity and cancer bioassays of chronically 

exposed rats (see the first paragraph for references) and one oral toxicity and cancer bioassay in 

mice (NTP, 2001). 

 Results from a single chronic inhalation toxicity study in rats (Quast et al., 1980b) 

identified the nasal epithelium as a sensitive noncancer toxicity target of AN. Hyperplasia of 

mucus-secreting cells and flattening of the respiratory epithelium developed with chronic 

exposure to concentrations as low as 20 ppm. A limited number of other subchronic studies in 

rats identified impaired sensory nerve conduction (Gagnaire et al., 1998) and mild developmental 

effects in the presence of maternal toxicity (Saillenfait et al., 1993; Murray et al., 1978) (see 

Section 4.3) as other noncancer effects associated with repeated inhalation exposure to AN. 

4.2.1. Oral Exposure 

4.2.1.1. Subchronic Studies 

Single studies in dogs and mice are the only well-documented standard bioassays for the 

subchronic toxicity of AN in experimental animals by the oral route (NTP, 2001; Quast et al., 

1975). A full report of a study in rats is not available (Humiston et al., 1975 [as cited in Quast, 

2002]). Additional subchronic studies have evaluated only functional effects of AN exposure in 

specific organs, such as the adrenals (Szabo et al., 1984) and the brain (Gagnaire et al., 1998). 

These endpoint-specific studies are discussed in Section 4.4.1. 

 Humiston et al. (1975) (as cited in Quast, 2002) exposed groups of Sprague-Dawley rats 

(10/sex/group) to AN in drinking water at concentrations of 0, 35, 85, 210, or 500 ppm for 

90 days. Reported intakes of AN for males/females, respectively, were 0/0, 4/5, 8/10, 17/22, or 

38/42 mg/kg-day. Water consumption was decreased in a dose-related manner in both sexes, 

with females more affected than males. However, the lowest dose affecting males was not 

identified in the summary; in females exposed at 35 ppm, 9 of 26 measured intervals showed 

statistically significant decreases compared with controls. In the 210 and 500 ppm groups, there 

were significant decreases in water consumption, food consumption, and BW, but no information 

was provided as to the magnitude of these changes. Exposure to AN had no effect on 

hematology, clinical chemistry, or histopathologic findings; urinalysis results were also 

unaffected by treatment, except for an increase in specific gravity that was correlated with 

increasing dose. Apparently, a number of treatment-related effects was observed in the 85 ppm 

group, but neither their identity nor the magnitude of change were specified. The summary 
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provided by Quast (2002) did not provide sufficient detail to accurately identify NOAEL or 

LOAEL values from the study by Humiston et al. (1975) (as cited in Quast, 2002). 

 Szabo et al. (1984) evaluated the effect of subchronic oral exposure to AN on the 

structure and function of the adrenal gland and intestinal tract in rats. Female Sprague-Dawley 

rats (three to four per group) were exposed for 7, 21, or 60 days to AN in drinking water at 

concentrations of 0, 1, 20, 100, and 500 ppm, representing approximate daily doses of 0, 0.2, 4, 

20, and 100 mg/kg. Other groups of rats received equivalent doses of AN by gavage for the 

same duration. Water and food intakes were monitored continuously and BWs were recorded 

every fourth day. At the end of the studies, blood samples were taken to measure plasma 

corticosterone and aldosterone, and a complete necropsy was carried out on all survivors. The 

adrenals, thyroid, liver, and one kidney were weighed. Samples of liver, kidney, lung, brain, and 

the entire adrenal and thyroid glands were measured for levels of nonprotein sulfhydryls in tissue 

homogenates. Adrenals, “other” endocrine organs, stomach, duodenum, liver, kidney, lung, and 

heart were evaluated for histopathology. 

BWs were reduced by about 25% in rats exposed to 500 ppm in drinking water up to 

60 days, but no reduction in BW was observed in rats receiving the equivalent dose of 

100 mg/kg-day by gavage (Szabo et al.,1984). Water intake was reduced in rats exposed to 

500 ppm in drinking water but increased at the equivalent gavage dose. Adrenal weights were 

slightly lower than in controls in the 7- and 21-day exposure groups, but significant increases in 

relative adrenal weights were observed after 60 days of exposure to 500 ppm in drinking water or 

to ≥0.2 mg/kg-day by gavage. The kidneys were enlarged in rats exposed to 100 or 500 ppm AN 

in drinking water for 60 days or 500 ppm for 21 days. 

Histopathological lesions included adrenocortical hyperplasia in all rats exposed by 

gavage at ≥0.2 mg/kg-day for 60 days. Enlarged kidneys and hyperplasia of the gastric mucosa 

at the junction of the glandular stomach and forestomach was observed in rats exposed to 100 or 

500 ppm in drinking water for 21 or 60 days. No incidence data were provided for these lesions. 

Plasma corticosterone levels were significantly decreased by both 500 ppm AN in drinking water 

or by gavage in the 21-day study. Even the lowest concentration of 1 ppm AN by gavage 

resulted in a 50% reduction in corticosterone. Plasma aldosterone concentration was reduced, 

starting from 20 ppm AN. In the 60-day study, significant suppression of plasma corticosterone 

was observed after exposure to 100 or 500 ppm AN in drinking water and in all exposure levels 

given by gavage. 

Levels of nonprotein sulfhydryls (glutathione) were increased by 20–50% in the 7- and 

21-day studies but were significantly reduced by 20–30% in the adrenals after 60 days of gavage 

exposure to 4–60 mg/kg-day. Increases in nonprotein sulfhydryl concentrations in duodenal 

mucosa were observed in the 100 or 500 ppm AN exposure groups in the 7- and 21-day studies 

and in all doses after 60 days, but not in the control group of rats that received water by gavage. 

For the drinking water study, a NOAEL of 20 ppm (4 mg/kg-day) and a LOAEL of 100 ppm 
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(20 mg/kg-day) were identified for enlarged kidneys and increases in regional hyperplasia of the 

gastric mucosa in female rats exposed for 60 days. For the gavage study, no NOAEL was 

identified, but a LOAEL of 0.2 mg/kg-day was identified for adrenocortical hyperplasia in rats 

exposed for 60 days. 

In a separate experiment, Szabo et al. (1984) evaluated age-dependency in the sensitivity 

of Sprague-Dawley rats to the action of AN on the adrenals. Groups of weanling rats (40 g) and 

adult rats (190 g) were treated with 0, 0.002% (20 ppm), 0.01% (100 ppm), or 0.05% (500 ppm) 

of AN in drinking water for 21 days, or were given by the corresponding amount of AN by daily 

gavage for 21 days. The animals were sacrificed, and plasma and adrenals were collected as in 

the previous experiments. Young, immature rats treated with AN were found to have lower (up 

to 66%) levels of plasma corticosterone and aldosterone than adult rats. These differences were 

statistically significant with 0.01% AN given by gavage or 0.05% AN in drinking water. 

 Quast et al. (1975) exposed beagles (four/sex/group) to 0, 100, 200, and 300 ppm AN 

(purity >99%) in drinking water for 6 months; the reported calculated doses were approximately 

0, 10, 16, and 17 mg/kg-day in males, respectively, and 0, 8, 17, and 18 mg/kg-day in females, 

respectively. Dogs were evaluated daily for clinical signs and weighed weekly; food and water 

consumption were calculated from the consumption by groups of dogs penned together. Routine 

hematology examinations were conducted on all samples taken from all dogs 20 days before 

exposure and on days 83, 130, and 179. Blood and urine samples for standard biochemical 

analyses were collected from all dogs 8 days before exposure, on days 84, 135, and 176, and at 

termination (day 182 for males and day 183 for females). Serum samples were collected from all 

dogs on day 155 to determine total protein concentrations and evaluate the percentages of 

specific Igs by electrophoresis. Ophthalmic examinations were conducted pretest and at 85, 112, 

and 175 days. All dogs were subjected to gross necropsy at which time organ weights were 

recorded for brain, heart, liver, kidneys, and testes; a full set of tissues from all dogs was 

examined for histopathology. Samples of liver and kidney were analyzed for nonprotein free 

sulfhydryl content. 

 The following treatment-related effects were observed in dogs exposed to AN in drinking 

water for 6 months (Quast et al., 1975). No mortality was observed in the control or 100 ppm 

groups, but dogs exposed at 200 ppm (2/4 males and 3/4 females) and 300 ppm (3/4 males and 

2/4 females) either died prematurely or were euthanized in a moribund condition. Signs of 

toxicity manifested in these dogs included reduced consumption of food and water, decreased 

BW, roughened hair coat, and a nonproductive cough. These dogs subsequently exhibited 

lethargy, weakness, emaciation, respiratory distress, and terminal depression. Decreased water 

consumption was observed throughout the study in males at 300 ppm and sporadically in females 

at ≥200 ppm. Food consumption was reduced in males at 300 ppm and females at ≥100 ppm. A 

supplemental study was conducted on eight female dogs treated with 100 ppm AN for 5 weeks, 

and no reduction in food or water consumption was observed. 
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 Substantial reductions in BW were observed among dogs that died (200 and 300 ppm); 

group mean weights among surviving male and female dogs were not statistically significantly 

different from controls. RBC and Hb counts were reduced by 19–21% in males exposed to 

200 ppm for 83 days but not at later time points; females exposed at 300 ppm exhibited 22–26% 

decreases in RBC counts after 83 and 130 days of exposure. No treatment-related changes in 

hematology parameters were evident after 179 days of exposure. Exposure to AN had no effect 

on urinalysis, clinical chemistry, ophthalmoscopic examinations, nonprotein free sulfhydryl 

content in liver or kidney, or the electrophoretic behavior of serum proteins. Statistically 

significant alterations in organ weight, such as increases in relative kidney weights in males 

treated at 100 and 200 ppm, were not biologically significant (less than 10% change). 

Histopathologic changes were observed in the esophagus (focal erosions and/or ulcerations in the 

middle one-third, dilations, and thinning of the walls) and tongue (increased thickness of 

epithelium lining of the dorsal surface) of male and female dogs treated at 200 and 300 ppm. 

Lesions of the lung were attributed to parasitic nematode infection that was present in all dogs. 

In this study, a NOAEL of 100 ppm (8–10 mg/kg-day) and a LOAEL of 200 ppm (16–17 mg/kgday) were identified for early mortality and histopathological lesions of the esophagus and 

tongue in male and female dogs. 

In a comparative study of the neurotoxicity of nitriles, Gagnaire et al. (1998) 

administered AN (>99% purity) at doses of 0, 12.5, 25, or 50 mg/kg-day to male SpragueDawley rats (12/group plus 10 controls) by gavage in olive oil, 5 days/week for 12 weeks. BWs 

were measured weekly. After 3, 6, 9, and 12 weeks of treatment and after an 8-week recovery 

period (week 20), rats were evaluated for electrophysiological parameters, with testing occurring 

16 hours after dosing (or 48 hours for testing after weekends). Electrical stimulation of the tail 

nerve was used to assess four neurological properties, the motor conduction velocity (MCV), 

sensory conduction velocity (SCV), and amplitudes of the sensory and motor action potentials 

(ASAPs and AMAPs). 

One high-dose rat died during the first week of treatment, but no other mortality was 

observed. High-dose rats showed reduced BW gain that became significant after the fourth week 

of treatment, leading to a terminal BW 17% lower than in controls. BWs of mid-dose rats 

became significantly lower than controls after the fifth week, resulting in a terminal weight 

approximately 7% lower than controls (as estimated by visual inspection of the data graph); this 

weight change was not considered biologically significant. Five of 11 high-dose rats exhibited 

significant weakness of the hind limbs that somewhat improved during the recovery period. Rats 

exposed to AN showed acute signs of behavioral abnormalities, including salivation, locomotor 

hyperactivity, and fur wetting within 1 hour of dosing. Gagnaire et al. (1998) attributed these 

findings to cholinomimetic effects possibly caused by AN-induced changes in muscarinic 

acetylcholine receptors or by alterations in hepatic metabolism. Exposure to AN had no effect 

on MCV or AMAP except for a 40% increase in AMAP observed in high-dose rats at the 9-week 
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time point. The most consistent effect of AN was a significant reduction in SCV compared with 

that in controls (Table 4-23), ranging from 7.5 to 15% between weeks 6 and 12 (p < 0.05 to 

p < 0.001); this effect abated following the cessation of exposure, but a 10.6% reduction 

compared with controls (p < 0.001) was observed after 8 weeks of recovery (week 20). A 25% 

reduction in ASAP was also observed in high-dose rats at week 20, but no effect on this 

parameter was observed during the treatment period. A NOAEL of 25 mg/kg-day and a LOAEL 

of 50 mg/kg-day were identified in the study by Gagnaire et al. (1998), based on reduced BW 

and neurotoxic effects (weakness of the hind limbs and reduced SCV) in male rats exposed to 

AN by gavage. 

Table 4-23. Effect on SCV in male Sprague-Dawley rats exposed to AN via 

gavage for 12 weeks 

SCV (m/s)a

Group Exposure (weeks) Recovery

(mg/kg) 0 3 6 9 12 20

0 34.2 ± 0.7 43.2 ± 0.6 45.2 ± 1.3 48.4 ± 1.1 46.6 ± 0.8 53.8 ± 1.5 

12.5 34.9 ± 0.5 42.6 ± 0.9 45.7 ± 0.7 47.8 ± 0.7 46.7 ± 0.9 51.8 ± 0.9 

25 34.6 ± 0.8 40.0 ± 1.0 45.5 ± 0.6 46.0 ± 0.9 44.4 ± 0.9 51.3 ± 0.7 

50 35.8 ± 1.1 42.2 ± 1.1 41.8 ± 1.3b 44.0 ± 1.2c 39.8 ± 0.6c 48.1 ± 0.7c

aValues are means ± SDs, n = 12 for treated rats and n = 10 for controls. 

b

Statistically significant compared with controls (p < 0.05), as calculated by the authors. 

c

Statistically significant compared with controls (p < 0.001), as calculated by the authors. 

Source: Gagnaire et al. (1998). 

 In a comparative study on the effects of nine compounds related to acrylamide (Barnes, 

1970), AN was administered by gavage over a period of 7 weeks to six young adult albino rats of 

the Porton strain as 15 daily doses of 30 mg/kg, followed by 7 doses of 50 mg/kg, and finally

13 doses of 75 mg/kg. The time-adjusted average dose administered over the course of the study 

was 36 mg/kg-day. Rats were weighed weekly, and their gait and stance when walking on a 

sloping nonslippery surface including an ascent up a sloping wooden board were evaluated. 

Treated rats were also held by the tail in front of a sloping bar, and tested for the ability to grasp

the bar with the front paws, and then grasp it with the hind feet, a reflex typically lost early in 

rats with peripheral neuropathies. No data were provided for this experiment, but the study 

author reported that there was no evidence of adverse effects. 

 In a recent study that explored the neurobehavioral effects of AN in rats (Rongzhu et al., 

2007), male Sprague-Dawley rats (10/group) were exposed to 0, 50, or 200 ppm AN in drinking 

water. The study authors estimated AN doses to be 0, 4.03, and 13.46 mg/kg-day. Three 

neurobehavioral tests, including the open field test, rotarod test, and spatial water maze, were 

conducted to evaluate locomotor activities, motor coordination, and learning and memory, 
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respectively, prior to initiation of exposure and at 4, 8, and 12 weeks of exposure. Thiocyanate 

levels in urine were measured in a minimum of five rats from each group at week 12 and were 

reported to be 2.79, 6.10, and 25.03 mg/g creatinine, respectively. 

 Beginning from the sixth week of AN administration, three rats in the 50 ppm AN group 

and five rats in the 200 ppm AN group showed behavioral changes. The coat appearance in all 

treated rats was soiled, and the main changes were head twitching, trembling, circling, 

backwards pedaling, and decreased home-cage activities. The two treatment groups also showed 

less BW gain than the control group. In the open field test, there were no significant differences 

in start-up latency among the exposed and unexposed groups. The 200 ppm group consistently 

had higher locomotor activity than the control group, from pretreatment to 12 weeks of exposure. 

There were also no changes in the number of rearing and grooming episodes. Therefore, there 

were no uniform changes in exploration and locomotion. In the rotarod test, the maximal and the 

total and falling latency in the 50 and 200 ppm groups were significantly decreased in a doseand time-dependent manner. In the spatial water maze test, rats in the 200 ppm group had 

significantly increased training time and training duration, compared with the control and 

50 ppm groups. However, these two parameters in the exposed groups returned to close to 

control level at the end of the experiment. Rongzhu et al. (2007) suggested that this reversible 

phenomena may be caused by tolerance. The study authors concluded that oral exposure to AN 

induced neurobehavioral alterations. The neurochemical mechanisms need to be further 

investigated. The LOAEL for neurobehavioral alterations is 4 mg/kg-day. 

 In a range-finding study for a 2-year bioassay (see Section 4.2.1.2), the National 

Toxicology Program (NTP) (2001) treated B6C3F1 mice (10/sex/group) with 0, 5, 10, 20, 40, or 

60 mg/kg-day AN (purity >99%) by gavage in water, 5 days/week for 14 weeks; adjusted for 

intermittent exposure (5 days/7 days), the intakes were 0, 3.6, 7.1, 14.3, 28.6, and 42.9 mg/kgday. Clinical findings were recorded on day 8 and once weekly thereafter. BWs were recorded 

before treatment, weekly, and at study termination. Necropsies were performed on all animals, 

at which time organ weights were recorded for heart, right kidney, liver, lung, spleen, right testis, 

and thymus. Hematology analysis was conducted on all mice surviving at the end of the study. 

Complete histopathologic analyses were conducted on all control mice and those treated with 

40 and 60 mg/kg-day; males receiving 20 mg/kg-day were also examined. At the end of the 

study, 10 males/group in the groups receiving 0, 5, 10, and 20 mg/kg-day were selected for 

reproductive evaluations; the left cauda, left epididymis, and left testis were weighed and sperm 

samples were evaluated for sperm counts and motility. Also, 10 females/group in the groups 

receiving 0, 10, 20, and 40 mg/kg-day were evaluated for vaginal cytology (estrous cycle and 

stage length) in the last 12 days of the study before termination. 

 The following effects were observed in mice exposed by gavage to AN. Aside from one 

control male at week 9, there were no deaths at exposures up to and including 20 mg/kg-day. 

Mortality at the two highest doses comprised 9/10 males and 3/10 females at 40 mg/kg-day and 
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all mice treated at 60 mg/kg-day. All deaths occurred on the first day, except for one male in the 

40 mg/kg-day group. Slight (2–8%) decreases in BW in treated mice compared with controls 

were not biologically significant. Survivors (seven females and one male) receiving 40 mg/kgday exhibited lethargy and abnormal breathing immediately after dosing “for several days” but 

then appeared to develop tolerance to AN. 

 Sporadic, statistically significant alterations in hematological parameters included 

reductions in platelet counts by 20% in males at 20 mg/kg-day, in leukocyte and lymphocyte 

counts (~30% in males at 20 mg/kg-day and ~37% in females at 40 mg/kg-day), and in Hb and 

RBC counts by 10% in females at 40 mg/kg-day; other statistically significant changes of 

doubtful biological significance in females included reductions in RBC counts by 4% in groups 

treated with 5–20 mg/kg-day and in hematocrit by 6% in the 40 mg/kg-day group. Some of these 

hematological effects may have been secondary to stomach ulceration observed in some mice. 

 Absolute and relative heart weights were increased by 20 and 30%, respectively, in males 

at 20 mg/kg-day. The absolute weights of the left cauda epididymides were increased by 15% in 

groups exposed at 10 and 20 mg/kg-day. However, no histopathological findings were reported 

in these organs. The only treatment-related lesions were in the forestomach of females at 

40 mg/kg-day: 4/7 with chronic active inflammation (associated with hyperplasia) and 5/7 with 

focal epithelial hyperplasia. Two females in this group exhibited focal ulceration of the 

forestomach associated with the hyperplasia. No other treatment-related histopathology was 

observed. Exposure to AN produced no effects on sperm motility in males at ≤20 mg/kg-day. 

There were no differences in vaginal cytology parameters in females at ≤40 mg/kg-day. A 

NOAEL of 20 mg/kg-day and a LOAEL of 40 mg/kg-day were identified in the NTP (2001) 

bioassay, based on hyperplastic lesions in the forestomach of female mice. 

4.2.1.2. Chronic Studies 

 The chronic toxicity and/or carcinogenicity of AN have been evaluated in drinking water 

or gavage studies in rats and a gavage study in mice (Johannsen and Levinskas, 2002a, b; Quast, 

2002; Biodynamics, 1980a, b; Quast et al., 1980a). Studies by Gallagher et al. (1988), Maltoni et 

al. (1988, 1977), and Bigner et al. (1986) were cancer bioassays that did not investigate 

nonneoplastic lesions caused by oral exposure to AN. In addition, a three-generation 

reproductive toxicity assay involving up to 46 weeks of exposure to AN (Friedman and Beliles, 

2002; Litton Bionetics, 1992) provided evidence of AN carcinogenicity. These studies are 

discussed below. 

4.2.1.2.1. Quast (2002) and Quast et al. (1980a). Quast (2002) and Quast et al. (1980a) 

conducted a 2-year toxicity and carcinogenicity study in Sprague-Dawley rats (48/sex/group) 

exposed to AN (purity >99%) in drinking water at concentrations of 35, 100, or 300 ppm; groups 

of 80/sex receiving untreated drinking water served as controls. Additional interim-sacrifice 
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groups of 10/sex/dose were exposed for 1 year and analyzed under the same protocol as the main 

study. The reported intakes of AN were 0, 3.4, 8.5, and 21.3 mg/kg-day for male rats and 0, 4.4, 

10.8, and 25.0 mg/kg-day for female rats. Rats were observed daily for clinical signs of toxicity 

and were weighed and examined monthly for palpable masses. Food and water consumptions 

were determined for 30 rats/sex/group weekly for the first 3 months of the study and for 1 week 

during each of the following months: 4, 5, 6, 7, 9, 11, 12, 15, 18, 21, and 24. Hematology 

examinations and urinalysis were conducted on 10 rats/sex in the control and the highest dose 

group on days 45, 87, 180, and 355. Additional hematology examinations were conducted on 

10 rats/sex from all groups on days 544 (males) and 545 (females) and at study termination on 

day 724 (males and females); an additional urinalysis was conducted on 10 rats/sex from all 

groups on day 181 to evaluate a dose response for increased urine specific gravity observed 

previously at the highest dose group. Clinical chemistry examinations were conducted on 

10 rats/sex from the control and highest dose groups on days 46 and 356, on 10 rats/sex from all 

groups on days 88, 180, and 550, and on all survivors on day 746. All rats, whether dying 

prematurely, sacrificed in a moribund condition, or sacrificed on schedule, were subjected to a 

gross necropsy, which included an ophthalmologic examination. Necropsies of rats on scheduled 

sacrifice included organ weight determinations for brain, heart, liver, kidneys, and testes. 

Complete histopathologic examinations were conducted for rats in the control and 300 ppm 

groups in the 1-year interim and 2-year studies, and, based on those results, a set of 22 tissues 

was examined microscopically in nearly all rats exposed at 35 and 100 ppm; tumors and other 

lesions identified at gross necropsy were also examined microscopically. 

Noncancer results

Exposure to AN in drinking water reduced survival, BW, and consumption of food and 

water by Sprague-Dawley rats in a dose-related manner (Quast, 2002; Quast et al., 1980a). In 

male rats exposed at 300 ppm, survival was significantly reduced compared with controls 

(p < 0.05), beginning at 16 months, and none survived after 22 months; survival in other treated 

male groups was not significantly different from controls. In female rats, exposure at 300, 100, 

and 35 ppm resulted in significantly reduced survival beginning at 10, 12, and 18 months, 

respectively, with no high-dose females surviving past month 22; at 24 months, survival was 25, 

8.3, 2.1, and 0% for the control and low- to high-dose groups, respectively. The magnitude, time 

of onset, and duration of significantly lower BWs in exposed rats compared with controls were 

dose related. Only the 17–22 and 17–18% decreases observed in males and females, 

respectively, at 300 ppm were biologically significant. Reductions only reached ~8–9% in the 

100 ppm groups and ~6–9% in the 35 ppm groups. 

The study authors mentioned that BW comparisons near the end of the study tended to be 

confounded by geriatric changes, few surviving rats, and excessive tumor growth in exposed rats. 

Food intake (g/rat/day) was significantly lower in 100 and 300 ppm groups compared with 
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controls beginning during the first week of the study and only in females at 35 ppm. 

Significantly lower feed intake values for males and females, respectively, compared with 

controls were measured on 12/24 and 16/24 occasions at 300 ppm, 8/24 and 11/24 times at 

100 ppm, and 9/24 times in females only at 35 ppm. The largest difference in high-dose rats was 

a 25% reduction of feed intake in males after 6 months and a 27% reduction in females after 

9 months. Feed intakes during the last weeks of the study were not significantly different among 

the different groups. 

Water intake was reduced during the first 10 days by 36% in males and 38% in females 

exposed to 300 ppm AN and remained significantly lower for all 26 measurements throughout 

the study. Significantly lower water consumption was also measured 24/26 times for males and 

23/26 times for females at 100 ppm and 13/26 times for males and 21/26 times for females at 

35 ppm. Male and female rats in the 100 and 300 ppm dose groups showed a lack of normal 

grooming later in the study. In addition, signs of nervous system dysfunction (erratic 

movements, trembling, circling, and limb weakness) were observed in the higher dose groups 

rats in the absence of end-stage kidney disease or pituitary tumors. These signs of nervous 

system dysfunction when they occurred in controls were correlated with end-stage kidney 

disease or pituitary tumors and occurred more frequently in males than in females. The study 

authors were unable to detect microscopic tumors or lesions that would correlate with the 

observed clinical signs. 

 AN had no primary effect on hematological parameters, except for lowered RBC counts 

associated with blood loss from ulcerated tumors or nutritional anemia during the later stages of 

the study. The only effect of AN on urinalysis was a slight, but statistically significant increase 

(1.3–3.0%) in urine specific gravity noted for 300 ppm group males at five time points (45–

355 days) and females at all six time points (45–545 days). Significant increase in urine specific 

gravity was also observed in 100 ppm male and female rats on day 181 and day 544 (females 

only). The lack of significant effect in treated males on days 544 and 724 was attributed by 

Quast (2002) to higher incidence of advanced chronic renal disease in controls that resulted in an 

inability to concentrate urine normally. All 300 ppm male and female rats were dead by 

day 724. No toxicological significant alterations were observed in clinical chemistry parameters 

or in absolute or relative organ weights in the few treated rats surviving at termination. 

 Lesions of the forestomach were the most prominent nonneoplastic histopathologic 

effects observed in Sprague-Dawley rats (Quast, 2002; Quast et al., 1980a). In the 1-year interim 

sacrifice, the only treatment-related noncancer lesion was squamous cell hyperplasia of the 

forestomach, which was observed in 10/10 males and 9/10 females in the 300 ppm group and 

4/10 males and 7/10 females in the 100 ppm group. At 2 years, the incidence of forestomach 

lesions (hyperplasia and/or hyperkeratosis of the squamous epithelium) was dose related and 

significantly elevated in males at ≥100 ppm and in females at ≥35 ppm; incidences were 15/80, 

15/47, 44/48, and 45/48 for males and 20/80, 23/48, 41/48, and 47/48 for females in the 0, 35, 
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100, and 300 ppm dose groups, respectively. Minimal progressive chronic nephropathy was also 

elevated in females treated at ≥100 ppm; incidences were 37/80, 24/48, 37/48, and 38/48 for 

control to high-dose groups. In males, minimal progressive nephropathy was elevated only in 

the 300 ppm group. However, significant increase in severe progressive nephropathy was 

observed in males in the 35 and 100 ppm groups; incidences were 11/80, 13/47, 13/48, and 10/48 

for control to high-dose groups. Gliosis of the brain, with or without perivascular cuffing, was 

significantly increased in the low- and middle-dose females (8/48 and 13/48, respectively, vs. 

2/80 in controls), although the incidence (5/48) did not reach statistical significance in the highdose females. In males, it was present in one rat exposed at 100 ppm and three rats exposed at 

200 ppm. A NOAEL was not identified in this drinking water study. A LOAEL of 4.4 mg/kgday was identified for increases in forestomach lesions, decreased survival, and gliosis in brain in 

female rats exposed to 35 ppm AN in drinking water. Table 4-24 summarizes incidence of 

nonneoplastic lesions in Sprague-Dawley rats exposed to AN in drinking water for 2 years. 

Table 4-24. Incidence of nonneoplastic lesions in Sprague-Dawley rats 

exposed to AN in drinking water for 2 years 

AN in drinking water (ppm) 0 35 100 300 

Male rats Dose (mg/kg-d) 0 3.4 8.5 21.3 

Forestomach hyperplasia and/or hyperkeratosis 15/80 (19%) 15/47 (32%) 44/48 (92%)a 45/48 (94%)a 

Kidneys—chronic progressive nephropathy

Severity: minimal 10/80 (12%) 4/47 (9%) 7/48 (15%) 16/48 (33%)a 

 moderate 10/80 (12%) 5/47 (11%) 10/48 (21%) 16/48 (33%)a 

 severe 11/80 (14%) 13/47 (28%)a 13/48 (27%)a 10/48 (21%) 

Female rats Dose (mg/kg-d) 0 4.4 10.8 25.0 

Forestomach hyperplasia and/or hyperkeratosis 20/80 (25%) 23/48 (48%)a 41/48 (85%)a 47/48 (98%)a 

Kidneys—chronic progressive nephropathy

Severity: minimal 37/80 (46%) 24/48 (50%) 37/48 (77%)a 38/48 (79%)a 

 moderate 17/80 (21%) 13/48 (27%) 8/48 (17) 5/48 (10%) 

 severe 13/80 (16%) 9/48 (19%) 1/48 (2%) 4/48 (8%)

Brain—gliosis and perivascular cuffing 2/80 (3%) 8/48 (17%)a 13/48 (27%)a 5/48 (10%) 

a

Statistically significant at p < 0.05. 

Source: Quast (2002). 
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Cancer results

The drinking water study by Quast (2002) and Quast et al. (1980a) provided evidence of 

the carcinogenicity of AN in male and female Sprague-Dawley rats. Tumor findings in the 

1-year sacrifices included forestomach papillomas in males: 1/10 at 100 ppm and 7/10 at 

300 ppm. In females, the occurrence was 5/10 at 300 ppm. Also observed after 1 year of 

exposure were microscopic tumors of the CNS (brain) in 2/10 males and 4/10 females at 

100 ppm and 1/10 males and 2/10 females at 300 ppm. Carcinoma of Zymbal gland and benign 

and malignant tumors of the mammary gland, also observed after 1 year of exposure, were 

considered by the study authors to be related to treatment. 

Histopathologic examinations after 2 years of exposure revealed statistically significant 

and dose-dependent increase in incidences of several types of tumors (Table 4-25). Squamous 

cell papillomas or carcinomas of the forestomach were significantly elevated in males and 

females exposed at ≥100 ppm. Carcinomas of Zymbal gland were significantly increased in 

males at 300 ppm and in females at ≥35 ppm. 

Table 4-25. Selected tumor incidences in response to AN administered to 

Sprague-Dawley rats in drinking water for up to 2 years 

Incidence of tumor formation

Male rats Female rats

Exposure concentration (ppm) 

0 35 100 300 0 35 100 300

Dose (mg/kg-d)

Tissue type 0 3.4 8.5 21.3 0 4.4 10.8 25.0

Astrocytomas only 1/80 8/47a 19/48 23/48a 1/80 17/48a 22/48a 24/48a

Combined astrocytomas/glial 

cell proliferation 1/80 12/47a 22/48a 30/48a 1/80 20/48a 25/48a 31/48a

Tongue 

(papilloma or carcinoma) 1/80 2/47 4/48 5/48a 0/80 1/48 2/48 12/48a

Forestomach 

(papilloma or carcinoma) 0/80 2/47 23/48a 39/48a 1/80 1/48 12/48a 30/48a

Zymbal gland 

(carcinoma or adenoma) 3/80 4/47 3/48 16/48a 1/80 5/48a 9/48a 18/48a

Small intestine (mucous 

cystadenocarcinoma) NDb ND ND ND 0/80 1/48 4/48a 4/48a 

Mammary gland (malignant) ND ND ND ND 1/80 1/48 3/48 10/48a

Mammary gland 

(malignant or benign) ND ND ND ND 58/80 42/48a 42/48a 35/48 

a

Significantly different from controls (p < 0.05), as calculated by the study authors. 

bND = not determined. 

 

Sources: Quast (2002); Quast et al. (1980a). 
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An increase in papillomas or carcinomas of the tongue in males at 300 ppm was also 

considered to be related to exposure. Increases were also observed in the incidences of 

malignant tumors of the mammary gland. The incidence of malignant or benign mammary 

tumors was significantly increased in the low- and high-dose females but decreased in the highdose group. Quast (2002) noted that the lower mammary tumor incidence in the 300 ppm group 

was likely due to the marked early mortality in this group, despite the earlier occurrence of these 

tumors. The incidence of mammary tumors increased considerably in controls during the latter 

portion of the study, when few high-dose females survived. 

Two diagnostic categories—focal or multifocal glial cell proliferation (suggestive of 

early tumors), and focal or multifocal glial cell tumor (astrocytomas)—were used by Quast 

(2002) for tumors present in the brain or spinal cord. These diagnoses were mutually exclusive 

and primarily based on the size of the lesion, with glial cell proliferation a smaller-sized lesion 

than astrocytoma. For enumerating the astrocytomas of the CNS, the incidence of glial 

proliferation was combined with the incidence of astrocytomas and was elevated in both males 

and females in all exposed groups (Table 4-25). 

 Distribution of astrocytomas in the various regions of nervous tissue in male and female 

Sprague-Dawley rats is shown in Table 4-26. No tumors were found from 0 to 12 months in any 

location in either male or female rats. As noted by Quast (2002), the sections of cerebral cortex 

contained most of the tumors because of the cortex’s larger size. However, astrocytomas were 

also found in the cerebellum, brain stem, and spinal cord in male and female rats. Smaller-sized 

lesions (glial cell proliferation) had a distribution similar to astrocytomas. 
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Table 4-26. Histopathologic location of astrocytomas in the CNS of male 

Sprague-Dawley rats administered AN in drinking water for 2 years 

Location of astrocytomasa

Male rats Female rats 

Age at sacrifice

Cerebral 

cortex Cerebellum 

Brain 

stem 

Spinal 

cord 

Cerebral 

cortex Cerebellum

Brain 

stem 

Spinal 

cord

0 ppm

13–18 mos 0/23 0/23 0/23 0/22 0/11 0/11 0/10 0/11 

19–24 mos 1/43 0/43 0/43 0/43 0/48 0/48 0/47 0/46 

Terminal kill 0/7 0/7 0/7 0/7 1/20 0/20 0/20 0/20 

35 ppm

13–18 mos 2/14 0/14 1/14 0/14 1/13 0/13 1/13 0/13 

19–24 mos 5/26 1/26 1/25 0/26 5/30 2/29 6/30 0/30 

Terminal kill 1/5 0/5 1/5 0/5 3/4 0/4 2/4 0/4 

100 ppm

13–18 mos 3/16 1/16 2/16 1/16 5/19 2/20 1/19 1/19 

19–24 mos 13/26 0/26 6/26 1/26 12/24 1/24 9/24 1/24

Terminal kill 2/5 0/5 0/5 0/5 0/1 0/1 1/1 0/1 

300 ppm

13–18 mos 10/26 0/26 2/26 1/26 11/23 2/23 4/23 3/22 

19–24 mos 11/18 2/18 4/18 2/18 8/11 2/11 3/11 2/11 

Terminal kill 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0 

aNo astrocytomas were found in any locations from 0 to 12 mos. 

Sources: Quast (2002); Quast et al. (1980a). 

4.2.1.2.2. Johannsen and Levinskas (2002a) and Biodynamics (1980a): drinking water study. 

Johannsen and Levinskas (2002a) and Biodynamics (1980a) carried out another 2-year drinking 

water study of AN in Sprague-Dawley rats. Groups of 100 rats/sex/group were exposed to 0, 1, 

or 100 ppm AN (100% purity) in drinking water; as calculated by the study authors, average 

daily doses were 0, 0.09, and 8.0 mg/kg-day , respectively, for males and 0, 0.15, and 

10.7 mg/kg-day, respectively, for females. Ten rats/sex/group were selected from these groups 

for interim evaluations at 6, 12, and 18 months and at study term, leaving a maximum of 

70/sex/group for lifetime exposure. Although the study was designed to last 24 months, because 

of high mortality among high-dose rats, surviving males were necropsied after 22 months and 

females at 19 months to ensure that a sufficient number of animals would be available for 

clinical and pathological analyses. Rats were observed daily for morbidity and mortality and 

examined and palpated weekly to detect growths. All rats received ophthalmoscopic 

examinations in the period before treatment started and again at the time of necropsy. 

BWs were recorded weekly for the first 14 weeks, biweekly between weeks 16 and 26, 

and monthly thereafter. Food intake and water consumption were recorded over 3-day periods 
134 DRAFT - DO NOT CITE OR QUOTE 

for about 25 rats/sex/group at the same intervals at which BWs were recorded. Ten rats/sex from 

each group were selected for hematological, clinical chemical, and urinalysis examinations at 6, 

12, and 18 months and at study termination (22 months for males and 19 months for females). 

All rats, whether dying prematurely, sacrificed in a moribund condition, or sacrificed on 

schedule, were subjected to a gross necropsy that included preservation of 40 tissues and organs, 

gross lesions, and tissue masses for possible histopathological examination. At interim and 

terminal necropsies, weights were recorded for selected organs (brain, pituitary, adrenal, gonads, 

heart, kidney, and liver) in 10 rats/sex/group. Interim gross necropsies were performed after 6, 

12, and 18 months on 10 rats/sex/group and on the remaining rats at termination. For the 

scheduled interim and terminal sacrifices, complete histopathologic examinations were 

conducted on 10 rats/sex from the control and 100 ppm groups; on all other rats, a limited set of 

tissues was examined microscopically that included potential target organs (brain, ear canal, 

spinal cord, and stomach) and any tissue masses observed at necropsy. 

Noncancer results 

Treatment-related noncancer effects were observed in Sprague-Dawley rats exposed to 

AN for 19–22 months (Johannsen and Levinskas, 2002a; Biodynamics, 1980a). Statistically 

significant increases in early deaths were observed in high-dose male and female rats after 

10 months and became particularly severe during the last 5 months of the study. Reduction in 

survival compared with controls was not significant in high-dose males at termination 

(22 months) but was significant in high-dose female rats terminated at 19 months. Food and 

water consumption in high-dose rats was lower than in controls throughout the study. Reduction 

in mean BW compared with controls was observed in high-dose males and females throughout 

the study (a significant 10% reduction in males and an insignificant 8% reduction in females at 

term). Slight reductions in hematocrit, RBC count, and Hb values compared with controls were 

observed during the study in high-dose groups but were generally not statistically significant; 3–

6% reductions in Hb values in high-dose males were statistically significant at the 6- and 

18-month interim time points. Exposure to AN had no effect on clinical chemistry or urinalysis 

parameters or ophthalmoscopic examinations; there were no treatment-related clinical signs 

except for some neurological symptoms at the time of terminal necropsy in a few rats with 

astrocytomas of the brain or spinal cord. The only significant treatment-related effects on organ 

weights were lower absolute pituitary weights in high-dose males at 12 months and in females at 

termination. Significant increase in mean relative kidney and liver weights observed in highdose males and females were considered by the study authors to reflect the reduced BWs rather 

than target organ effects, since this effect did not occur at other study intervals. 

Statistically significant increases in nonneoplastic lesions related to exposure to AN 

included renal transitional cell hyperplasia in high-dose females at termination (Table 4-27). 

Significant increase in squamous metaplasia of the uterus was observed in high-dose females at 
135 DRAFT - DO NOT CITE OR QUOTE 

12 months compared with controls (5/10 vs. 0/10), and in low-dose females at 18 months (3/3 vs. 

2/10). This effect was not significant in high-dose females at 18 months (4/10), and was not 

observed at terminal sacrifice. 

Table 4-27. Incidence of nonneoplastic lesions in Sprague-Dawley rats 

exposed to AN in drinking water for 2 years 

AN in drinking water (ppm) 0a 1 100 

Male rats Dose (mg/kg-d) 0 0.09 8.0 

Kidney transitional cell hyperplasia 1/15 2/18 0/12

Forestomach squamous cell hyperplasia 

 Incidence at terminationb14/19 24/26 14/15 

 Severity: mild 5 4 1 

 moderate 7 14c 8c

 severe 2 6c 5c

 Forestomach squamous cell hyperplasia 

 Incidence in early deaths or unscheduled sacrifices 36/46 31/37 37/42 

 Severity: mild 9 10 4 

 moderate 17 15 18c

 severe 10 6 15c

Female rats Dose (mg/kg-d) 0 0.15 10.7 

Kidney transitional cell hyperplasia 2/27 1/18 8/14d

Forestomach squamous cell hyperplasia 

 Incidence at terminationb39/48 40/57 17/17 

 Severity: mild 12 8 4 

 moderate 18 25 9 

 severe 9 7 4 

 Incidence in early deaths or unscheduled sacrifices 14/20 6/12 33/43 

 Severity: mild 4 1 1 

 moderate 7 2 21d

 severe 3 3 11d

aDrinking water control. 

bMales exposed for 22 mos, females for 19 mos. 

c

Significantly different from controls as calculated by authors (p ≤ 0.05). 

d

Significantly different from controls as calculated by authors (p ≤ 0.01). 

Sources: Johannsen and Levinskas (2002a); Biodynamics (1980a). 

In addition, the incidence of squamous cell hyperplasia was increased in high-dose males 

and females at terminal sacrifice and in spontaneous deaths in high-dose groups (Table 4-27). 

The severity of squamous cell hyperplasia of the forestomach was significantly greater 

(characterized as moderate or severe) than in controls in male rats at termination after exposure 

to 1 or 100 ppm AN; a significant increase in severity in high-dose males was also observed at 

12 months (not shown) but not at 18 months. Increased incidences in forestomach hyperplasia 
136 DRAFT - DO NOT CITE OR QUOTE 

characterized as moderate or severe were also observed in high-dose rats of both sexes that died 

prematurely or were sacrificed in a moribund condition. A NOAEL for nonneoplastic effects 

was not identified in this study. A LOAEL of 1 ppm (0.09 mg/kg-day) was identified for 

increased severity of squamous cell hyperplasia of the forestomach in male Sprague-Dawley rats 

exposed to AN in drinking water for 2 years (22 months). 

Cancer results 

Significant increases in the cumulative incidences of neoplasms of the CNS, ear canal 

(Zymbal gland), and forestomach were observed in Sprague-Dawley rats exposed to 100 ppm 

AN in drinking water for 2 years (Johannsen and Levinskas, 2002a; Biodynamics, 1980a). 

Statistically significant, dose-dependent increases were observed for astrocytomas of the brain in 

both sexes and astrocytomas of the spinal cord in females. The astrocytomas varied from 

discrete solid masses to localized areas of diffuse infiltrations of neoplastic cells. In addition, 

adenomas of Zymbal gland (ear canal) in both sexes, carcinomas of Zymbal gland in both sexes, 

and squamous cell papillomas of the forestomach in females were increased. Intestinal 

adenocarcinomas were also found in high-dose male and female rats (see Table 4-28). 
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Table 4-28. Selected tumor incidences in Sprague-Dawley rats exposed to AN 

in drinking water for up to 2 years 

Tumor incidencea

Male rats Female rats

Exposure concentration (ppm)

0 1 100 0 1 100

Dose (mg/kg-d)

Tissue type

0 0.09 7.98 0 0.15 10.7

CNS 

Brain (astrocytomas) 2/78 3/75 23/77b 0/79 1/80 32/77b

Spinal cord (astrocytomas) NDc ND ND 0/76 0/79 7/78b

Total 2/78 3/75 23/77b 0/79 1/80 39/78b

Zymbal gland 

Carcinomas 1/80 0/71 14/83b 0/79 0/75 7/78b

Adenomas 0/80 0/71 5/83 1/79 0/75 5/78 

Total 1/80 0/71 19/83b 1/79 0/75 12/78b

Forestomach 

Carcinomas 0/78 1/78 3/77 0/80 0/79 0/79 

Papillomas 3/78 2/78 8/77 1/80 4/79 7/79b

Total 3/78 3/78 11/77b 1/80 4/79 7/79b

Intestine 

Adenocarcinomas 0/40 0/34 2/41 0/78 0/79 2/70 

aDenominators are calculated from the total number of animals examined (as reported in Table 4 of Johannsen and 

Levinskas, 2002a) minus the animals scheduled for sacrifice at 6 and 12 mos. Thus, incidences are for animals 

scheduled for the 18-mo, spontaneous deaths and terminal sacrifices (22 mos for males and 19 mos for females). For 

Zymbal gland tumors in the 100 ppm male, one carcinoma and adenoma occurred in the 12-mo sacrifice; therefore, 

adjustment to the denominator was only made for the 6-mo sacrifice. 

b

Significantly different from controls (p < 0.05), Fisher’s exact test. 

cND = no data collected. 

Sources: Johannsen and Levinskas (2002a); Biodynamics (1980a). 

Johannsen and Levinskas (2002a) reported that most of the tumors occurred in rats after 

12 months of exposure. CNS astrocytomas were not detected at the 6- or 12-month interim 

sacrifices (at which about 10 rats of each gender were sacrificed from each group). However, 

brain astrocytomas and Zymbal gland carcinomas were detected in high-dose females as early as 

after 6 months of exposure. One each of Zymbal gland carcinoma, adenoma, and squamous cell 

carcinoma of the forestomach was detected at the 12-month interim sacrifice in high-dose males. 

This finding was consistent with findings in the other drinking water bioassay with SpragueDawley rats, indicating that some male and female rats exposed to 300 ppm AN developed 

tumors after only 7–12 months of exposure (Quast, 2002). Mammary gland carcinomas were 

detected in female rats scheduled for the terminal sacrifice but not in male or female rats 

scheduled for sacrifice at 6, 12, or 18 months. Incidences of female rats (scheduled for the 
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terminal sacrifice) with mammary gland carcinomas, however, did not show exposure-related 

increases: 13/80, 4/79, and 14/79 for the control, 1 ppm, and 100 ppm female groups, 

respectively. 

4.2.1.2.3. Johannsen and Levinskas (2002a) and Biodynamics (1980b): gavage study. In 

parallel to the chronic drinking water study in Sprague-Dawley rats, Johannsen and Levinskas 

(2002a) and Biodynamics (1980b) conducted a lifetime study in which groups of SpragueDawley rats (100 rats/sex/group) received 0, 0.1, or 10 mg/kg-day AN by gavage in water for 

7 days/week. The doses were selected to match the daily intake levels in the drinking water 

study. The schedule and protocols used in the gavage study for observations of clinical signs, 

measurements of food and water consumption and BW, clinical biochemistry analyses, and gross 

necropsy and histopathologic analyses were identical to those in the drinking water study. 

Ingestion of 10 mg/kg-day AN resulted in increased mortality after 12 months and was 

significantly higher in males at termination and in females beginning at month 14 compared with 

controls. The study was terminated after 20 months of exposure because of high treatmentrelated deaths, with a decreased survival of about 30 and 50% in males and females compared 

with their respective controls. BWs showed a significant reduction of about 6% in high-dose 

males compared with controls, beginning on week 12 and reaching 13% by termination; there 

were no BW effects in exposed females. 

Exposure to AN had no effect on food consumption in either sex or on water 

consumption in males; high-dose females had slightly increased water consumption during the 

first 12 months only. Small reductions in hematocrit, Hb, and RBC counts were observed in 

high-dose males at 12 and 18 months and reached statistical significance at terminal sacrifice 

(hematocrit, 15%; Hb, 19%; and RBC counts, 18%). Significant increases in absolute mean liver 

weights were observed in the high-dose males and females and low-dose males at the 18-month 

interval. Relative liver weights for high-dose males and females were significantly increased in 

most intervals and might be reflective of lower BWs. Absolute and relative kidney weights of 

high-dose males were increased significantly at 18 months and increased insignificantly in both 

males and females at study term. The adrenal gland of high-dose males was the organ that 

showed the most significant weight increase of 43% at termination. 

Noncancer results

Nonneoplastic histopathological effects were observed in male and female SpragueDawley rats exposed to 10 mg/kg-day AN by gavage for 20 months (Table 4-29). A significant 

increase in epidermal inclusion cysts was observed in male and female rats, most notably in 

animals dying spontaneously. Significant increases in renal transitional cell hyperplasia were 

observed in high-dose females at 12-month sacrifice and in high-dose males after 18 months. In 

addition, there was a significant increase in the severity of squamous cell hyperplasia of the 
139 DRAFT - DO NOT CITE OR QUOTE 

forestomach in high-dose males and females. This effect was most noticeable among rats dying 

early or at scheduled sacrifices after at least 12 months. High-dose rats showed a significant 

elevation in the incidence of moderate or severe hyperplasia. In this gavage study, a NOAEL of 

0.1 mg/kg-day and a LOAEL of 10 mg/kg-day were identified for increased severity of 

forestomach lesions (squamous cell hyperplasia) in male and female rats. 

Table 4-29. Incidence of nonneoplastic lesions in Sprague-Dawley rats 

exposed to AN by gavage for 20 months 

Dose (mg/kg-d) 0

a

 0.1 10 

Male rats 

Skin: Epidermal inclusion cysts (in spontaneous deaths) 2/59 4/68 8/56b 

Kidney: Transitional cell hyperplasia (18 mos) 3/11 0/8 10/10c 

Heart: Cardiomyopathy (18 mos) 3/11 No data 8/10b 

Forestomach: Squamous cell hyperplasia 

 Incidence at terminal sacrifice 10/10 No data 8/10 

 Severity: mild 2 0 

 moderate 5 2 

 severe 3 6 

 Incidence in early deaths or unscheduled sacrifices 46/58 46/67 49/56 

 Severity: mild 18 11 2 

 moderate 19 26 13c

 severe 9 10 34c

Female rats 

Skin: Epidermal inclusion cysts (in spontaneous deaths) 0/10 No data 4/10b

Kidney: Transitional cell hyperplasia (12 mos) 0/10 0/1 4/10b 

Heart: Cardiomyopathy (18 mos) 4/10 No data 3/10 

Forestomach squamous cell hyperplasia 

 Incidence at terminal sacrifice 8/10 No data 9/10 

 Severity: mild 1 1 

 moderate 5 3 

 severe 2 5 

 Incidence in early deaths or unscheduled sacrifices 47/57 63/69 53/59 

 Severity: mild 12 12 0 

 moderate 23 38 14c

 severe 12 13 39c

aWater vehicle control. 

b

Significantly different from controls as calculated by the study authors (p < 0.05). 

c

Significantly different from controls as calculated by the study authors (p ≤ 0.01). 

Sources: Johannsen and Levinskas (2002a); Biodynamics (1980a). 
140 DRAFT - DO NOT CITE OR QUOTE 

Cancer results

The carcinogenic effects of AN on Sprague-Dawley rats exposed via gavage were similar 

to those in the drinking water studies (Johannsen and Levinskas, 2002a; Biodynamics, 1980b). 

Significant increase in tumor incidences were observed in male and female rats dosed with 

10 mg/kg-day and included carcinomas of Zymbal gland, astrocytomas of the brain, and tumors 

of the squamous epithelium of the forestomach (papillomas and carcinomas in males and 

papillomas in females) (Table 4-30). Adenocarcinomas of the intestine were also observed in 

high-dose male rats that died or were killed after at least 12 months of exposure. Increases in 

carcinomas of the mammary gland were observed in high-dose females that died prematurely. 

Table 4-30. Cumulative incidence of tumors in response to AN administered 

to Sprague-Dawley rats by gavage for up to 2 years 

Tumor incidencea

Male rats (mg/kg-d) Female rats (mg/kg-d)

Tissue type 0 0.1 10 0 0.1 10

Brain astrocytomas 2/80 0/79 16/77b 1/80 2/78 17/80b

Spinal cord astrocytomas 0/74 0/73 1/77 0/80 0/75 1/79 

Zymbal gland papillomas 0/76 0/73 3/76 0/65 0/74 0/74 

Zymbal gland carcinomas 1/76 0/73 10/76b 0/65 0/74 9/74b

Zymbal gland adenomas 0/76 1/73 5/76b 1/65 0/74 5/74 

Forestomach carcinomas 0/79 0/77 18/79b 0/79 0/79 1/79 

Forestomach papillomas 2/79 6/77 19/79b 2/79 4/79 14/79b

Intestine adenocarcinomas 0/80 0/80 6/80b 0/40 0/40 1/41 

Mammary gland carcinomas 0/80 0/78 0/80 5/80 6/80 21/80b

aDenominators are calculated from the total number of animals examined (as reported in Table 4 of Johannsen and 

Levinskas, 2002a) minus the animals scheduled for sacrifice at 6 and 12 mos; thus, incidences are for animals 

scheduled for the 18-mo, spontaneous death, and terminal sacrifices (20 mos). 

b

Significantly different from controls (p < 0.05), as calculated by the study authors. 

Sources: Johannsen and Levinskas (2002a); Biodynamics (1980a). 

4.2.1.2.4. Johannsen and Levinskas (2002b); Biodynamics (1980c). A 2-year drinking water 

assay was conducted in F344 rats (Johannsen and Levinskas, 2002b; Biodynamics, 1980c). 

Groups of rats (100/sex/group) were given AN (100% purity) in drinking water at concentrations 

of 0, 1, 3, 10, 30, or 100 ppm; two groups of 100/sex served as untreated controls. The study 

authors reported the equivalent average daily doses of AN as 0, 0.1, 0.3, 0.8, 2.5, and 8.4 mg/kgday for males and 0, 0.1, 0.4, 1.3, 3.7, and 10.9 mg/kg-day for females. Rats were observed 

twice daily for overt signs of toxicity and examined and palpated weekly to detect growths. 

Ophthalmoscopic examinations were carried out before testing and again at the time of necropsy. 

BWs were recorded weekly for the first 14 weeks, biweekly between weeks 16 and 26, and 

monthly thereafter. Food intake and water consumption were recorded over a 3-day period at the 
141 DRAFT - DO NOT CITE OR QUOTE 

same intervals that BWs were recorded for about 25 rats/sex/group for all groups. At intervals of 

6, 12, and 18 months and at study termination (26 months for males and 23 months for females), 

10 rats/sex/group from each exposed and control group were sacrificed for clinical pathology and 

microscopic evaluation. 

At 6, 12, and 18 months and at termination, 10 rats/sex from the 100 ppm group and 

5 rats/sex from each of the control groups were selected for hematology, clinical chemistry, and 

urinalysis examinations. Lower dose group rats were evaluated as needed to determine possible 

dose-response relationships. All rats, whether dying prematurely, sacrificed in a moribund 

condition, or sacrificed on schedule, were subjected to a gross necropsy that included 

preservation of 40 tissues and organs, all gross lesions, and tissue masses for possible 

histopathologic examination. At interim and terminal sacrifice, weights were recorded for 

selected organs (brain, pituitary, adrenal, gonads, heart, kidney, and liver) for 10 rats/sex from 

treated groups and 5 rats/sex from each control group. For the interim sacrifices, complete 

histopathologic examinations were conducted on 10 rats/sex from the 100 ppm group and 

5 rats/sex from the two control groups. Potential target organs (e.g., brain, ear canal, spinal cord,

and stomach), gross lesions, and tissue masses were examined microscopically in all study 

animals. All surviving females were terminated after 23 months and all males after 26 months. 

Terminal necropsies included complete microscopic examinations for 10 rats/sex exposed to 

100 ppm AN and 5/sex/group for the two control groups. Potential target organs and suspicious 

lesions were examined in all animals in other dose groups. 

Noncancer results

Treatment-related noncancer effects were observed in F344 rats exposed to AN in 

drinking water for 2 years (Johannsen and Levinskas, 2002b; Biodynamics, 1980c). Statistically 

significantly early deaths (p < 0.05), compared with controls, were observed in male and female 

rats exposed to 100 ppm, beginning after 14 months of exposure. A statistically significant 

decrease in survival was also observed in female rats exposed to 30 ppm but not to 10 ppm, 

beginning after 18 months of exposure. Exposure to AN did not result in any overt neurological 

impairments or ophthalmoscopic findings. 

Statistically significant decrease in BWs (~12% lower than controls, p < 0.01) were 

observed in male and female rats exposed to 100 ppm AN. A statistically significant decrease in 

BWs of less than 5% was found in male rats exposed to 30 ppm AN and was not biologically 

significant. Total food consumption (g/week) was reduced compared with controls in rats 

exposed at 100 ppm (more prominently in female rats after week 13), but consumption on a BW 

basis (g/kg) for both 100 ppm male and female rats was not significantly different from that for 

controls. Total water consumption (mL/week) was significantly lower in the 100 ppm male and 

female rats compared with controls. No differences in food and water consumption from 

controls were found for groups exposed to ≤30 ppm AN. Hematological analyses revealed slight 
142 DRAFT - DO NOT CITE OR QUOTE 

reductions in Hb, hematocrit, and RBC counts in the 100 ppm group, beginning at 12 months, 

with Hb significantly lower in female rats at 12 and 18 months (13% at 18 months). Hematocrit 

in 100 ppm female rats was 4% lower at 12 months. However, no statistically significant 

differences from controls were noted at termination. 

Serum alkaline phosphatase levels were significantly elevated by 80 and 65% (p < 0.05), 

respectively, in 100 ppm females at 18 and 23 months. Results of clinical chemistry for the 

30 and 10 ppm groups were not reported. However, the study authors noted that female rats in 

these dose groups also showed significant elevation of this enzyme. A significant 33% increase 

in SGPT was also observed in 100 ppm female rats at 18 months but not at other intervals. The 

only treatment-related urinalysis finding was a slight increase in urine specific gravity in 

100 ppm males at 18 and 26 months. No significant dose-related changes were observed for 

absolute organ weights; elevations in relative organ weights (kidney, brain, liver, adrenal, testis, 

heart, and pituitary in females) sporadically observed at 100 ppm at intervals throughout the 

study were attributed by the study authors to lower BWs rather than target-organ toxicity. 

Unlike Sprague-Dawley rats exposed to AN in drinking water (see above, Quast [2002]), 

F344 rats did not show forestomach lesions at the 6- or 12-month sacrifices. In rats exposed for 

periods >1 year, treatment-related nonneoplastic effects were observed in the forestomach 

(Table 4-30) and skin. The incidence of squamous cell hyperplasia or hyperkeratosis of the 

forestomach was elevated in male and female rats exposed to 3, 10, and 30 ppm but not to 

100 ppm. Johannsen and Levinskas (2002b) suggested that, because the lesions were observed 

more frequently in late surviving animals, the reduced survival in 100 ppm group may have been 

the reason that no significant increase was observed for that dose group. Because these 

forestomach lesions were not observed in rats examined during the 6- or 12-month sacrifices, no 

such incidence data are listed in Table 4-31. An increase in epidermal inclusion cysts of the 

skin, observed in 4/50 male rats treated at 100 ppm but in no other group, was also considered by 

the study authors to be treatment related. A NOAEL of 1 ppm (0.1 mg/kg-day) and a LOAEL of 

3 ppm (0.3 and 0.4 mg/kg-day for males and females, respectively) were identified for increases 

in squamous cell lesions (hyperplasia and/or hyperkeratosis) of the forestomach in male and 

female F344 rats exposed to AN in drinking water for 2 years. 
143 DRAFT - DO NOT CITE OR QUOTE 

Table 4-31. Incidences of nontumorous lesions in F344 rats exposed to AN 

in drinking water for 2 years 

AN in drinking water (ppm) 0a

 1 3 10 30 100 

Male rats Dose (mg/kg-d) 0 0.1 0.3 0.8 2.5 8.4 

Forestomach squamous cell hyperplasia or 

hyperkeratosisb

11/159 3/80 18/75c 13/80d 17/80c 9/77 

Foci of cellular alteration in liver 7/94 5/31 11/51 8/45 14/50c 6/68 

Epidermal inclusion cysts 0/61 0/12 0/12 0/11 0/17 4/50d 

Chronic nephropathy, bilateral 118/149 57/58d 62/64c 52/54d 57/60d 42/62 

Atrophy of seminiferous tubules, bilateral 150/172 72/75d 68/84 64/74 78/78c 64/87 

Female rats Dose (mg/kg-d) 0 0.1 0.4 1.3 3.7 10.9 

Forestomach squamous cell hyperplasia or 

hyperkeratosisb

4/156 2/80 16/80c 23/74c 13/80c 5/74 

Foci of cellular alteration in liver 1/84 2/20 4/39d 3/49 0/40 1/70 

Chronic nephropathy, bilateral 52/68 10/19 21/26 20/29 23/26 18/50 

aDrinking water control.

bMales exposed for 18–26 mos, females for 18–23+ mos; excludes rats sacrificed at 6 or 12 mos. These incidences 

were further adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. Rats 

dying during this time period were determined from page 6 of Appendix H and Table 1 in Biodynamics (1980c) 

and Table 8 in Johannsen and Levinskas (2002b). Unscheduled deaths between 0 and 12 mos in the study occurred 

in two female controls, two males at 3 ppm, three females at 10 ppm, and three males and three females at 100 ppm.

c

Significantly different from vehicle control as calculated by study authors (p ≤ 0.01). 

d

Significantly different from vehicle control as calculated by study authors (p ≤ 0.05). 

Sources: Johannsen and Levinskas (2002a); Biodynamics (1980a). 

Other microscopic findings included increase in chronic nephropathy and atrophy of 

seminiferous tubules, which were significant at 1 ppm. However, the study authors did not 

consider these effects to be related to treatment, but rather to be due to the sample selection 

procedure that only tissues showing questionable or suspicious lesions were selected for 

microscopic examination for the intermediate dose groups (1–30 ppm), resulting in the selection 

of tissues from more aged animals. 

Cancer results 

Increases in tumor incidences (Table 4-32) were observed in multiple organs, following 

chronic exposure of F344 rats to AN in drinking water (Johannsen and Levinskas, 2002b; 

Biodynamics, 1980c). No tumors were detected in rats sacrificed after only 6 months of 

exposure. One female rat exposed to 100 ppm for 12 months had an adenocarcinoma of the 

mammary gland that the study authors considered to be possibly related to treatment. Treatmentrelated tumors, appearing at the 18-month interim sacrifice, included brain astrocytomas 

(one/sex/group) in male and female rats exposed to 30 and 100 ppm, squamous cell papillomas 

of the ear canal (Zymbal gland) in 2/9 males at 100 ppm and 1/9 females at 30 ppm, and 

squamous cell carcinomas of the latter organ in one female at 100 ppm. AN-related neoplastic 
144 DRAFT - DO NOT CITE OR QUOTE 

lesions were observed at terminal sacrifice in the brain, spinal cord, forestomach, ear canal 

(Zymbal gland), and mammary gland (females only). Significant dose-related elevations in 

astrocytomas were observed in the brains of male and female rats exposed to 30 and 100 ppm 

and in the spinal cord of male rats exposed to 100 ppm (see Table 4-32). Dose-related increases 

in squamous cell adenomas/carcinomas of the ear canal (Zymbal gland) were observed in males 

exposed to 30 and 100 ppm and in females at 10–100 ppm. Increased incidences of squamous 

cell papillomas or carcinomas of the forestomach, observed in males exposed to 3 and 10 ppm 

and in both sexes exposed to 30 ppm, were considered by the study authors to be likely treatment 

related despite the lack of a dose response. Fibroadenomas of the mammary gland were slightly 

increased in females treated with 10 and 30 ppm. Other lesions considered by the study authors 

to be possibly treatment related included a single case of squamous cell carcinoma of the salivary 

gland in one male at 100 ppm and squamous cell papillomas of the tongue in female rats 

(one/group) exposed to 10 and 30 ppm. 
145 DRAFT - DO NOT CITE OR QUOTE 

Table 4-32. Selected tumor incidences in F344 rats exposed to AN in 

drinking water for 2 years 

AN in drinking water (ppm) 0a

 1 3 10 30 100 

Male ratsb Dose (mg/kg-d) 0 0.1 0.3 0.8 2.5 8.4 

Brain astrocytoma Totalc

 Adjustedd 

2/200c 

2/160d 

2/100 

2/80 

1/100 

1/78 

2/100 

2/80 

10/99e

10/79e 

21/99e

21/76e 

Spinal cord astrocytoma 1/196 

1/156 

0/99 

0/79 

0/92 

0/70 

0/98 

0/78 

0/99 

0/79 

4/93f

4/70f 

Ear canal (Zymbal gland) squamous cell 

papilloma/adenoma and carcinoma 

2/189 

1/147 

1/97 

1/76 

0/93 

0/73 

2/88 

0/67 

7/94e

2/71e 

16/93e

14/68e 

Forestomach squamous cell papilloma/carcinoma 0/199 

0/159 

1/100 

1/80 

4/97f

4/78f 

4/100f

3/80f 

4/100f

4/80f 

1/101 

1/77 

Mammary gland fibroadenoma 2/48 1/4 2/7 2/12 0/7 2/45 

Mammary gland carcinoma 1/48 0/4 0/7 0/12 0/7 0/45 

Female ratsb Dose (mg/kg-d) 0 0.1 0.4 1.3 3.7 10.9 

Brain astrocytoma 1/199 

1/157 

1/100 

1/80 

2/101 

2/80 

4/95 

4/75 

6/100e

6/80e 

23/98e

23/76e 

Spinal cord astrocytoma 0/197 

0/155 

0/97 

0/78 

0/99 

0/79 

1/92 

1/72 

0/96 

0/77 

1/91 

1/69 

Ear canal (Zymbal gland) squamous cell 

papilloma/adenoma and carcinoma 

0/193 

0/157 

0/94 

0/73 

2/92 

0/73 

4/90e 

0/70e 

5/94e

2/73e 

10/86e

8/62e 

Forestomach squamous cell papilloma/carcinoma 1/199

1/157 

1/100 

1/80 

2/100 

2/79 

2/97 

2/77 

4/100f

4/80f 

2/97 

2/75 

Mammary gland fibroadenoma 12/65 

12/156 

5/14 

5/80 

6/14 

6/80 

9/16e

8/79

10/22f

9/80 

9/49 

9/73 

Mammary gland carcinoma 1/65 

3/156 

2/14 

4/80 

0/14 

0/80 

0/16 

1/78 

3/22 

3/80 

2/49 

6/73 

aDrinking water control. 

bMales exposed for 26 mos, females for 23+ mos. 

cTotal cumulative number of rats with lesion. 

dThe denominators for incidences excluded rats from the 6- and 12-mo sacrifices and rats that died before the 

appearance of the first tumor for each of three tumor sites: CNS, Zymbal gland, and forestomach. The termination 

history reports in Appendix C and the individual animal histopathology reports in Appendix H of the Biodynamics 

(1980b) report were examined to determine time of death and tumor occurrence for each of the F344 rats. Times of 

first detection of tumors were 419 d for forestomach tumors, 495 d for CNS tumors, and 475 d for Zymbal gland 

tumors. Due to the limited number of mammary glands examined in most groups, the adjusted denominators 

represented the number of animals that were exposed for more than 12 mos for each group; mammary gland tumor 

incidences are for animals scheduled for the 18-mo and terminal sacrifices. 

e

Significantly different from vehicle control as calculated by study authors (cumulative only) (p ≤ 0.01). 

f

Significantly different from vehicle control as calculated by study authors (cumulative only) (p ≤ 0.05). 

Sources: Johannsen and Levinskas (2002a); Biodynamics (1980a). 

4.2.1.2.5. NTP (2001). NTP (2001) evaluated the toxicity and carcinogenicity of AN (>99% 

purity) given by gavage in water to B6C3F1 mice (50/sex/dose) at doses of 0, 2.5, 10, and 

20 mg/kg-day, 5 days/week for 2 years. Adjusted for discontinuous exposure (5 days/7 days), 

the intakes were 0, 1.8, 7.1, and 14.3 mg/kg-day. The doses were chosen based on results of the 
146 DRAFT - DO NOT CITE OR QUOTE 

14-week assay described in Section 4.2.1.1. Mice were observed twice daily for clinical signs 

that were recorded on day 29, every 4 weeks, and at study termination. BWs were recorded 

before the start of the exposure period, then every 4 weeks, and at study termination. Five male 

and five female mice were evaluated at 2 weeks and 3, 12, and 18 months for urinalysis 

parameters. All mice were subjected to gross necropsies and complete histopathologic 

examinations. 

Noncancer results 

Survival was significantly reduced in male and female mice treated with 20 mg/kg-day; 

38/50, 42/50, 39/50, and 14/50 males and 39/50, 32/50, 39/50, and 23/50 females survived to 

104–105 weeks with increasing dose. Despite a tendency for BWs in high-dose mice to be 

slightly lower compared with controls after 30 weeks of treatment, AN had no significant effect 

on terminal BWs; no treatment-related clinical signs were observed. 

Exposure to AN significantly increased the incidences of nonneoplastic lesions in male 

and female mice compared with control mice (Table 4-33). Statistically significant increases in 

the incidences of mild focal or multifocal epithelial hyperplasia of the forestomach were 

observed in males treated with 10 or 20 mg/kg-day and in focal or multifocal epithelial 

hyperplasia of the forestomach in females treated with 20 mg/kg-day. The hyperplastic lesions 

were often accompanied by focal hyperkeratosis and occasionally associated with chronic 

inflammation. The incidence of hyperkeratosis (diffuse or focal) of the forestomach was 

statistically significantly elevated in males treated at 20 mg/kg-day. AN-treated males showed a 

higher incidence of hyperplasia of the Harderian gland, but only the increase observed at 

10 mg/kg-day was statistically significantly different from the control. No significant increase 

was found in treated females (Table 4-33). Statistically significant elevations were observed in 

the incidences for ovarian cysts in females treated with 2.5–20 mg/kg-day and for ovarian 

atrophy in females treated with 10–20 mg/kg-day; for both ovarian lesions, the highest 

incidences were observed at 10 mg/kg-day. A NOAEL was not identified for noncancer effects 

in this gavage study. A LOAEL of 1.8 mg/kg-day (adjusted for continuous exposure) was 

identified for increased incidence of ovarian cysts in female mice. A NOAEL of 1.8 mg/kg-day 

and a LOAEL of 7.1 mg/kg-day were identified for increased incidences of forestomach 

hyperplasia in male mice. 
147 DRAFT - DO NOT CITE OR QUOTE 

Table 4-33. Incidence and severity of nonneoplastic lesions in B6C3F1 mice 

exposed by gavage to AN for 2 years 

Adjusted dose (mg/kg-d)a

 0b 1.8 7.1 14.3 

Males

Number of male mice examined 50 50 50 50 

Forestomach hyperkeratosis, diffuse/focal 2c (2.5)d 3 (2.0) 7 (1.7) 12f(1.8) 

Forestomach epithelial hyperplasia, focal 2 (3.0) 4 (2.3) 8e (2.0) 9f(1.9) 

Harderian gland hyperplasia 1 (2.0) 4 (2.3) 7e (3.4) 4 (2.3) 

Females

Number of female mice examined 50 50 50 50 

Forestomach hyperkeratosis, diffuse/focal 2 (1.5) 1 (2.0) 2 (2.0) 4 (2.0) 

Forestomach epithelial hyperplasia, focal, or multifocal 2 (1.5) 2 (3.0) 5 (1.8) 7e (1.6) 

Harderian gland hyperplasia 5 (3.0) 4 (3.3) 6 (2.2) 8 (3.5) 

Ovarian atrophy 6 (3.0) 8 (3.9) 45f (4.0) 40f (4.0) 

Ovarian cyst 12 (2.3) 20e (2.3) 27f (2.1) 19e (2.1) 

aDoses administered 5 d/wk. 

bVehicle control. 

cNumber of mice with lesion. 

dAverage severity grade of lesions in affected mice: 1 = minimal, 2 = mild, 3 = moderate, 4 = marked. 

e

Significantly different from vehicle control as calculated by authors (p ≤ 0.05). 

f

Significantly different from vehicle control as calculated by authors (p ≤ 0.01). 

Source: NTP (2001). 

Cancer results 

In mice exposed to AN, treatment-related carcinogenic effects (Table 4-34) were 

observed in the forestomach, Harderian gland, and, less consistently, lung and ovary of treated 

female mice (NTP, 2001). Histopathologic examination revealed significantly increased 

incidences of forestomach squamous cell papillomas and in overall incidence of papillomas or 

carcinomas in male and female mice treated with 10 or 20 mg/kg-day. Forestomach squamous 

cell carcinomas alone were significantly increased in males at ≥10 mg/kg-day and in females at 

20 mg/kg-day. Incidences of Harderian gland adenoma and adenomas or carcinomaswere 

significantly elevated in males at ≥2.5 mg/kg-day and in females at ≥10 mg/kg-day. The overall 

incidence of alveolar/bronchiolar adenomas or carcinomas was significantly elevated in females 

treated at 10 mg/kg-day but not at the highest dose. Increase in benign or malignant granulosa 

cell tumor of the ovary was observed in females treated with 10 mg/kg-day AN. However, the 

increase was not statistically significant. Significant positive trends (p ≤ 0.001) were observed in 

both male and female mice for the incidences of forestomach squamous cell papilloma or 

carcinoma and Harderian gland adenoma or carcinoma; there was also a significant positive 

trend (p = 0.029) for alveolar/bronchiolar adenoma or carcinoma in treated females. An inverse 

relationship between tumor latency and dose was observed for forestomach squamous cell 

papillomas or carcinomas in females and for Harderian gland adenomas or carcinomas in males. 
148 DRAFT - DO NOT CITE OR QUOTE 

Table 4-34. Incidences of selected neoplastic lesions in B6C3F1 mice exposed 

by gavage to AN for 2 years 

Adjusted Dose (mg/kg-d)a

 Controlb 1.8 7.1 14.3 

Malesc

Number of mice examined 50 50 50 50 

Forestomach 

Squamous cell papilloma (includes multiple) 3 4 19d 25d 

Squamous cell carcinoma 0 0 8d 9

d 

Squamous cell papilloma or carcinoma 3 4 26e 32e 

Harderian gland 

 Adenoma (includes bilateral) 5 16d 24d 27d 

Carcinoma 1 1 4 3 

Adenoma or carcinoma 6 16f 27e 30e 

Femalesc

Number of mice examined 50 50 50 50 

Forestomach 

Squamous cell papilloma (includes multiple) 3 6 24d 19d 

Squamous cell carcinoma 0 1 1 11d 

Squamous cell papilloma or carcinoma 3 7 25e 29e 

Harderian gland 

Adenoma (includes bilateral) 10 10 25d 23d 

Carcinoma 1 0 3 2 

Adenoma or carcinoma 11 10 26e 25e 

Lung 

Alveolar/bronchiolar adenoma or carcinoma 6 6 14g 9 

Ovary 

Benign or malignant granulosa cell tumor 0 0 4 1 

aDoses administered 5 d/wk. 

bVehicle control. 

cNumber of mice with tumor. 

d

Significantly different from vehicle control as calculated by authors (p ≤ 0.01). 

e

Significantly different from vehicle control as calculated by authors (p ≤ 0.001). 

f

Significantly different from vehicle control as calculated by authors (p = 0.014). 

g

Significantly different from vehicle control as calculated by authors (p = 0.039). 

Source: NTP (2001). 

4.2.1.2.6. Gallagher et al. (1988). In a cancer bioassay, groups of 20 male Sprague-Dawleyderived CD rats were exposed to 0, 20, 100, or 500 ppm AN in drinking water for 2 years 

(Gallagher et al.,1988). As calculated from the reported AN concentration and average daily 

drinking water consumption data, the intakes of AN were 0, 1.5, 7.1, and 28 mg/kg-day. Rats 

were weighed weekly, and feed intake and water consumption were measured for 1 week each 

month. All rats, whether dying prematurely or sacrificed at termination, were subjected to a 
149 DRAFT - DO NOT CITE OR QUOTE 

complete gross necropsy. Tissues exhibiting gross lesions and a selection of organs (liver, 

stomach, adrenal, kidney, heart, brain, pituitary, and lung) were examined for histopathology. 

Significantly reduced survival compared with controls was observed in the high-dose 

group after 1 year of exposure but not in the other treatment groups. The last high-dose rat died 

shortly before the scheduled termination. BWs were significantly reduced in high-dose rats after 

8 months and in mid-dose rats after 16 months; compared with terminal BWs of the control 

group, reductions of >50% at 500 ppm and >20% at 100 ppm were estimated from the data 

graph. Exposure to AN had no effect on food consumption, but water consumption was reduced 

in a dose-related fashion (by 7.5, 11.3, and 30% in the low- to high-dose groups). A NOAEL of 

1.5 mg/kg-day and a LOAEL of 7.1 mg/kg-day were identified for reduced BW in rats exposed 

to AN for 2 years. This study was limited as to its usefulness for noncancer risk assessment 

because few tissues were evaluated for histopathology and noncancer histopathology was not 

reported. 

Gallagher et al. (1988) reported dose-related increases for the incidences of tumors of the 

forestomach and ear canal (Zymbal gland). Four of 20 high-dose rats (20%) had papillomas of 

the squamous epithelium of the forestomach, a tumor type not observed in the other groups. 

Squamous carcinomas of Zymbal gland were observed in 1/20 (5%) mid-dose rats and 

9/20 (45%) high-dose rats but not in low-dose rats or controls. This study provided evidence of 

the carcinogenicity of AN to the forestomach and Zymbal gland in male rats. Limitations of the 

study in evaluation of AN carcinogenicity included small group sizes, lack of testing in females, 

and only limited tissues were evaluated in gross and histopathological examination. 

4.2.1.2.7. Bigner et al. (1986). In an interim (18-month) report of a 2-year drinking water study 

(Bigner et al., 1986), F344 rats were exposed to AN at targeted concentrations of 0 ppm 

(51 males and 49 females), 100 ppm (50 rats/sex), and 500 ppm (two subgroups, with a total of 

197 males and 203 females). One group of the 500 ppm rats, 147 males and 153 females, was 

allocated for studies of morphology, tumor biology, and karyotyping, leaving the remaining rats 

for studies of comparative survival and tumor incidences. By using reference average BWs for 

F344 rats in a chronic-duration study and an allometric equation deriving drinking water 

consumption from BW (U.S. EPA, 1988), the average daily doses of AN were calculated as 0, 

12.9, and 64.5 mg/kg-day for males and 0, 14.8, and 74.2 mg/kg-day for females. Rats were 

observed twice daily for neurological signs and death and were weighed weekly. Complete 

gross necropsies were conducted on all rats. Brains were evaluated for tumors using light and 

electron microscopy. The only endpoints related to noncancer effects reported for this study 

were mortality, BW, and clinical signs. Incomplete quantitative data were provided for 

mortality, which was reported to show dose-response effect in both sexes, occurring earlier in 

100 and 500 ppm females than in males. A total of 215 high-dose rats died between month 6 and 

18, whereas only “a few” male and female controls were reported to have died by month 18. No 
150 DRAFT - DO NOT CITE OR QUOTE 

quantitative results were provided for the magnitude or statistical significance of BW reductions 

that affected high-dose male rats by the third week and high-dose females “slightly” later. BW 

reductions in the mid-dose group occurred in males after 2 months and females sometime during 

the second year. The incidences of neurological clinical signs (paralysis, head tilt, circling, and 

seizures) were dose related, affecting a total of 45/400 rats treated at 500 ppm, 4/100 rats at 

100 ppm, and 0/100 controls exposed for 12–18 months. The reported data were insufficient to 

accurately identify a NOAEL or LOAEL for noncancer effects in this study. A final report of 

this study was not located. 

 In 215 rats in the 500 ppm group that died between months 6 and 18, the types of tumors 

frequently found included s.c. papillomas, papillomas of the forestomach, and tumors in Zymbal 

gland, but no incidence data were provided for these lesions (Bigner et al., 1986). A statistically 

significant increase in tumors of the brain bearing similarity to astrocytomas was observed in rats 

exposed to 500 ppm AN, with 49 primary brain tumors observed among the 215 rats dying 

between months 6 and 18; incidences in other treatment groups were not reported. The tumors 

were observed mostly in the cerebral cortex (about 75%) and also in the brain stem and 

cerebellum. When the brain tumors were classified according to size, 10/49 of these tumors 

were larger than 5 mm, 28/49 were between 1 and 5 mm in diameter, and 11/49 were detected 

only microscopically. Although this study provided support for the carcinogenic effect of AN at 

multiple sites in rats, the lack of numerical results rendered it inadequate for the purpose of 

quantifying cancer risk. 

4.2.1.2.8. Maltoni et al. (1988, 1977). Maltoni et al. (1988, 1977) reported a cancer bioassay 

(designated BT203) in which groups of Sprague-Dawley rats (40/sex) received 5 mg/kg AN by 

gavage in olive oil, 3 days/week for 52 weeks; a control group of 75/sex received olive oil alone 

on the same schedule. After the exposure period, rats were maintained without further treatment 

for the rest of their natural lives (the study ending on week 131). Rats were examined 3 times 

daily for their general health status and were subjected to a clinical examination for gross 

changes every 2 weeks. Rats were weighed every 2 weeks during the first year and monthly 

thereafter. All rats were examined by gross necropsy. All tissues with gross lesions and a 

limited set of 12 tissues/organs from each rat were examined microscopically. No statistically 

significant increases in tumors were observed in treated rats in this study. However, slight 

decrease in tumor latency or increase incidence were observed for some types of tumors 

identified in other studies on AN. For example, a carcinoma of Zymbal gland was noted in 

1/40 exposed males (latency 84 weeks) and 1/75 control females (latency 90 weeks). Papillomas 

and acanthomas of the forestomach were observed in 1/40 exposed males (latency 92 weeks), 

4/40 exposed females (average latency 97.5 weeks), and 1/ 75 control females (latency 

54 weeks). Maltoni et al. (1977) recognized the increase in forestomach tumors as treatment 

related. Gliomas (a category that includes astrocytomas) appeared in 1/40 treated females 
151 DRAFT - DO NOT CITE OR QUOTE 

(latency of 33 weeks), 2/75 control females (average latency 104 weeks), and 1/74 control males 

(latency 98 weeks). The major limitation of this study as a cancer bioassay was the relatively 

short exposure period and the small number of animals in each group. The dose was also low for 

a single exposure group study. 

4.2.1.2.9. Friedman and Beliles (2002); Litton Bionetics (1992). In a three-generation 

reproductive toxicity study in Sprague-Dawley rats, Friedman and Beliles (2002) and Litton 

Bionetics (1992) provided further evidence of the possible carcinogenicity of AN (methods and 

reproductive/developmental findings of this study are presented in Section 4.3.2). In this study, 

15 males and 30 females per dose level (F0 parents) were exposed to 0, 100, and 500 ppm AN in 

drinking water for 100 days prior to mating for 6 days. As calculated by the study authors, the 

concentrations were equivalent to doses of 0, 11, and 37 mg/kg-day for males and 0, 20, and 

40 mg/kg-day for females. A subset of F0, F1, and F2 females underwent two cycles each of 

breeding, then were held for a further 20 weeks after weaning of the second litter prior to 

termination. 

Considering each generation separately, F1b female breeders in the 500 ppm group 

showed statistically significant increased incidences of brain and Zymbal gland tumors, while 

increased incidences of tumors in F0 or F2b female breeders in the 100 or 500 ppm groups 

compared with controls were consistent with the F1b responses, but not statistically significant 

(Table 4-35). These were relatively small groups, however, with low power to detect responses 

as high as 10% statistically significant. Across all of the generations, there was a statistically 

significant increasing trend in both tumor types, supporting the conclusion that exposure to AN 

for up to 51 weeks at 100 or 500 ppm in drinking water was associated with increased tumor 

incidence in female Sprague-Dawley rats. 
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Table 4-35. Incidence of tumors in female Sprague-Dawley rats exposed to 

AN in drinking water for up to 46 weeks 

Tumor incidence in rats

Brain astrocytomas Zymbal gland

Exposure concentration (ppm) 

0 100 500 0 100 500

Dose (mg/kg-d)

Generation 0 20 40 0 20 40

F0 0/19 1/20 2/24 0/19 0/20 2/24 

F1b 0/20 1/19 4/17a 0/20 2/19 3/17a

F2b 0/20 1/20 1/20 0/20 0/20 3/20 

Total 0/59b 3/59 7/61a 0/59b 2/59 8/61a

a

Significantly different from controls (p < 0.05), as calculated by the authors. 

b

Statistically significant by Cochran-Armitage trend test, p < 0.01. 

Sources: Friedman and Beliles (2002); Litton Bionetics (1992). 

 Table 4-36 summarizes the noncancerous effects observed in chronic oral studies of AN 

in rats and mice. Table 4-37 summarizes the cancerous effects observed in chronic oral studies 

of AN in rats and mice. 

Table 4-36. Summary of chronic oral toxicity studies of AN: noncancer 

effects in rats and mice 

Strain 

number/sex 

Exposure 

route/ 

durationa

 Doses Effects 

NOAEL/ 

LOAELa References Comments 

Rats 

F344 

100/sex/group 

Unexposed 

controls = 

200/sex 

Drinking 

water/ 

2 yrs 

M: 0, 0.1, 0.3, 

0.8, 2.5, 

8.4 mg/kg-d; 

F: 0, 0.1, 0.4, 

1.3, 3.7, 

10.9 mg/kg-d 

Squamous cell 

hyperplasia/ 

hyperkeratosis of 

the forestomach; 

decreased 

survival in highdose groups, 

increase in 

epidermal 

inclusion cysts of 

the skin 

NOAEL = 

0.1 mg/kg-d; 

LOAEL = 

0.3 mg/kg-d 

(M) 

0.4 mg/kg-d (F)

Johannsen and 

Levinskas 

(2002b); 

Biodynamics 

(1980c) 

10 rats/sex/group 

were taken from 

exposed and 

control groups for 

interim sacrifice at 

6, 12, and 18 mos 
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Table 4-36. Summary of chronic oral toxicity studies of AN: noncancer 

effects in rats and mice 

Strain 

number/sex 

Exposure 

route/ 

durationa

 Doses Effects 

NOAEL/ 

LOAELa References Comments 

SpragueDawley 

100/sex/group

Drinking 

water: 

22 months 

(M); 

19 months 

(F) 

M: 0, 0.09, 

8.0 mg/kg-d; 

F: 0, 0.15, 

10.7 mg/kg-d 

Squamous cell 

hyperplasia of 

the forestomach, 

decreased 

survival in highdose groups, 

reduction in 

absolute/relative 

pituitary weight 

(F) 

LOAEL = 

0.09 mg/kg-d 

(M) 

Johannsen and 

Levinskas 

(2002a); 

Biodynamics 

(1980a) 

10 rats/sex/group 

were taken from 

exposed and 

control groups for 

interim sacrifice at 

6, 12, and 18 mos 

SpragueDawley 

100/sex/group

Gavage/ 

20 months 

0, 0.1, 

10 mg/kg-d 

Squamous cell 

hyperplasia of 

the forestomach, 

small reductions 

in hematocrit, 

Hb, and RBC 

count in highdose males, 

increase in 

absolute/relative 

liver weight in 

high-dose groups

NOAEL = 

0.1 mg/kg-d; 

LOAEL = 

10 mg/kg-d 

Johannsen and 

Levinskas 

(2002a); 

Biodynamics 

(1980b) 

10 rats/sex/group 

were taken from 

exposed and 

control groups for 

interim sacrifice at 

6, 12, and 18 mos 

SpragueDawley 

48/sex/group; 

Controls: 

80/sex 

Drinking 

water/ 

2 yrs 

M: 0, 3.4, 8.5, 

21.3 mg/kg-d; 

F: 0, 4.4, 

10.8, 

25.0 mg/kg-d 

Hyperplasia/ 

hyperkeratosis of 

the forestomach, 

reduced survival 

and BW, 

minimal 

progressive 

nephropathy, 

gliosis of the 

brain 

LOAEL = 

4.4 mg/kg-d (F)

Quast (2002); 

Quast et al. 

(1980a) 

F344 

50/sex lowdose; 

197 males and 

203 females 

high-dose. 

Controls: 

51-males and 

49-females: 

Drinking 

water/ 

lifetime 

M: 0, 12.9, 

64.5 mg/kg-d; 

F: 0, 14.8, 

74.2 mg/kg-d 

Neurological 

signs 

No data Bigner et al. 

(1986) 

Doses calculated 

using default 

assumptions (U.S. 

EPA, 1988); 

noncancer effects 

not evaluated in 

the study 
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Table 4-36. Summary of chronic oral toxicity studies of AN: noncancer 

effects in rats and mice 

Strain 

number/sex 

Exposure 

route/ 

durationa

 Doses Effects 

NOAEL/ 

LOAELa References Comments 

Mice 

B6C3F1

50/sex/group 

Gavage/ 

2 yrs 

0, 2.5, 10, 

20 mg/kg-d, 

5 d/wk; 

continuous 

exposureadjusted 

doses: 0, 1.8, 

7.14, 

14.3 mg/kg-d 

Reduced survival 

in high dose 

group; 

hyperkeratosis/ 

hyperplasia of 

the forestomach; 

ovarian cysts and 

atrophy (F) 

LOAEL: 

1.8 mg/kg-d 

(F); NOAEL = 

1.8 mg/kg-d; 

(M) LOAEL = 

7.1 mg/kg-d 

(M) 

NTP (2001) 

aM = male; F = female. 

Table 4-37. Summary of chronic oral toxicity studies of AN: cancer effects 

in rats and mice 

Strain 

number/sex

Exposure 

route/ 

Duration Dosesa Effectsa References Comments

Rats

F344 

100/sex/group 

Unexposed 

controls = 

200/sex 

Drinking 

water/ 

2 yrs 

Males: 0, 0.1, 

0.3, 0.8, 2.5, 

and 8.4 mg/kgd; 

females: 0, 0.1, 

0.4, 1.3, 3.7, 

and 

10.9 mg/kg-d

Males: increase in brain 

astrocytomas and Zymbal 

gland tumors, increase in 

forestomach tumors; females: 

increase in brain 

astrocytomas, Zymbal gland 

tumors, and forestomach 

tumors 

Johannsen 

and 

Levinskas 

(2002b); 

Biodynamics 

(1980c)

10 rats/sex/group 

were taken from 

exposed and control 

groups for interim 

sacrifice at 6, 12, 

and 18 months

SpragueDawley 

100/sex/group 

Drinking 

water/ 

22 months 

(M); 

19 months (F)

Males: 0, 0.09, 

and 8.0 mg/kgd; females: 0, 

0.15, and 

10.7 mg/kg-d

Significant increases in 

incidences of tumors of the 

CNS, Zymbal gland, and 

forestomach 

Johannsen 

and 

Levinskas 

(2002a); 

Biodynamics 

(1980a)

10 rats/sex/group 

were taken from 

exposed and control 

groups for interim 

sacrifice at 6, 12, 

and 18 months

SpragueDawley 

100/sex/group

Gavage/ 

20 months

0, 0.1, and 

10 mg/kg-d

Increase in brain 

astrocytomas, and tumors of 

Zymbal gland, forestomach, 

and intestine. Carcinomas of 

the mammary gland in 

females 

Johannsen 

and 

Levinskas 

(2002a); 

Biodynamics 

(1980b)

10 rats/sex/group 

were taken from 

exposed and control 

groups for interim 

sacrifice at 6, 12, 

and 18 months

SpragueDawley 

48/sex/group; 

Controls: 

80/sex

Drinking 

water/ 

2 yrs

Males: 0, 3.4, 

8.5, and 

21.3 mg/kg-d; 

females: 0, 4.4, 

10.8, and 

25.0 mg/kg-d

Increases in CNS tumors, 

squamous cell papillomas or 

carcinomas of the 

forestomach, carcinomas of 

Zymbal gland, as well as 

benign and malignant tumors 

of the mammary gland 

Quast (2002); 

Quast et al. 

(1980a)
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Table 4-37. Summary of chronic oral toxicity studies of AN: cancer effects 

in rats and mice 

Strain 

number/sex

Exposure 

route/ 

Duration Dosesa Effectsa References Comments

F344 

50/sex lowdose; 197 males 

and 203 females 

high-dose. 

Controls: 

51 males and 

49 females

Drinking 

water/ 

lifetime

M: 0, 12.9, and 

64.5 mg/kg-d; 

females: 0, 

14.8, and 

74.2 mg/kg-d

Tumors found included brain 

astrocytomas, Zymbal gland 

tumors, and papillomas of the 

forestomach 

Bigner et al. 

(1986)

Doses calculated 

using default 

assumptions (U.S. 

EPA, 1988); no 

tumor incidence data 

were provided

SpragueDawley 

40/sex 

Control: 75/sex

Gavage/ 

3 ds/week for 

52 weeks; rats 

maintained 

without 

treatment 

until natural 

death (study 

ended week 

131) 

0, 5 mg/kg in 

olive oil 

Treatment-related increase in 

forestomach tumors 

Maltoni et al. 

(1977) 

Study limitations: 

single dose, short 

exposure period, and 

small number of 

animals in each 

group 

SpragueDawley 

20 M/group 

Drinking 

water/2 yrs 

0, 1.5, 7.1, and 

28 mg/kg-d 

Increase in tumors of the 

forestomach and Zymbal 

gland 

Gallagher et 

al. (1988) 

Study limitations: 

small group size, 

lack of testing in 

females, and only 

limited tissues were 

examined for 

histopathology. 

SpragueDawley 

15 M/group, 

30 F/group

Drinking 

water/ 

46 weeks 

(threegeneration 

reproduction/ 

developmental 

study)

0, 11, 

37 mg/kg-d 

(M); 0, 20, and 

40 mg/kg-d (F)

Increase in incidences of 

brain and Zymbal gland 

tumors 

Friedman and 

Beliles 

(2002); 

Litton 

Bionetics 

(1992)

Study suggested 

increased 

susceptibility to the 

carcinogenicity of 

AN from early-life 

exposure (see 

Section 4.8.1). 

Mice 

B6C3F1

50/sex/group 

Gavage/ 

2 yrs 

0, 2.5, 10, and 

20 mg/kg-d, 

5 d/wk, 

continuous 

exposureadjusted doses: 

0, 1.8, 7.14, and 

14.3 mg/kg-d 

Increase in tumors of the 

forestomach and of Harderian 

gland in males and females 

NTP (2001) Overall incidence of 

alveolar/bronchiolar 

adenomas or 

carcinomas was 

significantly 

elevated in females 

at 10 mg/kg-d, but 

not at 20 mg/kg-d. 

aM = male; F = female.
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4.2.2. Inhalation Exposure 

4.2.2.1. SubchronicSubchronic Studies 

 The only subsubchronic study of inhalation effects of AN in animals was a comparative 

study of the neurotoxicity of nitriles (Gagnaire et al., 1998). Groups of 12 male Sprague-Dawley 

rats were exposed (whole body) to AN vapor at concentrations of 25, 50, or 100 ppm, 

6 hours/day, 5 days/week for 24 weeks. A control group of 10 male rats was exposed to filtered 

air. BWs were measured weekly. Following 4, 8, 12, 16, 20, and 24 weeks of exposure and an 

8-week recovery period (week 32), rats were evaluated for the same electrophysiological 

parameters that were tested in parallel experiments on orally exposed rats (see Section 4.2.1.1). 

As in the companion study, electrophysiological testing was performed at least 16 hours after 

daily exposure (waiting period was 48 hours for weekends). Electrical stimulation of the tail 

nerve was used to assess MCVs, SCVs, ASAPs, and AMAPs. No mortality was observed during 

the treatment period, but, during the first and second week of the recovery period, 2/12 rats in the 

100 ppm group died and one rat each in the 100 and 25 ppm groups was euthanized in week 31 

because of tumors in the neck. BW gain in the 100 ppm group was significantly lower than in 

controls in weeks 4, 8, 16, and 21–24, such that the BW was 11% lower at the end of week 24. 

 Rats exposed to AN did not develop weakness of the hind limbs or disturbances in gait. 

After 1 or 2 weeks of exposure, rats exposed at ≥50 ppm exhibited clinical signs of gross toxicity 

(wet fur and excessive salivation but not hyperactivity). Excessive salivation was attributed by 

the study authors to a cholinomimetic effect of AN. Exposure to AN had no effect on 

neurophysiological parameters during the first 8 weeks and no effect on the AMAP at any time 

during the study. Statistically significant concentration-dependent SCV reductions of ~9% 

compared with controls were observed in the 100 ppm group from weeks 12–24 (Table 4-38). In 

week 12, an ~7% reduction was observed in the 50 ppm group, and in week 24 the SCV was 

reduced by 5% in the 25 ppm group (not biologically significant) and by >8% in the 50 and 

100 ppm groups. The ASAP was significantly reduced by 14.5–20% in the 50 ppm group and by 

29–30% in the 100 ppm group from weeks 16–24. After recovery in week 32, a 21% reduction 

in ASAP persisted in the 100 ppm group. Sporadic reductions in MCV were observed in 

100 ppm rats beginning in week 16 (11% reduction) but were not concentration dependent in 

week 24 or after recovery in week 32. A LOAEL of 25 ppm was identified for reductions in 

SCV in rats exposed to AN by inhalation for 24 weeks. A NOAEL was not identified. 
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Table 4-38. Effect on SCV in male Sprague-Dawley rats exposed to AN via 

inhalation for 24 weeks 

SCV (m/s)a

Exposure Exposure (weeks) Recovery

(ppm) 0 12 16 20 24 32

0 35.0 ± 0.5 49.7 ± 0.8 49.9 ± 1.0 50.3 ± 0.5 53.3 ± 1.0 53.4 ± 0.6 

25 35.2 ± 0.4 48.2 ± 0.7 47.8 ± 1.0 50.2 ± 0.7 50.5 ± 0.8b 51.8 ± 0.8 

50 35.3 ± 0.6 46.3 ± 0.8c 48.0 ± 1.1 50.5 ± 0.6 49.1 ± 0.5d 51.3 ± 1.0 

100 35.8 ± 0.5 45.3 ± 1.0c 46.2 ± 0.7b 48.1 ± 0.7b 48.4 ± 1.0d 50.4 ± 0.8 

aValues are means ± SDs (n = 12 for treated, n = 10 for controls). 

b

Statistically significant compared with controls (p < 0.05) as calculated by the study authors. 

c

Statistically significant compared with controls (p < 0.01) as calculated by the study authors. 

d

Statistically significant compared with controls (p < 0.001) as calculated by the study authors. 

Source: Gagnaire et al. (1998). 

4.2.2.2. Chronic Studies 

 Two chronic inhalation bioassays in rodents were available: Dow Chemical (1992a)/

Quast et al. (1980b) and Maltoni et al. (1988, 1977). 

4.2.2.2.1. Dow Chemical (1992a) and Quast et al. (1980b). Dow Chemical (1992a) and Quast 

et al. (1980b) evaluated the effects of AN in Sprague-Dawley rats (100/sex/group) exposed by 

inhalation at concentrations of 0, 20, or 80 ppm (0, 43.4, or 173.6 mg/m3

) 6 hours/day, 

5 days/week for 2 years. Additional groups of 7 and 13 rats/sex/group were exposed and 

sacrificed at 6 and 12 months, respectively. BWs were determined 10 times during the first 

3 months and monthly thereafter. Rats were observed daily for clinical signs and mortality, and 

beginning after 6 months, were examined for palpable masses and dental condition. Moribund 

animals or those with ulcerating tumors were sacrificed and subjected to gross necropsy. 

Hematology and urinalysis examinations were conducted on 10 rats/sex/group on days 174/175, 

365/366, 616/617, and 727/727 for males/females, respectively. The hematology determinations 

of male rats was also conducted on day 183 to verify observations made on day 174. Clinical 

chemistry analyses were conducted on 10 rats/sex/group on days 176, 372, and 735. Water 

consumption was determined for representative male and female rats in each group for the first 

8 months. At terminal sacrifice, all rats received an ophthalmologic examination and necropsy 

during which organ weights were recorded for brain, heart, liver, kidneys, and testes. Complete 

histologic examinations were carried out on all rats in the control and 80 ppm groups at terminal 

sacrifice. More than 80% of rats in the 20 ppm group were examined for gross lesions, and 

23 selected organs and all tissues with grossly recognized tumors were collected for 

histopathology examination. Because there were signs of upper respiratory tract irritation in the 

nasal turbinate, about 10 rats/sex/group from the terminal sacrifice were evaluated by light 
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microscopy. In addition, because of brain lesions observed during drinking water studies, nine 

sections from various regions of the CNS of all rats were examined microscopically. 

Noncancer results

Inhalation exposure to AN resulted in significant concentration-related noncancer effects 

compared with controls (Quast et al., 1980b). Statistically significant (p < 0.05) decreases in 

survival with respect to controls were observed in males after 6 months of exposure at 80 ppm 

and in females after 10 months of exposure at 80 ppm or 22 months at 20 ppm. The numbers of 

rats surviving at termination (out of 100/sex) were 18, 14, and 4 males and 22, 9, and 1 females 

in the control, 20 ppm, and 80 ppm groups, respectively. BWs were decreased by about 10–15% 

in male and female rats after 9 months of exposure to 80 ppm AN. A significant decrease of less 

than 10% was also observed in 20 ppm female rats. By the end of the study, BWs in 20 and 80 

ppm females were not significantly different from those in controls. 

Hb and RBC counts were significantly lower (by ~9%) in rats exposed to 80 ppm for 4–

8 months but not later. However, the study authors considered these changes to be a secondary 

effect of reduced growth, tumor formation, and hemorrhage, resulting from exposure and not due 

to bone marrow toxicity. Statistically significant increases in water consumption were observed 

in both exposed groups of male and female rats during the first 6 months of the study and were 

consistent with slightly decreased urine specific gravity measured in 80 ppm groups during that 

period. No significant effects on urinalysis parameters were observed after 6 months. Exposure 

to AN had no consistent significant effect on clinical chemistry parameters or results of 

ophthalmoscopic examinations. A significant elevation (about 26%) in blood urea nitrogen 

(BUN) was observed in the 20 and 80 ppm female rats on day 176. SGPT was also elevated by 

57% in the 80 ppm females at that time. However, no significant findings of these parameters 

were found upon subsequent evaluation at a later time interval. Hence, Quast et al. (1980b) 

considered these changes as secondary responses and not indications of direct renal or 

hepatotoxicity from AN exposure. Significant increases in relative weights of brain, heart, and 

testes of male rats exposed at 80 ppm were considered by the study authors to be a consequence 

of the reduction in BW. 

Gross pathological examinations found statistically significantly findings in the nasal 

turbinates, lungs, teeth (malocclusion), and liver of the 80 ppm rats. Gross observation of male 

rats indicated significant increase in minimal chronic nephropathy in the 80 ppm group 

(40/100 vs. 24/100). Significant increase in pneumonia, atelectasis, or edema was found in the 

20 and 80 ppm males (14/100, 27/100, and 30/100 for 0, 20, and 80 ppm groups, respectively). 

Gross observations of nontumorous changes included enlarged liver in female rats, with 

incidence of 2/100, 9/100, and 7/100 in 0, 20, and 80 ppm groups, respectively. (The increased 

incidence in the 20 ppm group was statistically significant.) 
159 DRAFT - DO NOT CITE OR QUOTE 

Statistically significant increases in the incidence of histopathologic lesions of the nasal 

turbinates were observed in all rats exposed at 80 ppm and most rats in the 20 ppm group. These 

effects were considered by the study authors to be the result of irritant effects of AN 

(Table 4-39). These lesions appeared in rats sacrificed after at least 13 months (usually 

19 months) of exposure. These inflammatory and degenerative changes included hyperplasia, 

flattening, focal erosion, and squamous metaplasia of the respiratory epithelium and hyperplasia 

of mucus secreting cells. Flattening of the respiratory epithelium in females and hyperplasia of 

mucus-secreting cells in males were both significantly increased at the 20 ppm exposure level. 

Table 4-39. Incidence of histopathological lesions of the nasal turbinates in 

Sprague-Dawley rats exposed to AN via inhalation for 2 years 

Concentration (ppm)

0 20 80

Response Incidence 

Males

Suppurative rhinitis 0/11 1/12 5/10a

Hyperplasia of respiratory epithelium 0/11 4/12 10/10a

Focal erosion of mucous lining 0/11 0/12 4/10a

Squamous metaplasia of the respiratory epithelium 0/11 1/12 7/10a

Hyperplasia of mucus-secreting cells 0/11 7/12a 8/10a

Focal inflammation 0/11 1/12 1/10 

Flattening of the respiratory epithelium 0/11 2/12 3/10 

Females

Suppurative rhinitis 1/11 0/10 2/10 

Hyperplasia of respiratory epithelium 0/11 2/10 5/10

a

Focal erosion of mucous lining 0/11 1/10 1/10 

Squamous metaplasia of the respiratory epithelium 0/11 2/10 5/10a

Hyperplasia of mucus-secreting cells 0/11 2/10 8/10a

Focal inflammation 2/11 6/10 7/10a

Flattening of the respiratory epithelium 1/11 7/10a 8/10a

a

Statistically significant (p < 0.05), as calculated by the study authors. 

Source: Quast et al. (1980b). 

Increase in acute suppurative pneumonia was observed in the lungs of the 80 ppm male 

rats during the 7–12-month time interval. A nonsignificant increase was also observed in the 

20 ppm group. 

 Other histopathological observations included an increase in the incidence of gliosis and 

perivascular cuffing in the brain of high-dose rats (either sex) and, in males only, minimal 

chronic focal progressive nephrosis and formation of keratinized cysts in the thyroid gland 

(Table 4-40). Incidences of focal necrosis of the liver were increased in 20 and 80 ppm female 
160 DRAFT - DO NOT CITE OR QUOTE 

rats. The incidence of AN-related hyperplasia and hyperkeratosis of the nonglandular portion of 

the stomach did not achieve statistical significance in either sex but was statistically significant 

(p < 0.05) by Fisher’s exact test when the data were combined. There were concentration-related 

increases in the incidences of several lesions that were secondary to other effects of AN exposure 

(numerical data not provided here). These included hepatocellular atrophy without fatty changes 

and atrophy of mediastinal fat in 80 ppm male rats, attributed by the study authors to the 

decreased feed intake of the rats at the end of the study, and extramedullary hematopoiesis of the 

spleen in females, a consequence of the reductions in RBC and Hb counts. An increase in 

lymphoid hyperplasia in males at 80 ppm was interpreted by the study authors to be secondary to 

tumors of the ear canal and inflammatory changes in the nasal turbinates. A NOAEL was not 

identified in this study. A LOAEL of 20 ppm was identified for increased lesions of the nasal 

turbinates (hyperplasia of mucus-secreting cells in males and flattening of the respiratory 

epithelium in females) and focal necrosis in liver of female rats exposed to AN vapor for 2 years. 

Table 4-40. Incidence of dose-related noncancerous histopathological lesions 

in Sprague-Dawley rats exposed to AN via inhalation for 2 years 

Concentration (ppm)

0 20 80

Response Incidence 

Males

Focal nephrosis (progressive) 22/100 24/100 48/100a

Minimal chronic nephropathy 24/100 21/100 40/100a 

Thyroid cyst 4/95 9/97 13/96a

Gliosis and perivascular cuffing (brain) 1/100 2/99 7/99a

Acute suppurative pneumonia 0/100 4/100 10/100a

Pulmonary changes 15/100 26/100a 20/100 

Hyperplasia of the nonglandular epithelium (stomach) 8/98 7/100 16/99 

Females

Gliosis and perivascular cuffing (brain) 0/100 2/100 8/100a

Focal necrosis in liver 3/100 16/100a 10/100a

Vasculization of spinal myelin (minimal) 42/100 67/100a 47/100 

Hyperplasia of the nonglandular epithelium (stomach) 2/99 3/99 7/97 

a

Statistical significance (p < 0.05), as calculated by the study authors. 

Source: Quast et al. (1980b). 

Cancer results 

In rats chronically exposed to AN vapor, there were significant increases in tumors at 

multiple sites, several of which also had been affected in oral exposure bioassays (Quast et al., 

1980b). In males and females exposed to 80 ppm AN, there were increased incidences of 
161 DRAFT - DO NOT CITE OR QUOTE 

astrocytomas of the brain as well as glial cell proliferation that was considered an earlier stage in 

the progression to astrocytomas. The incidence data in Table 4-41 combine the incidences of 

astrocytomas and glial cell proliferation. The incidence of CNS tumors was also significantly 

increased in females exposed to 20 ppm AN and insiginificantly increased in males exposed to 

20 ppm AN. Carcinomas of Zymbal gland were significantly elevated in the 80 ppm rats of both 

sexes. Other tumor increases observed in the 80 ppm groups were squamous cell papillomas or 

carcinomas in the tongue and carcinomas of the intestinal tract of males and adenocarcinomas of 

the mammary gland in females. An increase was observed in forestomach tumors in 80 ppm 

male rats and nasal turbinate tumors in 80 ppm female rats. Both types of tumors were 

considered by the study authors to be treatment related, although the increase was not 

statistically significant. Table 4-41 presents incidences of AN-induced target organ-specific 

tumor formation. All tumors were found in exposed rats that died or were sacrificed after 

12 months of exposure, with the exception of one male rat with a CNS tumor and three female 

rats with mammary gland adenocarcinomas that died between 7 and 12 months. 

Table 4-41. Cumulative incidence of tumors in Sprague-Dawley rats 

exposed to AN via inhalation for up to 2 years 

Males (ppm) Females (ppm)

Tissue 0 20 80 0 20 80

All brain/CNSa 0/96 4/93 22/82b 0/93 8/99b 20/89b

Zymbal gland 2/96 4/93 11/82b 0/93 1/98 11/89b

Intestinal tract 4/96 3/93 17/82b Not increased 

Mammary gland (adenocarcinomas) 0/100 0/100 1/100 9/93 8/98 20/99b

Mammary gland (total, benign and malignant) 4/100 5/100 7/100 88/100 95/100 85/100 

Forestomach (squamous cell papilloma) 1/98 1/100 4/99 0/99 0/99 1/97 

Tongue 1/95 0/14 7/82b 0/96 0/9 1/91 

Nasal turbinate (carcinoma in respiratory 

epithelial region) 

Not increased 0/11 0/98 2/10 

a

Incidence data include all brain/CNS tumors (astrocytomas and glial cell proliferation). Male tumor incidence data 

are from Tables 22, 25, and 26 of the Quast et al. (1980b) report; female tumor incidence data are from Tables 31, 

34, and 35 in the same report. For all incidence data, the denominators excluded rats dying earlier than 12 mos in 

the study. These data were ascertained from Tables 22, 25, 31, 34, and 35 in the original study report by Quast et 

al. (1980b). 

b

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Sources: Dow Chemical (1992a); Quast et al. (1980b). 

 An apparent decrease in the incidence of tumors of the pituitary, adrenals, thyroid, and 

pancreas of male and female treated rats, and testes of males, was observed when compared with 

controls. 
162 DRAFT - DO NOT CITE OR QUOTE 

4.2.2.2.2. Maltoni et al. (1988, 1977). The following studies by Maltoni et al. (1988, 1977) 

were cancer bioassays that did not investigate nonneoplastic effects in rats exposed to AN vapor. 

These study authors reported a number of experiments in which Sprague-Dawley rats were 

exposed to AN by inhalation. In the first (designated BT201 by the authors), 30 rats/sex/group 

were exposed to 0, 5, 10, 20, and 40 ppm 4 hours/day, 5 days/week for 52 weeks; the animals 

then were allowed to complete their natural life spans, with the final deaths occurring in week 

136 (Maltoni et al., 1977). Rats were examined 3 times weekly for general health status and 

subjected to a clinical examination for gross changes every 2 weeks. Rats were weighed every 

2 weeks during the exposure period and monthly thereafter. All rats were subjected to gross 

necropsy. Histopathologic examinations were conducted on all gross lesions and a selection of 

about 12 organs and tissues, including the Zymbal glands, interscapular brown fat, salivary 

glands, tongue, lungs, liver, kidneys, spleen, stomach, intestine, bladder, and brain. 

 Exposure to AN had no significant effect on survival or BWs in male or female rats. A 

moderate increase in gliomas, forestomach tumors, Zymbal gland carcinomas, and mammary 

tumors was found in the treated group. However, increases in the incidences of these tumors in 

exposed rats were not statistically significant and could be due to the small number of animals in 

each dose group. For example, gliomas were found in 20 and 40 ppm males at 1/30 and 2/30, 

respectively, and not in controls and other exposure groups. The average latency of the gliomas 

was shorter at the higher concentration (63.5 vs. 84 weeks). Forestomach papillomas and 

acanthomas were found in males at 0/30, 1/30, 2/30, and 3/30 for 0, 5, 10, and 40 ppm, 

respectively. In females, forestomach tumor incidences were 0/30, 1/30, 2/30, and 1/30 for the 

0, 5, 10, and 20 ppm groups. The average latency of forestomach tumors ranged from 103 to 

124 weeks. Zymbal gland carcinomas were also found at 1/30 in the 10 ppm group for male and 

female and 1/30 for the female 20 ppm group. No Zymbal gland carcinomas were found in the 

control and other dose groups. 

Moreover, a possible treatment-related effect of AN in the mammary gland of females 

was observed, as indicated by the following incidences of benign or malignant tumors in relation 

to exposure level: 5/30 (controls), 10/30 (5 ppm), 7/30 (10 ppm), 10/30 (20 ppm), and 

7/30 (40 ppm) (Maltoni et al., 1977). Slight discrepancies in the incidence of tumors of the 

mammary gland were reported for controls and highest-exposed females in a subsequent report 

of this study (Maltoni et al., 1988). In the later study, the incidence of tumors in control females 

was listed as 20%, an incidence of 6/30, whereas that of highest-concentration females was listed 

as 26.7%, an incidence of 8/30. In the later report, taking both sexes together, the incidences of 

encephalic gliomas were 3/60 and 2/60 in the 40 and 20 ppm groups, respectively, and none in 

the control and lower-dose groups. Although this cancer study was consistent with other studies 

in the identification of tumor sites associated with exposure to AN, it was limited in that the 

exposure concentrations were too low, the number of animals per group was too small, and the 

exposure duration was too short to result in statistically significant increases in specific tumor 
163 DRAFT - DO NOT CITE OR QUOTE 

types. However, this study demonstrated that rats with less-than-lifetime exposure and allowed 

to recover to their natural life span developed the same tumor types as rats with lifetime exposure 

to AN. 

 The later report by Maltoni et al. (1988) described two additional lifetime exposure 

experiments in which Sprague-Dawley rats were exposed to AN by inhalation beginning during 

the gestation period. In the first experiment (designated BT4003), 54 adult pregnant females, 

beginning on gestation day 12, were exposed to 60 ppm AN for 4 hours/day, 5 days/week for 

7 weeks and then 7 hours/day, 5 days/week for 97 weeks. A group of 60 unexposed adult 

females served as controls. Gestation was permitted to proceed normally and the offspring were 

exposed on the same schedule as the dams. The exposed offspring included 67 males and 

54 females, whereas the controls were 158 males and 149 females. 

 Overall, there was a statistically significant treatment-related increase in the percentage 

of dams with malignant tumors at all sites (37 vs. 15%). Increased incidences in exposed dams 

compared with controls were observed for several sites, but none of these was statistically 

significant: Zymbal gland carcinomas (5.5 vs. 1.7%), mammary gland carcinomas (5.5 vs. 

3.3%), benign or malignant mammary gland tumors (69 vs. 40%), extrahepatic angiosarcomas 

(1.8 vs. 0%), and encephalic gliomas (5.5 vs. 0%). No hepatomas were observed in exposed or 

unexposed dams. These site-specific results are summarized in Table 4-42. 

Table 4-42. Comparison of carcinogenic effects of chronic exposure to AN at 

60 ppm starting either in utero or in adulthood, in Sprague-Dawley rats 

Percent with tumor 

Stage 

during 

exposure 

Exposure 

protocol Sexa

Number 

of rats at 

startb

Brain 

tumors 

(encephalic 

gliomas) 

Zymbal 

gland 

carcinomas Hepatomas

Malignant 

mammary 

tumors 

Extrahepatic 

angiosarcomas 

Chronicc F 54 5.5 5.5 0.0 5.5 1.8 

Adult only Unexposed 

controls F 60 0.0 1.7 0.0 3.3 0.0 

Chronic M 

F 

67 

54 

16.4 

18.5 

14.9c 

1.8 

7.5 

1.8 

0.0 

16.7d 

4.4 

5.5e 

Subchronicd M 

F 

60 

60 

5.0 

3.3 

6.7 

1.7 

1.7 

0.0 

0.0 

6.7 

5.0 

1.7 

Starting at 

GD 12 

Unexposed 

controls 

M 

F 

158 

149 

1.3 

1.3 

1.3 

0.0 

0.6 

0.0 

1.9 

5.4 

0.6 

0.0 

a

F = female; M = male. 

bAnimals were allowed to live until spontaneous death. 

cChronic: 4 hrs/d, 5 d/wk for 7 wks (starting during gestation), followed by 7 hrs/d for 97 wks. 

d

Statistically significantly higher than correspondng control incidence, p < 0.05. 

e

Subchronic: 4 hrs/d, 5 d/wk for 7 wks (starting during gestation), followed by 7 hrs/d for 8 wks. 

Source: Maltoni et al. (1988). 
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 In contrast, chronically exposed male and female offspring showed statistically 

significant increases in the incidences of specific types of tumors: malignant tumors of the 

mammary gland in females (16.7 vs. 5.4%; p < 0.05), extrahepatic angiosarcomas in females 

(5.5 vs. 0%; p < 0.05), hepatomas in males (7.5 vs. 0.6%; p < 0.05), Zymbal gland carcinomas in 

males (14.9 vs. 1.3%; p < 0.01), and encephalic gliomas (16.4% in males and 18.5% in females 

vs. 1.3% for controls of both sexes; p < 0.01) (see Table 4-42). Higher responses in the exposed 

offspring at these sites relative to the dams suggests some early-life susceptibility to AN 

carcinogenity. These results are discussed further in Section 4.8.1. 

The second exposure experiment (BT4006) involving gestational exposure of SpragueDawley rats started with the same exposure conditions as for experiment BT4003, except that 

exposure of the offspring (127 males and 114 females) ended after 15 weeks (Maltoni et al., 

1988). Exposure in this group of offspring was for 4 hours/day, 5 days/week for 7 weeks starting 

on GD 12, followed by 7 hours/day, 5 days/week for 8 weeks. All animals were kept under 

observation until spontaneous death, at which time they were examined for the presence of 

tumors. The control group of offspring was the one used in experiment BT4003 (158 males and 

149 females). There was a statistically significant increase in the total incidence of malignant 

tumors in exposed offspring compared with controls for both males (31.7 vs. 17.1%, p < 0.05) 

and females (35.0 vs. 17.4%, p < 0.01). Increases in the following tumors were observed when 

compared with controls: Zymbal gland tumors in males and females (4.2 vs. 0.7%); extrahepatic 

angiosarcomas in males (5.0 vs. 0.6%); encephalic gliomas in males and females (4.2 vs. 1.3%); 

and hepatomas in males (1.7 vs. 0.6%) (see Table 4-42). However, these increases were not 

statistically significant. 

4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL AND INHALATION 

 In contrast to the extensive information on cancer and noncancer effects of AN in 

experimental animals and exposed human populations, there are comparatively few data that 

address the reproductive and developmental toxicity and teratogenic action of AN. 

4.3.1. Studies in Humans 

 There have been some preliminary translated reports of surveys of the reproductive 

history of women occupationally exposed to AN in chemical factories in China. While these 

studies pointed to a possible link between occupational exposure to AN and adverse effects on 

pregnancy, in some cases, there was insufficient information in the reports to assess the validity 

of these claims. However, there are studies with usable data. As described in Section 4.1.2.2, 

Dong and Pan (1995) provided data on exposure and reproductive outcomes in 150 male and 

106 female workers employed at a chemical fiber plant. These subjects, routinely exposed to 

AN concentrations ranging from 0.53 to 15.5 mg/m3

 (0.24–7.1 ppm), were compared with 

110 male and 121 female workers who had not been exposed to AN. The results of the study 
165 DRAFT - DO NOT CITE OR QUOTE 

were divided into two sections, one dealing with a comparison of the reproductive outcome for 

female employees, exposed vs. unexposed, and the second comparing the reproductive outcome 

of the wives of exposed male employees to that of the wives of unexposed male controls. In the 

former case, there were few differences in reproductive performance between exposed females 

and controls (see Table 4-21 for details), although the incidence of stillborn fetuses in the 

exposed group was significantly greater than in controls (5/112 vs. 0/124). However, it should 

be noted that there was a statistically significant age difference between the groups 

(29.36 ± 5.12 in exposed females vs. 20.68 ± 4.05 in female controls). The wives of exposed 

male workers at the plant had poorer reproductive outcomes than the wives of male controls, 

even though they were significantly younger than their counterparts. For example, there were 

differences in the incidence of live births as a proportion of the total number of pregnancies 

(159/168 vs. 113/113), spontaneous abortions (8/168 vs. 1/113), threatened abortions (5/168 vs. 

1/113), stillborn fetuses (4/168 vs. 0/113), and sterility (9/150 vs. 2/110). These data suggested a 

potential AN-related impact on the sperms and reproductive performance of exposed males. 

 An elevated incidence of complications in pregnancy was reported also by Li (2000) in 

379 female workers exposed to an average AN concentration of 7.5 ppm for ≥1 year. When 

compared with 511 unexposed controls, exposed subjects had a higher rate of overall 

complications (20.8 vs. 7.14%) and premature deliveries (11.62 vs. 4.72%). Exposed subjects 

were subdivided to create a category where both partners had been exposed to AN. Overall rates 

of complications, premature delivery, overdue delivery, and deficiency were greater than in cases 

where only the female partner was exposed. 

 In another Chinese study, Wu et al. (1995) reported statistically significant increases in 

the incidence of pernicious vomiting, anemia, preterm delivery, and birth defects in 477 females 

exposed to AN in the workplace compared with 527 controls. 

 The epidemiological report and follow-up by Czeizel et al. (2000, 1999) examined the 

environmental distribution of congenital abnormalities in 30 settlements within a 25 km radius of 

an AN factory, drawing on data from the Hungarian Congenital Abnormality Registry covering 

46,326 infants born between 1980 and 1996. A number of time-space-specific clusters of 

abnormalities were identified among the subjects, the most striking of which was the incidence 

of pectus excavatum in the community of Tata between 1990 and 1992. This effect was 

associated with an OR of 78.5 and a 95% CI of 8.4–729.6. Other clusters of congenital 

abnormalities in the vicinity of the factory were undescended testis in the community of 

Nyergesujfalu between 1980 and 1983 (OR = 8.6, CI = 1.4–54.3) and at Esztergom between 

1981 and 1982 (OR = 4.2, CI = 1.3–13.5) and clubfoot in the Tata community between 1980 and 

1981 (OR = 5.5, CI = 1.5–20.3). 

 As set forth in Section 4.1.2.2, the relationship between the findings of clusters of 

abnormalities and AN is uncertain because there are no exposure data in the report (Czeizel et 

al., 2000, 1999). Consequently, it is not known by how much the mothers of affected infants 
166 DRAFT - DO NOT CITE OR QUOTE 

were exposed to the compound if at all. Furthermore, when the incidence of these and other 

abnormalities was considered for infants born throughout the duration of the study, there were no 

overall increased incidences of congenital abnormalities within the study area compared with 

infants born throughout Hungary. 

 The study authors stated that there was a technological change at the AN factory in 1984 

that resulted in greater environmental protection, implying that releases of the compound to the 

environment were less after 1984 than before the change. This suggested that the cluster of 

pectus excavatum obtained at Tata between 1990 and 1992 was unlikely to have been due to AN 

exposure. However, the high incidence of undescended testis in Nyergesujfalu between 1980 

and 1983 may have been an environmental phenomenon, because the region-wide incidence of 

this congenital abnormality appeared to decrease with increasing distance from the factory. In 

general, however, it was difficult to draw conclusions about a link between maternal exposure to 

AN and the incidence of congenital abnormalities from the data in this study because of a lack of 

exposure data. 

 Ivanescu et al. (1990) reported lower serum testosterone level in male workers exposed to 

AN in a chemical factory (see Section 4.1.2.2.2). 

 Xu et al. (2003) performed conventional sperm analysis according to WHO guidelines 

and investigated DNA strand breakage and sex chromosome aneuploidy in spermatozoa of 

30 AN-exposed workers compared with 30 unexposed controls. The mean concentration of AN 

at exposure sites was reported to be 0.8 ± 0.25 mg/m

3

 (0.37 ppm). Sperm density was 

significantly lower in the exposed group (75 × 106/mL) than in the control group (140 × 106/mL). 

Sperm number per ejaculum was 205 × 106

 in the exposed group, significantly lower than the

280 × 106 spermatozoa in the control. However, there were no significant differences between 

the groups in semen volume, sperm motility, viability, or morphology. Xu et al. (2003) used 

single cell gel electrophoresis (comet assay) to monitor the incidence of DNA strand breakage of 

sperm cells. The rate of comet sperm nuclei was 28.7% in the exposed group, significantly 

higher than in the control group (15.0%). Mean comet tail length was 9.8 μm in exposed 

workers but 4.3 μm in control workers. The frequency of sex chromosome aneuploidy in sperm 

cells was analyzed using fluorescence in situ hybridization (FISH). Sex chromosome disomy 

was found to be 0.69% in the exposed group, significantly higher than 0.35% in controls. 

XY-bearing sperm was the most common sex chromosome disomy, with an average rate of 

0.37% in exposed vs. 0.20% in controls. XX- and YY-bearing sperm accounted for an additional 

0.09 and 0.23% of sperm in exposed vs. 0.05 and 0.10% in controls, respectively. Xu et al. 

(2003) concluded that AN exposure affected semen quality among occupationally exposed 

persons by the induction of DNA strand breakage and sex chromosome nondisjunction. 
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4.3.2. Studies in Animals 

4.3.2.1. Oral Studies 

 Assessments of reproductive/developmental effects of AN in orally exposed animals are 

derived from standard toxicity assays in rats and mice, standard developmental toxicity assays in 

female rats, and a three-generation reproductive toxicity assay in male and female rats. 

4.3.2.1.1. Standard toxicity assays: reproductive organ pathology. As described in 

Section 4.2.1, standard 2-year oral toxicity assays in rats revealed no evidence for increased 

reproductive histopathology in males or females exposed to AN at doses as high as 8–25 mg/kgday (Johannsen and Levinskas, 2002a, b; Quast, 2002; Biodynamics 1980a, b, c; Quast et al., 

1980a). In addition, there was no evidence for adverse effects of AN on functional reproductive 

parameters (sperm morphology, estrous cycle) or the histology of reproductive organs in male 

B6C3F1 mice treated with AN by gavage 5 days/week at 20 mg/kg-day or in females at 

40 mg/kg-day for 14 weeks (NTP, 2001). In this subchronic study, the weights of the left cauda 

epididymides were significantly elevated compared with controls in male mice exposed to 

10 and 20 mg/kg-day, but this effect was not considered biologically significant in the absence of 

histopathology. In the companion 2-year gavage assay (NTP, 2001), no reproductive 

histopathology was observed in male mice treated 5 days/week with AN at doses as high as 

20 mg/kg-day, but effects were observed in females (Table 4-33). The incidence of ovarian cysts 

was significantly elevated at 2.5, 10, and 20 mg/kg-day, and the incidence of atrophy of the 

ovary increased at 10 and 20 mg/kg-day. Atrophy was severe and was characterized by lack of 

histologically evident follicle and corpus luteum development with a predominance in interstitial 

tissue. The lowest dose of 2.5 mg/kg-day in this study was identified as the LOAEL for ovarian 

cysts and atrophy. 

4.3.2.1.2. Developmental toxicity assays. Dow Chemical (1992b) and Murray et al. (1978) evaluated 

developmental effects in pregnant female Sprague-Dawley rats (29–39/group) that received 10, 

25, or 65 mg/kg AN by gavage in water on GDs 6–15; an additional group of 43 controls 

received water alone. Dams were observed daily for clinical signs and weighed on GDs 6, 10, 

16, and 21. Food and water consumption were monitored at 3-day intervals on GDs 6–21, at 

which point all animals were sacrificed and maternal liver weights were recorded. Among the 

reproductive parameters evaluated were the numbers and positions of live, dead, and resorbed 

fetuses and the number of implantation sites. Developmental toxicity was evaluated by the 

weight, sex ratio, and crown-rump length of the fetuses. One-third of the fetuses in each litter 

were evaluated for visceral malformations and soft tissue abnormalities; the rest were examined 

for skeletal alterations. 

 Maternal toxicity of AN was most evident in the high-dose group. Systemic effects 

observed only at this dose included a single maternal death on GD 6, an increase in clinical signs 
168 DRAFT - DO NOT CITE OR QUOTE 

(hyperexcitability and excessive salivation) during the dosing period, BW gain reduced 46% 

compared with controls by GD 15 (22% by GD 21), water consumption significantly increased 

by an unspecified amount on GDs 6–20, and a statistically significant 11% increase in absolute 

(but not relative) liver weight compared with controls. Food consumption was significantly 

reduced by an unspecified amount compared with controls in high- and mid-dose dams on 

GDs 6–8. At necropsy, most (number not specified) dams dosed with 65 mg/kg-day and 

3/33 dams dosed with 25 mg/kg-day displayed a thickening of the nonglandular portion of the 

stomach. Pregnancy rate was significantly decreased among dams given 65 mg/kg-day AN, with 

only 20 of 29 dams producing litters. Uterine staining revealed implantation sites in four 

additional dams. A NOAEL for maternal toxicity was identified as 10 mg/kg-day AN, and 

25 mg/kg-day was the LOAEL for hyperplasia of forestomach. 

 Exposure to AN had no statistically significant effect on the average numbers of 

implantations/dam, live fetuses/litter, or resorptions/litter; the average sex ratio of litters was not 

reported. At 65 mg/kg-day, there were statistically significant reductions in fetal BW (by 7.4%) 

and crown-rump length (by 1.8%) compared with controls. The high-dose group also showed a 

significant increase in external malformations (short tail in 6/17 litters and short trunk in 

3/17 litters); there was also a significant increase in skeletal malformations (missing vertebrae) 

(Table 4-43). The defect ranged in severity from the absence of a single lumbar vertebra to the 

absence of all sacral and lumbar vertebrae and most thoracic vertebrae. Although the incidence 

of malformations at 25 mg/kg-day was not statistically significant (Table 4-43), a minimal 

LOAEL of 25 mg/kg-day was identified for fetal malformation in Sprague-Dawley rats. The 

NOAEL for fetal toxicity was 10 mg/kg-day. 
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Table 4-43. Incidence of fetal abnormalities among litters of SpragueDawley rats following maternal exposure to AN on GDs 6–15 

AN (mg/kg-d)

Type of malformation 0 10 25 65

Number of fetuses affected/number of litters examined

External and skeletal malformations 443/38 388/35 312/29 212/17 

Visceral malformations 154/38 135/35 111/29 71/17 

 Number of fetuses (litters) affected 

External malformations

Short tail 1 (1) 0 (0) 2 (2) 8 (6)a

Short trunk 0 (0) 0 (0) 0 (0) 3 (3)a

Imperforate anus 0 (0) 0 (0) 0 (0) 2 (2) 

Visceral abnormalities 

Right side aortic arch 0 (0) 0 (0) 1 (1) 1 (1) 

Missing kidney, unilateral 1 (1) 0 (0) 0 (0) 1 (1) 

Anteriorly displaced ovaries 0 (0) 0 (0) 1 (1) 1 (1) 

Skeletal malformations 

Missing vertebrae 1 (1) 0 (0) 2 (2) 8 (6)a

Missing two vertebrae and two ribs 7 (1) 0 (0) 7 (2) 0 (0) 

Hemivertebrae 0 (0) 0 (0) 0 (0) 0 (0) 

Total malformed 8 (2) 0 (0) 10 (4) 8 (6)a

a

Significantly different from controls (p < 0.05), as determined by the study authors. 

Source: Murray et al. (1978). 

 Behavioral teratogenicity of AN was examined in the progeny of pregnant Wistar rats 

(15/group) that received 0 or 5 mg/kg-day AN by gavage on GDs 5–21 (Mehrotra et al., 1988). 

Dams were weighed at intervals, and food and water intakes and the length of gestation were 

recorded. At parturition (postnatal day [PND] 0), litters were culled to four males and four 

females. On PND 1, pups were sexed and examined for gross external anomalies; litters with 

fewer than two/sex were rejected. Eight pups from four litters were examined for behavioral 

abnormalities, including tests for spontaneous locomotion and passive avoidance. Excised brains 

of 21-day-old pups were assayed for biogenic amines (noradrenaline, dopamine, and 

5-hydroxytryptamine) and for the activities of Na+

,K+-adenosine triphosphatase (ATPase), 

monoamine oxidase, and acetylcholinesterase. 

 Exposure to AN at 5 mg/kg-day had no significant effect on BW or food and water 

intakes in dams or on reproductive parameters such as gestational length, number of viable 

offspring, or pup sex ratio. No AN-induced effects were observed on postnatal morphological 

development, pup BWs, developmental indices (eye opening or incisor eruption), or tests of 

neurological impairment (righting reflex, cliff avoidance, and grip strength). The levels of 

biogenic amines were significantly altered in specific brain regions as a result of exposure. 
170 DRAFT - DO NOT CITE OR QUOTE 

Levels of 5-hydroxytryptamine were increased by 32% in the pons medulla and decreased by 

44% in the corpus striatum and 30% in the hippocampus. Levels of noradrenaline were 

decreased by 40% in the pons medulla and increased by 81% in the hippocampus. Gestational 

exposure to AN resulted in a statistically significant 49% reduction in brain levels of monoamine 

oxidase in 21-day-old pups; levels of acetylcholinesterase and Na+,K+-ATPase were not 

significantly affected. The biological significance of the enzyme and neurotransmitter changes 

was unclear, given that no treatment-related behavioral effects were observed. However, 

Mehrotra et al. (1988) noted that alterations in the levels of biogenic amines may become more 

prominant after prolonged exposure or exposure to higher doses of AN. 

 In a study comparing developmental toxicities of aliphatic nitriles in vitro and in vivo, 

Saillenfait and Sabaté (2000) administered a single dose of 0 or 100 mg/kg AN by gavage in 

olive oil to groups of four pregnant Sprague-Dawley rats on GD 10. Dams were sacrificed on 

GD 12, and the numbers of uterine implantation sites and fetuses with heartbeats were recorded. 

Viable fetuses were examined for defects of the allantois, trunk, and misdirected caudal 

extremity (left-sided), which the investigators had found to be typical in embryos exposed to 

sodium cyanide. Maternal effects of all of the nitriles (including AN) included increases in 

clinical signs (piloerection, prostration, and/or tremors) and unspecified maternal BW loss 

between GDs 10 and 12. AN exposure had no effect on the numbers of implants/litter or live 

embryos/litter, but significantly increased the incidence of overall poor and abnormal 

development and the incidence of misdirected allantois or allantois, trunk, and caudal extremity 

misdirected (Table 4-44). The study authors suggested that maternal production of the 

metabolite cyanide may have contributed to the developmental toxicity of AN since the 

characteristic defects that occurred in embryos exposed to cyanide were found in AN-exposed 

embryos. The single applied dose of 100 mg/kg is a LOAEL for maternal and fetal effects. 

Table 4-44. Morphological alterations in GD 12 fetuses of Sprague-Dawley 

rats exposed to 100 mg/kg AN on GD 10 

Group (number of litters examined)

Response Control (n = 4) 100 mg/kg (n = 4)

Implants/litter 13.25 ± 1.71 13.75 ± 0.96 

Live embryos/litter 13.0 ± 1.83 12.5 ± 1.0 

Total embryos examined 52 50 

Allantois, trunk, and/or caudal extremity misdirected

Embryos affected/embryos examined 0/52 13/46a

Litters affected/litters examined 0/4 3/4 

a

Significantly different from controls (p < 0.01) as calculated by the reviewers (Fisher’s exact test). 

Source: Saillenfait and Sabaté (2000). 
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4.3.2.1.3. Reproductive toxicity assay. Friedman and Beliles (2002) and Litton Bionetics (1992) 

conducted a three-generation reproductive study in Sprague-Dawley rats (groups of 15 males and 

30 females) exposed to 100 or 500 ppm AN in drinking water for 100 days before mating. 

Groups of 10 male and 20 female controls received untreated drinking water. As calculated by 

the study authors, the concentrations were equivalent to average doses of 0, 11, and 37 mg/kgday for males and 0, 20, and 40 mg/kg-day for females. The calculated average doses, averaged 

across sexes, were 0, 16, and 39 mg/kg-day. Rats were observed daily, especially for signs of 

neurotoxicity (e.g., abnormal gait). Water consumption in the F0 generation was measured twice 

a week, food intake was measured weekly, and BWs were recorded every 2 weeks. After 

100 days of exposure, rats were paired for mating for 6 days; females not bred after 6 days were 

mated to another proven breeding male from the same exposure group. The offspring (F1a) of 

the first mating were examined on PNDs 0, 4, and 21. Litters were culled to 10 pups on PND 4 

to achieve an equal sex ratio. Litter BWs were recorded on PND 4 and individual pup weights 

were recorded on PND 21. Two weeks after removal of the F1a offspring, F0 females were 

remated to produce the F1b litter, and those not used in breeding F1a were also mated to produce 

F1b pups to ensure a sufficient number of offspring for the F2 generation, although these animals 

should have been discarded according to the original study design. The original study design 

stipulated discarding F1a pups (those not scheduled for breeding) at weaning, but, because of 

high mortality in the 500 ppm group, they were retained to ensure sufficient time-mated females 

to use as foster mothers (one-half of each high-dose litter was fostered onto untreated females). 

All F0 males used for breeding were discarded after the second mating, and those not used in 

breeding were discarded when the F1a litter were weaned. 

At weaning (21 days), one male and one female from the unfostered F1b litter (or from 

the F1a litter, if needed) were selected as potential breeders for the F2 generation. All 

F1 offspring exposed to AN were checked daily for mortality, and necropsies were performed on 

all animals either found dead or killed in a moribund condition. The F0 dams and females not 

producing a litter were exposed for an additional 20 weeks after weaning the F1b pups. After 

that period, they were sacrificed and the sciatic nerve, gastrocnemius muscle, brain, and gross 

lesions were examined for histopathology. F1a and F1b rats were sacrificed in week 95 of the 

study and necropsied for the examination of papillomas in the stomach and intestines. The 

protocol for the subsequent generations (F1b parents and F2a and F2b offspring; F2b parents and 

F3a and F3b offspring) was as described for the first generation. F2 females, after an additional 

20 weeks of exposure following the weaning of the F3b litters, were necropsied, and sciatic 

nerve, gastrocnemius muscle, brain, stomach, and gross lesions were evaluated for 

histopathology. F3b rats (10/sex) in the control and 500 ppm groups were randomly selected for 

histologic examination. 

 The following discussion of results does not include cancer data from this study, which 

were presented separately in Section 4.2.1.2. In F0 parents, BWs were lower than controls after 
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4 weeks of exposure to 500 ppm, the reduction reaching 22% in males and 17% in females by 

week 10. This BW reduction was accompanied reduction in food intake by ~18% in 500 ppm 

males and 8% in 500 ppm females for the first 10 weeks. Water consumption was reduced in 

males and females by about 50% at the high dose and 20–25% at the low dose for the first 

10 weeks. Reduced water consumption and possibly BWs may have been a result of reduced 

palatability of treated water. Exposure to AN had no effect on the incidence of neurological or 

other clinical signs, male or female fertility indices, or the duration of mating or gestation of 

F0 parents. 

Compared with controls, no significant changes in fertility index or gestational index 

were observed in any of the exposed generations (Table 4-45) (Friedman and Beliles, 2002; 

Litton Bionetics, 1992). However, poor fertility among controls for the F1b (50–60%) and 

F2b (60–70%) parents might have limited the capability of this study to detect differences in 

fertility between control and treated rats (Table 4-45). The durations of mating and gestation 

were also unaffected, except the mating duration of F2b rats for F3a generation. Significant 

decreased viability and lactation indices were observed in the 500 ppm F0 parents for the 

F1a generation, due to the deaths of pups between 1–4 and 5–21 days, respectively. Significant 

decreases in viability index were also observed in 100 and 500 ppm F0 parents for the 

F1b generation and in 500 ppm F2b parents for the F3a generation (Table 4-45). In addition, 

decreases of about 10–40% in pup weights were observed in the F1a, F1b, F2a, F2b, F3a, and 

F3b generations in the 500 ppm groups (Table 4-46). Overall, the results identified a drinking 

water concentration of 100 ppm (16 mg/kg-day) as a minimal reproductive toxicity LOAEL for 

decrease in lactation index in F2a generations. Although no effects on fertility were observed in 

this three-generation study, poor fertility among controls in F1b and F2b parents might have 

limited the sensitivity of this assessment. The study also identified a LOAEL of 100 ppm for 

reduced viability in F0 parents. 
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Table 4-45. Group-specific reproductive indices in three generations of 

Sprague-Dawley rats receiving AN in drinking water 

Malea,b Femalec,d

Generation/group Fertility index Gestation indexe Viability indexf Lactation indexg

F0 parents for F1a 

Control 10/10 18/20 18/18 185/186 138/150 

100 ppm 8/10 16/20 16/16 197/201 139/150 

500 ppm 10/10 16/20 16/16 166/177h 95/143h

F0 parents for F1b 

Control 10/10 16/20 16/16 186/186 137/150 

100 ppm 10/10 17/20 17/17 182/202h 132/139 

500 ppm 13/15 22/28 22/22 99/109h 87/99 

F1b parents for F2a 

Control 5/10 10/20 10/10 107/109 91/91 

100 ppm 7/10 11/20 11/11 116/124 95/104h

500 ppm 8/10 14/20 14/14 133/140 107/114h

F1b parents for F2b 

Control 6/10 10/20 10/10 101/101 82/82 

100 ppm 5/10 8/20 8/8 93/97 70/73 

500 ppm 8/10 14/20 14/14 138/138 123/123 

F2b parents for F3a 

Control 6/10 14/20 14/14 161/161 128/131 

100 ppm 9/10 13/20 13/13 157/158 124/124 

500 ppm 10/10 15/20 15/15 157/166h 134/135 

F2b parents for F3b 

Control 9/10 14/20 14/14 170/176 106/108 

100 ppm 10/10 15/20 15/15 198/198 117/119 

500 ppm 10/10 17/20 17/17 170/178 115/125 

aDoses in males: 0, 11, or 37 mg/kg-d for 0, 100, or 500 ppm as calculated by the study authors. 

b

Fertility index in males = number of males producing a litter/number mated. 

cDoses in females: 0, 20, or 40 mg/kg-d for 0, 100, or 500 ppm, as calculated by the study authors. 

d

Fertility index in females = number of pregnant females/number mated. 

eGestation index = number of litters born/number of pregnant females. 

fViability index = number of pups that survived to PND 4/number of pups born alive. 

gLactation index = number of pups surviving to weaning/number of pups alive on PND 4. 

h

Significantly lower than controls (p < 0.05), as calculated by the study authors. 

Sources: Friedman and Beliles (2002); Litton Bionetics (1992). 
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Table 4-46. Group-specific pup weights in three generations of SpragueDawley rats receiving AN in drinking water 

Weight (g)

Generation-concentration D 4 D 21 (males)

F1a-control 11 42 

F1a-100 ppm 10 40 

F1a-500 ppm 9

a

 28a

F1b-control 10 39 

F1b-100 ppm 9 36 

F1b-500 ppm 10 34a

F2a-control 11 39 

F2a-100 ppm 10 39 

F2a-500 ppm 9

a

 30 

F2b-control 11 53 

F2b-100 ppm 10 46 

F2b-500 ppm 9 30a

F3a-control 10 43 

F3a-100 ppm 9 43 

F3a-500 ppm 8

a

 30a

F3b-control 10 50 

F3b-100 ppm 10 47 

F3b-500 ppm 8

a

 32a

a

Significantly different from controls (p < 0.05), as calculated by the study authors. 

Sources: Friedman and Beliles (2002); Litton Bionetics (1992). 

4.3.2.1.4. Male exposure reproductive toxicity studies. Tandon et al. (1988) evaluated reproductive 

toxicity in male CD-1 mice that received 0, 1, or 10 mg/kg-day AN by gavage in saline for 60 

days. The testes of six mice/group were examined histopathologically, and homogenates of 

pooled testes (four testes) in each group were assayed for the activities of sorbitol dehydrogenase 

(SDH), acid phosphatase, LDH, glucose-6-phosphatase dehydrogenase, and β-glucuronidase. 

Exposure to AN decreased the epididymal sperm count by 21 and 45% at the low- and 

high-dose group, respectively. However, the decrease was statistically significant (p < 0.05) 

only with the 10 mg/kg-day group. Histopathological examination of the testes did not reveal 

changes in the low-dose group. In high-dose mice, degenerative changes were seen in 40% of 

seminiferous tubules. In addition, the testes of mice dosed with 10 mg/kg-day showed a 12% 

increase in the activity of LDH, a 22% decrease in the activity of SDH, a 37% increase in the 

activity of β-glucuronidase, and a 16% decrease in the activity of acid phosphatase compared 

with controls. AN exposure had no effect on the activity of testicular glucose-6-phosphatase 

dehydrogenase. The study authors suggested that the changes in the activities of LDH and SDH 

were related to the AN-induced degeneration of germinal epithelium. In this study, a NOAEL of 
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1 mg/kg-day and a LOAEL of 10 mg/kg-day were identified for the toxicological effects of AN 

on the testes of male CD-1 mice.

 In a range-finding acute toxicity study for a dominant lethal assay, groups of 10 male 

F344 rats received 45, 60, 68, 75, or 90 mg/kg-day AN by gavage in 0.9% saline daily for 5 days 

(Working et al., 1987). Rats were observed for a total of 42 days from the first administration. 

No deaths were observed in groups receiving 45 or 60 mg/kg-day. In the higher dose groups, the 

study was terminated early on account of mortality: 40% at 68 mg/kg-day (terminated on day 6), 

30% at 75 mg/kg-day (terminated on day 4), and 30% at 90 mg/kg-day (terminated on day 2). 

As a result of this range-finding study, 60 mg/kg-day was selected as the maximum tolerated 

dose for the dominant lethal assay. In this assay, groups of 50 male F344 rats received AN by 

gavage at 0 or 60 mg/kg-day in 0.9% saline for 5 days. BWs of males were recorded three times 

during the week of treatment and then weekly during the mating period of 10 weeks; males were 

caged with a different female each week for 6 days. A transient reduction in mean BW (~4%) 

compared with controls was observed in rats on treatment days 3 and 5 and on the fourth posttreatment day; BW gain in treated rats was equivalent to controls beginning the second week of 

observation. AN exposure in males had no effect on the incidence of pre- or postimplantation 

losses, indicating a negative result in the dominant lethal assay. AN also had no effect on the 

fertility of exposed males in any postexposure week. 

4.3.2.2. Inhalation Exposure 

 Information about reproductive/developmental toxicity in animals exposed to AN by 

inhalation comes from a standard chronic toxicity assay in rats, developmental toxicity assays in 

rats, and a dominant lethal assay in male mice. 

4.3.2.2.1. Standard toxicity assays. As described in Section 4.2.2.2, no reproductive 

histopathology was observed in male or female Sprague-Dawley rats that were exposed to AN at 

concentrations as high as 80 ppm 6 hours/day, 5 days/week for up to 2 years (Dow Chemical 

Co., 1992a; Quast et al., 1980b). 

4.3.2.2.2. Developmental toxicity assays. Haskell Laboratory (1992a) and Murray et al. (1978)

evaluated developmental toxicity in groups of 30 pregnant Sprague-Dawley rats exposed (whole 

body) to 0, 40, or 80 ppm AN vapor for 6 hours/day on GDs 6–15. The parameters examined 

were the same as those for the oral exposure study by these authors described in Section 4.3.2.1. 

Inhalation exposure to 40 or 80 ppm AN did not result in deaths, changes in appearance, gastric 

thickening, or increase in terminal liver weight in dams. Maternal BW gain was significantly 

reduced during GDs 6–15 by 47% in the 40 ppm group and by 58% in the 80 ppm group 

(a reduction of about 20% in both groups for GDs 6–21). Both exposure groups exhibited 

significant (unspecified) decreases in food consumption on GDs 6–9 (but not later intervals) and 
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increases in water consumption on GDs 9–20. In this study, a NOAEL for maternal effects was 

not identified, but a LOAEL of 40 ppm was identified for reduced BW gain in dams. 

Gestational exposure to AN had no significant effect on any of the reproductive 

parameters (pregnancy rates, numbers of implantations, live fetuses, or resorptions) and no effect 

on fetal BW or crown-rump length measurements. Furthermore, no single major malformation 

occurred at significantly higher incidence in AN-exposed rats vs. controls. However, as shown 

in Table 4-47, there was an increase in the incidence of total major malformations when they 

were considered collectively (p < 0.06) for the high-dose group (present in 6/35 litters). 

Malformations observed in litters of 80 ppm group included short tail, missing vertebrae, short 

trunk, omphalocele, and hemivertebra. In this study, a NOAEL of 40 ppm and a LOAEL of 

80 ppm were identified for increases in total malformations in rats.

Table 4-47. Incidence of fetal malformations among litters of SpragueDawley rats exposed to AN by inhalation 

AN concentration (ppm)

Type of malformation 0 40 80

Number of fetuses/number of litters examined

External and skeletal malformations 421/33 441/36 406/35 

Visceral malformations 140/33 148/36 136/35 

Number of fetuses (litters) affected

External malformations 

Short tail 0 (0) 0 (0) 2 (2) 

Short trunk 0 (0) 0 (0) 1 (1) 

Imperforate anus 0 (0) 0 (0) 0 (0) 

Omphalocele 0 (0) 1 (1) 1 (1) 

Visceral abnormalities 

Right-sided aortic arch 0 (0) 0 (0) 0 (0) 

Missing kidney, unilateral 0 (0) 0 (0) 0 (0) 

Anteriorly displaced ovaries 0 (0) 0 (0) 1 (1) 

Skeletal malformations 

Missing vertebrae 0 (0) 0 (0) 2 (2) 

Missing two vertebrae and two ribs 8 (1) 2 (1) 7 (2) 

Hemivertebrae 0 (0) 0 (0) 1 (1) 

Total malformed 8 (1) 3 (2) 11 (6)a

subchronic

a

Significantly different from control, as calculated by the study authors (p = 0.06). 

Source: Murray et al. (1978). 

Saillenfait et al. (1993) included AN in a survey of the relative developmental toxicities 

of inhaled aliphatic mononitriles in rats. Pregnant Sprague-Dawley rats (20–21/group) were 

exposed (whole body) for 6 hours/day to 0, 12, 25, 50, and 100 ppm AN vapor on GDs 6–20. 
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Dams were observed daily throughout pregnancy and BWs were recorded on GDs 0, 6, and 21. 

All subjects were sacrificed on GD 21, and the uteri were weighed and opened to assess the 

numbers of implantations, resorption sites, and live and dead fetuses. The fetuses were 

examined for external abnormalities and then split into two equal groups for examination of 

skeletal or visceral anomalies. 

 AN exposure did not cause premature deaths in the dams, but exposure to ≥25 ppm 

caused concentration-related, statistically significant reductions (by 16–45%) in overall BW gain 

and concentration-related losses in absolute BW (exclusive of gravid uterus weight) in dams. In 

this study, 12 ppm is a NOAEL and 25 ppm is a LOAEL for reduced BW in dams. 

AN exposure had no effect on reproductive parameters (pregnancy rate, average number 

of implantations, numbers of live fetuses, incidences of nonsurviving implants, or resorptions per 

litter). Concentration-dependent, statistically significant reductions in average fetal weight (by 

5–15% compared with controls) were observed at ≥25 ppm. There were no significant increases 

in the incidences of external, visceral, or skeletal anomalies in the exposed groups and one 

control fetus. In this study, a NOAEL of 12 ppm and a LOAEL of 25 ppm were identified for 

significantly reduced fetal BW. 

 In a dominant lethal assay for AN, Zhurkov et al. (1983) continuously exposed male ICR 

mice (20/group, whole body) to AN at concentrations of 0, 20, or 100 mg/m3 (0, 9.1, or 46 ppm) 

for 5 days. After exposure, each male was mated to two unexposed females for 8 weeks. 

Females were sacrificed between GDs 13 and 15, and a number of reproductive and 

developmental parameters were monitored, including the percentage of pregnant females, 

number of corpora lutea, implantations, and live and dead fetuses per female as well as total and 

pre- and postimplantation mortality. Exposure to AN did not result in any dominant lethal effect 

on male germ cells nor did it cause adverse pre- or postimplantation outcomes. The highest 

exposure level in this study, 46 ppm, was a NOAEL for reproductive toxicity. This study was 

limited by sparse descriptions of methods and a lack of quantitative reporting of results. 

4.3.2.3. Intraperitoneal Administration 

 In a translated study in Chinese, the effect of AN on spermatogenesis was examined in 

groups of male Kunming mice (10 3–4-week-old pubertal and five 6–8-week-old adult mice per 

group) treated by i.p. injection (Liu et al., 2004). The animals received AN (>99% purity) at 

doses of 1.25, 2.5, or 5.0 mg/kg-day (1/24, 1/12, or 1/6 of the LD50) for 5 days. Negative 

controls received physiological saline (10 mL/kg) daily for 5 days, whereas positive controls 

received a single injection of 40 mg/kg CP (not identified but presumably cyclophosphamide). 

On day 35, mice were sacrificed, the left testicle was selected from five mice per group, and 

testicular cell suspensions were evaluated using flow cytometry. 

 The following dose-related effects observed in the 2.5 and 5.0 mg/kg-day groups were 

statistically significantly different from the negative control group (p < 0.05); the same effects 
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were observed in positive controls (Liu et al., 2004). AN decreased the percentage of haploid 

testicular cells (indicative of completed spermatogenic meiosis) by 14.3 and 15% in mid- and 

high-dose adult mice, but a slight reduction was not statistically significant in pubertal mice. 

The percentage of apoptotic testicular cells was significantly increased by 58.7 and 74.8% in 

mid- and high-dose pubertal mice and by 81.5 and 108% in mid- and high-dose adult mice. The 

percentages of spermatogenic epithelial cells in G0/G1 phase were significantly reduced by 

18 and 20% in mid- and high-dose pubertal mice and by 35.5 and 40.5% in mid- and high-dose 

adult mice. The percentage of spermatogenic epithelial cells in G2/M phase was significantly 

elevated in adult mice by 31.4 and 32.8% at the mid- and high doses, respectively. AN exposure 

had no effect on the percentage of spermatogenic epithelial cells in S phase. The NOAEL and 

LOAEL for suppression of spermatogenesis were 1.25 and 2.5 mg/kg-day, respectively. 

 The teratogenic effects of AN were investigated in groups of pregnant golden hamsters 

that were exposed via an i.p. injection on GD 8 (Willhite et al., 1981). The actual numbers of 

dams per group were not reported, but data were presented for 3–6 litters in the exposed groups 

and 12 litters for the controls injected with sodium chloride. Dose levels were 0, 0.09, 0.19, 

0.47, 1.23, and 1.51 mmol/kg (equivalent to 0, 5, 10, 25, 65, and 80 mg/kg). No adverse clinical 

symptoms were observed in the dams exposed to up to 1.23 mmol/kg (65 mg/kg) AN by GD 14, 

when the dams were sacrificed. No malformations were observed in the offspring. In contrast, 

dams exposed to 1.51 mmol/kg (80 mg/kg) showed intense dyspnea, gasping, incoordination, 

hypothermia, salivation, and convulsions for 1–5 hours after injection. Additionally, several 

fetal abnormalities and malformations were observed at this exposure level, including 

encephaloceles and fused or bifurcated ribs. Coadministration of 8.06 mmol/kg STS and 

1.51 mmol/kg AN induced neither maternal toxicity nor fetal malformations. Coadministration 

of 8.06 mmol/kg STS and a higher dose of AN (1.88 mmol/kg, 100 mg/kg) prevented toxic 

symptoms in dams but not the teratological effects in fetuses. The study authors concluded that 

the teratogenic action of AN was related to the metabolic release of cyanide. 

 The effect of AN on rat liver cytochrome P-450 and serum hormone levels were studied 

in male Sprague-Dawley rats (4/group) injected with 33 mg/kg AN (i.p.) for 3 consecutive days 

(Nilsen et al., 1980). Control animals were treated with 0.9% sodium chloride. Blood were 

collected immediately after the animals were sacrificed and serum luteinizing hormone (LH), 

follicle stimulating hormone (FSH), and prolactine (PRL) were measured by radioimmunoassay. 

Serum corticosterone levels and liver microsomal cytochrome P-450 were also determined. 

 A significant increase (3%) in BW was reported in the AN treated group when compared 

with controls (Nilsen et al., 1980), but relative liver weight was not increased. A significant 

decrease in liver microsomal content of CYP450 was observed. Serum corticosterone measured 

24 hours after the last AN injection was decreased by 70%, while FSH levels were increased by 

118%. Serum PRL levels were decreased by 63% when compared with the controls, while 
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serum LH levels were unchanged. Nilsen et al. (1980) suggested that the increase in FSH might 

be secondary to impaired spermatogenesis in the testes of treated rats. 

4.3.3. In Vitro Studies 

 The embryotoxicity of AN was evaluated in cultures of whole rat embryos by Saillenfait 

and coworkers in a series of studies (Saillenfait et al., 2004, 1992; Saillenfait and Sabaté, 2000). 

As described initially in Saillenfait et al. (1992), the experimental system involved incubating 

day 10 embryos from pregnant Sprague-Dawley rats for 26 hours in whole organ culture in a 

medium containing AN at concentrations of 76–760 μmol/L. The growth-related parameters 

evaluated were functional yolk-sac circulation, yolk-sac diameter, crown-rump length, head 

length, number of somites, number of malformed embryos, incidences of abnormal brain, 

malformed caudal extremities, delayed yolk-sac circulation, and defective flexion. The effects of 

metabolic activation on the embryotoxicity of AN were evaluated by the inclusion of S9 and 

cofactors (NADPH, glucose-6-phosphate) for CYP450-dependent biotransformation in the 

incubation system. 

 Exposure to AN induced concentration-related effects on growth and development. 

Functional yolk-sac circulation (circulating erythrocytes) was reduced at ≥304 μM and was 

completely absent at 760 μM. Crown-rump length was reduced at 304 μM and could not be 

measured at higher concentrations. A concentration-dependent increase in the incidence of 

malformations was observed following in vitro exposure of day 10 fetuses to AN at 152 μM and 

above. AN at 152 and 304 μM induced malformations in 53 and 100% of the exposed embryos, 

respectively. Malformations primarily consisted of a shortened caudal extremity (significant at 

152 μM) and a reduction of the brain (achieving significance at 304 μM). Other general 

malformations were delayed development of the yolk-sac circulation and defective flexion. 

Furthermore, growth retardation and severity of malformations induced by 304 μM AN were 

enhanced by the presence of S9 and cofactors, suggesting a role for oxidative biotransformation 

in AN embryotoxicity. Addition of 0.1–2.2 mM GSH in the incubation medium reduced the 

embryotoxic effects of AN in this system. 

 Similarly, a later experiment by this research group (Saillenfait and Sabaté, 2000) 

demonstrated that day 10 rat embryos exposed to AN for 46 hours in vitro showed concentrationrelated effects on growth, development, and morphology. Reduced growth (reduced yolk sac 

diameter and crown-rump length) occurred at 100 μM. The head length and somite number were 

reduced at 125 μM. Abnormal development (reduced prosencephalon and mesencephalon) and 

maxillary process defects occurred at ≥125 μM AN. Defects of the rhombencephalon and the 

auditory system were observed less frequently. These effects were characteristic of those 

developed by embryos exposed to sodium cyanide in culture. Addition of microsomes and 

NADPH to the culture medium containing 150 or 175 μM AN enhanced the observed growth 
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retarding and dysmorphogenic effects, especially in increasing the incidence of 

rhombencephalon and auditory system defects. 

 Saillenfait et al. (2004) evaluated the effects of eight aliphatic nitriles on the viability and 

differentiation of cultured limb bud cells from Sprague-Dawley rat embryos on GD 13. Limb 

bud micromass cultures were exposed for 5 days to AN at concentrations between 0.01 and 

0.45 mM (0.5 and 23.9 μg/mL), with or without microsomal activation, after which they were 

evaluated for cytotoxicity (neutral red uptake assay) and differentiation of chondrocytes (number 

and total surface of foci with Alcian blue staining were used as indicator of cell differentiation). 

The concentrations that inhibited cell viability and cell differentiation by 50% of concurrent 

untreated controls were determined. 

 The IC50 values were 0.24 mM (13 μg/mL) for cytotoxicity (viability) and 0.33–0.38 mM

(18–20 μg/mL) for differentiation (total surface of foci and number of foci), respectively. The 

ratios of IC50 for cytotoxicity and differentiation were 0.6 for number of foci and 0.7 for total 

surface of foci. Microsomal activation had no effect on the results with AN. In parallel 

experiments, the IC50 for cytotoxicity in cultured 3T3 cells (differentiated mouse fibroblast cell 

line) exposed to AN was 0.065 mM. The relative potency of the tested nitriles in this limb bud 

cell culture system matched previously published results for cultured whole embryos, but not 

necessarily for in vivo teratogenicity (false negative results were obtained for two of the eight 

nitriles). Saillenfait et al. (2004) characterized the response of AN in the micromass culture 

assay as equivocal, since it depended on the criteria used to define a positive result. According 

to one criterion, AN might be considered to have teratogenic potency because its IC50 was less 

than 50 μg/mL. However, under the “twofold rule” that defines a positive result by a value 

>2 for the ratio (IC50 for cytotoxicity)/(IC50 for differentiation), AN would be classified as 

having poor potential developmental hazard. As suggested by comparison of the IC50 for 

cytotoxicity, embryonic rat limb bud cells were not more vulnerable to AN than differentiated 

3T3 mouse fibroblasts. These suggestive results are consistent with the observations in vivo (see 

Section 4.3.2) that fetal toxicity from AN occurs only at exposure levels that cause maternal 

toxicity. 

4.4. OTHER DURATION- OR ENDPOINT-SPECIFIC STUDIES 

4.4.1. Acute Toxicity Data 

 Closely similar values have been reported for the oral LD50 in rats: 78 mg/kg (Benesh 

and Cherna, 1959), 93 mg/kg (Smyth and Carpenter, 1948), 90 mg/kg (Sprague-Dawley rats) 

(Younger Labs, 1992), and 81 mg/kg (male CF Nelson rats) (Vernon et al., 1990). Lower value 

has been published for the oral LD50 in mice: 25 mg/kg (H-strain, sex not stated) (Benesh and 

Cherna, 1959) and 36 and 48 mg/kg in male and female mice, respectively (strain not stated) 

(Tullar, 1947, as cited in IPCS, 1983). These findings indicate that mice are more susceptible to 

the acute toxicity of AN than are rats. Published LD50 values for guinea pigs (56 mg/kg) 
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(Jedlicka et al., 1958) and rabbits (93 mg/kg) (Paulet and Desnos, 1961) are in the same narrow 

range as those for rats and mice. For the inhalation route, median lethal concentration (LC50) 

values in rats of 217 ppm (470 mg/m3) (Knobloch et al., 1971) and 333 ppm (777 mg/m3) 

(Haskell Laboratory, 1992b) have been reported. However, exposing Sprague-Dawley rats to 

1,008 ppm AN for 1 hour failed to produce mortality (Younger Labs, 1992). A 4-hour 

LC50 value of 946 ppm (2,053 mg/m3) was reported for Sprague-Dawley rats following noseonly exposure (WIL Research Laboratories, 2005); no mortality was observed in male or female 

rats at exposures as high as 775 ppm (1,682 mg/m3) in this study. However, ataxia, labored 

respiration, and hypoactivity were observed at this exposure concentration and higher. 

LC50 values (duration not reported) of 138 ppm (300 mg/m

3

) in mice and 456 ppm (990 mg/m3) 

in guinea pigs have been reported (Knobloch et al., 1971). 

 As set forth in the English abstract of an article in Polish, Knobloch et al. (1971) 

investigated the acute and subacute toxicity of AN in BN mice, Wistar rats, and guinea pigs 

(strain not given). For rats, s.c. and i.p. LD50 values of 80 and 100 mg/kg, respectively, were 

reported. For mice, the LD50 was 34 mg/kg. 

 An earlier subacute study examined the effect of oral AN administration on the liver of 

sodium PB-pretreated (400 μmol/kg) or Aroclor 1254-pretreated (300 μmol/kg) male and female 

Sprague-Dawley rats that received 100 or 500 ppm AN in drinking water for 21 days (Silver et 

al., 1982). Other pretreated animals were given 0, 50, 75, 100, or 150 mg/kg AN by gavage for 

up to 3 days. Some liver-related biochemical changes were noted as a result of AN exposure, 

including a dose-dependent reduction in hepatic nonprotein sulfhydryl concentrations (maximal 

reduction of 81% at the highest dose of 150 mg/kg). Serum SDH activity was increased by 

fourfold 24 hours after administration of 150 mg/kg AN. On the other hand, SGPT activity was 

not significantly altered. Pretreatment with PB or Aroclor 1254 resulted in only a slight 

enhancement of AN-induced elevation of serum SDH or SGPT activities. In the experiment in 

which female rats were pretreated with either vehicle, PB or Aroclor 1254, and treated with 

100 ppm or 500 ppm AN for 21 days, there was a 60% increase in serum SDH activity in 

animals receiving 500 ppm AN in drinking water. 

In the 3-day studies, there was some evidence of focal superficial necrosis of the liver in 

rats receiving high gavage doses (100 or 150 mg/kg). This effect was associated with the 

presence of hemorrhagic gastritis and distention of the forestomach. However, while the 

biochemical and pathology changes implied a limited perturbation of the liver by AN, light 

microscopy showed only minor changes in the histopathology of the organ and no ultrastructural 

changes to the liver were evident when evaluated by electron microscopy. Silver et al. (1982) 

concluded that liver did not appear to be a target organ in the acute or subacute toxicity of AN. 

 Dudley and Neal (1942) exposed several species of laboratory animals—rat, guinea pig, 

rabbit, cat, dog, rhesus monkey—to AN vapor for 0.5–8 hours at concentrations ranging from 

0.063 to 5.3 mg/L (30–2,445 ppm). In rats (Osborne Mendel, sex not stated), 1,260 ppm was 
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found to be an effective lethal concentration when administered for 4 hours. During or after an 

8-hour exposure, 320 ppm AN was fatal. A 4-hour exposure to 260 ppm AN was fatal in rabbits 

(strain and sex not stated), while 1,160 ppm appeared to be a fatal concentration in guinea pigs. 

Other lethal concentrations were 600 ppm for 1.5 hours in cats and 110–165 ppm for 3 hours in 

dogs (breed not given, male and female), while Rhesus monkeys (males and females) tolerated 

90 ppm AN with only minor, transitory adverse effects (skin redness, sleepiness). In all species 

except guinea pig, AN caused an initial respiratory stimulation, followed by rapid, shallow 

breathing, nasal exudate, and watering eyes. In rats, the most striking symptom was reddening 

of the skin in the less prominently haired regions (nose, ear, feet). Reddening of the skin was 

also observed in the other species, again with the exception of guinea pigs. The study authors 

concluded that, in five of the six species investigated, AN-induced symptoms resembled cyanide 

poisoning. By contrast, AN acted as a severe pulmonary irritant in guinea pigs. Consistent with 

these findings, sodium nitrite (a cyanide antidote) protected five of the species studied, but not 

guinea pigs, from AN toxicity. The study authors postulated that guinea pigs may metabolize 

AN differently than rats, rabbits, cats, dogs, or monkeys, possibly by transformation to acrolein 

rather than cleavage of the cyano group. However, Dudley and Neal (1942) were unable to 

extract any cyanide from the tissues of animals that had succumbed to AN exposure. 

 Knobloch et al. (1971) evaluated the acute toxicity of AN via inhalation exposure 

(duration not given) in three species. The LC50 in mice was 0.30 mg/L (138 ppm), in rats 

0.47 mg/L (217 ppm), and in guinea pigs 0.99 mg/L (456 ppm). These values confirmed the 

roughly twofold species difference between rats and guinea pigs, but were about threefold lower 

than values reported by Dudley and Neal (1942). 

 Two studies by Gut et al. (1985, 1984) evaluated the subchronic toxicity of AN in rats 

when administered via inhalation. In both studies, male Wistar rats were exposed to 280 mg/m3

AN by inhalation 8 hours/day for 5 days (Gut et al., 1985, 1984). As shown in Table 4-48, BW 

was decreased in rats exposed to AN for 5 days. The absolute weight of liver decreased, while 

brain weight remained unchanged. Hence, the relative liver weight was significantly decreased, 

while relative brain weight increased due to the BW decrease. However, there were no 

significant histopathological changes in the lungs, livers, kidneys, or adrenals. The 

concentrations of glucose, pyruvate, and lactate were elevated in the brain and blood of exposed 

rats (Table 4-48). Treatment-related reductions in the concentrations of serum cholesterol and 

triglycerides were found in test animals. The study authors considered the increase in blood 

glucose concentration to be the most sensitive indicator of AN exposure under these 

experimental conditions (Gut et al., 1984). 
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Table 4-48. Effects of AN on organ weight, clinical chemistry, and 

biochemical parameters when administered to male Wistar rats via 

inhalation 

Parameter (units) Controls (n) AN (n)

BW (g) 341 ± 18 (8) 287 ± 24a (8) 

Relative liver weight (g/100 g BW) 3.39 ± 0.29 (8) 2.79 ± 0.08a (8) 

Relative brain weight (g/100 g BW) 0.564 ± 0.06 (8) 0.647 ± 0.076a (8) 

Serum triglyceride (mmol/L) 2.36 ± 0.51 (10) 1.47 ± 0.47b (10) 

Serum cholesterol (mg/dL) 72.3 ± 8.5 (10) 54.6 ± 12.9b (10) 

Pyruvate (mmol/L) 

Blood 0.080 ± 0.012 0.128 ± 0.028a (5) 

Brain 0.039 ± 0.007 0.068 ± 0.014a (5) 

Lactate (mmol/L) 

Blood 2.259 ± 0.577 (5) 4.032 ± 1.061a (5) 

Brain 6.002 ± 0.258 (5) 8.034 ± 0.471a (5) 

Glucose (mmol/L) 4.10 ± 0.21 10.22 ± 1.26c (5) 

a

Significantly different from controls (p < 0.05). 

b

Significantly different from controls (p < 0.001). 

c

Significantly different from controls (p < 0.01). 

Source: Gut et al. (1984). 

 Gut et al. (1984) further examined the dose-response effects of AN on blood glucose 

levels by giving food-deprived male Wistar rats a single 12-hour exposure of 0, 57, 125, or 

271 mg/m3

 AN. Blood glucose levels were dose-dependently increased at the end of the 

exposure period (4.33 ± 0.64 at 57 mg/m3; 10.88 ± 3.74 at 271 mg/m3 vs. 3.46 ± 0.29 mg/m3 in 

controls) but declined to normal or below normal levels 24 hours after exposure 

(1.79 ± 0.84 at 271 mg/m3

 vs. 4.73 ± 0.34 mg/m3 in controls). The simultaneous increase in the 

pyruvate and lactate concentrations suggests that AN affected carbohydrate metabolism on the 

level of glycolysis as well as on the citric acid cycle level. 

 In a subsequent study using exposure regimens identical to those in Gut et al. (1984), Gut 

et al. (1985) monitored AN-induced changes in sulfhydryl concentrations in the liver and brain 

and the appearance of thioethers (AN-mercapturic acid) and thiocyanate in the urine. GSH 

concentrations in the liver were significantly reduced compared with controls (3.86 ± 0.41 vs. 

7.66 ± 0.58 μmol/g) in rats exposed to AN for five consecutive daily 8-hour exposures at 

280 mg/m3

. No GSH depletion was evident in the brain. The protein sulfhydryl level remained 

unchanged in the brain but was increased by 17% in the liver, although not statistically 

significant. One out of 15 treated animals died, and the study authors suggested that GSH 

depletion could have been responsible. 
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Urinary excretion of thioethers and thiocyanate was proportional to the inhaled 

concentration. The ratio between urinary thioethers and thiocyanate in exposed rats was about 

2:4 and was not influenced by the exposed AN concentrations (Gut et al., 1985). 

 Bhooma et al. (1992) evaluated the effect of AN on the procoagulant activity in 

pulmonary alveolar macrophages of rats. Six male Wistar rats/group were exposed to 100 ppm 

AN 5 hours/day for 5 days. Animals were sacrificed at 1–28 days after the last exposure. The 

lungs were lavaged, and alveolar macrophages were collected from the broncho alveolar lavage 

(BAL) fluid. Procoagulant activity (the ability of a cell or cell products to accelerate the 

conversion of fibrinogen to fibrin) in macrophage and BAL fluid was determined. The 

procoagulant activity in the isolated macrophages from exposed animals was about 10-fold 

higher than in controls 1 day after AN exposure and then slowly declined to control levels by 

day 28 after exposure. Procoagulant activity of BAL fluid remained unaltered in rats sacrificed 

up to 7 days after exposure but was elevated in those sacrificed 14 and 28 days after exposure. 

The study authors noted that acute lung injury often resulted in deposition of fibrin in alveolar 

spaces (Bachofen and Weibel, 1977) and that fibrin and its degradation products have been 

implicated in contributing to pulmonary inflammation (Malik et al., 1979; Cuterman et al., 

1977). Since this study showed macrophage-associated procoagulant activity in the lung 

following inhalation to AN, the study authors suggested the alveolar macrophages participated in 

the pulmonary deposition of fibrin. 

 Other experimental studies have used acute dosing protocols to study toxicological 

effects of AN on various target organs. These studies are summarized in the following sections. 

4.4.1.1. Effects of AN on the GI Tract 

Two studies have reported GI hemorrhage and gastric erosion in rats administered with 

single doses of AN. In the first report (Ghanayem and Ahmed, 1983), a single dose of 50 mg/kg 

AN was administered to Sprague-Dawley rats (orally or s.c.). GI bleeding was observed 3 hours 

after treatment, with no significant difference in the amount of GI blood loss resulting from s.c. 

or oral administration. Thus, AN-induced GI bleeding was not a result of direct irritation of AN 

on the GI tract. A time-course study of a single 50 mg/kg dose of AN administered by the s.c. 

route indicated that the amount of blood recovered from the stomach was significantly higher 

than that of controls at 1, 2, and 3 hours after treatment, while the amount recovered from the 

intestinal contents was significantly higher than in controls at 2 and 3 hours. Dose-response 

study of s.c. administration of AN and GI bleeding indicated that significantly higher GI 

bleeding than in controls occurred at 40, 50, and 70 mg/kg AN, with the maximum at 50 mg/kg 

AN. 

Pretreatment of rats with the CYP450 enzyme inducer, PB, decreased the AN-induced GI 

blood loss by 55%, whereas pretreatment with Aroclor 1254 increased blood loss by 240% 

(Ghanayem and Ahmed, 1983). In contrast, pretreatment of rats with CYP450 inhibitors, cobalt 
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chloride or SKF 525A, prior to AN administration produced significant decreases in blood loss 

of 10 and 40%, respectively. Pretreatment of rats with diethylmaleate (DEM), a known depletor 

of GSH, prior to AN administration produced no significant change in GI bleeding. In addition, 

s.c. administration of a sublethal dose (6 mg/kg) of KCN did not induce GI bleeding when 

compared with controls, whereas 50 mg/kg AN produced significant GI bleeding. The study 

authors concluded that metabolic activation of AN to a reactive metabolite other than cyanide 

(probably CEO) by CYP450 was a prerequisite for AN to induce gastric hemorrhage. 

 In the second paper, Ghanayem et al. (1985) studied the mechanism of AN-induced 

gastric mucosal necrosis in the glandular stomach. Male Sprague-Dawley rats were treated with 

a single s.c. dose of AN (50 or 30 mg/kg), and the glandular stomach was removed and evaluated 

for histopathology and GSH concentrations. The liver was also removed for GSH determination. 

Gastric erosion severity index (GEI) was obtained for each exposure group by multiplying the 

mean severity score by the incidence of gastric necrosis in the group. Calculated GEI was found 

to be dose and time dependent: higher at 50 mg/kg than 30 mg/kg AN 3 hours after 

administration and in rats killed 3 hours as compared with rats killed 1 hour after the same dose 

of AN. 

Subcutaneous administration of 30, 40, or 50 mg/kg AN also caused a significant 

decrease in hepatic GSH concentration 3 hours after treatment, with greater decrease at lower 

dose (30 mg/kg) than in high dose (50 mg/kg). A significant decrease in gastric GSH 

concentrations was observed 3 hours after treatment at 40 and 50 mg/kg AN. Pretreatment of 

rats with various metabolic modulators (CYP450 monooxygenase and GSH) before 

administration showed that there was a significant inverse relationship between gastric GSH 

concentration and AN-induced gastric erosions. P450 inducers (Na PB and Aroclor 1254) alone 

increased GSH levels in the liver. Pretreatment of rats with these P450 inducers inhibited 

AN-induced gastric necrosis, and partially blocked AN-induced gastric GSH depletion. SKF 

525A, a CYP450 inhibitor, caused a slight depletion of gastric and hepatic GSH and potentiated 

the AN-induced gastric necrosis and GSH depletion. In contrast, cobaltous chloride, another 

inhibitor of CYP450 enzyme, inhibited AN-induced gastric necrosis and increased both the 

hepatic and gastric GSH concentrations. In rats treated with DEM, a depletor of GSH and AN, 

or DEM + cysteamine + AN, GEIs were increased up to fivefold when compared with rats 

treated with AN alone. Mucosal erosion severity in these two groups was also greatly increased, 

with more than 50% of rats showing severe or extensive lesions. Pretreatment of rats with 

sulfhydryl-containing compounds (cysteine or cysteamine) protected against AN-induced gastric 

necrosis and blocked the depletion of gastric GSH. 

In addition, AN-induced gastric erosions could be prevented by pretreatment with 

atropine, a muscarinic receptor blocker, suggesting the involvement of muscarinic receptors in 

the AN-induced gastric mucosal necrosis (Ghanayem et al., 1985). Activation of acetylcholine 

muscarinic receptors is known to increase gastric acid secretion and cause gastric erosions. 
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Because muscarinic receptors are known to contain sulfhydryl groups in their active site (Ikeda 

et al., 1980; Aronstam et al., 1978), Ghanayem et al. (1985) hypothesized that AN inactivated 

critical sulfhydryl groups and caused gastric erosions by locally modulating muscarinic 

acetylcholine receptors in the stomach. 

 More recently, Ahmed et al. (1996a) showed accumulation of AN-derived radioactivity 

in intestinal contents and intestinal mucosa following i.v. injection of 2-[14C]-AN to rats. A 

recent study by Jacob and Ahmed (2003a) also demonstrated that AN and or its metabolites 

accumulated and covalently interacted in GI mucosa of male F344 rats treated either i.v. or orally 

with 2-[14C]-AN. These studies supported the hypothesis that AN-induced injury of the GI 

mucosa is not due to direct irritation by AN but by metabolic incorporation and macromolecular 

interaction of AN in these tissues. 

4.4.1.2. Effects of AN on the Kidney 

 The acute nephrotoxic effect of AN was investigated in single exposure studies in rats 

and hamsters by inhalation or i.p. administration. Intraperitoneal injection of Chinese hamsters 

with 30 mg/kg AN increased kidney weight and renal GSH concentration 24 hours after injection 

(Zitting et al., 1981). Kidney deethylation activity was also decreased. Rouisse et al. (1986) 

administered i.p. doses (0, 10, 20, 40, 60, or 80 mg/kg) of AN to male F344 rats (six/dose group). 

Urinary volume was increased two- to threefold during the 24-hour period following 

administration for all dose groups. Urinary glucose was about 6 times higher in the 20 mg/kg 

group than in controls, and 40–60 times higher in the higher dose groups. Urinary excretion of 

N-acetyl-β-D-glucosaminidase was increased at the highest doses, up to 80% over controls in the 

80 mg/kg group. An increased number of lysosomes or dense bodies in renal proximal tubules 

was seen under the light or electron microscope. In the inhalation study, a similar array of 

toxicological and clinical chemistry effects relating to kidney structure and function was 

observed in male rats (seven/group) exposed to 200 ppm AN for 4 hours (Rouisse et al., 1986). 

4.4.1.3. Effects of AN on the Adrenal Gland 

 An experimental model for the toxicity of AN investigated the capacity of single i.v. 

doses of AN to induce acute hemorrhagic necrosis of the adrenal gland (Szabo et al., 1976). This 

condition has a parallel in man, the Waterhouse-Friderichsen syndrome, which is characterized 

by thrombocytopenia, disseminated intravascular coagulation, and the appearance of fibrin 

degradation products in the circulation (Szabo et al., 1976). The condition has been induced in 

female Sprague-Dawley rats by a single injection of 150 mg/kg AN into the jugular vein (Szabo 

et al., 1980) and typically has been marked by massive “bilateral apoplexy,” a usually fatal 

hemorrhagic necrosis of the adrenal glands that occurs in 90–100% of the rats within 90–

150 minutes. Thrombocytopenia and a range of associated clinical signs, including tremors, 

cyanosis, and ultimately respiratory failure, were observed. Light and electron microscopy 
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showed that an early event in the onset of this condition was damage to the vascular endothelium 

of the adrenal cortex, with parenchymal injury as a late event. However, these AN-induced 

lesions could be prevented by pretreatment with the α-adrenergic antagonist phenoxybenzamine, 

the α,β-blocker labetalo, or the 11-β-hydoxylase inhibitor metyrapone. Elevation of tissue 

sulfhydryl levels by cysteine or GSH reduced the adrenal apoplexy. Dopamine concentrations in 

the adrenals increased over time. Because depletion of catecholamines by reserpine, or 

medullectomy, could prevent the chemically induced adrenocortical necrosis, the study authors 

proposed that cortical damage resulting from AN was associated with vasoactive amines released 

from the medulla and/or with metabolites of AN. 

4.4.1.4. Effects of AN on Neurological Endpoints 

 Neurotoxic effects were induced in male Sprague-Dawley rats receiving single gavage or 

s.c. doses of 20, 40, or 80 mg/kg AN (Ghanayem et al., 1991). Two distinct phases of 

neurological response were evident. The early phase was cholinomimetic in nature, with signs 

such as salivation, lacrimation, polyuria, miosis, vasodilatation, gastric secretion, and diarrhea. 

The second phase developed 4–5 hours later with toxic signs, including depression, convulsions, 

and respiratory failure, followed by death at the higher doses. These CNS effects were observed 

in rats treated with 40 and 80 mg/kg and were similar to those caused by cyanide. Pretreatment 

of animals with 1 mg/kg atropine, an acetylcholine muscarinic antagonist, abolished the 

cholinomimetic toxicity, implicating an involvement of the cholinergic system in some aspects 

of acute AN neurotoxicity. Since effects were observed even at the lowest dose, a NOAEL was 

not identified, and 20 mg/kg was the LOAEL. 

 In another study, male Sprague-Dawley rats that were administered s.c. doses of 

112 mg/kg AN (LD90) showed a biphasic response consisting of an early phase with tremors and 

seizures about 100 minutes after dose administration, followed by severe clonic convulsions that 

preceded death at about 3–4 hours (Benz and Nerland, 2005). The effects of preadministered 

inhibitors of oxidative metabolism by CYP450 (80 mg/kg SKF 525A, 75 mg/kg 

1-benzylimidazole, or 100 or 200 mg/kg metyrapone) and an alternative CYP450 substrate, 

ethanol (5,000 mg/kg), on the acute convulsions were examined. Although blood levels of 

cyanide, and the development of the first phase of tremors and seizures, were inhibited by 

1-benzylimidazole or ethanol, treatment with these two agents did not prevent the terminal 

convulsions or the death of rats injected with 112 mg/kg AN. Ethanol, being a CNS depressant, 

decreased the incidence of terminal convulsion (5/17 vs. 15/17). These results suggested that the 

initial phase of the acute neurotoxically lethal effects may have been due to cyanide, which is 

released via the CYP450 metabolic pathway for AN, and that the second phase was mediated by 

the parent compound. 

Because ethanol showed some effect on lessening the second phase response to AN 

(although it did not prevent lethality), several anticonvulsants were examined for their ability to 
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counteract the acute neurotoxicity and lethality of 112 mg/kg AN. Administration of PB 

(25 mg/kg) or phenytoin (150 mg/kg) (but not 144 mg/kg valproic acid) markedly inhibited the 

lethal response to 112 mg/kg AN: 9/10 rats died following administration of AN alone or AN 

plus valproic acid, whereas 1/10 and 2/10 rats died following administration of AN plus PB or 

AN plus phenytoin, respectively. The protection by phenytoin and PB against convulsion and 

lethality was not due to inhibition of metabolism of AN to cyanide, since only phenytoin was 

able to lower blood cyanide levels (by about 32%), and was much less effective than 

1-benzylimidazole or ethanol (97 and 94%, respectively). 

4.4.1.5. Effects of AN on Hearing 

 AN is one of a number of organic compounds that have been shown to promote noiseinduced hearing loss (NIHL) in rats (Fechter, 2004; Fischel-Ghodsian et al., 2004). The 

ototoxicity of AN was examined in several experiments in male Long-Evans rats exposed by s.c. 

injection (Fechter et al., 2003). The AN used in these experiments was stabilized to minimize 

the accumulation of peroxides. Ten rats were anesthetized and surgically prepared for the 

assessment of the compound action potential (CAP), which represents the synchronous neural 

activity elicited by primary auditory neurons (spiral ganglion cells) and directly measures 

auditory threshold sensitivity. Auditory thresholds at each test frequency were measured for 

each rat under anesthesia on 20 different occasions before treatment with AN to determine 

baseline auditory thresholds. Auditory thresholds for 11 test frequencies between 2 and 40 kHz 

were recorded at 5-minute intervals up to 100 minutes postinjection with AN. The acute effect 

of 50 mg/kg s.c. AN on auditory sensitivity was studied in five rats; five control rats were 

injected only with water. In a second study, the effects of AN on permanent NIHL were 

evaluated in six experimental groups (six rats each) that received the following: no treatment; 

50 mg/kg AN alone, two injections of 50 mg/kg-day AN on 2 consecutive days, noise alone 

(108 dB octave-band noise for 8 hours), single injection of 50 mg/kg AN immediately followed 

by noise, and exposure to noise after a second injection of AN. 

 The acute study showed that exposure to 50 mg/kg AN s.c. alone elevated auditory 

threshold temporily and produced a 10–20 dB loss in auditory threshold sensitivity (temporary 

threshold shift) in the stimulus range of 8–40 kHz (Fechter et al., 2003). This transient loss 

reached a maximum within 10–20 minutes after injection but returned to control levels within 

75–100 minutes. In the study on permanent auditory threshold shifts, when rats were tested 

3 weeks following AN and AN + noise treatment, exposure to AN alone did not produce a 

persistent loss in auditory threshold sensitivity. AN-treated rats had slightly reduced auditory 

threshold compared with controls, indicating slightly increased sensitivity (within 5 dB of 

controls), but the difference was not statistically significant. Noise treatment alone elevated 

auditory thresholds by less than 20 dB at all tested frequencies. However, rats given two 

injections of AN followed by noise in the high frequency range of 12–40 kHz exhibited auditory 
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impairments averaging 27 dB (maximally 40 dB) compared with controls; this shift was 

statistically significant compared with other groups (controls, noise alone, AN alone, or no 

treatment). Rats given a single injection before exposure to noise showed an average 11 dB 

threshold shift in the high-frequency range (12 and 40 kHz). This study demonstrates that 

exposure to AN exacerbated NIHL. 

 Fechter et al. (2003) also assessed blood cyanide and glutathione levels in brain, liver, 

and paired cochleae in additional groups of rats exposed to AN. Groups of five rats given 20, 50, 

or 80 mg/kg s.c. AN produced peak levels of cyanide, a metabolite of AN, in the blood at 1 hour 

(for 20 and 50 mg/kg) and 2 hours (for 80 mg/kg) following injection. Cyanide levels returned 

to baseline values within 2, 3, and 4 hours, respectively. Since AN produced maximal auditory 

threshold impairment within 20 minutes of administration, before blood cyanide level peaked at 

1 hour, the acute ototoxic effect of AN was not likely associated with elevated cyanide levels. 

 When rats were given a single injection of 50 mg/kg, maximal reductions in glutathione 

levels (measured between 15 minutes and 8 hours postinjection) were detected in the brain by 

15 minutes (–50%), in the liver by 1 hour (–80%), and in the cochlea by 2 hours (–45%). 

Cochlear glutathione levels remained depressed for about 4 hours. Recovery of glutathione 

levels to near control levels was achieved in all tissues by 8 hours. Since AN induced transient 

cochlear function loss that peaked within 10–20 minutes after injection and recovered within 75–

100 minutes, the acute ototoxic effect of AN could not be associated with GSH level in the 

cochlea. Fechter et al. (2003) concluded that, while AN-induced oxidative stress in the cochlea 

may play a role by which AN promotes NIHL, the acute ototoxic effect of AN might reflect 

other unidentified toxic action of AN in the cochlea. 

 Fechter et al. (2004) extended their evaluation of the potentiation effect of AN exposure 

on NIHL. Two experiments were conducted: the first experiment studied the effects of a single 

AN exposure on permanent NIHL, while the second one evaluated the effects with five daily AN 

and noise exposures. In both experiments, six male Long-Evans rats were assigned to each 

treatment group: AN alone, noise alone, AN + noise, and untreated controls. AN exposed 

groups were given s.c. injections of 50 mg/kg-day AN, with or without 4 hours of exposure to 

noise (105 dB), and then assessed for auditory threshold sensitivity 4 weeks later. 

 In the single-day treatment study, AN alone did not alter the auditory threshold, but a 

single AN exposure in combination with noise significantly elevated auditory thresholds by an 

average of 10 dB above the effect of noise alone. Noise exposure alone increased auditory 

thresholds compared with controls by an average of 10 dB in the range of 12–40 kHz (Fechter et 

al., 2004). In the 5 consecutive-day treatment study, AN plus noise treatment exacerbated the 

impairment induced by noise alone by an average of 30–45 dB at frequencies between 20 and 

40 kHz and by no more than 10 dB at frequencies <16 kHz. Similar to the single-exposure 

study, repeated AN exposure had no effect on auditory thresholds assessed 4 weeks later. 

Repeated noise exposure elevated auditory thresholds about 17 dB above control rats. 
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 When the reactive-oxygen scavenger phenyl-N-tertiary-butylnitrone (PBN) (100 mg/kg 

i.p.) was injected twice daily for 5 days prior to exposure to noise alone and rats were assessed 

4 weeks later, PBN reduced the magnitude of hearing loss. When PBN was injected daily prior 

to the injection of AN and again following noise exposure, the magnitude of hearing loss was 

equivalent to that exhibited by rats treated by noise alone. (No significant difference was found 

between rats receiving noise alone and those receiving PBN plus noise.) These results indicated 

that reactive oxygen species (ROS) were responsible for the ototoxic effects of AN. These 

findings are consistent with the suggestion that mitochondria injury within cochlear cells, 

primarily or secondarily through oxidative stress, may be a common feature of ototoxicity 

induced by chemicals and noise (Fischel-Ghodsian et al., 2004). 

 Results from a recent study indicated that hearing loss from AN and noise exposure 

involves histologic damage to hair cells on the surface of the organ of Corti (Pouyatos et al., 

2005). Groups of five male Long-Evans rats were given s.c. injections of 0 or 50 mg/kg-day AN 

for 5 consecutive days, with or without exposure 30 minutes later to noise for 4 hours/day (95 or 

97 dB octave-band noise at 8 kHz). Hearing dysfunction of these rats were then assessed by: 

(1) distortion product otoacoustic emissions (DPOAEs) before exposure, as well as 1 hour and 

4 weeks postexposure; (2) CAP for auditory threshold sensitivity 4 weeks after the last treatment; 

and (3) number of hair cells on surface preparation of the organ of Corti 4 weeks after treatment. 

Permanent effects on these endpoints (i.e., effects observed 4 weeks following the last treatment) 

were only observed in rats exposed to both AN and noise and not in rats exposed to AN or noise 

alone. Permanent effects from combined exposure to AN and noise included auditory threshold 

shifts (13–16 dB between 7 and 40 kHz), a decrease in DPOAE amplitudes (up to 25 dB at 

19 kHz), and significant outer hair cell (OHC) loss in the cochleae. With the AN plus 97 dB 

treatment, average OHC loss was 20, 16, and 9% in the first, second, and third rows, 

respectively, in the areas corresponding to frequencies ranging from 13 to 47 kHz. Similar 

effects were found in the AN plus 95 dB treatment group. This study demonstrated AN could 

potentiate NIHL at noise levels that are relevant to human exposure. 

 Pouyatos et al. (2007) further proposed that AN exacerbated NIHL by decreasing 

antioxidant defenses of hair cell. This hypothesis was tested in a study in which the capability of 

specific antioxidants in the protection of the cochlea of male Long-Evans rats treated with 

50 mg/kg AN s.c. 30 minutes prior to the daily noise exposure of 97 dB sound pressure level 

4 hours/day for 5 days. Sixty-five Long-Evans rats (2–12/group) were exposed to different 

combinations of noise, AN, and antioxidants; AN alone or AN + STS (150 mg/kg i.p.), a CN 

inhibitor; AN + 4-methylpyrazole (4MP,100 mg/kg i.p.), a drug that blocks CN generation by 

competing with CYP2E1; AN + L-N-acetylcysteine (L-NAC) (4 × 400 mg/kg, orally), a 

pro-GSH drug; noise (97 dB octave band of noise [OBN]/8 kHz) alone; noise and STS, 4MP, or 

L-NAC; or noise plus AN and antioxidants. To evaluate auditory impairment, DPOAEs and 

CAPs were measured prior to experimental treatment and 3 days and 4 weeks after treatment. At 
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the end of exposure, cochleae were harvested for histologic examination. Additional rats (n = 

64) were used to measure cochlear and liver GSH and blood CN levels at different time points 

after treatment. 

 At 3 days postexposure, similar auditory loss was found in animals exposed to AN + 

noise, STS + AN + noise, 4MP +AN + noise, and L-NAC + AN + noise. The maximum shifts 

averaged 25–30 dB between 12 and 32 kHz. At 4 weeks postexposure, animals exposed to 

L-NAC + AN + noise recovered to baseline levels above 25 kHz. However, at lower 

frequencies, L-NAC did not prevent auditory loss caused by AN + noise exposure. Animals 

received combined exposure to AN + noise, and AN + noise + STS or AN + noise + 4MP 

showed little change in producing auditory loss. 

 In addition, the cochleae from rats exposed to AN and noise demonstrated substantial 

damage in the basal half of the organ of Corti. Mean OHC loss averaged 35% in the three rows 

in the region corresponding to frequencies above 12 kHz. Neither STS nor 4MP pretreatment 

protected against OHC loss caused by AN + noise. However, pretreatment with L-NAC reduced 

the OHC loss caused by AN + noise in the region corresponding to 25 kHz and above. 

Liver GSH level was depleted by 63% 1 hour after AN injection. Cotreatment with STS 

or 4MP reduced GSH level about 80% at 1 hour and 52% at 3 hours. However, with L-NAC 

pretreatment, GSH level was reduced only by 23 and 20% at 1 and 3 hours, respectively. 

Similarly, whereas AN treatment depleted cochlear GSH levels to undetectable levels at 1 hour, 

STS pretreatment had no effect on GSH depletion. 4MP pretreatment only slightly reduced GSH 

depletion. However, L-NAC pretreatment not only protected but induced an increase in GSH 

levels above control levels. Pouyatos et al. (2007) concluded that, since L-NAC cotreatment 

reduced auditory loss and OHC loss from AN + noise treatment, GSH is involved in the 

protection of the cochlea against ROS generated by moderate noise levels. However, CN did not 

appear to be involved in this potentiation. 

4.4.2. Immunological Effects of AN 

 A case study by Balda (1975) described a human subject who developed contact 

dermatitis following the use of a Plexidur finger splint. Investigators obtained a positive result in

a patch test with AN, which is one of the constituents of the polymer Plexidur. This observation 

suggested that AN might induce immunological response in exposed subjects. 

The immunotoxicity of AN was evaluated in groups of six male CD-1 mice given a 

single oral dose in water or repeated oral doses for 5 or 14 days (Ahmed et al., 1993). In each of 

these experiments, a positive control group received a single immunosuppressive dose of 

225 mg/kg of cyclophosphamide i.p. In the first experiment, mice given a single gavage dose of 

0 or 13.5 mg/kg AN in water were evaluated 3 or 5 days later for BW, relative organ weights 

(thymus, spleen, liver, and kidney), number of viable splenocytes, and total and differential 

WBC counts in spleen cells suspension (Ahmed et al., 1993). AN slightly reduced BWs in mice 
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(6–7%) after 3 and 5 days, but the difference was not biologically significant. In treated mice, 

relative spleen weights were increased by 50% after 5 days, whereas relative thymus weights 

were decreased by 42% after 5 days; relative liver weight was decreased by 11% on day 3 but 

was 9% higher than controls on day 5. AN treatment reduced total leucocytes by 42–57%, 

lymphocytes by 39 and 65%, monocytes by 38 and 50%, and neutrophils by 67 and 73% on 

days 5 and 3, respectively. 

 In the second experiment, mice received 0 or 6.75 mg/kg-day of AN in water on 

5 consecutive days and were evaluated on day 6 (Ahmed et al., 1993). In mice treated for 

5 days, BWs were reduced by 27%, relative liver weights were decreased by 10%, and relative 

spleen weights were increased by 25%. Total splenocytes were decreased by 51%, with total 

blood leucocytes and lymphocytes reduced by 48 and 68%, respectively; circulating monocytes 

were increased by 88%. The immunotoxic effects of AN in both studies were comparable to 

effects elicited by the known immunosuppressant cyclophosphamide. 

 In a third experiment, groups of male CD-1 mice (six/group) were treated with AN by 

gavage in water for 14 days (Ahmed et al., 1993). There were a total of nine groups: three 

groups dosed with AN at 1.35, 2.7, or 5.4 mg/kg-day only, three groups dosed the same way but 

immunized with sheep red blood cells (SRBCs) on day 9 of exposure, and three concurrent 

control groups (normal, SRBC-immunized, and a positive control group treated intraperitoneally 

with cyclophosphamide [225 mg/kg] 1 day before immunization). Mice were evaluated for total 

BW, relative organ weights (thymus, spleen, liver, and lung), number of splenocytes, total and 

differential WBC counts in spleen cell suspensions, and histopathology of lymph nodes, lung, 

and intestinal Peyer’s patches. Subsets of spleen lymphocytes (T and B cells) were enumerated 

by flow cytometry. Spleen cells from mice immunized with SRBCs were evaluated in a plaqueforming cell assay. 

 In nonimmunized mice, AN decreased BW by 12–15% and increased relative thymus 

weights by 43% at 2.7 mg/kg-day and relative lung weights by 39% at 5.4 mg/kg-day. AN 

increased splenocyte viability by 49–264% in a dose-independent manner. AN also caused doseindependent increases of 126–293% in relative spleen weight at all doses. Total leukocyte 

counts/spleen were increased by 171, 119, and 107% at the low to high doses; lymphocyte 

counts/spleen were significantly reduced by 25–45% at all doses, while monocyte and neutrophil 

counts/spleen were increased concomitantly by as much as 78-fold. Reductions in lymphocyte 

subsets were observed at all doses: T-cells by 40–53%, B-cells by 32–36%, T-helper cells by 

40–59%, and T-suppressor cells by 49–62%. Histological examination revealed severe 

enlargement of mesenteric lymph nodes and intestinal Peyer’s patches, abscesses and massive 

necrotic damage in the lung, and swellings in the brachial lymph nodes in mice treated with AN 

at all doses but more aggressive in the 5.4 mg/kg group. No incidence data were reported for 

these lesions. Some of the mice treated with 5.4 mg/kg-day died rapidly. Microbiological 
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examination revealed the swelling in the lymph nodes was related to migration of normal 

intestinal flora, which the study authors attributed to immunosuppressive effects of AN. 

 In the SRBC-immunized mice, AN treatment did not affect the BW. The relative weight 

of lung, liver, and thymus showed inconsistent and dose-independent increases. The viable 

spleen cells showed 77% increases only in the 2.7 mg/kg group. The lymphocytic count showed 

dose-independent decreases. However, the neutrophilic and monocytic counts showed large 

increases at all doses. Decreases in lymphocyte subsets were found in all three doses of AN: 

T-cells by 42–45%, B-cells by 37–50%, T-helper by 43–54%, and T-suppressors by 40–48%. 

The IgM antibody plaque forming cell response was decreased by 55, 23, and 65 after treatment 

with 1.35, 2.7, and 5.4 mg/kg AN, respectively. The lowest dose used in this study, 1.35 mg/kgday, was a LOAEL for immunotoxicity (suppression of humoral and cell-mediated immunity) in 

mice treated for 14 days. 

 Hamada et al. (1998) further investigated the immunotoxicity of AN by administering 

2.7 mg/kg-day AN (1/10 the LD50) to male CD-1 mice orally for either 5, 10, or 15 days. All 

mice were injected with 100 mg/kg bromodeoxyuridine (BrdU) i.p. 1 hour before sacrifice. An 

immunohistochemical assessment of the number of cells capable of producing IgA in different 

intestinal compartments as a result of AN administration was conducted. Uptake of 

3H-thymidine into splenocytes derived from treated animals and stimulated with different 

mitogens—phytohemagglutinin (PHA), concanavalin-A (con-A), or lipopolysaccharide (LPS)—

was measured. The rate of proliferation of gut epithelial cells of different intestinal 

compartments was determined by the incorporation of BrdU in newly synthesized DNA of 

S-phase cells. 

 The mitogenic response of mouse splenocytes to PHA, con-A, and LPS was affected by 

AN exposure as shown by a significant decrease in [3H]-thymidine incorporation (Table 4-49). 

The decreases were 68–79% with con-A and 35–57% with LPS, depending on the time intervals. 

However, uptake of [3H]-thymidine by splenocytes after stimulation with PHA was markedly 

reduced only after 15 days of exposure. These results suggested that AN induced systemic 

suppression of humoral immunity (by the decrease in mitogen response to LPS) and cellmediated immunity (by the inhibition of mitogen response to con-A and PHA). 
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Table 4-49. Time course of the effect of AN administration on 

[

3H]-thymidine uptake into mouse splenocytes under the influence of 

different mitogens in vitro 

D of AN treatment

Mitogens Control 5 10 15

PHAa 1,331 ± 163 1,203 ± 265 1,434 ± 35 898 ± 32b

con-Aa 14,927 ± 972 4,756 ± 532b 4,792 ± 946b 3,198 ± 448b

LPSa 1,225 ± 112 803 ± 87b 486 ± 2b 522 ± 31b

aValues are counts/min, mean ± standard error of the mean; n = 4. 

b

Significantly different from controls (p < 0.05) as calculated by the authors. 

Source: Hamada et al. (1998). 

 Inhibition of [3H]-thymidine uptake by stimulated spleen lymphocytes may indicate a 

systemic immunosuppression by AN. Such an effect could also occur locally, as indicated by a 

reduction in the number of IgA-producing cells in all intestinal compartments following AN 

administration. The counts of IgA-producing cells were reduced by 56–77% in the duodenum, 

44–67% in the jejunum, and 60–62% in the ileum. Another local effect of AN was demonstrated 

by the increased incorporation of BrdU into epithelial cells of the duodenum (threefold) and 

ileum (1.6-fold) of AN-treated animals. This result indicated that the rate of cell proliferation 

was markedly increased following oral AN administration, even as a result of short-term 

treatment. The study authors considered this to be the result of a regenerative response to 

chemically induced intestinal injury and suggested that AN-induced immunosuppressive effect 

systemically and locally in the gut, as well as increases in the rate of cell proliferation, may 

contribute to carcinogenicity of AN in the gut. 

Summary 

 AN caused contact dermatitis in a human subject exposed via the use of Plexidur finger 

splint. In mice, AN suppressed cell-mediated and humoral immunity systemically and locally in 

the intestine. Table 4-50 summarizes immunotoxicity studies of AN. 
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Table 4-50. Summary of immunotoxicity studies of AN 

Test 

species Endpoint/effect

Exposure 

concentration/condition

Exposure 

duration Results References

Human 

subject 

Contact dermatitis Use of a Plexidur finger splint ND Positive patch test Balda, 1975 

Study 1: 

Single dose of 0 or 

13.5 mg/kg AN in water 

(oral) 

 

225 mg/kg cyclophosphamide 

as positive control 

3 or 5 d Increased relative spleen 

by 50%, decreased 

relative thymus weight 

by 42%, reduction in 

total leucocytes, 

lymphocytes, 

monocytes, and 

neutrophils. 

Study 2: 

0 or 6.75 mg/kg-d AN in 

water 

225 mg/kg cyclophosphamide 

as positive control. 

5 d Increased relative spleen 

weights by 25%; 

decreased total 

spenocytes by 51%; 

reduction in total blood 

leucocytes and 

lymphocytes by 48 and 

68%, respectively. 

Male CD-1 

mice 

(n = 6) 

Immunosuppressive 

Effect 

Study 3: 

a. Three groups dosed with 

1.35, 2.7, or 5.4 mg/kg-d AN 

b. Three groups dosed with 

1.35, 2.7, or 5.4 mg/kg-d AN, 

but immunized with SRBCs 

on d 9 of exposure 

c. Three concurrent control 

groups (normal, SRBCimmunized) 

d. a positive control group 

treated intraperitoneally with 

cyclophosphamide 

(225 mg/kg) 1 d before 

immunization 

14 d In nonimmunized mice: 

increased spleen weight 

at all doses, increased 

total leukocyte counts, 

reduced lymphocyte 

counts/spleen, and 

increased monocyte and 

neutrophil 

counts/spleen. 

Enlargement of 

mesenteric lymph nodes 

and intestinal Peyer’s 

patches, swellings in the 

brachial lymph nodes for 

all dose groups. 

In the SRBC-immunized 

mice: viable spleen cells 

showed 77% increase in 

the 2.7 mg/kg group. 

Decreases in 

lymphocyte count, 

increases in neutrophilic 

and monocytic counts, 

and decreases in plaque 

forming cell response 

were observed. The 

LOAEL for 

immunotoxicity was 

1.35 mg/kg-d. 

Ahmed et al., 

1993 
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Table 4-50. Summary of immunotoxicity studies of AN 

Test 

species Endpoint/effect

Exposure 

concentration/condition

Exposure 

duration Results References

Male 

CD-mice 

Systemic and local 

immunosuppression

2.7 mg/kg-d AN orally 5, 10, or 

15 d 

Decrease 3H-thymidine 

incorporation into 

splenocytes in: (1) mice 

treated with mitogens 

con-A or LPS, 

suggesting systemic 

suppression of cellmediated immunity, and 

(2) mice treated with 

mitogen PHA, 

suggesting systemic 

suppression of humoral 

immunity. 

Local 

immunosuppression in 

the gut, as indicated by: 

(1) reduction in the 

number of IgAproducing cells in all 

intestinal compartments, 

and (2) increased 

proliferation of 

epithelial cells of the 

duodenum. 

Hamada et al., 

1998. 

4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUPPORT OF THE MODE OF 

ACTION 

4.5.1. Mode-of-Action Studies 

 Studies have been conducted with the primary purpose of evaluating the potential 

mechanisms by which AN and/or its metabolites produce noncancer and cancer effects in 

experimental animals. Studies that investigated potential mechanisms for noncancer effects 

include GI hemorrhaging, effects on Hb and metabolism in RBCs, neurotoxicity, oxidative 

stress, and immunotoxicity. Studies that investigated the potential mechanisms for the 

carcinogenicity of AN include formation of DNA adducts, oxidative stress, intercellular 

communication, and cell proliferation. In addition, genotoxicity studies are described in 

Section 4.5.2. 

4.5.1.1. Noncancer Endpoints 

4.5.1.1.1. GI hemorrhaging. Ghanayem and Ahmed (1983) administered AN to male SpragueDawley rats by both s.c. or oral routes, in each case observing significant gastric bleeding (see 

Section 4.4.1.1). The response appeared to peak at 50 mg/kg, the effect being maximal at 

2 hours after a 50 mg/kg s.c. dose. Different CYP450 inducers had different effects: 

Aroclor 1254 more than doubled the effect, while PB reduced the bleeding by half. CYP450 
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inhibitors SKF 525A and cobalt chloride were even more effective, with cobalt chloride reducing 

gastric bleeding to almost untreated levels. GSH depletion by DEM did not prevent 

hemorrhaging. The effect was not due to cyanide release from AN, since KCN administration 

(6 mg/kg) did not induce bleeding. The results indicated that the gastric hemorrhaging was 

caused by metabolic activation of AN to a reactive metabolite other than cyanide (probably 

CEO). 

 As described in Section 4.4.1.1, the follow-up study by Ghanayem et al. (1985) 

demonstrated that pretreatment of rats with sulfhydryl-containing compounds or atropine 

protected the rats from AN-induced lesions. The findings suggested that modulation of 

muscarinic receptors by AN increased gastric acid secretion and caused gastric mucosal erosions. 

4.5.1.1.2. Effects on Hb and metabolism in RBCs. Farooqui and Ahmed (1983b) studied the 

effect of AN on Hb and metabolism in RBCs both in vivo and in vitro. Male Sprague-Dawley 

rats (three/group) were administered a single oral dose of 80 mg/kg aqueous AN, and blood was 

collected 1 hour after treatment. Other groups of animals were sacrificed at 3, 6, and 24 hours 

after dosing. Mean cell Hb concentration, hematocrit, and platelet counts were reduced to 

78, 79, and 71% of the controls 1 hour after dosing. GSH levels were lowered significantly 

within 1 hour. Among the metabolic intermediates measured, a reduction in the intracellular 

concentration of 2,3-diphosphoglyceric acid and increases in intracellular levels of ATP, 

pyruvate, and lactate were observed. The increase in the levels of pyruvate and lactate, which 

were end products of glycolysis, suggested an increase in the metabolic rate in RBCs as a result 

of exposure to AN (Table 4-51). A significant decrease in the activity of 2,3-diphosphoglycerate 

mutase, an erythrocyte enzyme, was found in treated animals (3.61 ± 0.21 IU/g Hb in treated 

animals after 1 hour vs. 4.57 ± 0.23 IU/g Hb in controls). In general, the intermediates studied 

returned to normal values between 6 and 24 hours. 

Table 4-51. Effect of AN on RBC metabolic intermediates following a single 

oral dose 

Intermediates AN treatment

(μmol/mL blood) Control 1 hr 3 hrs 6 hrs 24 hrs

2,3-Diphosphoglycerate 3.6 ± 0.3 2.8 ± 0.2a 3.0 ± 0.4 3.2 ± 0.3 3.7 ± 0.5 

Adenosine triphosphate 0.49 ± 0.04 0.60 ± 0.05a 0.64 ± 0.06a 0.66 ± 0.06a 0.58 ± 0.05 

Pyruvate 58 ± 6 227 ± 21a 187 ± 13a 175 ± 16a 167 ± 11a

Lactate 1,478 ± 131 9,932 ± 211a 1,889 ± 129a 1,955 ± 160a 2,079 ± 151a

GSH 1.39 ± 0.11 0.28 ± 0.02a 0.34 ± 0.04a 0.47 ± 0.05a 1.27 ± 0.15 

a

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Source: Farooqui and Ahmed (1983b). 
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 In another study, male Sprague-Dawley rats were treated with single oral doses of 

46.5 mg/kg [2,3-14C]-AN (Farooqui and Ahmed, 1983b). RBC GSH concentrations were 

lowered to 10% of controls in 1 hour, followed by a slow recovery of 10% in 5 hours. Extensive 

covalent binding of AN to Hb (about 1.7 μmol equivalents of AN bound/mL RBCs) in 1 hour 

was also observed. 

 For the in vitro study, isolated RBCs from male Sprague-Dawley rats were incubated 

with 5 mmol/L AN at 37°C to investigate the ability of AN to interact covalently with Hb and 

deplete GSH, and the effect of such depletion on Hb (Farooqui and Ahmed, 1983b). GSH in the 

supernatant and in the RBCs was estimated by measuring nonprotein sulfhydryl groups. In 

addition, the levels of Hb and MetHb and GSH conjugates with AN were monitored. 

 Incubation of rat RBCs with AN caused a depletion of more than 85% of intracellular 

GSH within 1 hour. No hemolysis occurred during the incubation period. In addition, GSH was 

not detected in the incubation media. Most of the GSH in the RBCs was converted to a 

GSH-AN conjugate, S-cyanoethyl GSH. This conjugate was present in the RBCs after 24 hours, 

suggesting that it was not metabolized further at least for 24 hours. Moreover, about 6% of Hb 

was converted to MetHb in 1 hour and 8% in 3 hours (Farooqui and Ahmed, 1983b). MetHb 

levels in controls during this time period were 0.61–0.87%. 

 The rate and extent of MetHb reduction to Hb in AN-treated RBCs was also determined 

to investigate if this protective mechanism against such oxidative damage to Hb was affected. 

Incubation of nitrite-treated RBCs (for conversion of Hb in RBCs to MetHb) with AN resulted in 

a significant decrease in MetHb reduction, with a 70% decrease in RBCs treated with 10 mM 

AN when compared with controls. In the same experiment, AN initiated hemolysis of RBCs at a 

concentration of <0.1 M. 

 Farooqui and Ahmed (1983b) suggested that the effects of AN on RBC metabolism were 

related to the availability of GSH. Oxidative stress induced by depletion of GSH as a result of 

AN exposure may have stimulated the rate of RBC metabolism, based on increase in the end 

products of glycolysis. Another possible explanation could be the impaired permeability of the 

erythrocyte membrane due to extensive covalent binding of AN, resulting in the retention of 

metabolic products. Since the levels of ATP and 2,3-diphosphoglycerate were altered and these 

two intermediates regulate the oxygen dissociation curve, it was concluded that chronic exposure 

to AN may lead to methemoglobinemia, damage to the RBC membrane, and impaired delivery 

of oxygen to tissues. 

 Farooqui et al. (1990) provided in vitro data on the effect of AN on lipid metabolism in 

RBCs. Three types of RBC preparations from male Sprague-Dawley rats were incubated with 

AN: those containing oxyhemoglobin (HbO), those containing MetHb, and those containing 

carboxyhemoglobin (HbCO). HbO-containing RBCs were taken directly from the RBC pellet; 

MetHb-containing RBCs were produced by incubating packed RBCs with 0.5% sodium nitrite; 

while RBCs containing HbCO were prepared by blowing carbon monoxide over a 20% 
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suspension (volume/volume [v/v]) of RBCs until the visible spectrum of red cell lysate reached a 

maximum at 570 nm. All preparations of RBCs were incubated for 1 hour with 10 mM AN and 

variable additions of glucose. Following incubation, supernatants were removed and used to 

estimate lipid peroxidation by measuring the concentration of conjugated dienes, while the red 

cell pellets were used to determine Hb. In another set of experiments, isolated rat red cell 

membranes were incubated with 25 mM AN at different temperatures. Total and Na+/K+-

ATPase activity were measured in control and AN-incubated red cell membranes. 

 Incubation of HbO-containing RBCs with AN resulted in the formation of MetHb, loss of 

intact Hb, and membrane lipid peroxidation. The availability of glucose to HbO-RBC incubation 

reduced the formation of MetHb by 33% and the loss of intact HbO by 33% but increased lipid 

peroxidation by 35%. As a positive control, HbO-containing RBCs were incubated with 0.1 mM 

t-butyl hydroperoxide, a strong GSH depleter. The formation of MetHb and non-intact Hb in the 

positive control was 3 and 5 times higher than that in AN-incubated RBCs. Incubation of 

MetHb-containing RBCs with AN also resulted in the loss of intact Hb and membrane lipid 

peroxidation. However, availability of glucose resulted in only 13% increase in peroxidation of 

membrane lipids. Lipid peroxidation was about 3 times higher in incubations of HbCOcontaining RBCs with AN, with or without glucose, than the other two RBC preparations. The 

extent of lipid peroxidation in RBCs and isolated RBC membranes was dependent on the 

concentrations of AN. 

 Farooqui et al. (1990) also demonstrated an inverse relationship between GSH 

concentrations and lipid peroxidation in RBCs incubated with AN. A 75% reduction in GSH 

levels in RBCs was observed as a result of AN incubation for 2 hours, with the half-life of GSH 

depletion being less than 22 minutes. The concentration of lipid peroxides increased by 274% 

over control levels during the same period. 

In addition, Farooqui et al. (1990) showed that Na+/K+-ATPase activity was reduced in 

the isolated RBC membranes incubated with AN (release of inorganic phosphate: 87.9 ± 9.1 vs. 

145.6 ± 13.1 nmol/mg protein per hour at 37°C; and 4.3 ± 0.7 vs. 87.9 ± 9.1 nmol/mg protein per 

hour at 15°C). The degree of AN-induced inhibition of ATPase was temperature dependent. 

The Km of Na+/K+-ATPase (3.5 mM at 37°C) was barely affected by the AN treatment, while the 

Vmax was significantly lower (–36%) than that of controls. This noncompetitive inhibition of 

Na+/K+-ATPase by AN was proposed to be the result of changes in the physicochemical 

properties of RBC membrane macromolecules subsequent to irreversible binding of AN to 

membrane proteins. 

 In summary, Farooqui et al. (1990) demonstrated that AN induced GSH depletion, 

elevated lipid peroxidation, and enhanced concentration of MetHb in RBC, as well as inhibited 

Na+

/K+-ATPase activity in RBC membrane. 
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4.5.1.1.3. Neurotoxicity. Campian et al. (2002) evaluated the capacity of AN to inactivate the 

important glycolytic enzyme, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in vitro in 

order to elucidate the mechanism for the acute toxicity of AN. GAPDH was incubated with AN 

(final concentrations ranged from 50 to 400 μM), and the activity of GAPDH was assayed at 

different time points. An irreversible inhibition of GAPDH activity was obtained. Incubation of 

GAPDH with 200 μM AN resulted in 90% loss of activity in about 60 minutes. The secondorder rate constant for inhibition of GAPDH activity was measured as 0.2 M-1

 s

-1 at pH 7.4 and 

37°C. 

The site of AN incorporation was identified by using matrix-assisted laser desorption 

ionization time-of-flight mass spectrometry to analyze tryptic digests of control and AN-labeled 

GAPDH (Campian et al., 2002). Inactivation of GAPDH was due to covalent binding of AN to 

cysteine 149 at the active site of the enzyme. This finding demonstrated the specificity of AN 

binding to cysteine residues and, more widely, implied the ability of AN to impair glycolytic 

ATP production in vivo. Campian et al. (2002) speculated that the combination of glycolytic 

ATP production impairment with inhibition of mitochondrial ATP synthesis by the AN 

metabolite cyanide could result in metabolic arrest. This might have profound consequences for 

the toxicity of AN in sensitive tissues such as the brain. 

In a followup study (Campian et al., 2008), male Sprague-Dawley rats (3-5/group) were 

injected subcutaneously with LD90 (115 mg/kg) AN and the brains of treated rats were frozen 

when respiration ceased via head immersion (HI) in liquid nitrogen or funnel freezing (FF) 

technique. Only minor decreases in ATP of 5% (FF) and 21% (HI) were found when respiration 

ceased, although phosphocreatine was decreased by 74% (FF) and 80% (HI), possibly due to 

inhibition of creatine kinase by AN. Campian et al. (2008) concluded that no toxicological 

relevant depletion of ATP occurred when respiration ceased in AN treated rats. Hence, the acute 

lethality of AN was not due to brain metabolic arrest. 

 Dorman et al. (1996) investigated the mechanisms by which AN and CEO exert 

neurotoxic effects in primary dissociated cerebrocortical cell cultures prepared from GD16-18 

CD rats. Mature 7-day old cultures were exposed to 0-10 mM AN or 1-2 mM CEO for 8 h at 

37◦C. Cytotoxicity was evaluated by measuring leakage of LDH, GSH depletion, inhibition of 

acetylcholinesterase (AChE) and histopathology. 

 Both AN and CEO induced dose-dependent increased in cytoxicity. Significant increase 

in LDH-leakage was observed in neural cultures following 8 h exposure to 2.5-10 mM AN or 

0.125 – 1 mM CEO. Significant reduction in GSH only occurred following exposure to 5 mM 

AN. Thus, Dorman et al. (1996) concluded that GSH depletion probably played a limited role in 

the development of AN toxicity. No change in AN-induced cytotoxicity was observed following 

cotreatment with the cytochrome P-450 inhibitor 1-phenylimidazole, indicating minimal 

metabolism of AN to CEO in the neural cells. AChE inhibition was not observed following 8 h 

exposure up to 2.5 mM AN. Widespread necrosis of the small, round cholinergic neurons was 
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present in the cultures treated with 2.5 mM AN or 0.125 mM CEO for 8 h. Astrocytes, 

pyramidal neurons, and bipolar neurons were mostly unaffected. On the other hand, treatment 

of cell cultures with ≥0.6 mM cyanide resulted in extensive loss of cytochrome oxidase activity 

in the large pyramidal neurons without a concomitant increase in LDH leakage. Dorman et al. 

(1996) concluded that AN may selectively destroy cholinergic neurons and induce neurotoxicity 

in rats, and that AN metabolism to cyanide was not a prerequisite for the development of ANinduced neurotoxicity. 

 Satayavivad et al. (1998) provided some evidence for the alterations of central 

muscarinic functions from subchronic exposure to AN. Either 0, 1, or 25 mg/kg AN was 

injected subcutaneously to male Wistar rats (10/group) 5 days/week for 8 weeks. The authors 

studied the impact of AN on motor behavioral activities by using a computerized system to chart 

the movements of rats within the cage. The system provided information on a total of 11 motor 

behavioral parameters, such as distance traveled/time interval, resting time, time spent moving, 

and number of clockwise and counterclockwise rotations. This test model can be used to detect 

subtle changes of central muscarinic receptors during exposure to cholinomimetic agents. 

Evaluations were carried out on each animal on day 5 of weeks 1, 2, 4, 6, and 8, 1 hour after 

treatment with AN. 

Both doses of AN were associated with marked decreases in all motor activities and a 

concomitant increase in the resting time of treated rats compared with controls (Satayavivad et 

al., 1998). There was a decrease in all motor parameter values at weeks 1 and 2, but most of 

these effects were diminished by weeks 4 and 6. However, the effects of the high dose of AN 

were more pronounced and longer lasting. Thus, the incidence of clockwise and 

counterclockwise rotations in high-dose rats was reduced compared with controls throughout the 

study (for example, 0.7 ± 0.3 [high dose], 2.6 ± 0.8 [low dose], and 2.8 ± 0.4 [controls] 

counterclockwise rotations/10-minute study period after 8 weeks). The effects of intramuscular 

injection of the muscarinic receptor antagonist, atropine, and the reversible acetylcholinesterase 

inhibitor, physostigmine, with and without concurrent AN administration, also were evaluated in 

this system. Atropine administration (10 mg/kg) was associated with increases in motor activity 

that were enhanced by AN treatment at 25 mg/kg. Physostigmine (0.5 mg/kg) caused reductions 

in motor activity irrespective of AN administration. Satayavivad et al. (1998) concluded that AN 

possesses cholinomimetic effects, one of which might include the down-regulation of muscarinic 

receptors. This would explain the marked increase in the response to atropine. Since AN did not 

inhibit the activity of acetylcholinesterase, the cholinomimetic effect of AN might be mediated 

by the release of acetylcholine from nerve endings. 

 Jacob and Ahmed (2003b) studied AN-induced neurotoxicity by exposing proliferating 

normal human astrocytes (NHAs) in culture to 25–400 μM AN for 12 hours. Assessment was 

then made on cell viability, levels of endogenous antioxidants, GSH, catalase, levels of ROS, and 

secretion of tumor necrosis factor (TNF-α), a cellular marker for oxidative stress and oxidative 
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damage to nuclear DNA. Treatment with 25–50 μM AN had no significant effect on viability of 

the astrocytes. At 100–400 μM AN, 15–42% reduction in cell viability was observed (as 

indicated by trypan blue exclusion). Reduced viability was further substantiated by 8–40% 

increased cytotoxicity (as indicated by leakage of LDH). The morphology of astrocytes was 

normal at concentrations up to 200 μM, but cells exposed to 400 μM AN showed a larger 

number of swollen nuclei and enlarged membrane structures. 

 Intracellular levels of GSH were not affected at 25 and 50 μM AN. However, a 

significant dose-dependent decrease in GSH was observed at 100, 200, and 400 μM AN (18, 28, 

and 35% lower than controls, respectively). A concomitant increase in levels of oxidized GSH 

(glutathione disulfide [GSSG]) was observed (Jacob and Ahmed, 2003b). The ratio of GSH to 

GSSG was reduced from the control value of 37–18, 7, 3, and 2 at 50, 100, 200, and 400 μM 

AN, respectively. Compared to control level, catalase activity increased 21% at 100 μM AN, but 

declined to 37% below control levels at 400 μM. 

 Significant increases in measures of oxidative stress (four- to sevenfold increase in the 

generation of ROS) and oxidative DNA damage (greater than twofold increase in 

8-oxodeoxyguanosine [8-oxodG]), were observed at 200–400 μM AN. Treatment at 400 μM 

significantly increased the release of the inflammatory cytokine, TNF-α, by 30% compared with 

controls. The observation that compromised antioxidant defense mechanisms (depletion of 

glutathione, increase in GSSG, inhibition of catalase) occurred at the same exposure 

concentration as reduced cell viability supported the hypothesis that oxidative stress in astrocytes 

was a possible mechanism for neurotoxic effects of AN exposure. 

 In a translated Chinese study (Lu et al., 2005b), levels of monoamine neurotransmitters 

and their metabolites were measured in the striatum and cerebellum of the brains of male 

Sprague-Dawley rats (n = 10 per group, 7 selected randomly for measurement) exposed to 0, 50, 

or 200 ppm AN in drinking water for 12 weeks. The study authors estimated the administered 

doses to be 4.0 and 13.5 mg/kg-day for the 50 and 200 ppm groups, respectively. Monoamine 

oxidase activity in the cerebral cortex was also measured. 

Compared with control values, average dopamine levels in the striatum were decreased 

by 76 and 64% in the 50 and 200 ppm groups, respectively, and by 46 and 18% in the 

cerebellum. The decreases in dopamine levels were statistically significant only in the striatum. 

No statistically significant exposure-related changes were observed in average levels of the 

dopamine metabolite, 3,4-dihydroxyphenylacetic acid, in the striatum or the cerebellum except 

for increased levels (by about 32%) for the 50 ppm group in the cerebellum compared with 

controls. Average concentrations of serotonin were decreased by about 38 and 49% in the 

striatum in the 50 and 200 ppm groups, respectively, and by about 41 and 68% in the cerebellum. 

These changes were statistically significant only in the striatum. No statistically significant 

exposure-related changes were observed in average levels of the serotonin metabolite, 

5-hydroxyindoleacetic acid, in the striatum or the cerebellum, in average levels of 
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norepinephrine in the two brain regions, or in average activities of monoamine oxidase. The 

observed changes in the endpoints examined in this study are of uncertain biological relevance; 

as such, the study does not identify NOAELs or LOAELs suitable for health hazard 

identification or dose-response assessment. However, the striatum and cerebellum are major 

centers for movement control, balance, and coordination. Thus, an abnormality in the 

neurotransmitters will cause malfunction in the movement coordination of an organism. The 

study authors suggested that a decrease in dopamine will reduce the environmental adaptability 

of rats and provide neurotransmitter evidence for the effect of AN exposure on neurobehavior. 

Serotonin plays a role in the maintenance of sleep and the emotional and psychological states of 

the body. Thus, reduced serotonin level in the exposed groups may also have neurobehavioral 

effect. 

4.5.1.1.4. Oxidative stress. Farooqui and Ahmed (1983b) demonstrated that exposure of rats to 

AN resulted in depletion of GSH and induction of oxidative stress in RBCs (see Section 

4.5.1.1.2). Farooqui et al. (1990) provided in vitro data that AN induced GSH depletion, lipid 

peroxidation, and enhanced concentration of MetHb in rat RBCs. 

 In another study, the cytotoxic effect of AN-potentiated oxidative stress in rat alveolar 

macrophages was investigated (Bhooma and Venkataprasad, 1997). When alveolar macrophages 

isolated from male Wistar rats were incubated with 200 nM to 20 μM AN at 37°C for up to 

4 hours, a dose-dependent loss of viability was observed. Incubation of alveolar macrophages 

with 10 μM AN increased the release of H2O2 by 44% when compared with controls. This effect 

was abolished by the addition of antioxidant enzymes superoxide dismutase (SOD) or catalase to 

the incubation medium. In addition, while exposure of alveolar macrophages to 10 μM AN 

resulted in 42% viability, addition of SOD exerted a marked protective effect with a resultant 

viability of 79%. Thus, cell injury induced by AN is mediated by the production of highly toxic 

OH radicals. 

 The role of oxidative stress and lipid peroxidation in the induction of the toxic effects of 

AN was studied by a number of other research groups. In a study designed to evaluate the 

possible role of free-radical-mediated lipid peroxidation in the etiology of AN-induced acute 

adrenal necrosis, Silver and Szabo (1982) monitored the formation of MDA and conjugated 

diene concentrations in the adrenal glands and other tissues (brain, liver, stomach, duodenum) of 

female Sprague-Dawley rats treated with an i.v. dose of 150 mg/kg AN. Controls received i.v. 

injections of aqueous 0.1% Tween 80. Rats were killed at 15, 30, 60, or 90 minutes after 

injection of AN, and the liver, adrenal glands, brain, stomach, and duodenum were removed. 

While no effects on the monitored parameters were observed in the mitochondria or microsomes 

from adrenal gland, brain, duodenal mucosa, or glandular stomach mucosa of rats 30 minutes 

after injection of AN, conjugated diene concentrations were elevated by 60% in hepatic 

microsomes and 30 and 40% in gastric mitochondria and microsomes. Therefore, although lipid 
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peroxidation is unlikely to be involved in the pathogenesis of AN-induced adrenal necrosis, AN 

can cause lipid peroxidation in other target organs. 

 The cytotoxicity and oxidative stress induced by AN were examined in cultured 

colonocytes from male and female Sprague-Dawley rats (Mohamadin et al., 2005). These cells 

were exposed to AN in the concentration range of 0.1–2.0 mM for 60 minutes or incubated with 

1.0 mM (the concentration that reduced viability by 50%) for different time intervals up to 

180 minutes and then assayed for LDH leakage, cellular GSH levels, and lipid peroxidation. 

Cell viability was reduced (assessed by trypan blue exclusion method) after 60-minute exposure 

to 0.5 mM AN and higher; incubation with 1.0 mM reduced viability as early as 60 minutes and 

by 72% at 180 minutes. Concentration-dependent increases in plasma membrane damage, as 

assessed by leakage of LDH, and enhanced lipid peroxidation (production of thiobarbituric acidreactive substances [TBARS]) were observed following 60-minute exposures at all levels (0.1–2 

mM); exposure to 1.0 mM AN produced a 2.5-fold increase in leakage after 60 minutes. 

 Significant reductions in glutathione levels resulted from 60-minute exposure to ≥1.0 mM 

AN. The time course study revealed that, by 30 minutes, exposure to 1.0 mM AN caused a 

significant decrease in GSH concentration that kept decreasing until 180 minutes, when the 

experiment was terminated. In additional experiments, AN-induced membrane damage and lipid 

peroxidation were reduced, but not totally abolished, by cotreatment with thiol-containing 

compounds (GSH, N-acetyl-L-cysteine (NAC), and dithiothreitol (DTT)), antioxidant enzymes 

(SOD and catalase), as well as the iron chelator desferrioxamine (DFO) and the hydroxyl radical 

scavenger DMSO. Mohamadin et al. (2005) suggested that the observed protective effects of 

GSH, NAC, and DTT could be attributed to direct interaction with ROS, direct binding to toxic 

metabolites, and/or enhancement of cellular GSH synthesis, while depletion of iron by DFO 

could indirectly prevent cell damage by inhibiting the generation of hydroxyl radical. 

Pretreatment of colonocytes with either SOD or catalase inhibited LDH leakage by about 23 and 

54%, respectively, when compared with colonocytes treated with AN alone. These antioxidant 

enzymes reduced TBARS production that was induced by AN by 17 and 45%, respectively. 

Since these antioxidants could not restore the normal level of LDH leakage or TBARS 

production, Mohamadin et al. (2005) concluded that in addition to lipid peroxidation, other 

factors contributed to AN-induced cytotoxicity. 

 Mahalakshmi et al. (2003) evaluated the potential protective effect of taurine (TAU) 

against AN-induced oxidative stress in rat brain. Male Wistar rats (six/group) were exposed to 

0 or 100 ppm AN (average intake 8–10 mg/kg-day) in drinking water for 14 or 28 days. 

Additional groups of rats received TAU (10 g/kg in diet) alone or along with AN treatment for 

14 or 28 days. AN had no effect on BW gain or weights of liver or brain. AN treatment for 

14 days increased levels of TBARS by about 13% in plasma and 30% in brain and increased 

levels of lipid hydroperoxides by 38% in plasma and 31% in brain; values after 28 days were 

similar, except for a 45% increase in lipid hydroperoxides in plasma. AN exposure also 
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increased the percentage of DNA fragmentation detectable in brain by 60 and 81% after 14 and 

28 days, respectively. TAU completely prevented the AN-induced increases in levels of TBARS 

and lipid hydroperoxides in plasma and brain, but afforded only partial protection from 

AN-induced increases in DNA fragmentation, which was significantly increased to 30 and 19% 

after 14 and 28 days, respectively. These results demonstrated that, even as TAU completely 

prevented the formation of ROS and oxidative stress, DNA fragmentation still occurred. Thus, 

other factors in addition to oxidative stress caused DNA fragmentation as a result of AN 

exposure. 

 AN significantly reduced activity levels of enzymatic antioxidants after 14 days (28-day 

values were similar to 14-day values but slightly lower): SOD (50% lower in hemolysate, 30% 

lower in brain), catalase (50% in hemolysate, 62% in brain), glutathione peroxidase (39% in 

hemolysate, 60% in brain), and GST (20% in hemolysate and brain). TAU also partially 

protected against these AN-induced reductions of enzymatic antioxidant activities, resulting in 

reductions of less than 11% in rats treated with AN and TAU for 14 days when compared with 

controls. For rats treated with AN and TAU for 28 days, there was insignificant reduction of 

<5%. AN exposure for 14 days also lowered levels of nonenzymatic antioxidants, such as 

ascorbic acid (by 30% in plasma and brain), α-tocopherol (by 40% in plasma and brain), and 

GSH (by 45% in plasma and 28% in brain); reductions were slightly greater for the 28-day 

exposure. In animals treated with TAU and AN for 14 days, the AN-related reductions in 

nonenzymatic antioxidants were less than 10% compared with controls. These experiments 

demonstrated that oral exposure to AN in drinking water increased oxidative stress in the brain 

and that TAU partly protected against AN-induced oxidative stress by increasing the activities of 

enzymatic antioxidants and replenishing nonenzymatic antioxidants. 

 However, Carrera et al. (2007) were not able to reproduce the results obtained by 

Mahalakshimi et al. (2003) when oxidative stress parameters were measured in Wistar rats 

treated with AN in vivo. Male Wistar rats (12/group) were treated with 0 or 200 ppm AN in 

drinking water for 14 days. The estimated daily dose was 30 mg/kg-day, using water factor of 

0.15 L/kg-day (USEPA, 1988). Brains were excised and homogenized, and lipid peroxidation 

(as measured by nmol MDA/mg protein), catalase activity, GSH levels, and proteins in brain 

tissue were measured. No differences were found in lipid peroxidation products, catalase 

activity, and reduced and oxidized GSH levels in the control and treated rats. Carrera et al. 

(2007) concluded that there was no evidence of oxidative damage in the brain of AN-treated rats 

at the studied dose of AN. 

 In another study (El-Sayed et al., 2008), the effect of hesperidin (HES), an antioxidant 

flavonoid, on AN-induced oxidative stress in rat brain was investigated. Male Swiss rats 

(8/group) were treated with 50 mg/kg-day AN via oral gavage for 28 days (Group II). Control 

rats received distilled water (Group I). Group III rats received 200 mg/kg-day HES i.p. for 28 

days. Group IV rats received 200 mg/Kg-day HES i.p. 24 h before starting AN treatment and 
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concomitantly with AN treatment. At study termination, brain GSH content, MDA content, and 

enzymatic antioxidant parameters: SOD, CAT, glutathione peroxidase (GSH-Px), and GST were 

measured. Histopathological examination was conducted on brain samples from two rats in each 

group. 

 Brain lipid peroxides levels measured as MDA was increased by 107% in the AN-treated 

rats, accompanied by a 63% decrease in brain GSH content as compared with controls (El-Sayed 

et al., 2008). On the other hand, pretreatment of rats with HES prior to AN administration 

resulted in 55% reduction in brain MDA content and 183% increase in brain GSH content when 

compared with the AN-treated group. In addition, significant decreases in enzymatic antioxidant 

parameters were found in the brain of AN-treated rats, with SOD, CAT, GSH-Px, and GST 

decreased by 43%, 64%, 52%, & 43%, respectively, when compared with controls. Pretreatment 

with HES and coadministration with AN attenuated the reduction of enzymatic antioxidants 

levels, resulting in elevations of SOD, CAT, GSH-Px, and GST by 73%, 169%, 197%, and 71%, 

respectively, when compared with the AN-treated group. 

 Histopathological examination of brain sections indicated damage to neuronal cells of the 

brain in AN-treated rats, as manifested by edema and interstitial neuronal atrophy with 

perineuronal vacuolation. Pretreatment of the rats with HES nearly normalized the 

histopathological changes induced by AN. This study indicated that treatment of rats with 50 

mg/Kg-day AN via oral gavage induced oxidative stress in the brain, and that pretreatment with 

the antioxidant HES might have protective role against AN-induced oxidative stress in the brain. 

 Zhang et al. (2002) studied the mechanisms by which AN induced oxidative stress and 

found evidence that CYP450 metabolism is required for AN to affect the activities of antioxidant 

enzymes, such as catalase, xanthine oxidase, or SOD. Syrian hamster embryo (SHE) cells were 

incubated for 4, 24, and 48 hours with subcytolethal doses of AN (0, 25, 50, or 75 μg/mL), and 

the effects of AN on enzymatic and nonenzymatic antioxidants were monitored. All three 

concentrations of AN increased ROS (hydroxyl radicals, measured as 2,3-dihydroxybenzoic acid 

formation from salicylic acid) levels in SHE cells at all time points, with concurrent depletion of 

GSH after 4 hours of treatment, ranging from 80 to 66% reduction. GSH levels in all ANtreatment groups returned to control values after 24 hours of treatment and increased only in the 

SHE cells treated with 75 μg/mL AN after 48 hours of treatment. 

Inhibition of the antioxidant enzymes was temporal. Decreased catalase activity was 

observed following treatment with 50 and 75 μg/mL AN for 4 hours at 72 and 52%, respectively. 

However, catalase activity was increased with 25, 50, and 75 μg/mL AN treatment for 24 hours 

by 82, 138, and 182%, respectively. Similar increases were observed with 48 hours of treatment. 

SOD activity was decreased only in SHE cells treated with 75 μg/mL AN for 4 hours. 

The activity of xanthine oxidase, the enzyme that generates the superoxide radical and 

hydrogen peroxide via the oxidation of hypoxanthine or xanthine by oxygen, was also 

monitored. Xanthine oxidase activity was increased by 47% in SHE cells treated with 75 μg/mL 
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AN for 24 hours. After 48 hours of treatment, both 50 and 75 μg/mL AN significantly increased 

xanthine oxidase activity. The addition of 0.5 mM of ABT (a suicide inhibitor of CYP450) to 

the system prevented the AN-induced decrease in catalase activity after 4 and 24 hours. 

Cotreatment of AN with ABT also blocked the increase in xanthine oxidase in SHE cells after 

48 hours of treatment. ABT alone had no effect on catalase or xanthine oxidase activity. In 

addition, AN had no effect on catalase or SOD activities in the absence of metabolic source 

(SHE cell homogenate). Thus, AN-induced oxidative stress in SHE cells involved decrease of 

antioxidants and activation of the oxidant enzyme xanthine oxidase. Taken together, these data 

suggest that AN induced oxidative stress via its oxidative metabolism. 

Nerland et al. (2003) proposed another mechanism by which AN might induce oxidative 

stress in their study on the covalent binding site of AN to rat liver CAIII. Two-dimensional 

polyacrylamide gel electrophoresis and autoradiography were used to locate proteins in male rat 

liver cytosol that were radiolabeled after s.c. administration of 115 mg/kg of [2,3-14C]-AN to 

male Sprague-Dawley rats. The intensely labeled spots in the autoradiogram were identified as 

CAIII. Analysis of the trypic fragment established that only cysteine 186 in the CAIII was 

labeled. Thus, AN selectively bound to the cysteine 186 residue of CAIII in rat liver. Nerland et 

al. (2003) also showed that over 50% of rat CAIII had participated in scavenging the toxicant 

AN. CAIII has been proposed to protect cells against oxidative stress by scavenging reactive 

xenobiotics, thereby reducing covalent binding to more critical macromolecules. Thus, AN 

exposure would impair this protective function by covalently binding to cysteine 186 of CAIII. 

 In another study, the cytotoxicity of AN was related to disturbances in intracellular ionic 

homeostasis and induction of oxidative stress. Mikhutkina et al. (2004) investigated the role of 

disturbance in cell Ca2+ homeostasis in AN-induced blebbing of thymocyte plasma membrane 

and apotosis. Blebbing of cell membrane develops in the initial stage of cell damage and is a 

sign of apoptosis and necrosis. A component of apoptogenic and necrogenic factors on the cell 

is Ca2+ imbalance, a result of disturbed activity of ion channels and intracellular Ca2+ stores. 

Exhaustion of intracellular Ca2+ stores increases the activity of store-activated (capacitance) Ca2+

channels that allow influx of Ca2+ into cells. Exhaustion of Ca2+ stores is a stimulus for 

apoptosis. 

 When exposed to 5 mM AN in vitro for 1 hour, thymocytes isolated from male albino 

mice exhibited twofold increases in the incidence of blebbing of the plasma membrane, followed 

by apoptosis (as detected by the expression of phosphatidylserine on the outer membrane) and 

necrosis (as indicated by membrane permeability to propidium iodide) (Mikhutkina et al., 2004). 

The initial and terminal blebbing of the plasma membrane peaked by the 15th and 45th minutes of 

incubation. The dynamics of terminal blebbing correlated with the accumulation of MDA in the 

incubation medium. Cotreatment with compounds (e.g., caffeine and procaine) that regulate 

activity of intracellular Ca2+ stores modulated the cytotoxic effect of AN, suggesting to 

Mikhutkina et al. (2004) that AN induced the release of Ca2+ from the endoplasmic reticulum. 
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 Preincubation of thymoctyes with 10 μM isoptin, a blocker of voltage-dependent ion 

channels, decreased AN-induced apoptosis and necrosis but increased the number of cells in 

AN-induced secondary necrosis and decreased the intensity of oxidative stress (as indicated by 

the levels of MDA). This effect was related to the ability of isoptin (an antioxidant) to suppress 

AN-induced generation of free radicals. Cotreatment of AN with 10 μM SKF 96365, a blocker 

of calcium release-activated channels that were dependent on the activity of voltage-dependent 

ion channels, increased the apoptogenic, but not the necrogenic, activity of AN. (SKF96365 had 

low prooxidant activity.) The cells treated with SKF 96365 and AN developed intensive 

blebbing at various periods of incubation. Mikhutkina et al. (2004) interpreted the results to be 

that isoptin, via K+

 channels, only partially inhibited store-activated Ca2+ entry into cells through 

calcium release-activated channels and in turn, protected cells from apoptosis. However, 

secondary necrosis (the process associated with cells unable to form apoptotic bodies) developed 

in thymocytes with suppressed blebbing. On the other hand, direct inhibition of these channels 

with SKF 96365 completely blocked Ca2+ entry and promoted progression of apoptosis. The 

results of these experiments suggested that AN caused disturbances in intracellular calcium 

balance that led to plasma membrane blebbing, apoptosis, and necrosis of thymocytes. 

 A recent study on the effects of AN on primary-cultured astrocytes from Wistar male rats 

(Carrera et al., 2007) indicated that AN-induced cellular damage was not due to oxidative stress, 

since antioxidants did not prevent AN-induced toxicity. In this study, primary cultured rat 

astrocytes were treated for 1 hour with or without trolox (TRX) (100 μM), TAU (5 mM), NAC 

(20 mM), estradiol (10 μM), or melatonin (MEL) (10–3 M, 10–5 M, or 10–7 M). They were then 

exposed to 2.5 mM AN (which induced about 40% cell death) for 24 hours. Cell viability was 

determined by measuring the activity of LDH released by damaged cells into the medium. GSH 

levels were also measured. 

 Among the antioxidants included in this study, only NAC, a sulfhydryl donor, prevented 

the decrease of the number of viable cells in the culture. None of the other antioxidants 

prevented cell death induced by AN treatment. Moreover, 10–5 M MEL and TAU increased the 

toxicity of AN in astrocytes. Treatment of astrocytes for 4 hours with AN partially depleted 

intracellular GSH, whereas pretreatment with 20 mM NAC recovered GSH content to the control 

levels. Carrera et al. (2007) concluded that protective effect of NAC was due to increase in the 

intracellular pool of GSH, GSH conjugation with AN, decreasing the availability of AN for 

being metabolized to CEO and cyanide, halting the toxicity of AN. Carrera et al. (2007) also 

concluded cellular toxicity induced by AN could not be prevented only by antioxidants. 

Oxidative stress summary 

 The role of oxidative stress in AN-induced cytotoxicity was evaluated in both in vitro and

in vivo studies (Mohamadin et al., 2005). AN was reported to induce oxidative stress and 

decreased the viability of NHAs in cell cultures (Jacob and Ahmed, 2003b) and cultured rat 
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colonocytes (Mohamadin et al., 2005). However, other causes contributed to AN-induced 

cytotoxicity as antioxidants could not restore the normal level of LDH leakage or TBARS 

production. 

 Zhang et al. (2002) studied the mechanisms by which AN induced oxidative stress in 

SHE cells and suggested that AN induced oxidative stress via its oxidative metabolism. Other 

proposed mechanisms by which AN might induce oxidative stress included covalent binding of 

AN to cysteine 186 of rat liver CAIII (Nerland et al., 2003), and disturbances in intracellular 

ionic homeostasis (Mikhutkina et al., 2004). 

 Drinking water studies in Wistar rats yielded contradictory results. Mahalakshmi et al. 

(2003) reported exposure to 8–10 mg/kg-day AN significantly reduced enzymatic antioxidant 

(SOD, glutathione peroxidase, catalase) levels in rat brain after 14 or 28 days, and that TAU 

prevented the AN-induced increases in levels of TBARS and lipid hydroperoxides in plasma and 

brain. However, Carrera et al. (2007) were unable to reproduce the results obtained by 

Mahalakshimi et al. (2003) in another 14-day drinking water study in Wistar rats. No differences 

were found in lipid peroxidation products, catalase activity, and reduced and oxidized GSH 

levels in the control and treated rats. Carrera et al. (2007) concluded that there was no evidence 

of oxidative damage in the brain of rats treated with 30 mg/kg-day AN for 14 days. 

 In an oral gavage study of male Swiss albino rats, treatment of rats with 50 mg/Kg-day 

for 28 days induced increased levels of MDA in the brain, and decreased brain GSH content and 

enzymatic antioxidant levels (El-Sayed et al., 2008). Pretreatment with HES (200 mg/Kg, i.p.) 

attenuated the effects of AN treatment. 

4.5.1.1.5. Immunotoxicity. Zabrodskii et al. (2000) studied the mechanisms for cell and 

humoral immunosuppressive effect of AN. CBA mice were treated by a single s.c. injection at 

one-half the LD50 (28 mg/kg) of AN. One day after treatment, mice were tested for delayed-type 

hypersensitivity (DTH) reactions: α-naphthylbutyrate esterase activity in splenocytes, number of 

antibody-producing cells in spleen, and the paw edema test. AN treatment suppressed primary 

cell immune response, as demonstrated by a 61% reduction of the DTH reaction (edematous paw 

weight). Secondary DTH response (the number of esterase-positive splenocytes) was reduced by 

28%. Humoral immune response was also decreased, as shown by a 56% reduction of the 

number of antibody-producing cells. The cholinesterase reactivator, bispyridinium dioxime 

(dipyroxime), rehabilitated paw swelling completely but only partially restored the numbers of 

antibody-producing cells and esterase-positive splenocytes. 

 The role of cytochrome c oxidase a3 in the mitochondrial respiration enzyme system of 

immunocompetent cells was evaluated using hydrogen cyanide, a metabolite of AN, and its 

antidote anticyan. Anticyan, an agent that converts Hb to MetHb, also improved the DTH effects 

of AN but less efficiently than dipyroxime. A combination of both agents reversed the 

immunotoxic effects of AN completely. Zabrodskii et al. (2000) suggested that AN-induced 
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immunotoxic effects were the result of its anticholinesterase activity targeted at T lymphocytes 

and general toxicity associated with inhibition of cytochrome c oxidase a3 of the immunocytes. 

4.5.1.2. Cancer Effects 

4.5.1.2.1. Formation of DNA adducts. There is evidence that AN and its epoxide metabolite, 

CEO, can form a number of different DNA adducts in vitro. For example, Solomon and Segal 

(1985) demonstrated the direct, nonenzymatic alkylation of calf thymus DNA by AN. Following 

a 40-day incubation of AN at 37°C and pH 7.4, the reaction products were identified as 

cyanoethyl adducts of guanine and thymine and carboxyethyl adducts of adenine and cytosine. 

The major adducts were 1-carboxyethyl adenosine (26%), 7-cyanoethyl-guanine (26%), 

imidazole ring-opened 7,9-bis cyanoethyl guanine (19%), 3-cyanoethyl thymine (16%), and 

N

6

-cyanoethyl adenine (8%). 

 CEO formed a number of DNA adducts more quickly when incubated with DNA in vitro 

(Solomon et al., 1993; Yates et al., 1993; Hogy and Guengerich, 1986). When calf thymus DNA 

was incubated with CEO at pH 7.0–7.5 and 37°C for 3 hours (Solomon et al., 1993), 

N

7

-(oxoethyl)guanine (110 nmol/mg DNA), N3-(2-hydroxy-2-carboxyethyl)deoxyuridine (80 

nmol/mg DNA), and smaller amounts of adenine and thymine adducts were produced. 

Therefore, the adducts formed from CEO were different than those formed from AN. The order 

of reactivity with CEO was guanine > cytosine > adenine > thymine. In addition to reacting with 

N7 of guanine, forming N7

-(oxoethyl)guanine, CEO reacted to a great extent with the cytosine 

residue, resulting in the detection of a major adduct, N3-(2-hydroxy-2-

carboxyethyl)deoxyuridine. Solomon et al. (1993) proposed that the uracil adduct was formed 

from an initial cytosine adduct from hydrolytic deamination of cytosine to uracil. 

 Yates et al. (1993) also characterized an adduct formed when calf thymus DNA was 

incubated with 150 mM CEO at 37°C for 3 hours. The adduct was identified as N3

-(2-cyano2-hydroxyethyl)deoxythymidine. This adduct was also formed when 150 mM [2,3-14C]-CEO 

reacted with 10 mM deoxythymidine in vitro (Yates et al., 1993). Subsequent degradation of this 

adduct yielded N3

-(2,2-dihydroxyethyl)deoxythymidine. 

 Similarly, Guengerich et al. (1981) showed that when 1 mM [1-14C]-AN and 

[2,3-14C]-AN were incubated at 37°C with 1.5 mg/mL calf thymus DNA in the presence of rat 

liver microsomes or a reconstituted CYP450 system, DNA adducts were formed as measured by 

irreversible binding of radioactive label to DNA. Formation of DNA adducts was enhanced by 

the presence of NADPH. Only trace levels of DNA adducts were detected when incubated with 

rat brain microsomes, and the reaction was not NADPH dependent, probably due to insignificant 

metabolism of AN by brain microsomes. Guengerich et al. (1981) also showed nonenzymatic 

irreversible binding of labeled CEO to calf thymus DNA. The extent of binding for 

[2,3-14C]-labeled CEO was three- to fivefold greater than that for [1-14C]-labeled CEO. 

Moreover, when 100 mM CEO was incubated with 50 mM adenosine for 24 hours at 37°C, 
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1,N6-ethenoadenosine was formed. In another experiment, an unidentified product was formed 

when CEO was incubated with cytidine. 

 Data from Peter et al. (1983a) showed the extent of irreversible binding of AN or its 

metabolites to DNA to be lower after purification of isolated DNA and RNA by column 

chromatography on hydroxyapatite. In their in vitro incubation experiment, [2,3-14C]-AN was 

incubated with rat-liver microsomes, NADPH and DNA or RNA. Irreversible AN binding was 

found to be 3 nmol/hour per mg DNA, when ethanol precipitation or phenol extraction of DNA 

was used. When the isolated DNA was further purified by column chromatography on 

hydroxyapatite, irreversible binding was found to be 0.15 nmol/hour per mg DNA. Peter et al. 

(1983a) also administered [2,3-14C]-AN intraperitoneally to male Wistar rats and measured the 

incorporation of radioactivity into hepatic RNA bases. The amount of radiolabel from AN 

associated with hepatic DNA was lower than that from labeled vinyl chloride. 

 However, when hepatic DNA from these treated rats was isolated and hydrolyzed, 

chromatography on PEI-cellulose showed two 14C peaks that did not correspond to known 

standards. Thus, Peter et al. (1983a) concluded that AN or its metabolites could alkylate DNA, 

although these DNA adducts had not yet been identified. 

 Yates et al. (1994) also characterized the products formed when 150 mM CEO reacted 

with 50 mg/mL nucleotides for 3 hours at 37°C in vitro. The reaction of CEO with 

5′-monophosphates of deoxyguanosine, deoxyadenosine, deoxycytidine, or deoxythymidine 

resulted in the formation of at least one adduct for each nucleotide. These CEO-nucleotide 

adducts were characterized as 2-cyano-2-hydroxyethyl phosphodiesters. The reaction of 

deoxyguanosine-5′-monophosphate (dGMP) also produced a second adduct, N7

-(2-cyano2-hydroxyethyl)-dGMP. Yates et al. (1994) suggested that the cyano-hydroxyethylphosphodiester adduct could induce single and double DNA strand breaks (as observed when 

CEO was incubated with pBR322 plasmid DNA) via interaction of the adduct’s β-hydroxylgroup with the DNA phosphate backbone. 

 Irreversible binding of AN or its metabolites to DNA in vivo has also been studied. 

Farooqui and Ahmed (1983a) investigated the ability of [2,3-14C]-AN or its metabolites to bind 

to macromolecules in rats in vivo. [2,3-14C]-AN was administered in a single dose to male 

Sprague-Dawley rats (three to four per group) via gavage at a dose of 46.5 mg/kg in water. 

Animals were sacrificed at 1, 6, 24, and 48 hours after dosing. Organs, including liver, kidney, 

brain, spleen, and stomach, were dissected out and frozen rapidly. Nucleic acids extracted from 

the homogenates were applied to the hydroxyapatite column for separation of RNA and DNA 

fractions. Radioactivity was detected in the extracts of RNA and DNA from liver, stomach, and 

brain. Bound radioactivity (as pmol equivalent AN/mg DNA) to DNA in the brain was the 

highest at 24 hours (119 pmol/mg DNA), followed by stomach (81 pmol/mg DNA), and liver 

(25 pmol/mg DNA). Bound radioactivity in all three organs plateaued at 24 hours and remained 

unchanged thereafter. RNA from liver showed the highest amount of radioactivity, followed by 
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brain and stomach. Bound radioactivity in liver RNA peaked at 6 hours after dosing, whereas 

RNA from the brain and stomach showed maximal radioactivity at 24 hours. Binding to proteins 

was extensive and time dependent. In the first hour after oral dosing, the highest protein binding 

occurred in spleen and stomach, followed by liver, kidney, and brain. After 6 hours, protein 

binding plateaued until 48 hours. At 6 hours, the highest protein binding occurred in the spleen, 

followed by liver, stomach, and kidney, with brain having the lowest protein binding. The study 

authors developed numerical indices for the AN-derived DNA alkylation; covalent binding 

indices were 5.9, 51.9, and 65.3 for liver, stomach, and brain, respectively, after 24 hours. 

 Ahmed et al. (1992a) demonstrated the covalent binding of radiolabel from [2,3-14C]-AN 

to testicular DNA after a single oral dose of 46.5 mg/kg of [2,3-14C]-AN to male SpragueDawley rats. In a time course study, bound activity was shown to be greatest after 30 minutes 

(8.93 ± 0.80 μmol AN bound/mol nucleotide), with covalent binding index of 10.15. Using an 

identical experimental protocol, Ahmed et al. (1992b) demonstrated the capacity of AN to bind 

covalently to DNA in the lung. Covalent binding of radioactivity to DNA increased with time 

and was maximum at 12 hours after a single oral dose, with a covalent binding index of 3.48. 

Binding was associated with a 55–72% decrease in replicative DNA synthesis at time points up 

to 24 hours after dosing. 

 Hogy (1986) and Hogy and Guengerich (1986) studied the in vivo interaction of AN and 

CEO with DNA. Three male F344 rats were administered AN (50 mg/kg, i.p.); three more rats 

were administered CEO (6 mg/kg, i.p.). The rats were sacrificed after 2 hours, and the brain and 

livers were removed and frozen. DNA and RNA were isolated from these tissues. For detection 

of N7-(2-oxoethyl)guanine, DNA samples were reductively tritiated with NaB3H4; the adduct 

was released by neutral thermal hydrolysis and purified by thin-layer chromatography for 

subsequent quantitation by liquid scintillation counting. N7-(2-oxoethyl)guanine was detected in 

liver DNA at 3.1 × 107 nucleotides per alkylation in AN-treated rats and 6.9 × 107 nucleotides 

per alkylation in CEO-treated rats (Table 4-52). For brain DNA, N7-(2-oxoethyl)guanine was 

detected at 2.4 × 108 nucleotides per alkylation in AN-treated rats and at 1.1 × 109 nucleotides 

per alkylation for CEO-treated rats. The values obtained from the brain DNA samples were near 

the limit of detection. Thus, the presence of these adducts in the brain could not be 

unequivocally verified. 
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Table 4-52. Detection of N7-(2-oxoethyl)guanine after i.p. administration of 

50 mg/kg AN or CEO to male F344 rats 

Formation of N7

-(2-oxoethyl)guanine 

Liver Brain

Compound fmol/mg DNA Nucleotides/alkylation fmol/mg DNA Nucleotides/alkylation

AN 109 ± 71 3.1 × 107

 14 2.4 × 108

CEO 48 ± 15 6.9 × 107 3 1.1 × 109

Source: Hogy (1986). 

 In the same study (Hogy, 1986; Hogy and Guengerich, 1986), rat DNA samples were 

also analyzed by HPLC with a fluorescence detector for 1,N6

-ethenoadenosine and 

1,N6-ethenodeoxyadenosine. These adducts were not detected with limits of detection estimated 

to be 3 pmol/mg DNA and 1 pmol/mg RNA, respectively. 

 In another study, Prokopczyk et al. (1988) administered 50 or 100 mg/kg s.c. AN to male 

F344 rats (10/group). DNA was isolated from liver and brain after 2 hours (50 mg/kg group) or 

6 hours (100 mg/kg AN). An HPLC assay with fluorescence detector was used to detect 

7-(2-cyanoethyl)guanine (detection limit: 1 per 5 × 104

 guanine) and O6-cyanoethylguanine 

(detection limit: 1 per 7 × 104 guanine). Neither adduct was detected. These two adducts were 

not formed when CEO was incubated with calf thymus DNA in vitro (Solomon et al., 1993). 

4.5.1.2.2. Oxidative stress. Jiang et al. (1998) evaluated the ability of AN to induce oxidative 

stress in the brain cortex of rats. Male Sprague-Dawley rats (at least nine/group) were exposed 

to 0, 5, 50, 100, or 200 ppm AN in drinking water for either 14, 28, or 90 days. These 

concentrations were selected from those used in chronic bioassays (see Section 4.2.1.2). As 

calculated by the study authors, average daily doses of 0, 0.6, 5.1, 8.9, or 15.0 mg/kg-day were 

ingested over the 90-day treatment period by the control to high-dose groups, respectively. At 

study termination, brains and livers were weighed. The livers and brain cortexes from six 

rats/group were evaluated for the following oxidative endpoints: oxidative DNA damage 

(8-hydroxy-2′-deoxyguanosine levels), lipid peroxidation (MDA levels), levels of nonenzymatic 

antioxidants (glutathione and vitamin E), and the activities of enzymatic antioxidants (catalase, 

SOD, and glutathione peroxidases). 8-Hydroxy-2′-deoxyguanosine has also been referred to as 

8-oxo-7,8-dihyro-2′-guanosine (Murata et al., 2001) and 8-oxodeoxyguanosine (Whysner et al., 

1998a) and will be referred to as 8-oxodG in this document. ROS formation—as measured by 

the formation of 2,3-dihydrobenzoic acid from salicylic acid in brain cortex and liver—were 

evaluated in three rats/group injected with salicylic acid in saline 12 hours before termination. 

In rats exposed to AN at concentrations as high as 200 ppm for up to 90 days, no effects 

were noted on viability. A statistically significant reduction of 9% in BW was observed in the 

200 ppm group after 90 days. No differences were observed in brain or liver weights nor were 
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any of the measures of oxidative damage or antioxidant levels in the liver for all groups at any 

sampling times. AN exposure resulted in statistically significant increases in oxidative stress 

parameters and decreases in antioxidants levels in the brain cortex. Levels of hydroxy free 

radicals (ROS) were significantly elevated in a dose-related manner in the 50–200 ppm groups, 

beginning at 14 days and persisting until the 90-day time point; at 200 ppm, the increase was 

approximately fivefold over controls. Levels of 8-oxodG in the cellular DNA of brain cortex 

were significantly elevated (three- to fourfold compared with controls) in a dose-related manner 

in the 100 and 200 ppm groups, beginning at 14 days of exposure, and two- to threefold in the 

50 ppm group, beginning after 28 days of exposure. MDA levels were significantly increased 

(1.5-fold) in the 200 ppm group after 14 days but at no other time point. 

Slight but significant decreases in levels of vitamin E (about 20%) and glutathione (about 

20%) in the brain cortex were observed in the 50–200 ppm groups but were statistically 

significant only at the 14-day time point. Statistically significant, dose-dependent reductions (by 

up to 60%) in catalase activity were observed in brain cortex at all exposure levels after 14 days, 

at ≥100 ppm after 28 days, and at ≥50 ppm after 90 days; the transient effect at 5 ppm was not 

considered to be biologically significant. Reductions in SOD levels in the brain (by up to 30% at 

200 ppm) were dose related and statistically significant at ≥50 ppm after 14 days and at 200 ppm 

after 28 or 90 days. In this study, a NOAEL of 5 ppm (0.6 mg/kg-day) and a LOAEL of 50 ppm 

(5.1 mg/kg-day) were identified for increases in levels of oxidative damage (increased ROS and 

DNA damage) and reductions in the antioxidant enzymes catalase and SOD in the brain of rats 

exposed to AN in drinking water. Jiang et al. (1998) suggested that observed oxidative stress in 

rat brain cortex following AN treatment could be induced by: (1) direct generation of free 

radicals from AN or its metabolites, (2) binding of AN or its metabolites to free radical 

scavengers (e.g., GSH, vitamin E), (3) modulation of the activity and/or synthesis of antioxidant 

enzymes (e.g., SOD, catalase), and/or (4) interference with electron flow through the respiratory 

chain via inhibition of cytochrome C oxidase by the cyanide ion, a metabolite of AN. However, 

these potential mechanisms need to be further investigated. 

In a follow up study, Pu et al. (2009) examined the potential for AN to induce oxidative 

DNA damage in rats. These investigators also examined whether blood could serve as a 

surrogate for the biomonitoring of oxidative stress induced by AN in target tissues (in particular 

brain) of exposed populations. Male Sprague-Dawley rats (9/group) were treated with 0, 3, 30, 

100 or 200 ppm AN in drinking water for 28 days. N-acetyl cysteine (NAC), an acetylated 

precursor of glutathione, was coadministered at a dietary concentration of 0.3% to one group of 

rats receiving 200 ppm AN in drinking water to evaluate its protective effect against potential 

AN-induced oxidative stress. At the end of treatment, animals were sacrificed and blood 

samples were collected immediately. The alkaline comet assay was used as a measure of direct 

DNA damage in 3 rats/group, and the formamidopyrimidine DNA glycosylase (fpg)-modified 

comet assay was used as a measure oxidative DNA damage in brain cortex and white blood cells 
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(WBCs) of different treatment groups. 8-oxodG levels in brain tissues and WBCs were also 

measured by HPLC with electrochemical detection. 2,3-DHBA was measured in WBCs and 

brain tissues for the presence of ROS. 

Pu et al. (2009) observed no increase in DNA damage in rat WBC and brain tissue 

following exposure to AN with or without NAC coadministration using the alkaline comet assay. 

Dose-dependent increases in DNA damage were observed in rat WBC and brain following 

exposure to AN using the fpg-modified alkaline comet assay. These increases in DNA damage 

were not observed in WBC and brain of rats exposed to 200 ppm AN and NAC. Pu et al. (2009) 

interpreted the results as indicative of oxidative DNA damage in AN-exposed rats, and further 

that the absence of oxidative DNA damage in rats coadministered NAC reflected the antioxidant 

action of NAC. Significant increases in the level of 8-oxodG were found in WBC and brain of 

rats treated with 100 and 200 ppm AN; no increase was observed in rats treated with 200 ppm 

AN and NAC. 2,3-DHBA, a measure of ROS formation, was increased in the WBC of rats 

treated with AN in a dose-dependent manner, but was not detectable in the brain of treated rats. 

In addition, the ratios of reduced to oxidized glutathione (GSH/GSSG) were reported to be 

significantly lower in rats treated with 30, 100 and 200 ppm AN, but not in a dose dependent 

manner. Pu et al. (2009) concluded that AN induced oxidative stress and DNA damage in male 

Sprague-Dawley rats and that the fpg-modified comet assay in WBC correlated with target tissue 

oxidative DNA damage. 

EPA identified certain issues with study design and choice of analytical methods that 

raise questions about the interpretation of the findings by Pu et al. (2009). First, Pu et al. (2009)

stated that direct DNA damage was not detected in rat WBC and brain of AN-exposed rats based 

on results in the standard alkaline comet assay. The standard comet assay detects single and 

double strand breaks, cross link, oxidative DNA damage, apurinic/pyrimidinic sites and DNA 

repair (Smith et al., 2006; Collins, 2007). The induction of other types of DNA damage not 

detected by the comet assay cannot be precluded. 

Second, Pu et al. (2009) utilized the fpg-modified comet assay to detect oxidative DNA 

damage induced by AN; however, this assay is not specific for the detection of oxidative DNA 

damage, as this assay also detects alkylation DNA damage (Speit et al., 2004; Smith et al., 2006). 

The fpg-modified comet assay has been shown to be especially sensitive for the detection of 

DNA damage by N-7 guanine alkylation, which was responsible for the observed DNA damage 

by alkylating agents methylmethanesulfonate (MMS) and ethylmethanesulfonate (EMS) (Speit et 

al., 2004). N-7 guanine adduct was detected in liver and brain (at the limit of detection) of ANtreated rats (see Section 4.5.1.2.1). Thus, the observed DNA damage using the fpg-modified 

comet assay in Pu et al. (2009) cannot necessarily be attributed to oxidative DNA damage, but 

could also be due to N-7 guanine alkylation. 

Third, NAC was used by Pu et al. (2009) to demonstrate the effect of an antioxidant to 

protect against observed DNA damage. It should be noted that NAC is a precursor of 
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glutathione. Glutathione conjugates with AN to N-acetyl-S-(2-cyanoethyl)cysteine, which can 

then be excreted in the urine. Glutathione conjugation is therefore a detoxification pathway for 

AN. Thus, the reduction in DNA damage in AN-treated rats coadministered with NAC observed 

by Pu et al. (2009) may, in fact, reflect increased detoxification of AN and reduced availability 

of AN for oxidation to CEO. The protective effect of NAC on AN toxicity was demonstrated by 

Carrera et al. (2007) (see Section 4.5.1.1.4). Fourth, Pu et al. (2009) reported that the ratios of 

reduced to oxidized glutathione (GSH/GSSH) were decreased in the brain cortex of rats treated 

with AN in drinking water at concentrations of 30, 100, and 200 ppm for 28 days. This 

reduction was not dose related; the GSH/GSSG ratio was similar in all three exposure groups 

[Figure 8 in Pu et al. (2009)]. GSH/GSSG provided the redox status in the brain cortex. It 

should be noted that in the 2-year drinking water study in Sprague-Dawley rats involving AN 

drinking water concentrations of 30, 100, and 300 pmm (Quast, 2002), the incidence of tumors 

increased with increasing exposure. The absence of a dose-related decrease in GSH/GSSG ratio 

observed by Pu et al. (2009) does not parallel the dose-related increase in tumor incidence 

observed in AN-exposed rats by Quast (2002). Thus, the GSH/GSSG ratio is not concordant 

with an oxidative stress mode of action for the carcinogenicity of AN. Fifth, no ROS was 

detected in the brain of AN exposed rats in Pu et al. (2009), as no 2,3-DHBA was detected in the 

brain of AN-treated rats. 

 Whysner et al. (1998a) also evaluated oxidative DNA damage (increased levels of 

8-oxodG) in the brains of male Sprague-Dawley and F344 rats exposed to AN in drinking water 

for durations of either 21 or 94 days. In the first experiment, male Sprague-Dawley rats 

(20/group) were exposed to 0, 3, 30, or 300 ppm AN in drinking water for 21 days (Whysner et 

al.,1998a). Based on default values for the BW of male Sprague-Dawley rats in a subchronic 

study (0.267 kg) and an allometric equation linking water consumption to BW (U.S. EPA, 1988), 

the average intakes of AN were calculated as approximately 0, 0.43, 4.3, and 43 mg/kg-day for 

the control to high-dose groups, respectively. At termination, brains, livers, and forestomachs 

were excised from five rats/group each for DNA isolation. These tissues were analyzed for 

GSH, cyst(e)ine, and 8-oxodG levels in nuclear DNA. TBARS levels in brains were determined 

for another five rats/group. Brain homogenate from another five rats/group were analyzed for 

cytochrome oxidase activity (in the mitochondria fraction), catalase (in supernatant), and 

glutathione peroxidase (in homogenate). Tissues from another five rats/group were examined for 

histopathology, but results were to be published separately. 

In rats exposed to 30 or 300 ppm AN, statistically significant increases in 8-oxodG levels 

in nuclear DNA were measured in brains (approximately twofold increase compared with control 

values for both dose groups) and livers (approximately 1.4-fold increase for both dose groups 

when compared with controls). Also observed in the 300 ppm dose group were approximately 

twofold increases in the levels of glutathione and cyst(e)ine in the forestomach, and 

approximately 50% increase in cyst(e)ine level in the brain. There were no exposure-related 
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effects on levels of glutathione in the brain and liver or on levels of cytochrome oxidase, 

catalase, glutathione peroxidase, or TBARS in the brain. However, glutathione level in the 

forestomach was increased about 1.8-fold in the 300 ppm dose group compared with controls. In 

this study, a NOAEL of 3 ppm (0.43 mg/kg-day) and a LOAEL of 30 ppm (4.3 mg/kg-day) were 

identified for increased oxidative DNA damage in the brains and livers of Sprague-Dawley rats. 

Whysner et al. (1998a) concluded that the formation of 8-oxodG from AN exposure did not 

involve disruption of antioxidant defense or lipid peroxidation. In addition, the absence of effect 

on brain cytochrome oxidase activity in exposed rats indicated lack of inhibition by cyanide, a 

metabolite of AN. Thus, Whysner et al. (1998a) concluded that cyanide-induced metabolic 

hypoxia did not appear to be involved in the generation of ROS by AN administered in drinking 

water. 

Whysner et al. (1998a) conducted a parallel 21-day drinking water study in male F344 

rats (10/group). Concentrations of AN in drinking water were of 0, 1, 3, 10, 30, or 100 ppm. 

Based on default values for the BW of male F344 rats in a subchronic study (0.18 kg) and an 

allometric equation linking water consumption to BW (U.S. EPA, 1988), the average doses of 

AN were estimated at 0, 0.16, 0.47, 1.6, 4.7, and 15.6 mg/kg-day in the control to high-dose 

groups. An additional group of rats received 5 mg methylnitrosourea (MNU) per kg/week via 

i.v. injection. At termination, rat brains were evaluated for levels of 8-oxodG in nuclear DNA, 

cytochrome oxidase, glutathione, and cyst(e)ine. Levels of all these parameters in the brains of 

AN-exposed rats and MNU-exposed rats were not significantly different from controls. The 

levels of 8-oxodG in the brains of 3–100 ppm AN dose groups were the same, about 1.3-fold 

higher than control values. However, the increases were not statistically significant. The highest 

drinking water concentration of 100 ppm AN (15.6 mg/kg-day) was a NOAEL for oxidative 

effects in the brains of F344 rats (i.e., oxidative stress was not demonstrated in the brains of F344 

rats even at the highest dose of 15.6 mg/kg-day). 

In the subchronic experiment by Whysner et al. (1998a), male Sprague-Dawley rats 

(10 rats/group) were exposed to 0 or 100 ppm AN in drinking water for 3, 10, 31, or 94 days. 

Two additional groups of Sprague-Dawley rats (six/group) were exposed to 5 mg MNU/kg/week 

or 5 mg MNU/kg/week + 100 ppm AN. Brains were assayed for levels of 8-oxodG, cytochrome 

oxidase, and glutathione. Levels of 8-oxodG were also measured in the livers of rats exposed for 

3, 10, or 94 days. 

No effects on brain levels of cytochrome oxidase or glutathione were observed in any 

dose group up to 94 days. The 8-oxodG levels were significantly increased by 77% following 

exposure to 100 ppm AN for 3, 10, and 94 days. Administration of 5 mg/kg MNU (a DNAreactive carcinogen that produces glial cell tumors in rats) did not increase the level of 8-oxodG 

in the brain of treated rats but increased 8-oxodG in the liver after 10 days. However, 

coadministration of 100 ppm AN and MNU increased the 8-oxodG level in the brain after 31 and 

94 days when compared with controls. Whysner et al. (1998a) proposed that AN-induced 
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generation of ROS and resultant oxidative DNA damage represented one possible mode of action 

for the neoplastic process in the rat brain. However, as discussed in Section 4.7.3.3.1, results 

from this study did not support the proposed oxidative stress mode of action. 

 The ability of AN to induce oxidative stress and oxidative DNA damage was also studied 

in a rat glial cell line and cultured rat hepatocytes in vitro (Kamendulis et al., 1999a). In parallel 

experiments, DITNC1 rat astrocytes and rat hepatocytes were incubated with sublethal 

concentrations (up to 1 mM) AN in vitro for 4 or 24 hours. The 8-oxodG levels in total cellular 

(nuclear and mitochondrial) DNA, generation of ROS (measured as increase in generation of 

2,3-dihydroxybenzoic acid in salicylic acid), levels of the lipid peroxidation product MDA, GSH, 

and antioxidant enzymes activity were measured at the end of the incubation period. 

 In rat astrocytes, significant increases (up to 3.8-fold) in the production of 8-oxodG over 

control was observed after 4 hours and up to 3.9-fold after 24 hours. No increase in 8-oxodG 

formation was observed in rat hepatocytes at all AN concentrations and time examined. The 

induction of 8-oxodG by AN in rat astrocytes was reversible. Following removal of AN after 

24 hours of treatment, 8-oxodG levels returned to control values at all studied concentrations in 

24 hours. Intercellular production of ROS was found to be increased 2- to 2.6-fold after 4 and 

24 hours at 0.1 and 1.0 mM AN. No increase in ROS generation was found in rat hepatocytes at 

any AN concentration or exposure duration. On the other hand, no significant change in MDA 

formation (as indicator of lipid peroxidation) was found in either cell type following treatment 

with AN. 

 A significant decrease in cellular GSH levels was observed in rat astrocytes treated with 

0.1 and 1.0 mM AN for 4 hours (25–36% of control) and 24 hour (43–61% of control) and in 

SOD activity in astrocytes treated for 4 hours with 1 mM AN (39% reduction over control) and 

for 24 hours with 0.1 and 1 mM AN (38–40% reduction over control). In contrast, no significant 

decrease in catalase and glutathione peroxidase activities was observed in treated astrocytes. 

Cotreatment with L-2-oxothiazolidine-4-carboxylic acid (OTC), a precursor to GSH 

biosynthesis, or with vitamin E, an antioxidant, reduced 8-oxodG and ROS formation induced by 

AN treatment. These effects were not evident in isolated hepatocytes treated with AN. Results 

from this study were in agreement with results from the in vivo study by Jiang et al. (1998) on rat 

brain cortex. Kamendulis et al. (1999a) suggested that, since the formation of 8-oxodG and ROS 

observed after AN treatment in this study was temporal, dose dependent, and reversible 

following removal of AN in the culture medium, these are established properties of tumorpromoting agents. Kamendulis et al. (1999a) proposed that AN-induced astrocytomas in rats 

were produced via tumor promotion mechanisms. 

 Jacob and Ahmed (2003b) also demonstrated the ability of AN to induce oxidative stress 

and oxidative DNA damage in NHA culture (see Section 4.5.1.1.3). 

 Pu et al. (2006) measured direct and oxidative DNA damage in cultured D1 TNC1 rat 

astrocytes treated with 0–2.5 mM AN for 24 hours. Direct DNA damage was measured by the 
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comet assay, and oxidative DNA damage was measured with a modified comet assay that 

included enzymatic digestion with formamidopyrimidine glycosylase. 7-Ethoxyresorufin-Odeethylase (EROD) and CYP2E1 activities in the astrocytes were measured. 

 At 2.5 mM AN, a 40% decrease in cell viability was observed. No increase in direct 

DNA damage (measured as increase in tail moment) was observed at any AN concentration. 

Hydrogen peroxide (20 μM) was used as positive control, and significant increase in DNA 

damage was found. On the other hand, a threefold increase in oxidative DNA damage was 

observed in astrocytes treated with 1 mM AN. Supplementation of 1 mM AN with three 

different antioxidants—vitamin E (150 μM), TRX (water-soluble analog of vitamin E, 150 μM), 

and epigallocathechin-3 gallate (a polyphenol from green tea, 5 μM)—reduced AN-induced 

oxidative DNA damage by 65, 54, and 65%, respectively. 

 As expected, only low level CYP2E1 activity was measured in the astrocytes and was 

about 10% of that measured in mouse liver. EROD (an indicator of CYP1A) activity was 

measured in rat astrocytes and was about 500-fold higher than that for CYP2E1. In addition, a 

90% reduction in the activities of EROD and CYP2E1 was observed when the astrocytes were 

cotreated with AN and 0.5 mM ABT for 24 hours. Cotreatment of astrocytes with 1 mM AN and 

0.5 mM ABT also prevented the increase in oxidative DNA damage induced by AN, indicating 

the metabolism of AN by P450 was required for the production of oxidative stress. GSH 

depletion induced by 4 and 24 hours of treatments with DL-buthionine [S,R]-sulfoximine, a 

selective inhibitor of γ-glutamylcysteine synthetase, enhanced the oxidative DNA damage 

induced by AN by 44–160% over control). On the other hand, cotreatment with 2.5 mM OTC, a 

precursor for glutathione biosynthesis, reduced AN-induced oxidative DNA damage by 63–85%. 

Exposure to 0.1–0.5 mM cyanide also increased oxidative DNA damage (Pu et al., 2006). 

 EPA has identified issues in the study design, analytical methods, and data interpretation 

in Pu et al. (2006). First, as mentioned previously in the discussion of Pu et al. (2009), the 

alkaline comet assay measures DNA strand breaks and alkali-labile sites, and is not limited to the 

detection of direct DNA damage only. For the alkaline comet assay, Pu et al. (2006) used 

hydrogen peroxide as a positive control, demonstrating that this assay is not limited to detecting 

direct DNA damage, but also oxidative DNA damage. Second, Pu et al. (2006) used the fpgmodified comet assay for detection of oxidative DNA damage. As discussed previously, the fpgmodified comet assay is not specific for the detection of oxidative DNA damage. Third, 

CYP2E1 level in astrocytes was known to be low and was found to be about 10% that found in 

the mouse liver. Since bioactivation of AN to CEO via CYP2E1 is needed for direct DNA 

damage to be detected, it is not surprising that direct DNA damage could not be detected in 

astrocytes treated with AN (although oxidative DNA damage could have been detected in the 

alkaline comet assay). As discussed previously in Section 3, CEO is a relatively stable reactive 

metabolite, with a half-life of about 2 hours; therefore, most of the CEO detected in rat brain is 

presumed to be formed in the liver of rats treated with AN and transported to the rat brain. 
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Hence, direct DNA damage could not be detected in this in vitro study. Another weakness in 

this study concerns the selection of the positive control. A carcinogen that needs bioactivation 

via CYP2E1 to form a reactive metabolite and induce DNA damage would have served as a 

better positive control than hydrogen peroxide, which does not require bioactivation. Therefore, 

the findings reported in this in vitro study are not anticipated to predict what can occur in vivo. 

Murata et al. (2001) investigated the enhancing effect of AN on the formation of 

8-oxodG in calf thymus DNA, induced by hydrogen peroxide (H2O2) and Cu(II). Calf thymus 

DNA was incubated with various concentrations of H2O2 plus CuCl2 in the presence or absence 

of AN for 30 minutes. The level of Cu(II)-mediated 8-oxodG formation increased with 

increasing concentration of H2O2. The addition of AN (0.1–0.5%) enhanced the formation of 

8-oxodG by hydrogen peroxide and Cu(II) in a dose-dependent manner, whereas AN itself did 

not cause DNA damage. The enhancing effect of AN was more marked in double-stranded than 

in single-stranded DNA. Further experiments with [32P]-labeled DNA showed that addition of 

AN enhanced the site-specific DNA damage at guanine residues, particularly at the 5′-site of the 

GG and GGG sequences while H2O2/Cu(II) induced piperidine-labile sites at thymine, cytosine, 

and guanine residues. Electron spin resonance spectroscopy showed that a nitrogen-centered 

radical was generated from AN during incubation with hydrogen peroxide and Cu(II). Murata et 

al. (2001) proposed that AN enhanced H2O2-mediated DNA damage via nitrogen-centered 

radical formation. Thus, AN may enhance endogenous oxidative stress, although AN itself does 

not have the ability to induce oxidative DNA damage. 

4.5.1.2.3. Intercellular communication. Kamendulis et al. (1999b) investigated the effect of 

AN on gap junction intercellular communication (GJIC) in D1 TNC1 astrocytes (a rat astrocyte 

transformed cell line) and primary rat hepatocytes in culture. Noncytolethal concentrations of 

AN (0.01–1.0 mmol/L) were incubated with D1 TNC1 astrocytes or primary rat hepatocytes. 

GJIC was determined by microinjection of lucifer yellow CH into cells. Dye coupling was 

quantitated by determining the number of recipient cells in contact with microinjected cells that 

showed communication. The reversibility of AN inhibition of GJIC was also evaluated by 

replacement of AN with fresh medium. 

Following 2 hours of treatment, AN at 0.1 and 1 mmol/L inhibited GJIC in D1 TNC1 

astrocytes, which were putative target cells. After treatments for 4 and 24 hours, all 

concentrations of AN (0.01–1.0 mmol/L) inhibited GJIC. The inhibitory effect of AN in this 

system was dose dependent at all time points, reversible by removal of AN, and partially 

suppressed by the presence of antioxidants such as vitamin E (0.1 mmol/L). After treatment with 

both vitamin E and AN for 24 hours, inhibition of GJIC was reduced by 23%. On the other 

hand, AN did not inhibit GJIC in primary cultured hepatocytes at all concentrations and 

durations of treatment. 
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AN also caused a concentration-dependent decrease in cellular GSH content in both 

D1 TNC1 astrocytes and rat hepatocytes (Kamendulis et al., 1999b). Cotreatment with 

5 mmol/L OTC, a precursor of GSH synthesis, reduced inhibition of GJIC by AN in D1 TNC1 

astrocytes following 4 and 24 hours of exposure, with the greatest reduction observed at 

1.0 mmol/L AN (up to 68%). However, depleting GSH by L-BSO (an inhibitor of intracellular 

GSH synthesis) alone without AN did not affect GJIC in rat astrocytes. Thus, depletion of GSH 

alone in astrocytes was not sufficient for the observed decrease in GJIC by AN. 

Inhibition of intercellular communication by AN was implied in an inhibition of 

metabolic cooperation assay. Two studies (Elmore et al., 1985; Umeda et al., 1985) evaluated 

AN by using the Chinese hamster V79 cells, which are 6-thioguanine (6-TG) sensitive and 

6-TG-resistant cloned cells that are the hypoxanthine guanine phosphoribosyl transferase (hprt–)

mutant of the V79 cell line. The hprt– mutant cannot phosphorylate several purine analogues, 

including 6-TG, and are therefore resistant to cell killing by the purine analogue. When the WT 

cells are cultured at a density that permits frequent contact with the mutant cells, metabolic 

cooperation (i.e., gap junction formed between these cells) allows the transfer of nutrients and 

phosphorylated purine analogue from the WT cells to the mutant cells and decreases probability 

of recovery of the mutant cells in purine analog selective medium. The principle of the assay is 

based on the fact that recovery of 6-TG-resistant cells cocultivated with 6-TG-sensitive cells in 

6-TG-containing medium increased by addition of compounds that inhibit metabolic 

cooperation. This assay evaluates if the test agent can modulate gap junctional communication. 

AN inhibited gap junction formation slightly and dose dependently (Umeda et al., 1985). 

Average recovery of the mutant cells was 22% in the control, 33% at 1 mM AN, and 39% at 

2 mM AN. Umeda et al. (1985) considered AN as positive in the metabolic cooperation assay. 

In the study by Elmore et al. (1985), AN produced positive responses at noncytotoxic 

concentrations of 10–50 μg/mL after incubation for 3 days. 

4.5.1.2.4. Cell proliferation. Ghanayem et al. (1997) examined the effects of AN on 

forestomach cell proliferation and apoptosis in male F344 rats (12/group) administered either 0, 

0.22, or 0.43 mmol/kg (0, 11.67, or 22.8 mg/kg) by gavage for 6 weeks. Six rats from each dose 

group were used to assess BrdU incorporation in the stomach, the remaining six rats from each 

group were used to assess BrdU incorporation in hepatocytes. Proliferation of forestomach 

squamous epithelial cells was evaluated with light microscopy by determining the number of 

cells (nuclei) per unit length muscularis and by quantitating BrdU-stained cells. 

 AN was shown to induce a dose-dependent increase in epithelial cell proliferation in the 

forestomach, as determined by the incorporation of BrdU into S-phase DNA. The increase in 

forestomach mucosal cell proliferation was significant at both the low and high doses of AN. No 

cellular proliferation was detected in the liver and glandular stomach, which are not target organs 

of AN carcinogenicity. 
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 There was an associated increase in the thickness (hyperplasia) of the forestomach 

squamous mucosa, also possibly indicative of enhanced cell proliferation. Forestomach 

hyperplasia (expressed as the increase in the total number of epithelial cells per mm muscularis) 

was significant in the high-dose group and was about 60% above vehicle-treated controls. 

Hyperplasia in the low-dose group was only 7% above controls and was statistically 

insignificant. The effects of AN on cellular proliferation in the forestomach of treated rats were 

also evaluated by quantitative determination of BrdU incorporation into S-phase DNA, using 

immunohistochemical staining. The increase in forestomach mucosal cell proliferation was 

significant at both the low- and high-dose groups. In addition, the effect of AN on apoptosis was 

determined by in situ end labeling of tissue sections. Apoptotic bodies were observed in the 

forestomach of rats treated with high-dose AN. No increase in apoptosis was detected in the 

liver or glandular stomach of control or treated rats. Thus, AN induced a significant increase in 

forestomach apoptosis at the high dose, coupled with an increase in hyperplasia. 

 Ghanayem et al. (1997) proposed that disruption of the normal balance between cell 

proliferation and apoptosis in favor of enhanced forestomach cell proliferation (as reflected by 

hyperplasia of the forestomach epitheilium) probably contributed to the pathogenesis of 

AN-induced forestomach tumors. This suggestion was supported by the observations that cell 

proliferation in forestomach squamous mucosa of treated rats occurred at doses that caused 

forestomach tumors in rats and that cell proliferation was selective and only occurred in the 

target organ forestomach but not in liver. 

 In a recent study, Chantara et al. (2006) evaluated whether AN induced extracellular 

signal-regulated kinase (ERK) activation in human neuroblastoma SK-N-SH cells. The 

activation of ERKs belonging to the mitogen-activated PK family has been implicated to play 

crucial roles in cell proliferations and is involved in many steps of tumor progression (Fang and 

Richardson, 2005; Platanias, 2003; Seger and Krebs, 1995). Dysfunction of the ERK signaling 

pathways was shown to play a pivotal role in the development of many cancers, including 

leukemia and colon cancer. Active forms of ERK1/2 were found to be dually phosphorylated at 

threonine and tyrosine. To investigate whether AN could activate ERK, the effect of AN on the 

activation-association phosphorylation of ERK1/2 was measured in SK-N-SH cells. Treatment 

with 400 μg/mL AN for 1 hour increased the activation-associated phosphorylation of ERK1/2. 

Further increase in ERK1/2 phosphorylation was observed with 3 and 24 hours of incubation. 

Furthermore, increase in ERK phosphorylation was found to be dependent on AN concentration. 

When SK-N-SH cells were treated with specific mitogen-activated/ERK-activating kinase 

(MEK) inhibitors, PD98059 (10 μM) and U0126 (10 μM), for 1 hour prior to treatment with 

400 μg/mL AN for 24 hours, activation of ERK by AN was significantly abolished. Thus, 

Chantara et al. (2006) concluded that AN induced ERK1/2 phosphorylation in SK-N-SH cells via 

activation of MEK. 
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 The role of muscarinic receptors in AN-mediated ERK activation was also investigated 

by pretreating SK-N-SH cells with or without 10 μM atropine, a muscarinic receptor antagonist, 

followed by incubation with AN for 24 hours. Carbachol, a muscarinic receptor agonist, was 

used as a positive control. Previous studies suggested that expression of muscarinic receptors 

can induce cell proliferation by activating the ERK1/2 pathway (Jiménez and Montiel, 2005). 

The results showed that 1 mM carbachol induced ERK1/2 activation, and this effect was reduced 

by atropine pretreatment. However, AN-induced ERK activation was not significantly altered by 

atropine pretreatment, suggesting that muscarinic receptor stimulation may not be directly 

involved in the observed AN-induced ERK activation (Chantara et al., 2006). 

 Chantara et al. (2006) also investigated whether oxidative stress generated by various 

stimuli might result in activation of ERK by studying the effects of antioxidants on AN-induced 

ERK activation. Three non-enzymatic antioxidants were used: NAC, ascorbic acid, and watersoluble vitamin E (TRX) were used. When SK-N-SH cells were pretreated with 20 mM NAC 

for 10 minutes or 1 mM ascorbic acid or 1 mM TRX for 1 hour prior to addition of 400 μg/mL 

AN for 24 hours, no reduction in AN-induced ERK activation was found. Therefore, Chantara et 

al. (2006) concluded that the activation of ERK by AN observed in SK-N-SH cells was not 

mediated via an oxidative stress-dependent mechanism. 

 To determine if AN-induced ERK activation was mediated via PKC, PKC was inhibited 

via several methods. In addition to applying the PKC inhibitors, GF109203X 

(bisindolymalcimide) and rottlerin, PKC was also depleted by prolonged incubation of the cells 

with phorbol 12-myristate 13-acetate (PMA). Inhibition of PKC by GF109203X significantly 

reduced the increase in ERK1/2 phosphorylation to 26% of that caused by AN alone. Similarly, 

rottlerin and prolonged treatment with PMA reduced the activation of ERK by AN. Therefore, 

the study authors concluded that PKC played an important role in AN-induced ERK activation in 

SK-N-SH cells. In summary, this study demonstrated that AN activated ERK1/2 in a 

PKC-dependent manner and that oxidative stress and muscarinic receptor activation were 

probably not involved in ERK1/2 activation by AN. 

4.5.2. Genotoxicity Studies 

 The following subsections provide a summary of the results of AN and its reactive 

metabolite, CEO, in in vitro and in vivo mutagenicity/genotoxicity assays. The overall 

conclusion that can be drawn from these studies is that AN is genotoxic after metabolic 

activation to CEO. Table 4-53, which provides a summary of studies on the mutagenicity/

genotoxicity of AN, is at the end of this section. 

4.5.2.1. Studies in Humans 

 Seven studies have examined the genotoxicity of AN in vivo in humans who may have 

been occupationally exposed to AN. 
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 Xu et al. (2003) measured the incidence of DNA strand breakage and sex chromosome 

aneuploidy in the sperm of 30 workers exposed to AN for 2.8 years. The mean AN 

concentration at operation sites was 0.8 mg/m3. Thirty sperm donors of the same approximate 

age range from the general population were recruited as controls. Lower sperm density was 

noted in exposed workers compared with controls (75 × 106/mL vs. 140 × 106/mL). DNA strand 

breakage was detected in AN-exposed workers by using single-cell gel electrophoresis, with the 

rate of comet sperm higher in the exposed workers than in the controls (28.7 vs. 15%). The 

frequency of sex chromosome disomy was 0.69% in the exposed group and was >0.35% in the 

control group. There were also significant differences in the frequencies of XX-, YY-, and 

XY-bearing sperm between the exposed and control groups. 

 Fan et al. (2006), in an article translated from Chinese, evaluated the application of a 

micronucleus test by using buccal mucosal cells to detect genetic damages in AN-exposed 

workers. The low concentration (average concentration 0.522 mg/m3 AN) exposed group 

consisted of 41 healthy male workers with direct contact with AN in a chemical plant that 

produced AN (by the oxidation of propylene, ammonia, and air) in Shanghai. Since the entire 

propylene-ammonia oxidation process was carried out in a closed system of pipes and automated 

technology, the chance of contact with AN was primarily at the time of on-site sampling and 

pipe inspection. The average age of this exposed group was 37.4 years, and the range and 

average exposure duration were 1–33 and 15.7 years, respectively. 

 The intermediate (average concentration 1.998 mg/m3

) exposed group consisted of 

47 healthy male workers in an acrylic fiber factory in Shanghai. AN was used as a raw material 

in the synthesis of polyacrylonitrile by polymerization. The average age of workers was 

39.8 years, and the range and average exposure duration were 1–33 and 17.2 years, respectively. 

The control group consisted of 31 healthy male workers with no exposure to any known mutagen 

or AN and living in the same community. Their average age was 37.2 years, and the average 

working duration was 16.7 years. The rates of alcohol consumption and cigarette smoking were 

similar in the exposed and control groups. 

 Buccal mucosal cells were collected from second scrapings from the mucous membrane 

on the inside of both cheeks of study subjects after rinsing their mouths with clean water. Blood 

samples were also collected for measurement of micronuclei (MN) in peripheral blood 

lymphocytes. The rates of occurrence of MN in buccal mucosal cells in the intermediate 

concentration exposed, low concentration exposed, and control groups were 4, 3.68, and 2.03%, 

respectively. The rates of MN in the low and intermediate concentration groups were 

significantly higher than in the control group (p < 0.05). The rates of occurrence of MN in 

peripheral blood lymphocytes in the intermediate and low concentration exposed and control 

groups were 4.23, 2.44, and 2.48%, respectively. The rate of occurrence of MN in blood 

lymphocytes in the intermediate exposed group was significantly different from that in the 

control group (p < 0.05). 
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 To investigate the relationship between AN exposure and the rate of occurrence of MN 

and to eliminate the possibility of the presence of other confounding factors, a multivariate linear 

regression analysis was conducted. The results indicated that the cumulative exposed amount of 

AN, the recent exposed amount of AN, and the extent of cigarette smoking were important 

factors in the rate of occurrence of MN in buccal mucosal cells and blood lymphocytes. Fan et 

al. (2006) concluded that the micronucleus test of buccal mucosal cells could replace the 

micronucleus test of lymphocytes in the peripheral blood as a screening test for genetic damage 

in AN-exposed workers. 

 Borba et al. (1996) evaluated urinary genotoxicity of three groups of workers in an AN 

fiber production plant (exposed group 1: 14 workers in the continuous polymerization section; 

exposed group 2: 10 equipment maintenance workers; control group: 20 administrative workers 

from the same plant). Urine extracts were used in the Ames test (using TA 98, +S9) to assess 

gene reversion activity. No differences in urinary genotoxicity were found in the three groups. 

Additionally, there were no significant differences in the incidence of SCE in peripheral 

lymphocytes among the groups. However, the maintenance workers had a higher incidence of 

CAs in lymphocytes, consisting of chromatid and chromosomal gaps and chromatid and 

chromosomal breaks, than the controls (p < 0.003). These effects were also increased in 

production workers but not to statistically significant levels, possibly due to the comparatively 

low number of subjects in the study. The significantly higher incidence of CAs in maintenance 

workers were in agreement with the highly significant levels of Hb adducts and CEVal in the 

same population (see Section 4.1.2.2). The maintenance workers also had significantly higher 

levels of erythrocyte MDA, an indicator of lipid peroxidation, than the other two group of 

workers. 

 Ding et al. (2003) compared deletion frequencies of mitochondrial DNA in peripheral 

lymphocytes in 47 workers exposed to a mean workplace concentration of 0.11 ppm AN and 

47 nonexposed workers using PCR techniques (this study is described more fully in Section 

4.1.2.2). No deletions were detected in the nonexposed group, but a deletion frequency of 17% 

was detected in the exposed group. In a separate experiment on presumably nonexposed 

individuals, no deletions in mitochondrial DNA were detected in samples from 12 high school 

students, whereas the deletion frequency was 25% in samples from 12 elderly persons. 

Consistent with the hypothesis that damage to mitochondrial DNA contributes to degenerative 

diseases related to aging, the study authors suggested that occupational exposure to AN may 

induce mitochondria DNA deletion in cells that are related to aging. 

 Using the FISH technique with probes for chromosomes 1 and 4, Beskid et al. (2006) 

examined patterns of CAs in cultured lymphocytes from blood samples of 61 AN-exposed male 

workers involved in the polymerization of Indian rubber and 49 nonexposed control subjects. 

Stationary monitoring in the workplaces indicated AN air concentrations of 0.05–0.3 mg/m3 for a 

group of 39 exposed workers sampled in 2000 and 0.05–0.7 mg/m3 for another group of 
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22 exposed workers sampled in 2003. A 38% increase in frequency of aberrant cells in 

AN-exposed workers was found to be statistically insignificant. However, the number of 

reciprocal translocations increased by 53% (p < 0.05) in the AN-exposed group. In addition, a 

significant increase in a relative number of insertions was found in the AN-exposed group. 

Furthermore, chromosomal specificity was observed in lymphocytes with aberrations on 

chromosome #1 and #4. In the AN-exposed group, the proportion of cells with aberrations on 

chromosome #1 decreased significantly (58.8 vs. 73.8% in the control subjects, adjusted to age 

and smoking), but aberrations on chromosome #4 increased (47.0 vs. 29.4% in the controls). 

 In an earlier study by the same research group, the frequency of CAs in peripheral blood 

samples was studied in 45 male rubber polymerization workers exposed for the last 3 months to 

0.05–0.3 mg AN/m3, 23 matched controls living in the same region (control group I), and 

33 unexposed controls from Prague (control group II) (Šrám et al., 2004). Subjects were 

interviewed and completed questionnaires on demographic data, occupational and environmental 

exposures, smoking habits, medications, X-ray examinations, viral infections, and alcohol 

consumption within the 3 months before sampling. Cytogenetic analysis was conducted using 

two methods. Conventional chromosomal analysis was used to quantify CAs (chromatid plus 

chromosome breaks and chromatid plus chromosome exchanges), the number of aberrant cells 

(those with breaks and exchanges, gaps not included), and the aberration frequency (number of 

breaks per cell). The FISH technique, using probes for chromosomes 1 and 4, was employed to 

quantify translocations. Conventional analysis did not detect any differences in the frequency of 

CAs in exposed workers compared with either control group. FISH detected no differences in 

the frequencies of aberrations or translocations in exposed workers compared with matched 

controls (control group I), but the frequencies in both groups were significantly elevated 

compared with unexposed controls from Prague (control group II). Šrám et al. (2004) concluded 

that occupational exposure to 0.05–0.3 mg/m3 AN did not present a significant genotoxic risk 

and attributed higher frequencies in the exposed group and control group I to undetermined 

factors present in the region in which the petrochemical industries are located but absent in 

Prague. 

Thiess and Fleig (1978) surveyed 18 workers at a plant that was used for manufacturing 

copolymers of styrene and AN, styrene, AN, and butadiene and also for synthesis of organic 

intermediates. The workers had been exposed to AN, on average, for 15.3 years and could have 

been exposed simultaneously to styrene, ethylbenzene, butadiene, and other chemicals. The 

control group consisted of 18 workers who had not been exposed to AN. Atmospheric 

monitoring conducted between 1963 and 1974 revealed AN concentration of about 5 ppm, with 

the possibility of higher peak values occurring in connection with special tasks. Between 1975 

and 1977, exposure to AN had been reduced to an average of 1.5 ppm. The incidence of CAs in 

the lymphocytes was measured in these 18 workers and in age-matched nonexposed controls. 

The numbers of aberrant metaphases (gaps and iso-gaps included) were 5.5 ± 2.5% in exposed 
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workers and 5.1 ± 2.3% in controls. When gaps were not included, the numbers dropped to 

1.8 ± 1.3% in exposed workers and 2.0 ± 1.6% in controls. The differences were statistically not 

significant. This study is of limited value because of mixed exposure in the exposed group, 

small group size, and uncertainty in exposure levels. 

4.5.2.2. In Vivo Tests in Mammals 

Rats 

 Oral administration of up to 40 mg/kg AN or i.v. administration of up to 98 mg/kg AN to 

male Sprague-Dawley rats did not induce MN in bone marrow and peripheral blood, respectively 

(Morita et al., 1997). However, Wakata et al. (1998) demonstrated induction of MN in bone 

marrow polychromatic erythrocytes of Sprague-Dawley rats (four/group) treated 2 times with 

124.8 mg/kg AN i.v. and sampled 24 hours after treatment. A negative result was obtained in 

peripheral blood. In another study (Rabello-Gay and Ahmed, 1980), male Sprague-Dawley rats 

treated orally with 16 daily doses of 40 mg/kg-day AN showed no increase in CAs in the bone 

marrow over controls. 

Irreversible binding of radioactivity from [2,3-14C]-AN to DNA in brain, stomach, and 

liver of male Sprague-Dawley rats was reported 24 hours after a single oral dose of 46.5 mg/kg 

(Farooqui and Ahmed, 1983a). DNA alkylation was significantly higher in the target organs, 

brain and stomach (119 and 81 pmol/mg DNA at 24 hours, respectively), than in the liver 

(25 pmol/mg DNA). The covalent binding indices in the liver, stomach, and brain at 24 hours 

after dosing were 5.9, 51.9, and 65.3, respectively. Similarly, covalent binding of [2,3-14C]-AN 

or its metabolite to testicular (Ahmed et al., 1992a), lung (Ahmed et al., 1992b), and gastric 

tissue DNA (Abdel-Rahman et al., 1994b) has been reported in male Sprague-Dawley rats 

treated with a single oral dose of 46.5 mg/kg AN. Maximum covalent binding of radioactivity to 

gastric DNA occurred at 15 minutes after dosing and occurred at 0.5 and 12 hours for testicular 

and lung DNA, respectively. Alkylation of hepatic DNA was also reported when a single dose 

of 0.2 mmol [2,3-14C]-AN was administered to male Wistar rats intraperitoneally (Peter et al., 

1983a). Two 14C peaks that did not cochromatograph with any known standards were observed 

when the DNA hydrolysate from rat livers was chromatographed on PEI-cellulose column. 

In another study, 0.6 mg/kg [2,3-14C]-CEO was administered to one F344 rat 

intraperitoneally (Hogy and Guengerich, 1986), and the rat was sacrificed after 1 hour. Covalent 

binding to both liver and brain protein was found, but no covalent binding to nucleic acids could 

be detected at the level of 0.3 alkylations per 106 bases. In the same study, three male F344 rats 

were administered 50 mg/kg AN i.p., and three other rats were administered 6 mg/kg CEO i.p. 

(Hogy and Guengerich, 1986). The rats were sacrificed after 2 hours. N7-(2-oxoethyl)guanine 

was measured in liver DNA at the level of 0.032 and 0.014 alkylations/106 bases for CEO- and 

AN-treated rats, respectively. In the brains of treated rats, the levels of N7-(2-oxoethyl)guanine 

were not above the limit of detection. Since DNA adduct was detected in liver DNA, covalent 
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binding to DNA had to occur. The method used in the study was not sensitive enough to detect 

low levels of alkylation of nucleic acids, probably because of the small amount of DNA sample 

from one rat, and the DNA isolation protocol (DNA extract purified by hydroxylapatite column 

chromatography and DNA fraction dialyzed against water and lyophilized then treated with 

RNAase and proteinase K) and method for correction for contaminating protein via quantitative 

amino acid analysis in the DNA sample may have allowed a more stringent determination of 

DNA-bound material. 

When the alkaline comet assay was used to detect DNA lesions, Sekihashi et al. (2002) 

demonstrated DNA damage in the forestomach, colon, kidney, bladder, and lung of Wistar rats 

treated with a single dose of 30 mg/kg AN i.p. but not in the brain or bone marrow. 

 Oral exposure to 100 ppm AN in drinking water for 14 or 28 days significantly increased 

the level of cellular DNA fragmentation in the brain of male Wistar rats (Mahalakshmi et al., 

2003). Other aspects of this study are discussed in Section 4.5.1.1.4. 

AN-induced unscheduled DNA synthesis (UDS) was demonstrated in several studies in 

rats. In a study by Hogy and Guengerich (1986), male F344 rats (12/group) received a single 

sublethal dose of 50 mg/kg AN in saline by gavage, followed by hydroxyurea to arrest 

replicative DNA synthesis but allowing excision repair DNA synthesis. Two hours after dosing, 

the animals received s.c. methyl [3H]-labeled thymidine. This dose was repeated after 2 hours, 

and half the dose was given again after 2 more hours for a total dose of 3.0 mCi/kg of BW. The 

animals were sacrificed 2 hours after the last methyl [3H]-labeled thymidine. A significant 

occurrence of UDS was found in the livers but not in the brains of AN-treated rats. 

 Hogy and Guengerich (1986) also studied the effect of treatment on DNA synthesis over 

4 hours in the liver and brain of male F344 rats 48 hours after an oral dose of 50 mg/kg AN. 

DNA synthesis was decreased in the brain but not in the liver; replicative indices were 0.29 and 

1.30, respectively. Thus, the carcinogenicity of AN in rat brain is not likely from cytotoxicity, 

followed by an increased rate of DNA replication and leading to a greater chance of error during 

the rapid DNA synthesis. 

 UDS was demonstrated in lung (Ahmed et al.,1992a), testis (Ahmed et al., 1992b), and 

gastric tissue (Abdel-Rahman et al., 1994a) of AN-treated male Sprague-Dawley rats (12/group). 

Animals received a single oral dose of 46.5 mg/kg AN in saline, with or without hydroxyurea 

cotreatment to block the endogenous deoxynucleotide pool. [3H]-Thymidine was administered 

0.5, 6, or 24 hours after AN dosing, and animals were sacrificed 2 hours later. The replicative 

index for DNA synthesis (i.e., the ratio of DNA synthesis in treated animals over controls) was 

significantly reduced at all three time points in lung, while DNA repair in the lung was increased 

by twofold at 0.5 hour and 1.6-fold at 6 hours following AN oral treatment. Similarly, DNA 

synthesis was inhibited in testes at 0.5 and 24 hours after treatment (but increased at 6 hours), 

whereas DNA repair increased at 1.5- and 33-fold at 0.5 and 24 hours after treatment. For 

gastric tissue, DNA replicative synthesis was inhibited 6 hours after AN administration but was 
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rebounded and followed by a twofold increase at 24 hours. A threefold increase in UDS was 

observed at 24 hours after dosing. 

 On the other hand, Butterworth et al. (1992) followed the incorporations of 

[

3H]-thymidine into the hepatocytes isolated from male F344 rats gavaged with either a single 

dose of 75 mg/kg AN or five daily doses of 60 mg/kg AN. Single-dosed animals were sacrificed 

2 or 12 hours after dosing. Multiple-dosed animals were sacrificed 4 hours after the last dose. 

Hepatocytes were isolated and plated on cover slips and incubated with [3H]-thymidine. 

Autoradiography was used to detect UDS. No sign of AN-induced UDS was found in 

hepatocytes from exposed rats. In addition, no UDS was found in the in vivo spermatocyte DNA 

repair assay with AN, using cells isolated from the seminiferous tubules of the same treated rats 

(Butterworth et al., 1992). The difference in results from Butterworth et al. (1992) and Hogy and 

Guengerich (1986) regarding UDS in rat liver may be due to differences in methodology in that 

incorporation of [3H]-thymidine actually took place in vitro in the study by Butterworth et al. 

(1992). 

 AN also produced negative results for dominant lethal assay in male F344 rats (Working 

et al., 1987). In this assay, groups of 50 male F344 rats received AN by gavage at 0 or 

60 mg/kg-day in 0.9% saline for 5 days. AN exposure in males had no effect on the incidence of 

pre- or postimplantation losses, indicating a negative result to germ cells. 

Mice 

When the alkaline comet assay was used to detect DNA lesions, Sekihashi et al. (2002) 

demonstrated DNA damage in the forestomach, colon, bladder, lung, and brain of male ddY 

mice treated with 20 mg/kg AN i.p. DNA damage was not detected in the liver, kidney, or bone 

marrow. 

Sharief et al. (1986) determined that AN caused a slight increase on SCE frequencies in 

bone marrow cells of male C57B1/6 mice (four/dose group). No increase in SCE frequencies 

was observed in mice administered a single dose of up to 30 mg/kg AN intraperitoneally. Higher 

doses were lethal to most of the animals. An increase in SCE frequency (2 × control) was 

observed in the only surviving mouse at the 45 mg/kg dose group. However, Fahmy (1999) 

reported AN-induced SCEs in bone marrow cells of male Swiss mice (five/group) treated with 

7.5 mg/kg or 10 mg/kg AN i.p. 8 hours following BrdU treatment and with colchicines 2 hours 

prior to sacrifice. The lowest dose of 5 mg/kg i.p. produced no significant effect on SCE 

frequency.

 Earlier CA studies in mice have been largely negative. Rabello-Gay and Ahmed (1980) 

showed that AN did not produce increases in CAs in bone marrow cells of male Swiss mice 

(six/group) when given orally for 4, 15, or 30 days at doses up to 21 mg/kg-day or by i.p. 

injection at doses up to 20 mg/kg-day for the same duration. No increase in the incidence of 

CAs compared with controls was observed in bone marrow cells of NMRI mice that were 
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injected intraperitoneally with 20 or 30 mg/kg AN (Leonard et al., 1981). No increase in CAs in 

bone marrow cells and spermatogonia was observed in ICR mice treated with 20 or 100 mg/m3

AN for 5 days (Zhurkov et al., 1983). However, Fahmy (1999) reported AN-induced CAs in 

mouse spermatocytes after single oral doses of 15.5 or 31 mg/kg or three or five successive oral 

doses of 7.75 mg/kg (1/8 LD50) in male Swiss mice. In addition, AN induced CAs in mouse 

bone marrow cells and spleen cells after a single oral dose of 7.75 mg/kg or three or five 

successive doses of 7.75 mg/kg. The aberrations were mainly of chromatid type (gaps, breaks, 

fragments, and deletions), with metaphases carrying one aberration only being dominant. 

 Leonard et al. (1981) also reported AN did not induce MN in polychromatic erythrocytes 

of male NMRI mice injected intraperitoneally with 20 or 30 mg/kg AN. Marginal, but 

statistically significant, increases in MN were observed in bone marrow polychromatic 

erythrocytes but not in peripheral blood when AN at doses of 5.6–45 mg/kg was administered to 

male CD-1 mice (five/group) via i.p. administration. Oral or i.v. injection yielded negative 

results (Morita et al., 1997). 

 Treatment with AN produced negative results for dominant lethal assays in male mice. 

The dominant lethal assay was used to detect CAs in meiotic and postmeiotic male germ cells. 

Groups of five male NMRI mice were injected intraperitoneally with 0 or 30 mg/kg AN in saline 

or isopropyl methanesulfonate (positive control) and then mated to untreated females (three per 

male) for 5 weeks (Leonard et al., 1981); females were replaced after 7, 14, 21, and 28 days, and 

the uterine contents were examined 17 days after mating. No evidence for dominant lethal 

effects was observed. 

4.5.2.3. Short-term Tests: Bacteria, Fungi, Drosophila, Others 

 There are a large number of reports of short-term genotoxicity test results on AN that 

have been made available through the auspices of the International Programme on Chemical 

Safety (IPCS). The IPCS coordinated the investigation of eight organic carcinogens known to be 

either inactive or difficult to detect in the Salmonella assay, including AN, benzene, 

diethylhexylphthalate, diethylstilbestrol, hexamethylphosphoramide (HMPA), PB, safrole, and 

o-toluidine, as well as two noncarcinogens in rodent bioassays (benzoin and caprolactam). Most 

of the available short-term genotoxicity tests were employed, and the work was carried out at 

some of the major research and testing laboratories throughout the world. The purpose of this 

endeavor was to evaluate the efficacy of these tests, to evaluate the strengths and weaknesses of 

such tests, and to identify the assay systems to complement the widely used Salmonella assay. 

All of the results from these studies have been compiled in a 750-page collection (Ashby et al., 

1985), and a 56-page synopsis of the results is available on the Internet (IPCS, 1985). The 

conclusion from these evaluations was that AN, along with HMPA, o-toluidine, and safrole, 

belonged to a group of genotoxins that were detected by most of the eukaryotic assays studied 

and could easily be found to be nonmutagenic in the Salmonella assay because of protocol 
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deficiencies associated with the overall metabolic capacity of the assay system. While several of 

these studies have been cited in this section, an overview of the findings as they pertain to AN 

follows. 

 AN, at concentrations not overtly toxic in a given assay, was found in 42 of 68 tests to 

positively cause genotoxicity in bacteria, fungi, Drosophila melanogaster (mutation, gene 

reversion, mitotic crossing over, aneuploidy), and mammalian cell culture assay systems, both 

human and animal (single-strand breaks, UDS, CAs, SCEs, MN, and transformation). Among 

the eight carcinogens studied, AN gave the most positive results, inducing genotoxicity 

responses in 62% of all tests (42 out of 68 tests; 25 were negative and 1 was questionable). That 

number of positive responses rose to 81% when a more stringent selection of assays was applied 

(IPCS, 1985). Other studies, covering all assay types used in that collaborative study, are listed 

in the two subsections on short-term assays (Sections 4.5.2.3 and 4.5.2.4). 

4.5.2.3.1. Bacterial tests. A number of research groups have examined the capacity of AN to 

induce gene reversion in the Ames test. One of the first published papers was Milvy and Wolff 

(1977), which reported positive results of AN on Salmonella typhimurium strains TA 1535, 

1538, and 1978 in the presence of S9 and an NADPH generating system. The first strain is 

sensitive to base substitution mutagens, and the latter two strains are sensitive to frameshift 

mutagens. Negative results were obtained when metabolic activation was excluded from the 

system. Gene mutation by exposure of bacteria to an atmosphere containing AN was found to 

occur at concentrations as low as 57 ppm (equivalent to 2 μL of AN), lower than exposure in 

solution or spotting AN to a “lawn” of bacteria on a plate. This could be because AN vaporized 

readily in solution such that the actual exposure concentrations in solution or by spotting were 

uncertain. The findings of Milvy and Wolff (1977) were criticized by Venitt (1978) in a letter to 

the editor. While not disagreeing with the overall conclusion, Venitt (1978) considered the study 

authors to have calculated mutation frequency incorrectly from the data. Venitt (1978) 

confirmed AN to be mutagenic in TA 1535 but not in the frameshift strains TA 1538 and 1978. 

 Among other reports of AN activity in the Ames test, Lijinsky and Andrews (1980) found 

AN at doses of 100–1,000 μg per plate to be positive in S. typhimurium TA 1535 in the presence 

of S9 but negative in TA 98, 100, 1537, and 1538 in the plate incorporation assay. Similarly, 

Brams et al. (1987) reported AN (50–750 μg/L) to be negative for gene reversion in TA 97, 98, 

and 100 using plate incorporation assay, irrespective of metabolic activation. The study authors 

accounted for these negative results with inadequate experimental conditions. Previously, they 

had demonstrated that AN was mutagenic in TA 1530, 1535, and 1950 when 0.2% gaseous AN 

was injected into the dessicator where the plates were incubated for 1 hour in the presence of S9 

(the plate agar contained 200 μg AN/plate) (de Meester et al., 1978). A lower mutagenic activity 

was also detected with strains reversed by frameshift mutation (TA 98, 1978, 100), and assays 
232 DRAFT - DO NOT CITE OR QUOTE 

conducted by the plate incorporation method gave negative results (de Meester et al., 1978; Dow 

Chemical Co., 1976). 

 Jung et al. (1992) provided data from three laboratories that examined the ability of AN 

to induce gene reversion in TA 102 in the plate incorporation assay, with uniformly negative 

results. Hakura et al. (2005) reported that AN induced dose-dependent increases in the number 

of revertants per plate in strain TA 100 exposed to concentrations ranging from 806 to 12,100 μg 

per plate in the presence of rat or human liver S9 preparations, but the maximum response at 

12,100 μg per plate was slightly less than twofold higher than the number of revertants per plate 

observed in the negative controls. 

 Although the methodologies of the experiments may have been different, the positive 

finding of mutagenicity by de Meester et al. (1978) for AN in TA 98 and 100 is in agreement 

with data from Khudoley et al. (1987) that AN (concentration not provided) was positive in 

TA 98 and 100 (with two- to fivefold increase in frequency of induced mutants), irrespective of 

the presence of S9. Zhurkov et al. (1983) reported AN to dose-dependently induce mutations in 

S. typhimurium TA 1535 but not in TA 1538. The presence of complete S9 fraction was required 

for this effect, but a 9,000 × g microsomal supernatant without cofactors gave inconsistent 

results. The concentrations tested were between 0.1 and 10,000 μg per dish. The highest 

concentration was overtly toxic to the bacteria. 

 Other tests of the mutagenicity of AN in bacterial systems were negative. For example, 

Nakamura et al. (1987) employed the SOS test to evaluate the capacity of AN to induce 

expression of the umu gene in S. typhimurium TA 1535/pSK1002. This strain contains a 

umuC-lacZ fused gene, such that a forward mutation results in umu gene expression and the 

transcription of the lac operon and can be demonstrated phenotypically by a twofold increase in 

β-galactosidase activity. AN, at concentrations up to 2,820 μg/mL, and seven other known 

mutagens gave negative results in this system. Similarly, AN was negative in the SOS 

chromotest in Escherichia coli PQ37 (Brams et al., 1987). It should be noted that only 4 out of 

14 compounds that were positive in the Ames assay were positive in the SOS chromotest kit 

used. Thus, some technical issues were responsible for the poor performance of the test kit 

(Brams et al., 1987). 

 Venitt et al. (1977) tested AN for mutagenicity in a gene reversion assay (2–3 days at 

37°C), using the tryptophan-dependent E. coli WP2 series of bacteria as indicator organisms. 

Doses of 75 and 150 μmol per plate of AN produced a dose-related increase in the number of 

revertant colonies (trp– → trp+) compared with untreated bacteria in WP2 (which is DNA repair 

proficient), WP2 uvrA (which lacks excision repair), and WP2 uvrApolA (which lacks both 

excision repair and DNA polymerase 1) without a need for S9 fraction. The study authors 

confirmed these results by using a simplified “fluctuation” assay in which they obtained a dosedependent increase in mutation rate induced by 0.4–2 mM AN (20- to 40-fold lower than the 

levels in plate test) in E. coli WP2. An exponential dose response was seen at lower 
233 DRAFT - DO NOT CITE OR QUOTE 

concentrations, 0.1–0.4 mM, with mutant WP2 uvrApolA, which lacked both excision repair and 

DNA polymerase-1. The effective mutagenic concentration range for AN was lowered by an 

order of magnitude when an error-prone DNA-repair plasmid, pKM101, was introduced into 

E. coli WP2. The study authors concluded from these results that AN caused non-excisable misrepair DNA damage that ultimately gave rise to DNA strand breaks. Venitt et al. (1977) 

hypothesized that AN might react with thymine residues in DNA since AN has been shown to 

cyanoethylate ring N atoms of minor tRNA nucleosides and ribothymidine and thymidine 

(Ofengand, 1967). 

 Lambotte-Vandepaer et al. (1985, 1981, 1980) collected urine from male Wistar rats 

(two/group) and NMRI mice (five/group) that had been administered a single dose of AN 

(30 mg/kg intraperitoneally). The urine samples were evaluated for potential induction of gene 

reversion in S. typhimurium TA 1530. Positive results were obtained in rats and mice in the 

absence of S9. Mutagenic activity in urine was abolished by the presence of S9 in rats and 

decreased in mice, a finding that suggests that the mutagenic agent in urine can be inactivated 

metabolically. Pretreatment with PB (induces CYP450 monooxygenase), CoCl2 (inhibits 

CYP450 monooxygenase), and DEM (depletes GSH), before AN treatment, slightly decreased 

the mutagenic response in urine from mice and completely abolished the response in urine from 

rats. However, the study authors were unable to identify the genotoxic compound in urine. 

4.5.2.3.2. Fungi. Available studies that employed fungi in short-term assays on the 

mutagenicity/genotoxicity of AN produced mostly positive results. AN induced mitotic gene 

conversion in both stationary-phase and log-phase cultures at the his4 and trp5 loci of 

Saccharomyces cerevisiae JD1, in the presence of metabolic activation by S9. Negative results 

were obtained without metabolic activation (Brooks et al., 1985; Shell Oil, 1984a). AN did not 

induce chromosome loss in S. cerevisiae D61.M (Whittaker et al., 1990) but elicited respiratory 

deficiency, reflecting antimitochondrial activity. 

4.5.2.3.3. Drosophila. A range of in vivo experimental systems used the fruit fly,

D. melanogaster, to examine the mutagenicity/genotoxicity of AN. Drosophila can biotransform 

certain procarcinogens to their reactive metabolites and are used in short-term tests for 

identifying carcinogens and in studies on the mechanism of mutagenesis of chemicals (Vogel et 

al., 1999). 

 Osgood et al. (1991) used the Drosophila ZESTE system to monitor the potential for AN 

to induce sex chromosome aneuploidy, following inhalation exposure of adult females to 

2.7 ppm for up to 70 minutes. AN induced chromosome loss after exposure for 50 and 

70 minutes. AN was mostly nontoxic at the tested dose, with only 13% killed after a 70-minute 

exposure. Similarly, in a Drosophila somatic recombination and mutation assay, Drosophila

larvae were exposed to 5–20 mM AN in water for 9–11 days, and hatching females were scored 
234 DRAFT - DO NOT CITE OR QUOTE 

for twin mosaic spots and single mosaic light spots in their eyes (Vogel, 1985). These genetic 

markers might arise from many types of genetic alterations. Mitotic recombination and 

chromosome breakage would result in mosaic twin spots, whereas deletions and gene mutations 

would give rise to mosaic single light spots. AN was positive for the induction of mosaic single 

spots at 5 mM (LC50 concentration was 10 mM) and negative for twin spots. Since the 

classification of single spots or twin spots might be subjected to personal bias, the total of twin 

and single spots was also reported, and AN gave positive result. 

 AN was shown to be mutagenic by having marginally positive effects in somatic 

mutation/recombination assay on wing spots of Drosophila, with gas exposure of larva to 0.5–

1 μL/1,150 mL for 0.5 or 1 hour (Würgler et al.,1985). AN gave negative results in a sex-linked 

recessive lethal mutation test on postmeiotic and meiotic germ cells of male D. melanogaster, 

exposed either by feeding of 420 ppm AN or injected with 3,500 ppm AN (Foureman et al., 

1994). 

 The in vitro effect of AN on taxol-purified microtubules from Drosophila and mouse 

brain was evaluated by Sehgal et al. (1990). (Taxol promoted the formation and stability of 

microtubules.) Microtubules assist in the movement of chromosomes in both mitosis and 

meiosis. Polymerization and depolymerization of microtubules occur in cell division to separate 

the chromosomes from the metaphase plate during anaphase. In this study, the assembly and 

disassembly of microtubules was monitored spectrophotometrically in vitro. Previous results 

from in vivo assays monitoring induced sex chromosome aneuploidy indicated that effective 

aneuploidogens affected microtubule assembly. When taxol-purified D. melanogaster 

microtubule was incubated at 37°C to allow polymerization, addition of 5 or 50 mM AN resulted 

in 28 and 64% inhibition of microtubule assembly, respectively. When taxol-purified mouse 

brain microtubules were incubated with 5 or 50 mM AN, 74 and 96% inhibitions of microtubule 

assembly were observed, respectively. Thus, these results indicated that AN was an 

aneuploidogen in vitro. On the other hand, taxol significantly affects microtubule 

depolymerization assay, probably by stabilizing the formed microtubules. None of the tested 

aneuploidogens, including colchicine, promoted disassembly to taxol-purified microtubules. 

4.5.2.3.4. Other short-term tests. Yates et al. (1994) reported on the ability of CEO to induce 

single- and double-strand DNA breaks in supercoiled DNA plasmid pBR322 DNA. Supercoiled 

DNA (1 μg) was incubated for 3 hours at 37°C with ≥50 mM CEO and then subjected to agarose 

gel electrophoresis. The study authors reported that CEO non-enzymatically induced DNA 

strand breaks in a dose- and time-dependent manner, but detailed data were not provided. Peter 

et al. (1983b) found that AN did not induce strand breaks in SV40 phage DNA in vitro, whereas 

synthetic glycidonitrile (i.e., CEO) was effective in the same system (both agents were incubated 

with DNA at 1 mmol/L for 17 hours in the dark, at 37°C, in a buffered solution without any 

enzyme addition). 
235 DRAFT - DO NOT CITE OR QUOTE 

4.5.2.4. Mammalian Cell Short-term Tests 

4.5.2.4.1. Mutations. A number of research groups have examined the ability of AN to induce 

forward mutations in human lymphoblast cell lines and the well-known mouse lymphoma 

L5178Y Tk+/– system. 

 Crespi et al. (1985) used two human lymphoblast cell lines, Tk6 (which does not contain 

CYP450 activities) and AHH-1 (which is metabolically competent) to assess AN mutagenicity at 

the thymidine kinase (Tk+/–) locus and the hprt locus, respectively. Tk6 cell cultures were treated 

with 0–40 μg/mL AN for 3 hours with and without externally added metabolic activation (rat 

liver S9). On the third day after treatment, the cultures were plated in a selective medium 

containing 2 μg/mL trifluorothymidine. After incubation for 12 days, the plates were scored for 

the presence of mutant colonies. Similarly, AHH-1 cell cultures were treated with AN for 

28 hours, and the cultures were plated on the 6th and 7th day after treatment in a selective medium 

containing 0.6 μg/mL 6-TG. AN induced dose-dependent mutations at the Tk+/– locus in Tk6 

cells in the presence, but not in the absence, of S9. AN induced mutations at the hprt locus in 

AHH-1 cells. The lowest AN concentrations that were mutagenic in these test systems were 

40 μg/mL with Tk6 cells +S9 and 25 μg/mL with AHH-1 cells. 

 Similarly, Recio and Skopek (1988a, b) assessed the mutagenicity of AN and its epoxide 

metabolite, CEO, at the Tk+/– locus in Tk6 human lymphoblast cells in the presence and absence 

of rat liver S9. In the presence of S9, 2-hour incubations with 1.4 mM AN induced mutations at 

the Tk+/– locus as demonstrated by the presence of mutant clones when plated in trifluorothymidine selection medium after treatment, but, in the absence of S9, no mutagenic activity was 

observed over the concentration range of 0.4–1.5 mM (Recio and Skopek, 1988b). In contrast, 

2-hour incubation with CEO at concentrations as low as 100 and 150 μM induced a mutagenic 

response (without metabolic activation) at the Tk+/– locus (Recio and Skopek, 1988b). On a 

molar basis, CEO was as mutagenic in this system as the well-known mutagen, ethyl 

methanesulfonate (Recio and Skopek, 1988a). 

Two classes of CEO-induced Tk–/– mutant phenotypes were identified that differed in

their growth rates: Tkn with normal growth rate and Tks with slower growth rates. Southern blot 

analysis of DNA of these two classes indicated that the phenotypes differed genotypically (Recio 

and Skopek, 1988b). Ninety-six percent (25/26) of Tks mutants had lost a 14.8 kb DNA 

fragment corresponding to the active Tk allele, whereas only 8% (1/12) of CEO induced Tkn

mutant clones and 22% (2/9) of spontaneous Tkn mutant clones had lost the 14.8 kb fragment 

(Recio and Skopek, 1988a, b). Recio and Skopek (1988a) suggested that Tks mutants resulted 

from large-scale DNA structural alterations involving the active Tk allele. CEO induced 

predominantly Tkn mutants. Southern blot analysis of CEO-induced Tkn mutants indicated the 

majority of these mutants were below the detection limit of <2 kb. Thus, CEO-induced 

alterations are relatively small DNA alterations. Recio and Skopek (1988a) suggested that 
236 DRAFT - DO NOT CITE OR QUOTE 

CEO-induced Tkn mutants resulted from point mutations or small insertion/deletions that 

occurred during the replication or repair of CEO-modified DNA. Karyotypic analysis on two 

Tkn mutants and 16 Tks mutants indicated that the majority of Tk mutants were not accompanied 

by abnormalities of the chromosome on which the Tk gene resides (chromosome 17). 

CEO also induced mutations at the hprt locus in Tk6 cells (Recio and Skopek, 1988a). 

Characterization of the hprt mutations by cDNA sequencing analysis indicated that several hprt 

mutations were formed. A major (8/14) type of CEO-induced mutation was the specific loss of 

exons from the coding region of hprt. Remaining mutants (6/14) were single base substitutions 

(point mutation) resulting from amino acid changes (A:T base pairs and G:C base pairs). 

The mutagenicity of AN was evaluated in the mouse lymphoma L5178Y Tk+/–

 forward 

mutation assay by a number of laboratories. Oberly et al. (1996) demonstrated that AN 

(activated with S9) was mutagenic at 40 μg/mL in this assay because of producing a more than

twofold increase in mutant frequency when compared to the mutant frequency of the solvent 

controls. Earlier results in the mouse lymphoma L5178Y Tk+/- system from several studies all 

pointed to the capacity of AN at 12.5–200 μg/mL to induce forward mutations at the Tk+/– with or 

without S9 (Lee and Webber, 1985; Myhr et al., 1985; Amacher and Turner, 1985; Rudd, 1983). 

Garner and Campbell (1985) also reported that AN induced mutations to ouabain and 6-TG 

resistance in the mouse lymphoma L5178 Y cells in the presence of S9. However, negative 

results were obtained by Styles et al. (1985) in the mouse lymphoma L5178Y Tk+/+ cell line 

(Na+/K+ ATPase locus, ouabain was used for mutant selection) and Tk+/– cell line 

(trifluorothymidine was used for mutant selection). Using P388F mouse lymphoma Tk+/–cell line

in the presence of S9, Anderson and Cross (1985) also obtained forward mutations to 5-iodo2-deoxyuridine resistance with AN. However, negative results were obtained by Lee and 

Webber (1985) in Chinese hamster V79/HGPRT assay in which AN did not induce 8-azaguanine 

resistance mutation with or without S9. 

4.5.2.4.2. Other DNA effects

UDS 

AN, at concentrations up to 2.5 mg/mL, was negative for induction of UDS in HeLa cells 

with or without the presence of S9, using the scintillometric method (Martin and Campbell, 

1985). However, an increase in UDS, as measured by uptake of [3H]-thymidine, was reported in 

cultured human lymphocytes treated with 5 × 10-1 M AN and S9 (Perocco et al., 1982). Negative 

results were reported for the ability of AN to induce DNA repair synthesis (measured by 

incorporation of [3H]-thymidine and autoradiographic techniques) in rat hepatocyte primary 

culture (Probst and Hill, 1985; Williams et al., 1985). However, no UDS, as measured by 

autoradiography, was observed in any of the cultures treated with the eight tested carcinogens 

(Probst and Hill, 1985). Similarly, only one of the eight carcinogens tested by Williams et al. 

(1985) induced DNA repair synthesis as determined by autoradiography of [3H]-thymidine 
237 DRAFT - DO NOT CITE OR QUOTE 

incorporation (AN was negative in this assay). Thus, IPCS (1985) concluded the rat hepatocyte 

autoradiographic UDS assay was an insensitive assay for determination of genotoxicity of these 

chemicals and should be avoided for use as a complement to the Ames assay. 

Butterworth et al. (1992) used incorporation of [3H]-thymidine and autoradiographic 

techniques to study the effect of AN and CEO on unscheduled DNA repair in vitro in rat 

hepatocytes, and human mammary epithelial cells. AN and CEO were negative for the induction 

of DNA repair in hepatocytes in vitro. There was some indication of a statistically insignificant 

response at 0.1 mM CEO. However, CEO was toxic to the hepatocyte culture at 1 mM, the next 

higher tested concentration. As noted previously, IPCS (1985) has determined that rat 

hepatocyte autoradiographic UDS assay is insensitive for genotoxicity testing of AN and a group 

of seven other carcinogens. However, CEO, but not AN, was positive for UDS in human 

mammary epithelial cells in vitro (Butterworth et al., 1992). 

DNA strand breaks

DNA single-strand breaks were measured by the alkaline elution method in the following 

studies. DNA single-strand breaks were induced in [

14C]-thymidine-labeled cultured adult 

human bronchial epithelial cells treated with 200 or 500 μg/mL AN for 20 hours (Chang et al., 

1990). These concentrations were below the cytotoxic concentration of 600 μg/mL AN. DNA 

single-strand breaks were also reported in cultured rat hepatocytes treated with 65.8 μg/mL AN 

for 3 hours (Bradley, 1985). Higher concentrations of 197 or 658 μg/mL AN resulted in 

cytotoxicity. In another study, AN induced DNA single-strand breaks in cultured Chinese 

hamster ovary (CHO) cells treated with 3.7 × 103 or 5.3 × 104μg/mL AN (7 × 10-2 or 1 × 10-1 M 

AN) with or without S9 mix for 1 hour (Douglas et al., 1985). These concentrations were above 

the cytotoxic concentrations of 5.31 and 53.1 μg/mL AN (10-5 and 10-4 M) with and without 

S9 mix, respectively. Thus, the observed DNA strand break effect was relatively weak in CHO 

cells. Lakhanisky and Hendrickx (1985) reported that AN (concentrations not reported) did not 

in induce DNA strand breaks in cultured CHO cells with or without S9. Therefore, cultured 

CHO cells may not be a sensitive assay system to test for DNA strand breaks induced by AN 

when compared with other cell cultures. On the other hand, DNA strand breaks was reported in 

SHE cells treated with AN. Parent and Casto (1979) observed incubation of [3H]-thymidinelabeled primary SHE cells with 200 or 400 μg/mL AN for 18 hours caused a shift in the 

sedimentation pattern of the labeled cellular DNA when subjected to alkaline sucrose gradient. 

4.5.2.4.3. Cytogenic effects. AN induced SCE in cultured adult human bronchial epithelial cells 

treated with noncytotoxic concentrations of 150 or 300 μg/mL AN for 20 hours (Chang et al., 

1990). An increase in frequency of SCE was observed in human lymphocytes from two different 

donors incubated for 1 hour with 5 × 10-4 M AN and S9 mix. No increase in SCE was observed 

without the S9 mix metabolizing system. (Perocco et al., 1982). AN was negative for the 
238 DRAFT - DO NOT CITE OR QUOTE 

induction of SCEs in CHO cells (Ved Brat and Williams, 1982). However, when CHO cells 

were cocultured with freshly isolated rat hepatocytes, Ved Brat and Williams (1982) observed 

that AN at 10-4 M produced a greater than twofold increase in SCEs in the CHO cells, suggesting 

that the rat hepatocytes metabolized AN to its reactive metabolite, which was then transported 

into the CHO cells. Other cytogenetic findings in CHO cells included positive results for the 

induction of SCEs at 2 mM AN with S9 (Natarajan et al., 1985) and CA at 4 mM AN with or 

without S9, while Douglas et al. (1985) reported that AN at 10-1 M induced the formation of MN. 

AN was reported to induce CAs in Chinese hamster lung (CHL) fibroblasts in culture without 

metabolic activation at nontoxic concentrations of 12.5 μg/mL (Ishidate and Sofuni, 1985). AN 

induced structural CAs in Chinese hamster liver fibroblast cell line (CH1-L) at the lowest 

concentration of 2.5 μg/mL and higher (Danford, 1985). 

Sasaki et al. (1980) found that 0.0053 mg/mL AN induced chromosome breaks in a 

pseudodiploid Chinese hamster cell line (Don-6). AN was negative at concentrations up to 

10 μg/mL for the induction of CAs, SCEs, and polyploidy in cultured epithelial-like cells from 

rat liver (RL4 cell line) (Priston and Dean, 1985; Shell Oil Co., 1984b). Mangir et al. (1991) 

reported that CHO cells treated with AN demonstrated a growth and RNA synthesis rate that is 

similar to that for agents that cause damage to nuclear DNA in cells. Growth and RNA synthesis 

of CHO cells was inhibited with 0.001% (v/v) AN and completely inhibited at 0.005% (v/v) AN. 

 Kodama et al. (1989) conducted cytogenetic analyses on eight spontaneous and eight 

CEO-induced Tks mutant clones in Tk6 human lymphoblastoid cultures that had lost the 14.8 kb 

polymorphic band corresponding to the active Tk allele. These CEO-induced Tk-/- mutants were 

reported in the Recio and Skopek (1988a, b) studies. No chromosomal abnormalities were found 

in the eight spontaneous mutants. On the other hand, a visible abnormality on chromosome 17 

was found in one of the CEO-induced tks mutants and was marked by duplication of the long arm 

of chromosome 17, with break points at q11 and q21. The latter break point was close to the 

Tk locus, suggesting the observed aberration might be associated with Tk-/- phenotype. 

4.5.2.4.4. Transformation assays. Parent and Casto (1979) studied the capacity of AN to 

induce transformations in primary SHE cells in culture by monitoring the incidence of 

microscopically observed foci of morphologically transformed cells. In two experiments, SHE 

cell cultures were exposed to 25–200 μg/mL AN for 18 hours, after which AN was removed and 

cultures were subsequently inoculated with 200 focus-forming units of simian adenovirus SA7 

and incubated for 3 hours. Colonies of surviving cells were counted after 8 days, and virustransformed foci were counted after 21 days. Pretreatment of cells with AN prior to viral 

inoculation resulted in only slight enhancement of 1.8-fold in SA7 foci. In another experiment, 

SHE cells were treated with the same concentrations of AN 5 hours after viral inoculation. This 

resulted in an enhancement ratio that was markedly increased (8.9 at AN concentration of 200 

μg/mL vs. 1.0 in controls). 
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When SHE cells were treated for 6 days with 12–100 μg/mL AN without added 

SA7 virus, foci of morphologically transformed cells were observed at 50 μg/mL AN (two 

foci/six dishes) and 100 μg/mL AN (three foci/nine dishes). 

 The ability of AN to induce transformation in SHE cells was also evaluated by Barrett 

and Lamb (1985). AN was considered to give a positive response according to the criterion of 

inducing four or more transformed colonies per 2,000 surviving colonies. With a relative 

survival of unity, the lowest concentration of AN (0.01 μg/mL) generated morphologically 

transformed colonies at a rate of 4/1,149. 

Lawrence and McGregor (1985) evaluated the ability of 10 potential carcinogens, 

including AN, to induce morphological transformation in cultured embryonic mouse fibroblasts 

(C3H/10T1/2, Clone 8) in the presence or absence of S9. Positive response was obtained at 

16 μg/mL AN in the presence of S9, while responses were uniformly negative in its absence. 

Banerjee and Segal (1986) studied whether AN (0–200 μg/mL) could produce in vitro 

transformation of C3H/10T1/2 and NIH/3T3 mouse fibroblast cells in culture. AN was 

cytotoxic at the higher concentrations, with cell survival dropping below 75% at ≥50 μg/mL in 

C3H/10T1/2 and NIH/3T3 cells. Optimal transformation rates were obtained at AN 

concentrations of 12.5 μg/mL in C3H/10T1/2 cells. AN-induced transformation was observed at 

concentrations between 3 and 100 μg/mL in NIH/3T3 cells. 

Matthews et al. (1985) evaluated whether AN induced morphological transformation and 

mutation to ouabain resistance in Balb/c-3T3 cells in culture with or without exogenous 

metabolic activation. For activation transformation assay, Balb/c-3T3 cells were cocultured with 

lethally X-irradiated primary F344 rat liver cells (RLCs). The RLC-3T3 cocultures were treated 

with 0–25 μg/mL AN for 48 hours. The cocultures were then treated biweekly for 3 weeks with 

0.05 μg/mL 12-O-tetradecenoyl-phorbol-13-acetate beginning 1–2 days after completion of AN 

treatment. For nonactivation transformation assay, 3T3 cell cultures were incubated with 0–

20 μg/mL AN for 72 hours. For RLC-3T3 cocultures, significant increase in relative 

transformation activity was found in coculture treated with 8.8 μg/mL AN (noncytotoxic 

concentration). At 16.7 μg/mL AN, relative cell survival was only 22%, and no significant 

increase in transformation activity was found. No significant increase in transformation activity 

was observed in AN-treated 3T3 cell cultures without RLCs. 

For ouabain resistance (Ouar) mutation assay, 3T3 cell cultures were treated with 0–

150 μg/mL AN with or without S9 mix for 4 and 24 hours, respectively. After the treatment, AN 

was removed and the cultures were refed and maintained for 5–6 days for expression and 

selection, using 2 mM cardiac glycoside ouabain. The appearance of ouabain-resistant (Quar

) 

variants would indicate a mutation arose in the gene controlling the synthesis of cell membrane 

Na+

/K+ ATPase (Corsaro and Migeon, 1978). Significant increase in relative Ouar frequency 

was observed at 50 μg/mL AN with S9 activation. 
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 Yuan and Wong (1991) used a nonfocus transfection-transformation assay to study the 

capacity of the oxidative metabolite CEO to bring about functional changes in a plasmid that 

would be indicative of a compound-induced mutation. A new plasmid that had been constructed 

by ligating a human c-HA-ras-1 protooncogene to a pSV2neo mammalian vector was reacted 

with CEO in vitro and then transfected into NIH3T3 cells. Cells were selected for neomycin 

resistance and/or abnormal growth characteristics, the latter serving to discriminate between 

colonies arising from ras mutations and those from cells that were not transfected (or that were 

transfected with nonplasmid DNA). Although CEO-modified ras gave rise to two neomycin 

resistant clones, they were probably not indicative of a ras mutation because their normal growth 

rate and monolayer density were similar to negative control. Southern blot analysis of 

transformant DNA also supported this conclusion. For example, when anti-benzo(a)pyrene7,8-dihydrodiol-9,10-epoxide transformant DNA was examined in this system as a positive 

control, a fragment of 411 base pairs was revealed, indicating a ras mutation at codon 11 or 12. 

However, both CEO-derived clones and untreated control showed the WT band of 355 base 

pairs. 

4.5.2.4.5. Genotoxicity summary. All identified studies concerning the mutagenicity or 

genotoxicity of AN are compiled in Table 4-53. The overall weight of evidence from in vitro 

and in vivo studies is adequate to support direct mutagenicity for the AN metabolite, CEO. 

Table 4-53. Summary of studies on the mutagenicity/genotoxicity of AN 

Test system Endpoint/effect 

Exposure 

concentration 

Exposure 

duration Resulta Reference

Humans 

AN-exposed workers

n = 30 

DNA strand breaks; 

nondisjunction of sex 

chromosomes in sperm

0.8 mg/m3 2.8 yrs + Xu et al. 

(2003) 

AN-exposed 

workers: 

31 controls, 41 low, 

47 intermediate 

Increase in MN in 

buccal mucosal cells 

(low and intermediate 

groups) and blood 

lymphocytes 

(intermediate group) 

of AN-exposed 

workers. 

Low = 

0.522 mg/m3

Intermediate = 

1.998 mg/m3

Low = 1–

33 yrs 

(average 

15.7 yrs) 

Intermediate = 

1–33 yrs 

(average 

17.2 yrs) 

+ Fan et al. 

(2006) 

AN-exposed 

polymerization 

workers: 

14 Maintenance 

workers: 

10 controls: 20 

CAs in lymphocytes NDb ND Maintenance 

workers: + 

Production 

workers: (+) 

Borba et al. 

(1996) 

AN-exposed 

workers: 47; 

47 controls 

Deletion of 

mitochondrial DNA in 

lymphocytes 

0.11 ppm 17.3 yrs + Ding et al. 

(2003) 
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Table 4-53. Summary of studies on the mutagenicity/genotoxicity of AN 

Test system Endpoint/effect 

Exposure 

concentration 

Exposure 

duration Resulta Reference

AN-exposed workers 

Group 1 = 39 

Group 2 = 22 

Unexposed controls 

= 49 

CAs (detected by 

FISH) in cultured 

lymphocytes from 

peripheral blood 

samples 

Group 1 = 0.05–

0.3 mg/m3

Group 2 = 0.05–

0.7 mg/m3

3 mos (+) 

Significant 

increase in the 

number of 

reciprocal 

translocations and 

relative number of 

insertions. 

Increase in 

frequency of 

aberrant cells not 

significant. 

Beskid et al. 

(2006) 

AN-exposed workers 

(n = 45) 

Matched controls = 

23, unexposed 

controls = 33 

CAs in cultured 

lymphocytes in 

peripheral blood 

samples 

0.05–0.3 mg/m3 3 mos – Srám et al. 

(2004) 

AN-exposed workers 

(n = 18); 

controls = 18 

CAs in lymphocytes 5 ppm, reduced 

to 1.5 ppm 

between 1975 

and 1977 

(possible 

exposure to other 

chemicals) 

15.3 yrs – Thiess and 

Fleig (1978) 

Rats 

Sprague-Dawley 

(male) (4/group) 

MN 125 mg/kg i.v. Two 

treatments 

Bone marrow: + 

Peripheral blood: 

– 

Wakata et al. 

(1998) 

MN in bone marrow 10–40 mg/kg oral Single dose – Morita et al. 

(1997) 

Sprague-Dawley 

(male) 

MN in peripheral 

blood 

24.5–98 mg/kg 

i.v. 

Single dose – Morita et al. 

(1997) 

Sprague-Dawley 

(male) n = 3 

CAs in bone marrow 40 mg/kg oral 16 d – Rabello-Gay 

and Ahmed 

(1980) 

Sprague-Dawley 

(male) n = 3–4/group

Binding to DNA in 

stomach, brain, and 

liver 

46.5 mg/kg oral Single dose + Farooqui and 

Ahmed (1983a)

Sprague-Dawley 

n = 4/group 

Binding to testicular 

DNA 

46.5 mg/kg oral Single dose + Ahmed et al. 

(1992a) 

Sprague-Dawley 

(male) n = 4/group 

Binding to lung DNA 46.5 mg/kg oral Single dose + Ahmed et al. 

(1992b) 

Sprague-Dawley 

(male) n = 3/group 

Binding to gastric 

tissue DNA 

46.5 mg/kg oral Single dose + Abdel-Rahman 

et al. (1994b) 

Wistar (male) Alkylation of hepatic 

DNA 

0.2 mmol i.p. Single dose + Peter et al. 

(1983a) 

F344 

n = 1 

Binding to liver and 

brain DNA 

0.6 mg/kg CEO 

i.p. 

Single dose – Hogy and 

Guengerich 

(1986) 
242 DRAFT - DO NOT CITE OR QUOTE 

Table 4-53. Summary of studies on the mutagenicity/genotoxicity of AN 

Test system Endpoint/effect 

Exposure 

concentration 

Exposure 

duration Resulta Reference

F344 

n = 3 

DNA adduct formation 50 mg /kg AN 

i.p. or 6 mg/kg 

CEO i.p. 

Single dose Liver: + 

Brain: (+) 

Hogy (1986); 

Hogy and 

Guengerich 

(1986) 

Wistar DNA damage in 

forestomach, colon, 

kidney, bladder, and 

lung but not in brain or 

bone marrow 

30 mg/kg i.p. Single dose + Sekihashi et al. 

(2002) 

Wistar, male Fragmentation of brain 

DNA 

100 ppm AN in 

drinking water 

14 or 28 d + Mahalakshmi 

et al. (2003) 

F344 

n = 12/group 

UDS in liver but not 

brain 

50 mg/kg gavage Single dose + Hogy and 

Guengerich 

(1986) 

UDS in lung 46.5 mg/kg oral Single dose Ahmed et al. 

(1992a) 

UDS in gastric tissue 46.5 mg/kg oral Single dose Abdel-Rahman 

et al. (1994a) 

Sprague-Dawley 

UDS in testis 46.5 mg/kg oral Single dose 

+ 

Ahmed et al. 

(1992b) 

F344 UDS in isolated 

hepatocytes or 

spermatocytes 

a. 75 mg/kg 

b. 60 mg/kg oral 

a. Single dose 

b. five daily 

doses 

– Butterworth et 

al. (1992) 

F344 

n = 50 

Dominant lethal 

mutations 

60 mg/kg 5 d – Working et al. 

(1987) 

Mice 

ddY DNA damage in 

forestomach, colon, 

bladder, lung, and 

brain 

20 mg/kg i.p. Single dose + Sekihashi et al. 

(2002) 

C57B1/6 

n = 1–4/group 

SCEs in bone marrow 10–45 mg/kg Single dose (+) positive at 

toxic dose of 

45 mg/kg 

Sharief et al. 

(1986) 

Swiss SCEs in bone marrow 7.5 or 10 mg/kg 

i.p. 

Single dose + Fahmy (1999) 

 CAs in spermatocytes, 

bone marrow, and 

spleen cells 

a. 15.5 or 

31 mg/kg oral 

b. 7.75 mg/kg 

a. Single dose 

b. three or five 

doses 

+ Fahmy (1999) 

Swiss 

n = 3–6/group 

CAs in bone marrow 7, 14, or 

21 mg/kg-d oral 

or 10, 15, or 

20 mg/kg-d i.p. 

4, 15, or 30 d – Rabello-Gay 

and Ahmed 

(1980) 

NMRI male 

n = 4/group 

CAs in bone marrow 20 or 30 mg/kg 

i.p. 

Single dose – Leonard et al. 

(1981) 

C57B1/6 

n = 1–4/group 

CAs in bone marrow 10–45 mg/kg Single dose – Sharief et al. 

(1986) 

NMRI male 

n = 4–5/group 

MN in erythrocytes 20 or 30 mg/kg 

i.p. 

Single dose – Leonard et al. 

(1981) 
243 DRAFT - DO NOT CITE OR QUOTE 

Table 4-53. Summary of studies on the mutagenicity/genotoxicity of AN 

Test system Endpoint/effect 

Exposure 

concentration 

Exposure 

duration Resulta Reference

CD-1 MN in bone marrow 0–45 mg/kg i.p. 

0–32 mg/kg oral 

0–40 mg/kg i.v. 

Single dose i.p.: (+) 

oral and i.v.: – 

Morita et al. 

(1997) 

CD-1 MN in peripheral 

blood 

5.6–45 mg/kg i.p. 

or 10–40 mg/kg 

i.v. 

Single dose – Morita et al. 

(1997) 

ICR CAs in bone marrow 

cells and 

spermatogonia 

100 or 20 mg/m35 d – Zhurkov et al. 

(1983) 

NMR1 

n = 5/group 

Dominant lethal 

mutation 

30 mg/kg i.p. Single dose – Leonard et al. 

(1981) 

Short-term assays—bacteria (–S9 / +S9) 

S. typhimurium

TA 1535 

Gene reversion (His+

revertant) 

5–20 μL AN 

solution 

0.5 h –/+ Milvy and 

Wolff (1977) 

TA 1535 Gene reversion 2–300 μL AN 

vapor 

0.5–4 h –/+ Milvy and 

Wolff (1977) 

TA 1538 Gene reversion 200 μL AN vapor 2 h –/+ Milvy and 

Wolff (1977) 

TA 1978 Gene reversion 5–10 μL AN 

solution 

0.5 h –/+ Milvy and 

Wolff (1977) 

TA 1535 Gene reversion 100–1,000 μg 

AN plate 

incorporation 

assay 

ND –/+ Lijinsky and 

Andrews 

(1980) 

TA 1537, 1538, 98, 

100 

Gene reversion Plate 

incorporation 

assay 

ND –/– Lijinsky and 

Andrews 

(1980) 

TA 1535 Gene reversion 0.1–

1,000 μg/dish 

ND –/+ Zhurkov et al. 

(1983) 

TA 1538 Gene reversion 0.1–

10,000 μg/dish 

ND –/– Zhurkov et al. 

(1983) 

TA 97, 98, 100 Gene reversion 50–750 μg/mL 

plate 

incorporation 

assay 

48 h –/– Brams et al. 

(1987) 

TA 102 Gene reversion Up to 

5,000 μg/plate 

ND –/– Jung et al. 

(1992) 

TA 98, 100, 1535, 

1537, 1538 

Gene reversion 0.1–5,000 μg/ 

plate 

2 d –/– Dow Chemical 

Co. (1977) 

TA 1530, 1535, 

1950, 1538, 100, 98, 

1978 

Gene reversion 0.2% AN vapor 

(200 μg/plate) 

1 h –/+ (weaker 

response with 

TA 100, 98, and 

1978) 

de Meester et 

al. (1978); 

Dow Chemical 

Co. (1976) 

TA 98, 100 Gene reversion ND, plate 

incorporation 

assay 

ND +/+ Khudoley et al. 

(1987) 

TA 100 Gene reversion 806–12,100 μg/ 

plate 

48 h –/(+) Hakura et al. 

(2005) 
244 DRAFT - DO NOT CITE OR QUOTE 

Table 4-53. Summary of studies on the mutagenicity/genotoxicity of AN 

Test system Endpoint/effect 

Exposure 

concentration 

Exposure 

duration Resulta Reference

TA 1535/pSK1002 umu gene expression 

(increased 

β-galactosidase 

activity)

ND, 0.1 mL AN 

in 2.5 mL culture 

medium 

2 h –/– Nakamura et 

al. (1987) 

TA 1530 Gene reversion 0.1 mL 24-hr 

urine from rats 

and mice treated 

with a single dose 

30 mg/kg AN i.p. 

(plate 

incorporation 

assay) 

48 h + LambotteVandepaer et 

al. (1985, 1981, 

1980) 

E. coli WP2 series Gene reversion 

(trp– → trp+

) 

75 or 150 μmol/ 

plate 

2–3 d +c Venitt et al. 

(1977) 

E. coli PQ37 SOS chromotest ND 2 h –/– Brams et al. 

(1987) 

Short-term assays—fungi 

S. cerevisiae JD1 Mitotic gene 

conversion 

250 or 

500 μg/mL 

18 h 

–/+ 

Brooks et al. 

(1985); Shell 

Oil Co. (1984a)

S. cerevisiae D61.M Chromosome loss 0.8 or 

1.36 mg/mL 

16 h –/– Whittaker et al. 

(1990) 

Short-term assays—fruit fly 

Adult female 

Drosophila ZESTE 

system 

Sex chromosome loss Inhalation 

exposure to 

2.7 ppm AN 

50 min or 

70 min 

+ Osgood et al. 

(1991) 

Mosaic eye in 

hatching females 

Somatic recombination 

and mutation 

Treatment of 

larvae with 5–

20 mM AN 

Single dose, 

incubate for 

9–11 d 

(+) Vogel (1985) 

Germ cells of male 

D. melanogaster

Sex-linked recessive 

lethal 

Feeding: 

420 ppm or 

injection: 

3,500 ppm 

Feeding: 3 d – Foureman et al. 

(1994) 

Wing spots of 

Drosophila

(mwh+/+flr +/mei-9)

Somatic mutation and 

recombination 

Gas exposure of 

larvae to 0.5–

1 μL/1,150 mL 

0.5 or 1 h (+) Würgler et al. 

(1985) 

D. melanogaster

ZESTE (inhibition of 

taxol-purified 

microtubule 

assembly in vitro) 

Aneuploidy 5 mM Microtubule 

assembly 

monitored for 

80 min 

+ Sehgal et al. 

(1990) 

Other short-term assays 

Supercoiled plasmid 

DNA pBR322 

CEO induced DNA 

strand breaks 

50 mM CEO 

incubated with 

1.1 μg 

supercoiled 

pBR322 plasmid 

DNA 

3 h + Yates et al. 

(1994) 
245 DRAFT - DO NOT CITE OR QUOTE 

Table 4-53. Summary of studies on the mutagenicity/genotoxicity of AN 

Test system Endpoint/effect 

Exposure 

concentration 

Exposure 

duration Resulta Reference

SV40 phage DNA CEO induced DNA 

strand breaks, but not 

AN 

1 mM CEO 

incubated with 

5,000 dpm 

[

3H]-thymidine 

labelled SV–40 

phage DNA 

17 h + Peter et al. 

(1983b) 

In vitro mammalian cell assays 

Gene-locus mutations 

at the Tk (thymidine 

kinase) locus (Tk+/–→

Tk–/–) 

40 μg/mL AN 3 h –/+ Crespi et al. 

(1985) 

Mutation at Tk locus 1.4 mM AN 2 h –/+ Recio and 

Skopek (1988a, 

b) 

Mutation at Tk locus 100 μM and 

150 μM CEO 

2 h + Recio and 

Skopek (1988a, 

b) 

Abnormality at 

chromosome 17 in 1 of 

8 CEO-induced tks

mutant clones 

NAb

 NA + Kodama et al. 

(1989) 

Human lymphoblasts 

Tk6 

CEO-induced 

mutations at the hprt 

locus 

NA NA + Recio and 

Skopek 

(1988a) 

Human lymphoblasts 

AHH-1 

Gene-locus mutations 

at the hypoxanthine 

guanine 

phosphoribosyl 

transferase locus 

25 μg/mL AN 28 h + Crespi et al. 

(1985) 

Mutation at Tk+/– locus 30 and 40 μg/mL 

AN 

ND + Oberly et al. 

(1996) 

Mutation at Tk+/– locus 10–40 μg/mL AN 4 h +/+ Rudd (1983) 

Mutation to ouabain or 

6-TG resistance 

12.5–200 μg/mL 

AN 

2 h +/+ Garner and 

Campbell 

(1985) 

Induction of Tk–/–

mutants

80–225 μg/mL 

AN 

2 h +/+ Lee and 

Webber (1985)

Induction of Tk–/–

mutants

30 nL/mL AN 4 h +/+ Myhr et al. 

(1985) 

L5178Y mouse 

lymphoma cells 

Induction of Tk–/–

mutants

5–69 μg/mL AN 3 h +/+ Amacher and 

Turner (1985) 

L5178Y Tk+/+ Mutation to ouabain 

resistance (Na+/K+

ATPase locus) 

12.5–100 μg/mL 

AN 

2 h – Styles et al. 

(1985) 

L5178Y Tk+/– Mutation to 

trifluorothymidine 

resistance 

12.5–100 μg/mL 

AN 

2 h – Styles et al. 

(1985) 
246 DRAFT - DO NOT CITE OR QUOTE 

Table 4-53. Summary of studies on the mutagenicity/genotoxicity of AN 

Test system Endpoint/effect 

Exposure 

concentration 

Exposure 

duration Resulta Reference

P388F mouse 

lymphoma tk+/–

Mutation to 5-iodo2-deoxyuridine 

resistance 

80–160 μg/mL 

AN 

24–48 h –/+ Anderson and 

Cross (1985) 

V79/hprt Induction of 

8-azaguanine 

resistance 

50–200 μg/mL 

AN 

2 h –/– Lee and 

Webber (1985)

HeLa cells UDS 2.5 mg/mL AN 2.5 h –/– Martin and 

Campbell 

(1985) 

Human lymphocytes UDS 5 × 10-1 M 4 h –/+ Perocco et al. 

(1982) 

Primary cultures of 

F344 rat hepatocytes 

UDS 0.026–53 μg/mL 

AN 

20 h – Probst and Hill 

(1985) 

Primary cultures of 

F344 rat hepatocytes 

UDS 10-1–102μg/mL 

AN 

18–20 h – Williams et al. 

(1985) 

Primary F344 rat 

hepatocyte 

UDS 0.01–1 mM AN 17–19 h – Butterworth et 

al. (1992) 

Primary F344 rat 

hepatocyte 

UDS 0.01–0.1 mM 

CEO 

17–19 h – Butterworth et 

al. (1992) 

Human mammary 

epithelial cell 

UDS 0.1 mM CEO 24 h + Butterworth et 

al. (1992) 

Human bronchial 

epithelial cells 

DNA single-strand 

breaks 

200 and 

500 μg/mL AN 

20 h + Chang et al. 

(1990) 

Rat hepatocytes DNA single-strand 

breaks 

65.8 μg/mL AN 3 h + Bradley (1985)

CHO cells DNA single-strand 

breaks 

7 × 10-2– 

1 × 10-1 M AN 

1 h +/+ Douglas et al. 

(1985) 

CHO cells DNA single-strand 

breaks 

ND ND –/– Lakhanisky 

and Hendrickx 

(1985) 

SHE cells DNA single-strand 

breaks 

200 or 

400 μg/mL AN 

18 h + Parent and 

Castro (1979) 

Human bronchial 

epithelial cells 

SCEs 150 and 

300 μg/mL AN 

20 h + Chang et al. 

(1990) 

Human lymphocytes SCEs 5 × 10-4 M 1 h –/+ Perocco et al. 

(1982) 

CHO cells SCEs 10-7–10-4 M AN 3 h –d Ved Brat and 

Williams 

(1982) 

CHO cells cocultured 

with freshly isolated 

rat hepatocytes 

SCEs 10-4 M AN 3 h +d

 Ved Brat and 

Williams 

(1982) 

CHO cells SCEs 2 mM AN 1 h –/+ Natarajan et al. 

(1985) 

CHO cells CAs 4 mM AN 1 h +/+ Natarajan et al. 

(1985) 

CHL fibroblast CAs 12.5 μg/mL AN 24 and 48 h +d Ishidate and 

Sofuni (1985) 
247 DRAFT - DO NOT CITE OR QUOTE 

Table 4-53. Summary of studies on the mutagenicity/genotoxicity of AN 

Test system Endpoint/effect 

Exposure 

concentration 

Exposure 

duration Resulta Reference

CH1-L liver 

fibroblast 

CAs 2.5 μg/mL AN 36 h + Danford (1985)

Chinese hamster cell 

line Don-6 

CAs 1 × 10-4 M or 

0.0053 mg/mL 

26–30 h + Sasaki et al. 

(1980) 

CHO cells MN 10-1 M AN 1 h +/+ Douglas et al. 

(1985) 

Rat liver (RL4) cells CAs, polyploidy, 

SCEs 

1.25, 2.5, 5.0, or 

10 μg/mL AN 

2 h –d Priston and 

Dean (1985); 

Shell Oil Co. 

(1984b) 

CHO cells Inhibition of cell 

growth and RNA 

synthesis 

0.001, 0.002, and 

0.005% (v/v) AN

8 d +d Mangir et al. 

(1991) 

In vitro mammalian cell transformation 

SHE cells Cell transformation 50 or 100 μg/mL 

AN 

6 d + Parent and 

Castro (1979) 

SHE cells Enhancement of viral 

transformation 

100 or 

200 μg/mL AN 

18 hrs before 

SA7 or 5 hrs 

after SA7 

inoculation 

+ Parent and 

Castro (1979) 

SHE cells Cell transformation 0.01–1 μg/mL 

AN 

7 d + Barett and 

Lamb (1985) 

Mouse fibroblasts 

NIH/3T3 cells 

Cell transformation 12.5–200 μg/mL 

AN 

48 h + Banerjee and 

Segal (1986) 

Mouse fibroblasts 

C3H/10T1/2 cells 

Cell transformation 3–100 μg/mL AN 48 h + Banerjee and 

Segal (1986) 

Mouse fibroblasts 

C3H/10T1/2 cells 

Cell transformation 16 μg/mL AN 24 h –/(+) Lawrence and 

McGregor 

(1985) 

Balb/c-3T3 cells Cell transformation 8.8 μg/mL AN 48 h –/+e Matthews et al. 

(1985) 

Balb/c-3T3 cells Ouabain-resistant 

mutants 

50 μg/mL AN 24 h –/+ Matthews et al. 

(1985) 

NIH 3T3 cells Cell transformation 

after transfection with 

CEO modified ras

DNA 

NA 14 h – Yuan and 

Wong (1991) 

aNA = not applicable; ND = not determined. 

b

+ = Positive;– = negative; (+) = borderline positive. 

c

S9 activation not needed. 

d

S9 not included in the assay. 

eWith or without coculture with lethally X-irradiated primary F344 RLCs. 

 In vitro evidence indicates that AN can be directly mutagenic, most likely through the 

formation of CEO-DNA adducts. In short-term tests with bacteria, AN induced mutations in a 

majority of test systems, most often requiring exogenous metabolic activation (Table 4-53). In 
248 DRAFT - DO NOT CITE OR QUOTE 

mouse lymphoma cell assays, AN induced mutations at the Tk locus in most assays (Table 4-53). 

In human lymphoblast Tk6 cells devoid of CYP450 activity, AN induced multiple mutations at 

the Tk locus only in the presence of metabolic activation (Recio and Skopek, 1988a, b; Crespi et 

al., 1985). CEO was mutagenic in Tk6 cells at 10-fold lower concentrations than AN itself and 

was as mutagenic in this test system as the well-known mutagen, ethyl methanesulfonate (Recio 

and Skopek, 1988a, b). CEO also induced multiple mutations at the hprt locus in Tk6 cells 

(Recio and Skopek, 1988a). CEO induced UDS in cultured human mammary epithelial cells but 

not in cultured rat hepatocytes (Butterworth, 1992). 

 Supporting evidence for the direct mutagenicity of AN and its metabolites comes from in 

vivo studies (Table 4-53). Increases in the occurrence of MN in buccal mucosal cells and blood 

lymphocytes were recently reported in AN exposed workers in China (Fan et al., 2006). Three 

studies of AN workers reported genotoxic effects such as DNA strand breaks, nondisjunction of 

sex chromosomes, and CAs (Beskid et al., 2006; Xu et al., 2003; Borba et al., 1996), whereas an 

earlier study did not find elevated frequency of CAs in exposed workers (Thiess and Fleig, 

1978). Increases in cytogenetic aberrations such as MN were found in assays of exposed rats 

(Wakata et al., 1998) and a single assay of mice (Fahmy, 1999), but were not evident in other rat 

and mouse assays (Morita et al., 1997; Zhurkov et al., 1983; Leonard et al., 1981; Rabello-Gay 

and Ahmed, 1980). Comet assays found DNA damage in forestomach, colon, bladder, lung, and 

brain in mice, following single i.p. injections of 20 mg/kg AN, and in forestomach, colon, 

kidney, bladder, and lung of rats injected with 30 mg/kg (Sekihashi et al., 2002). 

 UDS was detected by following the time course of 3H-thymidine incorporation into DNA 

in lung, testis, and gastric tissue, following administration of single oral doses of 46.5 mg/kg AN 

to Sprague-Dawley rats (Ahmed et al., 1996b, 1992a, b; Abdel-Rahman et al., 1994a). 

Autoradiographic techniques did not detect UDS following incubation of primary cultures of 

hepatocytes or spermatocytes from F344 rats given single oral doses of 75 mg/kg or five daily 

doses of 60 mg/kg-day AN (Butterworth et al., 1992). Dominant lethal effects (from mutations 

in germ cells) were not found in mice given single i.p. doses of 30 mg/kg AN (Leonard et al., 

1981) or rats given five oral doses of 60 mg/kg (Working et al., 1987). DNA binding by AN or 

its metabolites was indicated by elevated levels of radioactivity in DNA from several tissues in 

rats given single oral doses of 46.5 mg/kg radiolabeled AN (Abdel-Rahman et al., 1994b; Ahmed 

et al., 1992a, b; Farooqui and Ahmed, 1983a). 

 In the European Union Risk Assessment Report on Acrylonitrile (EC 2004), AN was 

regarded as “genotoxic or at least mutagenic, despite the recent publication of Whysner et al. 

(1998a) which argues for a possible nongenotoxic mechanism for the tumour induction in 

experimental animals.” 

4.5.2.5. Indirect Genotoxicity 

As discussed in Section 4.5.1.2.2, studies are available that investigated the indirect 
249 DRAFT - DO NOT CITE OR QUOTE 

genotoxicity of AN resulting from oxidative stress. These studies measured 8-oxodG levels in 

DNA as biomarkers of oxidative DNA damage from AN exposure. 8-OxodG is mutagenic 

(Kamiat et al., 1992; Moriya et al., 1991; Wood et al., 1990) and causes GC → TA transversions 

during DNA replication. 

In vitro studies 

 Zhang et al. (2000) studied AN-induced morphological transformation in SHE cells. 

SHE cell culture was treated in vitro for up to 7 days with 0–75 μg/mL AN in 12.5 μg/mL 

increments (75 μg/mL was cytotoxic, with 50% reduction in cell colony number). After 7 days 

of exposure, there was a dose-dependent increase in morphological transformation at 50, 62.5, 

and 75 μg/mL, reaching a transformation frequency of 1.3% at 75 μg/mL. After a 24-hour AN 

exposure, an increase in transformation was not observed at all concentrations. Levels of 

8-oxodG in DNA isolated from cells incubated with 75 μg/mL were increased to 192 and 186% 

of control after 2 and 3 days, indicating an association between cell transformation and oxidative 

DNA damage. However, no increase in 8-oxodG was observed after 1 or 7 days. AN-induced 

morphological transformation was inhibited by cotreatment with the antioxidants α-tocopherol 

(100 μM: up to 65% inhibition) and (-)-epigallocathechin-3-gallate (5 μM: up to 87% 

inhibition) for 7 days. Cotreatment with antioxidants also inhibited the formation of 8-oxodG in 

SHE cell DNA from treatment with 75 μg/mL AN. 

 In a later study by the same research group, Zhang et al. (2002) investigated the time 

course of SHE cell morphological transformation in the presence of 75 μg/mL AN. The results 

indicated that statistically significant increases in morphological transformation frequency could 

not be observed until after 2 consecutive days of exposure; a plateau at a transformation 

frequency of about 2% was reached after 4–5 days of exposure. In another experiment, 

coadministration of 0.5 mmol/L ABT, a nonspecific suicidal CYP450 inhibitor, for 7 days 

significantly reduced the rate of cell transformation from about 1.25% to about 0.3% (shown 

graphically), demonstrating the need for metabolic activation of AN in this test system. 

 Zhang et al. (2002) also showed that AN (25, 50, and 75 μg/mL) increased the amount of 

ROS (measured by 2,3-dihydroxybenzoic acid production) in the SHE cells after 4, 24, and 

48 hours of treatment. At the same time, xanthine oxidase (which generates the superoxide 

radical and hydrogen peroxide via oxidation of hypoxanthine or xanthine by oxygen) activity 

was increased by 47% in SHE cells after 24 hours of treatment with 75 μg/mL AN. After 

48 hours of treatment, xanthine oxidase activity was increased in both 50 and 75 μg/mL (80%) 

AN groups. This increase in xanthine oxidase activity was blocked by cotreatment with 0.5 mM 

ABT. On the other hand, antioxidant GSH was depleted 66–80% by all doses of AN (25, 50, and 

75 μg/mL) after 4 hours of treatment and returned to control levels after 24 hours. At 48 hours, a 

significant increase in GSH was observed with the 75 μg/mL group but not in other dose groups. 

Antioxidant enzyme catalase activity was significantly decreased after 4 hours of treatment with 
250 DRAFT - DO NOT CITE OR QUOTE 

50 and 75 μg/mL AN but increased after 24 and 48 hours of treatment. Cotreatment with ABT 

prevented the decrease and increase in activity of catalase at 4 and 24 hours after treatment, 

respectively. A transient decrease in SOD activity was also observed after 4 hours of treatment 

with 75 μg/mL AN. 

 The effect of AN on catalase and SOD activities was also studied in a cell-free system 

(Zhang et al., 2002). Catalase and SOD activities were determined in samples containing 

purified catalase or SOD incubated with 75 μg/mL AN in the presence or absence of SHE cell 

homogenate. In the absence of a metabolic source of SHE cell homogenate, no inhibition of 

catalase activity was seen following incubation up to 60 minutes with AN. In the presence of 

SHE cell homogenate, AN significantly decreased catalase activity in a time-dependent manner 

after 10 minutes of incubation. Similarly, a significant time-dependent decrease in SOD activity 

was observed following 30 minutes incubation with AN. The study authors concluded that 

morphological transformation of SHE cells is caused by oxidative stress as a result of oxidative 

metabolism of AN. 

 Kamendulis et al. (1999a) also investigated oxidative DNA damage induced by AN in 

DITNC1, a rat glial astrocyte cell line, and primary rat hepatocytes exposed to AN in vitro (see 

Section 4.5.1.2.2). AN was cytotoxic at concentrations ≥2.5 mmol/L (133 μg/mL) (as measured 

by the release of LDH from the cells) to both cell lines, following ≥4 hours of exposure. 

Concentrations of 0.01, 0.1, and 1.0 mmol/L AN (0.53, 5.3, and 53 μg/mL, respectively) caused 

a dose-dependent increase in formation of 8-oxodG in astrocytes but not in hepatocytes. 

Corresponding increases in ROS formation were also observed in astrocytes only. However, no 

oxidative lipid damage (as evaluated by formation of MDA, a product of lipid peroxidation) was 

found in either cell type following treatment with AN at all exposure concentrations or durations. 

The formation of 8-oxodG in rat astrocytes was reversible. Following treatment with AN for 

24 hours and removal of AN for 24 hours afterwards, 8-oxodG levels returned to control values 

in all concentrations examined. Kamendulis et al. (1999a) concluded that this demonstrated 

property was consistent with tumor promoting agents. 

 Pu et al. (2006) investigated oxidative DNA damage induced by AN in D1TNC1 rat 

astrocyte cell line using the fpg-modified comet assay. Increase in oxidative DNA damage was 

observed in astrocytes treated with 1 mM AN for 24 h. No increase in oxidative DNA damage 

was observed in astrocytes treated with 0.005 – 0.75 mM AN for 24 hours. 

 Jacob and Ahmed (2003b) investigated oxidative stress in cultured NHA (4631) treated 

with up to 400 μM AN for 12 hours. AN was cytotoxic at concentrations >50 μM. Cell viability 

was 85, 78, and 58%, respectively, at AN concentrations of 100, 200, and 400 μM. Significant 

increases in measures of oxidative stress were observed at cytotoxic concentrations of 200–400 

μM AN: the production of ROS was increased four- to sevenfold, whereas 8-oxodG levels were 

increased more than twofold. 
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 Esmat et al. (2007) investigated cytoxicity in rat (strain not known) primary glial cells 

exposed to 0–5.0 mM AN up to 12 hours. Cell membrane integrity was evaluated by trypan blue 

exclusion and LDH leakage. About 50% membrane damage in primary glial cells was observed 

in incubations containing 1.0 mM AN for 3 hours. Thus, subsequent studies on AN-induced 

oxidative stress were performed using 1 mM AN for 3 hours incubation. AN increased MDA 

levels (indicator of lipid peroxidation) to about ninefold compared with control incubations and 

depleted GSH level to about 7% of controls., while no change in total glutathione level was 

observed. AN induced CN– formation by glial cells and decreased ATP level by about 90% as 

compared with the control. Pretreatment with 5 mM NAC (an acetylated precursor of cysteine 

and GSH, and an antioxidant), reduced MDA level by 40% as compared with glial cells treated 

with AN alone and raised GSH and total glutathione level in cell extract to about 2.5-fold of 

control and AN alone treated group. Pretreatment with NAC also caused reduction of CN–

induced by AN to about 15% as compared wth the AN alone treated group, and raised ATP level 

to about sixfold, as compared with the AN alone treated group. 

 It should be noted that NAC stimulated GSH synthesis, enhanced glutathione-Stransferase activity, and was a powerful nucleophile capable of scavenging free radicals (De 

Vries and De Flora, 1993). Observed increases in GSH and total glutathione and decrease in CNformation with NAC pretreatment in Esmat et al. (2007) would suggest that most of the 

administered AN could be detoxified via conjugation via the GSH pathway (consistent with 

findings by Carerra et al., 2007), as less AN was available for oxidation to CN-

. Esmat et al. 

(2007) concluded that AN toxicity was at least partly mediated by oxidative stress. 

In vivo studies 

As described in Section 4.5.1.2.2, Jiang et al. (1998) reported increases in measures of 

oxidative stress in the brain cortices but not the livers of male Sprague-Dawley rats exposed to 

AN in drinking water at concentrations of 50–200 ppm for up to 90 days. Increases in ROS and 

oxidative DNA damage (increased levels of 8-oxodG) and concomitant decreases in antioxidant 

enzymes (catalase, SOD) were observed in the brain cortices of exposed rats. Transient small 

decreases in the antioxidants vitamin E and glutathione were also observed in the brain cortices 

of AN-exposed rats only at 14 days. A transient increase in MDA level was observed only at the 

highest dose group after 14 days but not at other time points. 

Pu et al. (2009) reported oxidative DNA damage in WBC and brain of male SpragueDawley rats treated with 100-200 ppm AN; however, EPA has identified issues with this study 

(see Section 4.5.1.2.2). 

 In another study, Whysner et al. (1998a) examined the ability of AN to induce oxidative 

DNA damage in the brain, liver, and forestomach of rats by exposing male Sprague-Dawley and 

F344 rats up to 300 ppm AN in drinking water for 21 days (see Section 4.5.1.2.2). As shown in 

Table 4-54, elevated levels of 8-oxodG were found in DNA from the brain and liver of Sprague-
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Dawley rats. However, 8-oxodG levels in the forestomach of exposed Sprague-Dawley rats and 

the brain of exposed F344 rats were not statistically significantly elevated compared with 

controls. Significant increase in 8-oxodG levels was found in the liver of exposed SpragueDawley rats, although the liver is not a target organ for carcinogenicity in adult rats. 

Table 4-54. Formation of 8-oxodG in DNA from tissues of male SpragueDawley and F344 rats exposed to AN in drinking water for 21 days 

Formation of 8-oxodG (mol/105 mol dG)

Sprague-Dawley rats F344 rats

Dose group Liver Forestomach Brain Brain

Control 0.67 ± 0.22 0.68 ± 0.14 0.62 ± 0.08 0.79 ± 0.37 

3 ppm 0.72 ± 0.06 1.77 ± 0.55 0.86 ± 0.41 1.07 ± 0.41 

30 ppm 0.95 ± 0.19a 1.59 ± 0.30 1.35 ± 0.49a 1.03 ± 0.38 

300 ppm 0.96 ± 0.15a 1.44 ± 1.22 1.29 ± 0.10a 1.06 ± 0.48b

a

Significantly different from controls (p < 0.05) as calculated by the study authors. 

bExposure was at 100 ppm. 

Source: Whysner et al. (1998a). 

 Whysner et al. (1998a) also exposed male Sprague-Dawley rats to 100 ppm AN in 

drinking water for up to 94 days. (This dose was carcinogenic in Sprague-Dawley rats in a 

chronic study [Johannsen and Levinskas, 2002a; Biodynamics, 1980b].) The rats were divided 

into four groups and were exposed to distilled water, 100 ppm AN, 5 mg MNU (a DNA-reactive 

carcinogen that produces glial cell tumors in rats) per week, or 100 ppm AN plus 5 mg MNU per 

week. Levels of 8-oxodG in brain and liver of rats exposed to 100 ppm AN were significantly 

greater than those in controls after 10 days (1.31 ± 0.52 in brains of exposed rats vs. 0.65 ± 

0.22 mol per 105

 mol dG in controls and 0.70 ± 0.20 in livers of exposed rats vs. 0.49 ± 0.10 mol 

per 105 mol dG in controls). Administration of 5 mg/kg MNU alone did not increase the level of 

8-oxodG in the brain of treated rats but increased 8-oxodG in the liver after 10 days. However, 

coadministration of 100 ppm AN and MNU increased 8-oxodG level in the brain after 31 days 

and 94 days when compared with the MNU-only group. 

Whysner et al. (1998a) suggested that AN-induced tumors may be produced by a mode of 

action involving 8-oxodG. However, several findings in this study did not support this proposed 

mode of action. First, no significant increase in 8-oxodG levels were found in the brain DNA of 

F344 rats exposed to AN in the 21-day study whereas AN was carcinogenic to F344 rats in a 

chronic drinking water study (Johannsen and Levinskas, 2002b). Second, although a significant 

increase in 8-oxodG levels was found in the brain DNA of Sprague-Dawley rats exposed to AN 

for 21 days, no dose-dependent increase was observed above 30 ppm, which was not the dose 

producing the highest occurrence of tumors in the chronic bioassay. Third, no increase in 
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8-oxodG levels were found in the forestomach DNA of exposed rats. The forestomach was a 

target organ for AN carcinogenicity. Finally, increase in 8-oxodG levels was found in liver 

DNA of exposed rats. Liver was not a target organ for AN carcinogenicity in adult rats. 

Therefore, there was no association between 8-oxodG levels and tumorigenicity in target organs. 

 Results of indirect mutagenicity/genotoxicity studies of AN are summarized in 

Table 4-55. 
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Table 4-55. Summary of studies on the indirect mutagenicity or genotoxicity 

of AN 

Test system Endpoint/effect 

Exposure 

concentration 

Exposure 

duration Result Reference 

In vitro mammalian cell assays 

SHE cells Cell 

transformation 

50–75 μg/mL AN 7 d + Zhang et al. 

(2000) 

SHE cells 8-oxodG in DNA 75 μg/mL AN Increased after 

2 and 3 d but not 

after 1 or 7 d 

(+) Zhang et al. 

(2000)

SHE cells ROS 25–75 μg/mL AN 4–48 h + Zhang et al. 

(2002) 

DITNC1rat glial 

astrocytes 

8-oxodG in DNA 0.01–1 mM AN 

(0.53–53 μg/mL) 

4 or 24 h +a Kamendulis et al. 

(1999a) 

D1TNC1 rat 

astrocytes 

DNA damage in 

fpg-comet assay 

1 mM 24 h + Pu et al. (2006) 

Rat hepatocytes 8-oxodG in DNA 0.01–1 mM AN 4 or 24 h – Kamendulis et al. 

(1999a) 

NHAs 8-oxodG in DNA 200–400 μM AN 12 h + Jacob and Ahmed 

(2003b) 

NHAs ROS 200–400 μM AN 12 h + Jacob and Ahmed 

(2003b) 

In vivo studies in rats 

Male SpragueDawley rats 8-oxodG in brain 

cortex DNA 

0–200 ppm AN in 

drinking water

100 and 200 ppm: 

+ after 14–90 d 

50 ppm: + after 

28 and 90 d 

+ Jiang et al. (1998)

Male SpragueDawley rats 8-oxodG in liver 

DNA 

0–200 ppm AN in 

drinking water 

14–90 d – Jiang et al. (1998)

Male SpragueDawley rats 8-oxodG in WBC 

and brain DNA 

100 or 200 ppm 

AN in drinking 

water 

28 days + Pu et al. (2009) 

Male SpragueDawley rats8-oxodG in brain 

DNA

30 or 300 ppm 

AN in drinking 

water 

21 d + Whysner et al. 

(1998a) 

Male SpragueDawley rats 8-oxodG in liver 

DNA 

30 or 300 ppm 

AN in drinking 

water 

21 d + Whysner et al. 

(1998a) 

Male SpragueDawley rats 8-oxodG in 

forestomach DNA

0–300 ppm AN in 

drinking water 

21 d – Whysner et al. 

(1998a) 

Male F344 rats 8-oxodG in brain 

DNA

0–100 ppm AN in 

drinking water

21 d – Whysner et al. 

(1998a) 

Male SpragueDawley rats8-oxodG in brain 

DNA

100 ppm AN in 

drinking water

3–94 d + Whysner et al. 

(1998a)

aThe formation of 8-oxodG was reversible. Following treatment with AN for 24 hrs and removal of AN for 24 hrs 

afterwards, 8-oxodG levels returned to control values. 

+ = Positive;– = negative; (+) = borderline positive. 
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4.6. SYNTHESIS AND EVALUATION OF MAJOR NONCANCER EFFECTS AND 

MODE OF ACTION—ORAL AND INHALATION 

4.6.1. Oral 

 No studies are available regarding noncancer health effects in humans following acute, 

subchronic, or chronic oral exposure to AN. 

 The chronic oral noncancer toxicity database for AN consists of results from four rat 

toxicity and cancer bioassays (one with F344 rats and three with Sprague-Dawley rats) (see 

Table 4-56 for references), one toxicity and cancer bioassay with B6C3F1 mice (NTP, 2001), 

and a three-generation developmental/reproductive toxicity study with Sprague-Dawley rats 

(Friedman and Beliles, 2002; Litton Bionetics, 1992). NOAELs and LOAELs for noncancer 

effects in these studies are summarized in Table 4-56. Also included in Table 4-56 are 

summaries of results from a 12-week gavage study of nerve conduction velocities in male 

Sprague-Dawley rats (Gagnaire et al., 1998), a 60-day gavage study of testicular toxicity in male 

CD-1 mice (Tandon et al., 1988), a 14-week gavage toxicity bioassay in B6C3F1 mice (NTP, 

2001), a developmental toxicity study in Sprague-Dawley rats exposed by gavage during GDs 6–

15 (Murray et al., 1978), and a neurobehavioral study of Sprague-Dawley rats exposed to AN in 

drinking water for up to 12 weeks (Rongzhu et al., 2007). 

Table 4-56. Noncancer effects in animals repeatedly exposed to AN by the 

oral route 

Reference NOAEL LOAEL 

Species

Exposure conditions, 

mg/kg-d (mg/kg-d) Effect 

Johannsen and 

Levinskas (2002b); 

Biodynamics (1980c) 

F344 rat 

0, 0.1, 0.3, 0.8, 2.5, 8.4 (M) 

0, 0.1, 0.4, 1.3, 3.7, 10.9 (F) 

DW, 2 yrs; sacrifices at 6, 12, 

and 18 mos and termination 

(99 wks or 699–706 d [F]; 

107 wks or 770–777 d [M]) 

0.1(M) 

0.1 (F) 

2.5 (M) 

1.3 (F) 

2.5 (M) 

3.7 (F) 

0.4 (F) 

2.5 (M) 

0.3a (M) 

0.4a

 (F) 

8.4b

(M) 

3.7b

 (F) 

8.4a (M) 

10.9a (F) 

1.3b

 (F) 

8.4b (M) 

Forestomach squamous cell 

hyperplasia and hyperkeratosis, 

increased incidence 

Decreased survival after 18 mos 

Decreased BW (>10% compared 

with control) 

Increase in serum alkaline 

phosphatase (F only) 

Increase in epidermal inclusion 

cysts (M only) 

Johannsen and 

Levinskas (2002a); 

Biodynamics (1980a) 

Sprague-Dawley rat 

0, 0.09, 8.0 (M) 

0, 0.15, 10.7 (F) 

DW, 22 mos (M); 19 mos 

(F); sacrifices at 6, 12, and 

18 mos and termination 

ND (M) 

0.15 (F) 

8.0 (M) 

0.15 (F) 

0.09 (M) 

0.15 (F) 

0.09b

(M) 

10.7a (F) 

ND (M) 

10.7a

 (F) 

8.0b

 (M) 

10.7a

 (F) 

Forestomach squamous cell 

hyperplasia, increased severity 

Renal transitional cell hyperplasia 

(F only) 

Decreased survival at 10 mos (M + 

F); decreased BW (10/8% [M/F]) 
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Table 4-56. Noncancer effects in animals repeatedly exposed to AN by the 

oral route 

Reference NOAEL LOAEL 

Species

Exposure conditions, 

mg/kg-d (mg/kg-d) Effect 

Johannsen and 

Levinskas (2002a); 

Biodynamics (1980b) 

Sprague-Dawley rat 

0, 0.1, 10 (M + F) 

Gavage, 7 d/wk for 20 mos; 

sacrifices at 6, 12, and 

18 mos and termination 

0.1 (M + F)

0.1 

0.1 

10a (M + F) 

10a 

10a 

Forestomach squamous cell 

hyperplasia, increased severity 

Renal transitional cell hyperplasia 

at some but not all sacrifices 

Decreased survival after 14 mos 

(M + F); decreased BW (6–13% 

compared with controls [M only]).

Quast (2002); Quast 

et al. (1980a) 

Sprague-Dawley rat 

0, 3.4, 8.5, 21.3 (M) 

0, 4.4, 10.8, 25.0 (F) 

DW, 2 yrs 

3.4 (M) 

ND (F) 

ND (F) 

ND (M) 

4.4 (F) 

8.5 (M) 

ND (F) 

8.5 (M) 

10.8 (F) 

8.5b(M) 

4.4b(F) 

4.4b(F) 

3.4b (M) 

10.8b (F) 

21.3b(M) 

4.4b (F) 

21.3b (M) 

25.0b (F) 

Forestomach squamous cell 

hyperplasia and hyperkeratosis, 

increased incidence 

Gliosis in brain with or without 

perivascular cuffing in females; 

not significant in males 

Chronic nephropathy 

Decreased survival after 300 (F) or 

480 (M) d 

Decreased BW (>10% compared 

with control); clinical signs of 

nervous system dysfunction 

NTP (2001) 

B6C3F1 mouse 

0, 2.5, 10, 20 (M + F) 

Gavage, 5 d/wk for 2 yrs 

Adjusted doses: 0, 1.8, 7.1, 

14.3 mg/kg-d (M + F) 

1.8 (M) 

7.1 (F) 

1.8 (M) 

14.3 (F) 

ND (F) 

7.1 (M + F)

7.1b (M) 

14.3b (F) 

7.1b

 (M) 

ND (F) 

1.8b

 (F) 

14.3a

 (M + 

F) 

Forestomach squamous cell 

hyperplasia and hyperkeratosis, 

increased incidence 

Increased incidence of Harderian 

gland hyperplasia 

Increased incidence of ovarian 

cysts or ovarian atrophy 

Decreased survival after 15 wks 

NTP (2001) 

B6C3F1 mouse 

0, 5, 10, 20, 40 60 (M + F) 

Gavage, 5 d/wk for 14 wks. 

Adjusted doses: 0, 3.6, 7.1, 

14.3, 28.6, and 42.9 (M + F) 

28.6 (M) 

14.3 (F) 

14.3 (M + 

F) 

ND (M) 

28.6a (F) 

28.6b

 (M + 

F) 

Forestomach inflammation, 

ulceration, and epithelial 

hyperplasia, increased incidence in 

F only 

No histopathology data for 

60 mg/kg groups 

Increased mortality 

Tandon et al. (1988) 

CD-1 mouse 

0, 1, 10 (M only) 

Gavage, for 60 d 

1 10b 45% decreased sperm count; 40% 

of seminiferous tubules examined 

degenerated 
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Table 4-56. Noncancer effects in animals repeatedly exposed to AN by the 

oral route 

Reference NOAEL LOAEL 

Species

Exposure conditions, 

mg/kg-d (mg/kg-d) Effect 

Friedman and Beliles 

(2002); Litton 

Bionetics (1992) 

Sprague-Dawley rat 

0, 11, 37 (M) 

0, 20, 40 (F) 

DW, three-generation 

reproduction study 

ND 

ND 

11b (M) 

20b (F) 

11b (M) 

20b

 (F) 

Decreased viability for F1b pups; 

no changes in fertility index or 

pregnancy outcome for F1a, F1b, 

F2a, F2b, F3a, or F3b generations 

 

LOAEL for decreased lactation 

index in F1b parents for F2a pups; 

small deficits in postnatal pup 

weights (10–40%, variable across 

generations) and postnatal survival 

(about 10%, variable across 

generations) in higher dosed 

groups 

Murray et al. (1978) 

Sprague-Dawley rat 

0, 10, 25, 65 (F only) 

Gavage GDs 6–15 

10 

10 

25 

25 

Maternal effects: forestomach 

hyperplasia, 11% increased liver 

weight, 22% decrease in BW gain 

Fetal effects: missing vertebrae in 

6/17 litters, 7% decreased BW 

Gagnaire et al. (1998)

Sprague-Dawley rat 

0, 12.5, 25, 50 (M only) 

Gavage, 5 d/wk for 12 wks 

25 50a SCV decreased beginning wk 6 

(-7.5%), –17.8% by wk 12; 

-10.6% after 8 wks recovery; 

decreased BW after 4 wks (-17% 

at wk 12); hind limb weakness in 

5/11 surviving high-dose rats after 

wk 9 

Rongzhu et al. (2007) 

Sprague-Dawley rat 

0, 4, 13.5 (M only) 

DW for 0, 4, 8, 12 wks 

ND 4b Neurobehavioral alterations, as 

indicated by decreased motor 

coordination, increased training 

duration, head twitching, 

trembling, circling, backwards 

pedaling, and decreased homecage activities 

Szabo et al., (1984) 

Sprague-Dawley rats 

0, 0.2, 4, 20, and 100 mg/kgday (F only) 

DW for up to 60 days 

4 (F) 20 (F) Enlarged kidneys, increase in 

regional hyperplasia of the gastric 

mucosa 

Szabo et al. (1984) 

Sprague-Dawley rats 

0, 0,2, 4, 20 or 100 mg/kgday (F only) 

Daily gavage for up to 60 

days 

ND 0.2 (F) Adrenocortical hyperplasia 

Quast et al. (1975) 

Beagle dog 

0, 10, 16, 17 (M) 

0, 8, 17, 18 (F) 

DW for 6 months 

10 (M) 

8 (F) 

16 (M) 

17 (F) 

Early mortality, histopathological 

lesions of the esophagus and 

tongue. 

a

significantly different from controls (p < 0.01). 

b

significantly different from controls (p < 0.05). 

DW = drinking water; F = female; M = male; ND = not determined 
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 Forestomach lesions (epithelial hyperplasia and hyperkeratosis) were the most 

consistently observed noncancer effect associated with chronic oral exposure of rats and mice to 

AN and were associated with the lowest LOAELs in AN-exposed rats (Table 4-56). The lowest 

LOAELs were 0.09 and 10.7 mg/kg-day for increased severity of forestomach lesions in male 

and female Sprague-Dawley rats exposed by drinking water (Johannsen and Levinskas, 2002a; 

Biodynamics, 1980a), 0.3 and 0.4 mg/kg-day for increased incidence of forestomach lesions in 

male and female F344 rats exposed in drinking water (Johannsen and Levinskas, 2002b; 

Biodynamics, 1980c), and 8.5 and 4.4 mg/kg-day for increased incidence of forestomach lesions 

in male and female Sprague-Dawley rats exposed in drinking water (Quast, 2002; Quast et al., 

1980a). Increased incidences of animals with hyperplasia or hyperkeratosis of the forestomach 

were also observed in B6C3F1 mice exposed by gavage (5 days/week) for 2 years to 10 mg/kgday (males) or 20 mg/kg-day (females) (NTP, 2001), female B6C3F1 mice exposed to 40 mg/kgday by gavage (5 days/week) for 14 weeks (NTP, 2001), and pregnant Sprague-Dawley rats 

exposed to 25 mg/kg-day by gavage on GDs 6–15 (Murray et al., 1978). Other effects observed 

in orally exposed animals generally were observed at higher doses (Table 4-56). 

 Kidney effects included increased incidence of renal transitional cell hyperplasia in 

Sprague-Dawley rats exposed by gavage or in drinking water to about 10 mg/kg-day but not 

0.1 mg/kg-day (Johannsen and Levinskas, 2002a; Biodynamics, 1980a) and increased incidence 

of chronic nephropathy in Sprague-Dawley rats exposed to drinking water doses of 3.4 mg/kgday (males) or 10.8 mg/kg-day (females) (Quast 2002; Quast et al., 1980a). 

 Decreased survival was observed after 18 months in F344 rats exposed to drinking water 

at 8.4 mg/kg-day (males) and 3.7 mg/kg-day (females) (Johnannsen and Levinskas, 2002b) and 

in Sprague-Dawley rats exposed to drinking water at 21.2 mg/kg-day (males) and 4.4 mg/kg-day 

(females) (Quast, 2002). In another drinking water study of Sprague-Dawley rats, decreased 

survival was observed at 8.0 mg/kg-day (males) and 10.7 mg/kg-day (females). 

 Increased incidences of ovarian lesions (cysts or atrophy) were observed in female mice 

exposed to gavage doses of 2.5, 10, or 20 mg/kg-day (NTP, 2001), but exposure-related ovarian 

lesions were not observed in the chronic rat bioassays. In a reproductive toxicity study in 

Sprague-Dawley rats exposed to 0, 100, or 500 ppm AN in drinking water (11 or 37 mg/kg-day 

[males]; 20 or 40 mg/kg-day [females]), small deficits in postnatal pup weights and pup survival 

without effects on fertility or pregnancy success were observed in three generations exposed to 

either 100 or 500 ppm (Friedman and Beliles, 2002; Litton Bionetics, 1992) (see Table 4-56). 

Other reproductive effects observed in animals were a reduction of epididymal sperm counts and 

degeneration of seminiferous tubules in CD-1 mice exposed to 10 mg/kg-day by gavage for 

60 days (Tandon et al., 1988), but no exposure-related lesions in male reproductive organs were 

found in B6C3F1 mice exposed by gavage to up to 40 mg/kg-day for 14 weeks or up to 

20 mg/kg-day for 2 years (NTP, 2001). Likewise, no effects on sperm motility parameters were 

found in male B6C3F1 mice exposed to up to 20 mg/kg-day for 14 weeks (NTP, 2001). 
259 DRAFT - DO NOT CITE OR QUOTE 

 The only oral developmental toxicity study (Murray et al., 1978) identified 10 and 

25 mg/kg-day as a NOAEL and LOAEL for maternal effects (increased incidence of 

forestomach hyperplasia, 10% increased absolute liver weight, and 22% decreased BW gain) and 

developmental effects (7% decrease in fetal BW and missing vertebrae associated with short tails 

in 6/17 litters, compared with 1/38 in the controls). The study involved daily gavage exposure 

on GDs 6–15. 

 Neurological effects in animals associated with chronic oral exposure to AN were 

observed in: (1) a report of gross clinical signs of neurological impairment in about 10% of 

Sprague-Dawley rats (paralysis, head tilt, circling, and seizures) exposed to drinking water 

concentrations of 500 ppm (providing doses of about 65 and 74 mg/kg-day for males and 

females) but not in rats exposed to 100 ppm (13 and 15 mg/kg-day, males and females) (Bigner 

et al., 1986); (2) decreases (8–15%) in SCV in tail nerves and hind-limb weakness in male 

Sprague-Dawley rats exposed by gavage to 50 mg/kg-day (5 days/week) for 6–12 weeks but not 

in rats exposed to 25 mg/kg-day (Gagnaire et al., 1998); and (3) neurobehavioral alterations in 

male Sprague-Dawley rats exposed to 4 and 13.46 mg/kg-day AN for 4, 8, or 12 weeks (head 

twitching, trembling, circling, backwards pedaling, decreased home-cage activities, decreased 

motor coordination, and learning and memory) (Rongshu et al., 2007). These studies indicated 

that neurological impairment in AN-exposed rats occurred at higher administered doses than 

doses associated with hyperplasia and hyperkeratosis in forestomach squamous epithelial cells. 

4.6.2. Inhalation 

 Table 4-57 lists the NOAELs and LOAELs from four cross-sectional health examinations 

and surveys of subjective symptoms in Japanese and Chinese acrylic fiber workers (Chen et al., 

2000; Kaneko and Omae, 1992; Muto et al., 1992; Sakurai et al., 1978), a cross-sectional 

examination of performance of acrylic fiber workers in a battery of neurobehavioral tests (Lu et 

al., 2005a), a study on the effect of AN exposure on the sperm cells of AN production plant 

workers (Xu et al., 2003), and three cross-sectional surveys of reproductive outcomes in Chinese 

acrylic fiber or AN manufacturing workers (Dong et al., 2000b; Li, 2000; Dong and Pan, 1995). 

More detailed descriptions of these studies are in Section 4.1.2.2. Each of these epidemiologic 

studies measured AN concentrations in workplace air samples and compared results of the 

examinations and surveys in exposed workers with unexposed workers of similar age. The 

human LOAELs and NOAELs in Table 4-57 are mean or midpoint values of the range of 

concentrations determined for various groups of exposed workers. Table 4-57 also lists 

NOAELs and LOAELs identified in the animal toxicity studies involving repeated inhalation 

exposure to AN. 
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Table 4-57. Noncancer effects in human workers and animals repeatedly exposed 

to AN by inhalation

NOAELa Reference/ LOAEL 

Study subjects Exposure conditionsa

ppm Effect 

Muto et al. (1992) 

Acrylic fiber workers 

Male workers with average 

17 yrs of occupational 

exposure compared with 

unexposed workers 

0.19 1.13 Statistically significantly increased 

prevalences of subjective symptoms (e.g., 

heaviness of stomach, poor memory, 

irritability) but no increases in prevalences of 

physical signs or abnormal values in 

urinalytic, hematological, liver function, or 

blood pressure variables compared with 

controls. 

Sakurai et al. (1978) 

Acrylic fiber workers 

Male workers with average 

10–12 yrs of occupational 

exposure compared with 

unexposed workers 

ND 4.2 Statistically insignificant increase in incidence 

of palpable liver, reddening of the conjunctiva 

and pharynx, and the occurrence of skin 

rashes compared with unexposed controls. 

No survey of subjective symptoms. 

Kaneko and Omae 

(1992) 

Acrylic fiber workers 

Male workers with average 

5.6, 7.0, or 8.6 yrs of 

occupational exposure in 

three groups of factories 

(mean AN concentrations 

at 1.8, 7.4, and 14.1 ppm) 

were compared with 

unexposed workers 

ND 1.8 Statistically significantly increased 

prevalences of subjective symptoms (e.g., 

headaches, tongue trouble, choking lump in 

chest, fatigue) were found in workers from all 

three groups of factories when compared with 

controls. 

Chen et al. (2000) 

Acrylic fiber workers 

Male and female workers 

with average 13 yrs of 

occupational exposure 

compared with unexposed 

workers 

ND 0.48 Statistically significantly increased 

prevalences of subjective symptoms (e.g., 

headache, dizziness, poor memory, choking 

feeling in chest, loss of appetite) compared 

with controls. 

Lu et al. (2005a) 

Acrylic fiber workers 

Male and female workers 

with >1 yr of occupational 

exposure (average duration 

not available) compared 

with unexposed workers 

ND 0.11 Small, but statistically significant, deficits in 

tests of neurobehavior in monomer workers 

and fiber workers (average air concentrations 

of 0.11 ppm for monomer workers and 

0.91 ppm for fiber workers) compared with 

controls. 

Xu et al. (2003) 

AN production workers

Male workers with 2.8 yrs 

of occupational exposure 

in a AN production plant, 

compared with controls of 

approximate age range in 

the general population. 

ND 0.37 Statistically significant decrease in sperm

density and sperm number in exposed 

workers, statistically significant increase in 

DNA strand breakage and sex chromosome 

aneuploidy in sperm cells of exposed workers 

compared with controls 

Dong and Pan (1995) 

Acrylic fiber workers 

Male and female workers 

with average 3.2 and 

10.2 yrs of occupational 

exposure compared with 

unexposed controls 

ND 3.7 Statistically significant increased prevalences 

of adverse reproductive outcomes (premature 

delivery [10.7 vs. 3.5%, in wives of exposed 

males], stillbirths [4.5 vs. 0%, in exposed 

females], and sterility [5.0 vs. 1.8%, in 

exposed males]) compared with controls. 

Dong et al. (2000b) 

Acrylic fiber workers 

Male and female workers 

with average 11 and 

10.4 yrs of occupational 

exposure compared with 

unexposed controls 

ND 3.6 Statistically significantly increased 

prevalences of adverse reproductive outcomes 

(increased stillbirths [2.7 vs. 0%], birth 

defects [21.3 vs. 4.8%], and premature 

deliveries [8.2 vs. 3.9%]) in female workers 

compared with controls. 
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Table 4-57. Noncancer effects in human workers and animals repeatedly exposed 

to AN by inhalation

NOAELa Reference/ LOAEL 

Study subjects Exposure conditionsa

ppm Effect 

Li (2000) 

AN manufacturing 

workers 

Female workers with 

average 14 yrs of 

occupational exposure 

compared with unexposed 

controls 

ND 7.5 Statistically significant increased prevalences 

of adverse reproductive outcomes (sterility 

[2.6 vs. 0.8%], pregnancy complications 

[20.8 vs. 7.1%], premature deliveries [11.6 vs. 

4.7%], and congenital defects [25.4 vs. 4.2%]) 

in female exposed workers compared with 

controls. 

Quast et al. (1980b) 

Sprague-Dawley rats 

(M + F) 

0, 20, 80 ppm, 6 hrs/d, 

5 d/wk for 2 yrs 

ND 20 Statistically significant increase in incidence 

of lesions in nasal epithelia at 20 ppm in 

males and females; focal necrosis in liver of 

females. At 80 ppm, other lesions occurred at 

increased incidences—gliosis and 

perivascular cuffing in brain in both sexes, 

hepatic necrosis in females, focal nephrosis 

and thyroid cysts in males, and hyperplasia in 

nonglandular stomach. 

Gagnaire et al. (1998) 

Sprague-Dawley rats 

(M only) 

0, 25, 50, 100 ppm, 

6 hrs/d, 5 d/wk for 24 wks 

ND 25 Statistically significant deficits (5% decreased 

compared with controls) in sensory 

conduction velocity of the tail nerve. 

Murray et al. (1978) 

Pregnant SpragueDawley rats 

0, 40, or 80 ppm, 6 hrs/d 

on GDs 6–15 

ND 

40 

40 

80 

Maternal weight gain decreased by >20% 

compared with controls. 

No increased incidence of litters with a single 

malformation; 6/35 litters with short tail, short 

trunk, missing vertebrae, or missing ribs vs. 

1/33 in controls. 

Saillenfait et al. (1993) 

Pregnant SpragueDawley rats 

0, 12, 25, 50, 100 ppm, 

6 hrs/d on GDs 6–20 

12 

12 

25 

25 

Statistically significant decreased maternal 

weight gain compared with controls. 

Statistically significant decreased fetal BW, 

>5% decreased compared with controls. No 

exposure-related increased incidences of 

litters with fetal anomalies. 

aND = cannot be determined 

In acute AN poisoning cases involving humans (Chen et al., 1999), first aid treatment of 

victims generally included antidotes for cyanide poisoning and pure oxygen to overcome 

respiratory distress caused by damage to the lung. Other clinical symptoms following such 

poisoning included blood chemistry changes indicative of slight liver damage. In an analysis of 

144 case reports of acute AN poisoning, Chen et al. (1999) estimated that exposure levels were 

in the 18–258 ppm range (40–560 mg/m3) for 60 cases and >460 ppm (>1,000 mg/m3) for the 

remaining 84 cases. Subjective symptoms reported for 92–100% of the cases included dizziness, 

headache, chest tightness, feebleness, and hyperactive knee jerk. Sore throat, dyspnea, vomiting, 

abdominal pain, fainting, and congestion of the pharynx were reported in 60–87% of cases. 

Other less frequently reported symptoms or effects (5–32% of cases) included numbness of 
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limbs, convulsion, rapid heart rate, cough, hoarseness, rough breathing sound, coma, and 

abnormal liver function (Chen et al., 1999). 

 In the cross-sectional studies of AN-exposed workers, subjective symptoms that were 

reported with increased prevalences compared with unexposed workers included dizziness, 

headache, chest tightness, and poor memory, indicating respiratory irritation and neurological 

effects. Average workplace air concentrations associated with increased prevalences of these 

subjective symptoms were 1.13 ppm (Muto et al., 1992), 1.8 ppm (Kaneko and Omae, 1992), and 

0.48 ppm (Chen et al., 2000) (see Table 4-57). No statistically significant increases in the 

prevalences of subjective symptoms were found in a group of acrylic fiber workers whose 

average workplace air concentration was 0.19 ppm (Muto et al., 1992). The studies by Muto et 

al. (1992) and Sakurai et al. (1978) included clinical physical examinations, but no statistically 

significant increases in prevalences of physical signs (such as reddened conjunctiva or pharynx) 

or abnormal values in clinical chemistry variables (including activities of liver enzymes) were 

found in exposed workers (more details of results from these studies can be found in Section 

4.1.2.2.2 and Table 4-22). 

 To provide support that neurological effects are the most sensitive identified class of 

effects from repeated inhalation exposure to AN, statistically significant deficits in several 

neurobehavioral tests were measured in exposed workers in a Chinese acrylic fiber 

manufacturing plant with mean workplace air concentrations of 0.11 ppm (range 0.00–1.70 ppm) 

and 0.91 ppm (range 0.00–8.34 ppm) in two different process areas. Deficits in exposed workers 

compared with nonexposed workers were noted in a Profile of Mood States test (20–68% higher 

for negative moods such as anger and confusion), a Simple Reaction Time test of attention and 

response speed (10–16% deficits), and the backward sequence of the Digit Span test of auditory 

memory (21–24% deficits). 

 Statistically significant increases in the prevalences of adverse reproductive outcomes 

were associated with mean workplace air concentrations of 3.7 ppm (Dong and Pan, 1995), 

3.6 ppm (Dong et al., 2000a), and 7.5 ppm (Li, 2000), indicating that reproductive effects from 

occupational exposure may occur at higher exposure levels than those associated with mild 

neurobehavioral effects. However, statistically significant decrease in sperm density and 

number, statistically significant increase in DNA strand breakage and sex chromosome 

aneuploidy in sperm cells were reported in workers exposed to 0.37 ppm AN with average 2.8 

years of exposure (Xu et al., 2003). An epidemiological study conducted in the area surrounding 

an AN-using plant in Hungary reported increased ORs for several congenital malformations 

(e.g., undescended testis), but no exposure data were provided in this study (Czeizel et al., 2000, 

1999). 

 Exposure levels associated with adverse effects in Sprague-Dawley rats were higher than 

the workplace air concentrations associated with adverse effects in AN-exposed workers 

(Table 4-57). The lowest exposure level in the 2-year inhalation bioassay, 20 ppm, produced 
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increased incidence of lesions in nasal epithelia (hyperplasia of mucus-secreting cells in males 

and flattening of the respiratory epithelium in females). At 80 ppm, further increases in 

incidences of nasal lesions of a wider variety were observed as well as statistically significant 

increases in the incidences of histopathological lesions at other sites, including gliosis and 

perivascular cuffing in the brain of males and females, focal nephrosis and thyroid cysts in 

males, hepatic necrosis in females, and hyperplasia and hyperkeratosis of the nonglandular 

portion of the stomach in both sexes combined (Quast et al., 1980b). Other effects in SpragueDawley rats associated with repeated inhalation exposure to AN included deficits in sensory 

nerve conduction in the tail nerve of rats exposed to 25 ppm AN (Gagnaire et al., 1998) and 

developmental effects. Statistically significantly increased incidence of litters with missing 

vertebrae, missing ribs, or anteriorly displaced ovaries were observed in rats exposed to 80 ppm, 

but not 40 ppm, 6 hours/day on GDs 6–15 (Murray et al., 1978). In another study involving 

6 hours/day inhalation exposure of Sprague-Dawley rats on GDs 6–20, developmental effects 

were restricted to a statistically significant decrease in fetal weight gain per litter, compared with

controls, associated with exposure to 25 ppm (5% decrease), 50 ppm (8% decrease), or 100 ppm 

(15% decrease); no effects on fetal weight gain were observed at 12 ppm (Saillenfait et al., 

1993). 

4.6.3. Mode-of-Action Information 

 The precise modes of action whereby AN induces noncancer effects are unknown. 

However, a general understanding of the processes by which AN is metabolized within the body 

allows some conclusions to be drawn about the range of processes that might be involved in 

bringing about one or more of its toxic responses. Relevant metabolic processes are likely to 

include partitioning between detoxification and oxidative activation sub-pathways, conversion of 

AN to one or more toxic metabolites, depletion of GSH, the association of AN metabolism with 

the onset of oxidative stress, and the ability of CEO, the reactive metabolite of AN, to covalently 

bind to macromolecules, such as proteins. In addition, other processes related to the parent 

compound AN, such as its cholinomimetic effects, may also be involved. 

4.6.3.1. GI Effects 

 The relationship between AN metabolism and GI hemorrhage in rats was suggested by 

Ghanayem and Ahmed (1983). GI bleeding was observed 3 hours after a single dose of 

50 mg/kg AN was administered to Sprague-Dawley rats orally or subcutaneously, with no 

significant difference in the amount of GI blood loss resulting from either route of 

administration. Thus, AN-induced GI bleeding was not a result of direct irritation of AN on the 

GI tract. 

Pretreatment of rats with CYP450 enzyme inducer Aroclor 1254 increased blood loss by 

240% (Ghanayem and Ahmed, 1983). In contrast, pretreatment of rats with CYP450 inhibitors 
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cobalt chloride or SKF 525A prior to AN administration produced significant decreases in blood 

loss of 10 and 40%, respectively. Pretreatment of rats with DEM, a known depletor of GSH, 

prior to AN administration produced no significant change in GI bleeding. In addition, 

administration of a sublethal dose (6 mg/kg s.c.) of KCN did not induce GI bleeding when 

compared with controls. Therefore, Ghanayem and Ahmed (1983) concluded that metabolic 

activation of AN by CYP450 to a reactive metabolite other than cyanide (probably CEO) was a 

prerequisite for AN to induce gastric hemorrhage. 

Ahmed et al. (1996a) showed irreversibly bound AN-derived radioactivity in intestinal 

mucosa following a single i.v. injection of 2-[14C]-AN to male F344 rats. A recent study by 

Jacob and Ahmed (2003a) also demonstrated that AN and or its metabolites accumulated and 

covalently interacted in GI mucosa of male F344 rats treated either by i.v. or orally with 

2-[14C]-AN. These studies supported the hypothesis that AN-induced injury of the GI mucosa is 

not due to direct irritation by AN but by metabolic activation and macromolecular interaction of 

AN metabolite in these tissues. 

 Ghanayem et al. (1985) also studied the mechanism of AN-induced gastric mucosal 

necrosis in the glandular stomach in male Sprague-Dawley rats. Subcutaneous administration of 

40 or 50 mg/kg AN caused a significant decrease in hepatic and gastric GSH concentration 

3 hours after treatment, and induced gastric necrosis. Pretreatment of rats with various metabolic 

modulators (CYP450 monooxygenase and GSH) before administration showed that there was a 

significant inverse relationship between gastric GSH concentration and AN-induced gastric 

erosions. Pretreatment of rats with sulfhydryl-containing compounds (cysteine or cysteamine) 

protected against AN-induced gastric necrosis and blocked the depletion of gastric GSH. 

In addition, AN-induced gastric erosions could be prevented by pretreatment with 

atropine, a muscarinic receptor blocker, suggesting the involvement of muscarinic receptors in 

the AN-induced gastric mucosal necrosis (Ghanayem et al., 1985). Activation of acetylcholine 

muscarinic receptors is known to increase gastric acid secretion and cause gastric erosions. 

Because muscarinic receptors are known to contain sulfhydryl groups in their active site (Ikeda 

et al., 1980; Aronstam et al., 1978), Ghanayem et al. (1985) hypothesized that AN inactivated 

critical sulfhydryl groups and caused gastric erosions by locally modulating muscarinic 

acetylcholine receptors in the stomach. 

 

4.6.3.2. Neurological Effects 

Increased prevalence of subjective symptoms of neurological effects was associated with 

average workplace air concentrations of 1.13 ppm (Muto et al., 1992), 1.8 ppm (Kaneko and 

Omae, 1992), and 0.48 ppm (Chen et al., 2000), and small deficits in performance in a battery of 

neurobehavioral tests were observed in workers from factories with average workplace air 

concentrations of 0.11 and 0.91 ppm (Lu et al., 2005a). In a case of acute severe accidental AN 

poisoning (AN concentration at 62 mg/m3

) of a worker (Fei and Xu, 2006), impairment of the
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CNS, including diffused damage to the cerebral cortex layer (pyramidal system) and damage to 

the subcortical layer (extrapyramidal system), was observed. In addition to poisoning symptoms 

(dizziness, headache, difficulty breathing, confusion, convulsion, etc.), cerebral focal damage 

was also detected in the patient, suggesting Parkinson’s syndrome (static tremor, muscle rigidity, 

increased muscle tension and lead-pipe rigidity, slow motor activity). The clinical symptoms 

were related to those induced by adverse effects on the cholinergic system and dopaminergic 

system. 

Neurotoxicological effects of AN in animals included cholinomimetic effects on the 

peripheral and central muscarinic systems in Sprague-Dawley rats after administration of 

nonlethal oral doses of 20, 40, or 80 mg/kg (Ghanayem et al., 1991) and the development of 

brain lesions in Sprague-Dawley rats (gliosis and perivascular cuffing) following chronic 

inhalation exposure to 80 ppm (Quast et al., 1980b) or chronic drinking water exposure to 

4.4 mg/kg-day (females only). 

 The neurobehavioral effect of AN was suggested to be related to changes in brain 

monoamine neurotransmitter levels (Lu et al., 2005b). In a 12-week drinking water study of 

male Sprague-Dawley rats (Lu et al., 2005b), dopamine levels were decreased by 76 and 46% in 

rats exposed to 50 ppm AN, in the striatum and cerebellum, respectively. Serotonin levels were 

decreased by 38 and 41% in the striatum and cerebellum, respectively, for rats exposed to 

50 ppm AN. In the case of acute severe AN poisoning, the development of Parkinson’s 

syndrome and other CNS impairment in the exposed worker would suggest involvement of the 

cholinergic system and dopaminergic system (Fei and Xu, 2006). 

The cholinomimetic effects were thought to be due to an effect of AN on muscarinic 

receptors, since atropine sulfate (which blocks both central and peripheral muscarinic receptors) 

protected animals against these effects (Ghanayem et al., 1991). In an earlier study on 

AN-induced gastric mucosal necrosis (Ghanayem et al., 1985), it was reported that pretreatment 

with atropine and sulfhydryl-containing chemicals protected against such lesions. Since 

muscarinic receptors contain sulfhydryls in their active sites (Aronstam et al., 1978) and 

sulfhydryl-depleting chemicals are known to potentiate chemically induced activation of 

muscarinic receptors (Hedlund and Bartfai, 1979), Ghanayem et al. (1991) speculated that 

depletion and/or inactivation of endogenous sulfhydryls by AN and/or its metabolite may cause 

configurational changes of muscarinic receptor binding affinity that, in turn, lead to the 

development of acetylcholine-like (cholinomimetic) toxic effects. It is unlikely that these 

cholinomimetic effects are due to inhibition of acetylcholinesterase activity. Rajendran and 

Muthu (1981) reported that AN did not inhibit the activity of acetylcholinesterase. In addition, 

Satayavivad et al. (1998) reported that AN had no effect on decreased motor activity induced by 

physostigmine (an inhibitor of acetylcholinesterase). Thus, Satayavivad et al. (1998) proposed 

that the cholinomimetic effect of AN might be mediated by the release of acetylcholine from 

nerve endings. 
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 In addition, Ghanayem et al. (1991) proposed that lipid peroxidation may at least partly 

be involved in AN-induced cholinergic overstimulation. In noting that AN enhanced lipid 

peroxidation and inhibited Na+,K+-ATPase in RBCs in vitro, Farooqui et al. (1990) speculated 

that disruption of the lipid microenvironment in membranes by either or both of these processes 

might impact the muscarinic receptor function and induce cholinergic overstimulation. 

 For acute CNS effects, the signs were similar to those produced by cyanide. Ghanayem 

et al. (1991) proposed that the free cyanide liberated from AN during its metabolism may 

contribute to these effects. It is well established that cyanide causes CNS dysfunction by 

inhibition of cellular respiration via inactivation of tissue cytochrome c oxidase, which is the 

terminal electron acceptor in cellular energy production (Klaassen, 2001). Intraperitoneal 

injection of 30 mg/kg AN in Chinese hamsters decreased cerebral succinate dehydrogenase and 

cytochrome oxidase activities (Zitting et al., 1981). These authors suggested that the observed 

biochemical effects were likely due to the formation of cyanide from AN. 

 The neurotoxicity of AN may also result from the covalent binding of AN or its 

metabolites to enzymes. There is abundant evidence that important proteins bearing cysteine 

residues (e.g., enzymes such as GSTM1) can bind AN, thereby possibly impairing their functions 

and creating metabolic imbalances leading to toxicity. For example, AN was shown to 

covalently bind to the important glycolytic enzyme GAPDH in vitro (Campian et al., 2002). AN 

specifically targeted and bound to cysteine 149 in the active center of this enzyme, causing 

irreversible inhibition of its activity. This suggested that AN might impair glycolytic ATP 

production in vivo. Campian et al. (2002) speculated that the combination of glycolytic 

impairment with inhibition of mitochondrial ATP synthesis by cyanide released from AN could 

result in metabolic arrest. However, Campian et al. (2008) demonstrated in male SpragueDawley rats that acute lethality of AN was not due to brain metabolic arrest (see Section 

4.5.1.1.3), 

4.6.3.3. Reproductive/Developmental Effects 

As discussed in Section 4.5.2.1, lower sperm density was noted in workers exposed to 

0.8 mg/m3 AN compared with controls of approximate age range from the general population 

(75 × 106/mL vs. 140 × 106/mL) (Xu et al., 2003). DNA strand breakage was also detected in 

AN-exposed workers using single-cell gel electrophoresis, with the rate of comet sperm higher in 

the exposed workers than in the control (28.7 vs. 15%). The frequency of sex chromosome 

disomy was 0.69% in exposed groups and was higher than 0.35% in the control group. There 

were also significant differences in the frequencies of XX-, YY-, and XY-bearing sperm between 

exposed and control groups. 

AN-induced effects on the male reproductive system are restricted to a report that 

treatment of CD-1 mice for 60 days with gavage doses of 10 mg/kg-day produced degeneration 

of the seminiferous tubules and altered testicular activities of several enzymes (SDH, acid 
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phosphatase, LDH, and β-glucuronidase) (Tandon et al., 1988). Exposure-related increases in 

the incidence of lesions in male reproductive organs were not observed in 14-week or 2-year 

gavage bioassays with B6C3F1 mice (NTP, 2001) or in the 2-year bioassays with SpragueDawley or F344 rats (see Table 4-56). 

 The potential male reproductive effect of AN may involve the distribution and 

metabolism of AN to CEO in the testis and interaction of CEO with tissue protein and DNA. 

Radiolabeled AN distributed to the rat testis after oral and i.v. administration (Ahmed et al., 

1996a; Young et al., 1977). The testis has the capability to bioactivate AN (Abdel-Aziz et al., 

1997). Thus, CEO can either be formed in the liver and transported to the testis or be formed in 

the testis in situ. AN has been reported to interact with testicular DNA in rats treated with a 

single 46.5 mg/kg oral dose (Ahmed et al., 1992b). Covalent binding of [2,3-14C]-AN-derived 

radioactivity to testicular DNA was maximal at 0.5 hours following administration, while DNA 

synthesis in testicular tissue was decreased (80% of control). In addition, testicular DNA repair 

was increased 1.5-fold at 0.5 hour and more than threefold at 24 hours after treatment (Ahmed et 

al., 1992b). Alkylating agents have the potential to produce infertility via destruction of dividing 

primary spermatogonia (Heinrichs and Juchau, 1980). Thus, any effect of AN on male 

reproductive tissue may be due to its interference with testicular DNA synthesis and repair 

processes. The consequence may be reproductive abnormalities as well as impact on altered 

heritability in offspring. 

 No mechanistic studies are available to elucidate the mode of action whereby AN 

induced ovarian atrophy and cysts in female mice chronically exposed by gavage to doses as low 

as 2.5 mg/kg-day (NTP, 2001). 

 The mild developmental effects associated with gestational exposure to 80 ppm AN by 

inhalation or 65 mg/kg-day by gavage (Murray et al., 1978) may be associated with the release of 

cyanide during maternal metabolism of AN. Concurrent administration of thiosulfate, a cyanide 

antagonist, was shown to protect against the malformations induced by i.p. injection of 80 mg/kg 

AN in hamsters (Willhite et al., 1981). However, Saillenfait et al. (1993) tested for relative 

developmental toxicities of eight aliphatic mononitriles and proposed that factors other than 

cyanide liberation from the nitrile may be involved, since teratogenicity of inhaled aliphatic 

mononitriles in rats could not be predicted based on the presence of a vinyl moiety in their 

molecular structure. 

4.6.3.4. Hematological Effects 

Farooqui and Ahmed (1983b) conducted work to elucidate the mechanism of the 

hematological effects of AN. Their findings pointed to substantial AN-induced covalent binding 

of CEO to RBCs, GSH depletion, increase in rate of RBC metabolism, and increase in the 

formation of two metabolic intermediates, ATP and 2,3-diphosphoglycerate, that regulate the 

oxygen dissociation curve. These authors suggested that chronic exposure to AN may lead to 
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methemoglobinemia, damage to RBC membranes, and impaired delivery of oxygen to the 

tissues. 

 Oxidative stress and lipid peroxidation were also suggested as additional factors aiding in 

the destruction of RBCs, evidenced by a significant decrease of Na+,K+-ATPase activity in 

isolated RBC membranes (Farooqui et al., 1990). 

 AN-Hb adducts have been measured and used as a marker of exposure in humans. AN 

can bind to amino acid residues other than cysteine. Thus, MacNeela et al. (1992) identified the 

N-terminal cyanoethyl-valine adduct of Hb (CEVal), the formation of which may have 

implications for the efficiency of oxygen transport to the tissues. 

4.6.3.5. Immunological Effects 

Zabrodskii et al. (2000) suggested a potential mechanism of action for the AN-induced 

DTH. They found that, in mice, AN reduced the number of esterase-positive splenocytes, the 

number of antibody-producing cells, and the inflammatory response induced by injection of 

SRBCs in the paws of animals. Treatment of the animals with an esterase activity-restoring drug 

restored the paw-response completely but not the numbers of immune-competent cells. 

However, a combination of the esterase-restoring drug and a cyanide-trapping drug restored 

immune function completely. Therefore, the study authors concluded that the immunotoxic 

effect of AN was due to combined inhibition of esterase and cytochrome c oxidase a3 activities. 

4.6.3.6. Covalent Binding to Sulfhydryl Groups 

The capacity of AN to bind to proteins may be an important determinant of its 

toxicological effects. AN has been shown to have high affinity for cysteine residues on proteins 

and polypeptides. There is abundant evidence that AN will bind to the cysteine-bearing 

tripeptide, GSH, even without the contribution of enzymes such as GST. As discussed in 

Chapter 3, the formation of 2-(cyanoethyl)glutathione and the appearance of 

2-(cyanoethyl)cysteine and N-acetyl 2-(cyanoethyl)cysteine in the urine have been taken as an 

indication of the ready interaction of AN and GSH. However, the presence of excess AN can 

cause GSH to become depleted. This will tend to channel AN into an oxidative reaction with 

CYP2E1 and result in formation of CEO and other products. Perturbing the balance between 

detoxification of AN with GSH and oxidation by CYP2E1 (for example, by blockade of 

CYP2E1) may facilitate the binding of AN to other cysteine-bearing proteins when GSH levels 

are low. 

 AN also has been shown to bind to the cysteine 186 residue of the enzyme CAIII in rat 

liver in vivo. Nerland et al. (2003) pointed out that this enzyme may play a role in protecting 

cells from oxidative stress. AN binding to this component, with possible conformational 

changes in tertiary structure and functionality, might abolish this protective ability and increase 

cell vulnerability to oxidative stress. In a similar study, Nerland et al. (2001) demonstrated that 
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AN can bind also with high selectivity to cysteine 86 of GSTM1. However, in this case, the 

binding did not exert an effect on the catalytic activity of the enzyme. 

4.7. EVALUATION OF CARCINOGENICITY—SYNTHESIS OF HUMAN, ANIMAL, 

AND OTHER SUPPORTING EVIDENCE, CONCLUSIONS ABOUT HUMAN 

CARCINOGENICITY, AND LIKELY MODE OF ACTION 

4.7.1. Summary of Overall Weight of Evidence 

Following EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), AN is 

“likely to be carcinogenic to humans,” based predominantly on consistent results showing that 

lifetime inhalation or oral exposure caused a statistically significantly increased incidence of 

tumors at multiple tissue sites in rats and mice. The most consistently observed tissue sites with 

tumors were the brain, forestomach, Zymbal gland in the ear canal in rats, and forestomach and 

ocular Harderian gland in mice. In addition, rats exposed during gestation and throughout 

adulthood showed higher incidences of brain tumors, Zymbal gland tumors, and extrahepatic 

angiosarcomas than did rats with exposure throughout adulthood only; hepatomas, which were 

not observed in exposed adult rats, were reported in rats exposed during gestation and throughout 

adulthood. Epidemiological studies of AN-exposed workers provide no strong evidence that 

mortality from any type of cancer is causally related to occupational exposure to AN, but limited 

evidence from the largest and best-designed epidemiologic study (Blair et al., 1998) indicated 

that workers with the longest duration and highest exposures to AN had a small, but statistically 

significant, increased risk for dying from lung cancer. 

 The available weight of evidence is adequate for a direct mutagenic mode of action 

involving DNA modification by reactive metabolite CEO. Other modes of action, including 

oxidative stress and inhibition of intercellular communication, may also contribute. Currently, 

no mechanistic explanations are available for the fact that AN induces brain tumors in rats but 

not in mice, although this may be related to higher CEO levels in rat brains and the more rapid 

clearance of CEO in mice than in rats (see Section 3.2). Mouse liver GST has a greater capacity 

for conjugating AN or CEO than rat liver GST (see Section 3.3.2). The modes of action 

involved in tumors induced by AN at other sites in animals (e.g., forestomach squamous 

epithelium in rats and mice and Zymbal gland in rats) have not received adequate investigation. 

 The mutagenic mode of action for AN-induced tumors is considered to be relevant to 

humans.The metabolism of AN in rats and humans is similar and there is evidence for 

mutagenicity of AN in exposed humans. 

4.7.2. Synthesis of Human, Animal, and Other Supporting Evidence 

 Section 4.1.2.2 presents an historical perspective and evaluation of the epidemiologic 

studies of possible relationships between occupational exposure to AN and elevated risks for 

cancer. The early studies were of small cohorts with limited follow-up periods and limited 
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assessment of actual exposures. Elevations for incidence and death from lung cancer and 

incidence of prostate cancer were sufficiently consistent among the early studies to provoke the 

conduct of several additional studies over a 20-year period. The later studies had increased 

power due to increased number of workers, longer periods of follow-up, increased sophistication 

and quantification of exposure assessments, or inclusion of information on smoking habits. 

Small excess risks for lung and prostate cancer were identified in a few of these studies, but 

consistently and statistically significantly elevated risks were not observed across studies (see 

Tables 4-3 and 4-9). Other studies reported small excess risks for other types of cancer (e.g., 

bladder, colon, and brain cancers), but these findings were even less consistent across studies 

than the findings for lung and prostate cancer (see Tables 4-8, 4-11, 4-12 and 4-13). 

 The most informative study in the later generation of studies was the large, welldocumented study by Blair et al. (1998). This study was strong because it examined a large 

cohort and attempted to adjust for known problems with earlier studies by quantifying exposures, 

estimating the effect of smoking, and using an internal control group of unexposed workers. The 

AN-exposed cohort as a whole experienced fewer deaths from lung cancer than those expected 

from the experience of the general U.S. population (probably reflecting a healthy worker effect), 

but when the exposed workers were grouped into quintiles of cumulative exposure, the lung 

cancer rate in the highest quintile of exposure (>8 ppm-years) for those who were followed for 

20 or more years was about two times the rate in the unexposed group of workers (RR = 2.1; 

95% CI = 1.2–3.8). Conclusions regarding the association between AN exposure and other 

cancer types (stomach, brain, breast) are limited due to the small number of site-specific cancer 

deaths (Blair et al., 1998). 

 As concluded in Section 4.1.2.2, there is no strong evidence from the body of 

epidemiologic studies that mortality from any type of cancer is causally related to exposure to 

AN at the levels that have been measured in workplaces utilizing this chemical. However, based 

on these epidemiology studies, there is suggestive evidence of a possible association between 

occupational exposure to AN and increased risk of lung cancer. 

 In rat and mouse bioassays, AN has been demonstrated to be a multiple-site carcinogen. 

Chronic oral exposure to AN induced tumors in the brain or spinal cord, Zymbal gland in the ear 

canal, the forestomach, and, to a lesser degree and less consistently, the female mammary gland, 

tongue, and intestine in several oral bioassays with F344 rats (Johanssen and Levinskas, 2002b; 

Biodynamics, 1980c) and Sprague-Dawley rats (Johannsen and Levinskas, 2002a; Quast, 2002; 

Biodynamics, 1980a, c; Quast et al., 1980a). In addition, lifetime inhalation cancer bioassays 

with Sprague-Dawley rats found exposure-related increased incidences of brain tumors, Zymbal 

gland tumors, intestinal tumors, malignant mammary gland tumors, and tongue tumors (Dow 

Chemical Co., 1992a; Maltoni et al., 1988, 1977; Quast et al., 1980b). Strong evidence exists for 

dose-response relationships for the carcinogenic responses in the CNS, Zymbal gland, and the 

forestomach of rats, especially in the lifetime drinking water studies with multiple exposure 
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levels. The lowest drinking water concentrations associated with significant increased incidence 

of forestomach and brain tumors were 3 and 30 ppm, respectively, corresponding to daily doses 

of about 0.3 and 2.5 mg/kg-day in F344 rats (Johanssen and Levinskas, 2002b; Biodynamics, 

1980c). 

With chronic inhalation exposure of Sprague-Dawley rats, increased incidences of brain 

tumors occurred at air concentrations of 20 and 80 ppm, whereas the incidences of Zymbal gland 

tumors, mammary gland adenocarcinomas and intestinal tumors were increased only at the 

80 ppm level (Quast et al., 1980b). In mice, a single gavage lifetime bioassay identified the 

forestomach and the Harderian gland as sites of tumor development, but elevated incidences of 

brain, Zymbal gland, or mammary gland tumors were not found (NTP, 2001). A significant 

increase in lung tumors was found in the female mid-dose group of exposed mice but not in the 

female high-dose group or in any of the male exposed groups. NTP (2001) concluded that the 

evidence for carcinogenicity in the mouse lung was equivocal; this conclusion is consistent with 

the small magnitude of the increase, lack of a monotonic dose-response relationship, and lack of 

a demonstrated carcinogenic response in exposed male mice. No consistent evidence was found 

for carcinogenicity in the rat lung or the prostate or bladder tumors in rats or mice. 

 Results from two rat studies provide evidence that chronic exposure starting during earlylife periods may result in increased susceptibility to the carcinogenicity of AN, compared with 

lifetime exposure during adulthood only (see Sections 4.2.2.2.2 and 4.2.1.2.8 for more details). 

The possible human relevance of the rodent carcinogenic responses to AN is not fully 

understood. The brain is the only organ for which there is a direct human counterpart among 

rodent organs showing strong carcinogenic responses to AN, but the forestomach squamous 

epithelium and Zymbal gland have analogous tissues in humans. Although humans do not have 

a forestomach, the human esophagus is lined with squamous epithelial cells morphologically 

similar to those in which tumors develop in rats, with the exception that the rat cells are 

keratinized and the human cells are not (Cohen, 2004; Wester and Kroes, 1988). Likewise, 

although humans do not have a Zymbal gland, a sebaceous gland in the ear canal, they do have 

sebaceous glands. In contrast, humans and other primates do not have tissue analogous to the 

Harderian gland, an ocular gland in rodents that secretes lipids and porphyrins (Cohen, 2004; 

Sheldon, 1994; Albert et al., 1986). However, given that mutagenic modes of carcinogenic 

action are plausible for AN or its metabolites (see Section 4.6.3), formation of tumors in these 

organs may be indicative of a more generic carcinogenic hazard (Cohen, 2004). Chemicals with 

a mutagenic mode of action are frequently observed to cause cancers in many sites in one 

species, as well as to have different sites of tumor formation in different species. Therefore, it is

reasonable to consider the tumor responses in these rodent organs as indicators of AN-induced 

carcinogenicity in humans. In addition, the National Academy of Sciences (NAS) (2008) in its 

Science and Decisions: Advancing Risk Assessment, stated on page 134 that “...the target organ 

in a rodent species, such as the forestomach or Zymbal gland, may not have an exact human 
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counterpart. However, the presence of carcinogenic action in tissues for which there is no 

correspondence in humans or that may be regulated differently in humans does not mean that the 

toxicity or tumor finding in animals is irrelevant. That the rodent tissue is sensitive to the 

toxicant signifies that the toxicant MOAs operate in a mammalian system that has characteristics 

in common with similar or even not obviously related tissues in humans or human 

subpopulations...it is typically impossible to rule out the relevance of an effect seen in a 

particular rodent tissue unless there is detailed mechanistic information on why humans would 

not be affected...In general, tissues that are responsive to a toxicant should be considered 

relevant to human risk assessment unless mechanistic information demonstrates that the 

processes occurring in the tissues could not occur in humans.” 

4.7.3. Mode-of-Action Information 

 The U.S. EPA (2005a) Guidelines for Carcinogen Risk Assessment defines mode of 

action as a sequence of key events and processes, starting with the interaction of an agent with a 

cell, proceeding through operational and anatomical changes, and resulting in cancer formation. 

Mode of action is distinct from “mechanism of action,” a term that implies greater understanding 

and description of events, including those at the molecular level. Toxicokinetic processes 

leading to the formation or distribution of the active agent (i.e., parent material or metabolite) to 

the target tissue are not part of the mode of action. Examples of possible modes of carcinogenic 

action include mutagenic, mitogenic, anti-apoptotic (inhibition of programmed cell death), 

cytotoxic with reparative cell proliferation, and immunologic suppression. 

AN has been demonstrated to be a multiple-site carcinogen in rats and mice, inducing 

tumors in the forestomach, brain, and Zymbal gland in two strains of rats following chronic oral 

exposure; in the forestomach and Harderian gland in a mouse strain following chronic oral 

exposure; and in the forestomach, brain, Zymbal gland, intestinal tract, and tongue in one rat 

strain following chronic inhalation exposure. Carcinogenic responses have also been reported 

less consistently across studies in the female mammary gland and small intestine. Several 

hypothesized modes of action by which AN causes cancer in the brain of rats have been 

investigated to varying degrees and are discussed within the context of the modified Hill criteria 

of causality as recommended in the most recent Agency guidelines (U.S. EPA, 2005a). These 

discussions are followed by discussion of possible modes of action involved in the development 

of forestomach tumors and hepatomas in rats and lung cancer in humans. Modes of action by 

which AN may induce tumors in the Zymbal gland, Harderian gland, mammary gland, and 

tongue have not been investigated. The generic mutagenic modes of action probably apply to 

these organs also, unless there is information to indicate otherwise. 
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4.7.3.1. Hypothesized Mode of Action: Direct Mutagenic Mode-of-Action 

Key Events 

This mode of action hypothesizes that AN is first activated by CYP2E1 (mostly in the 

liver but also at other sites, such as intestinal mucosa or squamous epithelium of the 

forestomach) to its reactive metabolite, CEO. CEO is then distributed to target organs (e.g., rat 

brain) where it reacts with DNA, forming DNA adducts. DNA adduct formation results in 

genetic damage, especially the formation of point mutations. Other types of DNA damage by 

CEO are also observed in vivo, including DNA strand breaks, SCEs, and MN formation. 

Mutagenicity is a well-established cause of carcinogenicity. 

AN 

 ↓ CYP 2E1 

 CEO 

 ↓

 Interaction with DNA 

 

 ↓

Gene mutation for tumor initiation 

Following these key events, tumor growth may be promoted by any one or combination 

of a number of cell-signaling pathways, leading to enhanced cell proliferation or inhibition of 

programmed cell death. 

4.7.3.2. Experimental Support for the Hypothesized Mode of Action 

4.7.3.2.1. Strength, consistency, specificity of association. The evidence that supports a 

mutagenic mode of action is strong and consistent (as summarized in Table 4-53). In addition to 

positive findings in blood lymphocytes, buccal mucosal cells, and sperm in five epidemiologic 

studies, DNA alkylation by AN was found in numerous tissues in rats or mice (brain, liver, 

testes, forestomach, colon, kidney, bladder, and lung) treated with a single dose of AN. AN or 

its reactive metabolite CEO yielded positive results in in vitro mutation assays using bacteria, 

fungi, and insects, as well as animal and human cell cultures. The mutagenicity/genotoxicity is 

specific and occurs in the absence of cytotoxicity or other overt toxicity. Although the temporal 

relationship of adduct formation and mutagenicity with carcinogenicity has not been adequately 

explored, these effects are seen in short-term assays (before tumor formation). Dose-response 

concordance is observed between mutagenic doses in vivo and tumorigenic doses in rats and 

mice. A mutagenic mode of action also comports with notions of biological plausibility and 

coherence because AN is metabolized to an epoxide intermediate. Such agents are generally 

capable of forming DNA adducts, which in turn have the potential to cause genetic damage, 
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including mutations, and mutagenicity, in its turn, is a well-established cause of carcinogenicity. 

This chain of key events is consistent with current understanding of the biology of cancer. 

The possible association between a direct mutagenic action of CEO, the epoxide 

metabolite of AN, and brain tumors in rats is supported by the detection of CEO in rat brains 

after oral administration of 10 mg/kg AN to rats (Kedderis et al., 1993b), reported binding of 

CEO to brain DNA after oral administration of [2,3-14C]-AN to rats (Farooqui and Ahmed, 

1983a), results from studies of in vitro DNA reactivity, positive results from in vitro tests of 

mutagenicity and cytogenetic effects, and positive results from in vivo studies of DNA damage 

and repair assays and other genotoxic endpoints in rats and mice. Studies that demonstrate the 

mutagenicity of AN in occupational exposed workers are also available. 

In the following subsections, experimental evidence supporting the mutagenic mode of 

action of AN using different test systems is summarized. 

In vitro DNA binding

AN itself reacts very slowly with DNA in vitro at very high, nonphysiological 

concentrations (>1 M) (Solomon et al., 1984), but CEO forms different adducts in vitro with 

DNA (Solomon et al., 1993; Yates et al., 1993) or nucleotides (Yates et al., 1994) more rapidly 

(see Section 4.5.1.2.1). When calf thymus DNA was incubated with CEO for 3 hours (Solomon 

et al., 1993), the main adducts formed included N7-(oxoethyl)guanine, N3-(2-hydroxy-2-carboxyethyl)deoxyuridine, and smaller amounts of adenine and thymine adducts. Yates et al. (1993) 

also identified the formation of N3-(2-cyano-2-hydroxylethyl)deoxythymidine when CEO was 

incubated with calf thymus DNA in vitro. 

Mutations in bacteria

In short-term tests with bacteria, AN induced mutations in a majority of test systems, 

often requiring the presence of exogenous metabolic systems (Table 4-53). AN induced 

mutation in S. typhimurium strains TA 1530, 1535, 1538, 1937, and 1950 with strong response 

when AN was tested in the vapor phase in the presence of S9. AN induced a weak response for 

TA 98, 100, and 1978. Thus, AN induced gene reversion mainly by base substitution and 

induced lower mutagenic activity with strains reversed by frameshift mutation. AN also 

produced a dose-related increase in the number of revertant colonies compared with untreated 

bacteria in E. coli WP2 (which is DNA repair proficient), WP2uvrA (which lacks excision 

repair), and WP2 uvrApolA (which lacks both excision repair and DNA polymerase 1) without a 

need for S9 fraction (Venitt et al., 1977). 

Mutations in fungi and Drosophila 

As shown in Table 4-53, AN induced mitotic gene conversion in S. cerevisiae JD1 

(Brooks et al., 1985). AN also induced sex chromosome loss in the adult female Drosophila
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ZESTE system (Osgood et al., 1991), as well as somatic recombination and mutation in hatching 

Drosophila with exposure in the larvae stage (Vogel, 1985; Würgler et al., 1985). 

Mutations in mammalian cell culture 

AN also induced mutations in mammalian cells in vitro. In the mouse lymphoma cell 

assay, AN induced forward mutations at the Tk+/– locus in most assays (Table 4-53). In human 

lymphoblastoid Tk6 cells devoid of CYP450 activity, AN induced mutations at the Tk locus only 

in the presence of an exogenous S9 metabolic system (Crespi et al., 1985), and CEO was 

effective at 10-fold lower concentrations than AN (Recio and Skopek, 1988a, b). 

Characterization of the Tk– mutants in human lymphoblastoid Tk6 cultures by Recio and 

Skopek (1988b) identified two classes of CEO-induced Tk–/– mutant phenotypes that differed in 

their growth rates. CEO-induced predominantly Tkn mutant with normal growth rate and Tks

with slower growth rate. Southern blot analysis of CEO-induced Tkn mutants indicated that the 

majority of these mutants were below the detection limit of <2 kb. Thus, CEO-induced 

alterations are relatively small DNA alterations. Recio and Skopek (1988a) suggested that CEO 

induced Tkn mutants resulted from point mutations or small insertions/deletions that occurred 

during the replication or repair of CEO-modified DNA. Kodama et al. (1989) conducted 

cytogenetic analyses of eight CEO-induced Tks mutant clones reported in Recio and Skopek 

(1988a, b). A visible abnormality on chromosome 17 was found in one of the CEO-induced Tks

mutants and was marked by duplication of the long arm of chromosome 17, with break points at 

q11 and q21. The latter break point was close to the Tk locus, suggesting that the observed 

aberration might be associated with Tk–/– phenotype. 

CEO also induced mutations at the hprt locus in Tk6 cells (Recio and Skopek, 1988a). 

Characterization of the hprt mutations by cDNA sequencing analysis indicated that several hprt

mutations were formed. The majority of CEO-induced mutations were the specific loss of exons 

from the coding region of hprt. Remaining mutants were single base substitutions (point 

mutation) resulting from amino acid changes (A:T base pairs and G:C base pairs). 

Cytogenetic effects in vitro 

Additional evidence of mutagenicity included AN-induced cytogenetic changes, such as 

SCEs or CAs in a majority of assays with CHO or CHL cells (Natarajan et al., 1985; VedBrat 

and Williams,1982; Ishidate et al., 1981) and human lymphocytes in vitro (Perocco et al., 1982) 

but not in epithelial-like cells from rat liver (RL4 cell line) (see Table 4-53). AN also induced 

DNA single-strand breaks in rat hepatocytes (Bradley, 1985) and CHO cells (Douglas et al., 

1985). Of note is that AN induced SCEs and DNA single-strand breaks in human bronchial 

epithelial cells in culture without S9 (Chang et al., 1990), indicating that human bronchial 

epithelial cells have the metabolic capabilities to activate AN to CEO. 
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DNA repair in vitro 

In DNA repair assays, neither AN nor CEO induced UDS in cultured rat hepatocytes 

(Butterworth et al., 1992; Probst and Hill, 1985; Williams et al., 1985) (as measured by 

incorporation of [3H]-thymidine and autoradiographic techniques) or in HeLa cells with or 

without the presence of S9 (using liquid scintillation spectrometry) (Martin and Campbell, 1985). 

However, IPCS (1985) concluded that the rat hepatocyte autoradiographic UDS assay was too 

insensitive for determination of genotoxicity of the eight tested carcinogens, including AN. On 

the other hand, CEO, but not AN, induced UDS in human mammary epithelial cells in vitro 

(Butterworth et al., 1992). 

DNA repair in vivo

Unscheduled DNA repair activity was detected by following the time course of 

[

3H]-thymidine incorporation into DNA isolated from lung (Ahmed et al., 1992a), testis (Ahmed 

et al., 1992b), and gastric tissue (Ahmed et al., 1996b; Abdel-Rahman et al., 1994a) after 

exposure of Sprague-Dawley rats to single oral doses of 46.5 mg/kg AN. In a study by Hogy and 

Guengerich (1986), UDS was found in the liver of male F344 rats administered 50 mg/kg AN or 

6 mg/kg CEO i.p. but was not found in the brain. The absence of detected UDS in the brain 

could reflect the absence of DNA damage. Alternatively, this absence could reflect differences 

in the repair rate of CEO-DNA adducts and could account for the observed target organ 

specificity of AN in rat brain but not liver. Since the difference in DNA repair rates in brain and 

liver is well known (Kleihues et al., 1977), the second explanation may be more sound. In 

another study, UDS activity was not detected by autoradiographic techniques following 

incubation of primary cultures of hepatocytes or spermatocytes from F344 rats given single oral 

doses of 75 mg/kg or five daily doses of 60 mg/kg-day with [3H]-thymidine (Butterworth et al., 

1992). This difference in results from those by Hogy and Guengerich (1986) was probably due 

to differences in methodology. 

DNA binding in vivo 

 Several studies examining the amounts of radioactivity in DNA fractions of tissues 

following acute in vivo exposure of rats to radiolabeled AN provide evidence of in vivo DNA 

reactivity of AN or its metabolites. Maximal amounts of radioactivity covalently bound to 

hydroxyapatite-purified DNA from the liver, stomach, and brain showed the following order 

24 hours after male Sprague-Dawley rats were given single oral doses of 46.5 mg/kg 

[2,3-14C]-AN: brain (≈120 pmol AN equivalent/mg DNA) > stomach (≈80 pmol/mg) > liver 

(≈25 pmol/mg) (Farooqui and Ahmed, 1983a). Other studies from the same group of 

investigators found elevated covalent binding of radioactivity in gastric, testicular, and lung 

DNA from similarly exposed rats (Abdel-Rahman et al., 1994b; Ahmed et al., 1992a, b). The 

results from these studies provided some evidence of associations between covalent DNA 
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binding following acute exposure and sites of tumor development following chronic exposure. 

The methods to isolate DNA in these studies may not have been stringent enough to exclude 

covalent binding of radiolabel to proteins (Whysner et al., 1998b; Geiger et al., 1983); however, 

the degree to which these alternative processes may have contributed to the measured amounts of 

radioactivity in the DNA fractions is unknown. When 0.6 mg/kg [2,3-14C]-CEO was 

administered to one F344 rat i.p., covalent binding to both liver and brain protein was found, but 

no covalent binding to both liver and brain nucleic acids could be detected at the level of 

0.3 alkylations per 106 base (Hogy and Guengerich, 1986). However, the N7-(2-oxoethyl) 

guanine adduct was detected in liver DNA of F344 rats treated with 6 mg/kg CEO or 50 mg/kg 

AN i.p. in the same experiment. Thus, covalent binding of CEO to DNA had to occur. No DNA 

binding was detected in the Hogy and Guengerich (1986) study, presumably due to the small 

DNA sample from one rat, low CEO concentration (0.6 vs. 6 mg/kg CEO), stringent DNA 

isolation procedure, and overcorrection of protein binding. 

DNA adducts in vivo 

 Limited attempts to detect CEO-DNA adducts in brain tissues following acute in vivo 

exposure protocols have been largely unsuccessful, but in vitro studies indicate that the 

formation of other DNA adducts from AN and its metabolites are possible (Yates et al., 1994; 

Solomon et al., 1993; Hogy and Guengerich, 1986; Solomon et al., 1984). N7-(2-oxoethyl)-

guanine, a CEO-DNA adduct formed in vitro following incubation of calf thymus DNA with 

CEO, was detected in DNA isolated from the livers of male F344 rats, following single i.p. 

administration of doses of 50 mg/kg AN or 6 mg/kg CEO, but was found only equivocally at 

detection limit in DNA isolated from the brains of exposed rats (Hogy and Guengerich, 1986). 

In another study, 7-(2-cyanoethyl)guanine and O6

-(2-cyanoethyl)deoxyguanosine adducts were 

not detected in DNA isolated from the liver or brain of male F344 rats given s.c. or i.v. injections 

of 50 or 100 mg/kg AN (Prokopczyk et al., 1988). The DNA samples were analyzed for the 

presence of the two adducts using HPLC with fluorescence detection. The detection limits were 

20 μmol/mol guanine for 7-(2-cyanoethyl)guanine and 15 μmol/mol guanine for O6-(2-cyanoethyl)deoxyguanosine. These detection limits may be not sensitive enough. More importantly, 

these two DNA adducts were not formed from incubation of CEO with calf thymus DNA in

vitro. Hence, the limitations of these studies were that not all the major adducts formed in in 

vitro incubation of CEO with DNA were measured. 

As discussed previously, the main adducts found after 3 hours of incubation of CEO with 

calf thymus DNA were N7

-(oxoethyl)guanine, N3-(2-hydroxy-2-carboxyethyl)deoxyuridine 

(Solomon et al., 1993), and N3

-(2-cyano-2-hydroxylethyl)deoxythymidine (Yates et al., 1993). 

Yet only N7-(oxoethyl)guanine has been measured in available studies. Thus, it is highly likely 

that the actual adducts formed from interaction of CEO with brain DNA have not yet been 

looked for. It is also likely that the analytical methods used to measure DNA adducts in 
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available studies were not sensitive enough for their detection. In addition, DNA adducts were 

measured only in single-dose studies not repeated-dose studies. 

DNA damage in rats and mice 

 Evidence of DNA damage after AN exposure in rats and mice is available. Comet assays 

showed DNA damage in various tissues in both rats and mice exposed to AN (Sekihashi et al., 

2002). Single i.p. injections of 20 mg/kg AN induced DNA damage in forestomach, bladder, and 

brain but not in colon, liver, kidney, or bone marrow of ddY mice, whereas single doses of 

30 mg/kg induced DNA damage in forestomach, colon, kidney, bladder, and lung but not in 

brain or bone marrow of Wistar rats (Sekihashi et al., 2002). 

 Increased frequencies of MN in bone marrow were found in Sprague-Dawley rats, 

following i.v. injection of 98 or 124 mg/kg AN (Wakata et al., 1998) but were not found in 

Sprague-Dawley rats following administration of oral doses up to 40 mg/kg (Morita et al., 1997) 

or in male CD-1 mice following administration of oral, i.p., or i.v. doses up to 45 mg/kg (Morita 

et al., 1997). Increases in CAs in bone marrow cells were not found in Swiss albino mice 

exposed to oral doses up to 20 mg/kg-day for 4, 15, or 30 days (Rabello-Gay and Ahmed, 1980); 

in Sprague-Dawley rats given 16 daily doses of 40 mg/kg-day (Rabello-Gay and Ahmed, 1980); 

in NMRI mice given single i.p. doses of 30 mg/kg (Leonard et al., 1981); or in ICR mice 

exposed in inhalation chambers to 20 or 100 mg/m3 for 5 days (Zhurkov et al., 1983). In 

contrast, Fahmy (1999) reported that increased CAs occurred in spermatocytes of Swiss mice 

following single oral doses of 15.5 or 31 mg/kg AN or five daily doses of 7.75 mg/kg and in 

spleen cells and bone marrow cells after a single oral dose of 7.75 mg/kg. 

Dominant lethal mutations in rats and mice 

 Dominant lethal mutations were not increased by treating male NMRI mice with single 

i.p. doses of 30 mg/kg AN (Leonard et al., 1981) or male F344 rats with five oral doses of 

60 mg/kg-day AN (Working et al., 1987), indicating no AN-induced germ cell mutations. 

Chromosomal mutations in humans

There is sufficient evidence of AN-induced mutagenicity in occupationally exposed 

workers. Fan et al. (2006) reported significant increase in the occurrence of MN in buccal 

mucosal cells of workers exposed to 0.52 or 1.99 mg/m3 AN for an average duration of 15.7–

17.2 years and significant increase in MN in peripheral blood lypmphocytes in workers exposed 

to 1.99 mg/m3

 AN for an average of 17.2 years. The workers in the Fan et al. (2006) study were 

exposed to higher concentrations than those in a previous study by Srám et al. (2004), in which 

the exposure concentration range was 0.05–0.3 mg/m3

 AN, thus explaining the negative results 

reported in Srám et al. (2004) or in other studies where exposure concentrations were not 

reported. Evidence of CAs in AN-exposed workers was also reported by Borba et al. (1996), and 
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DNA strand breakage and sex chromosome aneuploidy in the sperm of AN-exposed workers 

were reported by Xu et al. (2003). In addition, Beskid et al. (2006) reported an increase in the 

number of reciprocal translocations and the relative number of insertions in the chromosomes of 

cultured lymphocytes of AN-exposed male workers. 

 Therefore, the overall in vitro and in vivo evidence in support of the direct mutagenicity 

of CEO is strong, consistent, and specific. 

4.7.3.2.2. Dose-response concordance. Chronic exposures of rats to AN in drinking water 

concentrations ≥30 ppm (≥2.5 mg/kg-day) or air concentrations ≥20 ppm were associated with 

significantly increased incidences of brain tumors. No published studies are available that have 

measured CEO-DNA adducts or other endpoints pertinent to mutagenicity in brain tissues 

following acute-, subchronic-, or chronic-duration oral or inhalation exposures of rats to AN, 

mainly because in vivo DNA adduct studies were conducted before the Solomon et al. (1993) 

and Yates et al. (1993) studies that reported on DNA adducts formed from CEO in vitro. Hence, 

these DNA adduct studies were not looking for the adducts formed in vitro from CEO. The 

available studies that looked for CEO-DNA adducts in brain or other tissues involved single i.p. 

(Hogy and Guengerich, 1986), s.c., or i.v. (Prokopczyk et al., 1988) administration protocols at 

dose levels (50 or 100 mg/kg-day AN) that were higher than the chronic oral doses associated 

with brain tumors in rats (0.3 to 40 mg/kg-day). However, no repeated-dose studies have been 

conducted for detection of DNA adducts. The single oral dose of 46.5 mg/kg used in studies that 

demonstrated UDS in the lung, gastric tissue, and testis of treated Sprague-Dawley rats (AbdelRahman et al., 1994b; Ahmed et al., 1992a, b) was comparable to the high dose of 40 mg/kg-day 

used in studies by Friedman and Beliles (2002), providing evidence that the dose that caused 

DNA repair was carcinogenic. 

 A study in mice by Fahmy (1999) showed that increased CAs occurred in spermatocytes 

of Swiss mice, following single oral doses of 15.5 or 31 mg/kg AN or five daily doses of 

7.75 mg/kg, and in spleen cells, and bone marrow cells after a single oral dose of 7.75 mg/kg. 

Fahmy (1999) also reported increases in SCEs in bone marrow cells of male Swiss mice after a 

single i.p. dose of 7.5 or 10 mg/kg of AN. These doses were all in the range of, or comparable 

to, the tumorigenic doses in B6C3F1 mice of 2.5–20 mg/kg-day in a 2-year bioassay. 

 The single doses employed by Sekihashi et al. (2002) that demonstrated DNA damage in 

forestomach, colon, kidney, bladder, and lung of rats treated with 30 mg/kg i.p. and in colon, 

bladder, lung, and brain of male ddY mice treated with 20 mg/kg i.p. were also within the range 

of tumorigenic doses in the 2-year bioassay. 

 Therefore, the doses that demonstrated DNA damage or chromosome mutations in singledose studies are in concordance with tumorigenic doses in chronic bioassays. 
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4.7.3.2.3. Temporal relationships. Currently available examinations of DNA damage, 

chromosome mutations, SCEs, UDS, or CEO-DNA adducts in brain or other tissues are 

restricted to single-dose acute administration protocols. Studies designed to examine temporal 

relationships of key events, such as the presence of CEO-DNA adducts in brain tissue, are not 

available. Nevertheless, results from the rat bioassays indicated that most AN tumors occur after 

12–14 months of exposure or longer. Thus, the observed mutagenic effects of AN occurred 

before tumor formation and provide support for a mutagenic mode of action. 

4.7.3.2.4. Biological plausibility and coherence. The hypothesis that the key primary event in 

AN induction of brain tumors is the formation of CEO-DNA adducts that lead to mutations that 

initiate tumor formation is plausible based on in vitro and in vivo evidence for the direct 

mutagenicity of the AN metabolite, CEO. However the available data do not establish that this is 

the only mode of action by which AN may induce brain tumors in rats. Notably lacking in the 

database are studies designed to detect a range of DNA adducts or mutations associated with 

tumor initiation in brain tissues following prolonged oral or inhalation exposures at levels that 

induced brain tumors in the chronic rat bioassays. In vitro studies by Solomon et al. (1993) 

reported that CEO interacted with calf thymus DNA and, in addition to N7-(oxoethyl)guanine, 

formed N3-(2-hydroxy-2-carboxyethyl)deoxyuridine from an initial cytosine adduct. Other 

adenine and thymine adducts were also formed. Yates et al. (1993) demonstrated that CEO 

reacted calf thymus DNA formed N3-(2-cyano-2-hydroxylethyl)-deoxythymidine. Yet, only 

N

7

-(oxoethyl)guanine has been measured in exposed rats in available studies (Hogy, 1986). 

The available data do not provide an explanation of why AN induces brain tumors in 

F344 and Sprague-Dawley rats but not in B6C3F1 mice. Kedderis et al. (1993b) reported that 

when male F344 rats and male B6C3F1 mice were administered 10 mg/kg AN in water by 

gavage, higher CEO concentrations were found in blood and brains of rats than in mice (13% 

higher in blood, 23% higher in brain). Higher CEO concentrations in rat brain may at least 

partially explain why tumors were only found in the brains of exposed rats but not in mice. In 

addition, the clearance of CEO in mice was more rapid than in rats (Roberts et al., 1991). It may 

also be that mice are more efficient in repairing DNA damage since DNA damage has been 

detected in the brain of ddY mice exposed to 20 mg/kg AN, i.p. (Sekihashi et al., 2002). It has 

been noted that the B6C3F1 mouse is generally insensitive to chemically induced neurogenesis in 

NTP carcinogenesis bioassays (Radovsky & Mahler,1999). 

The difference in susceptibility to AN induction of brain tumors between mice and rats is 

similar to that observed for glycidol, an aliphatic epoxide structurally similar to CEO (Irwin et 

al., 1996). Glycidol is a direct acting alkylating agent, which induces tumors at a variety of sites 

in both rats and mice. However, although significant induction of gliomas was observed in both 

sexes of F344 rats after glycidol treatment, no brain tumors were induced in B6C3F1 mice. 

Ethylene oxide also shows a similar pattern of tumorigenesis, inducing brain tumors in both 
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sexes of exposed rats (Garmin et al., 1985; 1986), but no brain tumors in exposed mice (NTP, 

1987). Thus, induction of brain tumors in rats but not in mice by known genotoxic carcinogenic 

appears to reflect primarily a species difference in inherent susceptibility to brain tumorigenesis. 

There have been no investigations to attempt to explain the apparent susceptibility of 

early-life plus chronic adult exposures compared with adult-only exposures. It is possible that 

mutations are established more effectively in rapidly dividing tissues such as the fetal brain, 

since the higher rate of cell division increases the number of cells in S phase (Slikker et al., 

2004), which tends to make the cell population more vulnerable to the genotoxic effects of 

chemicals. It is also possible that the lack of key DNA repair mechanisms in embryonic tissues 

may be involved. However, DNA repair was not found in adult rat brain after administration of 

6 mg/kg CEO i.p. (Hogy and Guengerich, 1986). It would appear that the rapid cell division in 

earlier stages of development is a determining factor for the greater mutagenic and subsequent 

carcinogenic sensitivity of perinatal life (Slikker et al., 2004). 

 Data for another chemical, ethylene oxide, that causes brain tumors (gliomas) in rats 

show a different accumulation pattern for N7

-(2-oxoethyl)guanine adducts than that observed 

following i.p. administration of AN or CEO. In rats exposed to 500 ppm ethylene oxide for 

1 day, higher levels of N7

-(2-oxoethyl)guanine adducts were detected in DNA from brain than in 

DNA from liver (Walker et al., 1990), whereas N7-(2-oxoethyl)guanine adducts were detected in 

brain at detection limit and only at low levels in the liver of rats given single i.p. injections of 

50 mg/kg AN or 6 mg/kg CEO (Hogy and Guengerich, 1986). Whysner et al. (1998b) suggested 

that these and other results indicated that glioma formation from chronic exposure to AN may 

not involve the formation of N7

-(2-oxoethyl)guanine adducts; however, several alternative 

explanations are possible. The lack of unequivocal detection of CEO-DNA adducts in rat brain 

may indicate that the detection limits of the methods used were not sensitive enough. More 

sensitive methods of detection, such as liquid chromatography-mass spectrometry (Poirier, 

2004), have not been used in AN-induced DNA adduct studies. Alternatively, the stringent 

methods used to isolate purified DNA (without associated proteins) in the experiments by Hogy 

and Guengerich (1986) may have caused the loss of adducts or inhibited the recovery of 

adducted DNA (Meek et al., 2003). Another possibility is that N7

-(2-oxoethyl)guanine adduct 

may not be involved in mutations leading to AN-induced brain tumors, and other, as yet 

uninvestigated, DNA adducts that were reported by Solomon et al. (1993) and Yates et al. (1993) 

may be involved. Still another possibility is that CEO-DNA adducts and resultant mutations in 

target tissues may occur only after prolonged exposure to AN. Notably absent from the available 

mode-of-action database are experiments designed to detect a range of possible DNA adducts in 

target tissues following repeated oral or inhalation exposure at exposure levels producing tumors 

in the chronic bioassays. 

Guengerich et al. (1986) discussed the findings in which AN was metabolized by liver 

microsomes but not brain microsomes to form CEO. N7-(2-oxoethyl)guanine DNA adducts were 
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detected in liver but not the brain, yet AN induced tumors in the rat brain with chronic exposure 

but not in the adult rat liver. In addition, AN-induced UDS was demonstrated in rat liver but not 

brain (Hogy and Guengerich, 1986). Guengerich et al. (1986) proposed that AN was 

metabolized in the liver to CEO. Since CEO formed by liver microsomes from AN has a halflife of about 2 hours in neutral buffer, it can be transported easily via blood from liver to the 

brain. Although DNA adducts have not yet been detected unequivocally in rat brains, CEO has 

been measured in rat brains (Kedderis et al., 1993b) and shown to bind to brain DNA (Farooqui 

and Ahmed, 1983b). Liver cells are efficient in repairing DNA damage via UDS, while brain 

cells do not have this capability. This could help to explain why the rat brain is a target tissue of

AN carcinogenicity but the adult rat liver is not. It should be noted that hepatomas were found in 

rats that were exposed to AN during gestation and extending through adulthood (Maltoni et al., 

1988). It is conceivable that the rat fetal and neonatal liver do not have sufficient capability to 

repair DNA damage. 

 Meek et al. (2003) noted that there are several aspects of the development of AN-induced 

tumors that are characteristic of tumors induced by compounds or metabolites that directly 

interact with DNA. These comparisons add support to the evidence of a direct mutagenic mode 

of carcinogenic action. 

• Tumors are systemic and occur at multiple sites. Exposure-related increased incidences 

were found for forestomach tumors, CNS tumors, and Zymbal gland tumors in chronic 

oral exposure bioassays with F344 rats and Sprague-Dawley rats (which also showed 

exposure-related increased incidence of tongue tumors); for forestomach and Harderian 

gland tumors in a chronic oral exposure bioassay with B6C3F1 mice; for brain tumors, 

Zymbal gland tumors, intestinal tumors, and tongue tumors in a chronic inhalation 

exposure bioassay with Sprague-Dawley rats; and for brain tumors, Zymbal gland 

tumors, hepatomas, and extrahepatic angiosarcomas in a chronic inhalation bioassay with 

Sprague-Dawley rats exposed during gestation and extending throughout adulthood. 

Particularly noteworthy is that Zymbal gland tumors in rats commonly occur with 

carcinogens that are also mutagens. Of the 27 chemicals associated with site-specific 

tumor induction in this gland found in NTP database, 23 were mutagenic in the 

Salmonella assay. The NTP database indicated that these chemicals were multisite 

carcinogens. 

• Tumors sometimes occur at nontoxic doses or concentrations. Elevated incidences for 

CNS tumors occurred in Sprague-Dawley (Quast, 2002; Quast et al., 1980a) and F344 

(Johannsen and Levinskas, 2002b; Biodynamics, 1980c) rats chronically exposed to 

drinking water concentrations (30 or 35 ppm) that did not induce elevated incidences of 

nonneoplastic CNS lesions in interim sacrifices at 6, 12, or 18 months. 

• Tumors sometimes occur after less-than-lifetime exposure durations. In an inhalation 

study by Maltoni et al. (1977), Sprague-Dawley rats were exposed to 0–40 ppm AN via 
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inhalation for 52 weeks. The animals were then allowed to complete their natural life 

spans, with the final deaths occurring in week 136 (Maltoni et al., 1977). Gliomas were 

developed in 20 and 40 ppm males at 84 and 63.5 weeks, respectively, and not in other 

dose groups. In addition, forestomach papillomas and acanthomas (latency 103–

124 weeks) and Zymbal gland carcinomas (latency 77–102 weeks) were developed in 

exposed rats. Thus, these tumors were developed long after exposure was terminated, 

indicating the carcinogenic effect from AN exposure was not reversible. Although the 

incidence of these tumors did not reach statistical significance, development of these 

tumors does not support the hypothesis that AN-induced tumors are due to the promoting 

action of AN alone. 

• Tumors developed as early as 7–12 months following AN exposure. In the SpragueDawley chronic drinking water bioassay, the number of high-dose (300 ppm) female rats 

dying or sacrificed with CNS tumors were 1/1 during months 0–6, 5/13 during months 

7–12, 14/23 during months 13–18, and 11/11 during months 19–24 (Quast, 2002). At the 

lower exposure levels in this study (35 and 100 ppm), nearly all of the tumors in female 

rats were detected after 13 months of exposure. In all groups of exposed SpragueDawley male rats, all but one tumor were detected after 13 months of exposure (Quast, 

2002). In the F344 chronic drinking water bioassay, the time of first detection of a rat 

with a brain tumor was 481 days for male rats and 495 days for female rats, 

approximately 16 months (Johannsen and Levinskas, 2002b; Biodynamics, 1980c). In 

the three-generation reproductive toxicity study involving 46 weeks of exposure to AN in 

drinking water, brain tumors were detected in 0/19, 1/20, and 2/24 F0 breeding females 

exposed to 0, 100, or 500 ppm, respectively. In the other generations, incidences of brain 

tumors were 0/20, 1/19, and 4/17 for the F1 breeding females and 0/20, 1/20, and 1/20 for 

the F2 breeding females (Friedman and Beliles, 2002). Statistically significantly elevated 

incidences of brain tumors occurred in Sprague-Dawley rats exposed by inhalation to 

60 ppm AN during gestation and extending chronically throughout adulthood, but rats 

exposed during gestation followed by a subchronicsubchronic-duration exposure during 

adulthood showed an elevated incidence of brain tumors that was not statistically 

significant when compared only with control (Maltoni et al., 1988). The weight of the 

available evidence indicates that most AN-induced brain tumors require at least a halflifetime duration of exposure to develop, but associations with shorter durations of 

exposure have been observed, specifically in female Sprague-Dawley rats exposed to 300 

ppm in drinking water.

• The ratio of benign to malignant tumors is small. The brain tumors noted in AN-exposed 

Sprague-Dawley or F344 rats were astrocytomas, which were malignant tumors. Most of 

the Zymbal gland tumors were also malignant tumors. 
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4.7.3.2.5. Human relevance. The metabolic scheme of AN in rats and humans is similar. 

Humans are known to be able to activate AN to its reactive metabolite, CEO. As discussed in 

Section 4.5.2.1, studies that demonstrate the mutagenicity of AN in humans are available. There 

is sufficient evidence for mutagenicity of AN in exposed humans, and the direct mutagenic mode 

of action of AN-induced carcinogenicity is considered to be relevant to humans. 

4.7.3.3. Other Possible Modes of Action 

Other modes of action may contribute, along with the direct mutagenic mode of action, to 

tumorigenesis. These additional modes of action are evaluated in the following subsections. The 

results of these evaluations indicate that these modes of action are not likely to be prinicipal 

modes of action or to contribute to the carcinogenicity in a significant manner. 

4.7.3.3.1. Oxidative stress

Key events 

This mode of action hypothesizes that ROS are generated either directly from the oxidant 

or are indirectly produced via activation of endogenous sources when the oxidant or its 

metabolite is distributed to the target organ. Oxidative stress is induced. These free radical ROS 

can interact with DNA and produce DNA damage leading to gene mutation for tumor initiation. 

ROS can also interact with lipids via lipid peroxidation, resulting in cell damage. 

One of the most prevalent biomarkers of oxidative DNA damage is 8-oxodG. This DNA 

lesion has been found to produce mutations involving GC→TA transversions due to base 

mispairing and AT→CG transversions due to misincorporation during DNA synthesis (Cheng et 

al., 1992). G-C base pairs provide a common target for activating point mutations (e.g., in both 

p53 and retinoblastoma tumor suppressor genes and in the ras family of oncogenes). Thus, 

G-C base pairs in both tumor suppressor genes and oncogenes may represent a vulnerable target 

for mutation by oxidative stress (Guyton and Kensler, 1993). The induction of base changes in 

the DNA sequence of these genes may be the basis for tumor initiation by the oxidant. 

Another role that oxidants may play in carcinogenesis is tumor promotion. ROS 

generating systems are known to possess some of the biochemical actions of tumor promoters, 

such as promoting a rapid and sustained decrease in antioxidant defenses, including SOD, 

catalase, and glutathione peroxidase activities (O’Connell et al., 1986; Slaga et al., 1981). 

Tumor growth may also be promoted by oxidative stress via modification of gene expression 

through induction of gene transcription factors (e.g., NFКB or transcription factor protein [AP-1]) 

or change in DNA methylation status by ROS. Signal transduction pathways, including 

AP-1 and NFКB, are known to be activated by ROS, and they lead to the transcription of genes 

involved in cell growth regulatory pathway. Oxidative DNA damage can also result in DNA 

hypomethylation by interfering with the ability of methyltransferases to interact with DNA, 

allowing the expression of normally quiescent genes and promoting tumor growth. ROS can 
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also induce the release of calcium from intracellular stores, resulting in the activation of kinases, 

including PKC (Larsson and Cerrutti, 1989), which is known to regulate many intracellular 

processes, including those related to growth and differentiation. Hence, any one or a 

combination of these events may lead to enhanced cell proliferation or inhibition of programmed 

cell death. 

 The plausibility of an indirect mutagenicity mode of action for AN-induced tumors is 

evaluated in the following discussion. 

Strength, consistency, specificity of association 

Experimental data for indirect mutagenicity of AN are discussed in Section 4.5.2.5 and 

summarized in Table 4-55. These studies are only briefly discussed here. 

In vitro studies 

There is some in vitro experimental evidence that supports an indirect mutagenic mode of 

action for AN. When SHE cells were treated in vitro with 0–75 μg/mL AN in 12.5 μg/mL 

increments, there was a dose-dependent increase in morphological transformation at 50, 62.5, 

and 75 μg/mL after 7 days of exposure (Zhang et al., 2000). Levels of 8-oxodG isolated from 

cells incubated with 75 μg/mL AN were increased to 192 and 186% of control after 2 and 3 days. 

However, no increase in 8-oxodG was observed after 1 or 7 days. 

AN-induced oxidative stress in SHE cells was confirmed in a later study by Zhang et al. 

(2002). AN at 25, 50, or 75 μg/mL increased the amount of ROS in SHE cells after 4, 24, and 

48 hours of treatment and increased xanthine oxidase activity 24 and 48 hours after treatment 

with 75 μg/mL AN. AN also caused temporal changes in GSH levels and antioxidant enzyme 

catalase and SOD activities. The involvement of CYP450 metabolism of AN in the production 

of oxidative stress was indicated by the observation that inclusion of a nonspecific suicidal 

inhibitor of CYP450 enzyme, ABT (0.5 mM), in the medium resulted in a significant reduction 

(about 77%) in the cell transformation activity of 75 μg/mL AN (Zhang et al., 2002). 

In another study, when cultured rat astrocytes were exposed for 4 or 24 hours to 0.01, 0.1, 

or 1 mM AN, up to a 3.9-fold increase in 8-oxodG was found in cellular DNA of the rat 

astrocytes (Kamendulis et al., 1999a). No increase in 8-oxodG was found in rat hepatocytes 

exposed to 0.01, 0.1, or 1 mM AN for 4 or 24 hours (Kamendulis et al., 1999a). Pu et al. (2006) 

also reported a 3-fold increase in oxidative DNA damage (as measured by the fpg-modified 

comet assay) in cultured D1TNC1 rat astrocytes treated with 1 mM AN for 24 hours. When 

NHAs were treated with 200–400 μM AN for 12 hours, a four- to sevenfold increase in the 

generation of ROS and a greater than twofold increase in 8-oxodG were observed (Jacob and 

Ahmed, 2003b). 

In vivo studies
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Three studies on rats are available that investigated oxidative DNA damage in the brain 

after exposure to AN in drinking water (Jiang et al., 1998; Whysner et al., 1998a). A two- to 

threefold increase in 8-oxodG levels was found in cellular DNA from brain cortex of SpragueDawley rats exposed to 50, 100, or 200 ppm AN in drinking water for 28 or 90 days (Jiang et al., 

1998). Levels of 8-oxodG in DNA increased with increasing exposure levels in this study. At 

90 days, levels of 8-oxodG were more than twofold higher in DNA from 50 ppm rat brain cortex 

compared with controls (Jiang et al., 1998). In addition, no increased levels of 8-oxodG were 

found in the liver DNA of exposed rats at all dose levels following 14, 28, or 90 days of 

exposure (Jiang et al., 1998). The liver is not a target organ for AN-induced carcinogenicity in 

adult rats. In a follow-up study, Pu et al. (2009) reported an increase in 8-oxodG levels in brain 

DNA of male Sprague-Dawley rats exposed to 100 or 200 ppm AN in drinking water for 28 

days. However, EPA has identified issues with Pu et al. (2009) (see Section 4.5.1.2.1); therefore, 

this study was not discussed separately here. 

 In another study, levels of 8-oxodG in brain nuclear DNA were increased by about 

twofold in Sprague-Dawley rats exposed to 30 or 300 ppm AN in drinking water for 21 days and 

by about 1.5-fold in rats exposed to 100 ppm AN for 94 days (Whysner et al., 1998a). However, 

no significant increase in 8-oxodG levels was found in F344 rats exposed to 10, 30, or 100 ppm 

for 21 days (Whysner et al., 1998a). (A statistically insignificant increase of about 30% was 

found in the 3–100 ppm AN dose groups.) Levels of 8-oxodG in liver DNA were increased by 

about 1.4-fold in Sprague-Dawley rats exposed to 30 or 300 ppm for 21 days and by about 

1.3- and 2-fold following exposure to 100 ppm for 10 and 94 days, respectively (Whysner et al., 

1998a). Levels of 8-oxodG in liver DNA were not measured in F344 rats in this study. No 

significant increase in 8-oxodG levels in DNA of forestomach (a target organ of AN 

carcinogenicity) were found in Sprague-Dawley rats exposed to 3–300 ppm AN (see 

Table 4-54). 

 Several inconsistencies can be found in the results of Jiang et al. (1998) and Whysner et 

al. (1998a). While a dose-related increase in 8-oxodG levels in brain cortex DNA of SpragueDawley rats exposed up to 200 ppm AN was reported by Jiang et al. (1998), a twofold increase 

in 8-oxodG levels in brain DNA was found for Sprague-Dawley rats exposed to either 30 or 

300 ppm in the study by Whysner et al. (1998a). Thus, there was no increase in 8-oxodG level 

with a 10-fold increase in exposure concentration in Sprague-Dawley rats (Whysner et al., 

1998a). While 8-oxodG levels were measured via different sample preparation methods in these 

two studies (i.e., 8-oxodG level was measured in nuclear DNA in whole brain in Whysner et al. 

[1998a] and in cellular DNA from brain cortex in Jiang et al. [1998]), 8-oxodG level measured in 

Sprague-Dawley rats exposed to 3 or 30 ppm AN for 21 days in Whysner et al. (1998a) was 

comparable to that measured in Sprague-Dawley rats exposed to 5 or 50 ppm AN for 28 days in 

Jiang et al. (1998) (0.86/105

 and 1.35/105 dG vs. 1.8/105 and 2.5/105 dG). Thus, inconsistencies 
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in the two studies regarding 8-oxodG levels in rat brain are not likely due to differences in 

sample preparation. 

Inconsistencies were also found in 8-oxodG levels in livers in the two rat studies. Jiang 

et al. (1998) reported no increase in 8-oxodG levels in liver DNA of exposed rats, but Whysner 

et al. (1998a) reported a 1.4-fold increase in 8-oxodG levels in liver DNA of Sprague-Dawley 

rats exposed to 30 or 300 ppm for 21 days and a 1.3- and twofold increase following exposure to 

100 ppm AN for 10 and 94 days, respectively. Moreover, the increase in 8-oxodG levels in brain 

DNA was not much higher than that in liver DNA (see Table 4-55). The rat brain is a target 

organ for AN-induced carcinogenicity but not adult rat liver. In addition no significant increase 

in 8-oxodG levels in forestomach DNA was found. Thus, no specificity is indicated regarding 

increased 8-oxodG levels (oxidative DNA damage) in target organ DNA and tumor formation. 

Inconsistencies were also found regarding AN-induced disruption of antioxidant defense. 

While Jiang et al. (1998) reported increases in ROS and concomitant persistent decreases in 

antioxidant enzyme catalase activity in the brain cortex of Sprague-Dawley rats exposed to 50–

200 ppm AN in drinking water after 14, 28, and 90 days, as well as decrease in SOD activity and 

GSH level in all dose groups after 14 days of treatment, Whysner et al. (1998a) reported no 

changes in catalase and glutathione peroxidase activities and GSH levels in the brains of 

Sprague-Dawley rats treated with 3, 30, or 300 ppm AN in drinking water for 21 days. Whysner 

et al. (1998a) did report a dose-related increase in cysteine levels in the brains of SpragueDawley rats exposed to AN for 21 days, and the increase was significant for the 300 ppm dose 

groups. However, no changes in GSH and cysteine levels were found in the brains of F344 rats 

exposed to 0, 1, 3, 10, 30, or 300 ppm AN in the drinking water for 21 days (Whysner et al., 

1998a). Since F344 rats exposed to these dose levels of AN also developed brain tumors in 

chronic bioassay, the formation of these tumors cannot be explained by oxidative stress resulting 

from disruption of antioxidant defense. Whysner et al. (1998a) also found no changes in 

cytochrome oxidase activities in the brain mitochondria of both exposed Sprague-Dawley rats 

and F344 rats. Cyanide, a metabolite of AN, is a noncompetitive inhibitor of cytochrome 

oxidase. No change in cytochrome oxidase activity indicated that no metabolic hypoxia occurred 

in brain mitochondria as a result of inhibition of the enzyme by cyanide. Therefore, cyanideinduced metabolic hypoxia did not appear to be involved in the mechanism of ROS generation 

by AN. 

Moreover, Whysner et al. (1998a) reported no changes in TBARS in the brains of all 

groups of AN-exposed Sprague-Dawley rats, indicating the absence of lipid peroxidation, 

another biomarker of oxidative stress and oxidative lipid damage. Jiang et al. (1998) reported 

significant increase in MDA only in the brain cortex of rats exposed to 200 ppm AN for 14 days 

and not in other dose groups at 14 days. No increase was found in all dose groups at 28 and 

90 days. Since lipid peroxidation is another biomarker of oxidative stress, there is no strong 

evidence for occurrence of significant oxidative stress in the brain of AN-exposed rats. 
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In addition, Chantara et al. (2006) demonstrated that AN induced ERK activation via 

PKC in SK-N-SH neuroblastoma cells. However, oxidative stress was found not to be involved 

in AN-induced ERK1/2 activation, which played a crucial role in cell proliferation and tumor 

progression. Thus, the potential tumor promotion effect of AN has not been related to oxidative 

stress. 

Dose-response concordance 

Levels of 8-oxodG in DNA from brain cortex of Sprague-Dawley rats (Jiang et al., 1998) 

or rat astrocytes (Kamendulis et al., 1999a) increased with increasing in vivo (50, 100, 200 ppm) 

or in vitro (0.01, 0.1, 1.0 mM) exposure levels. However, 8-oxodG in DNA from brain of F344 

rats exposed to 1–100 ppm AN were not significantly increased. In addition, 8-oxodG levels in 

DNA from brain of F344 rats did not show a dose-response relationship (see Table 4-54), and no 

correlation can be found between 8-oxodG levels in brain DNA of these rats and brain tumor 

incidence of F344 rats exposed to the same concentration of AN in drinking water for 2 years 

(Table 4-58). Thus, experimental data do not support the hypothesis that brain tumors from 

F344 rats are the result of oxidative DNA damage. 

Table 4-58. 8-OxodG in brain DNA and brain tumor incidence in male F344 

rats exposed to AN in drinking water 

Dose group (ppm) 8-oxodG (mol/105 mol dG)aIncidence of brain astrocytomasb 

0 0.79 ± 0.37 2/160 

1 0.84 ± 0.25 2/80 

3 1.07 ± 0.41 1/78 

10 1.04 ± 0.30 2/80 

30 1.03 ± 0.38 10/79 

100 1.06 ± 0.48 21/76 

aData are from 21-d drinking water study by Whysner et al. (1998a). 

bData are from 2-yr drinking water study by Biodynamics (1980b) and Johannsen and Levinskas (2002b). The 

denominators for incidence of brain astrocytomas excluded rats from the 6- and 12-mo interim sacrifices and rats 

that died before the appearance of the first tumor for this site. 

 Moreover, although Whysner et al. (1998a) demonstrated a significant increase in levels 

of 8-oxodG in brain DNA of Sprague-Dawley rats exposed to AN for 21 days, no correlation can 

be found between 8-oxodG levels in brain and tumor incidence in the 2-year bioassay 

(Table 4-59). Therefore, dose-response data on Sprague-Dawley rats from Whysner et al. 

(1998a) did not support oxidative DNA damage as the mode of action for AN-induced brain 

tumor formation. 
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Table 4-59. 8-OxodG in brain DNA and brain tumor incidence in male 

Sprague-Dawley rats exposed to AN in drinking water

Dose group (ppm) 8-oxodG (mol/105

 mol dG)aIncidence of brain astrocytomasb 

0 0.62 ± 0.08 1/80 

1 0.86 ± 0.41 ND 

3 1.35 ± 0.49 ND 

10 ND 8/47 

30 ND 19/48 

100 1.29 ± 0.10 23/48 

a

Data are from 21-d drinking water study by Whysner et al. (1998a). 

bData are from 2-yr drinking water study by Quast (2002). 

ND = cannot be determined 

Temporal relationships 

The detection of increased 8-oxodG levels in brains of Sprague-Dawley rats exposed for 

subchronic durations (Jiang et al., 1998; Whysner et al., 1998a) is temporally consistent with 

oxidative DNA damage being a plausible key precursor event in the development of laterappearing tumors. However, no significant increase in 8-oxodG levels in the brain of exposed 

F344 rats was found. 

Biological plausibility and coherence 

The demonstration of AN-induced oxidative DNA damage in rat brain cortexes following 

subchronic-duration exposure to AN at dose levels producing brain tumors with chronic 

exposure would have provided support for the involvement of an indirect mutagenic mode of 

action in AN carcinogenicity. However, no increase in oxidative DNA damage was found in 

F344 rats exposed to AN in drinking water. Brain tumors were found in F344 rats at similar 

frequencies as Sprague-Dawley rats in chronic bioassays. Thus, brain tumors in F344 rats cannot 

be explained by oxidative DNA damage, and the predicted greater sensitivity of Sprague-Dawley 

rats vs. F344 rats based on 8-oxodG levels measured in short-term studies is not reflected in 

cancer bioassays. In addition, the presence of increased oxidative DNA damage in the livers of 

Sprague-Dawley rats exposed to AN in drinking water in one study (Whysner et al., 1998a) but 

not in another (Jiang et al., 1998) also raised the question regarding a significant association 

between oxidative DNA damage and tumor formation. 

 The origin of oxidative stress is unclear. Proposed molecular mechanisms that may be 

involved in AN induction of oxidative stress in the brain (or other toxicity targets) include direct 

generation of free radicals by AN (or its metabolites), stimulation by AN or its metabolites of 

systems that generate free radicals, binding of AN to free radical scavengers (e.g., GSH, vitamins 

C or E) and depletion of stores of these antioxidants, inhibition of the expression or activities of 
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antioxidant enzymes, and interference of mitochondrial respiratory electron flow via cyanide 

inhibition of cytochrome c oxidase (Zhang et al., 2002; Jiang et al., 1998). As discussed 

previously, some of these potential mechanisms have been ruled out. 

 As with the direct mutagenic mode of action, there are no data currently available to 

indicate how or if this indirect mutagenic mode of action may explain the occurrence of brain 

tumors in rats but not in mice, following chronic exposure to AN. 

Human relevance 

Humans possess the biochemical pathways for the key steps of this proposed mode of 

action. This hypothetical mode of action, if it occurs, is considered to be relevant to humans. 

Conclusion

While plausible, this postulated mode of action is not supported by in vivo studies in rats. 

Studies on oxidative DNA damage or oxidative lipid damage in the brain of exposed rats do not 

provide sufficient evidence to support this mode of action. In addition, Chantara et al. (2006) 

demonstrated AN-induced ERK activation via PKC in SK-N-SH neuroblastoma cells. Oxidative 

stress was found to be not involved in AN-induced ERK1/2 activation, which played a crucial 

role in cell proliferation and tumor progression. Therefore, while this mode of action may play a 

role, it is not likely to be the principal mode of action for AN-induced carcinogenicity. 

4.7.3.3.2. Other modes of action for brain tumors

Key events 

Other hypothesized modes involve actions by AN or its metabolites to directly or 

indirectly alter the expression of genes (either at the level of translation, post-translation, or 

protein activity), leading to the loss of control of cell growth and the ultimate promotion of 

initiated cells into brain tumors. Possible modes of AN carcinogenic action include stimulation 

of cell proliferation (mitogenic), cytotoxicity with subsequent reparative cell proliferation 

(cytotoxic), inhibition of programmed cell death (anti-apoptotic), and inhibition of GJIC. 

 Studies specifically designed to examine these possible modes of action are restricted to a 

study of GJIC in rat astrocytes (Kamendulis et al., 1999b). 

Strength, consistency, and specificity of association 

 No studies are available that examine cellular proliferation indices in brain cells 

following in vivo exposure to tumor-producing doses of AN. In in vitro studies with rat 

astrocytes, indices of cytolethality after 24 hours of exposure occurred at higher AN 

concentrations (2.5, 5.0, and 10.0 mM) than increased 8oxodG levels in DNA (0.01, 0.1, and 

1.0 mM) (Kamendulis et al., 1999a). The available data do not support a prominent role for 

cytotoxic or mitogenic modes of action in AN-induced rat brain tumors. 
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 Inhibition of GJIC has been shown to correlate with tumor promotion activity (i.e., the 

loss of control of growth) and to be induced by various chemical agents thought to operate via 

other modes of carcinogenic action, such as phorbol esters and PB (Kamendulis et al., 1999b). 

Exposure of rat astrocytes to 0.01, 0.1, or 1 mM AN for 4–48 hours statistically significantly 

inhibited GJIC compared with controls (Kamendulis et al., 1999b). The inhibition was reversible 

and prevented by the presence of an antioxidant, α-tocopherol, or a precursor for the synthesis of 

glutathione, OTC, in the culture medium. The results are consistent with the involvement of 

AN-induced oxidative stress in the inhibition of GJIC. The inhibitory concentrations were the 

same as those that produced oxidative DNA damage in a companion experiment (Kamendulis et 

al., 1999a). The specificity of the inhibitory response to rat astrocytes was demonstrated by the 

lack of inhibition of GJIC in rat hepatocytes exposed to 0.01, 0.1, or 1.0 mM AN (Kamendulis et 

al., 1999b). 

Dose-response concordance 

The inhibition of GJIC in rat astrocytes increased with increasing sublethal 

concentrations in the range of 0.01–1 mM (Kamendulis et al., 1999b). A concordance of these 

concentrations to dose levels associated with brain tumors is not available. 

Temporal relationships 

The acute nature of the observed inhibition of GJIC is consistent with the hypothesis that 

this action may be one of a number of precursor events involved in tumor promotion. 

Biological plausibility and coherence 

Other potential modes of action for AN-induced brain tumors have not been adequately 

studied. The involvement of inhibition of GJIC by oxidative stress induced by AN or its 

metabolites is plausible, based on the limited evidence with rat astrocytes (Kamendulis et al., 

1999b). However, the available histopathology data from interim sacrifices of the chronic rat 

bioassays do not support the involvement of a mode of action involving brain cell cytotoxicity 

followed by reparative cell proliferation. 

4.7.3.3.3. Conclusions about modes of action for brain tumors. Data gaps still exist in the current 

understanding of the mode of action for carcinogenicity of AN. However, there is sufficient 

experimental evidence to support direct mutagenicity as the principal mode of action. Key 

events are the generation of direct DNA damage by the AN metabolite, CEO, and interaction 

with DNA. There is in vitro and in vivo evidence to support the occurrence of key events in the 

brain following AN exposure. Other modes of action may contribute, along with direct 

mutagenesis, to tumorigenesis. For example, AN-induced ERK activation via PKC may play a 

role in cell proliferation and tumor progression. However, limited experimental evidence does 
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not support them as alternatives. Available data are inadequate to establish an oxidative stress 

mode of action for AN-induced carcinogenicity. 

The available data do not provide an explanation for AN induction of brain tumors in 

F344 and Sprague-Dawley rats but not in B6C3F1 mice. However, it should be noted that 

generally mice are much less susceptible than rats in developing brain tumors resulting from 

exposure to chemical carcinogens (Rice and Wilbourn, 2000; Radovsky and Mahler, 1999). 

Hence, this species difference in response is not limited to AN alone. In addition, there have 

been no investigations to attempt to explain the apparent susceptibility of early-life plus chronic 

adult exposures compared with adult-only exposures. It is possible that a higher rate of cell 

division in the fetal brain and the resultant greater sensitivity to direct mutagenic damage may be 

involved (Slikker et al., 2004). Possible differences between early-life and adult stages of rat 

development in pertinent physiologic processes, such as distribution of AN or its metabolites to 

the brain, levels of antioxidants, activities of antioxidant enzymes, or repair of DNA damage, 

have not been investigated to explain this apparent susceptibility of early-life stages to AN 

carcinogenicity. 

 Possible differences between rats and humans in distribution of AN or its metabolites to 

the brain, susceptibility to oxidative stress, or repair of DNA damage have not been investigated. 

Identified differences between rats and humans in AN disposition are restricted to the finding of 

higher rates of metabolic oxidation of AN in human vs. rat hepatic microsomes, presumably due 

to a more active EH in humans (Kedderis and Batra, 1993; Kedderis et al., 1993c). The 

relevance of this apparent difference in AN metabolism to possible species differences in 

susceptibility to AN carcinogenicity in the brain is not understood. Within the framework of the 

hypothesized direct mutagenic mode of action, the balance between the formation of CEO by 

CYP2E1 and its hydrolysis by EH is thought to be important in determining the levels of CEO 

that might be available to bind DNA or GSH. Experimental comparison of this balance in 

human and rat brain tissues is not available. 

4.7.3.4. Possible Modes of Action for Forestomach Tumors 

There is evidence to suggest that, once delivered to forestomach epithelial cells, AN or its 

metabolites shift the normal balance between cell proliferation and apoptosis, leading to 

hyperplasia and eventually, with continued exposure and sustained net cellular proliferation, to 

tumor formation. Sustained increased cellular proliferation is viewed as the key precursor event 

in this hypothesized mode of carcinogenic action. Exposure of male F344 rats to gavage doses 

of about 12 and 23 mg/kg-day AN for 6 weeks produced minimal to mild hyperplasia and 

hyperkeratinization of the squamous mucosa of the forestomach but not the epithelium of the 

glandular stomach or the liver (Ghanayem et al., 1997). The early induction of hyperplasia by 

AN doses that resulted in forestomach tumors in chronic rat bioassays is temporally consistent 

with the involvement of sustained cell proliferation in the development of these tumors. A dose-
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related increase in cell proliferation (as determined by BrdU incorporation into DNA) was 

observed in the forestomach epithelium, but no increases were found in the glandular stomach or 

the liver, which are not targets of AN toxicity or carcinogenicity from chronic exposure to AN 

during adulthood. At the high-dose level, an increase in apoptotic cells was found. These results 

suggest that AN stimulation of cellular proliferation overcame the apparent stimulation of 

apoptosis at the higher dose, since hyperplasia was observed. Whether or not the stimulation of 

cellular proliferation was due to a reparative response to cytotoxicity or to a direct mitogenic 

action is uncertain. Acute administration of a higher dose of AN (50 mg/kg) caused gastric 

mucosal necrosis in rats, which was shown to involve CYP-mediated metabolism of AN 

(Ghanayem et al., 1985; Ghanayem and Ahmed, 1983). Whether or not these findings relate to 

the stimulation of cellular proliferation and development of hyperplasia at the lower doses is 

uncertain. 

Possible direct or indirect mutagenic modes of action for forestomach tumors, such as 

those investigated for brain tumors, have not been investigated. However, DNA damage, as 

detected by the comet assay, was reported in the stomach of rats and mice exposed by i.p. 

injection (Sekihashi et al., 2002). No significant oxidative DNA damage (levels of 8-oxodG) 

was measured in the forestomach of rats exposed to 3, 30, or 300 ppm in drinking water for 

21 days (Whysner et al., 1998a). In addition, AN was reported to bind to DNA in the stomach of 

rats following a single oral dose of 46.5 mg/kg (Farooqui and Ahmed, 1983a). Given that a 

mutagenic MOA is hypothesized for AN induced brain tumors in rats, that mutagenic 

carcinogens usually cause tumors in multiple sites, and evidence of DNA damage in the 

forestomach of AN treated rats, direct mutagenicity is a likely mode of action for AN-induced 

forestomach tumors. 

4.7.3.5. Possible Modes of Action for Hepatomas 

Although adult female Sprague-Dawley rats exposed to 60 ppm AN by inhalation during 

adulthood did not develop hepatomas, these tumors were found in 5/67 male offspring and 

1/54 female offspring exposed during gestation and extending throughout adulthood (Maltoni et 

al., 1988). In unexposed offspring in this study, hepatomas were found in 1/158 males and 

0/149 females. This apparent susceptibility of early-life stages to the initiation of liver tumors 

may be suggestive of a direct mutagenic mode of action in which embryonic DNA repair 

mechanisms are inadequate to repair AN-induced DNA damage during this stage of development 

when cells are rapidly dividing. N7-(2-oxoethyl)guanine-DNA adducts have been measured in 

the livers of adult rats following i.p. exposure to AN (Hogy and Guengerich, 1986). Increased 

levels of 8-oxodG have also been measured in DNA from the livers of adult Sprague-Dawley 

rats exposed to AN in drinking water for 21 or 94 days (Whysner et al., 1998a). Thus, indirect 

mutagenic mode of action may also contribute. However, possible modes of action for the 
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development or initiation of liver tumors during early stages of development have not been 

investigated. 

4.7.3.6. Possible Modes of Action for Tumors of Intestines, Tongue, Zymbal Gland, and 

Harderian Gland 

Based on analogy to other direct-acting mutagens that cause tumors at multiple sites in 

animal bioassays, it is possible that a direct mutagenic mode of action may be involved in the 

formation of AN-induced tumors at these sites in rats and mice. Although possible modes of 

carcinogenic actions of AN at these sites have not been investigated, direct mutagenic mode of 

action is the most likely mode of action. CYP2E1 enzymes occur in intestinal mucosa, and CEO 

can form in intestine and bind to DNA. In addition, there is no evidence that AN would have a 

tissue specificity that would lead to mutagenesis in brain but not other organs. Moreover, AN 

appears to act systemically with DNA damage, and tumors occur in multiple tissues of treated 

animals. The direct mutagenic mode of action is considered relevant to all tumor sites 

4.7.3.7. Possible Modes of Action for Lung Cancer 

Evidence of a possible association between occupational exposure to AN and lung cancer 

is found in some studies, including the best available epidemiologic study that workers in the 

highest exposure category (>8 ppm-years) with more than 20 years of employment displayed a 

twofold increased risk for lung cancer compared with unexposed workers (Blair et al., 1998). 

Human bronchial epithelium has CYP2E1 metabolic activities. In a short-term mutagenicity 

assay, AN induced SCEs and DNA single-strand breaks in human bronchial epithelial cells 

without the addition of S9 mix (Chang et al., 1990). Thus, a direct mutagenic mode of action is 

supported for potential AN-induced lung cancer. 

In contrast, there is no convincing evidence of lung cancer in rodents chronically exposed 

by the oral or inhalation routes. The possible mode of action by which AN may induce lung 

tumors in humans and not in rodents has not been investigated but may involve species 

differences in inhalation rates and anatomical features of the respiratory tract. 

4.8. SUSCEPTIBLE POPULATIONS AND LIFE STAGES 

4.8.1. Possible Childhood Susceptibility 

 Evidence that children may be more susceptible to the acute or chronic toxicity of AN is 

restricted to a report that children died after sleeping in rooms fumigated with a commercial form 

of AN called Ventox, whereas adults sharing the same rooms only experienced skin or eye 

irritation (Grunske, 1949; see Section 4.1.3.1). 

 Animal studies specifically designed to examine whether or not early-life stages of 

development are more susceptible than adult stages to the induction of noncancer or cancerrelated effects by AN include a lifetime inhalation cancer bioassay in Sprague-Dawley rats 

(Maltoni et al., 1988) and a three-generation drinking water reproductive toxicity bioassay in 
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Sprague-Dawley rats that provides evidence of increased tumor incidences in F1 and F2 female 

breeders after 46 weeks of exposure starting in utero (Friedman and Beliles, 2002). In addition, 

a subacute study on Sprague-Dawley rats (Szabo et al., 1984) also found weanling rats to be 

more susceptible than adult rats to the action of AN on the adrenals (see Section 4.2.1.1). 

 Results from the lifetime inhalation bioassay showed that rats that were chronically 

exposed starting in utero had higher incidences of tumors at several sites (brain, Zymbal gland, 

mammary gland, liver, and blood vessels) compared with rats chronically exposed during 

adulthood only (Maltoni et al., 1988; see Section 4.2.2.2.2 for details). For example, brain 

tumors occurred in 5.5% of rat dams chronically exposed to 60 ppm AN compared with no brain 

tumors in unexposed controls (Table 4-42). In contrast, 16.4% of male and 18.5% of female 

offspring of the exposed dams had brain tumors compared with 1.3% of male and 1.3% of 

unexposed female rats exposed starting in utero, otherwise under the same exposure protocol as 

the dams. The responses for brain tumors (male and female offspring), extrahepatic 

angiosarcomas (female offspring), Zymbal gland (male offspring), and mammary gland (female 

offspring) with chronic exposure were about threefold higher than those observed in female rats 

exposed only during adulthood (Table 4-42). In addition, although none of the exposed or 

unexposed dams had hepatomas, 5/67 male offspring with early-life plus chronic exposure had 

hepatomas compared with 1/158 unexposed male offspring; hepatomas were observed in 

1/54 exposed female offspring compared with 0/149 unexposed female offspring. Rats with 

early-life plus subchronic (8-week) adult exposure did not show elevated incidences for these 

tumors compared with adults with chronic adult exposure (Table 4-42). 

 Comparison of the results from the two chronic phases of this experiment indicated that, 

compared with chronic exposure to 60 ppm during only adult stages of development, chronic 

exposure to 60 ppm AN starting during gestation increased the risk for development of 

extrahepatic angiosarcomas and malignant mammary gland tumors in females, hepatomas and 

Zymbal gland carcinomas in males, and encephalic gliomas in males and females. Although 

testing in adult male rats was not included in this study, the increase in hepatomas in male 

offspring may indicate differences in detoxification and DNA repair mechanisms between fetal 

and adult livers. 

 In the drinking water bioassay involving 46-week exposures of each of three generations 

of female breeder Sprague-Dawley rats, there were slightly increased incidences of tumors in 

F0 or F2b female breeders in the 100 or 500 ppm groups compared with controls, which were not 

statistically significant, while F1b female breeders in the 500 ppm group showed statistically 

significantly increased incidences of brain and Zymbal gland tumors compared with control, at 

24 (4/17) vs. 0 and 18 (3/17) vs. 0%, respectively (Friedman and Beliles, 2002). Compared with 

the 500 ppm F0 breeders that were exposed starting in adulthood, there was an approximate 

twofold increase in Zymbal gland tumor incidence and a threefold increase in brain tumor 

incidence in the 500 ppm F1b female breeders, exposed starting in utero (Table 4-35). The 
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results provide evidence for the increased susceptibility to the carcinogenicity of AN during 

early-life exposure, positive evidence being in the F1 generation. Increases in tumor incidence in 

the F2 generation were not as pronounced and were not statistically significant. 

 As discussed in Sections 4.5.1 and 4.6.3, toxic effects from acute or chronic exposure to 

AN have been associated with inhibition of glutathione-mediated detoxification of AN by 

conjugation (e.g., glutathione depletion), transformations in the CYP2E1 metabolic pathway to 

CEO and cyanide, and oxidative stress. Differences in enzymatic activities (e.g., CYP2E1, EH, 

DNA repair enzymes, or antioxidant enzymes such as catalase or SOD) or pool sizes of reactive 

oxygen scavengers (e.g., levels of vitamin E or C) or glutathione between early-life and adult 

stages may result in life stage differences in susceptibility to AN toxicity. 

For CYP2E1, immunoreactive CYP2E1 protein has been detected in human liver 

microsomes as early as the second trimester (GDs 93–186) (Johnsrud et al., 2003). CYP2E1 

enzyme activity increases shortly after birth but less in neonates than in older infants, children, 

and adults (Johnson, 2003; Johnsrud et al., 2003; Vieira et al., 1996). However, in the fetal 

brain, CYP2E1 activity is seen as early as 50 days gestation, with increasing levels seen to at 

least the end of the first trimester (Brzezkinski et al., 1999). In rats, CYP2E1 protein is not 

significantly expressed in fetal hepatic tissues, although an elevation of CYP2E1 mRNA was 

seen within a few hours after birth, coincident with the transcriptional activation of the gene 

(Borlakoglu et al., 1993). Moreover, only neonates expressed small quantities of the CYP2E1 

protein, despite the large quantities of CYP2E1 mRNA found in perinatal and neonatal rats. 

For EH, fetal immunoreactive enzyme content in human livers averages only 25% of that 

found in adults with corresponding less enzyme activity (Cresteil et al., 1985). EH activity in 

fetal liver and adrenal glands are about threefold higher than in kidney and lung with only a 

weak correlation with gestational age between 10 and 25 weeks. Overall, EH activity in fetal 

tissue is about 30–40% of that in adults (Pacifici and Rane, 1983b; Pacifici et al., 1983a). In 

another study (Omiecinski et al., 1994), human microsomal EH (mEH) was detected in fetal liver 

as early as 7.2 weeks, although at a much lower level of mEH protein, and demonstrated a linear 

increase with gestational age to a level at 77 weeks that is about half of that observed in adult 

liver. However, mEH activity in the fetal lung did not correlate with increasing age. Lung mEH 

activity from days 85 to 130 of gestation was maintained at consistent levels, at about the same 

level as fetal hepatic EH at 53 days, and varied only by threefold. In addition, Omiecinski et al. 

(1994) reported that mEH activities in liver or lung, from either fetal or adult tissues, did not 

correlate with corresponding mRNA levels. 

The overall balance of pertinent enzymatic activities (AN metabolizing enzymes and 

antioxidant enzymes) and pool sizes of reactive oxygen scavengers and glutathione will 

determine the relative susceptibility of an individual or a life stage. The relatively high activity 

of CYP2E1 in the brain compared to the liver of the developing human fetus, and low EH 

activity for detoxification raise concern for increased susceptibility in early life to lung tumors, 
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and brain tumors from AN exposure, as seen in rats. Additional research examining agedependent changes in these physiological variables and responses to AN may help to provide 

explanations for the observed susceptibility of early-life stages in rats to the carcinogenicity of 

AN, and is outside the scope of this assessment. 

 The importance of CYP2E1 metabolism in the acute toxicity and lethality of AN has been 

demonstrated by the lack of lethality or gross signs of intoxication in CYP2E1-null male mice 

given single gavage doses up to 40 mg/kg, whereas all WT male mice given doses of 40 mg/kg 

died within 3 hours of administration (Wang et al., 2002). This type of research approach (i.e., 

the comparison of pertinent endpoints in WT and CYP2E1-null animals) may be useful in 

helping to better understand the physiologic basis of the apparent susceptibility of early-life 

stages to the carcinogenicity of AN, which was demonstrated in the rat study by Maltoni et al. 

(1988).SubchronicSubchronic

4.8.2. Possible Geriatric Susceptibility 

 Age-related reductions in antioxidant or glutathione pool sizes may increase 

susceptibility of elderly people to the tissue-damaging actions of AN and reactive metabolites, 

but specific studies of the possible increased susceptibility of aged people or rats to AN are not 

available. A 35% decrease in glutathione levels in the liver of aged F344 rats compared with 

younger animals was associated with an age-related decrease in the levels and activity of 

γ-glutamylcysteine ligase, a key enzyme in the synthesis of glutathione (Suh et al., 2004). In 

Wistar rats, the liver and kidney of 22-month-old rats showed significant decreases, compared 

with 10-week-old rats, in glutathione and glutathione peroxidase and increased levels of 

biomarkers of lipid peroxidation (Martin et al., 2003). In another study with F344 rats (Tian et 

al., 1998), activities of several antioxidant enzymes in several tissues displayed an age-dependent 

decline. Enzymatic activities showing significant decline with age included SOD in the heart, 

kidney, and serum; glutathione peroxidase in the serum and kidney; and catalase activities in the 

brain, liver, and kidney. These changes indicated a lower resistance to oxidative stress in older 

animals. 

 The possible toxicological impact of an age-related decline in glutathione could be offset 

by an age-related decline in CYP2E1-mediated metabolism of AN leading to reactive 

metabolites (CEO), cyanide, or ROS. Many studies have reported that hepatic enzymatic 

activities of CYP2E1 are lower in elderly human subjects (>65 years) compared with younger 

adults (see Tanaka, 1998, for review). Decreased hepatic CYP2E1 enzyme activities have also 

been reported in aged rats. For example, hepatic CYP2E1 enzyme activities were decreased by 

46% in 18-month-old rats compared with 8-month-old rats, whereas no age-related changes in 

CYP2E1 mRNA or protein content were evident (Wauthier et al., 2004). Such age-related 

declines in CYP2E1 enzyme activities may lead to lower tissue levels of reactive metabolites or 

cyanide but also may lead to elevated levels or increased residence time of AN in aged tissues 

compared with younger tissues. No definitive conclusions about the possible susceptibility of 
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the elderly to AN toxicity can be drawn without more specific studies designed to examine the 

effects of age on susceptibility to AN toxicity. 

 As studied in a small number of individuals (n = 47), long-term occupational exposure to 

AN increased the deletion rate in mitochondrial DNA to a level equivalent to that seen in a group 

of elderly nonexposed subjects (n = 12) (Ding et al., 2003) (see Section 4.1.2.2). The study 

authors suggested that AN may have an effect on the molecular processes of aging.

4.8.3. Possible Gender Differences 

 No reports of gender differences in susceptibility of humans to AN toxicity are available. 

No consistent gender-related differences in carcinogenic responses were observed in rats or 

mice, following chronic oral exposure to AN, or in rats, following chronic inhalation exposure. 

With oral exposure, male and female groups showed similarly increased incidences of brain 

astrocytomas (rats: Quast, 2002; Bigner et al., 1986; Biodynamics, 1980a, b, c; Quast et al., 

1980a), forestomach tumors (rats: Quast, 2002; Bigner et al., 1986; Biodynamics, 1980a, b, c; 

Quast et al., 1980a; mice: NTP, 2001), Zymbal’s gland tumors (rats: Quast, 2002; Bigner et al., 

1986; Biodynamics, 1980a, b, c; Quast et al., 1980a), and Harderian gland tumors (mice: NTP, 

2001). Following inhalation exposure to 80 ppm AN for 2 years, male and female exposed 

groups of rats showed similarly increased incidences of brain/CNS tumors and Zymbal’s gland 

tumors compared with the respective control groups (Quast et al., 1980b). 

 No marked gender-related differences in noncarcinogenic responses were observed in the 

rat chronic oral toxicity study reported by Quast (2002). Groups of male and female rats were 

exposed to AN in drinking water at concentrations of 0, 35, 100, or 300 ppm. At the 1-year 

interim sacrifice, the only exposure-related noncancer histopathologic finding was an increase in 

the incidence of forestomach squamous cell hyperplasia in rats exposed to concentrations of 

100 ppm (4/10 males, 7/10 females) or 300 ppm (10/10 males, 9/10 females). At the 2-year 

sacrifice, incidences of stomach lesions (nonglandular hyperplasia and/or hyperkeratosis) were 

similar in male (15/80, 15/47, 44/48, and 45/80 for the control through high-concentration 

groups, respectively) and female (20/80, 23/48, 41/48, and 47/48) rats at the same exposure level 

(Quast, 2002). These data, however, give some indication that the forestomach epithelium of 

female rats may have been slightly more susceptible than that of male rats: at the 1-year 

sacrifice, 7/10 100 ppm females (70%) had lesions compared with 4/10 100 ppm males (40%); at 

2 years, 23/48 35 ppm females (48%) had lesions compared with 15/47 35 ppm males (32%). 

 In contrast to the lack of apparent gender differences in carcinogenic or noncarcinogenic 

responses in rodents with chronic exposure, male mice appear to be more susceptible to the acute 

oral toxicity of AN than female mice (Chanas et al., 2003; NTP, 2001). 

 In a 14-week study, groups of 10 male and 10 female mice were given 0, 5, 10, 20, 40, or 

60 mg/kg AN in deionized water by gavage 5 days/week (NTP, 2001). Exposure-related 

mortalities were restricted to the first week of the study and occurred in the 40- and 60-mg/kg 
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groups. Both male and female groups showed mortality, but only at 40 mg/kg was the incidence 

of deaths higher in male mice compared with females (9/10 and 10/10, males, and 3/10 and 

10/10, females, at 40 and 60 mg/kg, respectively). 

 In a subsequent study, groups of three to four male and three to four female WT or 

CYP2E1-null mice (mixed 129/Sv and C57BL) were given single gavage doses of 0, 2.5, 10, 20, 

or 40 mg/kg in tap water and sacrificed 1 or 3 hours later (Chanas et al., 2003). All male WT 

mice exposed to 40 mg/kg died within 3 hours, showing gross signs typical of cyanide poisoning 

(rapid shallow breathing, cyanosis, trembling, and convulsions). In contrast, exposed female WT 

mice showed milder gross signs of poisoning, and none died within the 3-hour period. One hour 

after dose administration, concentrations of cyanide in blood were statistically significantly 

elevated, compared with vehicle controls, in WT male mice given doses ≥2.5 mg/kg. At doses 

≥10 mg/kg, female WT mice also showed elevated cyanide levels in blood, compared with 

controls, but cyanide levels were <50% that in male WT mice. Exposed CYP2E1-null mice of 

both genders showed no elevation in blood cyanide concentrations compared with vehicle 

controls. Cyanide levels in brain and kidney tissues were also higher in WT males compared 

with females; cyanide levels in liver and lung tissues showed less distinct differences between 

male and female mice. 

Expression of hepatic, renal, and pulmonary CYP2E1, soluble EH, and microsomal EH 

were measured in male and female WT mice using Western blot analysis (Chanas et al., 2003). 

In the liver, WT males showed greater expression of EH, both soluble and microsomal, than did 

females; CYP2E1 levels were similar in males and females. In the kidney, male WT mice 

showed markedly higher levels of CYP2E1 (about fourfold), moderately higher levels of soluble 

EH (about twofold), and comparable levels of microsomal EH compared with female mice. 

Higher CYP2E1 and soluble EH in the kidney of male mice provided explanation for higher 

blood cyanide levels in the kidney and acute lethality in male mice. In the lung, no gender 

differences in the expression of these enzymes were apparent. The results indicated that male 

mice were more susceptible than female mice to the acute toxicity and lethality of AN and that 

this difference was associated with higher blood, kidney, and brain levels of cyanide in males 

shortly after dose administration. Chanas et al. (2003) noted that another possible explanation 

was that female mice had greater detoxification capability of converting cyanide to thiocyanate, 

as demonstrated by excretion of greater amount of thiocyanate in urine than males after repeated 

administration of equal doses of AN (NTP, 2001). 

 In a subsequent study, male mice (mixed 129/Sv and C57BL) showed higher blood levels 

of cyanide than female mice 1 hour after gavage administration of 0.047, 0.095, 0.19, or 

0.38 mmol/kg (2.5, 5, 10, or 20 mg/kg) AN (El Hadri et al., 2005). This difference between 

genders was evident in WT mice and in microsomal EH-null (mEH-null) mice, but blood levels 

of cyanide were lower in exposed mEH-null mice, compared with comparably exposed WT 

mice. As in the previous experiments reported by Chanas et al. (2003), exposure to AN induced 
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no elevation of blood levels of cyanide in CYP2E1-null mice of either gender. Western blot 

analysis revealed no gender differences in expression of CYP2E1 in the liver of WT or mEHnull mice or in expression of mEH in WT or CYP2E1-null mice. However, expression of 

soluble EH in the liver was greater in WT males, compared with females. No gender differences 

in expression of this enzyme was observed in mEH-null mice or in CYP2E1-null mice. 

The effect of gender on the expression of CYP2E1 and EH have been investigated in 

humans and rats. Gender was reported to have no influence on the level of CYP2E1 in human 

liver (George et al., 1995). Sex-related patterns in the activity of hepatic EH activity was studied 

in Sprague-Dawley rats (Chengelis, 1988). At week 4, epoxide activity in both male and female 

rats was equivalent (3.5–4.0 nmol/minute per mg protein, or 85–100 nmol/minute per g liver). 

However, there were consistent increases in activity in males from week 4 to 78, while activity in 

females actually decreased, but returned to week 4 levels during the later stages (week 78–103). 

EH activity in male liver peaked at week 78 (about 10 nmol/minute per mg protein, or 

350 nmol/minute per g liver). There was a sharp decline in EH activity in aged male rats to 

about 6 nmol/minute per mg protein, or 200 nmol/minute per g liver at 104 weeks. Cornet et al. 

(1994) studied gender-related changes in microsomal and cytosolic EH activity in male and 

female Brown Norway rats. At 15 week, microsomal EH activity was about the same for male 

and female rats at 4.5 nmol/mg protein/minute. The microsomal EH activity decreased strongly 

as a function of age in female rats, and in the 125-week-old females, the activity was only half of 

that found in 15-week-old rats. However, there was no age-related change in males, although the 

activity in the 83- and 125-week age groups was significantly lower than that in 28-week-old 

males. The activity of EH activity was higher in males than in females in these aged animals. In 

another study that compared hepatic microsomal EH in different strains of adult rats (170–250 g) 

(Oesch et al., 1983), EH activities in females were found to be 71–88% of those in males in all 

strains. Denlinger and Vesell (1989) studied the hormonal regulation on the developmental 

pattern of EH in F344 rats, and found that EH activities in males increased gradually until 

puberty, when activities in males rose rapidly to be from 1.5- to twofold higher than those in 

females. The higher activity in males was not seen if the males were castrated 24 hours after 

birth. When castrated males and females were injected with testosterone propionate (0.5 mg s.c.) 

on days 1, 3, and 5 postpartum, increased mEH an cEH activities were observed at adulthood. 

Thus, Denlinger and Vesell (1989) concluded that full adult expression of EH activities depends 

on hormonal influences exerted neonatally. 

 Gender-related differences were also observed in cytosolic EH activity of Brown Norway 

rats (Cornet et al., 1994). Significant gender-related differences in the cytosolic EH activity 

were found in 15-, 28-, and 83-week-old rats with the male animals showing the highest values. 

In the oldest animals and in 56-week-old rats comparable cytosolic EH activities were found in 

both genders. 
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 In summary, the available data from animal studies provide no evidence of consistent or 

marked gender differences in susceptibility to noncancer or cancer-related effects from chronic 

exposure to AN. There is evidence that male mice are more susceptible than female mice to the 

acute, cyanide-induced toxicity and lethality of AN, but whether or not this apparent gender 

dimorphism extends to other species is uncertain at the present time. 

4.8.4. Genetic Polymorphisms 

4.8.4.1. CYP450 

In humans, CYP2E1 exists in several modifications that differ in amino acid sequence 

(alleles). Human variability in their susceptibility to the toxic effects of AN likely exists since 

CYP2E1 activities may fluctuate between one person and another. 

Microsomal CYP2E1 activities varied from 6- to 20-fold in human livers (Lucas et al., 

1993). Environmental factors, diet habits, and/or genetic factors may account for the observed 

interindividual variations observed. In addition, CYP2E1 is elevated in obese overfed rats 

(Salazar et al., 1988) and diabetic rats (Song et al., 1987), suggesting induction by increased 

plasma levels of ketone bodies (Bellward et al., 1988). Moreover, CYP2E1 is elevated in 

lymphocytes from poorly controlled insulin-dependent diabetics (Song et al., 1990). Thus, obese 

and diabetic individuals may have elevated levels of CYP2E1. 

 Besides induction, polymorphism of the human CYP2E1 gene may have an impact on 

AN metabolism in humans. Stephens et al. (1994) compared two restriction fragment length 

polymorphic sites of the CYP2E1 gene (Rsa 1 and Dra 1), in 695 African-American, EuropeanAmerican, and Taiwanese subjects. Rare alleles at these two loci have been associated with a 

reduced risk for lung cancer in Japanese and Swedish populations. Stephens et al. (1994) 

demonstrated that rare alleles (c2 and C) at the Rsa 1 and Dra 1 sites were at least twice as 

frequent in Taiwanese populations (28 and 24%, respectively) compared with AfricanAmericans (1–8%) or European-Americans (4–11%), raising the possibility of differential 

susceptibility to chemically induced cancers across ethnic groups. However, when Carrière et al. 

(1996) measured the allele frequencies for Ras 1, Dra 1, and Taq 1 polymorphic sites in liver 

CYP2E1 from kidney donors (n = 93) in Geneva, they failed to find a correlation between 

frequencies of rare alleles and CYP2E1 activity. This implied that observed differences in 

enzyme activity in humans were more likely to be the result of different levels of induction by 

environmental factors or other genetic factors. 

 McCarver et al. (1998) identified a 100-bp insertion mutation in the regulatory region of 

CYP2E1 gene. Associated with an elevated CYP2E1 metabolic activity, this insertion mutation 

appears to be present only in obese people or persons who had recently consumed alcohol. The 

incidence of this mutation was seen in 31% of 65 African-American samples but only in 6.9% of 

58 Caucasian samples (McCarver et al., 1998). If tumor formation is determined by the activity 
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of CYP2E1, this mutation might put affected individuals at a higher risk of cancer from 

tumorigenic agents that are metabolized by CYP2E1. 

 Thier et al. (2002) were unable to detect any influence of six genetic CYP2E1

polymorphisms (G-1259C, A-316G, T-297A, G-35T, G4804A, and T7668A) on the formation of 

N-(cyanoethyl)valine Hb adducts of AN. Conversely, in a study confined to a cohort of 

individuals from ethnic minorities (African-Americans and Mexican-Americans), Wu et al. 

(1998) observed an increased incidence of the CYP2E1 DraI DD genotype in peripheral WBC 

DNA in 126 patients with untreated lung cancer compared with 193 unaffected controls. This 

could imply an etiological association between the CYP2E1 DraI polymorphism and tumor 

formation in the lung. Altered toxicokinetic characteristics of CYP2E1 in persons exposed to 

AN might result in some persons being more vulnerable than others to the tumorigenic effects of 

the compound, with concomitant changes to the rate and amount of formation of the toxic 

metabolite and associated changes in susceptible individuals. 

 Kim et al. (1996), investigating the differences in CYP2E1 activities between 

20 Caucasian and 20 Japanese men, pointed out that the significantly lower activity of CYP2E1 

in Japanese men might account for the lower rate of some cancers in Japanese compared to 

Caucasian men. 

4.8.4.2. Glutathione S-transferases 

Thier et al. (1999) studied the formation of Hb adducts of AN (N-[cyanoethyl]valine, 

N-[methyl]valine, and N-[hydroxyethyl]valine) in a group of 59 people occupationally exposed 

to the chemical. They reported their findings in relation to subjects’ smoking habits and their 

genetic status with respect to the GST isozymes GSTM1 and GSTT1. Included in the study was 

an evaluation of smoking habits, since elevated adduct levels of AN in Hb have been reported in 

smokers. There was no correlation between adduct levels and either the subjects’ status of GST 

isozymes or smoking habit. Thus, neither GSTM1 nor GSTT1 appears as a major ANmetabolizing isoenzyme in humans. However, in a follow-up study with the same group of 

59 workers, Thier et al. (2001) reported that polymorphism of the GSTP1 gene at codon 104 was 

associated with a higher level of N-(cyanoethyl) valine adducts, while GSTM3 variants had no 

effect on Hb adduct formation. Any potential effect arising from such polymorphisms on the 

health risk to AN-exposed humans awaits to be evaluated. However, Zielinska et al. (2004) 

reported an increase in the frequency of the GSTP1b/b genotype in children with cancer (OR = 

5.7, CI = 2.4–13.8). 

4.8.4.3. EH 

Two major polymorphisms of mEH have been identified in human population (Hasset et 

al., 1997). One is a polymorphism in exon 3 that changes the tyrosine residue 113 (Tyr113) to 

histidine (His113), and the other is an A→G substitution in exon 4 that changes the histidine
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residue 139 (His 139) to arginine (Arg139). In vitro expression studies demonstrated that with 

the Tyr113His polymorphism, the corresponding mEH enzymatic activity is decreased by about 

40% (Hasset et al., 1997). On the other hand, the His139Arg polymorphism results in increased 

enzyme activity. Population studies have demonstrated that the low activity 113His allele 

correlates with an increased risk for lung cancer (Benhamou et al., 1998), colon cancer (Harrison 

et al., 1999), hepatocellular carcinoma developed after aflatoxin exposure (McGlynn et al., 

1995), and chronic obstructive pulmonary disease (Smith and Harrison, 1997). 

The mEH genotypes was shown to play a significant role in human sensitivity to the 

genotoxic effects of exposure to 1,3-butadiene (Abdel-Rahman et al., 2003, 2001). The 

carcinogenic and mutagenic effects of 1,3-butadiene are thought to be due to its epoxide 

metabolites, and the hydrolytic pathway involving mEH is the main detoxification pathway for 

1,3-butadiene-reactive intermediates in humans (Jackson et al., 2000). In a study of 

49 nonsmoking workers from two styrene-butadiene rubber plants, the hprt gene mutation assay 

was used as a biomarker of genotoxic effect of BD (Abdel-Rahman et al., 2003, 2001). AbdelRahman et al. (2003, 2001) evaluated the effect of polymorphisms in both exon 3 and exon 4 of 

the mEH gene as modifiers of individual susceptibility to the mutagenic response associated with 

exposure to 1,3-butadiene, and found a progressive increase in hprt mutant frequency with 

declining mEH activity in the high exposure group (>150 ppb). The highest frequency of hprt 

mutant lymphocytes occurred in the group with the mEH low-activity genotype. Individuals 

with low mEH activity had three- and twofold increases in hprt mutant frequency compared to 

individuals with high and intermediate mEH activity, respectively. In the low exposure group, 

there was no difference in hprt mutant frequency between high-, intermediate-, and low-activity 

individuals. Although there are no studies that evaluate the role played by mEH genotypes in 

human sensitivity to the toxicity of AN, since EH is involved in the hydrolysis of CEO and its 

elimination, polymorphisms in exon 3 and exon 4 of the mEH gene are likely to have a role in 

human susceptibility. 
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5. DOSE-RESPONSE ASSESSMENTS 

5.1. ORAL REFERENCE DOSE (RfD) 

5.1.1. Choice of Principal Study and Critical Effect 

 As previously discussed in Section 4, no human studies currently exist that involve oral 

exposures to AN. The primary route of AN exposure in humans is via inhalation. The available 

animal oral toxicity studies, however, identify forestomach lesions (i.e., squamous cell epithelial 

hyperplasia and hyperkeratosis) as the most sensitive, prevalent, and consistent noncancer effect 

associated with chronic oral exposure to AN (see Table 4-56 and Figure 5-1). Although, 

benchmark dose (BMD) modeling of dose-response data is preferred, several of the endpoints 

under consideration (i.e., incidences of chronic nephropathy, ovarian cysts, and gliosis in the 

brain in rodents) were not amenable to modeling because either there was no evidence of a dose 

response or the response was not a monotonically increasing function of dose. A 

NOAEL/LOAEL approach was used as a common basis for comparison. Using this approach, 

forestomach lesions were selected as the critical effect on which to base the derivation of the 

RfD. Although, anatomically, humans do not possess a forestomach, they do have comparable 

squamous cell epithelial tissues in their oral cavity and in the upper two-thirds of their esophagus 

(IARC, 1999). Moreover, the forestomach lesions observed in animals were not likely due to the 

direct irritating effect of AN on gastric tissue. GI bleeding has been observed with single s.c. or 

oral administration of AN in rats (Ghanayem and Ahmed, 1983) that likely resulted from the 

distribution of AN metabolites from blood into the GI mucosa. Jacob and Ahmed (2003a) have 

also demonstrated that AN or its metabolites accumulated and covalently interacted with the GI 

mucosa of F344 rats treated either orally or intravenously with 2-[14C]-AN, supporting the theory 

of metabolic incorporation and macromolecular interaction of AN or its metabolites with gastric 

tissue. 

 Two 2-year drinking water studies, one in Sprague-Dawley rats (Quast, 2002; Quast et 

al., 1980a) and the other in F344 rats (Johannsen and Levinskas, 2002b; Biodynamics 1980c), 

and a 2-year gavage study in B6C3F1 mice (NTP, 2001) provided the best available doseresponse data on which to base the RfD (Table 5-1 for rats and Table 5-2 for mice). In SpragueDawley rats, significantly elevated incidences of hyperplasia and hyperkeratosis in squamous 

epithelium of the forestomach occurred in both males and females exposed to AN in drinking 

water at the two highest concentrations administered (i.e., 100 and 300 ppm) with incidences 

approaching 100% at the highest dose. Female Sprague-Dawley rats also exhibited statistically 

significantly elevated incidences at the lowest concentration of AN administered (i.e., 35 ppm). 

In F344 rats, both males and females exposed to 3, 10, and 30 ppm AN in drinking water 

exhibited statistically significantly elevated incidences of forestomach lesions with incidences of 

approximately 20–30%. Male and female F344 rats exposed to the lowest and highest 
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concentrations of AN in drinking water (i.e., 1 and 100 ppm) did not show statistically 

significantly elevated incidences of forestomach lesions. 
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Table 5-1. Incidences of forestomach lesions (hyperplasia or 

hyperkeratosis) in Sprague-Dawley and F344 rats exposed to AN in 

drinking water for 2 years 

Predicted internal dose metricsb

Sex

Administered 

concentration 

(ppm in drinking 

water)

Administered 

dosea

(mg/kg-d)

AN-AUC in rat 

blood 

(mg/L)

CEO-AUC in rat 

blood 

(mg/L)

Incidence of 

forestomach 

lesionsc

Sprague-Dawley rats 

(Sources: Quast, 2002; Quast et al., 1980a) 

0 0 0 0 15/80 (19%) 

35 3.4 2.06 × 10-2 1.83 × 10-3 15/47 (32%) 

100 8.5 5.36 × 10-2 4.36 × 10-3 44/48 (92%)

Male 

c

300 21.3 1.46 × 10-1 9.70 × 10-3 45/48 (94%)c

0 0 0 0 20/80 (25%) 

35 4.4 2.37 × 10-2 2.07 × 10-3 23/48 (48%)c

100 10.8 6.18 × 10-2 4.87 × 10-3 41/48 (85%)c

Female 

300 25.0 1.56 × 10-1 1.01 × 10-2 47/48 (98%)c

F344 ratsd

(Sources: Johannsen and Levinskas, 2002b; Biodynamics, 1980c)

0 0 0 0 11/159 (7%) 

1 0.08 4.33 × 10-4 4.06 × 10-5 3/80 (4%) 

3 0.25 1.35 × 10-3 1.27 × 10-4 18/75 (24%)c

10 0.83 4.52 × 10-3 4.19 × 10-4 13/80 (16%)c

30 2.48 1.37 × 10-2 1.23 × 10-3 17/80 (22%)c

Male 

100 8.37 4.85 × 10-2 3.97 × 10-3 9/77 (12%) 

0 0 0 0 4/156 (3%) 

1 0.12 5.73 × 10-4 5.32 × 10-5 2/80 (3%) 

3 0.36 1.72 × 10-3 1.59 × 10-4 16/80 (20%)c

10 1.25 6.02 × 10-3 5.49 × 10-4 23/74 (31%)c

30 3.65 1.79 × 10-2 1.58 × 10-3 13/80 (16%)c

Female 

100 10.90 5.63 × 10-2 4.46 × 10-3 5/74 (7%) 

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water

intake. 

bThe EPA-modified rat physiologically based pharmacokinetic (PBPK) model of Keddaris et al. (1996) was 

employed to predict a rat internal dose (i.e., either AN-AUC or CEO-AUC concentration in blood, where AUC = 

area under the curve) resulting from the ingestion of the specified administered dose of AN consumed in six bolus 

episodes/d. 

c

Indicates significantly different (at p < 0.05) from control incidence by Fisher’s exact test. 

d

Incidences for F344 rats do not include animals from the 6- and 12-mo sacrifices and were further adjusted to 

exclude (from the denominators) rats that died between 0 and 12 mos in the study. Rats dying during this time 

period were determined from page 6 of Appendix H and Table 1 in Biodynamics (1980c) and Table 8 in 

Johannsen and Levinskas (2002b). Unscheduled deaths between 0 and 12 mos in the study occurred in two female 

controls, two males at 3 ppm, three females at 10 ppm, and three males and three females at 100 ppm. 
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Table 5-2. Incidences of forestomach lesions (hyperplasia or hyperkeratosis) 

in male and female B6C3F1 mice administered AN via gavage for 2 years 

Dose (mg/kg-d)a

Lesion site and type 0 2.5 10 20 

Males

Forestomach hyperplasia or hyperkeratosis 2/50 

(4%) 

4/50 

(8%) 

10/50a 

(20%) 

13/50b 

(26%) 

Females

Forestomach hyperplasia or hyperkeratosis 2/50 

(4%) 

2/50 

(4%) 

5/50 

(10%) 

8/50a 

(16%) 

a

Significantly elevated above vehicle control as determined by EPA using Fisher’s exact test (p ≤ 0.05). 

b

Significantly elevated above vehicle control as determined by EPA using Fisher’s exact test (p ≤ 0.01). 

Source: NTP (2001). 

In B6C3F1 mice, males exhibited statistically significantly elevated incidences of 

forestomach lesions (hyperplasia or hyperkeratosis) at the two highest doses administered (i.e., 

10 and 20 mg/kg-day), while females showed statistically significantly elevated incidences of 

forestomach lesions at the highest dose only. 

While the Johannsen and Levinskas (2002b) drinking water study with F344 rats was 

selected as the principal study on which to base the RfD, candidate RfDs were also developed 

from studies in Sprague-Dawley rats (Quast, 2002) and B6C3F1 mice (NTP, 2001) for 

comparison purposes. The Johannsen and Levinskas (2002b) study was selected as the principal 

study primarily because it employed five doses of AN, ranging from 1 to 100 ppm, and thus 

tested a more complete range of doses, especially in the low-dose region, than did either the 

Quast (2002) study in Sprague-Dawley rats or the NTP (2001) study in B6C3F1 mice, which 

both employed three doses (i.e., 35, 100, and 300 ppm in rats and 2.5, 10, and 20 mg/kg-day in 

mice). In addition, Johannsen and Levinskas (2002b) and Quast (2002) are both drinking water 

studies, which are preferred over the NTP (2001) gavage study in B6C3F1 mice because drinking 

water exposure is more relevant to humans. Finally, of these three studies1

, the Johannsen and 

Levinskas (2002b) study identified the lowest LOAELs based on an increased incidence of 

nonneoplastic stomach lesions (i.e., 0.3 mg/kg-day for males and 0.4 mg/kg-day for females). 

Therefore, hyperplasia or hyperkeratosis in F344 rats was selected as critical effect for derivation 

of RfD. 

 

1Although SD male rats in the Johannsen and Levinskas (2002a) study exhibited the lowest LOAEL (0.1 mg/kg-d) 

for all endpoints across all studies considered for RfD derivation (see Figure 5-1), this study experienced significant 

mortality, especially in the high-dose groups, rendering the results of this study highly suspect, and thus, it was 

deemed not suitable for RfD derivation. 
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5.1.2. Methods of Analysis—Including Use of PBTK Modeling 

 Candidate RfDs for AN were derived from the incidence of forestomach lesions in 

Sprague-Dawley rats, F344 rats, and B6C3F1 mice using a BMD approach. Incidences of 

forestomach lesions from chronic drinking water studies in male and female Sprague-Dawley 

rats (Quast, 2002) and F344 rats (Johannsen and Levinskas, 2002b) provided four sets of doseresponse data from which to derive candidate RfDs (see Table 5-1), while incidences of 

forestomach lesions from a chronic gavage study in male and female B6C3F1 mice provided an 

additional two sets of dose-response data (see Table 5-2). The incidence data from rats in Table 

5-1 were not combined across strains for purposes of dose-response modeling because response 

levels were different across the two strains. As described further below, dose-response modeling 

of the incidence of forestomach lesions after 2 years of AN exposure was carried out using BMD 

modeling. For rats, in addition to administered dose, two alternative internal dose metrics (AN 

in blood and CEO in blood), as estimated by PBTK modeling, were employed in BMD 

modeling. In mice, only administered dose was employed as a dose metric for BMD modeling 

purposes. 

5.1.2.1. PBTK Modeling 

In deriving candidate RfDs from the rat studies, internal dose metrics generated using 

PBTK models developed by EPA (see Section 3.5; Appendix C) based on the rat and human 

PBTK models of Kedderis et al. (1996) and Sweeney et al. (2003), respectively, were employed. 

The EPA-modified PBTK models included many realistic features, each of them leading to a 

different dose metric. The primary features of interest were estimated daily average internal 

concentrations of AN or CEO in blood (area under the curve [AUC] expressed on a 24-hour 

basis) and estimates based on continuous versus episodic exposure, with episodic exposure more 

realistically reflecting how rats (and humans) actually consume drinking water.

As indicated above, two potentially useful chemical markers of internal exposure were 

selected (i.e., the concentration in blood of the parent compound, AN, and its reactive metabolite, 

CEO). These two internal dose metrics were evaluated under an episodic exposure pattern 

because rats (and humans) consume drinking water in an episodic manner. In addition, for rats 

and mice, the externally administered AN dose was also used for deriving candidate RfDs for 

purposes of comparison with the candidate RfDs derived based on internal doses of AN and 

CEO estimated from the PBTK model. 

For this assessment, internal dose metrics were evaluated for use in cross-species 

extrapolation from rats because of the following: 

• The rat and human PBTK models incorporated species differences in physiological 

processes influencing the disposition of AN and CEO and were developed with rat in 

vivo toxicokinetic data, human in vitro metabolic data, and rat-to-human allometric 
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scaling (Section 3.5; Appendix C; Sweeney et al., 2003; Kedderis et al., 1996). As such, 

approaches using these models were expected to provide more accurate bases for 

extrapolation of dose-response relationships from rats to humans than approaches based 

on administered animal dose alone. 

• For oral exposures, PBTK model predictions of AN or CEO concentrations in blood 

appear to provide a more accurate basis for extrapolation than predictions based on 

forestomach AN-AUC or forestomach CEO-AUC concentrations because the stomach 

compartment in the PBTK model was not calibrated with measurements of AN or CEO in 

the stomach epithelium, the site of the forestomach lesions. Thus, more research is 

needed before a more physiologically meaningful stomach compartment can be 

incorporated into the model. Blood AN concentrations predicted by the rat PBTK model 

were fairly close to measured AN concentrations in rats following oral exposure, but the 

model consistently predicted higher CEO concentrations in blood than was reported in 

studies of orally exposed rats (see Figure 3 in Kedderis et al., 1996). 

Given the relative uncertainties in the PBTK predictions noted above, especially for 

CEO, both internal dose metrics (AN and CEO in blood) were used in deriving candidate RfDs 

based on the rat data, in addition to administered dose. The concentration of AN administered in 

the bioassay, in terms of mg/kg-day, was used as input into the EPA-modified rat PBTK model 

of Kedderis et al. (1996) in order to predict a rat internal dose (either AN-AUC or CEO-AUC 

concentration in blood) resulting from the ingestion of the total daily administered dose of AN 

consumed in six bolus episodes per day. The resulting predicted AN-AUC or CEO-AUC 

concentrations in rat blood are shown in Table 5-1 for male and female SD and F344 rats. 

5.1.2.2. BMD Modeling 

The incidences of forestomach lesions observed following 2 years of AN exposure in 

male and female SD and F344 rats were modeled using AN and CEO in blood, expressed in 

mg/L, as internal dose metrics. In addition, incidences of these same lesions were modeled in 

male and female SD and F344 rats, as well as male and female B6C3F1 mice, employing 

administered dose. For B6C3F1 mice, administered doses were multiplied by 5/7 to convert 5 

day/week gavage exposures to 7 day/week continuous exposures. In all cases, all of the 

dichotomous dose-response models available in EPA’s BMD Software (BMDS, version 2.0) 

(i.e., the gamma, logistic, log-logistic, probit, log-probit, multistage, Weibull, and quantal-linear 

models) were fit to these incidence data. Because the incidence of forestomach lesions in male 

and female F344 rats did not increase monotonically across all administered concentrations, 

however, only incidence data from the three lowest concentrations (i.e., 0, 1, and 3 ppm) were 

ultimately used in dose-response modeling. Although the incidence of forestomach lesions did 
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increase from 20 to 31% at 3 and 10 ppm, respectively, in female F344 rats, this dose-response 

relationship could still not be adequately described by any of the existing dichotomous doseresponse models in BMDS, and thus, the 10 ppm dose group was dropped in females prior to 

modeling. For the same reason, the incidence data from the highest dose group in male SpragueDawley rats needed to be dropped prior to BMD modeling. 

In most cases, several models fit the data equally well (i.e., exhibited χ

2

 goodness-of-fit 

p values >0.1). Of those models exhibiting adequate fit, the selected model was the one with the 

lowest Akaike’s Information Criterion (AIC) value. BMDL10 and BMDL05 estimates were then 

derived from this selected model. If more than one model shared the lowest AIC, the mean 

BMDL10 and BMDL05 were calculated, as per the EPA’s Benchmark Dose Technical Guidance 

Document (U.S. EPA, 2000b). Appendix B-1 provides additional details regarding the BMD 

modeling results used in the derivation of the RfD.

Although BMDL10 values were derived for comparison purposes, a benchmark response 

(BMR) of 5% extra risk was selected as the point of departure (POD) for deriving the RfD based 

on both biological and statistical considerations. Biologically, the endpoint selected on which to 

base the RfD derivation (i.e., forestomach lesions—hyperplasia or hyperkeratosis) is considered 

severe. Although the severity of the hyperplasia observed was generally not reported, Johannsen 

and Levinskas (2002b) concluded that, “This [forestomach] lesion has been described as 

progressing from hyperplasia and hyperkeratosis to papilloma, and ultimately to carcinoma, 

following chronic oral exposure....” Statistically, the dose at 5% extra risk identifies a POD 

near the lower end of the observed data. Consequently, 5% extra risk appears to be a reasonable 

choice for the POD for RfD derivation. 

For the two internal dose metrics selected (AN and CEO in blood), once the BMDL10 and 

BMDL05 estimates (or their means) were derived from the selected model(s), these estimates, 

expressed as rat internal AUCs (in mg/L), were then input into the EPA-modified human PBTK 

model of Sweeney et al. (2003) in order to predict the human equivalent administered dose of 

AN that would result in a human 24-hour blood AN-AUC or CEO-AUC equivalent to the 

corresponding rat AUC, again assuming six bolus ingestion episodes per day. The resulting 

predicted 95% lower bounds on the human equivalent administered dose of AN, expressed in 

mg/kg-day, represent potential PODs for deriving candidate RfDs. In the case of administered 

dose, the BMDL10 and BMDL05 estimates (or their means) are already expressed as human 

equivalent doses (HEDs) in mg/kg-day, and are thus used directly as potential PODs for deriving 

candidate RfDs. The BMDL10 and BMDL05 estimates and their corresponding PODs across the 

three dose metrics are presented in Tables 5-3, 5-4, and 5-5 for Sprague-Dawley rats, F344 rats, 

and B6C3F1 mice, respectively. 
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Table 5-3. Candidate RfDs based on BMD modeling of the incidence of forestomach lesions (hyperpla

hyperkeratosis) in male and female Sprague-Dawley rats exposed to AN in drinking water for 2 years 

Sex Endpoint Dose metric BMRa BMDLb

PODc 

(mg/kg-d) UF 

5% 0.72 mg/kg-d 0.72 100 

Administered dose (mg/kg-d) 10% 1.27 mg/kg-d 1.27 100 

5% 4.32 × 10-3 mg/L 1.27 30 

Predicted AN in blood (mg/L) 10% 7.72 × 10-3 mg/L 2.17 30 

5% 3.90 × 10-4 mg/L 3.86 × 10-2 30 

Male Forestomach lesions 

Predicted CEO in blood (mg/L) 10% 6.82 × 10-4 mg/L 6.75 × 10-2 30 

5% 0.64 mg/kg-d 0.64 100 

Administered dose (mg/kg-d) 10% 1.24 mg/kg-d 1.24 100 

5% 1.76 × 10-3 mg/L 5.35 × 10-1 30 

Predicted AN in blood (mg/L) 10% 3.62 × 10-3 mg/L 1.07 30 

5% 2.88 × 10-4 mg/L 2.84 × 10-2 30 

Female Forestomach lesions 

Predicted CEO in blood (mg/L) 10% 5.58 × 10-4 mg/L 5.51 × 10-2 30 

aBMR refers to the 95% lower confidence limit on the administered or PBPK-predicted internal dose in the rat associated with a 5 or 10% e

forestomach lesions. 

bAll dichotomous models in EPA’s BMDS (version 2.0) were fit to the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in 

data presented in Table 5-1. For BMD modeling, three different dose metrics were employed: (1) administered animal dose expressed in m(predicted) expressed in mg/L, and (3) CEO in blood (predicted) expressed in mg/L. Adequate fit of a model was achieved if the χ2 goodne

value >0.1. Of those models exhibiting adequate fit, the selected model was the model with the lowest AIC value. BMDL10 and BMDL05 e

the selected model. If more than one model shared the lowest AIC, the mean BMDL10 and BMDL05 were calculated and are presented, as p

Dose Technical Guidance Document (U.S. EPA, 2000b). Appendix B-1 provides additional details regarding these BMD modeling results

cFor administered dose, the POD is the BMDL05 or BMDL10 based on BMD modeling using administered animal dose as the dose metric. F

(AN and CEO in blood), the PODs are PBPK model-derived human equivalent administered doses of AN that would result in a human 24-h

AUC equivalent to the corresponding rat BMDL05 or BMDL10 values, assuming AN ingestion in six bolus episodes/d. 

dRfD = POD/UF. Sources: Quast (2002); Quast et al. (1980a). 
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Table 5-4. Candidate RfDs based on BMD modeling of the incidence of forestomach lesions (hyperpla

hyperkeratosis) in male and female F344 rats exposed to AN in drinking water for 2 years 

Sex Endpoint Dose metric BMRa BMDLb

PODc 

(mg/kg-d) UF 

5% 9.97 × 10-2 mg/kg-d 9.97 × 10-2 100 

Administered dose (mg/kg-d) 10% 0.151 mg/kg-d 0.151 100 

5% 5.39 × 10-4 mg/L 1.66 × 10-1 30 

Predicted AN in blood (mg/L) 10% 8.14 × 10-4 mg/L 2.50 × 10-1 30 

5% 5.06 × 10-5 mg/L 5.00 × 10-3 30 

Male Forestomach lesions 

Predicted CEO in blood (mg/L) 10% 7.65 × 10-5 mg/L 7.56 × 10-3 30 

5% 0.117 mg/kg-d 0.117 100 

Administered dose (mg/kg-d) 10% 0.209 mg/kg-d 0.209 100 

5% 5.58 × 10-4 mg/L 1.72 × 10-1 30 

Predicted AN in blood (mg/L) 10% 9.97 × 10-4 mg/L 3.06 × 10-1 30 

5% 5.17 × 10-5 mg/L 5.11 × 10-3 30 

Female Forestomach lesions 

Predicted CEO in blood (mg/L) 10% 9.23 × 10-5 mg/L 9.12 × 10-3 30 

aBMR refers to the 95% lower confidence limit on the administered or PBPK-predicted internal dose in the rat associated with a 5 or 10% e

forestomach lesions. 

bAll dichotomous models in EPA’s BMDS (version 2.0) were fit to the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in 

presented in Table 5-1. For BMD modeling, three different dose metrics were employed: (1) administered animal dose expressed in mg/kg

(predicted) expressed in mg/L, and (3) CEO in blood (predicted) expressed in mg/L. Adequate fit of a model was achieved if the χ2 goodne

p-value >0.1. Of those models exhibiting adequate fit, the selected model was the model with the lowest AIC value. BMDL10 and BMDL0

the selected model. If more than one model shared the lowest AIC, the mean BMDL10 and BMDL05 were calculated and are presented, as p

Dose Technical Guidance Document (U.S. EPA, 2000b). Appendix B-1 provides additional details regarding these BMD modeling results

cFor administered dose, the POD is the BMDL05 or BMDL10 based on BMD modeling using administered animal dose as the dose metric. F

(AN and CEO in blood), the PODs are PBPK model-derived human equivalent administered doses of AN that would result in a human 24-h

AUC equivalent to the corresponding rat BMDL05 or BMDL10 values, assuming AN ingestion in six bolus episodes/d. 

dRfD = POD/UF. Sources: Johannsen and Levinskas (2002b); Biodynamics (1980c). 
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Table 5-5. Candidate RfDs based on BMD modeling of the incidence of forestomach lesions (hyperpla

hyperkeratosis) in male and female B6C3F1 mice exposed to AN via gavage for 2 years 

Sex Endpoint Dose metric BMRa 

BMDLb

(mg/kg-d) 

PODc 

(mg/kg-d) UF 

5% 1.43 1.43 100 

Male Forestomach lesions Administered dose (mg/kg-d) 10% 3.01 3.01 100 

5% 3.02 3.02 100 

Female Forestomach lesions Administered dose (mg/kg-d) 10% 6.20 6.20 100 aBMR refers to the 95% lower confidence limit on the administered dose in the mouse associated with either a 5 or 10% extra risk for the in

lesions. 

bAll dichotomous models in EPA’s BMDS (version 2.0) were fit to the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in presented in Table 5-2. For BMD modeling, administered animal dose, expressed in mg/kg-d, was employed. Adequate fit of a model was 

of-fit statistic yielded a p-value >0.1. Of those models exhibiting adequate fit, the selected model was the model with the lowest AIC value

estimates were derived from the selected model. If more than one model shared the lowest AIC, the mean BMDL10 and BMDL05 were calc

per the EPA’s Benchmark Dose Technical Guidance Document (U.S. EPA, 2000b). Appendix B-1 provides additional details regarding the

cThe POD is the BMDL05 or BMDL10 based on BMD modeling using administered animal dose as the dose metric. No internal dose metric

because of the absence of a PBPK model for this species. 

dRfD = POD/UF. 

Source: NTP (2001). 
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5.1.3. RfD Derivation—Including Application of Uncertainty Factors (UFs) 

 In Tables 5-3 and 5-4, the candidate PODs based on the internal dose metrics (i.e., CEOAUC in blood and AN-AUC in blood) were divided by a composite UF of 30 to account for two 

areas of uncertainty. An UF of 3 (i.e., 100.5) was used to account for uncertainty associated with 

extrapolating from rats to humans. A factor of 3 was chosen instead of the default value of 10, 

because toxicokinetic uncertainty was decreased by the application of the rat and human PBTK 

models. The applied factor of 3 was selected to account for any remaining toxicokinetic 

uncertainties in the dosimetric extrapolation, and possible differences in the response of rat and 

human target tissues to AN or its metabolites (i.e., toxicodynamic differences). A default UF of 

10 was then used to account for uncertainty associated with extrapolation to individuals or 

groups within the human population who may be especially sensitive or susceptible to the 

noncancer toxicity of AN. 

The candidate PODs based on administered dose in Tables 5-3, 5-4, and 5-5 were divided 

by a composite UF of 100 to again account for two areas of uncertainty. First, a UF of 10 was 

used to account for uncertainty associated with extrapolating from rats to humans because no 

PBTK model was employed, and thus, a default factor of 10 was needed to account for both 

toxicokinetic and toxicodynamic uncertainties. Secondly, as above, a default UF of 10 was used 

to account for uncertainty associated with extrapolation to individuals or groups within the 

human population who may be especially sensitive or susceptible to the noncancer toxicity of 

AN. Considerations in selecting individual UFs are discussed in greater detail below. 

 A default UF of 10 was used to account for uncertainty associated with extrapolation to 

individuals or groups within the human population who may be especially sensitive or 

susceptible to the noncancer toxicity of AN. As discussed in Section 4.8, available data on AN 

are inadequate to reliably identify populations that may be especially susceptible to the 

noncancer toxicity of AN. There is one human case report indicating that children are more 

susceptible to AN toxicity. These data at least suggest that juvenile populations may be 

especially susceptible to the noncancerous effects of AN exposure. 

An UF to account for extrapolation from subchronic to chronic exposure was not 

necessary because of the availability of chronic oral studies in both rats and mice. 

An UF to account for LOAEL to NOAEL extrapolation was not applied because the 

BMR selected for BMD modeling, a 5% extra risk of forestomach lesions, was judged to have 

minimal biological significance. 

 A database deficiency UF was not used in the development of the RfD. Although studies 

of health effects in humans exposed to AN by the oral route are not available, the animal oral 

toxicity database is particularly robust. As discussed in Section 4.6.1, there are nine rat toxicity 

and cancer bioassays, one toxicity and cancer bioassay with B6C3F1 mice, a three-generation 

(46-week) developmental/reproductive rat toxicity study with Sprague-Dawley rats, a 12-week 

gavage study of nerve conduction velocities in male Sprague-Dawley rats, a 14-week gavage 
315 DRAFT - DO NOT CITE OR QUOTE 

toxicity bioassay in B6C3F1 mice, a developmental toxicity study in Sprague-Dawley rats 

exposed by gavage during GDs 6–15, and a 90-day study of oxidative stress indicators in the 

brain and liver of F344 rats. These animal data identify forestomach lesions as the most 

sensitive, prevalent, and consistent noncancer effect in animals associated with repeated oral 

exposure to AN, and thus provide evidence that an RfD based on this effect will be protective for 

other potential noncancer effects, including neurological, reproductive, and developmental 

effects. In addition, the data for forestomach lesions in rats and mice provide an adequate 

characterization of the dose-response relationship for the development of these lesions with 

chronic exposure, which, coupled with the application of the PBTK models for cross-species 

dosimetric extrapolation, adds to the confidence in the estimation of a chronic oral human dose 

expected to be without risk in the general population for the development of gastric lesions. 

For the purpose of this assessment, CEO-AUC in blood is considered to be the most 

appropriate dose metric to use in deriving an RfD. CEO is believed to be the reactive metabolite 

most likely responsible for the noncancer (and cancer) effects observed following AN exposure. 

Results from acute exposure studies in rats indicate that CEO plays a key role in the mode of 

action by which AN elicits stomach lesions. Research has shown that pretreatment with 

inhibitors of CYP2E1 inhibited the development of GI ulceration, following acute exposure of 

rats to AN, and doses of KCN equivalent to toxic doses of AN did not induce GI bleeding in a 

similar manner to AN (Ghanayem et al., 1985; Ghanayem and Ahmed, 1983). For oral 

exposures, then, the use of CEO-AUC as the internal dose metric for cross-species extrapolation 

is recommended. Therefore, while the PBTK model does not predict CEO in blood as accurately 

as it predicts AN in blood, CEO in blood provides the most biologically relevant dose metric for 

modeling the incidence of forestomach lesions and for extrapolating from orally exposed rats to 

humans. 

In comparing the candidate RfDs for the preferred dose metric of predicted CEO in blood 

across Tables 5-3 and 5-4, the candidate RfDs based on the forestomach lesion incidence data in 

F344 rats are about an order of magnitude lower than those candidate RfDs based on 

forestomach lesion incidence data in Sprague-Dawley rats. This comparison confirms what had 

previously been predicted (i.e., F344 rats are more sensitive to AN exposure than SpragueDawley rats). Moreover, these same candidate RfDs in F344 rats are approximately two orders 

of magnitude lower than the candidate RfDs based on administered dose in B6C3F1 mice. 

Therefore, for the critical endpoint (i.e., forestomach lesions), F344 rats are the most sensitive 

species and strain. Consequently, the RfD is 2 × 10-4 mg/kg-day. This RfD is consistent with 

the candidate RfDs derived for both male (1.67 × 10-4 mg/kg-day) and female (1.70 × 10-4

mg/kg-day) F344 rats using predicted CEO in blood as the dose metric and based on the 

incidence of forestomach lesions following chronic oral exposure to AN. 

5.1.4. Oral Data Array for Noncancer Endpoints 
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LOAELs based on selected animal studies presented in Table 4-56 are arrayed for 

comparison in Figure 5-1, and provide a perspective on the RfD developed in the previous 

section from data in F344 rats (Johannsen and Levinskas, 2002b). Figure 5-1 should be 

interpreted with caution, however, because the LOAELs across studies are not necessarily 

comparable due to the lack of any indication regarding the confidence in the data sets from 

which the LOAELs were derived. In addition, the nature, severity, and incidence of effects at a 

LOAEL are also likely to vary. For example, the incidence of forestomach squamous cell 

hyperplasia in male and female F344 rats at the LOAEL were both 17% (see Figure 5-1), while 

in Sprague-Dawley rats, the incidence of the same lesions at the LOAEL in males and females 

were 73 and 23%, respectively. Figure 5-1 provides a graphical comparison of organ-specific 

LOAELs from chronic studies in experimental animals. The predominant noncancer effect of 

chronic oral exposure to AN is hyperplasia and hyperkeratosis of squamous cell epithelial tissue 

in the forestomach. The LOAELs for this endpoint are lower than those observed for chronic 

nephropathy, gliosis, ovarian cysts, or developmental effects. Therefore, the RfD based on 

hyperplasia and hyperkeratosis of squamous cell epithelial tissue in the forestomach should be 

protective of other effects resulting from oral exposure to AN. 
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Figure 5-1. Comparison of LOAELs for noncancer effects across target organs following oral exposure to 

0.3 0.4

8.5

4.4

0.1

10.7

7.1

14.3

3.4

10.8

1.8

02468

101214161820

Squamous

cell

hyperplasia

in F344 male

rats

[Johannsen

& Levinskas,

2002b]

Squamous

cell

hyperplasia

in F344

female rats

[Johannsen

& Levinskas,

2002b]

Squamous

cell

hyperplasia

in SD male

rats [Quast,

2002]

Squamous

cell

hyperplasia

in SD female

rats [Quast,

2002]

Squamous

cell

hyperplasia

in SD male

rats

[Johannsen

& Levinskas,

2002a]

Squamous

cell

hyperplasia

in SD female

rats

[Johannsen

& Levinskas,

2002a]

Squamous

cell

hyperplasia

in B6C3F1

male mice

[NTP, 2001]

Squamous

cell

hyperplasia

in B6C3F1

female mice

[NTP, 2001]

Chronic

nephropathy

(severe) in

SD male rats

[Quast, 2002]

Chronic

nephropathy

(minimal) in

SD female

rats [Quast,

2002]

Ovarian

cysts in

B6C3F1

female mice

[NTP, 2001]

Target Organ Effects

Acrylonitrile Dose

(mg/kg-day) [73%]

[23%]

[18%]

[10%]

[10%]

[14%]

[31%]

[16%]

[5%]

[17%] [17%]

[ ] = Percent of animals with effects at the LOAEL (corrected for background)
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5.1.5. Previous RfD Assessment 

No RfD was derived in the previous IRIS assessment of AN. 

5.2. INHALATION RfC 

5.2.1. Choice of Principal Study and Critical Effect 

 As discussed in Section 4.1.2, results from several cross-sectional health examinations 

and surveys of AN-exposed workers (Chen et al., 2000; Kaneko and Omae, 1992; Muto et al., 

1992; Sakurai et al., 1978) and a study of the performance on a battery of neurobehavioral tests 

by exposed workers (Lu et al., 2005a) identified increased prevalence of subjective neurological 

symptoms (e.g., headache, poor memory, and irritability) and small performance deficits in 

neurobehavioral tests as the critical effects from chronic occupational inhalation exposure to AN. 

An increased prevalence of subjective symptoms was associated with average workplace air 

concentrations of 1.13 ppm (Muto et al., 1992), 1.8 ppm (Kaneko and Omae, 1992), and 

0.48 ppm (Chen et al., 2000). Deficits in the neurobehavioral tests were associated with average 

workplace air concentrations of 0.11 ppm for a group of workers designated as monomer 

workers and 0.91 ppm for a group of workers designated as fiber workers (Lu et al., 2005a). 

 Cross-sectional epidemiologic surveys of reproductive outcomes in AN-exposed workers 

found increased prevalence of adverse reproductive outcomes associated with somewhat higher 

average workplace air concentrations of 3.7 ppm (Dong and Pan, 1995), 3.6 ppm (Dong et al., 

2000a), and 7.5 ppm (Li, 2000). Adverse outcomes with statistically significantly increased 

prevalence compared with unexposed workers included the following: 

• Premature deliveries—10.7% in unexposed wives of exposed males vs. 3.5% in 

controls (implying the sperm of exposed males may be affected) (Dong and Pan, 

1995); 8.2% in exposed females vs. 3.9% in controls (Dong et al., 2000b); and 11.6% 

in exposed females vs. 4.7% in controls (Li, 2000) 

• Stillbirths—4.5% in exposed females vs. 0% in controls (Dong and Pan, 1995); 2.7% 

in exposed females vs. 0% in controls (Dong et al., 2000b) 

• Sterility—5.0% in wives of exposed males vs. 1.8% in wives of controls (Dong and 

Pan, 1995); 2.6% in exposed females vs. 0.8% in controls (Li, 2000) 

• Birth defects—21.3% in exposed females vs. 4.8% in controls (Dong et al., 2000b); 

25.4% in exposed females vs. 4.2% in controls (Li, 2000) 

• Pregnancy complications—20.8% in exposed females vs. 7.1% in controls (Li, 2000) 
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Exposure levels associated with adverse effects in the available animal inhalation toxicity 

studies were higher than the workplace air concentrations associated with adverse effects in 

AN-exposed workers (see Table 4-57). With repeated inhalation exposure to AN, effects noted 

with the lowest exposure levels were as follows: 

• Increased incidence of nasal epithelial lesions in Sprague-Dawley rats exposed for 

2 years to 20 ppm AN (Quast et al., 1980b) 

• Deficits in sensory nerve conduction in the tail nerve of Sprague-Dawley rats exposed for 

12 weeks to AN concentrations ≥50 ppm, but not 25 ppm (Gagnaire et al., 1998) 

• Increased incidence of litters with short tail, short trunk, missing vertebrae, or anteriorly 

displaced ovaries (combined) in Sprague-Dawley rats exposed to AN concentrations of 

80 ppm, but not 40 ppm, on GDs 6–15 (Murray et al., 1978) 

• Decreased fetal weight gain per litter in Sprague-Dawley rats exposed to AN 

concentrations ≥25 ppm, but not to 12 ppm, on GDs 6–20 (Saillenfait et al., 1993) 

 The cross-sectional study of neurobehavioral performance in acrylic fiber workers by Lu 

et al. (2005a) was selected as the principal study for deriving the RfC because it is the best 

available study that identified neurobehavioral effects in workers exposed to AN. Previous 

occupational studies by Kaneko and Omae (1992) and Muto et al. (1992) reported subjective 

neurological symptoms (e.g., poor memory and irritability) in exposed workers. Lu et al. 

(2005a) utilized the WHO-recommended NCTB administered by trained physicians to evaluate 

these neurobehavioral effects systematically. Hence, the results were more reliable when 

compared with those based on self reporting. In addition, neurobehavioral effects were also 

reported in AN-treated rats (Rongzhu et al., 2007; Ghanayem et al. 1991). Confounding by other 

workplace exposures is not considered likely. 

The distribution of employment duration for the monomer workers was 1–10 years, 23%; 

11–20 years, 42%; and >20 years, 35%. For fiber workers, the distribution was 1–10 years, 

47%; 11–20 years, 23%; and >20 years, 30%. Geometric mean workplace AN air concentrations 

were 0.11 ppm for the monomer operations areas (range 0–1.70 ppm based on 390 stationary air 

samples collected between 1997 and 1999) and 0.91 ppm for the acrylic fiber operations areas 

(range 0.00–8.34 ppm based on 570 samples). For monomer workers, the following statistically 

significant deficits, compared with unexposed controls, were measured: 

• 41–68% higher scores for negative moods (i.e., anger, confusion, depression, fatigue, and 

tension) in the Profile of Mood States Test. 
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• 16% longer times in the Simple Reaction Time Test of attention and visual response 

speed. 

• 21% lower scores in the backward sequence of the Digit Span Test of auditory memory. 

• 4% lower scores in the Benton Visual Retention Test, a measure of visual perception and 

memory. 

• 14% lower scores in the Pursuit Aiming II Test, a measure of motor steadiness. 

 Statistically significant deficits were not found in the Santa Ana Test for manual dexterity 

or in the Digital Symbol Test for perceptual motor speed. Fiber workers showed deficits of a 

similar magnitude in many of the same tests (20–44% higher in Profile of Mood States Test, 

10% longer in the Simple Reaction Time Test, 24% lower score in the backward sequence of the 

Digit Span Test, 4% lower scores in the Benton Visual Retention Test, and 10% lower scores in 

the Pursuit Aiming II Test), with the exception that scores in the forward sequence of the Digit 

Span Test were significantly better than those of unexposed workers. 

 Lu et al. (2005a) reported that air in these workplaces also presented potential exposures 

to cyanide in the monomer operations areas and methyl methacrylate in the fiber areas, but 

measurements of these chemicals in air samples were not made. Cyanide is a breakdown product 

of AN. Its concentration in the monomer plant should be low compared with AN. Methyl 

methacrylate was generally used as a minor component in the production of acrylic fiber. With 

an RfC of 0.7 mg/m3 (U.S. EPA, 1998b), its toxicity is much lower than that for AN. Therefore, 

potential exposure to these confounders was determined to be an insufficient limitation to 

preclude using Lu et al. (2005a) to identify neurological effects as potential health hazards from 

occupational exposure to AN and derive an RfC for chronic inhalation exposure to AN. Both 

groups of workers showed deficits, despite being exposed to different potentially confounding 

chemicals, and the results from this study are consistent with the increased prevalence of 

subjective symptoms in other studies of AN-exposed workers. 

 An RfC based on the results from the chronic inhalation bioassay with Sprague-Dawley 

rats (Quast et al., 1980b) was also derived for comparison purposes. As discussed in 

Section 4.6.2, statistically significant increased incidence of inflammatory and degenerative 

nasal lesions (i.e., hyperplasia of mucus-secreting cells in males and flattening of respiratory 

epithelium in females) occurred in rats exposed to the lowest level of AN in this two-year 

bioassay, 20 ppm (6 hours/day, 5 days/week), and represent the critical effects in animals 

exposed to AN chronically by inhalation. At the higher exposure level, 80 ppm, other nasal 

lesions with elevated incidences were suppurative rhinitis and focal erosion of the mucous lining 
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in females and hyperplasia of respiratory epithelium in males and females. Other lesions with 

elevated incidences at the 80 ppm exposure level were gliosis and perivascular cuffing in the 

brain of males and females, focal nephrosis and thyroid cysts in males, and hepatic necrosis in 

females (which was also elevated at 20 ppm). 

5.2.2. Methods of Analysis 

 A NOAEL/LOAEL approach to the human data was used to derive the RfC. The 

performance deficits measured in monomer and fiber workers were judged to be adverse and the 

geometric mean of the range of air concentrations measured for the monomer work areas, 

0.11 ppm (0.24 mg/m3), was selected as the POD for deriving the RfC. 

 For the animal data, a BMD approach was used. Dose-response models available in 

EPA’s BMDS (version 1.3.2) were fit to incidence data for flattening of the respiratory 

epithelium in female rats and hyperplasia of mucus-secreting cells in male rats. Prior to 

modeling, animal exposure data were converted to human equivalent concentrations (HECs) 

using U.S. EPA (1994) methods for extrathoracic respiratory effects from a category 1 gas 

(Table 5-6). A BMR of 10% extra risk was selected as the POD for deriving the RfC based on 

both biological and statistical considerations. Biologically, the endpoints selected on which to 

derive the RfC (i.e., flattening of the respiratory epithelium in female rats and hyperplasia of 

mucus-secreting cells in male rats) are relatively benign. Statistically, the dose at 10% extra risk 

identifies a POD near the lower end of the data range. Thus, a BMR of 10% extra risk was 

selected for this analysis consistent with the U.S. EPA (. Benchmark concentrations (BMCs) and 

the 95% lower bounds on the BMCs (BMCL10s) for the best-fitting models are shown in Table 5-

6. Potential PODs for the animal-based RfC are the BMCL10s of 0.082 and 0.059 mg/m3 for 

nasal effects in male and female rats, respectively. More detailed information on these BMD 

modeling results is presented in Appendix B-2. 
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Table 5-6. Results of dose-response analyses of incidence data for selected 

nasal lesions in male and female Sprague-Dawley rats exposed by inhalation 

to AN for 2 years 

Nasal lesion

Administered 

concentration 

(mg/m3

)

HEC 

(mg/m3)

a

Lesion 

incidence

BMC10

(mg/m3

)

b

BMCL10

(mg/m3

)

b

Candidate 

RfC 

(mg/m3)

c

0 0 0/11 (0%) 

43.4 2.1 7/12 (58%)d

Hyperplasia of mucussecreting cells in males 

173.6 8.5 8/10 (80%)d

0.187 0.082 3 × 10-3

0 0 1/11 (9.1%) 

43.4 2.1 7/10 (70%)d

Flattening of respiratory 

epithelium in females 

173.6 8.5 8/10 (80%)d

0.162 0.059 2 × 10-3

aHEC as per U.S. EPA (1994) methods for a category 1 gas producing an upper respiratory effect. 

Sample calculation: 43.4 mg/m3× 6h/24h × 5d/7d × RGDRET = 2.1 mg/m3, where RGDRET = 0.275 = [VE/SAET] rat 

÷ [VE/SAET] human; VE = minute volume = 0.281 L/min rat, 13.8 L/min human; SAET = extrathoracic surface area = 

15 cm2 rat, 200 cm2 human. 

bBMC10 and BMCL10 refer to the BMD model-predicted air concentration and its 95% lower confidence limit, 

associated with a 10% extra risk for having nonneoplastic nasal lesions. BMC10s and BMCL10s are estimated from 

the best-fitting model among those fit to the data. More detailed information on the BMD modeling results is 

presented in Appendix B-2. 

cRfC = BMCL10/UF, where the UF is 30. 

d

Statistically significantly different from control value as reported by Quast et al., 1980b. 

Source: Quast et al. (1980b). 

5.2.3. RfC Derivation—Including Application of UFs 

 The LOAEL of 0.11 ppm (0.24 mg/m3

) from Lu et al. (2005a) for statistically significant 

performance deficits in neurobehavioral tests of mood, attention and speed, auditory memory, 

visual perception and memory, and motor steadiness in humans occupationally exposed to AN 

via inhalation was used for derivation of the RfC. Since the LOAEL was from an occupational 

study, the adjusted LOAEL for continuous exposure was obtained by multiplying the study 

LOAEL by a factor of 0.36 (5 days/7 days × 10 m3

/day ÷ 20 m3/day). This adjusted LOAEL 

(LOAELADJ) of 0.03 ppm (0.086 mg/m3) was divided by a composite UF of 100 to arrive at an 

RfC of 9 × 10-4 mg/m3. This two-step calculation is illustrated below: 

1. LOAELADJ = 0.24 mg/m3 × 0.36 = 0.086 mg/m3 

2. RfC = 0.086 mg/m3 ÷ 100 = 0.00086 mg/m3 or 0.9 μg/m3 

 An UF of 10 was used for extrapolating from a LOAEL to a NOAEL. The RfC is 

derived from an occupational study. A default UF of 10 was used to account for sensitive or 

susceptible members of the general population, including children. A database UF was not 
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applied since the database for AN is robust, and occupational exposure studies exist that 

evaluated reproductive effects in AN-exposed workers. 

 Comparative animal-based RfCs of 3 × 10-3 mg/m3 (or 3 μg/m3) and 2 × 10-3 mg/m3 (or 

2 μg/m3) were derived by dividing the BMDL10s of 0.082 mg/m3 and 0.059 mg/m3 for nasal 

lesions in male and female rats, respectively, by UFs of 30 (3 for extrapolating from rats to 

humans using the default U.S. EPA [1994] dosimetric adjustment and 10 to protect sensitive 

subpopulations). These candidate RfCs are displayed in Table 5-6. Extrapolating the results 

from animal toxicity studies to derive an RfC has inherently greater uncertainty than using the 

results from the cross-sectional studies of health effects in human workers; however, the humanbased and animal-based RfCs differ by about twofold. For this assessment, the human-based 

RfC of 9 × 10-4 mg/m3

 or 0.9 μg/m3 is the recommended value. 

5.2.4. Inhalation Data Array for Noncancer Endpoints 

LOAELs based on selected studies included in Table 4-57 are arrayed in Figure 5-2 and 

provide perspective on the RfC derived from Lu et al. (2005a). Figure 5-2 should be interpreted 

with caution because the LOAELs across studies are not necessarily comparable, due to inherent 

limitations in NOAEL/LOAEL determination (U.S. EPA, 2000b), nor is the confidence in the 

data sets from which the LOAELs were derived the same. The nature, severity, and incidence of 

effects occurring at a LOAEL are likely to vary. The text in Section 5.2.1 should be consulted 

for a more complete understanding of the issues associated with each data set and the rationale 

for the selection of the critical effect and principal study used to derive the RfC. The most 

sensitive endpoint is the neurobehavioral effects identified in Lu et al. (2005a) and this endpoint 

provides the basis for the derivation of the RfC. 
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1.8

1.1

0.5

0.1

0.4

3.7 3.6

0123456789

10

Subjective

Symptoms in Males

[Kaneko & Omae,

1992]

Subjective

Symptoms in Males

[Muto et al., 1992]

Subjective

Symptoms in Males

and Females

[Chen et al., 2000]

Neurobehavioral

Deficits in Males

and Females

[Lu et al., 2005a]

Decrease in Sperm

Density and

Number and Sex

Chromosome

Aneuploidy in Males

[Xu et al., 2003]

Adverse

Reproductive

Outcomes in Males

and Females

[Dong & Pan, 1995]

Adverse

Reproductive

Outcomes in Males

and Females

[Dong et al., 2000b]

Observed Effects

Acrylonitrile Exposure

(ppm in air)

Figure 5-2. Comparison of LOAELs for noncancer effects in human workers following inhalation exposure to AN.
325 DRAFT - DO NOT CITE OR QUOTE 

5.2.5. Previous Inhalation Assessment 

 Previously, EPA derived an RfC of 2 × 10-3 mg/m3 from the low exposure level (i.e., 

20 ppm AN, duration-adjusted to a LOAELHEC of 1.9 mg/m3) in the Quast et al. (1980b) animal 

study, which was identified as a LOAEL for the onset of hyperplasia of the mucus-secreting 

cells. The LOAELHEC was adjusted with a combined UF of 1,000 to derive the RfC. This 

composite UF was made up of 10 for intraspecies variability; 3 for interspecies variability, where 

dosimetric adjustments had already been applied to account for part of this area of uncertainty; 

3 for extrapolation from a minimally adverse LOAEL to a NOAEL; and 10 for database 

deficiencies. The latter UF was applied because of the lack of an inhalation bioassay in a second 

species and the absence of reproductive data by the inhalation route where an oral study existed 

that showed reproductive effects. 

 New pertinent information, available since the previous RfC was developed, includes: 

(1) several cross-sectional health examinations and surveys of subjective symptoms and 

reproductive outcomes in AN-exposed workers; (2) a published cross-sectional study of 

performance in a battery of neurobehavioral tests by AN-exposed workers (Lu et al., 2005a) (the 

principal study for the current RfC); (3) toxicokinetic information and the development of PBTK 

models for AN; and (4) two inhalation developmental toxicity studies in rats. 

5.3. UNCERTAINTIES IN THE ORAL RfD AND INHALATION RfC 

The following discussion identifies uncertainties associated with the RfD or RfC for AN. 

As presented earlier in this chapter (Sections 5.1.2 and 5.1.3; and 5.2.2 and 5.2.3), the UF 

approach, following EPA methodology for RfC and RfD development (U.S. EPA, 2002, 1994), 

was applied to a POD. For the RfD, the POD was determined as BMDL05 of internal dose 

estimated from rats and subsequently converted to a HED. For the RfC, a LOAEL was derived 

from an epidemiologic study for neurobehavioral effects. Factors accounting for uncertainties 

associated with a number of steps in the analyses were adopted to account for extrapolating from 

the POD, the starting point in the analysis, to a no-adverse-effect level (LOAEL to NOAEL) 

given insufficient data in the principal study for BMD modeling, to a diverse population of 

varying susceptibilities. These extrapolations are carried out with default approaches instead of 

data on AN, given the paucity of experimental AN data to inform individual steps. 

Selection of principal study and critical effect for reference value determination

Hyperplasia and hyperkeratosis of squamous epithelium of the forestomach was selected 

as the critical effect for RfD. This effect is the most prevalent, consistent, and most sensitive 

effect in rats and mice. Since GI bleeding occurs after s.c. injection of AN in rats, this effect is 

probably not due to local irritation on gastric tissues, but is likely due to binding of CEO to GI 

mucosa. Although humans do not possess a forestomach, humans do have comparable 

squamous cell epithelial tissues in their oral cavity and the upper two-thirds of their esophagus 

(IARC, 1999). Thus, there is little uncertainty that this effect is relevant to humans.
326 DRAFT - DO NOT CITE OR QUOTE 

 For derivation of the RfC, both a 2-year rat inhalation study and epidemiologic studies 

are available. To reduce uncertainty in extrapolating from animals to humans, epidemiologic 

studies are preferred. Several earlier cross-sectional health surveys of AN-exposed workers 

reported subjective neurological symptoms. In addition, adverse reproductive outcomes were 

also found in cross-sectional epidemiologic surveys of AN-exposed workers in China. 

Neurobehavioral effects of AN-exposed workers were selected as the critical effect since this 

effect was observed from several occupational studies with workers chronically exposed to AN 

via the inhalation route. 

 Lu et al. (2005a) mentioned several limitations of this study. One was that the cited 

exposure data represented estimates of previous exposure levels and no contemporaneous 

personal monitoring data were available. Furthermore, as the NCTB was developed for 

populations in Europe and North America, it is not known to what extent cultural differences 

may have affected results of the Profile of Mood States Test, shown to be sensitive to cultural 

differences. In addition, the study authors could not rule out the possibility that examiner drift 

may have affected the results. Selection bias among volunteers in different groups was 

mentioned as a possible confounding effect, but was discounted on the basis that the 

participation among exposed workers was so high. Moreover, the largest measures of 

neurobehavioral effects occurred in the acrylic fiber workers, who had lower average AN 

exposure levels. 

Animal to human extrapolation 

No human oral exposure studies are available for derivation of the RfD. For derivation of 

the RfD, extrapolating dose-response data from animals to humans is a source of uncertainty. A 

PBTK model, which has its own associated uncertainties, was used to address toxicokinetic 

differences between animals and humans. Uncertainties of the PBTK model are discussed as 

part of the overall uncertainty discussion (Section 5.4.4.5), with quantitative details given in 

Appendix D. Residual uncertainties pertaining to unknown interspecies differences in 

pharmacodynamics were addressed by application of a UF of 3. 

 A human occupational exposure study (Lu et al., 2005a) was used for derivation of the 

RfC, eliminating uncertainty associated with extrapolation from animals to humans. An RfC 

was also derived from a two-year inhalation study of rats based on increased incidence of 

inflammatory and degenerative nasal lesions. This alternative RfC was, at most, threefold higher 

than the RfC derived from Lu et al. (2005a). 

Dose-response modeling 

BMD modeling was used to estimate the POD for the RfD. While models with better 

biological support may exist, the selected models provided adequate mathematical fits to the 

experimental data sets. BMD modeling has advantages over a POD based on a NOAEL or 
327 DRAFT - DO NOT CITE OR QUOTE 

LOAEL because NOAELs/LOAELs are a reflection of the particular exposure concentration or 

dose at which a study was conducted, they do not make use of the dose-response curve, and they 

do not address the variability of the study population. NOAELs and LOAELs also are less 

amenable to quantitative uncertainty analysis. 

The RfC was based on a LOAEL identified from an occupational epidemiology study. 

As stated above, there are several reasons to prefer a POD obtained from BMD modeling. 

However, the available data only supported a LOAEL. A UF to address extrapolation to a less 

adverse response level was applied. 

Intrahuman variability 

Heterogeneity among humans is another source of uncertainty. Uncertainty related to 

human variation needs consideration, also, in extrapolation from a small subset of presumably 

healthy humans (i.e., workers) to a larger, more diverse general population. Available data from 

animal studies provide no evidence of gender differences in susceptibility to toxicity of AN, 

although no data are available regarding possible gender differences in susceptibility. Human 

genetic polymorphisms in CYP2E1 activities likely contribute to variability in human 

susceptibility to the toxic effects of AN (see Section 4.8.4.1). A UF of 10 was used to account 

for intrahuman variability for derivation of RfD and RfC. A factor of 10 has been found to be 

generally sufficient to account for human variability in response to chemical exposure (Renwick 

and Lazarus, 1998). 

5.4. CANCER ASSESSMENT 

5.4.1. Choice of Study/Data—with Rationale and Justification 

As previously discussed in Section 4.1.2.2, evidence of a possible association between 

exposure to AN and cancer in humans has been found in some studies. The best available 

occupational epidemiologic study (Blair et al., 1998) reported that workers exposed to AN via 

inhalation in the highest cumulative exposure category (i.e., >8 ppm-years) with more than 

20 years of employment displayed a twofold increased risk of death from lung cancer compared 

with unexposed workers (RR = 2.1, 95% CI = 1.2–3.8). To date, Blair et al. (1998) is largest 

cohort study to assess the relationship between AN and cancer, following 25,460 workers in 

eight AN-producing facilities, with two-thirds of this cohort having a follow-up period of over 

20 years. The large sample size and the duration of follow-up time in this study provides a good 

opportunity to detect any substantial elevation of case-specific cancer deaths. The findings from 

Blair et al. (1998) are not inconsistent with other studies evaluating carcinogenic endpoints from 

AN exposure. However, Blair et al. (1998) addressed known problems with earlier studies by 

quantifying exposures, examining potential confounding from smoking, and employing an 

internal control group of unexposed workers. And although only 5% of the cohort had died by 

the time of analysis, this study has a large number of observed deaths that can be used to assess 
328 DRAFT - DO NOT CITE OR QUOTE 

the relationship between AN-exposure and cancer based on cancer mortality. Also, Blair et al. 

(1998) utilized a detail job-exposure matrix as part of the exposure assessment. For these 

reasons, data from Blair et al. (1998) were chosen to derive an inhalation unit risk (IUR) for AN. 

Additionally, the use of epidemiology data for the derivation of the IUR, versus using data from 

an animal bioassay, reduces uncertainty inherent to animal to human extrapolation. 

Sections 4.6.1 and 4.6.2 summarized the current animal data on AN indicating that it is a 

multiple-site carcinogen in chronic oral and inhalation bioassays with rats and mice. The best 

available animal studies for evaluating the dose-response relationship between AN exposures 

and forestomach, CNS, Zymbal gland, tongue, and mammary gland tumors were two chronic 

drinking water studies, one with Sprague-Dawley rats exposed to 0, 35, 100, or 300 ppm AN in 

drinking water for 2 years (Quast, 2002; Quast et al., 1980a) and the other with F344 rats 

exposed to 0, 1, 3, 10, 30, or 100 ppm AN in drinking water for 2 years (Johannsen and 

Levinskas, 2002b; Biodynamics, 1980c). In addition, data from another bioassay with SpragueDawley rats exposed to AN in drinking water at concentrations of 0, 1, or 100 ppm for 2 years 

were also considered (Johannsen and Levinskas, 2002a; Biodynamics, 1980a). In the absence of 

definitive human studies demonstrating the carcinogenicity of chronic oral exposure to AN, 

developing an oral cancer slope factor (CSF) from these animal studies is reasonable, especially 

because the application of the AN PBTK models described in Chapter 3 can decrease the 

toxicokinetic uncertainty in the interspecies extrapolation and in the mode of action of 

carcinogenicity of AN in rodents versus humans. 

Animal data from the only available chronic inhalation cancer bioassay with multiple 

exposure levels (Dow Chemical Co., 1992a; Quast et al., 1980b) were also used to develop an 

IUR to compare with the one derived from AN-exposed workers (Blair et al., 1998). In this 

animal study, male and female Sprague-Dawley rats were exposed to 0, 20, or 80 ppm AN in air, 

6 hours/day, 5 days/week, for 2 years. At 80 ppm, significantly increased incidences of 

astrocytomas and glial cell proliferation and Zymbal gland tumors in males and females, 

malignant mammary gland tumors (adenocarcinomas) in females, as well as intestinal and tongue 

tumors in males, were found. At 20 ppm, male and female rats showed increased incidences of 

astrocytomas and glial cell proliferation and Zymbal gland tumors. IUR estimates were derived 

based on dose-response data for these tumors using the AN PBTK models previously described to 

dosimetrically extrapolate from rats to humans. 

5.4.2. Dose-Response Data 

5.4.2.1. Human Occupational Data 

An analysis of the lung cancer mortality and AN exposure data from the Blair et al. 

(1998) study was conducted to derive an IUR estimate for AN. This analysis used the approach 

described by Starr et al. (2004) in which the risk of death from lung cancer in AN-exposed 

workers was characterized using a semi-parametric Cox regression model with time-dependent 
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covariates. The Cox regression model has several advantages in that it allows inclusion of 

individual exposure histories and utilizes internal controls, thus avoiding confounding by the 

“healthy worker” effect. In contrast to the analysis done by Starr et al. (2004), the analysis 

conducted for this assessment included the entire cohort (not just white male workers), and the 

final model only had cumulative exposure as a covariate. Starr et al. (2004) included a second 

covariate in their final model, plant of employment. This analysis is further described in 

Appendix B-7. 

5.4.2.2. Rat Oral Data 

Incidence data for forestomach, CNS, Zymbal gland, tongue, and mammary gland tumors 

in Sprague-Dawley and F344 rats exposed to AN in drinking water for 2 years were used to 

develop site-specific oral CSFs for AN (Tables 5-7–5-9). Tumor incidences in F344 rats were 

adjusted to exclude animals dying before the first appearance of each tumor type, which ranged 

from day 419 to 495. No early mortality adjustments were made to the cumulative tumor 

incidences from the Sprague-Dawley bioassay (Quast, 2002) because CNS and Zymbal gland 

tumors were seen in some high-dose female rats as early as 7 months (210 days) after exposure 

began, and no differences in survival were observed across the dose groups during the first 

6 months of the study. 
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Table 5-7. Incidence of CNS tumors in Sprague-Dawley and F344 rats 

exposed to AN in drinking water for 2 years 

Sprague-Dawley rats 

(Quast, 2002; Quast et al., 1980a)a

Sex 

AN drinking water 

concentration (ppm) Glial cell proliferationb Astrocytomas Overall CNS tumors

0 0/80 1/80 1/80

35 4/47c 8/47c 12/47c

100 3/48 19/48 22/48

Male 

c

300 7/48c 23/48c 30/48c

0 0/80 1/80 1/80

35 3/48 17/48c 20/48c

100 3/48 22/48c 25/48c

Female 

300 7/48c

 24/48c 31/48c

F344 rats 

(Johannsen and Levinskas, 2002b; Biodynamics, 1980c)

d

Glial cell proliferationb Astrocytomas Sex AN drinking water 

concentration (ppm) Brain Spinal cord Brain Spinal cord 

Overall CNS 

tumors 

0 0/160 0/156 2/160 1/156 3/160 

1 0/80 0/79 2/80 0/79 2/80 

3 0/78 0/70 1/78 0/70 1/78 

10 0/80 0/78 2/80 0/78 2/80 

30 0/79 0/79 10/79c 0/79 10/79c

Male 

100 0/76 0/70 21/76c

 4/70c 25/76c

0 0/157 0/155 1/157 0/155 1/157 

1 0/80 0/78 1/80 0/78 1/80 

3 0/80 0/79 2/80 0/79 2/80 

10 0/77 0/72 4/75 1/72 5/75 

30 0/80 0/87 6/80c 0/77 6/80c

Female 

100 0/76 0/69 23/76c 1/69 24/76c

a

Incidence denominators were calculated from the total number of animals examined from the beginning of the 

study. Numerators for CNS tumor incidences (glial cell proliferation, astrocytomas, or overall incidence of glial 

cell proliferation or astrocytomas) for these Sprague-Dawley rats were reported as combined brain and spinal cord 

lesions by Quast et al. (1980a). 

bGlial cell proliferation is a smaller-sized lesion, either focal or multifocal, than astrocytomas, suggestive of an early 

tumor. 

c

Statistically significantly different from controls (p < 0.05) as calculated by the study authors. 

dThe denominators for incidences in these F344 rats exclude rats from the 6- and 12-mo sacrifices and unscheduled 

deaths prior to the 12-mo sacrifice. Numerators for the overall incidences were the number of rats with astrocytomas 

in brain or spinal cord. Reviews of summaries of individual animal pathology reports for this study (Appendix H, 

Biodynamics, 1980c) indicated that five of the seven F344 rats showing spinal cord astrocytomas also showed a 

brain astrocytoma; thus, the number was not always as great as the sum of the numerators for the incidences of these 

lesions in the two tissues (e.g., 21/76 male 100-ppm brain tissues had astrocytomas and 4/70 male 100-ppm spinal 

cord tissues had astrocytomas, but all four rats with astrocytomas also had brain astrocytomas). Because the 

response to AN was predominately in brain tissue and a few spinal cord tissue samples were missing in each 

exposure group, denominators for the overall incidences were taken as the number of rats examined for brain lesions.
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Table 5-8. Incidence of mammary gland tumors in F344 and SpragueDawley rats exposed to AN in drinking water for 2 years

Sex

AN drinking water 

concentration 

(ppm)

Benign mammary gland 

tumorsa

Malignant 

mammary 

gland tumorsb

Benign and/or 

malignant mammary 

gland tumors

F344 rats 

(Johannsen and Levinskas, 2002b; Biodynamics, 1980c)

c,d

0 

1 

3 

10 

30 

Male 

100 

No statistically significantly elevated incidences of mammary gland 

tumors were found in exposed groups compared with controls. 

0 12/156 3/156 14/156 

1 5/80 4/80 8/80 

3 6/80 0/80 6/80 

10 8/79 1/78 9/80 

30 9/80 3/80 12/80 

Female 

100 9/73 6/73e

 14/73e

Sprague-Dawley rats 

(Quast, 2002; Quast et al., 1980a)f

0 

35 

100 

Male 

300 

Not 

reported 

Not 

reported 

Not 

reported 

0 52/80 1/80 58/80 

35 35/48 1/48 42/48e 

100 33/48 3/48 42/48e 

Female 

300 22/48 10/48e 35/48 

a

Incidence includes fibroadenomas for F344 rats and fibroadenomas/adenofibromas/adenomas for Sprague-Dawley 

rats. 

b

Incidence includes adenocarcinomas and carcinomas. 

cThe denominators for tumor incidences in F344 rats excluded rats from the 6- and 12-mo sacrifices and rats that 

died prior to 12 mos. Mammary gland tumor incidences are for animals scheduled for the 18-mo and terminal 

sacrifices. Microscopic examinations were only conducted on mammary glands showing gross signs of tumors—

the inclusion of all rats living for >52 wks in the denominators assumes that rats without gross signs of tumors were 

also without microscopic neoplastic changes. 

dAnimals with multiple tumor types within a tissue were counted only once. 

e

Statistically significantly different from controls (at p < 0.05) via Fisher’s exact test. 

fDenominators were calculated from the total number of animals examined from the beginning of the study. 

Incidences were reported as total number of rats with benign-only, malignant-only, or benign and/or malignant 

tumors. 
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Table 5-9. Tumor incidences Sprague-Dawley and F344 in rats exposed to 

AN in drinking water for 2 years 

Sex 

AN drinking 

water 

concentration 

(ppm) 

Forestomach 

tumors 

CNS 

tumors

Zymbal gland 

tumors

Tongue 

tumors 

Intestinal 

tumors 

Mammary gland 

tumors

Sprague-Dawley rats 

(Quast, 2002; Quast et al., 1980a) 

0 0/80 1/80 3/80 1/80

35 2/47 12/47a 4/47 2/47 

100 23/48a 22/48a 3/48 4/48 

Male 

300 39/48a

 30/48a 16/48a 5/48a

Not 

reported Not reported 

0 1/80 1/80 1/80 0/80 0/80 58/80 

35 1/48 20/48a 5/48a 1/48 1/48 42/48a

100 12/48a 25/48a 9/48a 2/48 4/48a 42/48a

Female 

300 30/48a 31/48a 18/48a 12/48a 4/48a 35/48 

F344 rats 

(Johannsen and Levinskas, 2002b; Biodynamics, 1980c)

b

0 0/159 3/160 1/147 3/159 

1 1/80 2/80 1/76 2/80 

3 4/78a 1/78 0/73 2/78 

10 3/80a 2/80 0/67 2/80 

30 4/80a 10/79c 2/71c 0/80 

Male 

100 1/77 25/76c

 14/68c

Not examined 

2/77 

0 1/157 1/157 0/157 14/156 

1 1/80 1/80 0/73 8/80 

3 2/79 2/80 0/73 6/80 

10 2/77 5/75 0/70 9/80 

30 4/80a 6/80c 2/73c 12/80 

Female 

100 2/75 24/76c

 8/62c

Not examined 

14/73a

a

Significantly different from controls (p < 0.05). 

bThe denominators for tumor incidences in F344 rats excluded rats from the 6- and 12-mo sacrifices and 

unscheduled deaths prior to the 12-mo sacrifice. Numerators for the incidences of CNS tumors were derived by 

adding the number of rats with brain or spinal astrocytomas; denominators were taken as the greater of the number 

of rats examined for brain or spinal cord lesions after the 12-mo sacrifice. Numerators for Zymbal gland tumor 

incidences included squamous cell papillomas and carcinomas designated to occur in the ear canal. Mammary 

gland tumor incidences are for fibroadenomas and adenocarcinomas in animals sacrificed or found dead after 

12 mos. Tongues were not routinely histopathologically examined for tumors in this bioassay. 

c

Significantly different from controls (p < 0.01). 
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As previously noted, a second 2-year AN drinking water study employing SpragueDawley rats has been conducted (Johannsen and Levinskas, 2002a; Biodynamics, 1980a). To 

determine whether these data should also be employed in the cancer assessment, an analysis was 

performed to evaluate the statistical validity of pooling tumor incidence data from the two 

Sprague-Dawley rat chronic AN drinking water studies. The first study (Quast, 2002; Quast et 

al., 1980a) exposed animals to AN drinking water concentrations of 0, 35, 100, and 300 ppm, 

while the second study (Johannsen and Levinskas, 2002a) employed AN drinking water 

concentrations of 0, 1, and 100 ppm. The dichotomous multistage model in BMDS was fit to the 

tumor incidence data from three sites (i.e., forestomach, CNS, and Zymbal gland) in each sex 

across both studies, using administered animal dose expressed in mg/kg-day. A statistical test 

described by Stiteler et al. (1993), which employs a maximum likelihood ratio statistic 

distributed as a χ

2

, was then used to test the null hypothesis that the two data sets are compatible 

with a common dose-response model. If the null hypothesis is not rejected, this provides 

evidence that the results from the two studies may be pooled. 

As discussed in more detail in Appendix B-5, the statistical tests indicated that some, but 

not all, of the data sets from the two studies were consistent with a common dose-response 

model. More specifically, the results of this analysis showed that forestomach and Zymbal gland 

tumors in both male and female Sprague-Dawley rats were not compatible with a common doseresponse model, while CNS tumors in male and female Sprague-Dawley rats were compatible 

with a common dose-response model. Because of these conflicting results, it was decided that 

the results from the two Sprague-Dawley rat drinking water studies would not be pooled. 

Therefore, the final dose-response analysis for deriving the oral slope factor for AN focused on 

the two rat drinking water studies containing the most dose groups (i.e., the Sprague-Dawley rat 

bioassay reported by Quast [2002] and the F344 rat bioassay reported by Johannsen and 

Levinskas [2002b]). 

5.4.2.3. Rat Inhalation Data 

Incidence data for intestinal, CNS, Zymbal gland, tongue, and mammary gland tumors in 

Sprague-Dawley rats exposed to AN via inhalation were used for deriving site-specific IURs for 

AN (Table 5-10). With the exception of one male in the 80 ppm exposure group that died with a 

CNS tumor after 7–12 months on study, all of the remaining tumors occurred in rats that died or 

were sacrificed after at least 12 months of AN exposure. Denominators for the incidences in 

Table 5-10 excluded animals that died without a tumor before 12 months on study because these 

animals were not exposed long enough to be at risk for tumor development. Although a 

statistically significantly elevated incidence in tongue tumors was observed in male rats at 80 

ppm, tongues from only 14 of the males in the 20 ppm exposure group were examined. No data 

on the incidence of tongue tumors in female rats were presented in the original study report by 

Quast et al. (1980b). 
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Table 5-10. Incidences of intestinal, CNS, Zymbal gland, tongue, and 

mammary gland tumors in Sprague-Dawley rats exposed to AN via 

inhalation for 2 years

Sex

AN air 

concentration 

(ppm)

Intestinal 

tumorsa

CNS 

tumorsa,b

Zymbal gland 

tumorsa

Tongue 

tumorsa

Mammary gland 

adenocarcinomasa

0 4/96 0/96 2/96 1/95 – 

Male 20 3/93 4/93 4/93 0/14 – 

80 17/82c 22/82c 11/82c 7/82c – 

0 – 0/93 0/93 – 9/93

20 – 8/99c Female 1/98 – 8/98 

80 – 20/89c 11/89c – 20/99c

a

For all incidence data, the denominators excluded rats dying earlier than 12 mos in the study. These data were 

ascertained from Tables 22, 25, 31, 34, and 35 in the original study report by Quast et al. (1980b). 

b

Incidences for CNS tumors (brain and spinal cord) in Sprague-Dawley rats listed in this table, as reported by 

Quast et al. (1980b), include both glial cell proliferation and astrocytomas. 

c

Statistically significantly different from controls (p < 0.05) as calculated by the study authors. 

Sources: Dow Chemical (1992a); Quast et al. (1980b). 

5.4.3. Dose-Response Modeling 

5.4.3.1. Human Occupational Data 

A Cox regression model was developed based on an analysis of the Blair et al. (1998) 

lung cancer mortality data for AN-exposed workers. This model yielded a regression coefficient 

(β) estimate of 1.2 × 10-3 with an associated estimated standard error of 2.47 × 10-3 and a 

corresponding p value of 0.61. The 95% upper confidence limit (UCL) on the parameter 

estimate, β, was 5.3 × 10-3. The parameter estimate, β, in this model was about threefold greater 

than the same parameter estimate in the final model developed by Starr et al. (2004), but the 

UCL was similar. The Cox regression model described above was used to predict an AN 

exposure concentration (EC) and its associated 95% lower confidence limit (LEC), associated 

with a 10-2 (1%) risk of dying from lung cancer at age 80 (EC01 and LEC01, respectively). 

Conversions of occupational exposures to continuous environmental exposures were performed 

to account for differences in the number of days exposed per year (240 vs. 365 days) and in the 

amount of air inhaled during an 8-hour workday versus a 24-hour day (10 and 20 m3

/day, 

respectively). The resulting AN exposure estimates (by age 80) were EC01 = 0.992 ppm (or 2.2 

mg/m3

) and LEC01 = 0.238 ppm (or 0.524 mg/m3). The IUR estimate was then derived by linear 

extrapolation from the LEC01. The corresponding unit risk was calculated to be 4.2 × 10-2

 ppm

-1

or 2 × 10-2 per mg/m3. As previously noted, Appendix B-7 provides more details on this Cox 

regression analysis. 
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5.4.3.2. Rat Oral Data 

Within each rat strain, sex, and tumor site, the multistage model, employing EPA’s 

BMDS (version 1.4.1), was fit to the tumor incidence data from the bioassays in SpragueDawley (Quast, 2002) and F344 (Johannsen and Levinskas, 2002b) rats shown in Table 5-9 

using two internal dose metrics, CEO concentration in blood (AUC/24 hours) and AN 

concentration in blood (AUC/24 hours). As already discussed, CEO is a DNA-reactive epoxide 

metabolite thought to play a key role in the carcinogenic mode of action of AN. The 

EPA-modified PBTK model employed consistently predicted higher CEO concentrations in 

blood and brain than were reported in studies of orally exposed rats (see Figures 3 and 4 in 

Kedderis et al., 1996). In contrast, AN concentrations in blood, brain, and liver predicted by the 

same PBTK model were fairly close to measured AN concentrations in rats following oral 

exposure. Ultimately, CEO levels in blood were chosen as the internal dose metric of choice for 

the oral cancer dose-response assessment because CEO is believed to be the most biologically 

relevant dose metric, and it is also consistent with the dose metric employed in derivation of the 

RfD. As with the RfD, CEO concentration in blood represents a reasonable internal dose metric 

for extrapolating from orally exposed rats to humans. 

The AN concentrations in drinking water (in ppm) employed in the Quast (2002) and 

Johannsen and Levinskas (2002b) rat studies were converted to AN administered doses (in 

mg/kg-day) by the study authors, using water intake data recorded during the study. These 

administered doses of AN were then used as input into the EPA-modified rat PBTK model of 

Kedderis et al. (1996) in order to predict a rat internal dose (either CEO-AUC or AN-AUC 

concentration in blood) resulting from the ingestion of a total daily dose of AN equivalent to the 

administered dose consumed in six bolus episodes per day that reflect the daily drinking water 

consumption pattern of rats. The resulting predicted CEO-AUC or AN-AUC concentrations in 

rat blood were then employed in dose-response modeling. Table 5-11 displays the relationship 

between AN drinking water concentrations (in ppm), administered animal doses (in mg/kg-day), 

and two internal dose metrics (i.e., CEO in blood and AN in blood, both expressed in mg/L) 

predicted from the PBTK model. 
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Table 5-11. Four different dose metrics, two external and two internal, based 

on doses employed in studies of Sprague-Dawley and F344 rats exposed to 

AN in drinking water for 2 years 

External dose Predicted internal doseaSpecies, strain 

(reference)

Sex

Concentration in 

drinking water 

(ppm) 

Administered 

doseb

(mg/kg-d) 

CEO in blood 

(mg/L) 

AN in blood 

(mg/L) 

0 0 0 0 

35 3.4 1.83 × 10-3 2.06 × 10-2

100 8.5 4.36 × 10-3 5.36 × 10

Male -2

300 21.3 9.70 × 10-3 1.46 × 10-1

0 0 0 0 

35 4.4 2.07 × 10-3 2.37 × 10-2

100 10.8 4.87 × 10-3 6.18 × 10-2

Rat, 

Sprague-Dawley 

(Quast, 2002)

Female 

300 25.0 1.01 × 10-2 1.56 × 10-1

0 0 0 0 

1 0.08 4.06 × 10-5 4.33 × 10-4

3 0.25 1.27 × 10-4 1.35 × 10-3

10 0.83 4.19 × 10-4 4.52 × 10-3

30 2.48 1.23 × 10-3 1.37 × 10-2

Male 

100 8.37 3.97 × 10-3 4.85 × 10-2

0 0 0 0 

1 0.12 5.32 × 10-5 5.73 × 10-4

3 0.36 1.59 × 10-4 1.72 × 10-3

10 1.25 5.49 × 10-4 6.02 × 10-3

30 3.65 1.58 × 10-3 1.79 × 10-2

Rat, F344 

(Johannsen and 

Levinskas, 2002b)

Female 

100 10.90 4.46 × 10-3 5.63 × 10-2

aThe EPA-modified rat PBPK model of Keddaris et al. (1996) was employed to predict a rat internal dose (i.e., 

either AN-AUC or CEO-AUC concentration in blood) resulting from the ingestion of an administered dose of AN 

consumed in six bolus episodes/d. 

bAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake.

Employing the internal dose metrics in Table 5-11 (i.e., CEO in blood and AN in blood), 

successive stages of the multistage model, starting with stage 1 and ending with the stage equal 

to the number of dose groups minus one, were fit to the tumor incidence data at a particular site 

for each rat strain and sex. Then, all stages of the multistage model that did not show a 

significant lack of fit (i.e., p > 0.1) were compared using AIC. The stage of the multistage model 

with the lowest AIC was selected as the “best-fit” model. For most tumor sites, the one-stage 

model exhibited the best fit. 

A BMR of 10% extra risk was selected for all tumor sites, consistent with the Guidelines 

for Carcinogen Risk Assessment (U.S. EPA, 2005a), which recommend identifying the POD near 

the lower end of the observed data. Using the best-fit model, the resulting BMD10s and 
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BMDL10s were estimated for each tumor site within each rat strain and sex. A summary of the 

results of this BMD modeling is shown in Table 5-12. Additional details regarding doseresponse modeling used in the derivation of the oral CSFs are provided in Appendix B-3. 

Table 5-12. BMD modeling results using tumor incidence data from male 

and female Sprague-Dawley and F344 rat studies in which animals were 

exposed to AN in drinking water for 2 years 

BMD modeling resultsa

Strain/species Sex Tumor site Dose metric

BMD10

(mg/L) 

BMDL10

(mg/L) 

CEO 1.87 × 10-3 1.44 × 10-3

Forestomach 

AN 2.26 × 10-2 1.70 × 10-2

CEO 8.87 × 10-4 7.16 × 10-4

CNS 

AN 8.82 × 10-3 6.64 × 10-3

CEO 5.46 × 10-3 3.15 × 10-3

Zymbal gland 

AN 8.94 × 10-2 4.26 × 10-2

CEO 8.78 × 10-3 4.90 × 10-3

Male 

Tongue 

AN 1.29 × 10-1 6.97 × 10-2

CEO 3.29 × 10-3 2.38 × 10-3

Forestomach 

AN 4.22 × 10-2 2.49 × 10-2

CEO 5.79 × 10-4 4.51 × 10-4

CNS 

AN 7.12 × 10-3 5.55 × 10-3

CEO 2.40 × 10-3 1.78 × 10-3

Zymbal gland 

AN 3.41 × 10-2 2.52 × 10-2

CEO 6.70 × 10-3 4.74 × 10-3

Tongue 

AN 9.67 × 10-2 6.10 × 10-2

CEO 5.50 × 10-4 2.98 × 10-4

Sprague-Dawley rats 

Female 

Mammary gland 

AN 7.05 × 10-3 3.77 × 10-3
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Table 5-12. BMD modeling results using tumor incidence data from male 

and female Sprague-Dawley and F344 rat studies in which animals were 

exposed to AN in drinking water for 2 years 

BMD modeling resultsa

Strain/species Sex Tumor site Dose metric

BMD10

(mg/L) 

BMDL10

(mg/L) 

CEO 6.03 × 10-4 3.55 × 10-4

Forestomach 

AN 6.48 × 10-3 3.81 × 10-3

CEO 1.16 × 10-3 8.74 × 10-4

CNS 

AN 1.37 × 10-2 1.03 × 10-2

CEO 2.73 × 10-3 2.19 × 10-3

Male 

Zymbal gland 

AN 3.31 × 10-2 2.59× 10-2

CEO 3.65 × 10-3 1.69 × 10-3

Forestomach 

AN 4.13 × 10-2 1.90 × 10-2

CEO 1.39 × 10-3 1.05 × 10-3

CNS 

AN 1.70 × 10-2 1.28 × 10-2

CEO 3.78 × 10-3 2.97 × 10-3

Zymbal gland 

AN 5.41 × 10-2 3.35 × 10-2

CEO 3.58 × 10-3 1.97 × 10-3

F344 rats 

Female 

Mammary gland 

AN 4.51 × 10-2 2.45 × 10-2

aThe multistage model in EPA’s BMDS (version 1.4.1) was fit to each set of tumor incidence data from the 

Sprague-Dawley and F344 rat bioassays, as shown in Table 5-9, using the two internal dose metrics, CEO in blood 

and AN in blood, expressed in mg/L. An adequate fit of the MS model was achieved if the χ

2

 goodness-of-fit 

statistic yielded p > 0.1. In the case of CNS tumors in Sprague-Dawley female rats, an adequate fit of the 

multistage model to the data could not be achieved; therefore, the best fitting of the other models available in 

BMDS (assessed by AIC), the log-logistic model, was used. Numbers in parentheses indicate the number of dose 

groups dropped in order to obtain an adequate fit (starting with the highest dose group). Appendix B-3 provides 

further details on these BMD modeling results. 

Sources: Johannsen and Levinskas (2002b) (F344); Quast (2002) (Sprague-Dawley). 

After completion of the dose-response modeling, the BMDL10s estimated for each tumor 

site within each rat strain and sex for each internal dose metric were input into the EPA-modified 

human PBTK model of Sweeney et al. (2003) in order to predict the human equivalent 

administered dose of AN that corresponds to the estimated BMDL10, assuming six bolus 

ingestion episodes of AN per day. The resulting predicted human equivalent administered dose 

of AN, expressed in mg/kg-day, are shown in the third column of Table 5-13 for the internal 

dose metric CEO in blood and Table 5-14 for the internal dose metric AN in blood. Finally, for 

each rat strain, sex, and tumor site, the site-specific oral CSFs shown in the last column of Table 

5-13 (based on CEO concentration in blood) and Table 5-14 (based on AN concentration in 

blood) were derived by dividing the BMR (i.e., 10% or 0.1) by the human equivalent 

administered dose of AN (in mg/kg-day), displayed in the third column of Tables 5-13 and 5-14. 
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Table 5-13. Site-specific oral CSFs for AN based on BMD modeling of 

tumor incidence data in rats and predicted CEO levels in blood 

(AUC/24 hours) of rats and humans assuming episodic exposure to AN 

Rat strain, gender

Tumor site

Rat BMDL10

a

(mg/L)

BMDL10/HED

b 

(mg/kg-d)

CSFc

(mg/kg-d)-1

Sprague-Dawley males 

Forestomach 1.44 × 10-3 0.142 0.704

CNS 7.16 × 10-4 0.071 1.410

Zymbal gland 3.15 × 10-3 0.312 0.320

Tongue 4.90 × 10-3 0.486 0.206

Sprague-Dawley females 

Forestomach 2.38 × 10-3 0.236 0.424 

CNS 4.51 × 10-4 0.045 2.222

Zymbal gland 1.78 × 10-3 0.176 0.567

Tongue 4.74 × 10-3 0.470 0.213

Mammary gland 2.98 × 10-4 0.029 3.390

F344 males

Forestomach 3.55 × 10-4 0.035 2.850 

CNS 8.74 × 10-4 0.086 1.160 

Zymbal gland 2.19 × 10-3 0.217 0.462 

F344 females

Forestomach 1.69 × 10-3 0.167 0.599 

CNS 1.05 × 10-3 0.104 0.963 

Zymbal gland 2.97 × 10-3 0.294 0.340 

Mammary gland 1.97 × 10-3 0.195 0.514 

aRat BMDL10 refers to the estimated 95% lower confidence limit on the internal dose of CEO in blood in 

the rat associated with a 10% extra risk for the incidence of tumors at the specified site in the associated 

strain and sex. This value is taken from the last column of Table 5-12. 

b

PBTK model-derived HED of AN that would result in a human 24-hr blood CEO-AUC equivalent to the 

rat CEO-AUC presented in the previous column of the table, assuming AN ingestion in six bolus 

episodes/d. 

cCSF = BMR/BMDL10/HED or 0.1/BMDL10/HED. 

Sources: Johannsen and Levinskas (2002b) (F344); Quast (2002) (Sprague-Dawley). 
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Table 5-14. Site-specific oral CSFs for AN based on BMD modeling of 

tumor incidence data in rats and predicted AN levels in blood 

(AUC/24 hours) of rats and humans assuming episodic exposure to AN 

Rat strain, gender

Tumor site 

Rat BMDL10

a

(mg/L) 

BMDL10/HED

b 

(mg/kg-d) 

CSFc

(mg/kg-d)-1

Sprague-Dawley males

Forestomach 1.70 × 10-2 4.30 0.023 

CNS 6.64 × 10-3 1.89 0.053 

Zymbal gland 4.26 × 10-2 8.59 0.012 

Tongue 6.97 × 10-2 11.85 0.008 

Sprague-Dawley Females

Forestomach 2.49 × 10-2 5.82 0.017 

CNS 5.55 × 10-3 1.60 0.062 

Zymbal gland 2.52 × 10-2 5.87 0.017 

Tongue 6.10 × 10-2 10.90 0.009 

Mammary gland 3.77 × 10-3 1.11 0.090 

F344 males

Forestomach 3.81 × 10-3 1.12 0.089 

CNS 1.03 × 10-2 2.82 0.036 

Zymbal gland 2.59 × 10-2 5.99 0.017 

F344 females

Forestomach 1.90 × 10-2 4.71 0.021 

CNS 1.28 × 10-2 3.38 0.030 

Zymbal gland 3.35 × 10-2 7.26 0.014 

Mammary gland 2.45 × 10-2 5.75 0.017 

aRat BMDL10 refers to the estimated 95% lower confidence limit on the internal dose of AN in blood in the 

rat associated with a 10% extra risk for the incidence of tumors at the specified site in the associated strain 

and sex. This value is taken from the last column of Table 5-12. 

b

PBTK model-derived HED of AN that would result in a human 24-hr blood AN-AUC equivalent to the 

rat AN-AUC presented in the previous column of the table, assuming AN ingestion in six bolus 

episodes/d. 

cCSF = BMR/BMDL10/HED or 0.1/BMDL10/HED. 

Sources: Johannsen and Levinskas (2002b) (F344); Quast (2002) (Sprague-Dawley). 

In comparing Tables 5-13 and 5-14, the CEO-based site-specific oral CSF estimates in 

Table 5-13 are higher than those based on AN blood levels in Table 5-14. This occurs because 

the VmaxC/Km for AN oxidation to CEO is estimated to be about 10 times higher in humans than 

in the rat. AN enzymatic GSH conjugation is estimated to be 1.5 times higher in the rat, but the 

2

nd-order removal constant for non-enzymatic reaction of AN and GSH is assumed to be the 

same and the GSH tissue levels are roughly the same (and lower in the larger tissue groups). The 

result, for example, with a steady oral “infusion” of 30 mg/kg-day, is that AN is removed 

somewhat faster overall, leading to physiologically based pharmacokinetic (PBPK) predicted 
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steady-state blood level of 0.114 mg/L AN in humans vs. 0.151 in the rat, but a much higher 

portion of this goes to CEO in the human yielding a CEO blood level of 0.297 vs. 0.013 mg/L in 

the rat. Thus, AN:CEO = 11.4 in the rat and 0.385 in the human, and so the CEO-based risk 

estimates are approximately 50 times higher than the AN-based estimates. 

For comparative purposes, in Table 5-15, the BMDL10 estimates generated from the 

BMD modeling of the incidence of tumors in male and female Sprague-Dawley and F344 rats 

using administered animal dose (modeling results not shown) were converted to human 

equivalent administered doses of AN using BW scaling to the 3⁄4 power. Then, as in Tables 5-13 

and 5-14, oral CSFs were derived by dividing the BMR (i.e., 10% or 0.1) by the human 

equivalent administered dose of AN (in mg/kg-day). 

Table 5-15. Site-specific oral CSFs for AN based on BMD modeling of 

tumor incidence data in rats and BW scaling to the 3⁄4 power to convert from 

rat to human administered doses 

Rat strain, gender

Tumor site 

Rat BMDL10

a

(mg/kg-d) 

BMDL10/HED

b 

(mg/kg-d) 

CSFc

(mg/kg-d)-1

Sprague-Dawley males

Forestomach 2.76 0.812 0.123 

CNS 1.48 0.436 0.229 

Zymbal gland 5.17 1.52 0.066 

Tongue 10.4 3.04 0.033 

Sprague-Dawley females

Forestomach 4.81 1.27 0.079 

CNS 0.99 0.262 0.382 

Zymbal gland 4.19 1.11 0.090 

Tongue 8.30 2.19 0.046 

Mammary gland 0.66 0.174 0.575 

F344 males

Forestomach 0.70 0.193 0.517 

CNS 1.81 0.493 0.203 

Zymbal gland 3.43 0.932 0.107 

F344 females

Forestomach 3.89 0.926 0.108 

CNS 2.52 0.602 0.166 

Zymbal gland 6.64 1.59 0.063 

Mammary gland 4.77 1.14 0.088 

aRat BMDL10 is the estimated 95% lower confidence limit on the administered dose of AN in the rat 

associated with a 10% extra risk for the incidence of tumors at the specified site in the associated strain 

and sex. This value is generated from the “best-fit” dose-response model in BMDS (version 1.4.1). 

bThe HED of AN equal to the rat BMDL10 in the previous column converted through use of BW scaling to 

the 3⁄4 power. 

cCSF = BMR/BMDL10/HED or 0.1/BMDL10/HED. 

Sources: Johannsen and Levinskas (2002b) (F344); Quast (2002) (Sprague-Dawley). 
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5.4.3.3. Rat Inhalation Data 

Within each sex and for each tumor site, the multistage model, employing EPA’s BMDS 

(version 1.4.1), was fit to the tumor incidence data from the AN inhalation bioassay in SpragueDawley rats (Quast et al., 1980b) shown in Table 5-10 using the internal dose metric, CEO 

concentration in blood (AUC/24 hours). In contrast to the approach used for oral exposure, only 

one internal dose metric was selected on which to base site-specific IURs (i.e., CEO in blood), 

because, in contrast to oral exposure, the EPA-modified PBTK model adequately predicted 

measured blood and brain concentrations of CEO in rats exposed to AN via inhalation (Kedderis 

et al., 1996). Furthermore, as mentioned previously, CEO is the DNA-reactive metabolite 

thought to be key in the carcinogenic mode of action of AN. 

Prior to dose-response modeling, the AN concentrations in air (in ppm) administered in 

the Quast et al. (1980b) rat study were input into the EPA-modified rat PBTK model of Kedderis 

et al. (1996) in order to predict a rat internal dose (CEO-AUC concentration in blood) resulting 

from inhalation exposure to the administered air concentration of AN. The resulting predicted 

CEO-AUC concentrations in rat blood were then employed in dose-response modeling. 

Table 5-16 displays the relationship between AN concentrations in air (expressed in ppm) and 

the internal dose metric, CEO in blood (expressed in mg/L), predicted from the PBTK model. 

Table 5-16. Two different dose metrics, one external and one internal, based 

on administered air concentrations of AN employed in a 2-year bioassay in 

Sprague-Dawley rats 

Species, strain Sex 

Exposed AN concentration in air 

(ppm) 

Predicted CEO 

concentration in blooda 

(mg/L) 

0 0 

20 2.17 × 10 Male -3

80 8.20 × 10-3

0 0 

20 2.18 × 10-3

Rat, Sprague-Dawley 

Female 

80 8.24 × 10-3

a

See Table 5-11. 

Source: Quast et al. (1980b). 

After completion of the dose-response modeling, the BMC10s and BMCL10s estimated 

within each sex for each tumor site using CEO in blood as the dose metric from Table 5-17 were 

input into the EPA-modified human PBTK model of Sweeney et al. (2003) in order to predict the 

HEC of AN in air that corresponds to the estimated BMC10 and BMCL10 in animals. The 

resulting predicted 95% lower bounds of the HECs (BMCL10/HEC) of AN in air, expressed in 
343 DRAFT - DO NOT CITE OR QUOTE 

mg/m3, are shown in the third column of Table 5-18 for the internal dose metric CEO in blood. 

Finally, for each sex and tumor site, the site-specific IURs shown in the last column of 

Table 5-19 (based on CEO concentration in blood) were derived by dividing the BMR (i.e., 10% 

or 0.1) by the BMCL10/HEC. 

Table 5-17. BMD modeling results using tumor incidence data from male 

and female Sprague-Dawley rats exposed to AN via inhalation for 2 years 

and CEO concentration in blood predicted from an EPA-modified PBTK 

model 

BMD modeling results 

Strain, species Sex Tumor site Dose metric

BMC10

(mg/L)

BMCL10

(mg/L)

Intestine CEO 6.06 × 10-3 4.47 × 10-3

CNS CEO 3.14 × 10-3 2.31 × 10 Male -3

Zymbal gland CEO 7.26 × 10-3 4.40 × 10-3

Tongue CEO 9.48 × 10-3 6.39 × 10-3

CNS CEO 3.21 × 10-3 2.39 × 10-3

Zymbal gland CEO 7.90 × 10-3 5.09 × 10-3

Rat, SpragueDawley 

Female 

Mammary gland CEO 7.31 × 10-3 4.33 × 10-3

aThe multistage model in EPA’s BMDS (version 1.4.1) was fit to each set of tumor incidence data from the 

Sprague-Dawley rat bioassay, as shown in Table 5-10, using the internal dose metric, CEO in blood, expressed in 

mg/L. An adequate fit of the multistage model was achieved if the χ

2

 goodness-of-fit statistic yielded p > 0.1. 

Appendix B-4 provides further details on these BMD modeling results. 

Source: Quast et al. (1980b).
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Table 5-18. Site-specific IURs for AN based on BMD modeling of tumor 

incidence data in Sprague-Dawley rats and PBTK modeling of CEO levels in 

blood (AUC/24 hours) of rats and humans 

Gender 

Tumor site 

Rat BMCL10

a

(mg/L) 

BMCL10/HEC

b 

(mg/m3)

IURc

(mg/m3)

-1

Males 

Intestine 4.47 × 10-3 6.00 0.017 

CNS 2.31 × 10-3 3.10 0.032 

Zymbal gland 4.40 × 10-3 5.91 0.017 

Tongue 6.39 × 10-3 8.58 0.012 

Females 

CNS 2.39 × 10-3 3.21 0.031 

Zymbal gland 5.09 × 10-3 6.83 0.015 

Mammary gland 4.33 × 10-3 5.81 0.017 

aRat BMCL10 refers to the estimated 95% lower confidence limit on the concentration of CEO in blood of 

the rat associated with a 10% extra risk for the incidence of tumors at the specified site based on BMD 

modeling. This value is taken from the last column of Table 5-17. 

b

PBTK model-derived HEC of AN in air that would result in a human 24-hr blood CEO-AUC 

concentration equivalent to the rat BMCL10 in the previous column of the table assuming continuous 

exposure to AN. The human PBTK model employed did not contain the human in vitro to in vivo 

modifying factor for CEO hydrolysis proposed by Sweeney et al. (2003). 

c

IUR = BMR/BMCL10/HEC or 0.1/BMCL10/HEC. 

Table 5-19. Site-specific IURs for AN based on BMD modeling of tumor 

incidence data in Sprague-Dawley rats exposed to AN via inhalation 

Gender 

Tumor site 

Rat BMCL10

a

(ppm) 

BMCL10/HEC

b 

(mg/m3)

IURc

(mg/m3)

-1

Males 

Intestine 42.68 93.58 1.07 × 10-3

CNS 22.23 48.74 2.05 × 10-3

Zymbal gland 42.53 93.25 1.07 × 10-3

Tongue 59.41 130.26 7.68 × 10-4

Females 

CNS 22.89 50.19 1.99 × 10-3

Zymbal gland 48.74 106.87 9.36 × 10-4

Mammary gland 37.82 82.92 1.21 × 10-3

aRat BMCL10 refers to the estimated 95% lower confidence limit on the concentration of AN in air 

associated with a 10% extra risk for the incidence of tumors at the specified site based on BMD modeling. 

bThe HEC of AN in air equivalent to the rat BMCL10 in the previous column of the table generated through 

use of the following conversion equation: mg/m3

 = [ppm × molecular weight]/24.20, where molecular 

weight = 53.06. 

c

IUR = BMR/BMCL10/HEC or 0.1/BMCL10/HEC. 
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5.4.4. Cancer Risk Values 

5.4.4.1. Oral CSFs 

Because AN has been demonstrated to produce tumors at multiple sites in rats, the 

estimation of risk based on only one tumor site may underestimate the overall carcinogenic 

potential of AN. Under the assumption that AN causes tumors by a mutagenic mode of action, 

estimates of the composite risk of etiologically distinct tumor types in each rat strain/sex 

combination considered in Section 5.4.3.2 were derived employing the Bayesian approach 

described in Appendix B-6. This approach is consistent with the recommendations of the NRC 

(1994) and the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), which 

recommends “adding risk estimates derived from different tumor sites (NRC, 1994) as an option 

for “how best to represent the human cancer risk.” This composite risk is associated with the 

potential for developing tumors, not at all of the sites, but at any combination of the sites 

observed in male or female rats. For this analysis, the etiologically distinct tumor sites 

associated with AN exposure were assumed to be statistically independent. This assumption 

cannot currently be verified, but if not correct could lead to an overestimate of risk. NRC (1994) 

concluded that a general assumption of statistical independence of tumors within animals was 

not likely to introduce substantial error in assessing carcinogenic potency from rodent bioassay 

data. 

Table 5-20 presents the estimated human equivalent oral CSFs for both site-specific risks 

and composite risks from multiple tumor types from each rat strain and sex exposed to AN via 

drinking water based on the internal dose metric, CEO concentration in blood (AUC over 

24 hours). 
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Table 5-20. Estimated human equivalent oral CSFs for composite risk based 

on tumor incidence in AN-exposed rats and predicted CEO-AUC levels in 

blood 

Rat strain and gender

Tumor sites included 

Site-specific oral CSFa 

(mg/kg-d)-1

Oral CSF for composite risk 

across sites 

(mg/kg-d)-1

Sprague-Dawley Male 

Forestomach 0.704 

CNS 1.410 

Zymbal gland 0.320 

Tongue 0.206 

2.8 

Sprague-Dawley Female 

Forestomach 0.424 

CNS 2.222 

Zymbal gland 0.567 

Tongue 0.213 

Mammary gland 3.390 

5.0 

F344 Male 

Forestomach 2.850 

CNS 1.160 

Zymbal gland 0.462 

3.1 

F344 Female 

Forestomach 0.599 

CNS 0.963 

Zymbal gland 0.340 

Mammary gland 0.514 

1.9 

aThese site-specific oral CSFs are taken from the last column of Table 5-13. 

In Sprague-Dawley rats, males showed statistically significantly increased incidences of 

tumors at four sites (i.e., forestomach, CNS, Zymbal gland, and tongue), while females showed 

statistically significantly increased incidences of tumors at five sites (i.e., forestomach, CNS, 

Zymbal gland, tongue, and mammary gland), following chronic oral exposure to AN. The 

composite oral CSF based on tumor incidences in male Sprague-Dawley rats chronically exposed 

to AN (using CEO concentration in blood) is estimated to be 2.8 per mg/kg-day, about twice as 

high as the estimated slope factor resulting from the most sensitive single site in this strain and 

sex. For female Sprague-Dawley rats, the composite oral CSF (based on CEO concentration in 

blood) was 5.0 per mg/kg-day, approximately 50% higher than the estimated slope resulting 

from the most sensitive single site in this strain and sex. 

In F344 rats, males showed statistically significant increased incidences of tumors at 

three sites (i.e., forestomach, CNS, and Zymbal gland), while females showed statistically 

significant increased incidences of tumors at four sites (i.e., forestomach, CNS, Zymbal gland, 

and mammary gland), following oral exposure to AN in drinking water for 2 years. Again, under 
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the assumption that the tumors at these sites are statistically independent, the composite oral CSF 

in F344 males (based on CEO concentration in blood) was 3.1 per mg/kg-day, slightly higher 

than the estimated slope factor of 2.8 per mg/kg-day based on tumors in the forestomach alone, 

the most sensitive single site in this strain and sex. For female F344 rats, the composite oral CSF 

(based on CEO concentration in blood) was 1.9 per mg/kg-day, about twice the estimated slope 

factor of 0.96 per mg/kg-day from tumors of the CNS, the most sensitive single site in this strain 

and sex. 

The slope factors obtained from male and female Sprague-Dawley rats and F344 rats 

ranged from 2 to 5 (mg/kg-day)-1. While female Sprague-Dawley rats had the highest slope 

factor due to increase in mammary gland tumor risk, the increase in mammary gland tumor risk 

in female F344 rats was not as high. There is no information as to which rat strain may be most 

similar to humans. Both strains of rats developed same tumors in response to AN exposure. For 

the purpose of this assessment, the slope factor of 5 per mg/kg-day is recommended for use in 

humans because it is the value obtained from the most sensitive species, strain, and sex (i.e., 

female Sprague-Dawley rats). This slope factor should not be used with exposures greater than 

0.04 mg/kg-day (the lowest POD supporting the composite risk) because above this level the 

slope factor cannot be expected to be an adequate approximation to the dose-response 

relationship. The fitted dose-response relationship and pharmacokinetic models should be used 

to estimate risk above this exposure level. See Section 5.6 regarding the application of agedependent adjustment factors (ADAFs). 

Previous IRIS Assessment

In the previous IRIS assessment completed in 1991, EPA derived an oral CSF of 

5 × 10-1 (mg/kg-day)-1 by application of the linearized multistage model to incidence data from 

rats with astrocytomas, Zymbal gland carcinomas, or forestomach papillomas or carcinomas 

from the three 2-year drinking water studies in rats considered under the current assessment 

(Biodynamics, 1980a,c; Quast et al., 1980a). At that time, no PBTK models were available for 

generating internal dose metrics or informing interspecies extrapolation; therefore, interspecies 

extrapolation was accomplished using BW2/3 scaling. The final slope factor of 5 × 10-1 (mg/kgday)-1 was the geometric mean of the slope factors derived from each of these three studies, i.e., 

4 × 10-1 (mg/kg-day)-1 (Biodynamics, 1980a), 4 × 10-1 (mg/kg-day)-1 (Biodynamics, 1980c), and 

10 × 10-1 (mg/kg-day)-1 (Quast et al., 1980a). 

5.4.4.2. Inhalation Unit Risk 

Employing human data, the EC01 and LEC01, defined as the AN exposure concentration 

and its associated 95% lower confidence limit, respectively, that result in a 1% increase in the 

risk of dying from lung cancer at age 80 were estimated from the Cox regression model derived 

from the Blair et al. (1998) occupational epidemiology study. These EC01 and LEC01 values 
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were 0.992 and 0.238 ppm, respectively (or 2,187 and 524 μg/m3, respectively). From the 

LEC01, an IUR of 4.2 × 10-2 ppm

-1 or 2 × 10-2 (mg/m3

)

-1 was derived. 

For inhalation exposures to AN in animals, as with oral exposures, estimates of composite 

risk addressing multiple tumor sites (within strain and sex) based on BMD modeling results from 

a chronic inhalation rodent bioassay in Sprague-Dawley rats (Dow Chemical 1992a; Quast et al., 

1980b) were generated. These estimates were derived employing the same Bayesian approach 

described in Appendix B-6 for oral exposures. 

Table 5-21 presents the human equivalent IURs for both site-specific risks and composite 

risks from multiple tumor types observed in each sex of Sprague-Dawley rat exposed to AN 

using the internal dose metric, CEO concentration in blood (AUC for 24 hours). 

Table 5-21. Estimated human equivalent composite IURs based on tumor 

incidence in AN-exposed rats and predicted CEO-AUC levels in blood 

Rat strain and gender

Tumor sites included

Site-specific IUR a 

(mg/m3)

-1

Composite IUR 

(mg/m3)

-1

Sprague-Dawley male 

Intestine 0.017 

CNS 0.032 

Zymbal gland 0.017 

Tongue 0.012 

6.8 × 10-2

Sprague-Dawley female 

CNS 0.031 

Zymbal gland 0.015 

Mammary gland 0.017 

5.7 × 10-2

aThese site-specific IURs are taken from the last column of Table 5-18. 

 From the inhalation bioassay, male rats showed statistically significant elevated tumor 

incidences at four sites (i.e., intestine, CNS, Zymbal gland, and tongue), while female rats 

showed statistically significant elevations at three tumor sites (i.e., CNS, Zymbal gland, and 

mammary gland), when exposed to AN via inhalation for 2 years. Under the assumption that 

tumors at these sites are statistically independent, the estimated composite IUR in male rats was 

6.8 × 10-2 per mg/m3

, approximately 2 times higher than the site-specific IUR estimate of 3.2 ×

10-2 per mg/m3 based on the most sensitive single site in males (i.e., CNS). For female rats, the 

composite IUR was 5.7 × 10-2 per mg/m3

, about 2 times higher than the site-specific estimate of 

3.1 × 10-2 per mg/m3 from the most sensitive single site in females (i.e., CNS). These unit risks 

should not be used with exposures greater than 3 mg/m3

 (the lowest POD supporting the 

composite risk), because above this level the unit risk cannot be expected to be an adequate 

approximation of the dose-response relationship. The fitted dose-response relationship and 

pharmacokinetic models should be used to estimate risk above this exposure level. 
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The IUR recommended for use in estimating cancer risks associated with chronic 

inhalation exposures to AN during adult stages of development is 2 × 10-2 per mg/m3 (or 

2 × 10-5 per μg/m3)—the value based on human data (i.e., the occupational epidemiology study 

by Blair et al., 1998). See Section 5.4.4.3 regarding the application of ADAFs. 

Previous IRIS assessment 

In the previous IRIS assessment, an IUR was also derived based on human data. This 

IUR was based on an increase in lung cancer incidence in humans occupationally exposed to 

AN, as described by O’Berg (1980). A value of 6.8 × 10-5 per μg/m3

 was derived by the 

application of an RR model, which was adjusted for smoking and was based on a continuous 

lifetime equivalent of occupational exposure to AN.

5.4.4.3. Quantitative Analysis of Early Life Exposure Scenarios

The mode of action for carcinogenicity of AN is determined to be mutagenic 

(Section 4.7.3.1), which raises concern for increased early life cancer susceptibility. Consistent 

with this possibility, two studies in Sprague-Dawley rats provide evidence of increased cancer 

susceptibility associated with chronic AN exposure that begins in early periods of 

development—a chronic-duration inhalation cancer bioassay (Maltoni et al., 1988) and a threegeneration drinking water reproductive toxicity study (Friedman and Beliles, 2002). This 

evidence was summarized in Section 4.8.1. According to the Supplemental Guidance for 

Assessing Susceptibility from Early-Life Exposure to Carcinogens (U.S. EPA, 2005b), “when 

developing quantitative estimates of cancer risk, the Agency recommends integration of agespecific values for both exposure and toxicity/potency where such data are available and 

appropriate” (also see Box 5 in Figure 3 in U.S. EPA [2005b]). The available evidence is 

considered below. 

5.4.4.3.1. Summary of Maltoni et al. (1988). Maltoni et al. (1988) exposed pregnant SpragueDawley rats to 60 ppm AN by inhalation for 104 weeks (see Section 4.2.2.2.2 for a complete 

description). In addition, the offspring of these dams were exposed to AN starting at GD 12 for a 

total of either 15 or 104 weeks. All animals were observed until natural death. 

 As noted in Section 4.2.2.2.2, Maltoni et al. (1988) reported statistically significant 

increases in tumor incidences for both male and female offspring exposed for 104 weeks 

compared with their controls. Female offspring showed statistically significant increases in 

malignant mammary tumors, encephalic gliomas, and extra-hepatic angiosarcomas, while male 

offspring showed statistically significant increases in encephalic gliomas, Zymbal gland 

carcinomas, and hepatomas. While there were no statistically significant increases for the 

exposed dams, their responses were slightly increased over background for most of these sites—

mammary tumors at 2.3% extra risk, encephalic gliomas at 5.6%, extra-hepatic angiosarcomas at 
350 DRAFT - DO NOT CITE OR QUOTE 

1.9%, and Zymbal gland tumors at 3.8%. No hepatomas were observed in the dams. These 

results are summarized in Table 5-22. Note that there were no concurrently exposed or control 

adult male rats with which to compare the male offspring incidences; comparisons with the 

female adult data involve assuming that adult male responses would have been concordant. 

Although this profile of responses is similar to that seen for the female rats in Quast et al. 

(1980b),2 the Quast study was not considered to be a suitable baseline for analyzing the male 

offspring responses. 

For offspring exposed for a total of 15 weeks, although there were no statistically 

significantly elevated tumor incidences at any of the evaluated sites, the responses at these sites 

were elevated over respective controls and were consistent with a linear or even supralinear 

increase in response with increasing length of exposure to 60 ppm. Figure 5-3 shows the 

responses for both sets of offspring and the dams for the sites with statistically significant 

responses after chronic exposure. Note that while the extra-hepatic angiosarcoma response in the 

male offspring was not statistically significant for either exposure group, the responses were of a 

similar magnitude to the response of the female offspring exposed for 104 weeks. Although the 

study did not have sufficient power to find individual group responses of about 5% and below 

statistically significant, the mostly statistically significant trends and their consistency across 

sites, as well as across sexes for the angiosarcomas, add weight to the overall conclusion of 

increased early-life susceptibility to the carcinogenicity of AN. 

 

2Assuming a continuous equivalent lifetime exposure concentration of 12.1 ppm for the administered concentration 

in the Maltoni et al. (1988) study, dose-response relationships developed from the Quast et al. (1980b) inhalation 

study (without considering pharmacokinetics) predict a similar incidence profile for the adult female rats, at about 

2% extra risk predicted vs. 2.3% observed for mammary tumors, 10 vs. 5.6% observed for gliomas, and 0% 

predicted vs. 1.9% observed for extra-hepatic angiosarcomas. The differences between the female adult rats in the 

two studies are not large and can be explained by differences between animal colonies and husbandry practices, 

including diet. This analysis provides some assurance that any early-life susceptibility estimates derived from 

Maltoni et al. (1988) are compatible with the unit risks derived from the Quast et al. (1980b) bioassay. 
351 DRAFT - DO NO

Table 5-22. Tumor incidences in Sprague-Dawley rats following inhalation exposure to 60 ppm AN fostarting either in utero (GD 12) or as adults at 13 wks of age 

Length of exposure to 60 ppm 

0 weeks (control) 15 weeks 104 weeks 

Tumor site 

Age at start of 

exposure x/n

a % x/n

a % Extra risk x/na % Extra risk

Trend 

p-valu

Female rats Malignant mammary GD 12 8/149 5.4 4/60 6.7 1.4 9/54 16.7 11.9 0.008 tumors 13 wks 2/60 3.3 – – – 3/54 5.6 2.3 >0.0

GD 12 2/149 1.3 2/60 3.3 2.0 10/54 18.5 17.4 <0.00

Encephalic gliomas 13 wks 0/60 0.0 – – – 3/54 5.6 5.6 >0.0Extrahepatic GD 12 0/149 0.0 1/60 1.7 1.7 3/54 5.6 5.6 0.005 angiosarcomas 13 wks 0/60 0.0 – – – 1/54 1.9 1.9 >0.0Male rats 

GD 12 2/158 1.3 3/60 5.0 3.8 11/67 16.4 15.3 <0.00

Encephalic gliomas 13 wksc 0/60 0.0 – – – 3/54 5.6 5.6 >0.0Zymbal gland GD 12 2/158 1.3 4/60 6.7 5.5 10/67 14.9 13.8 <0.00carcinomas 13 wks 1/60 1.7 – – – 3/54 5.6 3.8 >0.0

GD 12 1/158 0.6 1/60 1.7 1.0 5/67 7.5 6.9 0.002 Hepatomas 13 wks 0/60 0.0 – – – 0/54 0.0 0.0 >0.0

Extrahepatic GD 12 1/158 0.6 3/60 5.0 4.4 3/67 4.5 3.9 >0.0angiosarcomas 13 wks 0/60 0.0 – – – 1/54 1.9 1.9 >0.0ax = number of animals with specified tumor, n = number of animals at start of exposure. bCochran-Armitage trend test for datasets with 3 or more groups (early-life exposures); Fisher’s exact test otherwise (adult exposures). cValues in italics rely on adult female rat data; no male rats were exposed starting at age 13 wks in this study. 

Source: Maltoni et al. (1988). 
352 DRAFT- DO NOT CITE OR QUOTE 

Error bars denote 95% CIs for each response.

Figure 5-3. Comparison of tumor responses to inhalation exposure of 

acrylonitrile, by age at start of exposure (offspring at GD 12, adults at 

13 weeks), sex, and length of exposure, for Sprague-Dawley rats (Maltoni et 

al., 1988). 

Gliomas

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-10 0 10 20 30 40 50 60 70 80 90 100 110

Weeks of exposure

Proportion responding

female offspring

female adults

male offspring

Malignant mammary tumors

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-10 0 10 20 30 40 50 60 70 80 90 100 110

Weeks of exposure

Proportion responding

female offspring

female adults

Extra-hepatic angiosarcomas

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-10 0 10 20 30 40 50 60 70 80 90 100 110

Weeks of exposure

Proportion responding

female offspring

female adults

male offspring

Hepatomas

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-10 0 10 20 30 40 50 60 70 80 90 100 110

Weeks of exposure

Proportion responding

male offspring

female adults

Zymbal's gland tumors

0.00

0.05

0.10

0.15

0.20

0.25

0.30

-10 10 30 50 70 90 110

Weeks of exposure

Proportion responding

male offspring

female adults
353 DRAFT- DO NOT CITE OR QUOTE 

Figure 5-3 shows linear trends with increasing length of exposure among the offspring 

for malignant mammary tumors (females), gliomas (males and females), extrahepatic 

angiosarcomas (females) and hepatomas (males), while supralinear trends are suggested for 

extrahepatic angiosarcomas and Zymbal gland tumors in males. Linear trends suggest that 

offspring responses to the 15-week exposure are proportional to offspring responses resulting 

from the chronic exposure; that is, that the expected response is about 1/7 (15 weeks/104 weeks) 

of the response to chronic exposure starting in utero. The overall response after 104 weeks of 

exposure is markedly higher than that of the chronically exposed adult rats, suggesting that once 

the susceptible process (or processes) has started it continues well into adulthood. For each site, 

the ratios of the extra risk associated with chronic exposure starting at GD 12 relative to starting 

at age week 13 ranged from about 3 to 5 for individual sites in female rats, supported by a factor 

of 3 for gliomas in male rats (see Table 5-22). 

In contrast, the supralinear trends suggest greater than proportional susceptibility in the 

early-life period which decreases over time, or which does not occur after the early-life period, 

as possibly illustrated by the male offspring angiosarcomas. On the other hand, the 15-week 

period used in this study includes a nontrivial period that cannot be considered early-life, given 

that rats are generally considered sexually mature by about 8 weeks of age. Consequently the 

magnitude of the early-life sensitivity, at least for two tumor sites, may be underestimated by 

these data without further characterization of the most sensitive timeframe. The low numbers of 

responses from the 15-week exposures (1–4 offspring and 0–3 adults responding per site) likely 

impact the resolution of early-life susceptibility estimates for these sites. From an overall point 

of view, however, note that the 15-week responses considered collectively are generally similar 

to the female adult responses following 104 weeks of exposure. Because these early-life 

responses result from sevenfold less exposure, they demonstrate approximately 7 times (or 

approximately one order of magnitude) more sensitivity than the adult responses. 

5.4.4.3.2. Summary of Friedman and Beliles (2002). Supporting evidence of increased earlylife susceptibility was also seen in the three-generation reproduction study reported by Friedman 

and Beliles (2002). There were statistically significant increases in Zymbal gland carcinomas 

and astrocytomas after approximately 51 weeks of exposure to 500 ppm AN in drinking water 

for F1 Sprague-Dawley female rats relative to F1 controls, while the incidences for F0 female 

rats were not significantly elevated at 500 ppm. The incidences for F2 female rats, exposed in 

utero like the F1 females, were not considered to be significantly elevated. Section 4.2.1.2.8 

provides details of the study design, and Table 5-23 summarizes the results. 
354 DRAFT- DO NOT CITE OR QUOTE 

Table 5-23. Tumor incidences in female Sprague-Dawley rats exposed to 

AN in drinking water for approximately 46 weeks, starting either in utero 

or at 5 weeks of age 

Tumor incidence, and percent, at AN in 

drinking water, ppm 

Tumor site Generation 0 100 500 

Trend 

test 

p-valuea

Ratio of 

early life + 

adult to adult 

extra risks at 

500 ppm 

F0 (adult exposure) 0/19 (0%) 1/20 (5%) 2/24 (8%) 0.247 – 

F1b 0/20 (0%) 1/19 (5%) 4/17 (24%) 0.005 2.8 

F2b 0/20 (0%) 1/20 (5%) 1/20 (5%) 0.506 – 

Brain 

astrocytomas 

F1b + F2b 0/40 (0%) 2/39 (5%) 5/37 (14%) 0.007 1.8 

F0 (adult exposure) 0/19 (0%) 0/20 (0%) 2/24 (8%) 0.036 – 

F1b 0/20 (0%) 2/19 (11%) 3/17 (18%) 0.088 2.1 

F2b 0/20 (0%) 0/20 (0%) 3/20 (15%) 0.007 1.9 

Zymbal gland 

F1b + F2b 0/40 (0%) 2/39 (5%) 6/37 (16%) 0.005 2.0 

aCochran-Armitage test for linear trend. 

Sources: Friedman and Beliles (2002); Litton Bionetics (1992). 

Ratios of extra risks of astrocytomas and Zymbal gland tumors were estimated for the 

500 ppm F1b and F2b groups if there was a statistically significant linear trend. These results 

suggest an increased early-life cancer susceptibility of about two- to threefold at the high dose. 

However, these results do not support a quantitative estimate of relative susceptibility because 

several factors contribute to underestimating any susceptibility. First, with only 20 animals per 

treatment group, this study had limited power to detect tumor increases, relative to the Maltoni et 

al. (1988) study and most other carcinogencity studies, with the consequence that any increased 

susceptibility at the low dose (100 ppm) may be less readily apparent. For example, an apparent 

effect of 0/20 is consistent with a tumor response as high as 17%, the 95% UCL on a response of 

0/20. 

Second, while it is notable that tumors were observed as early as they were, after no more 

than 51 weeks without another year of follow-up, these data do not inform lifetime risk estimates 

adequately. Although cancer incidence is expected to increase with increasing age (Doll, 1971), 

dose-response relationships starting at different ages may not be parallel. Given the short 

exposure and follow-up in this study, the data from this group are better considered as supporting 

early-life susceptibility qualitatively. 

5.4.4.3.3 Analysis to support estimation of early-life susceptibility adjustment factors. In 

summary, two data sets support the conclusion of increased susceptibility to carcinogenicity with 

AN exposure in early life. One data set conducted by Maltoni et al. (1988), in female rats with 
355 DRAFT- DO NOT CITE OR QUOTE 

chronic exposure starting in early life or starting as adults, provides a sufficient basis for 

developing quantitative estimates of susceptibility. Due to the lack of adult male referent groups 

(control or exposed), the male offspring data provide support for early-life susceptibility. The 

female data supported point estimates for susceptibility adjustment factors of 5, based on 

malignant mammary tumors, and 3, based on gliomas or extra-hepatic angiosarcomas. In other 

words, cancer potency for specific tumor sites following chronic exposure to 60 ppm AN appears 

to be three- to fivefold higher if exposure starts in early-life rather than during adulthood. 

 Before recommending ADAFs based on these data, important considerations include the 

impact of experimental variability and overall risk encompassing multiple tumors. Given the 

incomplete understanding of the operant modes of action, it is unknown whether the tumor types 

observed in the Maltoni et al. (1988) study are independent of each other. They were not 

reported as metastases, which would clearly not be independent. Under the assumption that 

these tumor sites are independent, an analysis was undertaken focusing on overall risk as well as 

characterizing the impact of experimental variability. 

A Monte Carlo analysis was conducted to obtain the distribution of the ratio of combined 

extra risk from the three tumor sites for the chronically exposed female offspring to the 

analogous combined extra risk from adult-only exposure. For each simulation, the outcome in 

each control and dose group was simulated by drawing a binomial B(n,p) random variable with 

n equal to the number of animals in the group and p obtained by dividing number of animals with 

tumor in the original dataset by the total number of animals. Since data for only one dose group 

was available for each tumor site, the individual binomial probabilities for this simulation run 

were estimated by dividing the number of animals with tumors by the total number of animals, 

rather than by fitting a dose-response model to the responses for each pair of control and exposed 

group. Then the risks from the three individual tumor sites were combined assuming 

independence of different tumor outcomes, as noted above. The standard formula for the 

probability of the union of multiple sets was used to compute the combined probability of tumor 

(dose d = 60 ppm was the same for all three tumor types): 

 PAorBorC(d) = PA

(d) + PB(d) + PC(d) – PA(d) * PB(d) – PA(d) * PC(d) – (1) 

PB(d) * PC(d) + PA(d) * PB(d) * PC(d). 

Then the combined extra risk was computed as: 

 ERAorBorC(d) = [PAorBorC(d) – PAorBorC(0)]/ [1 - PAorBorC(0)]. (2) 

Only the individual extra risks where probabilities in the control group did not exceed the 

probability in dose group were retained, in order not to create negative estimates of extra risk. If 
356 DRAFT- DO NOT CITE OR QUOTE 

only two tumor results were combined in a particular realization, the combined probability in 

equation (1) was adapted for two tumors 

 PAorB(d) = PA(d) + PB(d) – PA(d) * PB(d). 

 Finally, the ratio of the extra risks is given by:

 

 ERAorBorC(d | adult & early-life)/ ERAorBorC(d | adult only) (3) 

was calculated and retained for each simulation. The simulation was repeated 10,000 times and 

results are summarized in the first row of 5-24. Simulations were done in R language 

(www.r-project.org). 

 Because some of the control groups did not have any observed tumors, the approach 

above assigns no variability to such groups. As historic background rates are not available, a 

sensitivity analysis was conducted to evaluate if assigning a small probability of tumor (1/2n) to 

these control groups and the resulting variability influences the distribution of the ratio (eq 3). 

The simulations were performed as described above. Results are summarized in the second row 

of Table 5-24. 

 

Table 5-24. Overall extra risks of multiple tumor incidence, for chronic 

exposure beginning either in early-life or in adulthood; based on SpragueDawley rats exposed to AN 

Number of simulations 

with k tumors retained 

Percentiles of the distribution of the ratio of 

extra risks 

Treatment of 0% 

tumors in 

referent groups 

Start of 

exposure period k = 3 k = 2 k = 1 5th Median Meana 95th

Adult 7,578 2,422 0 0.037 0.095 0.100 0.178 

Zero background Early-life 9,903 97 0 0.204 0.314 0.314 0.423 

as observed 

Ratio 1.543 3.232 4.219 

(9,957) 9.628 

Adult 5,483 3,923 574 0.021 0.085 0.089 0.166 

Zero background Early-life 9,685 314 1 0.199 0.311 0.311 0.421 

replaced by 1/2nb 

Ratio 1.610 3.594 6.373 

(9,929) 15.627 

a

For calculation of means, the figure in parentheses indicates the number of finite ratios; the other percentiles were 

based on 10,000 simulations. 

b

For n = 60, 1/2n = 1/120 = 0.0083. 

Source: Maltoni et al. (1988). 

Extra risks for chronic exposure starting in early-life are not sensitive to the assumption 

regarding background probabilities, as shown by the similar percentiles for both cases. But the 
357 DRAFT- DO NOT CITE OR QUOTE 

extra risks for adult-only exposure decrease slightly when some variability at 0% response is 

assumed, resulting in slightly higher ratios. Because the second analysis is more realistic, 

allowing a background response in two of the sites and addressing plausible variability, it is used 

to derive the data-specific adjustment factors. Ninety-five percent of the values fell between 

1.6 and 15.6. 

Note that the analogous composite adjustment factor resulting from the default factors in 

the SG for chronic exposure beginning in early life is 1.7; the analysis provides a distribution of 

adjustment factors with about 95% of the possible values being larger than the default adjustment 

factors. The median and mean ratios, at 3.6 and 6.4, respectively, are far enough apart to 

indicate a nonsymmetrical distribution. The median of 3.6 is a better estimate of central 

tendency in this case. 

Recommended early life susceptibility factors. The derived early-life susceptibility factor 

of 3.6 is to be used in assessing oral or inhalation exposures to AN that begin at birth (or earlier) 

and extend to or beyond 70 years of age. When exposures involving shorter periods of early-life 

exposure to AN are assessed, a modification consistent with the SG framework is recommended, 

as outlined in this section. 

The available information for identifying appropriate ADAF(s) to apply to specific earlylife periods is limited. While U.S. EPA’s SG (U.S. EPA, 2005b) separates the pre-adult period 

into two age ranges, 0−<2 and 2−<16 years, the Maltoni et al. (1988) study design did not 

address age periods corresponding to these windows of human susceptibility. The offspring 

exposed for 15 weeks were about 14 weeks old at the time their exposure stopped (estimated by 

subtracting 9 days (GDs 21−12) from 15 weeks); female rats reach sexual maturity at about 8 

weeks (35 days), so 14 weeks in rats would correspond to a higher age in humans than 16 years. 

Therefore, the Maltoni et al. (1988) data can support only one ADAF for the entire pre-adult 

window. 

 An ADAF for the pre-adult window can be derived from the derived lifetime estimate by 

treating it as a weighted sum of ADAFs for separate windows of susceptibility, consistent with 

the general framework in the SG for applying the default ADAFs, using a simplification of the 

SG framework for estimating human risk from exposure including early-life periods: 

ADAF for lifetime exposure starting at birth = 3.6 

 = [ADAFP × tP + ADAFA × (70 yr – tP)]/70, (4) 

where the subscripts P and A denote pre-adult and adult, respectively, and tP = duration (in years) 

of exposure during the pre-adult period. By convention, ADAFA must be 1. With two 

unknowns, ADAFP and tP, one value must be inferred so that the other can be estimated. 

Because the Maltoni et al. (1988) data from offspring exposed for 15 weeks are consistent with a 

10-fold increased sensitivity relative to rats exposed only as adults (see Figure 5-3 and 

accompanying text), and the default ADAF of 10 in the SG for the most sensitive period (0–
358 DRAFT- DO NOT CITE OR QUOTE 

<2 years of age) is also 10, an ADAFP of 10 seems a reasonable starting point. Substituting these 

two ADAFs in (eq 4) and solving for tP leads to an empirical age cutpoint of 20 years. 

 This cutpoint is necessarily somewhat arbitrary—it is not an assertion that 14 weeks of 

age in a rat is equivalent to 20 years in a human—but appears to be a straightforward 

interpretation of the available data. Other interpretations are possible, such as that sensitivity at

the earliest ages (i.e., before 2 years of age) could be relatively higher than later pre-adult ages, 

but further manipulation of the AN-specific data to align more closely with the SG early-life 

periods and relative sensitivities (i.e., that the earlier period might be about 3 times more 

sensitive that the second pre-adult period) is judged to be too speculative. 

 Illustrations of applying the derived ADAFs for estimating human cancer risk from 

lifetime exposures starting at birth are provided in Table 5-25. 

Table 5-25. Application of ADAFs for estimating human cancer risk from 

70-year oral or inhalation exposures to AN from ages 0 to 70 

Age Group 

(yrs) Duration adjustment ADAF Age group risk 

For oral exposure to 0.01 mg/kg-d, with oral slope factor of 5 (mg/kg-day)-1 for adult lifetime exposure: 

0–<20 20 yrs/70 yrs = 0.29 10 0.14a

20–70 50 yrs/70 yrs = 0.71 1 0.04 

Total: 0–70 70 yrs/70 yrs = 1 3.6 0.18 

For inhalation exposure to 1 mg/m3, with IUR of 2 × 10-2 (mg/m3)

-1 [or 2 × 10-5 (μg/m3

)

-1] for adult lifetime 

exposure:

0–<20 0.29 10 0.057 

20–70 0.71 1 0.014 

Total: 0–70 1 3.6 0.072 

aAge group risk = duration adjustment × ADAF × exposure × CSF or unit risk. 

Equation (4) provides the framework for estimating risks from exposures involving shorter earlylife periods. Two examples are provided: 

• If calculating the cancer risk for a 30-year exposure to a constant oral exposure level of 

0.01 mg/kg-day from ages 0 to 30, the duration adjustments would be 20/70 and 10/70, 

and the age group risks would be 0.14 and 0.01, resulting in a total risk estimate of 0.15. 

• If calculating the cancer risk for a 30-year exposure to a constant oral exposure level of 

0.01 mg/kg-day from ages 20–50, the duration adjustments would be 0/70 and 30/70, and 

the age group risks would be 0 and 0.02, resulting in a total risk estimate of 0.02. 
359 DRAFT- DO NOT CITE OR QUOTE 

5.4.4.3.4. Uncertainties in early-life susceptibility estimates. Unlike many of the studies 

supporting the default adjustment factors recommended in the SG, the available early-life studies 

for AN include gestational exposure. The pharmacodynamics and pharmacokinetics of AN 

during the perinatal period are not well understood, nor are the time frame and nature of the 

response leading to the apparent susceptibility; it is possible that gestational exposure is a 

necessary component of the increased susceptibility. 

Regarding the level of exposure, it is not known whether perinatal exposure was 

comparable to adult exposure. If perinatal exposure was greater than adult exposure, the 

apparent susceptibility would be at least partly attributable to higher exposure; if lower, the 

apparent susceptibility would be underestimated. 

Other uncertainties associated with the recommended data-derived early-life 

susceptibility adjustment factor include: (1) whether the relative susceptibility is dosedependent, leading to different values for other parts of the dose-response range; (2) whether the 

relative susceptibility estimated from female data characterizes the relative susceptibility for 

males; note particularly the observation of hepatomas in male offspring exposed chronically 

beginning in early life; (3) the relevance of extrapolating these results to humans; and 

(4) possible underestimation of risk associated with the lack of knowledge of individual times of 

death if tumors in the exposed animals tended to occur earlier than in control animals or if 

tumors in the animals exposed perinatally tended to occur earlier than in those exposed starting 

at age 13 weeks. 

 Some uncertainty in cancer risk estimates can generally be characterized by fitting a 

dose-response model to the incidence data in order to provide a CI on the risk estimate. In this 

case, however, there was only one exposed group for each exposure pattern. Other methods for 

characterizing the statistical uncertainty in these data are currently being investigated. 

5.4.5. Uncertainties in Cancer Risk ValuesRisk estimates have inherent uncertainties. This 

subsection discusses the uncertainties that may be associated with cancer risk values for oral and 

inhalation cancer assessments. 

5.4.5.1. Oral Cancer Assessment 

Uncertainties related to the oral cancer assessment are discussed below and summarized 

in Table 5-26 and Figure 5-4. 
360 DRAFT- DO NOT CITE OR QUOTE 

Table 5-26. Summary of uncertainty in the AN oral cancer risk assessment

Consideration/ 

approach

Impact on cancer risk 

estimate Decision Justification 

Low-dose 

extrapolation 

procedure 

The selected model does not 

represent all possible models 

one might fit, and other 

models could conceivably be 

selected to yield more 

extreme results consistent 

with the observed data, both 

higher and lower than those 

included in this assessment. 

Multistage model to 

determine POD, linear 

low-dose extrapolation 

from POD. 

Available mode of action data support 

direct mutagenicity as the key mode of 

action and low-dose linear extrapolation 

approach. EPA’s Guidelines for 

Carcinogen Risk Assessment (U.S. EPA, 

2005a): mutagens “are assessed with a 

linear approach.” Mutagenic mode of 

action functions systemically at multiple 

tumor sites. 

PBTK model Oral slope factor based on 

PBTK modeling and internal 

CEO levels is about sixfold 

higher than slope factor 

based on the default 

approach. 

EPA-revised model was 

used. 

The revised PBTK model includes EH 

activity in rats and provides better 

estimates of internal dose. 

Dose metric Alternatives could decrease 

oral slope factor (e.g., use of 

AN-AUC instead of CEOAUC could lower slope 

factor by 30-fold). 

CEO-AUC was used. CEO is the reactive metabolite that binds 

to DNA and initiates tumor formation. 

AN is not the causal agent for cancer. 

Statistical 

uncertainty at 

POD 

Oral slope factor will be 

reduced 1.3-fold if BMD 

used as POD instead of 

BMDL. 

BMDL (approach for 

calculating reasonable 

upper bound). 

Limited size of bioassay results in 

sampling variability; BMDL is lower 

95% confidence limit of BMD. 

Bioassay Oral slope factor would be 

the same if study on F344 

rats were used (Johannsen 

and Levinskas, 2002b). 

Quast (2002) study on 

Sprague-Dawley rats 

was used. 

Quast (2002) has separate interim 

sacrifice groups and examined more 

endpoints than the Biodynamics (1980c) 

data sets. 

Species/gender 

combination 

Human risk could decrease 

or increase, depending on 

relative sensitivity. 

Oral slope factor 

derived from study on 

female SpragueDawley rats. 

It was assumed that humans are as 

sensitive as the most sensitive rodent 

gender/species tested; true 

correspondence is unknown. The 

carcinogenic response occurs across 

species. Generally, direct site 

concordance is not assumed; consistent 

with this view, some rodent tumors are 

not found in humans (e.g., Zymbal’s 

gland tumors, Harderian gland tumors) 

and rat and mouse tumor types also 

differ. 

Human population 

variability in 

metabolism and 

response/sensitive 

subpopulations 

Low-dose risk increase to an 

unknown extent. 

Considered 

qualitatively. 

Increased early life susceptibility 

demonstrated in rat studies. Variability 

in human susceptibility likely exists due 

to differences in microsomal CYP2E1 

activities and possibly GST activity. 
361 DRAFT- DO NOT CITE OR QUOTE 

2.8

5.0

3.1

1.9

0.40

1.03

0.68

0.36

0

1

2

3

4

5

6

Male Sprague-Dawley

Rats

Female SpragueDawley RatsMale F344 Rats Female F344 Rats

Sex/Strain/Species

Oral Cancer Slope Factor

(mg/kg-day)-1

CSF - CEO in Blood

CSF - Administered Dose

Figure 5-4. Comparison of composite oral CSFs derived from tumor 

incidence data in four different sex/strain/species of rats exposed chronically 

to AN. For each sex/strain/species combination, two different dose metrics 

were employed: (1) CEO concentration in blood, and (2) human equivalent 

administered dose. 

Choice of study 

Several bioassays by the oral route are available. The 2-year drinking water studies of 

Sprague-Dawley rats (Quast, 2002; Quast et al., 1980a) and F344 rats (Johannsen and Levinskas, 

2002a; Biodynamics, 1980a) were selected as principal studies. These two studies have 

sufficient numbers of animals, investigate a thorough set of endpoints, and are considered well 

conducted. The tumor types observed and incidence of treatment-related tumors were similar in 

these two studies. Moreover, cancer risk estimates from these two studies differed only by a 

factor of 1.5. Similarities in these results increase the level of confidence of estimated cancer 

risk. The Quast (2002) study of Sprague-Dawley rats investigated more endpoints and is 

therefore a slightly stronger study. 
362 DRAFT- DO NOT CITE OR QUOTE 

PBTK model 

 Use of the PBTK model to extrapolate from rodents to humans also introduces some 

uncertainty. An extensive quantitative analysis of the PBPK model uncertainty is presented in 

Appendix D. Briefly, PBPK models are computational tools used to predict chemical/drug 

disposition and are comprised of three distinct types of information: physiological, 

physicochemical, and biochemical. The physiological data are independent of chemical-specific 

data, and describe such parameters as organ volumes and blood flows. Physicochemical 

parameters are chemical-specific and specify parameters, such as PCs or permeability. 

Biochemical parameters define the rates of chemical transformation or binding. Because the 

physiological data are considered to be well-characterized, analysis focused on uncertainties in 

the chemical-specific parameters employed in the PBPK model used to predict AN dosimetry in 

humans, which is adapted from that of Sweeney et al. (2003). (Only a small number of 

(metabolic) parameters were changed in the EPA's adaptation.) Uncertainty analysis and 

characterization of the human model lead to the following conclusions. 

• Blood:air and tissue:air PCs as measured directly (in rodents) vs. estimated by a 

computational tool were compared, and the impact on model predictions of peak AN and 

peak CEO levels in brain and blood was found to be less than 30% (difference between 

predictions using the alternate sets of PCs).

• Comparison of model predictions to the limited human data of Jakubowski et al. (1987) 

shows that the model over-predicts the inhalation respiratory retention measured 

(predicted ~ 70%; measured 44–58%). This over-prediction may be due to the fact that 

the model does not fully describe the exposure apparatus (which can introduce additional 

airway “dead-space”) or that the model does not describe gas absorption/desorption in the 

conducting airways that can reduce uptake rates. However, since the error (if any) is in 

the direction of over-prediction of uptake, the error is health-protective. 

• Once absorbed, the model predicts that 8.4% of AN is converted to CEO and then 

hydrolyzed, while 30% is converted to CEO and then conjugated with GSH. These 

values bracket the observation of 16.3% of retained AN being excreted in urine as “CEO” 

(after acid extraction). Thus, this limited observation is in line with model predictions 

subsequent to AN predictions, though the exact level of agreement or error cannot be 

determined due to the distinction between observed quantity (CEO in urine) and what the 

model predicts (CEO metabolic rates). 

• The PBTK model over-predicts CEO levels in the rat at early time-points after i.v. 

injection (Figure 3-3) and in blood and brain at all time points measured after oral 

exposure (Figure 3-5a). Kedderis et al. (1996) suggest that the overestimation of CEO by 

the rat model at the early time points (which also occurs in the EPA’s revision) may be 

due to an intrahepatic first pass effect, as occurs with other epoxides formed in situ from 
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their parent olefins (Filser and Bolt, 1984). However, this explanation is unlikely and a 

more plausible explanation is that the model does not account for time-dependence in 

GSH levels. Inclusion of GSH dynamics would be a much more significant and intensive 

change to the model structure than single variation implemented here (addition of EH to 

the rat model with parameter re-estimation) and so has not been considered.

• Parametric sensitivity analysis of human predictions showed a shift in importance 

between the EH and GSH pathways for CEO elimination from being approximately equal 

in the implementation of Sweeney et al. (2003) to lower significance for EH (now low 

but significant) and high significance for GSH with the revised parameters. The 

oxidation of AN to CEO has a significant effect on AN predictions but only a small effect 

on CEO in both model versions, reflecting the high dependence of CEO concentrations 

on CEO metabolic removal. Not surprisingly, brain:tissue PCs significantly affect 

predictions in brain tissue, and the rate constant for oral absorption affects peak AN 

concentrations in blood, but not the AUC. While the human parameters are largely 

derived from human in vitro data, which gives a much higher confidence than would 

occur had they only been extrapolated from rats, the high dependence of CEO 

concentrations on GSH conjugation rates, together with the hypothesis above regarding 

the lack of GSH dynamics in the model, point to that pathway description in particular as 

being the greatest source of quantitative uncertainty.

• Estimated coefficients of variation for predicted concentrations in brain and blood after 

inhalation exposure are ~0.6–0.7 for AN and 0.9–1.2 for CEO; after oral exposure these 

are 0.8–0.9 for AN and 0.7–1.0 for CEO. Based on these values, the human model 

predictions are expected to be accurate to within a factor of approximately 3, which is the 

standard assumption for pharmacokinetic variability among humans.

It can be noted that the oral CSFs are larger when based on blood levels of CEO versus 

blood levels of AN. The VmaxC/Km for AN oxidation in humans is estimated to be about 

10 times higher than in the rat. AN enzymatic GSH conjugation is estimated to be 1.5 times 

higher in the rat, but the 2nd-order removal constant is the same and the GSH tissue levels are 

roughly the same (and lower in the larger tissue groups). The result, for example, with a steady 

oral “infusion” of 30 mg/kg-day, is that AN is removed somewhat faster overall, leading to 

steady-state blood level of 0.114 mg/L in the human vs. 0.151 in the rat. However, a much 

higher portion of this goes to CEO in the human yielding a CEO blood level of 0.297 vs. 

0.013 mg/L in the rat. Thus, CEO:AN = 0.088 in the rat and 2.6 in the human so that the 

CEO-based risk estimate is higher than the AN-based estimate. 
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Dose metric

AN is activated by CYP2E1 into its reactive metabolite, CEO, which binds to DNA and 

initiates tumor formation. Therefore, AUC CEO concentration in blood was selected as the 

internal dosimetric for PBTK modeling. AN is not anticipated to be the causal agent for 

carcinogenesis. Uncertainty in the risk estimate related to the dose metric is primarily associated 

with PBTK model estimation. 

Statistical uncertainty at the POD

Parameter uncertainty within the chosen model reflects the sample size of the cancer 

bioassay. For the multistage model applied to this data set, there is a relatively small degree of 

uncertainty at the BMDL10 (the POD for linear low-dose extrapolation), which is approximately 

1.4-fold lower than the BMD10 (Appendix B, Table B-37). The highest value was selected in 

order to provide a reasonable upper-bound risk estimate. 

With regard to the combined risk estimate, under the assumption of independence of the 

tumor type/site considered, no additional uncertainty is added to the estimated POD. Each 

combined estimate is a statistically rigorous restatement of the statistical uncertainty associated 

with the risk estimates derived from the individual sites. The only assumption in the combining 

tumors approach is independence of tumors. This assumption is consistent with NRC (1994) 

recommendations. 

Choice of low dose extrapolation approach 

The mode of action is a key consideration in deciding how risks should be estimated for 

low-dose exposure. The mode of action for cancer effects of AN is discussed extensively in 

Section 4.7.3.1 and is determined to be mainly due to direct mutagenicity. Other modes of action 

are plausible, but the evidence suggests they may not be key to the carcinogenicity of AN. The 

pattern of tumors is consistent with DNA-reactive chemicals. When the mode of action is 

determined to be direct mutagenicity, a linear approach is used to estimate low-exposure risk, in 

accordance with EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a). 

Choice of species/gender 

No human cancer epidemiology study via the oral route is available. Cancer risk is 

estimated for both male and female rats, and cancer risk for the strain and gender with the 

highest risk, Sprague-Dawley females, was selected. Mammary gland tumors were observed in 

female rats of both studies. Although a cancer bioassay in B6C3F1 mice is also available, the 

exposure was via gavage and no PBTK model is available for mice. It was assumed that humans 

are as sensitive overall as rats, although the true correspondence is unknown. Site concordance 

is not assumed, nor is it necessary (U.S. EPA, 2005a). 
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Human population variability

Heterogeneity among humans is another source of uncertainty, in that human risk can be 

higher or lower than that estimated from rats, depending on relative sensitivity. Human genetic 

polymorphisms in CYP2E1 activities likely contribute to variability in susceptibility to the toxic 

effects of AN (see Section 4.8.4.1). In addition, increased early-life susceptibility was 

demonstrated in two studies in rats exposed gestationally (see Section 5.4.4.3). 

5.4.5.2. Inhalation Cancer Assessment 

Uncertainties related to the IUR assessment are discussed below and summarized in 

Table 5-27 and Figure 5-5. 

Table 5-27. Summary of uncertainty in the AN inhalation cancer risk 

assessment

Consideration/ 

approach 

Impact on cancer risk 

estimatea Decision Justification 

Choice of study Cancer risk estimate 

could increase because 

only lung cancer deaths 

evaluated. 

Lung cancer mortality and 

exposure data from Blair et al. 

(1998) study was used to derive 

IUR. 

IUR derived from best available 

cancer epidemiological study of AN 

exposed workers has fewer inherent 

uncertainties than IUR derived from 

rat study (Quast et al., 1980b). 

Low-dose 

extrapolation 

procedure 

The selected model does 

not represent all possible 

models one might fit, and 

other models could 

conceivably be selected 

to yield more extreme 

results consistent with the 

observed data, both 

higher and lower than 

those included in this 

assessment. 

Low-dose linear. EPA’s Guidelines for Carcinogen 

Risk Assessment (U.S. EPA, 2005a): 

mutagens “are assessed with a linear 

approach.” 

Statistical 

uncertainty at 

POD 

IUR would be reduced 

fourfold if BMD used as 

POD instead of BMDL. 

BMDL, approach for 

calculating reasonable upper 

bound. 

Limited size of study results in 

sampling variability; BMCL is 

lower 95% confidence limit on 

EC01. 

Choice of 

species/gender 

IUR estimated from 

exposed male and female 

workers. 

IUR estimated from entire 

cohort was used. 

No apparent gender difference 

between male and female workers; 

male and female rats were also 

similar. 

Human population 

variability in 

metabolism and 

response/sensitive 

subpopulations 

Low-dose risk for general 

population can increase to 

an unknown extent due to 

underestimation of human 

variability (healthy 

worker effect). 

Semi-parametric Cox 

regression model with timedependent covariates was used. 

The Cox model allows 

inclusion of individual 

exposure histories and utilizes 

internal controls, thus avoiding 

confounding by the healthy 

worker effect. 

Increased early-life susceptibility 

demonstrated in rat studies. Human 

variability in susceptibility likely 

exists due to differences in 

microsomal CYP2E1 activities, and 

possibly GST activity. 
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0.070

0.060

0.0040 0.0035

0.020

0.000

0.010

0.020

0.030

0.040

0.050

0.060

0.070

0.080

0.090

0.100

Male Sprague-Dawley Rats Female Sprague-Dawley Rats Humans Exposed

Occupationally

Sex/Strain/Species

Inhalation Unit Risk

(mg/m

3

)-1

IUR - CEO in Blood

IUR - Human Equivalent Administered Concentration

Figure 5-5. Comparison of composite IURs derived from: (1) tumor 

incidence data in male and female Sprague-Dawley rats exposed chronically 

to AN, and (2) neurological effects in humans exposed to AN occupationally. 

In deriving the animal-based IURs, two different dose metrics were 

employed: (1) predicted CEO concentration in blood, and (2) human 

equivalent administered AN concentration in air. 

Choice of study

As mentioned previously, the Blair et al. (1998) cohort study is the largest cohort 

assessment of the relationship between AN exposure and cancer. This study had the distinct 

advantage of quantifying exposure and using an internal control group of unexposed workers, all 

factors identified as shortcomings in previous studies. Information on smoking history, a 

potential confounder when lung cancer is the outcome of interest, was available, but only for a 

small subset within the Blair et al. (1998) cohort. Blair et al. (1998) limited their analysis to the

white male population and noted that adjustment for smoking reduced the risk of lung cancer 

slightly. The data used in this assessment to derive the IUR included the entire cohort; 

consequently, the smoking history data were incomplete for this analysis, leading to an area of 

uncertainty surrounding this risk estimate.
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Another source of uncertainty stems from the use of only lung cancer mortality for the 

derivation of the IUR. As previously described, other studies reported small, but not consistent, 

excess risks for other types of cancer (prostate, bladder, brain cancers) associated with AN 

exposure. Thus, basing the IUR on only lung cancer mortality may underestimate the 

carcinogenic potential of AN. Further, as the IUR is based on mortality rather than lung cancer 

incidence, though in the case of lung cancer mortality is a good surrogate of lung cancer 

incidence, there may be potential for underestimation of carcinogenic potential with this 

approach. Additional uncertainties related to the statistical analysis of these data are further 

discussed in Appendix B-7. Briefly, uncertainties of the statistical approach include: (1) Cox 

model that was fit to the data is not a biologically based model; (2) the estimator of the 

cumulative hazard does not account for the covariate path and hence is only an approximation; 

and (3) the estimate of risk is obtained using the first-order “linearized” approximation. 

However, obtained results are consistent with assumptions of the first-order approximation 

validity. 

 Other uncertainties associated with the NCI/NIOSH cohort include nondifferential 

exposure misclassification, lung cancer misdiagnosis among the internal controls, the relatively 

short follow-up period (reflected by the relatively small proportion of mortality within the 

cohort), and the extrapolation of continuous environmental exposure from 8-hour occupational 

exposure without consideration of potential recovery mechanisms between daily exposures. The 

nondifferential exposure misclassification contributes to an underestimation of risk, while the 

impacts of short follow-up and extrapolation to a continuous exposure scenario are unclear. 

Nonetheless, the NCI/NIOSH cohort provides the most robust data set in terms of sample size 

and exposure assessment for the derivation of the IUR. 

Statistical uncertainty at the POD 

Parameter uncertainty within the chosen model reflects the limited sample size of the 

cancer bioassay. For the results relying on the cohort study, the EC01 is approximately fourfold 

higher than the LEC01. 

For the multistage model applied to the rat data, in support of the human-based results, 

there is a reasonably small degree of uncertainty at the 10% incidence level (the POD for linear 

low-dose extrapolation). Composite BMC10s for overall cancer risk are approximately 1.3-fold 

higher than their corresponding BMCL10s for both male and female rats. 

With regard to the combined risk estimate, under the assumption of independence of the 

tumor type/site considered no additional uncertainty is added to the estimated POD. Each 

combined estimate is a statistically rigorous restatement of the statistical uncertainty associated 

with the risk estimates derived from the individual sites. This assumption is consistent with NRC 

(1994) recommendations. 
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Low-dose extrapolation procedure 

As discussed previously, the key mode of action for carcinogenicity of AN is determined 

to be direct mutagenicity. A linear approach is used to estimate low-exposure risk, in accordance 

with EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a). Nonlinear low-dose 

extrapolation approach is not used since data do not support other modes of action at this time. 

Choice of species/gender 

A human study was selected for quantification of IUR. Both male and female workers 

were evaluated. A 2-year inhalation study of male and female rats was used for comparison. 

Estimates of IURs from the human study and from the rat studies were similar. IURs estimated 

from male and female rats were also similar, although there was a suggestion of higher cancer 

risk in females associated with mammary gland tumors.

Human population variability 

Heterogeneity among humans is another source of uncertainty. Uncertainty related to 

human variation needs consideration, also, in extrapolation from a small subset of human 

population to a larger, more diverse population. The study population in Blair et al. (1998) was 

AN-exposed workers in the United States. To counter the healthy worker effect, internal 

controls were used in the study. Available data from animal studies provide no evidence of 

gender differences in susceptibility to toxicity of AN, although no data is available regarding 

possible gender differences in susceptibility. Polymorphisms in the CYP2E1 gene that affect 

enzyme activity likely contribute to the variability of human susceptibility towards the toxic 

effect of AN (see Section 4.8.4.1). 
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6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION 

OF HAZARD AND DOSE-RESPONSE 

6.1. HUMAN HAZARD POTENTIAL 

AN (CASRN 107-13-1) is a colorless, flammable, and volatile liquid with a weakly pungent 

onion- or garlic-like odor. It is a commercially important chemical used in the manufacture of 

acrylic and modacrylic fibers, plastics (ABS and AN-styrene resins), and nitrile rubbers and as 

an intermediate in the synthesis of other chemicals, such as adiponitrile and acrylamide. 

Exposure to airborne AN is possible for people living in the vicinity of emission sources such as 

acrylic fiber or chemical manufacturing plants or waste sites. 

 AN is rapidly and nearly completely absorbed, widely distributed to tissues, and 

biochemically transformed into metabolites that are excreted in the urine and, to a much lesser 

extent, in feces and expired air. Two major metabolic pathways for AN have been identified: 

detoxification of AN by conjugation with GSH, forming the urinary metabolite N-acetyl-S-

(2-cyanoethyl)cysteine, and oxidation of AN to its epoxide metabolite, CEO, via CYP2E1. CEO 

can bind to tissue macromolecules, such as proteins and DNA. CEO can be hydrolyzed to 

cyanide with further transformation to thiocyanate, which is excreted in urine. Alternatively, 

CEO can interact with GSH, resulting in the formation of a number of other urinary metabolites. 

 There are no studies directly identifying health hazards in humans following oral 

exposures of any duration, but results from a robust array of studies in rats and mice identify 

noncancer lesions in the gastric squamous epithelium and tumors in multiple tissues as potential 

health hazards to humans exposed to AN by the oral route for chronic durations. Results from 

cross-sectional epidemiologic studies of AN-exposed workers identify increased prevalences of 

neurological symptoms and adverse reproductive outcomes in occupationally exposed workers as 

potential health hazards from chronic inhalation exposure. Cancer is another potential human 

health hazard from chronic inhalation exposure, as indicated by increased incidences of tumors at 

several tissue sites in rat chronic inhalation bioassays. Studies of AN-exposed workers have 

provided no strong evidence that mortality from any type of cancer is casually related to 

occupational exposure, but limited evidence from the best-designed epidemiologic study found a 

small, but statistically significant, increased risk for dying from lung cancer in workers with the 

longest durations and highest exposures to AN. 

 The animal toxicity database identifies hyperplasia and hyperkeratosis of the squamous 

epithelium of the forestomach as the most sensitive noncancer effects associated with repeated 

oral exposure to AN. Following chronic oral exposure, these lesions have been observed in rats 

at drinking water concentrations as low as 1–3 ppm (0.09–0.3 mg/kg-day) (Johannsen and 

Levinskas, 2002a, b; Biodynamics, 1980a, b). Other effects have been observed in repeatedly 

exposed animals, generally at higher exposure levels. These include ovarian atrophy in female 
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mice exposed to doses ≥2.5 mg/kg-day for 2 years (NTP, 2001); chronic nephropathy in male 

and female rats exposed for 2 years to 3.4 and 10.8 mg/kg-day AN, respectively (Quast et al., 

1980a); gliosis in the brain of female Sprague-Dawley rats at 4.4 mg/kg-day (Quast et al., 

1980a); decreased sperm count in male mice exposed to 10 mg/kg-day for 60 days (Tandon et 

al., 1988); hind-limb weakness and decreased sensory nerve conduction velocity in male rats 

exposed to 50 mg/kg-day AN for 12 weeks (Gagnaire et al., 1998); and neurobehavioral effects 

in male rats exposed to 4 mg/kg-day AN in drinking water for 8 or 12 weeks (Rongzhu et al., 

2007). No changes in fertility index or pregnancy success were found in a three-generation study 

of rats exposed to drinking water doses as high as 39 mg/kg-day (Friedman and Beliles, 2002; 

Litton Bionetics, 1992). Mild developmental effects were observed at 11 and 20 mg/kg-day 

(small deficits in postnatal pup weight or survival) in this three-generation rat study and at 25 

mg/kg-day (increased litters with pups with missing vertebrae) but not at 10 mg/kg-day in rat 

fetuses exposed on GDs 6–15 (Murray et al., 1978). 

 Repeated inhalation exposure to AN in the workplace has been associated with increased 

prevalence of subjective neurological symptoms, such as headache, poor memory, and irritability 

(Chen et al., 2000; Kaneko and Omae, 1992; Muto et al., 1992; Sakurai et al., 1978) and small 

performance deficits in neurobehavioral tests of mood, attention and speed, auditory memory, 

visual perception and memory, and motor steadiness (Lu et al., 2005a). Such effects have been 

associated with average workplace air concentrations of 0.1 or 0.9 ppm and appear to be the most 

sensitive noncancer effects from repeated inhalation exposure to AN. Adverse reproductive 

outcomes, such as increased prevalences of premature deliveries, stillbirths, sterility, birth 

defects, and pregnancy complications, have been associated with occupational exposure to 

average workplace concentrations ranging from 3.6 to 7.5 ppm (Dong et al., 2000a; Li, 2000; 

Dong and Pan, 1995). SubchronicSubchronic and chronic inhalation toxicity studies in rats 

identified other noncancer effects at higher exposure levels, including nasal epithelial lesions in 

rats exposed to concentrations of 20 or 80 ppm for 2 years (Quast et al., 1980b), decreased nerve 

conduction velocity and hind-limb weakness in rats exposed to ≥25 ppm AN (Gagnaire et al., 

1998), increased incidence of rat fetuses with missing vertebrae, missing ribs, or anteriorly 

displaced ovaries following exposure of pregnant Sprague-Dawley rats to 80 ppm on GDs 6–15 

(Murray et al., 1978), and decreased rat fetal weight gain following exposure of pregnant 

Sprague-Dawley rats to concentrations ≥25 ppm on GDs 6–20 (Saillenfait et al., 1993). 

 The genotoxicity of AN has been evaluated in multiple systems in vitro and in vivo. In 

addition to positive findings in blood lymphocytes, buccal mucosal cells, and sperm in five 

epidemiologic studies, DNA alkylation by AN was found in numerous tissues in rats or mice 

(brain, liver, testes, forestomach, colon, kidney, bladder, and lung) treated with a single dose of 

AN. AN or its reactive metabolite, CEO, yielded positive results in in vitro mutation assays 

using bacteria, fungi, and insects, as well as animal and human cell cultures. The weight of 

evidence from these studies suggests that AN is mutagenic after metabolic activation to CEO. 
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 Following EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), AN is 

“likely to be carcinogenic to humans,” based predominantly on consistent results showing that 

lifetime inhalation or oral exposure caused statistically significantly increased incidence of 

tumors at multiple tissue sites in rats and mice. Lifetime oral exposure to AN caused increased 

incidences of tumors at multiple tissue sites, including the brain, forestomach, and Zymbal gland, 

in several rat studies and the forestomach and Harderian gland in a gavage study in mice (NTP, 

2001). Lifetime inhalation bioassays with Sprague-Dawley rats found exposure-related increases 

in the incidences of brain tumors, Zymbal gland tumors, intestinal tumors, tongue tumors, and 

malignant mammary gland tumors (Dow Chemical Co., 1992a; Maltoni et al., 1988, 1977; Quast 

et al., 1980b). Also, there is some association between AN exposure and lung cancer deaths in 

occupationally exposed workers. Rats exposed during gestation and through adulthood 

displayed higher incidences of tumors at several tissue sites than did rats exposed throughout 

adulthood only (Friedman and Beliles, 2002; Maltoni et al., 1988). The latter results suggest that 

exposure to AN during gestation and childhood may present increased risk of developing cancer 

compared with exposure during adulthood alone. 

Although data gaps still exist in the current understanding of the mode of action for 

carcinogenicity of AN, there is adequate experimental evidence to support a direct mutagenic 

mode of action as the key mode of action for AN-induced tumors. Other modes of action may 

contribute, but limited data do not appear supportive at this time. Indirect mutagenicity via 

oxidative DNA damage is plausible, but oxidative stress was not supported by experimental 

evidence as a key mode of action. 

6.2. DOSE-RESPONSE 

6.2.1. Oral RfD 

 The available oral toxicity studies in animals identify nonneoplastic forestomach lesions 

(i.e., squamous cell epithelial hyperplasia and hyperkeratosis) as the most sensitive noncancer 

effect associated with chronic oral exposure to AN. These lesions are expected to be relevant to 

humans because, although humans do not possess a forestomach, they do have comparable 

squamous cell epithelial tissue in their oral cavity and in the upper two-thirds of their esophagus. 

 A 2-year drinking water study with F344 rats (Johanssen and Levinskas, 2002b) was 

selected as the principal study on which to base the RfD because it provided the best available 

dose-response data. This study included five drinking water exposure levels ranging from 1 to 

100 ppm, and it also identified the lowest administered-dose LOAEL of the available chronic 

animal toxicity studies based on an increased incidence of forestomach lesions (i.e., LOAELs of 

0.3 and 0.4 mg/kg-day for males and females, respectively, with associated NOAELs of 0.1 

mg/kg-day for both sexes). 

 An RfD of 2 × 10-4 mg/kg-day (or 0.2 μg/kg-day) is derived for use in humans because it 

is the lowest value derived based on the observed critical effect in the selected principal study 
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(i.e., incidence of nonneoplastic forestomach lesions in F344 rats in a 2-year drinking water 

study). This RfD was derived using a BMD approach based on incidence data for forestomach 

lesions in male and female F344 rats exposed chronically to AN via drinking water and 

pharmacokinetic data from EPA-modified rat and human PBTK models (Section 3.5; Appendix 

C; Sweeney et al., 2003; Kedderis et al., 1996). 

 The RfD derivation process involved first fitting all available dichotomous models in 

BMDS (version 2.0) to the incidence data for male and female rats, separately, employing two 

different internal dose metrics (i.e., AN in blood and CEO in blood). These two internal dose 

metrics were derived by converting administered rat doses of AN to internal rat doses (either AN 

or CEO in blood) using the rat PBTK model of Kedderis et al. (1996), as modified by EPA 

(Section 3.5; Appendix C). Then, for each sex, the BMDL associated with both a 5 and 10% 

extra risk for gastric epithelial lesions was derived based on the best-fitting model. This BMDL 

based on rat internal dose was then converted to the human equivalent administered dose of AN 

by using the human PBTK model of Sweeney et al. (2003) (with EPA-modified parameters; 

Section 3.5; Appendix C). As discussed in more detail in Section 5.1, CEO in blood was 

selected as the best available internal dose metric for cross-species extrapolation with oral 

exposure, while 5% extra risk was chosen as the most appropriate BMR level. The human 

equivalent administered dose of AN represents a POD for noncancer effects and was then 

divided by a UF of 30 (3 to account for uncertainty in extrapolating from rats to humans with 

dosimetric adjustment and 10 to account for variation in response from average humans to 

sensitive humans) to arrive at an RfD. 

 Confidence in the principal study selected for the RfD is high. The principal study, 

Johannsen and Levinskas (2002b), was selected from eight chronic rat studies and one gavage 

study in exposed mice. The study employed five exposure levels of AN, ranging from 1 to 

100 ppm, and thus provided a more complete description of the dose-response relationship in the 

low-dose region than did either the Quast (2002) study in Sprague-Dawley rats or the NTP 

(2001) study in B6C3F1 mice, which started at higher dose levels, and both employed only three 

dose groups. Johannsen and Levinskas (2002b) identified the lowest LOAELs based on an 

increased incidence of hyperplasia and hyperkeratosis in squamous epithelium of forestomach 

(0.4 mg/kg-day for males and 0.4 mg/kg-day for females). No human exposure study is 

available for derivation of the RfD. Overall confidence in the RfD is medium, reflecting these 

considerations. 

6.2.2. Inhalation RfC 

Results from several cross-sectional epidemiologic studies of AN-exposed workers 

identified increased prevalence of neurological symptoms and small performance deficits in 

neurobehavioral tests as the critical effects resulting from chronic inhalation exposure to AN. 

The cross-sectional study of neurobehavioral performance measures in acrylic fiber workers by 
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Lu et al. (2005a) was selected as the principal study for RfC derivation because it identified the 

lowest reliable exposure level in humans associated with adverse neurological effects. 

 A NOAEL/LOAEL approach was used to derive the RfC from the human data. The 

average workplace AN air concentration of 0.11 ppm for workers in the monomer work areas of 

the acrylic fiber plant was selected as the LOAEL or POD for RfC derivation. This LOAEL of 

0.11 ppm (0.24 mg/m3) for small, but statistically significant, performance deficits in 

neurobehavioral tests of mood, attention and speed, auditory memory, visual perception and 

memory, and motor steadiness was divided by a UF of 100 (10 for extrapolating from a LOAEL 

to a NOAEL and 10 to account for extrapolating from healthy workers to sensitive humans), 

after conversion to an equivalent continuous exposure of 0.086 mg/m3, to arrive at an RfC for 

AN of 0.9 μg/m3. 

 As discussed in more detail in Section 5.2, comparative animal-based RfCs for AN of 3 

× 10-3 mg/m3 (or 3 μg/m3) and 2 × 10-3 mg/m3 (or 2 μg/m3) were derived based on PODs from 

BMD modeling of nasal lesions observed in male and female rats, respectively, exposed to AN 

via inhalation for 2 years (Quast et al., 1980b). In deriving these RfCs, the PODs were divided 

by a composite UF of 30 (3 for extrapolating from rats to humans using the default U.S. EPA 

(1994) dosimetric adjustment and 10 to account for variation from average humans to sensitive 

humans). These animal-based RfCs are quite consistent with the human-based value. However, 

the human-based value of 0.9 μg/m3 is selected as the RfC, because extrapolating from animals 

has greater associated uncertainty than extrapolating from humans. 

 The principal study is given medium confidence because it is the best available study 

that identified neurobehavioral effects of AN in occupationally exposed workers. Previous 

occupational studies by Kaneko and Omae (1992) and Muto et al. (1992) reported subjective 

neurological symptoms in exposed workers. Lu et al. (2005a) utilized the WHO-recommended 

NCTB administered by trained physicians to evaluate these neurobehavioral effects systemically. 

Hence, the results were more reliable when compared with those based on self reporting. The 

confidence in the principal study is medium because there are several limitations in the study. 

One was that the cited exposure data represented estimates of previous exposure levels and no 

contemporaneous personal monitoring data were available. In addition, the study authors could 

not rule out the possibility that examiner drift may have affected the results. Moreover, largest 

measures of neurobehavioral effect occurred on the acrylic fiber workers, who had lower average 

exposure level. 

Confidence in the database is medium to high. An RfC based on the results from a 

chronic inhalation study with Sprague-Dawley rats was also derived for comparison. 

Statistically significant increased incidence of inflammatory and degenerative nasal lesions 

occurred in rats exposed to the lowest level in this 2-year bioassay. The alternative RfC derived 

from the rat study is only about threefold higher than the RfC derived from the occupational 

exposure study. Overall confidence in the RfC is medium to high, reflecting these 
374 DRAFT- DO NOT CITE OR QUOTE 

considerations. 

6.2.3. Oral CSF 

Incidence data for forestomach, CNS, Zymbal gland, tongue, and mammary gland tumors 

in male and female Sprague-Dawley (Quast, 2002) and F344 (Johanssen and Levinskas, 2002a) 

rats were used to develop site-specific oral CSFs for AN, employing EPA-modified rat and 

human PBTK models for cross-species dosimetric extrapolation (Section 3.5; Appendix C; 

Sweeney et al., 2003; Kedderis et al., 1996). These animal studies were selected for the 

development of oral CSFs because human data are not available, and these studies are the best 

available chronic bioassays for characterizing the dose-response relationships for these 

AN-induced tumors. Weight-of-evidence evaluation following U.S. EPA (2005a) guidelines 

determined that a direct mutagenic mode of action, most likely via the reactive AN metabolite 

CEO, was the principal mode of action. Consequently, a linear low-dose extrapolation approach 

was used in the development of the oral CSFs. 

As discussed in more detail in Section 5.4, CEO in blood and AN in blood were both 

evaluated as internal dose metrics for use in cross-species extrapolation with oral exposure. The 

multistage dose-response model in BMDS (version 1.4.1) was fit to the male and female rat 

tumor incidence data, using internal animal dose expressed as either CEO or AN in blood. Rat 

administered doses were converted to rat internal doses (either CEO or AN in blood) by using 

the rat PBTK model of Kedderis et al. (1996), as modified by EPA (Section 3.5; Appendix C). 

For each of these two dose metrics, the resulting best-fit model for each endpoint was then used 

to derive a 95% lower confidence limit on the dose associated with 10% extra risk (i.e., a 

BMDL10). These BMDLs, based on internal rat doses, were then converted to human equivalent 

administered doses of AN using the human PBTK model of Sweeney et al. (2003), as modified 

by EPA (Section 3.5; Appendix C). The site-specific oral CSFs based on incidence data from 

each tumor site were derived by linear extrapolation from the human equivalent administered 

doses down to the origin (oral CSF = 0.1/BMDL10/HED). Within rat strain and sex, an oral slope 

factor for the composite risk across these tumor sites, based on CEO in blood, was then estimated 

by employing the procedure described in Section 5.4.4.1. 

The highest composite slope factor of 5 per mg/kg-day is recommended for use in 

humans because it has the highest potency based on the observed critical effect in the selected 

principal study (i.e., incidence of tumors in male and female Sprague-Dawley rats). This slope 

factor is recommended for estimating composite cancer risks in humans who experience chronic 

oral exposures to AN during adulthood. This slope factor should not be used with exposures 

greater than 0.04 mg/kg-day (the lowest POD supporting the composite risk) because above this 

level, the slope factor cannot be expected to be an adequate approximation to the dose-response 

relationship. The fitted dose-response relationship and pharmacokinetic models should be used 

to estimate risk above this exposure level. 
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Results from a chronic rat inhalation cancer bioassay (Maltoni et al., 1988) and a threegeneration rat drinking water reproductive toxicity study (Friedman and Beliles, 2002) indicate 

that AN exposure during gestation and early periods of development may increase risks for 

cancer by at least threefold compared with chronic AN exposures during adulthood only. A 

chemical-specific early life susceptibility factor of 3.6 was developed for assessing cancer risks 

associated with lifetime exposure beginning at birth, based on the incidence data in the Maltoni 

et al. (1988) bioassay for mammary tumors, brain tumors, and extra-hepatic angiosarcomas in 

female rats. 

6.2.4. Cancer Inhalation Unit Risk 

An analysis of the human lung cancer mortality data from the Blair et al. (1998) cohort 

study of AN-exposed workers was conducted to derive an IUR estimate for AN based on human 

data. This analysis employed the approach presented by Starr et al. (2004) and is further 

described in Appendix B-7. In brief, the risk of death from lung cancer in AN-exposed workers 

was characterized by using a semi-parametric Cox regression model with a cumulative exposure 

metric (i.e., ppm-working years) as the only time-dependent covariate. In contrast to the analysis 

by Starr et al. (2004), the entire cohort was included in the analysis conducted for this assessment 

(not just white male workers), and the final model only included cumulative exposure as the 

covariate. 

 The Cox regression model described above was used to estimate an AN exposure level 

and its associated 95% lower confidence limit corresponding to a 1% risk of dying from lung 

cancer by age 80 (i.e., EC01 and LEC01, respectively). Conversion of occupational exposures to 

continuous environmental exposures was accomplished by adjusting for differences in the 

amount of air inhaled during an 8-hour workday versus a 24-hour day (10 and 20 m3/day, 

respectively). The IUR estimate was derived by linear extrapolation from the LEC01. The 

predicted EC01 and LEC01 derived from the Cox regression model based on the Blair et al. (1998) 

data were 0.992 and 0.238 ppm (2,168 and 524 μg/m3) AN, respectively. From the LEC01, an 

IUR estimate of 0.042 per ppm (2 × 10-5 per μg/m3

) was derived. 

 Some uncertainty is associated with this IUR estimate because of the study on which it is 

based. More specifically, no adjustment for smoking was applied in the Blair et al. (1998) study. 

The investigators collected smoking information on only about 10% of the exposed and 

unexposed members of the cohort and found similar incidences of smoking in the two groups. 

Because their statistical analysis compared exposed and unexposed groups of workers, Blair et 

al. (1998) noted that the adjustment for smoking made only a slight difference in the results of 

their analysis. Other uncertainties associated with the Blair et al. (1998) data set included 

nondifferential exposure misclassification and a relatively short follow-up period, an average of 

21 years. Additionally, the outcome of the study was lung cancer mortality, not lung cancer 
376 DRAFT- DO NOT CITE OR QUOTE 

incidence. Additional uncertainties related to the statistical analysis of these data are discussed 

further in Appendix B-7.

Tumor incidence data from the best available animal inhalation study (Dow Chemical 

Co., 1992a) were selected for describing the dose-response relationship between intestinal, CNS, 

Zymbal’s gland, tongue, and mammary gland tumors and AN exposure. These dose-response 

relationships were used to derive animal-based IURs for AN for comparative purposes. As with 

the animal-based oral slope factor, a direct mutagenic mode of action, most likely via the 

reactive AN metabolite CEO, was assumed, because available information was inadequate to 

establish AN’s mode of carcinogenic action in these tissues in animals. Consequently, a linear 

low-dose extrapolation approach was used in the development of the animal-based IURs. 

Based on the assumption that the epoxide metabolite, CEO, is critical to AN’s 

carcinogenic mode of action, the selected internal dose metric was CEO in blood. In contrast to 

oral exposure, the EPA-modified PBTK model adequately predicted measured blood and brain 

concentrations of CEO in rats exposed to AN by inhalation (Kedderis et al., 1996). The 

multistage model was fit to the rat tumor incidence and CEO concentration in blood predicted by 

the PBTK model of Kedderis et al. (1996), as modified by EPA (Section 3.5; Appendix C). The 

best-fitting stage of the model was used to derive 95% lower bounds on rat internal blood 

concentrations of CEO associated with 10% extra risk (BMCL10s). The human PBTK model of 

Sweeney et al. (2003) (parameters modified; Section 3.5; Appendix C), was then used to 

calculate human equivalent administered concentrations of AN, corresponding to the rat 

BMCL10s. These human equivalent administered concentrations of AN were used as the POD 

for the IUR estimates via linear extrapolation down to the origin (i.e., IUR = 0.1/BMCL10/HEC). 

The IUR estimates for multiple tumor sites were derived within each rat sex by 

employing the procedure described in Section 5.4.4.1. The resulting composite IUR estimates 

were 7 × 10-2 and 6 × 10-2 per mg/m3 (7 × 10-5 and 6 × 10-5 per μg/m3) and were derived based on 

tumor incidence data from male and female Sprague-Dawley rats, respectively. These unit risks 

should not be used with exposures greater than 3 mg/m3 (the lowest POD supporting the 

composite risk), because above this level, the slope factor cannot be expected to be an adequate 

approximation of the dose-response relationship. The fitted dose-response relationship and 

pharmacokinetic models should be used to estimate risk above this exposure level. 

Given that the IUR of 2 × 10-5 per μg/m3 is based on human data and is consistent with 

the IUR derived from the animal data, it is the IUR recommended for estimating cancer risks 

associated with chronic inhalation exposures to AN during adult stages of development. 

As described for the oral slope factor, a chemical-specific early-life adjustment factor of 

3.6 was developed for assessing cancer risks associated with lifetime exposure beginning at 

birth, based on the multisite tumor incidence data for female rats in the Maltoni et al. (1988) 

bioassay. 

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APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC 

COMMENTS AND DISPOSITION 
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APPENDIX B. BENCHMARK DOSE CALCULATIONS 

APPENDIX B-1. NONCANCER ORAL DOSE-RESPONSE ASSESSMENT (RfD): 

BENCHMARK DOSE MODELING RESULTS EMPLOYING THE INCIDENCE OF 

FORESTOMACH LESIONS (HYPERPLASIA AND HYPERKERATOSIS) IN MALE 

AND FEMALE SPRAGUE-DAWLEY RATS, F344 RATS, AND B6C3F1 MICE 

CHRONICALLY EXPOSED ORALLY TO AN FOR 2 YEARS 

As previously discussed in Section 4, no human studies currently exist that involve oral 

exposures to AN. The available animal oral toxicity data, however, identify forestomach lesions 

(i.e., squamous cell epithelial hyperplasia and hyperkeratosis) as the most sensitive, prevalent, 

and consistent noncancer effect associated with chronic oral exposure to AN. Therefore, this 

endpoint was selected as the critical effect on which to base derivation of the RfD. 

 Two 2-year drinking water studies, one in Sprague-Dawley rats (Quast, 2002; Quast et 

al., 1980a) and the other in F344 rats (Johannsen and Levinskas, 2002b; Biodynamics 1980c), 

and a 2-year gavage study in B6C3F1 mice (NTP, 2001) provided the best available doseresponse data on which to base the RfD. Candidate RfDs for AN were derived from the 

incidence of forestomach lesions in Sprague-Dawley rats, F344 rats, and B6C3F1 mice using a 

BMD approach. Incidences of forestomach lesions from chronic drinking water studies in male 

and female Sprague-Dawley rats (Quast, 2002) and F344 rats (Johannsen and Levinskas, 2002b) 

provided four sets of dose-response data from which to derive candidate RfDs, while incidences 

of forestomach lesions from a chronic gavage study in male and female B6C3F1 mice provided 

an additional two sets of dose-response data. These six data sets are presented in Tables B-1 (for 

rats) and B-2 (for mice). 

Table B-1. Incidences of forestomach lesions (hyperplasia or 

hyperkeratosis) in Sprague-Dawley and F344 rats exposed to AN in drinking 

water for 2 years 

Predicted internal dose metricsb

Sex 

Administered 

concentration 

(ppm in drinking 

water) 

Administered 

dosea

(mg/kg-d) 

AN-AUC in rat 

blood 

(mg/L) 

CEO-AUC in rat 

blood 

(mg/L) 

Incidence of 

forestomach 

lesionsc

Sprague-Dawley rats 

(Sources: Quast, 2002; Quast et al., 1980a)

0 0 0 0 15/80 (19%) 

35 3.4 2.06 × 10-2 1.83 × 10-3 15/47 (32%) 

100 8.5 5.36 × 10-2 4.36 × 10-3 44/48 (92%)

Male 

c

300 21.3 1.46 × 10-1 9.70 × 10-3 45/48 (94%)c

Female 0 0 0 0 20/80 (25%) 

35 4.4 2.37 × 10-2 2.07 × 10-3 23/48 (48%)c
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Table B-1. Incidences of forestomach lesions (hyperplasia or 

hyperkeratosis) in Sprague-Dawley and F344 rats exposed to AN in drinking 

water for 2 years 

Predicted internal dose metricsb

Sex 

Administered 

concentration 

(ppm in drinking 

water) 

Administered 

dosea

(mg/kg-d) 

AN-AUC in rat 

blood 

(mg/L) 

CEO-AUC in rat 

blood 

(mg/L) 

Incidence of 

forestomach 

lesionsc

100 10.8 6.18 × 10-2 4.87 × 10-3 41/48 (85%)c

300 25.0 1.56 × 10-1 1.01 × 10-2 47/48 (98%)c

F344 ratsd

(Sources: Johannsen and Levinskas, 2002b; Biodynamics, 1980c)d

0 0 0 0 11/159 (7%) 

1 0.08 4.33 × 10-4 4.06 × 10-5 3/80 (4%) 

3 0.25 1.35 × 10-3 1.27 × 10-4 18/75 (24%)c

10 0.83 4.52 × 10-3 4.19 × 10-4 13/80 (16%)c

30 2.48 1.37 × 10-2 1.23 × 10-3 17/80 (22%)c

Male 

100 8.37 4.85 × 10-2 3.97 × 10-3 9/77 (12%) 

0 0 0 0 4/156 (3%) 

1 0.12 5.73 × 10-4 5.32 × 10-5 2/80 (3%) 

3 0.36 1.72 × 10-3 1.59 × 10-4 16/80 (20%)c

10 1.25 6.02 × 10-3 5.49 × 10-4 23/74 (31%)c

30 3.65 1.79 × 10-2 1.58 × 10-3 13/80 (16%)c

Female 

100 10.90 5.63 × 10-2 4.46 × 10-3 5/74 (7%) 

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake. 

bThe EPA-modified rat PBPK model of Keddaris et al. (1996) was employed to predict a rat internal dose (i.e., 

either AN-AUC or CEO-AUC concentration in blood) resulting from the ingestion of the specified administered 

dose of AN consumed in six bolus episodes/d. 

c

Indicates significantly different (at p < 0.05) from control incidence by Fisher’s exact test performed by Syracuse 

Research Corporation. 

d

Incidences for F344 rats do not include animals from the 6- and 12-mo sacrifices and were further adjusted to 

exclude (from the denominators) rats that died between 0 and 12 mos in the study. Rats dying during this time 

period were determined from page 6 of Appendix H and Table 1 in Biodynamics (1980c) and Table 8 in Johannsen 

and Levinskas (2002b). Unscheduled deaths between 0 and 12 mos in the study occurred in two female controls, 

two males at 3 ppm, three females at 10 ppm, and three males and three females at 100 ppm. 
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Table B-2. Incidences of forestomach lesions (hyperplasia or 

hyperkeratosis) in male and female B6C3F1 mice administered AN via 

gavage for 2 years 

Dose (mg/kg-d)a

Lesion site and type 0 2.5 10 20 

Males

Forestomach hyperplasia or hyperkeratosis 2/50 

(4%) 

4/50 

(8%) 

10/50a 

(20%) 

13/50b 

(26%) 

Females

Forestomach hyperplasia or hyperkeratosis 2/50 

(4%) 

2/50 

(4%) 

5/50 

(10%) 

8/50a 

(16%) 

a

Significantly elevated above vehicle control as determined by EPA using Fisher’s exact test (p ≤ 0.05). 

b

Significantly elevated above vehicle control as determined by EPA using Fisher’s exact test (p ≤ 0.01). 

Source: NTP (2001). 

The incidences of forestomach lesions observed following 2 years of AN exposure in 

male and female SD and F344 rats were modeled using AN and CEO in blood, expressed in 

mg/L, as internal dose metrics. In addition, incidences of these same lesions were modeled in 

male and female SD and F344 rats, as well as male and female B6C3F1 mice, employing 

administered dose. In all cases, all of the dichotomous dose-response models available in EPA’s 

BMDS software (version 2.0) (i.e., the gamma, logistic, log-logistic, probit, log-probit, 

multistage, Weibull, and quantal-linear models) were fit to these incidence data. Because the 

incidence of forestomach lesions in male and female F344 rats did not increase monotonically 

across all administered concentrations, however, only incidence data from the three lowest 

concentrations (i.e., 0, 1, and 3 ppm) were used in dose-response modeling. Similarly, in male 

Sprague-Dawley rats, the incidence data from the highest dose group needed to be dropped prior 

to BMD modeling. In most cases, several models fit the data equally well (i.e., exhibited χ

2

goodness-of-fit p values greater than 0.1). Of those models exhibiting adequate fit, the selected 

model was the one with the lowest AIC value. BMDL10 and BMDL05 estimates were derived 

from the selected model. If more than one model shared the lowest AIC, the mean BMDL10 and 

BMDL05 were calculated, as per the EPA’s Benchmark Dose Technical Guidance Document

(U.S. EPA, 2000b). 

In this appendix, detailed results of the dose-response modeling for forestomach lesions 

in male and female SD and F344 rats, and B6C3F1 mice are presented. For each species, strain, 

and sex, summaries of the dose-response data (i.e., animal administered and internal doses and 

incidence data) are presented (Table B-1 for rats and Table B-2 for mice). Then, again for each 

species, strain, and sex, Tables B-3 (Sprague-Dawley rats), B-4 (F344 rats), and B-5 (B6C3F1

mice) summarize the results of the dose-response modeling. Each of these tables is then 
B-4 DRAFT- DO NOT CITE OR QUOTE 

followed by the standard output from EPA’s BMDS, version 2.0, for the dose-response models 

that did not exhibit statistically significant lack of fit. 

 

Table B-3. Summary of the BMD modeling results based on the incidence of 

forestomach lesions (hyperplasia or hyperkeratosis) in male and female 

Sprague-Dawley rats exposed to AN in drinking water for 2 years

Sex Endpoint Dose metric Selected model(s)a

χ2

p-value AIC BMDL10

b

 BMDL05

b

Estimated 

administered 

dose 

(mg/kg-d) 

Two-stage multistage 

(1) 0.18 169.45 1.27 7.20 × 10-1

Predicted AN 

in blood 

(mg/L) 

Two-stage multistage 

(1) 0.24 169.01 7.72 × 10-3 4.32 × 10

Male -3

Forestomach 

lesions 

Predicted CEO 

in blood 

(mg/L) 

Two-stage multistage 

(1) 0.12 170.09 6.82 × 10-4 3.90 × 10-4
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Table B-3. Summary of the BMD modeling results based on the incidence of 

forestomach lesions (hyperplasia or hyperkeratosis) in male and female 

Sprague-Dawley rats exposed to AN in drinking water for 2 years

Sex Endpoint Dose metric Selected model(s)a

χ2

p-value AIC BMDL10

b

 BMDL05

b

gamma 0.38 212.77 6.87 × 10-1 3.34 × 10-1

logistic 0.45 211.31 1.24 6.39 × 10-1

log-logistic 0.98 212.03 1.41 9.17 × 10-1

log-probit 0.74 212.14 1.38 9.61 × 10-1

one-stage multistage 0.31 212.40 6.30 × 10-1 3.07 × 10-1

Weibull 0.31 213.07 6.74 × 10-1 3.28 × 10-1

Estimated 

administered 

dose 

(mg/kg-d) 

quantal linear 0.31 212.40 6.30 × 10-1 3.07 × 10-1

gamma 0.32 212.96 3.76 × 10-3 1.83 × 10-3

logistic 0.23 212.00 7.07 × 10-3 3.64 × 10-3

log-logistic 0.98 212.03 6.93 × 10-3 4.36 × 10-3

log-probit 0.70 212.18 7.02 × 10-3 4.88 × 10-3

one-stage multistage 0.42 211.79 3.62 × 10-3 1.76 × 10-3

Weibull 0.28 213.19 3.72 × 10-3 1.81 × 10-3

Predicted AN 

in blood 

(mg/L) 

quantal linear 0.42 211.79 3.62 × 10-3 1.76 × 10-3

gamma 0.51 212.45 3.53 × 10-4 1.74 × 10-4

logistic 0.69 210.72 5.58 × 10-4 2.88 × 10-4

log-logistic 0.87 212.06 7.25 × 10-4 4.87 × 10-4

probit 0.33 211.86 5.87 × 10-4 3.00 × 10-4

Female Forestomach 

lesions 

Predicted CEO 

in blood 

(mg/L) 

log-probit 0.86 212.06 7.17 × 10-4 5.15 × 10-4

aAll dichotomous models in EPA’s BMDS (version 2.0) were fit to the incidence of forestomach lesions 

(hyperplasia or hyperkeratosis) in Sprague-Dawley rats using the data presented in Table B-1. For BMD modeling, 

three different dose metrics were employed: (1) administered animal dose (estimated) expressed in mg/kg-d, (2) 

AN in blood (predicted) expressed in mg/L, and (3) CEO in blood (predicted) expressed in mg/L. Adequate fit of a 

model was achieved if the χ

2

 goodness-of-fit statistic yielded a p-value > 0.1. The numbers in parentheses indicate 

the number of dose groups dropped in order to obtain an adequate fit, starting with the highest dose group. Of those 

models exhibiting adequate fit, the selected model was the model with the lowest AIC value, and is indicated in 

bold in the table.

bBMDL10 and BMDL05 estimates were derived from the selected model. If more than one model shared the lowest 

AIC, the mean BMDL10 and BMDL05 were calculated, as per the EPA’s Benchmark Dose Technical Guidance 

Document (U.S. EPA, 2000b). 

Sources: Quast (2002); Quast et al. (1980a). 
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SD Male Rats: Forestomach lesions (administered dose) 

 0.2

 0.4

 0.6

 0.8

 1

 0 1 2 3 4 5 6 7 8

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

16:25 10/03 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpAB.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpAB.plt 

 Fri Oct 03 16:25:01 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 
B-7 DRAFT- DO NOT CITE OR QUOTE 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.110075 

 Beta(1) = 0 

 Beta(2) = 0.0325391 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.37 

 Beta(2) -0.37 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.170685 * * * 

 Beta(1) 0 * * * 

 Beta(2) 0.0278185 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -81.807 3 

 Fitted model -82.7268 2 1.83969 1 0.175 

 Reduced model -119.21 1 74.8052 2 <.0001 

 AIC: 169.454 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.1707 13.655 15.000 80 0.400 

 3.4000 0.3987 18.741 15.000 47 -1.114 

 8.5000 0.8889 42.666 44.000 48 0.613 

 Chi^2 = 1.78 d.f. = 1 P-value = 0.1825
B-8 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1.35789 

 BMDL = 0.719865 

 BMDU = 1.59564 

Taken together, (0.719865, 1.59564) is a 90 % two-sided confidence 

interval for the BMD 
B-9 DRAFT- DO NOT CITE OR QUOTE 

SD Male Rats: Forestomach lesions (AN in blood) 

 0.2

 0.4

 0.6

 0.8

 1

 0 0.01 0.02 0.03 0.04 0.05

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

11:55 10/06 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpBB.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpBB.plt 

 Mon Oct 06 11:55:17 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-10 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.121757 

 Beta(1) = 0 

 Beta(2) = 815.045 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.36 

 Beta(2) -0.36 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.172109 * * * 

 Beta(1) 0 * * * 

 Beta(2) 714.086 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -81.807 3 

 Fitted model -82.5048 2 1.39565 1 0.2375 

 Reduced model -119.21 1 74.8052 2 <.0001 

 AIC: 169.01 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.1721 13.769 15.000 80 0.365 

 0.0206 0.3885 18.261 15.000 47 -0.976 

 0.0536 0.8936 42.892 44.000 48 0.519 

 Chi^2 = 1.35 d.f. = 1 P-value = 0.2445
B-11 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0084753 

 BMDL = 0.0043156 

 BMDU = 0.0099743 

Taken together, (0.0043156, 0.0099743) is a 90 % two-sided confidence 

interval for the BMD 
B-12 DRAFT- DO NOT CITE OR QUOTE 

SD Male Rats: Forestomach lesions (CEO in blood) 

 0.2

 0.4

 0.6

 0.8

 1

 0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

12:07 10/06 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpCC.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpCC.plt 

 Mon Oct 06 12:07:44 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 
B-13 DRAFT- DO NOT CITE OR QUOTE 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.0947166 

 Beta(1) = 0 

 Beta(2) = 124268 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.37 

 Beta(2) -0.37 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.169148 * * * 

 Beta(1) 0 * * * 

 Beta(2) 102914 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -81.807 3 

 Fitted model -83.0465 2 2.47897 1 0.1154 

 Reduced model -119.21 1 74.8052 2 <.0001 

 AIC: 170.093 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.1691 13.532 15.000 80 0.438 

 0.0018 0.4114 19.334 15.000 47 -1.285 

 0.0044 0.8825 42.362 44.000 48 0.734 

 Chi^2 = 2.38 d.f. = 1 P-value = 0.1228

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000705982 

 BMDL = 0.000390266 

 BMDU = 0.000828151 

Taken together, (0.000390266, 0.000828151) is a 90 % two-sided confidence 

interval for the BMD 
B-14 DRAFT- DO NOT CITE OR QUOTE 

SD Female Rats: Forestomach lesions (administered dose) 

 0.2

 0.4

 0.6

 0.8

 1

 0 5 10 15 20 25

Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

14:42 10/06 2008

BMDL BMD

 

Gamma Multi-Hit

 ==================================================================== 

 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpD9.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpD9.plt 

 Mon Oct 06 14:42:46 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response]= background+(1-background)*CumGamma[slope*dose,power], 

 where CumGamma(.) is the cummulative Gamma distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.253086 

 Slope = 0.194377 
B-15 DRAFT- DO NOT CITE OR QUOTE 

 Power = 1.66787 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Slope Power 

Background 1 0.13 0.25 

 Slope 0.13 1 0.95 

 Power 0.25 0.95 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.247085 0.0476211 0.153749 0.340421 

 Slope 0.22327 0.0913548 0.0442181 0.402322 

 Power 1.72213 0.704799 0.340745 3.10351 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.386 3 0.738711 1 0.3901 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.772 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2471 19.767 20.000 80 0.060 

 4.4000 0.5044 24.212 23.000 48 -0.350 

 10.8000 0.8219 39.451 41.000 48 0.584 

 25.0000 0.9879 47.420 47.000 48 -0.555 

 Chi^2 = 0.78 d.f. = 1 P-value = 0.3785

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1.12 

 BMDL = 0.334344 
B-16 DRAFT- DO NOT CITE OR QUOTE 

 0.2

 0.4

 0.6

 0.8

 1

 0 5 10 15 20 25

Fraction Affected

dose

Logistic Model with 0.95 Confidence Level

14:44 10/06 2008

BMDL BMD

 

Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpDB.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpDB.plt 

 Mon Oct 06 14:44:22 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = 1/[1+EXP(-intercept-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 background = 0 Specified 

 intercept = -0.808992 

 slope = 0.180053 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-17 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.66 

 slope -0.66 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -1.07104 0.225024 -1.51208 -0.630006 

 slope 0.23795 0.0368793 0.165668 0.310232 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.655 2 1.27604 2 0.5283 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 211.31 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2552 20.416 20.000 80 -0.107 

 4.4000 0.4940 23.711 23.000 48 -0.205 

 10.8000 0.8174 39.235 41.000 48 0.659 

 25.0000 0.9924 47.637 47.000 48 -1.062 

 Chi^2 = 1.62 d.f. = 2 P-value = 0.4456

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.78799 

 BMDL = 0.639403 
B-18 DRAFT- DO NOT CITE OR QUOTE 

 0.2

 0.4

 0.6

 0.8

 1

 0 5 10 15 20 25

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

14:46 10/06 2008

BMDL BMD

 

Log-Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpDD.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpDD.plt 

 Mon Oct 06 14:46:39 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial Parameter Values 

 background = 0.25 

 intercept = -4.55921 

 slope = 2.51883 
B-19 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 background intercept slope 

background 1 -0.3 0.2 

 intercept -0.3 1 -0.96 

 slope 0.2 -0.96 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.250085 * * * 

 intercept -4.54432 * * * 

 slope 2.51011 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.017 3 0.000749029 1 0.9782 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.034 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2501 20.007 20.000 80 -0.002 

 4.4000 0.4785 22.970 23.000 48 0.009 

 10.8000 0.8550 41.041 41.000 48 -0.017 

 25.0000 0.9788 46.981 47.000 48 0.019 

 Chi^2 = 0.00 d.f. = 1 P-value = 0.9782

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1.89151 

 BMDL = 0.917407 
B-20 DRAFT- DO NOT CITE OR QUOTE 

 0.2

 0.4

 0.6

 0.8

 1

 0 5 10 15 20 25

Fraction Affected

dose

LogProbit Model with 0.95 Confidence Level

14:50 10/06 2008

BMDL BMD

 

LogProbit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpDE.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpDE.plt 

 Mon Oct 06 14:50:13 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = Background 

 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial (and Specified) Parameter Values 
B-21 DRAFT- DO NOT CITE OR QUOTE 

 background = 0.25 

 intercept = -2.53925 

 slope = 1.39624 

 Asymptotic Correlation Matrix of Parameter Estimates 

 background intercept slope 

background 1 -0.31 0.21 

 intercept -0.31 1 -0.96 

 slope 0.21 -0.96 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.248842 0.0480048 0.154755 0.34293 

 intercept -2.58881 0.657292 -3.87708 -1.30054 

 slope 1.42762 0.288071 0.86301 1.99223 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.07 3 0.106572 1 0.7441 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.14 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2488 19.907 20.000 80 0.024 

 4.4000 0.4876 23.406 23.000 48 -0.117 

 10.8000 0.8427 40.448 41.000 48 0.219 

 25.0000 0.9832 47.192 47.000 48 -0.216 

 Chi^2 = 0.11 d.f. = 1 P-value = 0.7415

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1.93713 

 BMDL = 0.961058 
B-22 DRAFT- DO NOT CITE OR QUOTE 

 0.2

 0.4

 0.6

 0.8

 1

 0 5 10 15 20 25

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:52 10/06 2008

BMDLBMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpDF.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpDF.plt 

 Mon Oct 06 14:52:05 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-23 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.18073 

 Beta(1) = 0.14774 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.46 

 Beta(1) -0.46 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.235056 * * * 

 Beta(1) 0.131634 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -104.199 2 2.36383 2 0.3067 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.397 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2351 18.804 20.000 80 0.315 

 4.4000 0.5714 27.425 23.000 48 -1.291 

 10.8000 0.8154 39.139 41.000 48 0.692 

 25.0000 0.9715 46.633 47.000 48 0.318 

 Chi^2 = 2.35 d.f. = 2 P-value = 0.3095

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.389667 

 BMDL = 0.306761 

 BMDU = 0.505425 

Taken together, (0.306761, 0.505425) is a 90 % two-sided confidence 

interval for the BMD 
B-24 DRAFT- DO NOT CITE OR QUOTE 

 0.2

 0.4

 0.6

 0.8

 1

 0 5 10 15 20 25

Fraction Affected

dose

Weibull Model with 0.95 Confidence Level

14:55 10/06 2008

BMDL BMD

 

Weibull

 ==================================================================== 

 Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpE2.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpE2.plt 

 Mon Oct 06 14:55:23 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.253086 

 Slope = 0.0679496 

 Power = 1.19621 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-25 DRAFT- DO NOT CITE OR QUOTE 

 Background Slope Power 

Background 1 -0.31 0.23 

 Slope -0.31 1 -0.97 

 Power 0.23 -0.97 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.245056 0.0471325 0.152678 0.337434 

 Slope 0.0673284 0.0436908 -0.018304 0.152961 

 Power 1.27711 0.255412 0.776514 1.77771 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.534 3 1.03516 1 0.3089 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 213.069 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2451 19.604 20.000 80 0.103 

 4.4000 0.5170 24.816 23.000 48 -0.525 

 10.8000 0.8150 39.118 41.000 48 0.700 

 25.0000 0.9876 47.404 47.000 48 -0.526 

 Chi^2 = 1.05 d.f. = 1 P-value = 0.3051

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.808158 

 BMDL = 0.327975 
B-26 DRAFT- DO NOT CITE OR QUOTE 

 0.2

 0.4

 0.6

 0.8

 1

 0 5 10 15 20 25

Fraction Affected

dose

Quantal Linear Model with 0.95 Confidence Level

14:57 10/06 2008

BMDLBMD

 

Quantal Linear

==================================================================== 

 Quantal Linear Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpE4.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpE4.plt 

 Mon Oct 06 14:57:14 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.253086 

 Slope = 0.127782 

 Power = 1 Specified 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-27 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -Power 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.31 

 Slope -0.31 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.235057 0.0449515 0.146954 0.323161 

 Slope 0.131633 0.019868 0.0926927 0.170574 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -104.199 2 2.36383 2 0.3067 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.397 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2351 18.805 20.000 80 0.315 

 4.4000 0.5714 27.425 23.000 48 -1.291 

 10.8000 0.8154 39.139 41.000 48 0.692 

 25.0000 0.9715 46.633 47.000 48 0.318 

 Chi^2 = 2.35 d.f. = 2 P-value = 0.3095

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.389668 

 BMDL = 0.306761 
B-28 DRAFT- DO NOT CITE OR QUOTE 

SD Female Rats: Nonneoplastic forestomach lesions (AN in blood) 

 0.2

 0.4

 0.6

 0.8

 1

 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

15:59 10/06 2008

BMDL BMD

 

Gamma Multi-Hit

 ==================================================================== 

 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpF1.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpF1.plt 

 Mon Oct 06 15:59:50 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response]= background+(1-background)*CumGamma[slope*dose,power], 

 where CumGamma(.) is the cummulative Gamma distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.253086 
B-29 DRAFT- DO NOT CITE OR QUOTE 

 Slope = 28.0854 

 Power = 1.40734 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Slope Power 

Background 1 0.12 0.24 

 Slope 0.12 1 0.94 

 Power 0.24 0.94 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.24677 0.0475578 0.153558 0.339981 

 Slope 32.9782 13.6708 6.18402 59.7725 

 Power 1.45925 0.592225 0.298512 2.61999 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.482 3 0.931283 1 0.3345 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.965 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2468 19.742 20.000 80 0.067 

 0.0237 0.5082 24.395 23.000 48 -0.403 

 0.0618 0.8175 39.238 41.000 48 0.658 

 0.1560 0.9886 47.454 47.000 48 -0.617 

 Chi^2 = 0.98 d.f. = 1 P-value = 0.3220

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00495567 

 BMDL = 0.00183293 
B-30 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

Logistic Model with 0.95 Confidence Level

16:01 10/06 2008

BMDL BMD

 

Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpF2.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpF2.plt 

 Mon Oct 06 16:01:31 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = 1/[1+EXP(-intercept-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 background = 0 Specified 

 intercept = -0.712868 

 slope = 28.3794 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-31 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.65 

 slope -0.65 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -1.0292 0.221998 -1.46431 -0.594092 

 slope 40.4482 6.53178 27.6462 53.2503 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -104.001 2 1.9683 2 0.3738 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.002 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2632 21.059 20.000 80 -0.269 

 0.0237 0.4824 23.153 23.000 48 -0.044 

 0.0618 0.8131 39.030 41.000 48 0.729 

 0.1560 0.9949 47.757 47.000 48 -1.539 

 Chi^2 = 2.98 d.f. = 2 P-value = 0.2258

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00450626 

 BMDL = 0.00363943 
B-32 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

16:03 10/06 2008

BMDL BMD

 

Log-Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpF3.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpF3.plt 

 Mon Oct 06 16:03:04 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial Parameter Values 

 background = 0.25 

 intercept = 7.87595 

 slope = 2.32252 
B-33 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 background intercept slope 

background 1 0.11 0.2 

 intercept 0.11 1 0.98 

 slope 0.2 0.98 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.249911 * * * 

 intercept 7.9009 * * * 

 slope 2.32966 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.017 3 0.000533199 1 0.9816 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.034 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2499 19.993 20.000 80 0.002 

 0.0237 0.4797 23.025 23.000 48 -0.007 

 0.0618 0.8535 40.966 41.000 48 0.014 

 0.1560 0.9795 47.017 47.000 48 -0.017 

 Chi^2 = 0.00 d.f. = 1 P-value = 0.9816

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00951077 

 BMDL = 0.00435683 
B-34 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

LogProbit Model with 0.95 Confidence Level

16:04 10/06 2008

BMDL BMD

 

LogProbit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpF5.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpF5.plt 

 Mon Oct 06 16:04:48 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = Background 

 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial (and Specified) Parameter Values 
B-35 DRAFT- DO NOT CITE OR QUOTE 

 background = 0.25 

 intercept = 4.35171 

 slope = 1.28667 

 Asymptotic Correlation Matrix of Parameter Estimates 

 background intercept slope 

background 1 0.12 0.21 

 intercept 0.12 1 0.97 

 slope 0.21 0.97 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.248635 0.0479558 0.154644 0.342627 

 intercept 4.47618 0.818254 2.87243 6.07993 

 slope 1.32091 0.267134 0.797338 1.84448 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.09 3 0.14675 1 0.7017 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.18 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2486 19.891 20.000 80 0.028 

 0.0237 0.4892 23.484 23.000 48 -0.140 

 0.0618 0.8406 40.348 41.000 48 0.257 

 0.1560 0.9838 47.222 47.000 48 -0.253 

 Chi^2 = 0.15 d.f. = 1 P-value = 0.6982

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00971634 

 BMDL = 0.00488108 
B-36 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

16:06 10/06 2008

BMDLBMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpF7.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpF7.plt 

 Mon Oct 06 16:06:24 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-37 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.2349 

 Beta(1) = 23.4597 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.46 

 Beta(1) -0.46 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.237678 * * * 

 Beta(1) 22.7713 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.895 2 1.75601 2 0.4156 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 211.789 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2377 19.014 20.000 80 0.259 

 0.0237 0.5556 26.670 23.000 48 -1.066 

 0.0618 0.8134 39.042 41.000 48 0.725 

 0.1560 0.9782 46.951 47.000 48 0.048 

 Chi^2 = 1.73 d.f. = 2 P-value = 0.4207

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00225254 

 BMDL = 0.00176165 

 BMDU = 0.00294313 

Taken together, (0.00176165, 0.00294313) is a 90 % two-sided confidence 

interval for the BMD 
B-38 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

Weibull Model with 0.95 Confidence Level

16:08 10/06 2008

BMDL BMD

 

Weibull

==================================================================== 

 Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpF9.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpF9.plt 

 Mon Oct 06 16:08:23 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.253086 

 Slope = 24.7803 

 Power = 1.10265 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-39 DRAFT- DO NOT CITE OR QUOTE 

 Background Slope Power 

Background 1 0.14 0.23 

 Slope 0.14 1 0.97 

 Power 0.23 0.97 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.244833 0.0470971 0.152525 0.337142 

 Slope 36.5794 23.8993 -10.2624 83.4211 

 Power 1.17393 0.234182 0.71494 1.63291 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.595 3 1.15727 1 0.282 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 213.191 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2448 19.587 20.000 80 0.107 

 0.0237 0.5195 24.938 23.000 48 -0.560 

 0.0618 0.8125 38.998 41.000 48 0.740 

 0.1560 0.9879 47.417 47.000 48 -0.550 

 Chi^2 = 1.18 d.f. = 1 P-value = 0.2783

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00371148 

 BMDL = 0.00181169 
B-40 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

Quantal Linear Model with 0.95 Confidence Level

16:10 10/06 2008

BMDLBMD

 

Quantal Linear

 ==================================================================== 

 Quantal Linear Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpFA.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpFA.plt 

 Mon Oct 06 16:10:19 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.253086 

 Slope = 20.4779 

 Power = 1 Specified 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-41 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -Power 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.31 

 Slope -0.31 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.237678 0.0452051 0.149078 0.326278 

 Slope 22.7713 3.5337 15.8454 29.6972 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.895 2 1.75601 2 0.4156 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 211.789 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2377 19.014 20.000 80 0.259 

 0.0237 0.5556 26.670 23.000 48 -1.066 

 0.0618 0.8134 39.042 41.000 48 0.725 

 0.1560 0.9782 46.951 47.000 48 0.048 

 Chi^2 = 1.73 d.f. = 2 P-value = 0.4207

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00225254 

 BMDL = 0.00176165 
B-42 DRAFT- DO NOT CITE OR QUOTE 

SD Female Rats: Nonneoplastic forestomach lesions (CEO in blood) 

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 0 0.002 0.004 0.006 0.008 0.01

Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

09:34 10/07 2008

BMDL BMD

 

Gamma Multi-Hit

 ==================================================================== 

 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp1E.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp1E.plt 

 Tue Oct 07 09:34:01 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response]= background+(1-background)*CumGamma[slope*dose,power], 

 where CumGamma(.) is the cummulative Gamma distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.253086 
B-43 DRAFT- DO NOT CITE OR QUOTE 

 Slope = 550.799 

 Power = 2.0706 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Slope Power 

Background 1 0.15 0.26 

 Slope 0.15 1 0.96 

 Power 0.26 0.96 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.24778 0.0477681 0.154157 0.341404 

 Slope 600.839 241.065 128.36 1073.32 

 Power 2.07213 0.851839 0.402552 3.7417 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.226 3 0.419043 1 0.5174 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.453 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2478 19.822 20.000 80 0.046 

 0.0021 0.4972 23.867 23.000 48 -0.250 

 0.0049 0.8304 39.860 41.000 48 0.438 

 0.0101 0.9863 47.341 47.000 48 -0.423 

 Chi^2 = 0.44 d.f. = 1 P-value = 0.5092

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000640233 

 BMDL = 0.000173836 
B-44 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

Logistic Model with 0.95 Confidence Level

09:32 10/07 2008

BMDL BMD

 

Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp110.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp110.plt 

 Mon Nov 10 10:51:57 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = 1/[1+EXP(-intercept-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 background = 0 Specified 

 intercept = -0.929208 

 slope = 452.992 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-45 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.66 

 slope -0.66 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -1.11487 0.227873 -1.56149 -0.668246 

 slope 547.334 80.7582 389.05 705.617 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.359 2 0.684912 2 0.71 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 210.718 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2470 19.757 20.000 80 0.063 

 0.0021 0.5045 24.217 23.000 48 -0.351 

 0.0049 0.8250 39.600 41.000 48 0.532 

 0.0101 0.9880 47.425 47.000 48 -0.565 

 Chi^2 = 0.73 d.f. = 2 P-value = 0.6946

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000352967 

 BMDL = 0.000287581 
B-46 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

09:30 10/07 2008

BMDL BMD

 

Log-Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp16.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp16.plt 

 Tue Oct 07 09:30:55 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial Parameter Values 

 background = 0.25 

 intercept = 16.1818 

 slope = 2.75711 
B-47 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 background intercept slope 

background 1 0.17 0.21 

 intercept 0.17 1 0.99 

 slope 0.21 0.99 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.250617 * * * 

 intercept 15.839 * * * 

 slope 2.69969 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.03 3 0.027282 1 0.8688 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.061 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2506 20.049 20.000 80 -0.013 

 0.0021 0.4757 22.833 23.000 48 0.048 

 0.0049 0.8592 41.243 41.000 48 -0.101 

 0.0101 0.9766 46.875 47.000 48 0.119 

 Chi^2 = 0.03 d.f. = 1 P-value = 0.8699

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000951374 

 BMDL = 0.000486765 
B-48 DRAFT- DO NOT CITE OR QUOTE 

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 0 0.002 0.004 0.006 0.008 0.01

Fraction Affected

dose

Probit Model with 0.95 Confidence Level

09:47 10/07 2008

BMDL BMD

 

Probit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp21.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp21.plt 

 Tue Oct 07 09:47:22 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = CumNorm(Intercept+Slope*Dose), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 background = 0 Specified 

 intercept = -0.580731 

 slope = 266.006 
B-49 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.65 

 slope -0.65 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -0.645576 0.132116 -0.904519 -0.386633 

 slope 306.891 41.902 224.765 389.018 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.929 2 1.82488 2 0.4015 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 211.858 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2593 20.742 20.000 80 -0.189 

 0.0021 0.4959 23.803 23.000 48 -0.232 

 0.0049 0.8021 38.499 41.000 48 0.906 

 0.0101 0.9929 47.661 47.000 48 -1.139 

 Chi^2 = 2.21 d.f. = 2 P-value = 0.3315

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000360199 

 BMDL = 0.000300191 
B-50 DRAFT- DO NOT CITE OR QUOTE 

 0.2

 0.4

 0.6

 0.8

 1

 0 0.002 0.004 0.006 0.008 0.01

Fraction Affected

dose

LogProbit Model with 0.95 Confidence Level

09:38 10/07 2008

BMDL BMD

 

LogProbit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp1F.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp1F.plt 

 Tue Oct 07 09:38:17 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = Background 

 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 
B-51 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial (and Specified) Parameter Values 

 background = 0.25 

 intercept = 8.97119 

 slope = 1.53079 

 Asymptotic Correlation Matrix of Parameter Estimates 

 background intercept slope 

background 1 0.18 0.22 

 intercept 0.18 1 0.99 

 slope 0.22 0.99 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.249403 0.0481401 0.15505 0.343756 

 intercept 9.07823 1.71894 5.70916 12.4473 

 slope 1.54835 0.310846 0.939107 2.1576 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -103.017 4 

 Fitted model -103.031 3 0.0292544 1 0.8642 

 Reduced model -152.026 1 98.0188 3 <.0001 

 AIC: 212.063 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.2494 19.952 20.000 80 0.012 

 0.0021 0.4834 23.203 23.000 48 -0.059 

 0.0049 0.8482 40.715 41.000 48 0.115 

 0.0101 0.9814 47.106 47.000 48 -0.113 

 Chi^2 = 0.03 d.f. = 1 P-value = 0.8634

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000982443 

 BMDL = 0.000515017 
B-52 DRAFT- DO NOT CITE OR QUOTE 

 

Table B-4. Summary of the BMD modeling results based on the incidence of 

forestomach lesions (hyperplasia or hyperkeratosis) in male and female F344 

rats exposed to AN in drinking water for 2 years 

Sex Endpoint Dose metric Selected model(s)a

χ2

p-value AIC BMDL10

b

 BMDL05

b

gamma (3) 0.32 193.27 1.51 × 10-1 9.97 × 10-2 Estimated 

administered 

dose 

(mg/kg-d) 

two-stage multistage 

(3) 0.14 194.76 1.40 × 10-1 8.02 × 10-2

gamma (3) 0.32 193.27 8.14 × 10-4 5.39 × 10-4 Predicted AN 

in blood 

(mg/L) 

two-stage multistage 

(3) 0.14 194.77 7.56 × 10-4 4.34 × 10-4

gamma (3) 0.32 193.27 7.65 × 10-5 5.06 × 10-5

Male Forestomach 

lesions 

Predicted CEO 

in blood 

(mg/L) 

two-stage multistage 

(3) 0.14 194.76 7.10 × 10-5 4.07 × 10-5

logistic (3) 0.32 141.06 2.31 × 10-1 1.54 × 10-1

two-stage multistage 

(3) 0.39 140.80 2.09 × 10-1 1.17 × 10-1

Estimated 

administered 

dose 

(mg/kg-d) probit (3) 0.26 141.38 2.18 × 10-1 1.40 × 10-1

logistic (3) 0.32 141.06 1.11 × 10-3 7.34 × 10-4

two-stage multistage 

(3) 0.39 140.80 9.97 × 10-4 5.58 × 10-4

Predicted AN 

in blood 

(mg/L) 

probit (3) 0.26 141.38 1.04 × 10-3 6.69 × 10-4

logistic (3) 0.32 141.07 1.02 × 10-4 6.78 × 10-5

two-stage multistage 

(3) 0.39 140.81 9.23 × 10-5 5.17 × 10-5

Female Forestomach 

lesions 

Predicted CEO 

in blood 

(mg/L) 

probit (3) 0.26 141.40 9.63 × 10-5 6.19 × 10-5

aAll dichotomous models in EPA’s BMDS (version 2.0) were fit to the incidence of forestomach lesions 

(hyperplasia or hyperkeratosis) in F344 rats using the data presented in Table B-1. For BMD modeling, three 

different dose metrics were employed: (1) administered animal dose (estimated) expressed in mg/kg-d, (2) AN in 

blood (predicted) expressed in mg/L, and (3) CEO in blood (predicted) expressed in mg/L. Adequate fit of a model 

was achieved if the χ

2

 goodness-of-fit statistic yielded a p-value > 0.1. The numbers in parentheses indicate the 

number of dose groups dropped in order to obtain an adequate fit, starting with the highest dose group. Of those 

models exhibiting adequate fit, the selected model was the model with the lowest AIC value, and is indicated in 

bold in the table. 

bBMDL10 and BMDL05 estimates were derived from the selected model. If more than one model shared the lowest 

AIC, the mean BMDL10 and BMDL05 were calculated, as per the EPA’s Benchmark Dose Technical Guidance 

Document (U.S. EPA, 2000b). 

Sources: Johannsen and Levinskas (2002b); Biodynamics (1980c). 
B-53 DRAFT- DO NOT CITE OR QUOTE 

F344 Male Rats: Forestomach lesions (administered dose) 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0.35

 0 0.05 0.1 0.15 0.2 0.25

Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

14:10 10/07 2008

BMDL BMD

 

Gamma Multi-Hit

==================================================================== 

 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp104.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp104.plt 

 Tue Oct 07 14:10:45 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response]= background+(1-background)*CumGamma[slope*dose,power], 

 where CumGamma(.) is the cummulative Gamma distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.071875 
B-54 DRAFT- DO NOT CITE OR QUOTE 

 Slope = 5.59733 

 Power = 2.91574 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Power 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.24 

 Slope -0.24 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0585772 0.0151899 0.0288055 0.0883489 

 Slope 57.0862 2.86678 51.4674 62.705 

 Power 18 NA 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -94.1158 3 

 Fitted model -94.6364 2 1.04132 1 0.3075 

 Reduced model -103.388 1 18.5446 2 <.0001 

 AIC: 193.273 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0586 9.314 11.000 159 0.569 

 0.0800 0.0586 4.686 3.000 80 -0.803 

 0.2500 0.2400 18.000 18.000 75 0.000 

 Chi^2 = 0.97 d.f. = 1 P-value = 0.3250

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.203802 

 BMDL = 0.0996986 
B-55 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0.35

 0 0.05 0.1 0.15 0.2 0.25

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:12 10/07 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp105.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp105.plt 

 Tue Oct 07 14:12:49 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-56 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0438965 

 Beta(1) = 0 

 Beta(2) = 3.62384 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.49 

 Beta(2) -0.49 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0563684 * * * 

 Beta(1) 0 * * * 

 Beta(2) 3.20151 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -94.1158 3 

 Fitted model -95.381 2 2.53038 1 0.1117 

 Reduced model -103.388 1 18.5446 2 <.0001 

 AIC: 194.762 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0564 8.963 11.000 159 0.701 

 0.0800 0.0755 6.041 3.000 80 -1.287 

 0.2500 0.2275 17.062 18.000 75 0.258 

 Chi^2 = 2.21 d.f. = 1 P-value = 0.1368

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.126576 

 BMDL = 0.0802271 

 BMDU = 0.173506 

Taken together, (0.0802271, 0.173506) is a 90 % two-sided confidence 

interval for the BMD 
B-57 DRAFT- DO NOT CITE OR QUOTE 

F344 Male Rats: Forestomach lesions (AN in blood)) 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0.35

 0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014

Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

14:46 10/07 2008

BMDL BMD

 

Gamma Multi-Hit

 ==================================================================== 

 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp107.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp107.plt 

 Tue Oct 07 14:46:28 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response]= background+(1-background)*CumGamma[slope*dose,power], 

 where CumGamma(.) is the cummulative Gamma distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.071875 

 Slope = 1039.5 
B-58 DRAFT- DO NOT CITE OR QUOTE 

 Power = 2.92132 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Power 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.24 

 Slope -0.24 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0585772 0.01519 0.0288053 0.088349 

 Slope 10571.5 530.886 9531.01 11612 

 Power 18 NA 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -94.1158 3 

 Fitted model -94.6364 2 1.04133 1 0.3075 

 Reduced model -103.388 1 18.5446 2 <.0001 

 AIC: 193.273 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0586 9.314 11.000 159 0.569 

 0.0004 0.0586 4.686 3.000 80 -0.803 

 0.0014 0.2400 18.000 18.000 75 0.000 

 Chi^2 = 0.97 d.f. = 1 P-value = 0.3250

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00110053 

 BMDL = 0.00053936 
B-59 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0.35

 0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:54 10/07 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp10C.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp10C.plt 

 Tue Oct 07 14:54:25 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-60 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.043854 

 Beta(1) = 0 

 Beta(2) = 124287 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.49 

 Beta(2) -0.49 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0563637 * * * 

 Beta(1) 0 * * * 

 Beta(2) 109747 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -94.1158 3 

 Fitted model -95.3848 2 2.53803 1 0.1111 

 Reduced model -103.388 1 18.5446 2 <.0001 

 AIC: 194.77 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0564 8.962 11.000 159 0.701 

 0.0004 0.0756 6.047 3.000 80 -1.289 

 0.0014 0.2274 17.057 18.000 75 0.260 

 Chi^2 = 2.22 d.f. = 1 P-value = 0.1363

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000683652 

 BMDL = 0.000433678 

 BMDU = 0.000937168 

Taken together, (0.000433678, 0.000937168) is a 90 % two-sided confidence 

interval for the BMD 
B-61 DRAFT- DO NOT CITE OR QUOTE 

F344 Male Rats: Forestomach lesions (CEO in blood) 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0.35

 0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012

Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

16:32 10/07 2008

BMDL BMD

 

Gamma Multi-Hit

 ==================================================================== 

 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp115.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp115.plt 

 Tue Oct 07 16:32:49 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response]= background+(1-background)*CumGamma[slope*dose,power], 

 where CumGamma(.) is the cummulative Gamma distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.071875 
B-62 DRAFT- DO NOT CITE OR QUOTE 

 Slope = 11005 

 Power = 2.91337 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Power 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.24 

 Slope -0.24 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0585772 0.0151899 0.0288055 0.0883489 

 Slope 112374 5643.28 101314 123435 

 Power 18 NA 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -94.1158 3 

 Fitted model -94.6364 2 1.04132 1 0.3075 

 Reduced model -103.388 1 18.5446 2 <.0001 

 AIC: 193.273 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0586 9.314 11.000 159 0.569 

 0.0000 0.0586 4.686 3.000 80 -0.803 

 0.0001 0.2400 18.000 18.000 75 0.000 

 Chi^2 = 0.97 d.f. = 1 P-value = 0.3250

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000103532 

 BMDL = 5.06073e-005 
B-63 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0.35

 0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

16:39 10/07 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp11A.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp11A.plt 

 Tue Oct 07 16:39:04 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-64 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0439146 

 Beta(1) = 0 

 Beta(2) = 1.40418e+007 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.49 

 Beta(2) -0.49 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0563704 * * * 

 Beta(1) 0 * * * 

 Beta(2) 1.2408e+007 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -94.1158 3 

 Fitted model -95.3793 2 2.52713 1 0.1119 

 Reduced model -103.388 1 18.5446 2 <.0001 

 AIC: 194.759 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0564 8.963 11.000 159 0.700 

 0.0000 0.0755 6.038 3.000 80 -1.286 

 0.0001 0.2275 17.064 18.000 75 0.258 

 Chi^2 = 2.21 d.f. = 1 P-value = 0.1371

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 6.42953e-005 

 BMDL = 4.07373e-005 

 BMDU = 8.81314e-005 

Taken together, (4.07373e-005, 8.81314e-005) is a 90 % two-sided confidence interval for the 

BMD 
B-65 DRAFT- DO NOT CITE OR QUOTE 

F344 Female Rats: Forestomach lesions (administered dose) 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Fraction Affected

dose

Logistic Model with 0.95 Confidence Level

13:49 10/08 2008

BMDL BMD

 

Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpA62.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpA62.plt 

 Wed Oct 08 13:49:00 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = 1/[1+EXP(-intercept-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 background = 0 Specified 

 intercept = -3.79894 

 slope = 6.38252 
B-66 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.88 

 slope -0.88 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -3.92594 0.477082 -4.86101 -2.99088 

 slope 6.94669 1.60094 3.80891 10.0845 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.9873 3 

 Fitted model -68.5288 2 1.08303 1 0.298 

 Reduced model -79.8392 1 23.7038 2 <.0001 

 AIC: 141.058 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0193 3.017 4.000 156 0.571 

 0.1200 0.0434 3.474 2.000 80 -0.809 

 0.3600 0.1939 15.509 16.000 80 0.139 

 Chi^2 = 1.00 d.f. = 1 P-value = 0.3175

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.189157 

 BMDL = 0.153543 
B-67 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

13:58 10/08 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpA65.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpA65.plt 

 Wed Oct 08 13:58:05 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-68 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0147377 

 Beta(1) = 0 

 Beta(2) = 1.59649 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.51 

 Beta(2) -0.51 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0216322 * * * 

 Beta(1) 0 * * * 

 Beta(2) 1.47012 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.9873 3 

 Fitted model -68.401 2 0.827463 1 0.363 

 Reduced model -79.8392 1 23.7038 2 <.0001 

 AIC: 140.802 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0216 3.375 4.000 156 0.344 

 0.1200 0.0421 3.370 2.000 80 -0.763 

 0.3600 0.1914 15.308 16.000 80 0.197 

 Chi^2 = 0.74 d.f. = 1 P-value = 0.3901

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.18679 

 BMDL = 0.116832 

 BMDU = 0.243753 

Taken together, (0.116832, 0.243753) is a 90 % two-sided confidence 

interval for the BMD 
B-69 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

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 0.25

 0.3

 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Fraction Affected

dose

Probit Model with 0.95 Confidence Level

14:01 10/08 2008

BMDL BMD

 

Probit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpA66.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpA66.plt 

 Wed Oct 08 14:01:52 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = CumNorm(Intercept+Slope*Dose), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 background = 0 Specified 

 intercept = -2.03888 

 slope = 3.08079 
B-70 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.81 

 slope -0.81 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -2.0746 0.1976 -2.46189 -1.68732 

 slope 3.33316 0.739981 1.88282 4.78349 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.9873 3 

 Fitted model -68.6922 2 1.40991 1 0.2351 

 Reduced model -79.8392 1 23.7038 2 <.0001 

 AIC: 141.384 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0190 2.966 4.000 156 0.606 

 0.1200 0.0470 3.760 2.000 80 -0.930 

 0.3600 0.1909 15.270 16.000 80 0.208 

 Chi^2 = 1.28 d.f. = 1 P-value = 0.2588

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.175274 

 BMDL = 0.140136 
B-71 DRAFT- DO NOT CITE OR QUOTE 

F344 Female Rats: Forestomach lesions (AN in blood)

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018

Fraction Affected

dose

Logistic Model with 0.95 Confidence Level

16:01 10/08 2008

BMDL BMD

 

Logistic

==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpA6F.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpA6F.plt 

 Wed Oct 08 16:01:43 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = 1/[1+EXP(-intercept-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 background = 0 Specified 

 intercept = -3.79881 
B-72 DRAFT- DO NOT CITE OR QUOTE 

 slope = 1335.91 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.88 

 slope -0.88 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -3.92577 0.477035 -4.86074 -2.9908 

 slope 1453.89 335.047 797.213 2110.57 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.9873 3 

 Fitted model -68.5281 2 1.0816 1 0.2983 

 Reduced model -79.8392 1 23.7038 2 <.0001 

 AIC: 141.056 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0193 3.018 4.000 156 0.571 

 0.0006 0.0434 3.473 2.000 80 -0.808 

 0.0017 0.1939 15.509 16.000 80 0.139 

 Chi^2 = 1.00 d.f. = 1 P-value = 0.3178

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00090371 

 BMDL = 0.000733555 
B-73 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

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 0.2

 0.25

 0.3

 0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

16:07 10/08 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpA72.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpA72.plt 

 Wed Oct 08 16:07:08 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-74 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0147497 

 Beta(1) = 0 

 Beta(2) = 69935.2 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.51 

 Beta(2) -0.51 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.021634 * * * 

 Beta(1) 0 * * * 

 Beta(2) 64407.8 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.9873 3 

 Fitted model -68.4002 2 0.825863 1 0.3635 

 Reduced model -79.8392 1 23.7038 2 <.0001 

 AIC: 140.8 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0216 3.375 4.000 156 0.344 

 0.0006 0.0421 3.369 2.000 80 -0.762 

 0.0017 0.1914 15.310 16.000 80 0.196 

 Chi^2 = 0.74 d.f. = 1 P-value = 0.3905

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000892403 

 BMDL = 0.000558013 

 BMDU = 0.00116455 

Taken together, (0.000558013, 0.00116455) is a 90 % two-sided confidence 

interval for the BMD 
B-75 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

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 0.3

 0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018

Fraction Affected

dose

Probit Model with 0.95 Confidence Level

16:11 10/08 2008

BMDL BMD

 

Probit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpA73.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpA73.plt 

 Wed Oct 08 16:11:23 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = CumNorm(Intercept+Slope*Dose), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 background = 0 Specified 

 intercept = -2.03885 

 slope = 644.864 
B-76 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.81 

 slope -0.81 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -2.07454 0.197583 -2.4618 -1.68729 

 slope 697.628 154.868 394.091 1001.16 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.9873 3 

 Fitted model -68.6913 2 1.40812 1 0.2354 

 Reduced model -79.8392 1 23.7038 2 <.0001 

 AIC: 141.383 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0190 2.966 4.000 156 0.606 

 0.0006 0.0470 3.759 2.000 80 -0.929 

 0.0017 0.1909 15.271 16.000 80 0.207 

 Chi^2 = 1.27 d.f. = 1 P-value = 0.2590

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000837374 

 BMDL = 0.000669495 
B-77 DRAFT- DO NOT CITE OR QUOTE 

F344 Female Rats: Forestomach lesions (CEO in blood) 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012 0.00014 0.00016

Fraction Affected

dose

Logistic Model with 0.95 Confidence Level

09:45 10/09 2008

BMDL BMD

 

Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp10.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp10.plt 

 Thu Oct 09 09:45:26 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = 1/[1+EXP(-intercept-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 background = 0 Specified 

 intercept = -3.79973 
B-78 DRAFT- DO NOT CITE OR QUOTE 

 slope = 14448.5 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.88 

 slope -0.88 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -3.92703 0.4774 -4.86272 -2.99135 

 slope 15733 3627.17 8623.9 22842.1 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.9873 3 

 Fitted model -68.5334 2 1.09233 1 0.296 

 Reduced model -79.8392 1 23.7038 2 <.0001 

 AIC: 141.067 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0193 3.014 4.000 156 0.573 

 0.0001 0.0435 3.482 2.000 80 -0.812 

 0.0002 0.1938 15.504 16.000 80 0.140 

 Chi^2 = 1.01 d.f. = 1 P-value = 0.3155

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 8.35696e-005 

 BMDL = 6.78392e-005 
B-79 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012 0.00014 0.00016

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:46 10/09 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpFC.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpFC.plt 

 Thu Oct 09 14:46:41 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-80 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0146597 

 Beta(1) = 0 

 Beta(2) = 8.18648e+006 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.51 

 Beta(2) -0.51 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0216202 * * * 

 Beta(1) 0 * * * 

 Beta(2) 7.53198e+006 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.9873 3 

 Fitted model -68.4062 2 0.837895 1 0.36 

 Reduced model -79.8392 1 23.7038 2 <.0001 

 AIC: 140.812 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0216 3.373 4.000 156 0.345 

 0.0001 0.0423 3.380 2.000 80 -0.767 

 0.0002 0.1913 15.301 16.000 80 0.199 

 Chi^2 = 0.75 d.f. = 1 P-value = 0.3873

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 8.25232e-005 

 BMDL = 5.17106e-005 

 BMDU = 0.000107687 

Taken together, (5.17106e-005, 0.000107687) is a 90 % two-sided confidence interval for the 

BMD 
B-81 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012 0.00014 0.00016

Fraction Affected

dose

Probit Model with 0.95 Confidence Level

14:50 10/09 2008

BMDL BMD

 

Probit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmpFD.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmpFD.plt 

 Thu Oct 09 14:50:46 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = CumNorm(Intercept+Slope*Dose), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 background = 0 Specified 

 intercept = -2.03906 

 slope = 6972.11 
B-82 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.81 

 slope -0.81 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -2.075 0.197714 -2.46251 -1.68749 

 slope 7547.46 1676.24 4262.09 10832.8 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -67.9873 3 

 Fitted model -68.6981 2 1.42158 1 0.2331 

 Reduced model -79.8392 1 23.7038 2 <.0001 

 AIC: 141.396 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0190 2.963 4.000 156 0.608 

 0.0001 0.0471 3.769 2.000 80 -0.934 

 0.0002 0.1908 15.264 16.000 80 0.209 

 Chi^2 = 1.29 d.f. = 1 P-value = 0.2569

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 7.74403e-005 

 BMDL = 6.19187e-005 
B-83 DRAFT- DO NOT CITE OR QUOTE 

 

Table B-5. Summary of the BMD modeling results based on the incidence of 

forestomach lesions (hyperplasia or hyperkeratosis) in male and female 

B6C3F1 mice exposed to AN via gavage for 2 years 

Sex Endpoint Dose metric Selected model(s)a χ2

p-value AIC BMDL10

b

 BMDL05

b

gamma 0.80 156.45 3.45 1.68 

logistic 0.37 158.01 6.37 3.72 

log-logistic 0.87 156.30 3.01 1.43 

probit 0.42 157.74 5.96 3.42 

log-probit 0.33 158.23 5.53 3.85 

one-stage 

multistage 0.80 156.45 3.45 1.68 

Weibull 0.80 156.45 3.45 1.68 

Male Forestomach 

lesions 

Estimated 

administered dose

(mg/kg-d) 

quantal linear 0.80 156.45 3.45 1.68 

gamma 0.74 116.17 6.24 3.04 

logistic 0.87 114.33 8.95 5.60 

log-logistic 0.75 116.17 5.98 2.83 

probit 0.90 114.28 8.51 5.19 

log-probit 0.81 114.48 8.12 5.65 

one-stage 

multistage 0.92 114.24 6.20 3.02 

Weibull 0.74 116.18 6.24 3.04 

Female Forestomach 

lesions 

Estimated 

administered dose

(mg/kg-d) 

quantal linear 0.92 114.24 6.20 3.02 

aAll dichotomous models in EPA’s BMDS (version 2.0) were fit to the incidence of forestomach lesions 

(hyperplasia or hyperkeratosis) in B6C3F1 mice using the data presented in Table B-2. For BMD modeling, animal 

dose (estimated), expressed in mg/kg-d, was employed. Adequate fit of a model was achieved if the χ

2

 goodnessof-fit statistic yielded a p-value > 0.1. Of those models exhibiting adequate fit, the selected model was the model 

with the lowest AIC value, and is indicated in bold in the table. 

bBMDL10 and BMDL05 estimates were derived from the selected model. If more than one model shared the lowest 

AIC, the mean BMDL10 and BMDL05 were calculated, as per the EPA’s Benchmark Dose Technical Guidance 

Document (U.S. EPA, 2000b). 

Source: NTP (2001).
B-84 DRAFT- DO NOT CITE OR QUOTE 

B6C3F1 Male Mice: Forestomach lesions (administered dose)

 0

 0.05

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 0.15

 0.2

 0.25

 0.3

 0.35

 0.4

 0 2 4 6 8 10 12 14

Fraction Affected

dose

Gamma Multi-Hit Model with 0.95 Confidence Level

13:51 11/14 2008

BMDL BMD

 

Gamma Multi-Hit

 ==================================================================== 

 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp111.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp111.plt 

 Fri Nov 14 13:51:24 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response]= background+(1-background)*CumGamma[slope*dose,power], 

 where CumGamma(.) is the cummulative Gamma distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.0490196 
B-85 DRAFT- DO NOT CITE OR QUOTE 

 Slope = 0.0449456 

 Power = 1.3 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Power 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.53 

 Slope -0.53 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0444165 0.025521 -0.00560381 0.0944368 

 Slope 0.0201613 0.00593774 0.00852351 0.031799 

 Power 1 NA 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.0086 4 

 Fitted model -76.2255 2 0.433714 2 0.805 

 Reduced model -82.7874 1 13.5576 3 0.003574 

 AIC: 156.451 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0444 2.221 2.000 50 -0.152 

 1.8000 0.0785 3.924 4.000 50 0.040 

 7.1000 0.1719 8.593 10.000 50 0.527 

 14.3000 0.2838 14.188 13.000 50 -0.373 

 Chi^2 = 0.44 d.f. = 2 P-value = 0.8019

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 2.54415 

 BMDL = 1.68095 
B-86 DRAFT- DO NOT CITE OR QUOTE 

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Logistic Model with 0.95 Confidence Level

14:00 11/14 2008

BMDL BMD

 

Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp113.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp113.plt 

 Fri Nov 14 14:00:33 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = 1/[1+EXP(-intercept-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 background = 0 Specified 

 intercept = -2.67373 

 slope = 0.130289 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-87 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.83 

 slope -0.83 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -2.63925 0.372305 -3.36896 -1.90955 

 slope 0.121074 0.0365284 0.04948 0.192669 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.0086 4 

 Fitted model -77.0042 2 1.99121 2 0.3695 

 Reduced model -82.7874 1 13.5576 3 0.003574 

 AIC: 158.008 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0667 3.333 2.000 50 -0.756 

 1.8000 0.0816 4.078 4.000 50 -0.040 

 7.1000 0.1443 7.217 10.000 50 1.120 

 14.3000 0.2874 14.372 13.000 50 -0.429 

 Chi^2 = 2.01 d.f. = 2 P-value = 0.3660

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 4.80697 

 BMDL = 3.72464 
B-88 DRAFT- DO NOT CITE OR QUOTE 

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Log-Logistic Model with 0.95 Confidence Level

14:04 11/14 2008

BMDL BMD

 

Log-Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp116.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp116.plt 

 Fri Nov 14 14:04:51 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial Parameter Values 

 background = 0.04 

 intercept = -3.73286 

 slope = 1 
B-89 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -slope 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 background intercept 

background 1 -0.54 

 intercept -0.54 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.0421528 * * * 

 intercept -3.76687 * * * 

 slope 1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.0086 4 

 Fitted model -76.1489 2 0.280564 2 0.8691 

 Reduced model -82.7874 1 13.5576 3 0.003574 

 AIC: 156.298 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0422 2.108 2.000 50 -0.076 

 1.8000 0.0804 4.021 4.000 50 -0.011 

 7.1000 0.1772 8.862 10.000 50 0.422 

 14.3000 0.2802 14.009 13.000 50 -0.318 

 Chi^2 = 0.28 d.f. = 2 P-value = 0.8674

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 2.27602 

 BMDL = 1.42584 
B-90 DRAFT- DO NOT CITE OR QUOTE 

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dose

Probit Model with 0.95 Confidence Level

14:27 11/14 2008

BMDL BMD

 

Probit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp124.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp124.plt 

 Fri Nov 14 14:27:57 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = CumNorm(Intercept+Slope*Dose), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 background = 0 Specified 

 intercept = -1.57644 

 slope = 0.0736548 
B-91 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.8 

 slope -0.8 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -1.52854 0.189536 -1.90002 -1.15706 

 slope 0.0679152 0.0200887 0.028542 0.107288 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.0086 4 

 Fitted model -76.8681 2 1.71884 2 0.4234 

 Reduced model -82.7874 1 13.5576 3 0.003574 

 AIC: 157.736 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0632 3.159 2.000 50 -0.674 

 1.8000 0.0798 3.991 4.000 50 0.005 

 7.1000 0.1477 7.385 10.000 50 1.042 

 14.3000 0.2886 14.432 13.000 50 -0.447 

 Chi^2 = 1.74 d.f. = 2 P-value = 0.4189

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 4.44923 

 BMDL = 3.4216 
B-92 DRAFT- DO NOT CITE OR QUOTE 

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LogProbit Model with 0.95 Confidence Level

14:16 11/14 2008

BMDL BMD

 

LogProbit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp11E.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp11E.plt 

 Fri Nov 14 14:16:36 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = Background 

 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial (and Specified) Parameter Values 
B-93 DRAFT- DO NOT CITE OR QUOTE 

 background = 0.04 

 intercept = -3.00109 

 slope = 1 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -slope 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 background intercept 

background 1 -0.53 

 intercept -0.53 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.0650367 0.0264604 0.0131753 0.116898 

 intercept -3.3131 0.219612 -3.74353 -2.88267 

 slope 1 NA 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.0086 4 

 Fitted model -77.1132 2 2.20909 2 0.3314 

 Reduced model -82.7874 1 13.5576 3 0.003574 

 AIC: 158.226 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0650 3.252 2.000 50 -0.718 

 1.8000 0.0680 3.402 4.000 50 0.336 

 7.1000 0.1473 7.367 10.000 50 1.051 

 14.3000 0.3053 15.263 13.000 50 -0.695 

 Chi^2 = 2.21 d.f. = 2 P-value = 0.3304

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 5.30287 

 BMDL = 3.84888 
B-94 DRAFT- DO NOT CITE OR QUOTE 

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Multistage Model with 0.95 Confidence Level

14:22 11/14 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp121.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp121.plt 

 Fri Nov 14 14:22:26 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-95 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0536508 

 Beta(1) = 0.018443 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.71 

 Beta(1) -0.71 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0444165 * * * 

 Beta(1) 0.0201613 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.0086 4 

 Fitted model -76.2255 2 0.433714 2 0.805 

 Reduced model -82.7874 1 13.5576 3 0.003574 

 AIC: 156.451 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0444 2.221 2.000 50 -0.152 

 1.8000 0.0785 3.924 4.000 50 0.040 

 7.1000 0.1719 8.593 10.000 50 0.527 

 14.3000 0.2838 14.188 13.000 50 -0.373 

 Chi^2 = 0.44 d.f. = 2 P-value = 0.8019

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 2.54415 

 BMDL = 1.68095 

 BMDU = 4.75191 

Taken together, (1.68095, 4.75191) is a 90 % two-sided confidence 

interval for the BMD 
B-96 DRAFT- DO NOT CITE OR QUOTE 

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Weibull Model with 0.95 Confidence Level

14:36 11/14 2008

BMDL BMD

 

Weibull

 ==================================================================== 

 Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp127.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp127.plt 

 Fri Nov 14 14:36:13 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.0490196 

 Slope = 0.0179876 

 Power = 1 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-97 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -Power 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.53 

 Slope -0.53 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0444162 0.0255203 -0.00560266 0.0944351 

 Slope 0.0201613 0.00593763 0.00852374 0.0317988 

 Power 1 NA 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.0086 4 

 Fitted model -76.2255 2 0.433714 2 0.805 

 Reduced model -82.7874 1 13.5576 3 0.003574 

 AIC: 156.451 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0444 2.221 2.000 50 -0.152 

 1.8000 0.0785 3.924 4.000 50 0.040 

 7.1000 0.1719 8.593 10.000 50 0.527 

 14.3000 0.2838 14.188 13.000 50 -0.373 

 Chi^2 = 0.44 d.f. = 2 P-value = 0.8019

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 2.54415 

 BMDL = 1.68095 
B-98 DRAFT- DO NOT CITE OR QUOTE 

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dose

Quantal Linear Model with 0.95 Confidence Level

14:42 11/14 2008

BMDL BMD

 

Quantal Linear

 ==================================================================== 

 Quantal Linear Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp12A.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp12A.plt 

 Fri Nov 14 14:42:54 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.0490196 

 Slope = 0.0179876 

 Power = 1 Specified 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-99 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -Power 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.53 

 Slope -0.53 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0444162 0.0255203 -0.00560266 0.0944351 

 Slope 0.0201613 0.00593763 0.00852374 0.0317988 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.0086 4 

 Fitted model -76.2255 2 0.433714 2 0.805 

 Reduced model -82.7874 1 13.5576 3 0.003574 

 AIC: 156.451 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0444 2.221 2.000 50 -0.152 

 1.8000 0.0785 3.924 4.000 50 0.040 

 7.1000 0.1719 8.593 10.000 50 0.527 

 14.3000 0.2838 14.188 13.000 50 -0.373 

 Chi^2 = 0.44 d.f. = 2 P-value = 0.8019

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 2.54415 

 BMDL = 1.68095 
B-100 DRAFT- DO NOT CITE OR QUOTE 

B6C3F1 Female Mice: Forestomach lesions (administered dose) 

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Gamma Multi-Hit Model with 0.95 Confidence Level

15:44 11/14 2008

BMDL BMD

 

Gamma Multi-Hit

 ==================================================================== 

 Gamma Model. (Version: 2.13; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp131.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp131.plt 

 Fri Nov 14 15:44:47 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response]= background+(1-background)*CumGamma[slope*dose,power], 

 where CumGamma(.) is the cummulative Gamma distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.0490196 

 Slope = 0.0133015 
B-101 DRAFT- DO NOT CITE OR QUOTE 

 Power = 1.18093 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Slope Power 

Background 1 0.39 0.47 

 Slope 0.39 1 0.99 

 Power 0.47 0.99 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0367793 0.0231276 -0.00854987 0.0821085 

 Slope 0.0180646 0.0405793 -0.0614694 0.0975986 

 Power 1.28374 1.22475 -1.11674 3.68421 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -55.0321 4 

 Fitted model -55.0866 3 0.109064 1 0.7412 

 Reduced model -58.1629 1 6.26165 3 0.09955 

 AIC: 116.173 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0368 1.839 2.000 50 0.121 

 1.8000 0.0468 2.342 2.000 50 -0.229 

 7.1000 0.0924 4.618 5.000 50 0.187 

 14.3000 0.1639 8.197 8.000 50 -0.075 

 Chi^2 = 0.11 d.f. = 1 P-value = 0.7429

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 6.31104 

 BMDL = 3.03872 
B-102 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

Logistic Model with 0.95 Confidence Level

15:48 11/14 2008

BMDL BMD

 

Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp134.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp134.plt 

 Fri Nov 14 15:48:45 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = 1/[1+EXP(-intercept-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 background = 0 Specified 

 intercept = -3.00612 

 slope = 0.102222 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-103 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.84 

 slope -0.84 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -3.16594 0.471287 -4.08965 -2.24224 

 slope 0.108988 0.0453905 0.0200238 0.197951 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -55.0321 4 

 Fitted model -55.1666 2 0.269 2 0.8742 

 Reduced model -58.1629 1 6.26165 3 0.09955 

 AIC: 114.333 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0405 2.023 2.000 50 -0.017 

 1.8000 0.0488 2.441 2.000 50 -0.289 

 7.1000 0.0838 4.189 5.000 50 0.414 

 14.3000 0.1669 8.347 8.000 50 -0.132 

 Chi^2 = 0.27 d.f. = 2 P-value = 0.8725

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 7.64457 

 BMDL = 5.59724 
B-104 DRAFT- DO NOT CITE OR QUOTE 

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Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

15:51 11/14 2008

BMDL BMD

 

Log-Logistic

 ==================================================================== 

 Logistic Model. (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp137.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp137.plt 

 Fri Nov 14 15:51:59 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial Parameter Values 

 background = 0.04 

 intercept = -5.35004 

 slope = 1.30201 
B-105 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 background intercept slope 

background 1 -0.53 0.46 

 intercept -0.53 1 -0.98 

 slope 0.46 -0.98 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.0366811 * * * 

 intercept -5.29891 * * * 

 slope 1.2835 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -55.0321 4 

 Fitted model -55.0846 3 0.104995 1 0.7459 

 Reduced model -58.1629 1 6.26165 3 0.09955 

 AIC: 116.169 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0367 1.834 2.000 50 0.125 

 1.8000 0.0468 2.340 2.000 50 -0.228 

 7.1000 0.0928 4.639 5.000 50 0.176 

 14.3000 0.1637 8.186 8.000 50 -0.071 

 Chi^2 = 0.10 d.f. = 1 P-value = 0.7477

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 6.26147 

 BMDL = 2.83097 
B-106 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 2 4 6 8 10 12 14

Fraction Affected

dose

Probit Model with 0.95 Confidence Level

16:05 11/14 2008

BMDL BMD

 

Probit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp140.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp140.plt 

 Fri Nov 14 16:05:36 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = CumNorm(Intercept+Slope*Dose), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is not restricted 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 background = 0 Specified 
B-107 DRAFT- DO NOT CITE OR QUOTE 

 intercept = -1.75537 

 slope = 0.0561083 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 intercept slope 

 intercept 1 -0.8 

 slope -0.8 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 intercept -1.7601 0.219358 -2.19003 -1.33017 

 slope 0.0553914 0.0228374 0.0106309 0.100152 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -55.0321 4 

 Fitted model -55.1419 2 0.219734 2 0.896 

 Reduced model -58.1629 1 6.26165 3 0.09955 

 AIC: 114.284 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0392 1.960 2.000 50 0.029 

 1.8000 0.0484 2.421 2.000 50 -0.277 

 7.1000 0.0858 4.292 5.000 50 0.357 

 14.3000 0.1665 8.326 8.000 50 -0.124 

 Chi^2 = 0.22 d.f. = 2 P-value = 0.8955

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 7.2597 

 BMDL = 5.19213 
B-108 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 2 4 6 8 10 12 14

Fraction Affected

dose

LogProbit Model with 0.95 Confidence Level

15:56 11/14 2008

BMDL BMD

 

LogProbit

 ==================================================================== 

 Probit Model. (Version: 3.1; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp13A.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp13A.plt 

 Fri Nov 14 15:56:14 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = Background 

 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 

 where CumNorm(.) is the cumulative normal distribution function 

 Dependent variable = Response 

 Independent variable = DOSE 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial (and Specified) Parameter Values 
B-109 DRAFT- DO NOT CITE OR QUOTE 

 background = 0.04 

 intercept = -3.50754 

 slope = 1 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -slope 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 background intercept 

background 1 -0.51 

 intercept -0.51 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 background 0.0436672 0.0205583 0.00337363 0.0839607 

 intercept -3.75124 0.270066 -4.28056 -3.22192 

 slope 1 NA 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -55.0321 4 

 Fitted model -55.2386 2 0.413147 2 0.8134 

 Reduced model -58.1629 1 6.26165 3 0.09955 

 AIC: 114.477 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0437 2.183 2.000 50 -0.127 

 1.8000 0.0444 2.221 2.000 50 -0.151 

 7.1000 0.0787 3.935 5.000 50 0.559 

 14.3000 0.1753 8.765 8.000 50 -0.284 

 Chi^2 = 0.43 d.f. = 2 P-value = 0.8054

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 8.21852 

 BMDL = 5.64968 
B-110 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 2 4 6 8 10 12 14

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

16:01 11/14 2008

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 3.0; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp13D.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp13D.plt 

 Fri Nov 14 16:01:58 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-111 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.032589 

 Beta(1) = 0.00986338 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.7 

 Beta(1) -0.7 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0341442 * * * 

 Beta(1) 0.00957473 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -55.0321 4 

 Fitted model -55.1226 2 0.181118 2 0.9134 

 Reduced model -58.1629 1 6.26165 3 0.09955 

 AIC: 114.245 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0341 1.707 2.000 50 0.228 

 1.8000 0.0506 2.532 2.000 50 -0.343 

 7.1000 0.0976 4.881 5.000 50 0.057 

 14.3000 0.1577 7.887 8.000 50 0.044 

 Chi^2 = 0.18 d.f. = 2 P-value = 0.9162

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 5.35715 

 BMDL = 3.01931 

 BMDU = 16.4514 

Taken together, (3.01931, 16.4514) is a 90 % two-sided confidence 

interval for the BMD 
B-112 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 2 4 6 8 10 12 14

Fraction Affected

dose

Weibull Model with 0.95 Confidence Level

16:09 11/14 2008

BMDL BMD

 

Weibull

 ==================================================================== 

 Weibull Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp143.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp143.plt 

 Fri Nov 14 16:09:11 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose^power)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Power parameter is restricted as power >=1 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.0490196 

 Slope = 0.00467913 

 Power = 1.25557 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-113 DRAFT- DO NOT CITE OR QUOTE 

 Background Slope Power 

Background 1 -0.54 0.47 

 Slope -0.54 1 -0.99 

 Power 0.47 -0.99 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0366324 0.0230239 -0.00849362 0.0817585 

 Slope 0.00530377 0.0138578 -0.021857 0.0324646 

 Power 1.23448 1.00512 -0.735513 3.20447 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -55.0321 4 

 Fitted model -55.0891 3 0.114024 1 0.7356 

 Reduced model -58.1629 1 6.26165 3 0.09955 

 AIC: 116.178 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0366 1.832 2.000 50 0.127 

 1.8000 0.0471 2.357 2.000 50 -0.238 

 7.1000 0.0924 4.620 5.000 50 0.186 

 14.3000 0.1638 8.188 8.000 50 -0.072 

 Chi^2 = 0.11 d.f. = 1 P-value = 0.7375

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 6.28482 

 BMDL = 3.03737 
B-114 DRAFT- DO NOT CITE OR QUOTE 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 2 4 6 8 10 12 14

Fraction Affected

dose

Quantal Linear Model with 0.95 Confidence Level

16:13 11/14 2008

BMDL BMD

 

Quantal Linear

 ==================================================================== 

 Quantal Linear Model using Weibull Model (Version: 2.12; Date: 05/16/2008) 

 Input Data File: C:\USEPA\BMDS2\Temp\tmp146.(d) 

 Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tmp146.plt 

 Fri Nov 14 16:13:01 2008 

 ==================================================================== 

 BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP(-slope*dose)] 

 Dependent variable = Response 

 Independent variable = DOSE 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial (and Specified) Parameter Values 

 Background = 0.0490196 

 Slope = 0.00923495 

 Power = 1 Specified 

 Asymptotic Correlation Matrix of Parameter Estimates 
B-115 DRAFT- DO NOT CITE OR QUOTE 

 ( *** The model parameter(s) -Power 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Slope 

Background 1 -0.53 

 Slope -0.53 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0341442 0.0203958 -0.00583081 0.0741193 

 Slope 0.00957473 0.00414213 0.0014563 0.0176932 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -55.0321 4 

 Fitted model -55.1226 2 0.181118 2 0.9134 

 Reduced model -58.1629 1 6.26165 3 0.09955 

 AIC: 114.245 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0341 1.707 2.000 50 0.228 

 1.8000 0.0506 2.532 2.000 50 -0.343 

 7.1000 0.0976 4.881 5.000 50 0.057 

 14.3000 0.1577 7.887 8.000 50 0.044 

 Chi^2 = 0.18 d.f. = 2 P-value = 0.9162

 Benchmark Dose Computation 

Specified effect = 0.05 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 5.35715 

 BMDL = 3.01931 
B-116 DRAFT- DO NOT CITE OR QUOTE 

APPENDIX B-2. NONCANCER INHALATION DOSE-RESPONSE ASSESSMENT 

(RfC): BMD MODELING RESULTS EMPLOYING THE INCIDENCE DATA FOR 

NONNEOPLASTIC NASAL LESIONS IN RATS EXPOSED TO AN BY INHALATION 

FOR 2 YEARS (TABLES B-6 THROUGH B-9) 

 For these modeling exercises, a BMR of 10% extra risk was selected due to the limited 

number of rats in each exposure group. BMC and BMCL refer to the model-predicted 

concentration and its lower 95% confidence limit, respectively, associated with a 10% extra risk 

for developing the lesion. 

Table B-6. Incidence data for selected nasal lesions in Sprague-Dawley rats 

exposed by inhalation to AN for 2 years

Nasal lesion Exposure level (ppm) Exposure level 

(mg/m3

) 

HEC 

(mg/m3)

a Incidence 

0 0 0 0/11 (0%) 

20 43.4 2.1 7/12 (58%) Hyperplasia of mucus- b

secreting cells in males 

80 173.6 8.5 8/10 (80%)b

0 0 0 1/11 (9%) 

20 43.4 2.1 7/10 (70%) Flattening of respiratory b

epithelium in females 

80 173.6 8.5 8/10 (80%)b

aHEC as per U.S. EPA (1994b) methods for a category 1 gas producing an upper respiratory effect. 

Sample calculation: 43.4 mg/m3 × 6h/24h × 5d/7d × RGDRET = 2.1 mg/m3, where RGDRET = 0.275 = 

[VE/SAET] rat ÷ [VE/SAET] human; VE = minute volume = 0.281 L/min rat; 13.8 L/min human; and SAET

= extrathoracic surface area = 5 cm2 rat, 200 cm2 human. 

b

Statistically significantly different from control value as reported by the authors. 

Source: Quast et al. (1980b).
B-117 DRAFT- DO NOT CITE OR QUOTE 

Table B-7. A summary of BMDS (version 1.3.2) modeling results based on 

incidence of hyperplasia of mucus-secreting cells in male Sprague-Dawley 

rats exposed to AN via inhalation for 2 years 

Model χ

2

p-valuea AIC BMC10

b

(mg/m3

)

BMCL10

c

(mg/m3)

Gamma 0.34 30.27 0.396 0.252 

Logistic 0.02 38.05 1.17 0.718 

Log-logistic 0.94 28.43 0.187 0.082 

Multistage 0.34 30.27 0.396 0.252 

Probit 0.01 37.99 1.17 0.776 

Log-probit 0.37 29.98 0.625 0.382 

Weibull 0.34 30.27 0.396 0.252 

a

χ

2

p-value from the χ

2

 test for lack of fit. Values <0.1 fail to meet conventional goodness-of-fit criteria. 

bBMC10 = BMC associated with 10% extra risk for nonneoplastic nasal lesions. 

cBMCL10 = 95% lower confidence limit on the BMC10 for nonneoplastic nasal lesions. 

Source: Quast et al. (1980b). 
B-118 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.3.2) model output for the best-fit model (i.e., log-logistic) based on 

incidence of hyperplasia of mucus-secreting cells in male Sprague-Dawley rats exposed to 

AN via inhalation for 2 years 

0

0.2

0.4

0.6

0.8

1

0 2 4 6 8

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

13:38 05/16 2007

BMDL BMD

 

Log-Logistic

 

==================================================================== 

 Logistic Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:20 $ 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\NONCANCER\INHALATION\SD_MALE_NASAL_INHALATION.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\NONCANCER\INHALATION\SD_MALE_NASAL_INHALATION.plt 

 Wed May 16 13:38:57 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Response 

 Independent variable = Dose 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 
B-119 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 background = 0 

 intercept = -0.581093 

 slope = 1 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -background -slope 

 have been estimated at a boundary point, or have been specified by the user, and 

do not appear in the correlation matrix ) 

 intercept 

 intercept 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 background 0 NA 

 intercept -0.522564 0.479706 

 slope 1 NA 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -13.1543 

 Fitted model -13.2153 0.121833 2 0.9409 

 Reduced model -22.7373 19.1659 2 <.0001 

 AIC: 28.4305 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 11 0 

 2.1000 0.5546 6.655 7 12 0.2001 

 8.5000 0.8345 8.345 8 10 -0.2931 

 Chi-square = 0.13 DF = 2 P-value = 0.9390 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.187372 

 BMDL = 0.0818673 
B-120 DRAFT- DO NOT CITE OR QUOTE 

Table B-8. A summary of BMDS (version 1.3.2) modeling results based on 

incidence of flattening of respiratory epithelium in female Sprague-Dawley 

rats exposed to AN via inhalation for 2 years 

Model χ

2

p-valuea AIC BMC10

b

(mg/m3

)

BMCL10

c

(mg/m3)

Gamma 0.08 35.78 0.419 0.245 

Logistic 0.02 38.47 1.02 0.610 

Log-logistic 0.43 33.50 0.162 0.059 

Multistage 0.08 35.78 0.419 0.245 

Probit 0.02 38.54 1.05 0.683 

Log-probit 0.08 35.53 0.616 0.340 

Weibull 0.08 35.78 0.419 0.245 

a

χ

2

p-value from the χ

2

 test for lack of fit. Values <0.1 fail to meet conventional goodness-of-fit criteria. 

bBMC10 = BMC associated with 10% extra risk for nonneoplastic nasal lesions. 

cBMCL10 = 95% lower confidence limit on the BMC10 for nonneoplastic nasal lesions. 

Source: Quast et al. (1980b). 
B-121 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.3.2) model output for the best-fit model (log-logistic) based on incidence 

of flattening of respiratory epithelium in female Sprague-Dawley rats exposed to AN via 

inhalation for 2 years 

0

0.2

0.4

0.6

0.8

1

0 2 4 6 8

Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

16:25 05/14 2007

BMDL BMD

 

Log-Logistic

 ==================================================================== 

 Logistic Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:20 $ 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\NONCANCER\SD_FEMALE_NASAL_INHALATION.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\NONCANCER\SD_FEMALE_NASAL_INHALATION.plt 

 Mon May 14 16:25:24 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 

 Dependent variable = Response 

 Independent variable = Dose 

 Slope parameter is restricted as slope >= 1 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 User has chosen the log transformed model 

 Default Initial Parameter Values 

 background = 0.0909091 

 intercept = -0.457634 

 slope = 1 
B-122 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -slope 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 background intercept 

background 1 -0.27 

 intercept -0.27 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 background 0.0938695 0.089458 

 intercept -0.374871 0.586482 

 slope 1 NA 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -14.4637 

 Fitted model -14.751 0.574692 1 0.4484 

 Reduced model -21.4714 14.0155 2 0.0009048 

 AIC: 33.502 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0939 1.033 1 11 -0.03367 

 2.1000 0.6292 6.292 7 10 0.4637 

 8.5000 0.8676 8.676 8 10 -0.6305 

 Chi-square = 0.61 DF = 1 P-value = 0.4334 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.161645 

 BMDL = 0.0593975 
B-123 DRAFT- DO NOT CITE OR QUOTE 

APPENDIX B-3. CANCER ORAL DOSE-RESPONSE ASSESSMENT: BMD DOSE 

MODELING RESULTS FOR TUMOR INCIDENCE DATA FROM RATS

CHRONICALLY EXPOSED TO AN IN DRINKING WATER 

As summarized in Section 4.6.1, AN is a multisite carcinogen in chronic oral rodent 

bioassays. Oral carcinogenicity studies of animals chronically exposed to AN include drinking 

water studies in two strains of rats, Sprague-Dawley (Johannsen and Levinskas, 2002a; Quast, 

2002; Biodynamics, 1980a; Quast et al., 1980a) and F344 (Johannsen and Levinskas, 2002b; 

Biodynamics, 1980b). In Sprague-Dawley rats, significantly increased incidences of 

forestomach, CNS, Zymbal gland, tongue, and mammary gland (females only) tumors were 

found. In F344 rats, significantly increased incidences of forestomach, CNS, Zymbal gland, and 

mammary gland (females only) tumors were found. 

 Two of these chronic drinking water studies were selected for dose-response modeling 

using the BMD approach and derivation of oral CSFs for AN. In one study by Quast (2002), 

Sprague-Dawley rats were exposed to 0, 35, 100, or 300 ppm of AN in drinking water for 

2 years. In the second study by Johannsen and Levinskas (2002b), F344 rats were exposed to 0, 

1, 3, 10, 30, or 100 ppm of AN in drinking water for 2 years. 

 In this appendix, detailed results of the dose-response modeling for each of the tumor 

sites listed above are presented (Tables B-9 though B-26). For each tumor site, first a summary 

of the dose-response data is presented, followed by a table summarizing the results of the doseresponse modeling. Finally, the standard output from EPA’s BMDS, version 1.4.1, for the 

selected dose-response model for each tumor site is presented. 

In general, the multistage model was fit to all of the data sets with the BMR set at 

0.1 (i.e., 10% extra risk). In fitting this model, successive stages of the multistage model, 

starting with stage 1 and ending with the stage equal to the number of dose groups minus one, 

were fit to the tumor incidence data at a particular site for each rat strain and sex employing the 

internal dose metrics CEO in blood and AN in blood. Then, for each dose metric, all stages of 

the multistage model that did not show a significant lack of fit (i.e., p > 0.1) were compared 

using AIC. The stage of the multistage model with the lowest AIC was selected as the best-fit 

model. For most tumor sites, the one-stage model exhibited the best fit. For data sets that 

exhibited a significant lack of fit for all stages of the multistage model, dose groups were 

dropped (starting with the highest dose group) until an adequate fit was achieved. 
B-124 DRAFT- DO NOT CITE OR QUOTE 

Sprague-Dawley Rats (Quast, 2002; Quast et al., 1980a) 

Tumor Site: Forestomach

Table B-9. Incidence of forestomach (nonglandular) tumors in SpragueDawley rats exposed to AN in drinking water for 2 years 

Predicted internal dose metrics 

Sex 

Administered 

animal dose 

(ppm in drinking 

water) 

Equivalent 

administered 

animal dosea

(mg/kg-d) 

AN-AUC in blood 

(mg/L)

CEO-AUC in blood

(mg/L)

Incidence of 

forestomach 

tumorsb

0 0 0 0 0/80 (0%) 

35 3.42 2.06 × 10-2 1.83 × 10-3 2/47 (4%) 

100 8.53 5.36 × 10-2 4.36 × 10-3 23/48 (48%)

Male 

c

300 21.2 1.46 × 10-1 9.70 × 10-3 39/48 (81%)c

0 0 0 0 1/80 (1%) 

35 4.36 2.37 × 10-2 2.07 × 10-3 1/48 (2%) 

100 10.8 6.18 × 10-2 4.87 × 10-3 12/48 (25%)c

Female 

300 25.0 1.56 × 10-1 1.01 × 10-2 30/48 (62%)c

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake. 

b

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

c

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Sources: Quast (2002); Quast et al. (1980a).

Table B-10. Summary of BMD modeling results based on incidence of 

forestomach (nonglandular) tumors in Sprague-Dawley rats exposed to AN 

in drinking water for 2 years 

Dose metric Best-fit modelaχ

2

p-valueb AIC BMD10

c

 BMDL10

d

Males 

Administered dose 2°MSe0.46 86.82 3.62 mg/kg-d 2.76 mg/kg-d 

CEO 2°MSe0.39 87.28 1.87 × 10-3 mg/L 1.44 × 10-3 mg/L 

AN 2°MSe0.54 86.45 2.26 × 10-2 mg/L 1.70 × 10-2 mg/L 

Females 

Administered dose 2°MS 0.17 145.97 7.76 mg/kg-d 4.81 mg/kg-d 

CEO 2°MS 0.52 143.50 3.29 × 10-3 mg/L 2.38 × 10-3 mg/L 

AN 2°MS 0.13 146.45 4.22 × 10-2 mg/L 2.49 × 10-2 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “2°MS” indicates a two-stage multistage model. 

b

p value from the χ

2

 goodness-of-fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 

eHighest dose dropped prior to model fitting. 
B-125 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley male rats 

employing administered dose as a dose metric 

0

0.1

0.2

0.3

0.4

0.5

0.6

0 1 2 3 4 5 6 7 8

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

15:40 01/23 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_DW.plt 

 Fri Jan 23 15:40:45 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-126 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 0 

 Beta(2) = 0.00929613 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(2) 

 Beta(2) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 0 * * * 

 Beta(2) 0.00803192 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -41.5002 3 

 Fitted model -42.4099 1 1.81939 2 0.4026 

 Reduced model -71.7704 1 60.5403 2 <.0001 

 AIC: 86.8198 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 80 0.000 

 3.4200 0.0897 4.214 2 47 -1.131 

 8.5300 0.4426 21.243 23 48 0.511 

 Chi^2 = 1.54 d.f. = 2 P-value = 0.4633
B-127 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 3.62184 

 BMDL = 2.75694 

 BMDU = 4.3186 

Taken together, (2.75694, 4.3186 ) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0362721 
B-128 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley male rats 

employing CEO in blood as an internal dose metric 

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

13:46 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_BLOOD_CEO.plt 

 Thu Sep 27 13:46:37 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-129 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 0 

 Beta(2) = 35739.1 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, and 

do not appear in the correlation matrix ) 

 Beta(2) 

 Beta(2) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 0 * * * 

 Beta(2) 30229.1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -41.5002 3 

 Fitted model -42.6376 1 2.27473 2 0.3207 

 Reduced model -71.7704 1 60.5403 2 <.0001 

 AIC: 87.2752 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 80 0.000 

 0.0018 0.0963 4.525 2 47 -1.249 

 0.0044 0.4371 20.981 23 48 0.588 

 Chi^2 = 1.90 d.f. = 2 P-value = 0.3859

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00186692 

 BMDL = 0.00143604 

 BMDU = 0.00222594 

Taken together, (0.00143604, 0.00222594) is a 90 % two-sided confidence interval for the BMD 
B-130 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley male rats 

employing AN in blood as an internal dose metric 

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.01 0.02 0.03 0.04 0.05

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

10:32 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_BLOOD_AN.plt 

 Thu Sep 27 10:32:01 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-131 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0 

 Beta(1) = 0 

 Beta(2) = 234.473 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, and 

do not appear in the correlation matrix ) 

 Beta(2) 

 Beta(2) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 0 * * * 

 Beta(2) 206.388 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -41.5002 3 

 Fitted model -42.2261 1 1.45174 2 0.4839 

 Reduced model -71.7704 1 60.5403 2 <.0001 

 AIC: 86.4522 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 80 0.000 

 0.0206 0.0839 3.941 2 47 -1.022 

 0.0536 0.4473 21.470 23 48 0.444 

 Chi^2 = 1.24 d.f. = 2 P-value = 0.5377

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0225942 

 BMDL = 0.0170019 

 BMDU = 0.0269423 

Taken together, (0.0170019, 0.0269423) is a 90 % two-sided confidence 

interval for the BMD 
B-132 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley female rats 

employing administered dose as a dose metric

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 5 10 15 20 25

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

16:14 01/23 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_DW.plt 

 Fri Jan 23 16:14:45 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-133 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 0.0138175 

 Beta(2) = 0.00104033 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) Beta(2) 

Background 1 -0.57 0.39 

 Beta(1) -0.57 1 -0.93 

 Beta(2) 0.39 -0.93 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0107986 * * * 

 Beta(1) 0.000833319 * * * 

 Beta(2) 0.00164062 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -68.9836 4 

 Fitted model -69.9834 3 1.99958 1 0.1573 

 Reduced model -110.972 1 83.9771 3 <.0001 

 AIC: 145.967 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0108 0.864 1 80 0.147 

 4.3600 0.0447 2.143 1 48 -0.799 

 10.8000 0.1904 9.139 12 48 1.052 

 25.0000 0.6525 31.321 30 48 -0.401 

 Chi^2 = 1.93 d.f. = 1 P-value = 0.1652
B-134 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 7.76379 

 BMDL = 4.81488 

 BMDU = 9.11082 

Taken together, (4.81488, 9.11082) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0207689 
B-135 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley female rats 

employing CEO in blood as an internal dose metric

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 0.002 0.004 0.006 0.008 0.01

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:24 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_BLOOD_CEO.plt 

 Thu Sep 27 14:24:06 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-136 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0 

 Beta(1) = 14.7147 

 Beta(2) = 8253.52 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.48 

 Beta(2) -0.48 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.00991437 * * * 

 Beta(1) 0 * * * 

 Beta(2) 9752.18 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -68.9836 4 

 Fitted model -69.7499 2 1.53257 2 0.4647 

 Reduced model -110.972 1 83.9771 3 <.0001 

 AIC: 143.5 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0099 0.793 1 80 0.233 

 0.0021 0.0504 2.421 1 48 -0.937 

 0.0049 0.2144 10.289 12 48 0.602 

 0.0101 0.6339 30.426 30 48 -0.128 

 Chi^2 = 1.31 d.f. = 2 P-value = 0.5192

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00328691 

 BMDL = 0.00238295 

 BMDU = 0.0037821 

Taken together, (0.00238295, 0.0037821) is a 90 % two-sided confidence 

interval for the BMD 
B-137 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley female rats 

employing AN in blood as an internal dose metric 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

10:49 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_BLOOD_AN.plt 

 Thu Sep 27 10:49:49 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-138 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 3.15264 

 Beta(2) = 20.8062 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) Beta(2) 

Background 1 -0.57 0.4 

 Beta(1) -0.57 1 -0.93 

 Beta(2) 0.4 -0.93 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0105127 * * * 

 Beta(1) 0.96299 * * * 

 Beta(2) 36.4178 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -68.9836 4 

 Fitted model -70.2231 3 2.47911 1 0.1154 

 Reduced model -110.972 1 83.9771 3 <.0001 

 AIC: 146.446 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0105 0.841 1 80 0.174 

 0.0237 0.0524 2.516 1 48 -0.982 

 0.0618 0.1887 9.060 12 48 1.085 

 0.1560 0.6490 31.154 30 48 -0.349 

 Chi^2 = 2.29 d.f. = 1 P-value = 0.1300

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0421673 

 BMDL = 0.0249138 

 BMDU = 0.055287 

Taken together, (0.0249138, 0.055287) is a 90 % two-sided confidence 

interval for the BMD 
B-139 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: CNS (Quast, 2002; Quast et al., 1980a) 

Table B-11. Incidence of CNS tumors in Sprague-Dawley rats exposed to 

AN in drinking water for 2 years 

Predicted internal dose metrics 

Sex 

Administered 

animal dose 

(ppm in drinking 

water) 

Equivalent 

administered 

animal dosea

(mg/kg-d) 

AN-AUC in blood 

(mg/L)

CEO-AUC in blood 

(mg/L)

Incidence of CNS 

tumorsb

0 0 0 0 1/80 (1%) 

35 3.42 2.06 × 10-2 1.83 × 10-3 12/47 (26%)c

100 8.53 5.36 × 10-2 4.36 × 10-3 22/48 (46%)

Male 

c

300 21.2 1.46 × 10-1 9.70 × 10-3 30/48 (62%)c

0 0 0 0 1/80 (1%) 

35 4.36 2.37 × 10-2 2.07 × 10-3 20/48 (42%)c

100 10.8 6.18 × 10-2 4.87 × 10-3 25/48 (52%)c

Female 

300 25.0 1.56 × 10-1 1.01 × 10-2 31/48 (65%)c

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water

intake. 

b

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

c

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Table B-12. Summary of BMD modeling results based on incidence of CNS 

tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Males

Administered dose 1°MS 0.16 201.38 1.84 mg/kg-d 1.48 mg/kg-d 

CEO 1°MS 0.37 199.81 8.87 × 10-4 mg/L 7.16 × 10-4 mg/L 

AN 1°MSe

 0.59 134.64 8.82 × 10-3 mg/L 6.64 × 10-3 mg/L 

Females 

Administered dose 1°MSe0.06 149.85 1.26 mg/kg-d 0.99 mg/kg-d 

CEO 1°MSe0.08 149.29 5.79 × 10-4 mg/L 4.51 × 10-4 mg/L 

AN 1°MSe0.04 150.45 7.12 × 10-3 mg/L 5.55 × 10-3 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 

eHighest dose dropped prior to model fitting. 
B-140 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley male rats employing 

administered dose as a dose metric 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 5 10 15 20

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

15:48 01/23 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_CNS_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_CNS_DW.plt 

 Fri Jan 23 15:48:14 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-141 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.108455 

 Beta(1) = 0.0435027 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.62 

 Beta(1) -0.62 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0160781 * * * 

 Beta(1) 0.0572137 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -96.9359 4 

 Fitted model -98.6909 2 3.51012 2 0.1729 

 Reduced model -134.574 1 75.2765 3 <.0001 

 AIC: 201.382 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0161 1.286 1 80 -0.254 

 3.4200 0.1909 8.974 12 47 1.123 

 8.5300 0.3960 19.010 22 48 0.882 

 21.2000 0.7075 33.958 30 48 -1.256 

 Chi^2 = 3.68 d.f. = 2 P-value = 0.1587
B-142 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1.84153 

 BMDL = 1.4836 

 BMDU = 2.34034 

Taken together, (1.4836 , 2.34034) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0674034 
B-143 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley male rats employing 

CEO in blood as an internal dose metric

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 0.002 0.004 0.006 0.008 0.01

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

09:11 09/25 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $ 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_CNS_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_CNS_BLOOD_CEO.plt 

 Tue Sep 25 09:11:57 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

-beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.0859878 

 Beta(1) = 97.0212 
B-144 DRAFT- DO NOT CITE OR QUOTE 

**** WARNING: Completion code = -3. Optimum not found. Trying new starting point  

** ** WARNING 0: Completion code = -3 trying new start  

** ** WARNING 1: Completion code = -3 trying new start  

** ** WARNING 2: Completion code = -3 trying new start  

** ** WARNING 3: Completion code = -3 trying new start  

** ** WARNING 4: Completion code = -3 trying new start  

** ** WARNING 5: Completion code = -3 trying new start  

** ** WARNING 6: Completion code = -3 trying new start  

** ** WARNING 7: Completion code = -3 trying new start  

** ** WARNING 8: Completion code = -3 trying new start  

** ** WARNING 9: Completion code = -3 trying new start**** 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.62 

 Beta(1) -0.62 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 Background 0.0146577 0.100785 

 Beta(1) 118.766 28.4627 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -96.9359 

 Fitted model -97.9055 1.93933 2 0.3792 

 Reduced model -134.574 75.2765 3 <.0001 

 AIC: 199.811 

 Goodness of Fit 

 Dose Est._Prob. Expected Observed Size Chi^2 Res. 

 ----------------------------------------------------------------------- 

i: 1 

 0.0000 0.0147 1.173 1 80 -0.149 

i: 2 

 0.0018 0.2071 9.736 12 47 0.293 

i: 3 

 0.0044 0.4129 19.820 22 48 0.187 

i: 4 

 0.0097 0.6886 33.055 30 48 -0.297 

 Chi-square = 2.01 DF = 2 P-value = 0.3669 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00088713 

 BMDL = 0.00071632 
B-145 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley male rats employing AN 

in blood as an internal dose metric 

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.01 0.02 0.03 0.04 0.05

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

10:40 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_CNS_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_CNS_BLOOD_AN.plt 

 Thu Sep 27 10:40:46 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-146 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.032766 

 Beta(1) = 11.0585 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.61 

 Beta(1) -0.61 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0130586 * * * 

 Beta(1) 11.9435 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -65.1808 3 

 Fitted model -65.3204 2 0.279194 1 0.5972 

 Reduced model -87.5704 1 44.7792 2 <.0001 

 AIC: 134.641 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0131 1.045 1 80 -0.044 

 0.0206 0.2283 10.731 12 47 0.441 

 0.0536 0.4797 23.025 22 48 -0.296 

 Chi^2 = 0.28 d.f. = 1 P-value = 0.5940

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00882158 

 BMDL = 0.00664413 

 BMDU = 0.0121508 

Taken together, (0.00664413, 0.0121508) is a 90 % two-sided confidence 

interval for the BMD 
B-147 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley female rats employing 

administered dose as a dose metric 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 2 4 6 8 10

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

16:19 01/23 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_CNS_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_CNS_DW.plt 

 Fri Jan 23 16:19:26 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-148 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.0993663 

 Beta(1) = 0.0642026 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.62 

 Beta(1) -0.62 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0141417 * * * 

 Beta(1) 0.0833707 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -71.2064 3 

 Fitted model -72.9251 2 3.43738 1 0.06374 

 Reduced model -101.108 1 59.8036 2 <.0001 

 AIC: 149.85 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0141 1.131 1 80 -0.124 

 4.3600 0.3146 15.100 20 48 1.523 

 10.8000 0.5993 28.768 25 48 -1.110 

 Chi^2 = 3.57 d.f. = 1 P-value = 0.0589
B-149 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1.26376 

 BMDL = 0.985061 

 BMDU = 1.66456 

Taken together, (0.985061, 1.66456) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.101517 
B-150 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley female rats employing 

CEO in blood as an internal dose metric

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 0.001 0.002 0.003 0.004 0.005

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

09:03 12/03 2008

BMDL BMD

 

Multistage Cancer

Linear extrapolation

==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_CNS_BLOOD_CEO.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_CNS_BLOOD_CEO.plt 

 Wed Dec 03 09:03:51 2008 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-151 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0914603 

 Beta(1) = 144.025 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.62 

 Beta(1) -0.62 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0138803 * * * 

 Beta(1) 182.002 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -71.2064 3 

 Fitted model -72.6449 2 2.87694 1 0.08986 

 Reduced model -101.108 1 59.8036 2 <.0001 

 AIC: 149.29 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0139 1.110 1 80 -0.106 

 0.0021 0.3234 15.525 20 48 1.381 

 0.0049 0.5936 28.491 25 48 -1.026 

 Chi^2 = 2.97 d.f. = 1 P-value = 0.0848

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000578899 

 BMDL = 0.000451438 

 BMDU = 0.000761804 

Taken together, (0.000451438, 0.000761804) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 221.515 
B-152 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley female rats employing 

AN in blood as an internal dose metric 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 0.01 0.02 0.03 0.04 0.05 0.06

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

09:12 12/03 2008

BMDL BMD

 

Multistage Cancer

Linear extrapolation

==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_CNS_BLOOD_AN.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_CNS_BLOOD_AN.plt 

 Wed Dec 03 09:12:32 2008 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-153 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.106975 

 Beta(1) = 11.0861 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.62 

 Beta(1) -0.62 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0144346 * * * 

 Beta(1) 14.7901 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -71.2064 3 

 Fitted model -73.2271 2 4.04128 1 0.0444 

 Reduced model -101.108 1 59.8036 2 <.0001 

 AIC: 150.454 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0144 1.155 1 80 -0.145 

 0.0237 0.3058 14.681 20 48 1.666 

 0.0618 0.6049 29.034 25 48 -1.191 

 Chi^2 = 4.22 d.f. = 1 P-value = 0.0400

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0071237 

 BMDL = 0.00554992 

 BMDU = 0.00939265 

Taken together, (0.00554992, 0.00939265) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 18.0183 
B-154 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: Zymbal Gland (Quast, 2002; Quast et al., 1980a) 

Table B-13. Incidence of Zymbal gland tumors in Sprague-Dawley rats 

exposed to AN in drinking water for 2 years 

Predicted internal dose metrics 

Sex 

Administered 

animal dose 

(ppm in drinking 

water) 

Equivalent 

administered 

animal dosea

(mg/kg-d) 

AN-AUC in blood 

(mg/L)

CEO-AUC in blood 

(mg/L)

Incidence of 

Zymbal gland 

tumorsb

0 0 0 0 3/80 (4%) 

35 3.42 2.06 × 10-2 1.83 × 10-3 4/47 (9%) 

100 8.53 5.36 × 10-2 4.36 × 10-3 3/48 (6%) 

Male 

300 21.2 1.46 × 10-1 9.70 × 10-3 16/48 (33%)c

0 0 0 0 1/80 (1%) 

35 4.36 2.37 × 10-2 2.07 × 10-3 5/48 (10%)c

100 10.8 6.18 × 10-2 4.87 × 10-3 9/48 (19%)c

Female 

300 25.0 1.56 × 10-1 1.01 × 10-2 18/48 (38%)c

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake.

b

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

c

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Table B-14. Summary of BMD modeling results based on incidence of 

Zymbal gland tumors in Sprague-Dawley rats exposed to AN in drinking 

water for 2 years

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Males 

Administered dose 2°MS 0.43 142.15 11.80 mg/kg-d 6.29 mg/kg-d 

CEO 2°MS 0.38 142.46 5.46 × 10-3 mg/L 3.15 × 10-3 mg/L 

AN 3°MS 0.28 143.58 8.94 × 10-2 mg/L 4.26 × 10-2 mg/L 

Females 

Administered dose 1°MS 0.94 156.80 5.66 mg/kg-d 4.19 mg/kg-d 

CEO 1°MS 0.95 156.77 2.40 × 10-3 mg/L 1.78 × 10-3 mg/L 

AN 1°MS 0.85 156.98 3.41 × 10-2 mg/L 2.52 × 10-2 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model, 

“2°MS” indicates a two-stage multistage model, and “3°MS” indicates a three-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-155 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats 

employing administered dose as a dose metric 

0

0.1

0.2

0.3

0.4

0.5

0 5 10 15 20

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

16:01 01/23 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_ZYMBAL_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_ZYMBAL_DW.plt 

 Fri Jan 23 16:01:39 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-156 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.042253 

 Beta(1) = 0 

 Beta(2) = 0.00079507 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.49 

 Beta(2) -0.49 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0449236 * * * 

 Beta(1) 0 * * * 

 Beta(2) 0.000756128 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -68.2481 4 

 Fitted model -69.0738 2 1.65141 2 0.4379 

 Reduced model -80.2977 1 24.0991 3 <.0001 

 AIC: 142.148 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0449 3.594 3 80 -0.321 

 3.4200 0.0533 2.507 4 47 0.969 

 8.5300 0.0960 4.610 3 48 -0.789 

 21.2000 0.3201 15.364 16 48 0.197 

 Chi^2 = 1.70 d.f. = 2 P-value = 0.4267
B-157 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 11.8043 

 BMDL = 6.28905 

 BMDU = 15.532 

Taken together, (6.28905, 15.532 ) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0159007 
B-158 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats 

employing CEO in blood as an internal dose metric

0

0.1

0.2

0.3

0.4

0.5

0 0.002 0.004 0.006 0.008 0.01

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:09 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_ZYMBAL_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_ZYMBAL_BLOOD_CEO.plt 

 Thu Sep 27 14:09:41 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.0373755 
B-159 DRAFT- DO NOT CITE OR QUOTE 

 Beta(1) = 0 

 Beta(2) = 3819.76 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.51 

 Beta(2) -0.51 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0429942 * * * 

 Beta(1) 0 * * * 

 Beta(2) 3535.6 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -68.2481 4 

 Fitted model -69.231 2 1.96583 2 0.3742 

 Reduced model -80.2977 1 24.0991 3 <.0001 

 AIC: 142.462 
B-160 DRAFT- DO NOT CITE OR QUOTE 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0430 3.440 3 80 -0.242 

 0.0018 0.0543 2.550 4 47 0.934 

 0.0044 0.1052 5.050 3 48 -0.964 

 0.0097 0.3138 15.063 16 48 0.291 

 Chi^2 = 1.94 d.f. = 2 P-value = 0.3781

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00545893 

 BMDL = 0.00315099 

 BMDU = 0.00717256 

Taken together, (0.00315099, 0.00717256) is a 90 % two-sided confidence 

interval for the BMD 
B-161 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats 

employing AN in blood as an internal dose metric

0

0.1

0.2

0.3

0.4

0.5

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

10:44 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_ZYMBAL_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_ZYMBAL_BLOOD_AN.plt 

 Thu Sep 27 10:44:18 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 4 

 Total number of specified parameters = 0 

 Degree of polynomial = 3 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.0542857 

 Beta(1) = 0.0987621 

 Beta(2) = 0 
B-162 DRAFT- DO NOT CITE OR QUOTE 

 Beta(3) = 107.536 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(2) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(1) Beta(3) 

Background 1 -0.71 0.58 

 Beta(1) -0.71 1 -0.95 

 Beta(3) 0.58 -0.95 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0460186 * * * 

 Beta(1) 0.432974 * * * 

 Beta(2) 0 * * * 

 Beta(3) 93.2629 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -68.2481 4 

 Fitted model -68.7881 3 1.07988 1 0.2987 

 Reduced model -80.2977 1 24.0991 3 <.0001 

 AIC: 143.576 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0460 3.681 3 80 -0.364 

 0.0206 0.0553 2.597 4 47 0.896 

 0.0536 0.0812 3.897 3 48 -0.474 

 0.1460 0.3301 15.843 16 48 0.048 

 Chi^2 = 1.16 d.f. = 1 P-value = 0.2812

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0894055 

 BMDL = 0.0425525 

 BMDU = 0.117269 

Taken together, (0.0425525, 0.117269) is a 90 % two-sided confidence 

interval for the BMD 
B-163 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats 

employing administered dose as a dose metric

0

0.1

0.2

0.3

0.4

0.5

0 5 10 15 20 25

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

16:28 01/23 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_DW.plt 

 Fri Jan 23 16:28:50 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-164 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0190401 

 Beta(1) = 0.0180112 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.64 

 Beta(1) -0.64 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.013388 * * * 

 Beta(1) 0.0186127 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.3334 4 

 Fitted model -76.3975 2 0.128259 2 0.9379 

 Reduced model -93.6397 1 34.6128 3 <.0001 

 AIC: 156.795 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0134 1.071 1 80 -0.069 

 4.3600 0.0903 4.334 5 48 0.335 

 10.8000 0.1931 9.266 9 48 -0.097 

 25.0000 0.3805 18.263 18 48 -0.078 

 Chi^2 = 0.13 d.f. = 2 P-value = 0.9357

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 5.66068 

 BMDL = 4.19199 

 BMDU = 8.10463 

Taken together, (4.19199, 8.10463) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.023855 
B-165 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats 

employing CEO in blood as an internal dose metric

0

0.1

0.2

0.3

0.4

0.5

0 0.002 0.004 0.006 0.008 0.01

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:43 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_BLOOD_CEO.plt

 Thu Sep 27 14:43:02 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-166 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.00883347 

 Beta(1) = 44.8786 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.65 

 Beta(1) -0.65 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0125628 * * * 

 Beta(1) 43.9052 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.3334 4 

 Fitted model -76.385 2 0.103357 2 0.9496 

 Reduced model -93.6397 1 34.6128 3 <.0001 

 AIC: 156.77 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0126 1.005 1 80 -0.005 

 0.0021 0.0983 4.721 5 48 0.135 

 0.0049 0.2026 9.727 9 48 -0.261 

 0.0101 0.3662 17.580 18 48 0.126 

 Chi^2 = 0.10 d.f. = 2 P-value = 0.9501

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00239973 

 BMDL = 0.00178178 

 BMDU = 0.00341242 

Taken together, (0.00178178, 0.00341242) is a 90 % two-sided confidence 

interval for the BMD 
B-167 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats 

employing AN in blood as an internal dose metric 

0

0.1

0.2

0.3

0.4

0.5

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

10:55 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_BLOOD_AN.plt 

 Thu Sep 27 10:55:27 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-168 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0269441 

 Beta(1) = 2.86115 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.63 

 Beta(1) -0.63 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0143198 * * * 

 Beta(1) 3.08705 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -76.3334 4 

 Fitted model -76.4902 2 0.313733 2 0.8548 

 Reduced model -93.6397 1 34.6128 3 <.0001 

 AIC: 156.98 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0143 1.146 1 80 -0.137 

 0.0237 0.0839 4.025 5 48 0.508 

 0.0618 0.1855 8.905 9 48 0.035 

 0.1560 0.3910 18.770 18 48 -0.228 

 Chi^2 = 0.33 d.f. = 2 P-value = 0.8481

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0341298 

 BMDL = 0.0251994 

 BMDU = 0.0492353 

Taken together, (0.0251994, 0.0492353) is a 90 % two-sided confidence 

interval for the BMD 
B-169 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: Tongue (Quast, 2002; Quast et al., 1980a) 

Table B-15. Incidence of tongue tumors in Sprague-Dawley rats exposed to 

AN in drinking water for 2 years 

Predicted internal dose metrics 

Sex 

Administered 

animal dose 

(ppm in drinking 

water) 

Equivalent 

administered 

animal dosea

(mg/kg-d) 

AN-AUC in blood 

(mg/L)

CEO-AUC in blood

(mg/L)

Incidence of 

tongue tumorsb

0 0 0 0 1/80 (1%) 

35 3.42 2.06 × 10-2 1.83 × 10-3 2/47 (4%) 

100 8.53 5.36 × 10-2 4.36 × 10-3 4/48 (8%) 

Male 

300 21.2 1.46 × 10-1 9.70 × 10-3 5/48 (10%)c

0 0 0 0 0/80 (0%) 

35 4.36 2.37 × 10-2 2.07 × 10-3 1/48 (2%) 

100 10.8 6.18 × 10-2 4.87 × 10-3 2/48 (4%) 

Female 

300 25.0 1.56 × 10-1 1.01 × 10-2 12/48 (25%)c

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake.

b

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

c

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Table B-16. Summary of BMD modeling results based on incidence of 

tongue tumors in Sprague-Dawley rats exposed to AN in drinking water for 

2 years 

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Males

Administered dose 1°MS 0.69 91.62 18.89 mg/kg-d 10.35 mg/kg-d 

CEO 1°MS 0.78 91.40 8.78 × 10-3 mg/L 4.90 × 10-3 mg/L 

AN 1°MS 0.62 91.83 1.29 × 10-1 mg/L 6.97 × 10-2 mg/L 

Females 

Administered dose 3°MS 0.92 84.51 15.99 mg/kg-d 10.64 mg/kg-d 

CEO 3°MS 0.88 84.59 6.70 × 10-3 mg/L 4.74 × 10-3 mg/L 

AN 3°MS 0.93 84.48 9.67 × 10-2 mg/L 6.10 × 10-2 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model and 

“3°MS” indicates a three-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-170 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for tongue tumors in Sprague-Dawley male rats employing 

administered dose as a dose metric 

0

0.05

0.1

0.15

0.2

0.25

0 5 10 15 20

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

15:53 01/23 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_TONGUE_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_TONGUE_DW.plt 

 Fri Jan 23 15:53:59 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-171 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.0269073 

 Beta(1) = 0.00434306 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.69 

 Beta(1) -0.69 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0162768 * * * 

 Beta(1) 0.00557883 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -43.4536 4 

 Fitted model -43.8112 2 0.715245 2 0.6993 

 Reduced model -46.7384 1 6.56959 3 0.08696 

 AIC: 91.6224 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0163 1.302 1 80 -0.267 

 3.4200 0.0349 1.639 2 47 0.287 

 8.5300 0.0620 2.976 4 48 0.613 

 21.2000 0.1260 6.048 5 48 -0.456 

 Chi^2 = 0.74 d.f. = 2 P-value = 0.6916
B-172 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 18.8858 

 BMDL = 10.3512 

 BMDU = 62.8005 

Taken together, (10.3512, 62.8005) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.00966069 
B-173 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for tongue tumors in Sprague-Dawley male rats employing 

CEO in blood as an internal dose metric

0

0.05

0.1

0.15

0.2

0.25

0 0.002 0.004 0.006 0.008 0.01

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:19 09/27 2007

BMDL BMD

 

Multistage

==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_TONGUE_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_TONGUE_BLOOD_CEO.plt 

 Thu Sep 27 14:19:57 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-174 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0241886 

 Beta(1) = 9.76289 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.7 

 Beta(1) -0.7 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0150764 * * * 

 Beta(1) 11.9992 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -43.4536 4 

 Fitted model -43.6998 2 0.492394 2 0.7818 

 Reduced model -46.7384 1 6.56959 3 0.08696 

 AIC: 91.3995 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0151 1.206 1 80 -0.189 

 0.0018 0.0365 1.714 2 47 0.223 

 0.0044 0.0653 3.133 4 48 0.506 

 0.0097 0.1233 5.918 5 48 -0.403 

 Chi^2 = 0.50 d.f. = 2 P-value = 0.7772

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00878063 

 BMDL = 0.00489829 

 BMDU = 0.0274259 

Taken together, (0.00489829, 0.0274259) is a 90 % two-sided confidence 

interval for the BMD 
B-175 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for tongue tumors in Sprague-Dawley male rats employing 

AN in blood as an internal dose metric 

0

0.05

0.1

0.15

0.2

0.25

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

10:47 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_TONGUE_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_MALE_TONGUE_BLOOD_AN.plt 

 Thu Sep 27 10:47:13 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-176 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0289604 

 Beta(1) = 0.615459 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.68 

 Beta(1) -0.68 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0174494 * * * 

 Beta(1) 0.814352 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -43.4536 4 

 Fitted model -43.9131 2 0.919024 2 0.6316 

 Reduced model -46.7384 1 6.56959 3 0.08696 

 AIC: 91.8261 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0174 1.396 1 80 -0.338 

 0.0206 0.0338 1.588 2 47 0.332 

 0.0536 0.0594 2.852 4 48 0.701 

 0.1460 0.1276 6.124 5 48 -0.486 

 Chi^2 = 0.95 d.f. = 2 P-value = 0.6210

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.12938 

 BMDL = 0.0696872 

 BMDU = 0.4562 

Taken together, (0.0696872, 0.4562 ) is a 90 % two-sided confidence 

interval for the BMD 
B-177 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for tongue tumors in Sprague-Dawley female rats employing 

administered dose as a dose metric 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 5 10 15 20 25

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

16:26 01/23 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_DW.plt 

 Fri Jan 23 16:26:08 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 4 

 Total number of specified parameters = 0 

 Degree of polynomial = 3 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-178 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.00365935 

 Beta(1) = 0.00218662 

 Beta(2) = 0 

 Beta(3) = 1.46642e-005 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background -Beta(2) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) Beta(3) 

 Beta(1) 1 -0.93 

 Beta(3) -0.93 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 0.00329024 * * * 

 Beta(2) 0 * * * 

 Beta(3) 1.28922e-005 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -40.1666 4 

 Fitted model -40.2528 2 0.172251 2 0.9175 

 Reduced model -55.0401 1 29.7469 3 <.0001 

 AIC: 84.5055 
B-179 DRAFT- DO NOT CITE OR QUOTE 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 80 0.000 

 4.3600 0.0153 0.734 1 48 0.313 

 10.8000 0.0505 2.422 2 48 -0.278 

 25.0000 0.2470 11.856 12 48 0.048 

 Chi^2 = 0.18 d.f. = 2 P-value = 0.9151

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 15.9932 

 BMDL = 10.6421 

 BMDU = 19.9332 

Taken together, (10.6421, 19.9332) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.00939663 
B-180 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for tongue tumors in Sprague-Dawley female rats employing 

CEO in blood as an internal dose metric 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.002 0.004 0.006 0.008 0.01

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:49 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_BLOOD_CEO.plt

 Thu Sep 27 14:49:16 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 4 

 Total number of specified parameters = 0 

 Degree of polynomial = 3 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.0043768 

 Beta(1) = 2.92561 

 Beta(2) = 0 

 Beta(3) = 245868 
B-181 DRAFT- DO NOT CITE OR QUOTE 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background -Beta(2) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) Beta(3) 

 Beta(1) 1 -0.92 

 Beta(3) -0.92 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 6.26329 * * * 

 Beta(2) 0 * * * 

 Beta(3) 211165 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -40.1666 4 

 Fitted model -40.2953 2 0.257381 2 0.8792 

 Reduced model -55.0401 1 29.7469 3 <.0001 

 AIC: 84.5907 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 80 0.000 

 0.0021 0.0147 0.707 1 48 0.351 

 0.0049 0.0534 2.564 2 48 -0.362 

 0.0101 0.2448 11.752 12 48 0.083 

 Chi^2 = 0.26 d.f. = 2 P-value = 0.8776

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00669671 

 BMDL = 0.00473574 

 BMDU = 0.00818609 

Taken together, (0.00473574, 0.00818609) is a 90 % two-sided confidence 

interval for the BMD 
B-182 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for tongue tumors in Sprague-Dawley female rats employing 

AN in blood as an internal dose metric 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

10:57 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_BLOOD_AN.plt 

 Thu Sep 27 10:57:41 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 4 

 Total number of specified parameters = 0 

 Degree of polynomial = 3 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.0034253 

 Beta(1) = 0.462467 
B-183 DRAFT- DO NOT CITE OR QUOTE 

 Beta(2) = 0 

 Beta(3) = 55.8325 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background -Beta(2) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) Beta(3) 

 Beta(1) 1 -0.93 

 Beta(3) -0.93 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 0.629858 * * * 

 Beta(2) 0 * * * 

 Beta(3) 49.1667 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -40.1666 4 

 Fitted model -40.2395 2 0.145677 2 0.9298 

 Reduced model -55.0401 1 29.7469 3 <.0001 

 AIC: 84.479 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 80 0.000 

 0.0237 0.0155 0.742 1 48 0.302 

 0.0618 0.0493 2.365 2 48 -0.244 

 0.1560 0.2479 11.900 12 48 0.033 

 Chi^2 = 0.15 d.f. = 2 P-value = 0.9271

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0966976 

 BMDL = 0.0610292 

 BMDU = 0.122886 

Taken together, (0.0610292, 0.122886) is a 90 % two-sided confidence 

interval for the BMD 
B-184 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: Mammary Gland (Quast, 2002; Quast et al., 1980a)

Table B-17. Incidence of mammary gland tumors in Sprague-Dawley rats 

exposed to AN in drinking water for 2 years 

Predicted internal dose metrics 

Sex 

Administered 

animal dose 

(ppm in drinking 

water) 

Equivalent 

administered 

animal dosea

(mg/kg-d) 

AN-AUC in blood 

(mg/L)

CEO-AUC in blood

(mg/L)

Incidence of 

mammary gland 

tumorsb

0 0 0 0 58/80 (72%) 

35 4.36 2.37 × 10-2 2.07 × 10-3 42/47 (89%)c

100 10.8 6.18 × 10-2 4.87 × 10-3 42/48 (88%)c

Female 

300 25.0 1.56 × 10-1 1.01 × 10-2 35/48 (73%) 

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake. 

b

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

c

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Table B-18. Summary of BMD modeling results based on incidence of 

mammary gland tumors in Sprague-Dawley rats exposed to AN in drinking 

water for 2 years 

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Females 

Administered dose 1°MSe0.25 171.81 1.22 mg/kg-d 0.66 mg/kg-d 

CEO 1°MSe0.27 171.69 5.50 × 10-4 mg/L 2.98 × 10-4 mg/L 

AN 1°MSe

0.24 171.93 7.05 × 10-3 mg/L 3.77 × 10-3 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 

eHighest dose dropped prior to model fitting. 
B-185 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for mammary gland tumors in Sprague-Dawley female rats 

employing administered dose as a dose metric 

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

0 2 4 6 8 10

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

16:34 01/23 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_DW.plt 

 Fri Jan 23 16:34:25 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-186 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.771359 

 Beta(1) = 0.0674842 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.58 

 Beta(1) -0.58 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.741898 * * * 

 Beta(1) 0.0860351 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -83.2234 3 

 Fitted model -83.9062 2 1.36543 1 0.2426 

 Reduced model -86.3815 1 6.31609 2 0.04251 

 AIC: 171.812 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.7419 59.352 58 80 -0.345 

 4.3600 0.8226 39.486 42 48 0.950 

 10.8000 0.8981 43.108 42 48 -0.529 

 Chi^2 = 1.30 d.f. = 1 P-value = 0.2540
B-187 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1.22462 

 BMDL = 0.659237 

 BMDU = 4.94647 

Taken together, (0.659237, 4.94647) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.151691 
B-188 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for mammary gland tumors in Sprague-Dawley female rats 

employing CEO in blood as an internal dose metric 

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

0 0.001 0.002 0.003 0.004 0.005

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:53 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_BLOOD_CEO.plt 

 Thu Sep 27 14:53:05 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-189 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.768564 

 Beta(1) = 152.668 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.58 

 Beta(1) -0.58 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.740346 * * * 

 Beta(1) 191.729 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -83.2234 3 

 Fitted model -83.8471 2 1.24732 1 0.2641 

 Reduced model -86.3815 1 6.31609 2 0.04251 

 AIC: 171.694 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.7403 59.228 58 80 -0.313 

 0.0021 0.8254 39.619 42 48 0.905 

 0.0049 0.8979 43.101 42 48 -0.525 

 Chi^2 = 1.19 d.f. = 1 P-value = 0.2748

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000549528 

 BMDL = 0.000298184 

 BMDU = 0.00214159 

Taken together, (0.000298184, 0.00214159) is a 90 % two-sided confidence 

interval for the BMD 
B-190 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for mammary gland tumors in Sprague-Dawley female rats 

employing AN in blood as an internal dose metric 

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

0 0.01 0.02 0.03 0.04 0.05 0.06

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

11:00 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_BLOOD_AN.plt

 Thu Sep 27 11:00:59 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-191 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.773999 

 Beta(1) = 11.5581 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.58 

 Beta(1) -0.58 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.743458 * * * 

 Beta(1) 14.9428 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -83.2234 3 

 Fitted model -83.9649 2 1.48294 1 0.2233 

 Reduced model -86.3815 1 6.31609 2 0.04251 

 AIC: 171.93 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.7435 59.477 58 80 -0.378 

 0.0237 0.8200 39.358 42 48 0.992 

 0.0618 0.8981 43.110 42 48 -0.529 

 Chi^2 = 1.41 d.f. = 1 P-value = 0.2354

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00705091 

 BMDL = 0.00376506 

 BMDU = 0.0295793 

Taken together, (0.00376506, 0.0295793) is a 90 % two-sided confidence 

interval for the BMD 
B-192 DRAFT- DO NOT CITE OR QUOTE 

F344 Rats (Johannsen and Levinskas, 2002b; Biodynamics, 1980b)

Tumor Site: Forestomach

Table B-19. Incidence of forestomach (nonglandular) tumors in F344 rats 

exposed to AN in drinking water for 2 years 

Predicted internal dose metrics 

Sex 

Administered 

animal dose 

(ppm in drinking 

water) 

Equivalent 

administered 

animal dosea

(mg/kg-d) 

AN-AUC in blood 

(mg/L) 

CEO-AUC in blood

(mg/L) 

Incidence of 

forestomach 

tumorsb

0 0 0 0 0/159 (0%) 

1 0.08 4.33 × 10-4 4.06 × 10-5 1/80 (1%) 

3 0.25 1.35 × 10-3 1.27 × 10-4 4/78 (5%)c

10 0.83 4.52 × 10-3 4.19 × 10-4 3/80 (4%)c

30 2.48 1.37 × 10-2 1.23 × 10-3 4/80 (5%)c

Male 

100 8.37 4.85 × 10-2 3.97 × 10-3 1/77 (1%) 

0 0 0 0 0/157 (0%) 

1 0.12 5.73 × 10-4 5.32 × 10-5 1/80 (1%) 

3 0.36 1.72 × 10-3 1.59 × 10-4 2/79 (3%) 

10 1.25 6.02 × 10-3 5.49 × 10-4 2/77 (3%) 

30 3.65 1.79 × 10-2 1.58 × 10-3 4/80 (5%)c

Female 

100 10.90 5.63 × 10-2 4.46 × 10-3 2/75 (3%) 

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake. 

b

Incidences for F344 rats do not include animals from the 6- and 12-mo sacrifices and were further adjusted to 

exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

c

Significantly different from controls (p < 0.05) as calculated by the study authors. 
B-193 DRAFT- DO NOT CITE OR QUOTE 

Table B-20. Summary of BMD modeling results based on incidence of 

forestomach (nonglandular) tumors in F344 rats exposed to AN in drinking 

water for 2 years 

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Males 

Administered 

dose 1°MSe

0.18 74.08 1.19 mg/kg-d 0.70 mg/kg-d 

CEO 1°MSe

0.19 74.04 6.03 × 10-4 mg/L 3.55 × 10-4 mg/L

AN 1°MSe0.18 74.12 6.48 × 10-3 mg/L 3.81 × 10-3 mg/L

Females 

Administered 

dose 1°MSf

0.83 96.64 8.43 mg/kg-d 3.89 mg/kg-d 

CEO 1°MSf0.83 96.62 3.65 × 10-3 mg/L 1.69 × 10-3 mg/L

AN 1°MSf0.82 96.65 4.13 × 10-2 mg/L 1.90 × 10-2 mg/L

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 

eTwo highest doses dropped prior to model fitting. 

fHighest dose dropped prior to model fitting. 
B-194 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in F344 male rats employing 

administered dose as a dose metric 

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 0.2 0.4 0.6 0.8 1 1.2

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

14:29 01/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_DW.plt 

 Mon Jan 26 14:29:05 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-195 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0148134 

 Beta(1) = 0.0377128 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 0.0883999 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -33.9463 4 

 Fitted model -36.0377 1 4.18282 3 0.2424 

 Reduced model -39.1548 1 10.417 3 0.01533 

 AIC: 74.0755 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 159 0.000 

 0.0800 0.0070 0.564 1 80 0.583 

 0.2500 0.0219 1.705 4 78 1.777 

 0.8300 0.0707 5.660 3 80 -1.160 

 Chi^2 = 4.84 d.f. = 3 P-value = 0.1836
B-196 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 1.19186 

 BMDL = 0.701326 

 BMDU = 3.81474 

Taken together, (0.701326, 3.81474) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.142587 
B-197 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in F344 male rats employing CEO in 

blood as an internal dose metric

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

14:57 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_BLOOD_CEO.plt 

 Thu Sep 27 14:57:13 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-198 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0147622 

 Beta(1) = 74.9311 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 174.815 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -33.9463 4 

 Fitted model -36.0209 1 4.14909 3 0.2458 

 Reduced model -39.1548 1 10.417 3 0.01533 

 AIC: 74.0417 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 159 0.000 

 0.0000 0.0071 0.566 1 80 0.579 

 0.0001 0.0220 1.713 4 78 1.767 

 0.0004 0.0706 5.650 3 80 -1.157 

 Chi^2 = 4.80 d.f. = 3 P-value = 0.1873

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.000602696 

 BMDL = 0.000354643 

 BMDU = 0.00191036 

Taken together, (0.000354643, 0.00191036) is a 90 % two-sided confidence 

interval for the BMD 
B-199 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in F344 male rats employing AN in 

blood as an internal dose metric 

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 0.001 0.002 0.003 0.004 0.005 0.006

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

11:04 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_BLOOD_AN.plt 

 Thu Sep 27 11:04:04 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 4 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-200 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.0148807 

 Beta(1) = 6.89727 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 16.2684 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -33.9463 4 

 Fitted model -36.0601 1 4.22747 3 0.2379 

 Reduced model -39.1548 1 10.417 3 0.01533 

 AIC: 74.1201 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 159 0.000 

 0.0004 0.0070 0.562 1 80 0.587 

 0.0014 0.0217 1.694 4 78 1.791 

 0.0045 0.0709 5.672 3 80 -1.164 

 Chi^2 = 4.91 d.f. = 3 P-value = 0.1788

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00647638 

 BMDL = 0.00381089 

 BMDU = 0.0209986 

Taken together, (0.00381089, 0.0209986) is a 90 % two-sided confidence 

interval for the BMD 
B-201 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in F344 female rats employing 

administered dose as a dose metric 

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 1 2 3 4 5 6 7 8

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

14:49 01/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_DW.plt

 Mon Jan 26 14:49:27 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 5 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-202 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0127929 

 Beta(1) = 0.0107517 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.58 

 Beta(1) -0.58 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0101696 * * * 

 Beta(1) 0.0125023 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -45.9122 5 

 Fitted model -46.3178 2 0.81118 3 0.8468 

 Reduced model -48.4586 1 5.09287 4 0.2779 

 AIC: 96.6356 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0102 1.597 1 157 -0.475 

 0.1200 0.0117 0.932 1 80 0.071 

 0.3600 0.0146 1.155 2 79 0.793 

 1.2500 0.0255 1.965 2 77 0.025 

 3.6500 0.0543 4.346 4 80 -0.171 

 Chi^2 = 0.89 d.f. = 3 P-value = 0.8283
B-203 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 8.42727 

 BMDL = 3.88972 

 BMDU = 48.9918 

Taken together, (3.88972, 48.9918) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0257088 
B-204 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in F344 female rats employing CEO 

in blood as an internal dose metric 

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:07 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_BLOOD_CEO.plt 

 Thu Sep 27 15:07:15 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 5 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-205 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0127198 

 Beta(1) = 24.8654 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.58 

 Beta(1) -0.58 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0101112 * * * 

 Beta(1) 28.8833 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -45.9122 5 

 Fitted model -46.3121 2 0.799693 3 0.8495 

 Reduced model -48.4586 1 5.09287 4 0.2779 

 AIC: 96.6241 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0101 1.587 1 157 -0.469 

 0.0001 0.0116 0.930 1 80 0.072 

 0.0002 0.0146 1.157 2 79 0.789 

 0.0005 0.0257 1.978 2 77 0.016 

 0.0016 0.0543 4.342 4 80 -0.169 

 Chi^2 = 0.88 d.f. = 3 P-value = 0.8310

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0036478 

 BMDL = 0.00168696 

 BMDU = 1361.26 

Taken together, (0.00168696, 1361.26) is a 90 % two-sided confidence 

interval for the BMD 
B-206 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for forestomach tumors in F344 female rats employing AN in 

blood as an internal dose metric

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

11:30 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_BLOOD_AN.plt 

 Thu Sep 27 11:30:39 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 5 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-207 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.0128833 

 Beta(1) = 2.18924 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.58 

 Beta(1) -0.58 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0102427 * * * 

 Beta(1) 2.54885 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -45.9122 5 

 Fitted model -46.3252 2 0.826038 3 0.8432 

 Reduced model -48.4586 1 5.09287 4 0.2779 

 AIC: 96.6505 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0102 1.608 1 157 -0.482 

 0.0006 0.0117 0.935 1 80 0.068 

 0.0017 0.0146 1.151 2 79 0.797 

 0.0060 0.0253 1.949 2 77 0.037 

 0.0179 0.0544 4.351 4 80 -0.173 

 Chi^2 = 0.90 d.f. = 3 P-value = 0.8246

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0413364 

 BMDL = 0.0190324 

 BMDU = 0.242436 

Taken together, (0.0190324, 0.242436) is a 90 % two-sided confidence 

interval for the BMD 
B-208 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: CNS (Johannsen and Levinskas, 2002b; Biodynamics, 1980b) 

Table B-21. Incidence of CNS tumors in F344 rats exposed to AN in 

drinking water for 2 years 

Predicted internal dose metrics 

Sex 

Administered 

animal dose 

(ppm in drinking 

water) 

Equivalent 

administered 

animal dosea

(mg/kg-d) 

AN-AUC in blood 

(mg/L) 

CEO-AUC in blood

(mg/L) 

Incidence of CNS 

tumorsb

0 0 0 0 0/160 (0%) 

1 0.08 4.33 × 10-4 4.06 × 10-5 2/80 (3%) 

3 0.25 1.35 × 10-3 1.27 × 10-4 1/78 (1%) 

10 0.83 4.52 × 10-3 4.19 × 10-4 2/80 (3%) 

30 2.48 1.37 × 10-2 1.23 × 10-3 10/79 (13%)c

Male 

100 8.37 4.85 × 10-2 3.97 × 10-3 25/76 (33%)c

0 0 0 0 1/157 (1%) 

1 0.12 5.73 × 10-4 5.32 × 10-5 1/80 (1%) 

3 0.36 1.72 × 10-3 1.59 × 10-4 2/80 (3%) 

10 1.25 6.02 × 10-3 5.49 × 10-4 5/75 (7%) 

30 3.65 1.79 × 10-2 1.58 × 10-3 6/80 (8%)c

Female 

100 10.90 5.63 × 10-2 4.46 × 10-3 24/76 (32%)c

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake. 

b

Incidences for F344 rats do not include animals from the 6- and 12-mo sacrifices and were further adjusted to 

exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

c

Significantly different from controls (p < 0.01) as calculated by the study authors. 

Table B-22. Summary of BMD modeling results based on incidence of CNS 

tumors in F344 rats exposed to AN in drinking water for 2 years 

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Males 

Administered dose 1°MS 0.73 240.57 2.41 mg/kg-d 1.81 mg/kg-d 

CEO 1°MS 0.70 240.75 1.16 × 10-3 mg/L 8.74 × 10-4 mg/L 

AN 1°MS 0.74 240.44 1.37 × 10-2 mg/L 1.03 × 10-2 mg/L 

Females 

Administered dose 1°MS 0.68 222.13 3.34 mg/kg-d 2.52 mg/kg-d 

CEO 1°MS 0.66 222.30 1.39 × 10-3 mg/L 1.05 × 10-3 mg/L 

AN 1°MS 0.68 222.04 1.70 × 10-2 mg/L 1.28 × 10-2 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-209 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in F344 male rats employing administered 

dose as a dose metric 

0

0.1

0.2

0.3

0.4

0 1 2 3 4 5 6 7 8

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

14:34 01/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_CNS_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_CNS_DW.plt 

 Mon Jan 26 14:34:10 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-210 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.00946328 

 Beta(1) = 0.0466 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.47 

 Beta(1) -0.47 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0149509 * * * 

 Beta(1) 0.0437933 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -117.105 6 

 Fitted model -118.287 2 2.36443 4 0.6691 

 Reduced model -151.112 1 68.0145 5 <.0001 

 AIC: 240.574 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0150 2.392 3 160 0.396 

 0.0800 0.0184 1.472 2 80 0.440 

 0.2500 0.0257 2.003 1 78 -0.718 

 0.8300 0.0501 4.009 2 80 -1.030 

 2.4800 0.1163 9.190 10 79 0.284 

 8.3700 0.3172 24.110 25 76 0.219 

 Chi^2 = 2.05 d.f. = 4 P-value = 0.7258
B-211 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 2.40586 

 BMDL = 1.8134 

 BMDU = 3.32187 

Taken together, (1.8134 , 3.32187) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0551449 
B-212 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in F344 male rats employing CEO in blood as 

an internal dose metric

0

0.1

0.2

0.3

0.4

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:00 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_CNS_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_CNS_BLOOD_CEO.plt 

 Thu Sep 27 15:00:12 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-213 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.00793445 

 Beta(1) = 98.3167 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.47 

 Beta(1) -0.47 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0147547 * * * 

 Beta(1) 90.9591 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -117.105 6 

 Fitted model -118.375 2 2.54113 4 0.6373 

 Reduced model -151.112 1 68.0145 5 <.0001 

 AIC: 240.75 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0148 2.361 3 160 0.419 

 0.0000 0.0184 1.471 2 80 0.440 

 0.0001 0.0261 2.034 1 78 -0.734 

 0.0004 0.0516 4.128 2 80 -1.075 

 0.0012 0.1190 9.404 10 79 0.207 

 0.0040 0.3134 23.817 25 76 0.293 

 Chi^2 = 2.19 d.f. = 4 P-value = 0.7002

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00115833 

 BMDL = 0.000873641 

 BMDU = 0.00159795 

Taken together, (0.000873641, 0.00159795) is a 90 % two-sided confidence 

interval for the BMD 
B-214 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in F344 male rats employing AN in blood as 

an internal dose metric 

0

0.1

0.2

0.3

0.4

0 0.01 0.02 0.03 0.04 0.05

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

11:07 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_CNS_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_CNS_BLOOD_AN.plt 

 Thu Sep 27 11:07:15 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-215 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.0109984 

 Beta(1) = 8.0341 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.46 

 Beta(1) -0.46 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0151616 * * * 

 Beta(1) 7.67068 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -117.105 6 

 Fitted model -118.218 2 2.22757 4 0.694 

 Reduced model -151.112 1 68.0145 5 <.0001 

 AIC: 240.437 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0152 2.426 3 160 0.371 

 0.0004 0.0184 1.474 2 80 0.437 

 0.0014 0.0253 1.974 1 78 -0.702 

 0.0045 0.0487 3.898 2 80 -0.986 

 0.0137 0.1134 8.959 10 79 0.369 

 0.0485 0.3211 24.405 25 76 0.146 

 Chi^2 = 1.95 d.f. = 4 P-value = 0.7447

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0137355 

 BMDL = 0.0103458 

 BMDU = 0.0189838 

Taken together, (0.0103458, 0.0189838) is a 90 % two-sided confidence 

interval for the BMD 
B-216 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in F344 female rats employing administered 

dose as a dose metric

0

0.1

0.2

0.3

0.4

0 2 4 6 8 10

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

14:55 01/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_CNS_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_CNS_DW.plt 

 Mon Jan 26 14:55:28 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-217 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.00525608 

 Beta(1) = 0.0331149 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.49 

 Beta(1) -0.49 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.00823648 * * * 

 Beta(1) 0.0315054 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -107.86 6 

 Fitted model -109.065 2 2.41059 4 0.6607 

 Reduced model -140.644 1 65.5686 5 <.0001 

 AIC: 222.13 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0082 1.293 1 157 -0.259 

 0.1200 0.0120 0.958 1 80 0.043 

 0.3600 0.0194 1.554 2 80 0.362 

 1.2500 0.0465 3.490 5 75 0.828 

 3.6500 0.1160 9.278 6 80 -1.144 

 10.9000 0.2965 22.534 24 76 0.368 

 Chi^2 = 2.33 d.f. = 4 P-value = 0.6753
B-218 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 3.34421 

 BMDL = 2.51554 

 BMDU = 4.64166 

Taken together, (2.51554, 4.64166) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0397529 
B-219 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in F344 female rats employing CEO in blood 

as an internal dose metric

0

0.1

0.2

0.3

0.4

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:10 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_CNS_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_CNS_BLOOD_CEO.plt 

 Thu Sep 27 15:10:31 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-220 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.00362563 

 Beta(1) = 80.7118 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.5 

 Beta(1) -0.5 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.00790184 * * * 

 Beta(1) 75.5979 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -107.86 6 

 Fitted model -109.148 2 2.57752 4 0.6308 

 Reduced model -140.644 1 65.5686 5 <.0001 

 AIC: 222.297 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0079 1.241 1 157 -0.217 

 0.0001 0.0119 0.951 1 80 0.051 

 0.0002 0.0198 1.580 2 80 0.337 

 0.0005 0.0482 3.618 5 75 0.745 

 0.0016 0.1196 9.568 6 80 -1.229 

 0.0045 0.2919 22.181 24 76 0.459 

 Chi^2 = 2.44 d.f. = 4 P-value = 0.6554

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0013937 

 BMDL = 0.00104985 

 BMDU = 0.00193063 

Taken together, (0.00104985, 0.00193063) is a 90 % two-sided confidence 

interval for the BMD 
B-221 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in F344 female rats employing AN in blood 

as an internal dose metric

0

0.1

0.2

0.3

0.4

0 0.01 0.02 0.03 0.04 0.05

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

11:34 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_CNS_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_CNS_BLOOD_AN.plt 

 Thu Sep 27 11:34:20 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-222 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.00679319 

 Beta(1) = 6.4212 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.49 

 Beta(1) -0.49 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.00859669 * * * 

 Beta(1) 6.19715 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -107.86 6 

 Fitted model -109.017 2 2.31525 4 0.678 

 Reduced model -140.644 1 65.5686 5 <.0001 

 AIC: 222.035 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0086 1.350 1 157 -0.302 

 0.0006 0.0121 0.969 1 80 0.032 

 0.0017 0.0191 1.529 2 80 0.385 

 0.0060 0.0449 3.368 5 75 0.910 

 0.0179 0.1127 9.015 6 80 -1.066 

 0.0563 0.3006 22.846 24 76 0.289 

 Chi^2 = 2.29 d.f. = 4 P-value = 0.6828

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0170014 

 BMDL = 0.0127694 

 BMDU = 0.0236456 

Taken together, (0.0127694, 0.0236456) is a 90 % two-sided confidence 

interval for the BMD 
B-223 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: Zymbal’s Gland (Johannsen and Levinskas, 2002b; Biodynamics, 1980b)

Table B-23. Incidence of Zymbal gland tumors in F344 rats exposed to AN 

in drinking water for 2 years 

Predicted internal dose metrics 

Sex 

Administered 

animal dose 

(ppm in drinking 

water) 

Equivalent 

administered 

animal dosea

(mg/kg-d) 

AN-AUC in blood 

(mg/L) 

CEO-AUC in blood

(mg/L) 

Incidence of 

Zymbal’s gland 

tumorsb

0 0 0 0 1/147 (1%) 

1 0.08 4.33 × 10-4 4.06 × 10-5 1/76 (1%) 

3 0.25 1.35 × 10-3 1.27 × 10-4 0/73 (0%) 

10 0.83 4.52 × 10-3 4.19 × 10-4 0/67 (0%) 

30 2.48 1.37 × 10-2 1.23 × 10-3 2/71 (3%)c

Male 

100 8.37 4.85 × 10-2 3.97 × 10-3 14/68 (21%)c

0 0 0 0 0/157 (0%) 

1 0.12 5.73 × 10-4 5.32 × 10-5 0/73 (0%) 

3 0.36 1.72 × 10-3 1.59 × 10-4 0/73 (0%) 

10 1.25 6.02 × 10-3 5.49 × 10-4 0/70 (0%) 

30 3.65 1.79 × 10-2 1.58 × 10-3 2/73 (3%)c

Female 

100 10.90 5.63 × 10-2 4.46 × 10-3 8/62 (13%)c

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake. 

b

Incidences for F344 rats do not include animals from the 6- and 12-mo sacrifices and were further adjusted to 

exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

c

Significantly different from controls (p < 0.01) as calculated by the study authors. 

Table B-24. Summary of BMD modeling results based on incidence of 

Zymbal gland tumors in F344 rats exposed to AN in drinking water for 

2 years 

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Males 

Administered dose 2°MS 0.78 116.51 5.73 mg/kg-d 4.55 mg/kg-d 

CEO 2°MS 0.77 116.53 2.73 × 10-3 mg/L 2.19 × 10-3 mg/L 

AN 2°MS 0.78 116.52 3.31 × 10-2 mg/L 2.59 × 10-2 mg/L 

Females 

Administered dose 2°MS 0.95 70.80 9.16 mg/kg-d 7.17 mg/kg-d 

CEO 2°MS 0.99 68.68 3.78 × 10-3 mg/L 2.97 × 10-3 mg/L 

AN 1°MS 0.89 70.82 5.41 × 10-2 mg/L 3.35 × 10-2 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model and 

“2°MS” indicates a two-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-224 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 male rats employing 

administered dose as a dose metric 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 1 2 3 4 5 6 7 8

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

14:41 01/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_DW.plt 

 Mon Jan 26 14:41:15 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-225 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.00522088 

 Beta(1) = 0 

 Beta(2) = 0.00321913 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.37 

 Beta(2) -0.37 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.00563419 * * * 

 Beta(1) 0 * * * 

 Beta(2) 0.00321262 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -54.9964 6 

 Fitted model -56.2568 2 2.52093 4 0.6409 

 Reduced model -77.5815 1 45.1702 5 <.0001 

 AIC: 116.514 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0056 0.828 1 147 0.189 

 0.0800 0.0057 0.430 1 76 0.872 

 0.2500 0.0058 0.426 0 73 -0.654 

 0.8300 0.0078 0.525 0 67 -0.727 

 2.4800 0.0251 1.781 2 71 0.166 

 8.3700 0.2060 14.010 14 68 -0.003 

 Chi^2 = 1.78 d.f. = 4 P-value = 0.7758
B-226 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 5.72676 

 BMDL = 4.54678 

 BMDU = 7.26717 

Taken together, (4.54678, 7.26717) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0219936 
B-227 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 male rats employing CEO 

in blood as an internal dose metric

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:02 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_BLOOD_CEO.plt

 Thu Sep 27 15:02:53 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-228 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.00480523 

 Beta(1) = 0 

 Beta(2) = 14327.9 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.38 

 Beta(2) -0.38 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.00556639 * * * 

 Beta(1) 0 * * * 

 Beta(2) 14170.3 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -54.9964 6 

 Fitted model -56.2667 2 2.54061 4 0.6374 

 Reduced model -77.5815 1 45.1702 5 <.0001 

 AIC: 116.533 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0056 0.818 1 147 0.201 

 0.0000 0.0056 0.425 1 76 0.885 

 0.0001 0.0058 0.423 0 73 -0.652 

 0.0004 0.0080 0.538 0 67 -0.737 

 0.0012 0.0267 1.893 2 71 0.079 

 0.0040 0.2046 13.913 14 68 0.026 

 Chi^2 = 1.80 d.f. = 4 P-value = 0.7727

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00272678 

 BMDL = 0.00218772 

 BMDU = 0.00345798 

Taken together, (0.00218772, 0.00345798) is a 90 % two-sided confidence 

interval for the BMD 
B-229 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 male rats employing AN in 

blood as an internal dose metric 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 0.01 0.02 0.03 0.04 0.05

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

11:27 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_BLOOD_AN.plt 

 Thu Sep 27 11:27:02 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 

 Background = 0.00503997 

 Beta(1) = 0.191539 
B-230 DRAFT- DO NOT CITE OR QUOTE 

 Beta(2) = 91.9968 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.37 

 Beta(2) -0.37 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.00571347 * * * 

 Beta(1) 0 * * * 

 Beta(2) 96.3581 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -54.9964 6 

 Fitted model -56.2582 2 2.52365 4 0.6404 

 Reduced model -77.5815 1 45.1702 5 <.0001 

 AIC: 116.516 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0057 0.840 1 147 0.175 

 0.0004 0.0057 0.436 1 76 0.858 

 0.0014 0.0059 0.430 0 73 -0.658 

 0.0045 0.0077 0.514 0 67 -0.720 

 0.0137 0.0235 1.671 2 71 0.258 

 0.0485 0.2074 14.101 14 68 -0.030 

 Chi^2 = 1.78 d.f. = 4 P-value = 0.7755

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.033067 

 BMDL = 0.0258907 

 BMDU = 0.0419928 

Taken together, (0.0258907, 0.0419928) is a 90 % two-sided confidence 

interval for the BMD 
B-231 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 female rats employing 

administered dose as a dose metric 

0

0.05

0.1

0.15

0.2

0.25

0 2 4 6 8 10

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

15:01 01/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_DW.plt 

 Mon Jan 26 15:01:22 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-232 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 0.00476273 

 Beta(2) = 0.000742952 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) Beta(2) 

 Beta(1) 1 -0.95 

 Beta(2) -0.95 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 0.000111429 * * * 

 Beta(2) 0.00124232 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -33.0086 6 

 Fitted model -33.4019 2 0.786523 4 0.9402 

 Reduced model -49.1799 1 32.3425 5 <.0001 

 AIC: 70.8038 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 157 0.000 

 0.1200 0.0000 0.002 0 73 -0.048 

 0.3600 0.0002 0.015 0 73 -0.121 

 1.2500 0.0021 0.145 0 70 -0.382 

 3.6500 0.0168 1.227 2 73 0.703 

 10.9000 0.1383 8.573 8 62 -0.211 

 Chi^2 = 0.70 d.f. = 4 P-value = 0.9511
B-233 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 9.16446 

 BMDL = 7.17181 

 BMDU = 13.5889 

Taken together, (7.17181, 13.5889) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0139435 
B-234 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 female rats employing CEO 

in blood as an internal dose metric

0

0.05

0.1

0.15

0.2

0.25

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:13 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_BLOOD_CEO.plt 

 Thu Sep 27 15:13:27 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-235 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 9.4165 

 Beta(2) = 4928.95 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(2) 

 Beta(2) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 0 * * * 

 Beta(2) 7382.1 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -33.0086 6 

 Fitted model -33.3423 1 0.667255 5 0.9847 

 Reduced model -49.1799 1 32.3425 5 <.0001 

 AIC: 68.6845 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 157 0.000 

 0.0001 0.0000 0.002 0 73 -0.039 

 0.0002 0.0002 0.014 0 73 -0.117 

 0.0005 0.0022 0.156 0 70 -0.395 

 0.0016 0.0183 1.333 2 73 0.583 

 0.0045 0.1366 8.467 8 62 -0.173 

 Chi^2 = 0.54 d.f. = 5 P-value = 0.9905

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00377789 

 BMDL = 0.00297198 

 BMDU = 0.00541558 

Taken together, (0.00297198, 0.00541558) is a 90 % two-sided confidence 

interval for the BMD 
B-236 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 female rats employing AN 

in blood as an internal dose metric 

0

0.05

0.1

0.15

0.2

0.25

0 0.01 0.02 0.03 0.04 0.05

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

11:37 09/27 2007

BMDL BMD

 

Multistage

==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_BLOOD_AN.plt 

 Thu Sep 27 11:37:11 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-237 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 2.5025 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 1.94599 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -33.0086 6 

 Fitted model -34.4088 1 2.80031 5 0.7307 

 Reduced model -49.1799 1 32.3425 5 <.0001 

 AIC: 70.8176 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 157 0.000 

 0.0006 0.0011 0.081 0 73 -0.285 

 0.0017 0.0033 0.244 0 73 -0.495 

 0.0060 0.0116 0.815 0 70 -0.908 

 0.0179 0.0342 2.499 2 73 -0.321 

 0.0563 0.1038 6.434 8 62 0.652 

 Chi^2 = 1.68 d.f. = 5 P-value = 0.8915

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0541423 

 BMDL = 0.0335374 

 BMDU = 0.0957005 

Taken together, (0.0335374, 0.0957005) is a 90 % two-sided confidence 

interval for the BMD 
B-238 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: Mammary Gland (Johannsen and Levinskas, 2002b; Biodynamics, 1980b)

Table B-25. Incidence of mammary gland tumors in F344 rats exposed to 

AN in drinking water for 2 years 

Predicted internal dose metrics 

Sex 

Administered 

animal dose 

(ppm in drinking 

water) 

Equivalent 

administered 

animal dosea

(mg/kg-d) 

AN-AUC in blood 

(mg/L) 

CEO-AUC in blood

(mg/L) 

Incidence of 

mammary gland 

tumorsb

0 0 0 0 14/156 (9%) 

1 0.12 5.73 × 10-4 5.32 × 10-5 8/80 (10%) 

3 0.36 1.72 × 10-3 1.59 × 10-4 6/80 (8%) 

10 1.25 6.02 × 10-3 5.49 × 10-4 9/80 (11%) 

30 3.65 1.79 × 10-2 1.58 × 10-3 12/80 (15%) 

Female 

100 10.90 5.63 × 10-2 4.46 × 10-3 14/73 (19%) 

aAdministered doses were averages calculated by the study authors based on animal BW and drinking water intake. 

b

Incidences for F344 rats do not include animals from the 6- and 12-mo sacrifices and were further adjusted to 

exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

Table B-26. Summary of BMD modeling results based on incidence of 

mammary gland tumors in F344 rats exposed to AN in drinking water for 2 

years

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Females 

Administered dose 1°MS 0.94 388.94 8.73 mg/kg-d 4.77 mg/kg-d 

CEO 1°MS 0.94 388.88 3.58 × 10-3 mg/L 1.97 × 10-3 mg/L 

AN 1°MS 0.93 389.00 4.51 × 10-2 mg/L 2.45 × 10-2 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-239 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for mammary gland tumors in F344 female rats employing 

administered dose as a dose metric 

0.05

0.1

0.15

0.2

0.25

0.3

0 2 4 6 8 10

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

15:04 01/26 2009

BMDL BMD

 

Multistage Cancer

Linear extrapolation

 ==================================================================== 

 Multistage Cancer Model. (Version: 1.5; Date: 02/20/2007) 

 Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_DW.(d) 

 Gnuplot Plotting File: M:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_DW.plt 

 Mon Jan 26 15:04:09 2009 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-240 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.093497 

 Beta(1) = 0.0112514 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.52 

 Beta(1) -0.52 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0913697 * * * 

 Beta(1) 0.0120689 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -192.056 6 

 Fitted model -192.471 2 0.830208 4 0.9344 

 Reduced model -195.631 1 7.14977 5 0.2097 

 AIC: 388.943 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0914 14.254 14 156 -0.070 

 0.1200 0.0927 7.415 8 80 0.226 

 0.3600 0.0953 7.625 6 80 -0.619 

 1.2500 0.1050 8.398 9 80 0.220 

 3.6500 0.1305 10.442 12 80 0.517 

 10.9000 0.2034 14.846 14 73 -0.246 

 Chi^2 = 0.81 d.f. = 4 P-value = 0.9365
B-241 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 8.72994 

 BMDL = 4.77219 

 BMDU = 27.9615 

Taken together, (4.77219, 27.9615) is a 90 % two-sided confidence 

interval for the BMD 

Multistage Cancer Slope Factor = 0.0209547 
B-242 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for mammary gland tumors in F344 female rats employing 

CEO in blood as an internal dose metric

0.05

0.1

0.15

0.2

0.25

0.3

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:16 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_BLOOD_CEO.plt 

 Thu Sep 27 15:16:49 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-243 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0927789 

 Beta(1) = 27.631 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.53 

 Beta(1) -0.53 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0908696 * * * 

 Beta(1) 29.4458 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -192.056 6 

 Fitted model -192.441 2 0.770201 4 0.9424 

 Reduced model -195.631 1 7.14977 5 0.2097 

 AIC: 388.883 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0909 14.176 14 156 -0.049 

 0.0001 0.0923 7.383 8 80 0.238 

 0.0002 0.0951 7.609 6 80 -0.613 

 0.0005 0.1054 8.436 9 80 0.205 

 0.0016 0.1322 10.576 12 80 0.470 

 0.0045 0.2028 14.801 14 73 -0.233 

 Chi^2 = 0.75 d.f. = 4 P-value = 0.9447

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00357812 

 BMDL = 0.00196521 

 BMDU = 0.011322 

Taken together, (0.00196521, 0.011322) is a 90 % two-sided confidence 

interval for the BMD 
B-244 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for mammary gland tumors in F344 female rats employing 

AN in blood as an internal dose metric 

0.05

0.1

0.15

0.2

0.25

0.3

0 0.01 0.02 0.03 0.04 0.05

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

11:39 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_BLOOD_AN.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_BLOOD_AN.plt 

 Thu Sep 27 11:39:30 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 6 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-245 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.0941503 

 Beta(1) = 2.16751 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.52 

 Beta(1) -0.52 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0918429 * * * 

 Beta(1) 2.33757 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -192.056 6 

 Fitted model -192.5 2 0.887943 4 0.9263 

 Reduced model -195.631 1 7.14977 5 0.2097 

 AIC: 389.001 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0918 14.327 14 156 -0.091 

 0.0006 0.0931 7.445 8 80 0.214 

 0.0017 0.0955 7.639 6 80 -0.624 

 0.0060 0.1045 8.363 9 80 0.233 

 0.0179 0.1291 10.325 12 80 0.559 

 0.0563 0.2038 14.880 14 73 -0.256 

 Chi^2 = 0.87 d.f. = 4 P-value = 0.9282

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0450726 

 BMDL = 0.0245301 

 BMDU = 0.146059 

Taken together, (0.0245301, 0.146059) is a 90 % two-sided confidence 

interval for the BMD 
B-246 DRAFT- DO NOT CITE OR QUOTE 

APPENDIX B-4. CANCER INHALATION DOSE-RESPONSE ASSESSMENT: BMD 

MODELING RESULTS FOR TUMOR INCIDENCE DATA FROM RATS

CHRONICALLY EXPOSED TO AN VIA INHALATION 

As summarized in Section 4.6.2, AN is a multisite carcinogen in chronic rodent 

bioassays. Data from the only available chronic inhalation cancer bioassay with multiple 

exposure levels to AN were used for dose-response assessment (Dow Chemical Co., 1992a; 

Quast et al., 1980b). In this study, male and female Sprague-Dawley rats were exposed to AN in 

air at concentrations of 0, 20, or 80 ppm 6 hours/day, 5 days/week for 2 years. At 80 ppm, 

significantly increased incidences of CNS tumors (i.e., astrocytomas and glial cell proliferation) 

and Zymbal’s gland tumors were observed in males and females. Also at this concentration, 

significantly increased incidences of malignant mammary gland tumors (i.e., adenocarcinomas) 

in females, as well as intestinal and tongue tumors in males, were seen. At 20 ppm, male and 

female rats exhibited increased incidences (although nonsignificant) of CNS tumors (i.e., 

astrocytomas and glial cell proliferation) and Zymbal’s gland tumors. 

 In this appendix, detailed results of the dose-response modeling for each of the tumor 

sites listed above are presented (Tables B-27 through B-36). For each tumor site, first a 

summary of the dose-response data is presented, followed by a table summarizing the results of 

the dose-response modeling. Finally, the standard output from EPA’s BMDS, version 1.4.1, for 

the selected dose-response model for each tumor site is presented. 

In general, the multistage model was fit to all of the data sets with the BMR set at 

0.1 (i.e., 10% extra risk). In fitting this model, successive stages of the multistage model, 

starting with stage 1 and ending with the stage equal to the number of dose groups minus one, 

were fit to the tumor incidence data at a particular site for each rat sex employing either 

administered dose or the internal dose metric CEO in blood. Then, for each dose metric, all 

stages of the multistage model that did not show a significant lack of fit (i.e., p > 0.1) were 

compared using AIC. The stage of the multistage model with the lowest AIC was selected as the 

best-fit model. For most tumor sites, the one-stage model exhibited the best fit. For data sets 

that exhibited a significant lack of fit for all stages of the multistage model, dose groups were 

dropped (starting with the highest dose group) until an adequate fit was achieved. 
B-247 DRAFT- DO NOT CITE OR QUOTE 

Sprague-Dawley Rats (Dow Chemical Co., 1992a; Quast et al., 1980b) 

Tumor Site: Intestine

Table B-27. Incidence of intestinal tumors in Sprague-Dawley rats exposed 

to AN in air for 2 years 

Sex 

Administered AN concentration 

(ppm in air) 

Predicted CEO-AUC in blood 

(mg/L) 

Incidence of intestinal 

tumorsa

0 0 4/96 (4%) 

20 2.17 × 10-3 Male 3/93 (3%) 

80 8.20 × 10-3 17/82 (21%)b

a

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

b

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Table B-28. Summary of BMD modeling results based on incidence of 

intestinal tumors in Sprague-Dawley rats exposed to AN in air for 2 years 

Dose metric Best-fit modela

χ

2

p valueb AIC BMD10

c BMDL10d

Males 

Administered dose 2°MS 0.45 148.05 59.04 ppm 42.68 ppm 

CEO 2°MS 0.42 148.13 6.06 × 10-3 mg/L 4.47 × 10-3 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “2°MS” indicates a two-stage multistage model 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-248 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for intestinal tumors in Sprague-Dawley male rats employing 

administered dose as a dose metric

0

0.05

0.1

0.15

0.2

0.25

0.3

0 10 20 30 40 50 60 70 80

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

13:10 04/13 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $ 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_INTESTINE_INHALE_PPM.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_INTESTINE_INHALE_PPM.plt 

 Fri Apr 13 13:10:33 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

-beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-249 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0312892 

 Beta(1) = 0 

 Beta(2) = 3.12226e-005 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.55 

 Beta(2) -0.55 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 Background 0.033209 0.0736218 

 Beta(1) 0 NA 

 Beta(2) 3.02304e-005 2.28675e-005 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -71.7319 

 Fitted model -72.0247 0.585523 1 0.4442 

 Reduced model -81.082 18.7001 2 <.0001 

 AIC: 148.049 
B-250 DRAFT- DO NOT CITE OR QUOTE 

 Goodness of Fit 

 Dose Est._Prob. Expected Observed Size Chi^2 Res. 

 ----------------------------------------------------------------------- 

i: 1 

 0.0000 0.0332 3.188 4 96 0.263 

i: 2 

 20.0000 0.0448 4.169 3 93 -0.294 

i: 3 

 80.0000 0.2033 16.669 17 82 0.025 

 Chi-square = 0.57 DF = 1 P-value = 0.4521 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 59.036 

 BMDL = 42.6779 
B-251 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for intestinal tumors in Sprague-Dawley male rats employing 

CEO in blood as an internal dose metric

0

0.05

0.1

0.15

0.2

0.25

0.3

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:20 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_INTESTINE_INHALE_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_INTESTINE_INHALE_BLOOD_CEO.plt 

 Thu Sep 27 15:20:06 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-252 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.0306135 

 Beta(1) = 0 

 Beta(2) = 2979.81 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.55 

 Beta(2) -0.55 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0328821 * * * 

 Beta(1) 0 * * * 

 Beta(2) 2868.6 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -71.7319 3 

 Fitted model -72.0636 2 0.663417 1 0.4154 

 Reduced model -81.082 1 18.7001 2 <.0001 

 AIC: 148.127 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0329 3.157 4 96 0.483 

 0.0022 0.0459 4.265 3 93 -0.627 

 0.0082 0.2025 16.609 17 82 0.107 

 Chi^2 = 0.64 d.f. = 1 P-value = 0.4246

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00606044 

 BMDL = 0.004465 

 BMDU = 0.00809222 

Taken together, (0.004465, 0.00809222) is a 90 % two-sided confidence 

interval for the BMD 
B-253 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: CNS (Dow Chemical Co., 1992a; Quast et al., 1980b) 

Table B-29. Incidence of CNS tumors in Sprague-Dawley rats exposed to 

AN in air for 2 years 

Sex 

Administered AN concentration 

(ppm in air) 

Predicted CEO-AUC in blood

(mg/L) Incidence of CNS tumorsa

0 0 0/96 (0%) 

20 2.17 × 10-3 Male 4/93 (4%) 

80 8.20 × 10-3 22/82 (27%)b

0 0 0/93 (0%) 

20 2.18 × 10-3 8/99 (8%)b

Female 

80 8.24 × 10-3 20/89 (22%)b

a

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

b

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Table B-30. Summary of BMD modeling results based on incidence of CNS 

tumors in Sprague-Dawley rats exposed to AN in air for 2 years 

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Males

Administered dose 1°MS 0.56 131.64 30.22 ppm 22.23 ppm 

CEO 1°MS 0.50 131.92 3.14 × 10-3 mg/L 2.31 × 10-3 mg/L 

Females 

Administered dose 1°MS 0.80 152.86 30.79 ppm 22.89 ppm 

CEO 1°MS 0.87 152.70 3.21 × 10-3 mg/L 2.39 × 10-3 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-254 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley male rats employing 

administered dose as a dose metric 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 10 20 30 40 50 60 70 80

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

13:18 04/13 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $ 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_CNS_INHALE_PPM.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_CNS_INHALE_PPM.plt 

 Fri Apr 13 13:18:45 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

-beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-255 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 0.00403595 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 Background 0 NA 

 Beta(1) 0.00348587 0.00147454 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -64.1853 

 Fitted model -64.8194 1.26826 2 0.5304 

 Reduced model -85.6554 42.9402 2 <.0001 

 AIC: 131.639 

 Goodness of Fit 

 Dose Est._Prob. Expected Observed Size Chi^2 Res. 

 ----------------------------------------------------------------------- 

i: 1 

 0.0000 0.0000 0.000 0 96 0.000 

i: 2 

 20.0000 0.0673 6.263 4 93 -0.387 

i: 3 

 80.0000 0.2434 19.956 22 82 0.135 

 Chi-square = 1.15 DF = 2 P-value = 0.5617 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 30.225 

 BMDL = 22.2323 
B-256 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley male rats employing 

CEO in blood as an internal dose metric 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:22 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_CNS_INHALE_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_CNS_INHALE_BLOOD_CEO.plt 

 Thu Sep 27 15:22:30 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-257 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0 

 Beta(1) = 39.4721 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 33.5271 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -64.1853 3 

 Fitted model -64.9602 1 1.54975 2 0.4608 

 Reduced model -85.6554 1 42.9402 2 <.0001 

 AIC: 131.92 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 96 0.000 

 0.0022 0.0702 6.525 4 93 -1.025 

 0.0082 0.2404 19.711 22 82 0.592 

 Chi^2 = 1.40 d.f. = 2 P-value = 0.4963

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00314255 

 BMDL = 0.00231159 

 BMDU = 0.00442253 

Taken together, (0.00231159, 0.00442253) is a 90 % two-sided confidence 

interval for the BMD 
B-258 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley female rats 

employing administered dose as a dose metric 

0

0.05

0.1

0.15

0.2

0.25

0.3

0 10 20 30 40 50 60 70 80

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

13:31 04/13 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $ 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_CNS_INHALE_PPM.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_CNS_INHALE_PPM.plt 

 Fri Apr 13 13:31:42 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

-beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-259 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.00947538 

 Beta(1) = 0.00310229 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 Background 0 NA 

 Beta(1) 0.00342189 0.00148795 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -75.2138 

 Fitted model -75.4293 0.431111 2 0.8061 

 Reduced model -91.1284 31.8293 2 <.0001 

 AIC: 152.859 

 Goodness of Fit 

 Dose Est._Prob. Expected Observed Size Chi^2 Res. 

 ----------------------------------------------------------------------- 

i: 1 

 0.0000 0.0000 0.000 0 93 0.000 

i: 2 

 20.0000 0.0661 6.549 8 99 0.237 

i: 3 

 80.0000 0.2395 21.314 20 89 -0.081 

 Chi-square = 0.45 DF = 2 P-value = 0.7982 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 30.7901 

 BMDL = 22.8938 
B-260 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for CNS tumors in Sprague-Dawley female rats 

employing CEO in blood as an internal dose metric 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:38 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_CNS_INHALE_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_CNS_INHALE_BLOOD_CEO.plt 

 Thu Sep 27 15:38:25 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-261 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.00769725 

 Beta(1) = 30.2917 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 32.7805 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -75.2138 3 

 Fitted model -75.3524 1 0.277338 2 0.8705 

 Reduced model -91.1284 1 31.8293 2 <.0001 

 AIC: 152.705 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 93 0.000 

 0.0022 0.0690 6.827 8 99 0.465 

 0.0082 0.2367 21.065 20 89 -0.266 

 Chi^2 = 0.29 d.f. = 2 P-value = 0.8663

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00321413 

 BMDL = 0.00238988 

 BMDU = 0.00446381 

Taken together, (0.00238988, 0.00446381) is a 90 % two-sided confidence 

interval for the BMD 
B-262 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: Zymbal Gland (Dow Chemical Co., 1992a; Quast et al., 1980b)

Table B-31. Incidence of Zymbal gland tumors in Sprague-Dawley rats 

exposed to AN in air for 2 years 

Sex 

Administered AN concentration 

(ppm in air) 

Predicted CEO-AUC in 

blood 

(mg/L) 

Incidence of Zymbal gland 

tumorsa

0 0 2/96 (2%) 

20 2.17 × 10-3 Male 4/93 (4%) 

80 8.20 × 10-3 11/82 (13%)b

0 0 0/93 (0%) 

20 2.18 × 10-3 Female 1/98 (1%) 

80 8.24 × 10-3 11/89 (12%)b

a

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

b

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Table B-32. Summary of BMD modeling results based on incidence of 

Zymbal’s gland tumors in Sprague-Dawley rats exposed to AN in air for 

2 years 

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Males 

Administered dose 1°MS 0.78 121.17 70.29 ppm 42.53 ppm 

CEO 1°MS 0.73 121.21 7.26 × 10-3 mg/L 4.40 × 10-3 mg/L 

Females 

Administered dose 1°MS 0.50 81.47 75.70 ppm 48.74 ppm 

CEO 1°MS 0.46 81.67 7.90 × 10-3 mg/L 5.09 × 10-3 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-263 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats 

employing administered dose as a dose metric 

0

0.05

0.1

0.15

0.2

0 10 20 30 40 50 60 70 80

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

13:22 04/13 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $ 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_ZYMBAL_INHALE_PPM.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_ZYMBAL_INHALE_PPM.plt 

 Fri Apr 13 13:22:06 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

-beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-264 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0172853 

 Beta(1) = 0.00156747 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.66 

 Beta(1) -0.66 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 Background 0.0193054 0.0819561 

 Beta(1) 0.00149893 0.00187956 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -58.5432 

 Fitted model -58.5838 0.0811571 1 0.7757 

 Reduced model -63.5267 9.9669 2 0.00685 

 AIC: 121.168 

 Goodness of Fit 

 Dose Est._Prob. Expected Observed Size Chi^2 Res. 

 ----------------------------------------------------------------------- 

i: 1 

 0.0000 0.0193 1.853 2 96 0.081 

i: 2 

 20.0000 0.0483 4.489 4 93 -0.114 

i: 3 

 80.0000 0.1301 10.670 11 82 0.036 

 Chi-square = 0.08 DF = 1 P-value = 0.7780 
B-265 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 70.2907 

 BMDL = 42.5347 
B-266 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats 

employing CEO in blood as an internal dose metric 

0

0.05

0.1

0.15

0.2

0.25

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:25 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_ZYMBAL_INHALE_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_ZYMBAL_INHALE_BLOOD_CEO.plt 

 Thu Sep 27 15:25:06 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-267 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0165179 

 Beta(1) = 15.3411 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.66 

 Beta(1) -0.66 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0190621 * * * 

 Beta(1) 14.5086 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -58.5432 3 

 Fitted model -58.6032 2 0.120008 1 0.729 

 Reduced model -63.5267 1 9.9669 2 0.00685 

 AIC: 121.206 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0191 1.830 2 96 0.127 

 0.0022 0.0495 4.600 4 93 -0.287 

 0.0082 0.1291 10.586 11 82 0.136 

 Chi^2 = 0.12 d.f. = 1 P-value = 0.7323

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00726195 

 BMDL = 0.00440461 

 BMDU = 0.0159076 

Taken together, (0.00440461, 0.0159076) is a 90 % two-sided confidence 

interval for the BMD 
B-268 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats 

employing administered dose as a dose metric

0

0.05

0.1

0.15

0.2

0 10 20 30 40 50 60 70 80

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

13:35 04/13 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $ 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_ZYMBAL_INHALE_PPM.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_ZYMBAL_INHALE_PPM.plt 

 Fri Apr 13 13:35:30 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

-beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-269 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 0.0017365 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 Background 0 NA 

 Beta(1) 0.00139182 0.00127839 

NA - Indicates that this parameter has hit a bound 

 implied by some inequality constraint and thus

 has no standard error. 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -38.8683 

 Fitted model -39.7334 1.73007 2 0.421 

 Reduced model -49.5377 21.3387 2 <.0001 

 AIC: 81.4668 

 Goodness of Fit 

 Dose Est._Prob. Expected Observed Size Chi^2 Res. 

 ----------------------------------------------------------------------- 

i: 1 

 0.0000 0.0000 0.000 0 93 0.000 

i: 2 

 20.0000 0.0275 2.690 1 98 -0.646 

i: 3 

 80.0000 0.1054 9.378 11 89 0.193 

 Chi-square = 1.41 DF = 2 P-value = 0.4952 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 75.6997 

 BMDL = 48.7384 
B-270 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats 

employing CEO in blood as an internal dose metric 

0

0.05

0.1

0.15

0.2

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:41 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_ZYMBAL_INHALE_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_ZYMBAL_INHALE_BLOOD_CEO.plt 

 Thu Sep 27 15:41:40 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-271 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0 

 Beta(1) = 16.8864 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Background 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Beta(1) 

 Beta(1) 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0 * * * 

 Beta(1) 13.3383 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -38.8683 3 

 Fitted model -39.8337 1 1.93077 2 0.3808 

 Reduced model -49.5377 1 21.3387 2 <.0001 

 AIC: 81.6675 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0000 0.000 0 93 0.000 

 0.0022 0.0287 2.808 1 98 -1.095 

 0.0082 0.1041 9.263 11 89 0.603 

 Chi^2 = 1.56 d.f. = 2 P-value = 0.4579

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00789912 

 BMDL = 0.00508579 

 BMDU = 0.0132303 

Taken together, (0.00508579, 0.0132303) is a 90 % two-sided confidence 

interval for the BMD 
B-272 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: Tongue (Dow Chemical Co., 1992a; Quast et al., 1980b)

Table B-33. Incidence of tongue tumors in Sprague-Dawley rats exposed to 

AN in air for 2 years 

Sex 

Administered AN concentration 

(ppm in air) 

Predicted CEO-AUC in blood

(mg/L) Incidence of tongue tumorsa

0 0 1/95 (1%) 

20 2.17 × 10-3 Male 0/14 (0%) 

80 8.20 × 10-3 7/82 (9%)b

a

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

b

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Table B-34. Summary of BMD modeling results based on incidence of 

tongue tumors in Sprague-Dawley rats exposed to AN in air for 2 years

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Males 

Administered 

dose 1°MS 0.51 63.76 111.06 ppm 59.41 ppm 

CEO 2°MS 0.63 63.37 9.48 × 10-3 mg/L 6.39 × 10-3 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model. 

“2°MS” indicates a two-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-273 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for tongue tumors in Sprague-Dawley male rats employing 

administered dose as a dose metric

0

0.05

0.1

0.15

0.2

0 20 40 60 80 100 120

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

13:25 04/13 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $ 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_TONGUE_INHALE_PPM.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_TONGUE_INHALE_PPM.plt 

 Fri Apr 13 13:25:25 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

-beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-274 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 0.00109944 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.65 

 Beta(1) -0.65 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 Background 0.00947867 0.0968926 

 Beta(1) 0.000948673 0.00186696 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -29.4666 

 Fitted model -29.8775 0.821799 1 0.3647 

 Reduced model -33.2127 7.49227 2 0.02361 

 AIC: 63.755 

 Goodness of Fit 

 Dose Est._Prob. Expected Observed Size Chi^2 Res. 

 ----------------------------------------------------------------------- 

i: 1 

 0.0000 0.0095 0.900 1 95 0.112 

i: 2 

 20.0000 0.0281 0.393 0 14 -1.029 

i: 3 

 80.0000 0.0819 6.713 7 82 0.046 

 Chi-square = 0.43 DF = 1 P-value = 0.5124 
B-275 DRAFT- DO NOT CITE OR QUOTE 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 111.061 

 BMDL = 59.4126 
B-276 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for tongue tumors in Sprague-Dawley male rats employing 

CEO in blood as an internal dose metric

0

0.05

0.1

0.15

0.2

0.25

0 0.002 0.004 0.006 0.008

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:28 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_TONGUE_INHALE_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_MALE_TONGUE_INHALE_BLOOD_CEO.plt 

 Thu Sep 27 15:28:11 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-277 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.00257667 

 Beta(1) = 0 

 Beta(2) = 1279.63 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.64 

 Beta(2) -0.64 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.00925756 * * * 

 Beta(1) 0 * * * 

 Beta(2) 1172.26 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -29.4666 3 

 Fitted model -29.6826 2 0.431994 1 0.511 

 Reduced model -33.2127 1 7.49227 2 0.02361 

 AIC: 63.3652 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0093 0.879 1 95 0.129 

 0.0022 0.0147 0.206 0 14 -0.457 

 0.0082 0.0844 6.917 7 82 0.033 

 Chi^2 = 0.23 d.f. = 1 P-value = 0.6339

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.0094804 

 BMDL = 0.00638558 

 BMDU = 0.0279407 

Taken together, (0.00638558, 0.0279407) is a 90 % two-sided confidence 

interval for the BMD 
B-278 DRAFT- DO NOT CITE OR QUOTE 

Tumor Site: Mammary Gland (Dow Chemical Co., 1992a; Quast et al., 1980b) 

Table B-35. Incidence of mammary gland tumors in Sprague-Dawley rats 

exposed to AN in air for 2 years 

Sex 

Administered AN concentration 

(ppm in air) 

Predicted CEO-AUC in 

blood 

(mg/L) 

Incidence of mammary gland 

tumorsa

0 0 9/93 (10%) 

20 2.18 × 10-3 Female 8/98 (8%) 

80 8.24 × 10-3 20/99 (20%)b

a

Incidences for Sprague-Dawley rats do not include animals from the 6- and 12-mo sacrifices and were further 

adjusted to exclude (from the denominators) rats that died between 0 and 12 mos in the study. 

b

Significantly different from controls (p < 0.05) as calculated by the study authors. 

Table B-36. Summary of BMD modeling results based on incidence of 

mammary gland tumors in Sprague-Dawley rats exposed to AN in air for 

2 years

Dose metric Best-fit modela

χ

2

p-valueb AIC BMD10

c BMDL10d

Females 

Administered dose 1°MS 0.28 219.42 66.48 ppm 37.82 ppm 

CEO 2°MS 0.57 218.52 7.31 × 10-3 mg/L 4.33 × 10-3 mg/L 

aDose-response models were fit using BMDS, version 1.4.1. “1°MS” indicates a one-stage multistage model. 

“2°MS” indicates a two-stage multistage model. 

b

p value from the χ

2

 goodness of fit test. Values <0.1 indicate a significant lack of fit. 

cBMD10 = BMD at 10% extra risk. 

dBMDL10 = 95% lower confidence limit on the BMD at 10% extra risk. 
B-279 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for mammary gland tumors in Sprague-Dawley female rats 

employing administered dose as a dose metric

0.05

0.1

0.15

0.2

0.25

0.3

0 10 20 30 40 50 60 70 80

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

13:38 04/13 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $ 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_MAMMARY_INHALE_PPM.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_MAMMARY_INHALE_PPM.plt 

 Fri Apr 13 13:38:03 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

-beta1*dose^1)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 2 

 Total number of specified parameters = 0 

 Degree of polynomial = 1 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 
B-280 DRAFT- DO NOT CITE OR QUOTE 

 Default Initial Parameter Values 

 Background = 0.0767126 

 Beta(1) = 0.00173168 

 Asymptotic Correlation Matrix of Parameter Estimates 

 Background Beta(1) 

Background 1 -0.68 

 Beta(1) -0.68 1 

 Parameter Estimates 

 Variable Estimate Std. Err. 

 Background 0.0806351 0.0783644 

 Beta(1) 0.00158474 0.00179372 

 Analysis of Deviance Table 

 Model Log(likelihood) Deviance Test DF P-value 

 Full model -107.092 

 Fitted model -107.71 1.23579 1 0.2663 

 Reduced model -110.714 7.24319 2 0.02674 

 AIC: 219.421 

 Goodness of Fit 

 Dose Est._Prob. Expected Observed Size Chi^2 Res. 

 ----------------------------------------------------------------------- 

i: 1 

 0.0000 0.0806 7.499 9 93 0.218 

i: 2 

 20.0000 0.1093 10.713 8 98 -0.284 

i: 3 

 80.0000 0.1901 18.820 20 99 0.077 

 Chi-square = 1.19 DF = 1 P-value = 0.2754 

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 66.4843 

 BMDL = 37.8172 
B-281 DRAFT- DO NOT CITE OR QUOTE 

BMDS (version 1.4.1) output for mammary gland tumors in Sprague-Dawley female rats 

employing CEO in blood as an internal dose metric

0.05

0.1

0.15

0.2

0.25

0.3

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008

Fraction Affected

dose

Multistage Model with 0.95 Confidence Level

15:44 09/27 2007

BMDL BMD

 

Multistage

 ==================================================================== 

 Multistage Model. (Version: 2.8; Date: 02/20/2007) 

 Input Data File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_MAMMARY_INHALE_BLOOD_CEO.(d) 

 Gnuplot Plotting File: G:\ACN DOSE-RESPONSE 

MODELING\CANCER\INHALATION\SD_FEMALE_MAMMARY_INHALE_BLOOD_CEO.plt 

 Thu Sep 27 15:44:26 2007 

 ==================================================================== 

 BMDS MODEL RUN 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

 

 The form of the probability function is: 

 P[response] = background + (1-background)*[1-EXP( 

 -beta1*dose^1-beta2*dose^2)] 

 The parameter betas are restricted to be positive 

 Dependent variable = Response 

 Independent variable = Dose 

 Total number of observations = 3 

 Total number of records with missing values = 0 

 Total number of parameters in model = 3 

 Total number of specified parameters = 0 

 Degree of polynomial = 2 

 Maximum number of iterations = 250 

 Relative Function Convergence has been set to: 1e-008 

 Parameter Convergence has been set to: 1e-008 

 Default Initial Parameter Values 
B-282 DRAFT- DO NOT CITE OR QUOTE 

 Background = 0.0853385 

 Beta(1) = 0 

 Beta(2) = 1996.34 

 Asymptotic Correlation Matrix of Parameter Estimates 

 ( *** The model parameter(s) -Beta(1) 

 have been estimated at a boundary point, or have been specified by the user, 

 and do not appear in the correlation matrix ) 

 Background Beta(2) 

Background 1 -0.6 

 Beta(2) -0.6 1 

 Parameter Estimates 

 95.0% Wald Confidence Interval 

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 

 Background 0.0856208 * * * 

 Beta(1) 0 * * * 

 Beta(2) 1971.76 * * * 

* - Indicates that this value is not calculated. 

 Analysis of Deviance Table 

 Model Log(likelihood) # Param's Deviance Test d.f. P-value 

 Full model -107.092 3 

 Fitted model -107.258 2 0.332027 1 0.5645 

 Reduced model -110.714 1 7.24319 2 0.02674 

 AIC: 218.517 

 Goodness of Fit 

 Scaled 

 Dose Est._Prob. Expected Observed Size Residual 

 ------------------------------------------------------------------------ 

 0.0000 0.0856 7.963 9 93 0.384 

 0.0022 0.0941 9.226 8 98 -0.424 

 0.0082 0.2002 19.818 20 99 0.046 

 Chi^2 = 0.33 d.f. = 1 P-value = 0.5658

 Benchmark Dose Computation 

Specified effect = 0.1 

Risk Type = Extra risk 

Confidence level = 0.95 

 BMD = 0.00730992 

 BMDL = 0.00432882 

 BMDU = 0.0152838 

Taken together, (0.00432882, 0.0152838) is a 90 % two-sided confidence 

interval for the BMD 
B-283 DRAFT- DO NOT CITE OR QUOTE 

APPENDIX B-5. ANALYSIS TO ASSESS COMBINING TUMOR INCIDENCE DATA 

FROM TWO CANCER BIOASSAYS EMPLOYING SPRAGUE-DAWLEY RATS 

A statistical analysis was conducted to determine whether tumor dose-response data from 

two 2-year drinking water bioassays in Sprague-Dawley rats were similar enough to be 

combined. The first study employed AN drinking water concentrations of 0, 35, 100, and 

300 ppm (Quast, 2002; Quast et al., 1980a), while the second study used AN drinking water 

concentrations of 0, 1, and 100 ppm (Johannsen and Levinskas, 2002a). To conduct the analysis, 

the multistage model in BMDS (version 1.3.2) was fit to the tumor incidence data from three 

sites (forestomach, CNS, and Zymbal gland) in each sex across both studies, using administered 

animal dose expressed in mg/kg-day. Using the best-fit model, a statistical test described by 

Stiteler et al. (1993), which employs a maximum likelihood ratio statistic distributed as a χ

2

, was 

then used to test the null hypothesis that the corresponding data sets from the two studies are 

compatible with a common dose-response model. If the null hypothesis is not rejected, this 

analysis provides evidence that the results from the two studies may be pooled. 

The results of this analysis showed that forestomach and Zymbal gland tumors in male 

and female Sprague-Dawley rats were not compatible with a common dose-response model, 

while CNS tumors in male and female Sprague-Dawley rats were compatible with a common 

dose-response model. Because of these conflicting results, it was decided that the results from 

the two Sprague-Dawley drinking water studies would not be pooled. Therefore, the final doseresponse analysis for deriving the oral slope factor for AN focused on the two rat drinking water 

studies containing the most dose groups (i.e., the Sprague-Dawley rat bioassay reported by Quast 

[2002] and the F344 rat bioassay reported by Johannsen and Levinskas [2002b]). For each tumor 

site, summaries of the results of the statistical tests for compatibility are shown below. 

Test 1: Forestomach tumors in male Sprague-Dawley rats 

Tumor incidence data (Johannsen and Levinskas, 2002a): 

• 0 ppm (0 mg/kg-day): 3/78 

• 1 ppm (0.085 mg/kg-day): 3/78 

• 100 ppm (8.53 mg/kg-day): 11/77 

Best-fit model: 1-stage multistage 

Log (likelihood) = –57.0113 

Tumor incidence data (Quast, 2002): 

• 0 ppm (0 mg/kg-day): 0/80 

• 35 ppm (3.42 mg/kg-day): 2/47 
B-284 DRAFT- DO NOT CITE OR QUOTE 

• 100 ppm (8.53 mg/kg-day): 23/48 

• 300 ppm (21.20 mg/kg-day): 39/48 

Best-fit model: 2-stage multistage (highest dose group dropped) 

Log (likelihood) = –42.4099 

Tumor incidence data (combined): 

• 0 ppm (0 mg/kg-day): 3/158 

• 1 ppm (0.085 mg/kg-day): 3/78 

• 35 ppm (3.42 mg/kg-day): 2/47 

• 100 ppm (8.53 mg/kg-day): 34/125 

• 300 ppm (21.20 mg/kg-day): 39/48 

Best-fit model: 2-stage multistage 

Log (likelihood) = –132.865 

Conclusion: Based on the likelihood ratio test statistic, –2 ln Λ = 2[132.865 – (42.4099 + 

57.0113)] = 2 × 33.4438 = 66.89, the data sets are not compatible with a common dose-response 

model at p < 0.0001. 

 

Test 2: Forestomach tumors in female Sprague-Dawley rats 

Tumor incidence data (Johannsen and Levinskas, 2002a): 

• 0 ppm (0 mg/kg-day): 1/80 

• 1 ppm (0.11 mg/kg-day): 4/79 

• 100 ppm (10.80 mg/kg-day): 7/79 

Best-fit model: 1-stage multistage 

Log (likelihood) = –45.8328 

Tumor incidence data (Quast, 2002): 

• 0 ppm (0 mg/kg-day): 1/80 

• 35 ppm (4.36 mg/kg-day): 1/48 

• 100 ppm (10.80 mg/kg-day): 12/48 

• 300 ppm (25.00 mg/kg-day): 30/48 

Best-fit model: 2-stage multistage 

Log (likelihood) = –69.9834 
B-285 DRAFT- DO NOT CITE OR QUOTE 

Tumor incidence data (combined): 

• 0 ppm (0 mg/kg-day): 2/160 

• 1 ppm (0.11 mg/kg-day): 4/79 

• 35 ppm (4.36 mg/kg-day): 1/48 

• 100 ppm (10.80 mg/kg-day): 19/127 

• 300 ppm (25.00 mg/kg-day): 30/48 

Best-fit model: 2-stage multistage 

Log (likelihood) = –119.054 

Conclusion: Based on the likelihood ratio test statistic, –2 ln Λ = 2[119.054 – (69.9834 + 

45.8328)] = 2 × 3.2378 = 6.48, the data sets are not compatible with a common dose-response 

model at p = 0.011. 

 

Test 3: CNS tumors in male Sprague-Dawley rats 

Tumor incidence data (Johannsen and Levinskas, 2002a): 

• 0 ppm (0 mg/kg-day): 2/78 

• 1 ppm (0.085 mg/kg-day): 3/75 

• 100 ppm (8.53 mg/kg-day): 23/77 

Best-fit model: 1-stage multistage 

Log (likelihood) = –68.9254 

Tumor incidence data (Quast, 2002): 

• 0 ppm (0 mg/kg-day): 1/80 

• 35 ppm (3.42 mg/kg-day): 12/47 

• 100 ppm (8.53 mg/kg-day): 22/48 

• 300 ppm (21.20 mg/kg-day): 30/48 

Best-fit model: 1-stage multistage 

Log (likelihood) = –98.6909 

Tumor incidence data (combined): 

• 0 ppm (0 mg/kg-day): 3/158 

• 1 ppm (0.085 mg/kg-day): 3/75 
B-286 DRAFT- DO NOT CITE OR QUOTE 

• 35 ppm (3.42 mg/kg-day): 12/47 

• 100 ppm (8.53 mg/kg-day): 45/125 

• 300 ppm (21.20 mg/kg-day): 30/48 

Best-fit model: 1-stage multistage 

Log (likelihood) = –168.873 

Conclusion: Based on the likelihood ratio test statistic, –2 ln Λ = 2[168.873 – (98.6909 + 

68.9254)] = 2 × 1.2567 = 2.51, the data sets are compatible with a common dose-response model 

at p = 0.113. 

 

Test 4: CNS Tumors in female Sprague-Dawley rats 

Tumor incidence data (Johannsen and Levinskas, 2002a): 

• 0 ppm (0 mg/kg-day): 0/79 

• 1 ppm (0.11 mg/kg-day): 1/80 

• 100 ppm (10.80 mg/kg-day): 39/78 

Best-fit model: 1-stage multistage 

Log (likelihood) = –59.5775 

Tumor incidence data (Quast, 2002): 

• 0 ppm (0 mg/kg-day): 1/80 

• 35 ppm (4.36 mg/kg-day): 20/48 

• 100 ppm (10.80 mg/kg-day): 25/48 

• 300 ppm (25.00 mg/kg-day): 31/48 

Best-fit model: Log-logistic 

Log (likelihood) = –104.123 

Tumor incidence data (combined): 

• 0 ppm (0 mg/kg-day): 1/159 

• 1 ppm (0.11 mg/kg-day): 1/80 

• 35 ppm (4.36 mg/kg-day): 20/48 

• 100 ppm (10.80 mg/kg-day): 64/126 

• 300 ppm (25.00 mg/kg-day): 31/48 

Best-fit model: Log-logistic 
B-287 DRAFT- DO NOT CITE OR QUOTE 

Log (likelihood) = –164.485 

Conclusion: Based on the likelihood ratio test statistic, –2 ln Λ = 2[164.485 – (104.123 + 

59.5775)] = 2 × 0.7845 = 1.57, the data sets are compatible with a common dose-response model 

at p = 0.210. 

Test 5: Zymbal gland tumors in male Sprague-Dawley rats 

Tumor incidence data (Johannsen and Levinskas, 2002a): 

• 0 ppm (0 mg/kg-day): 1/80 

• 1 ppm (0.085 mg/kg-day): 0/71 

• 100 ppm (8.53 mg/kg-day): 17/73 

Best-fit model: 1-stage multistage 

Log (likelihood) = –45.815 

Tumor incidence data (Quast, 2002): 

• 0 ppm (0 mg/kg-day): 3/80 

• 35 ppm (3.42 mg/kg-day): 4/47 

• 100 ppm (8.53 mg/kg-day): 3/48 

• 300 ppm (21.20 mg/kg-day): 16/48 

Best-fit model: 1-stage multistage 

Log (likelihood) = –70.1142 

Tumor incidence data (combined): 

• 0 ppm (0 mg/kg-day): 4/160 

• 1 ppm (0.085 mg/kg-day): 0/71 

• 35 ppm (3.42 mg/kg-day): 4/47 

• 100 ppm (8.53 mg/kg-day): 20/121 

• 300 ppm (21.20 mg/kg-day): 16/48 

Best-fit model: 1-stage multistage 

Log (likelihood) = –118.806 

Conclusion: Based on the likelihood ratio test statistic, –2 ln Λ = 2[118.806 – (70.1142 + 

45.815)] = 2 × 2.8768 = 5.75, the data sets are not compatible with a common dose-response 

model at p = 0.016. 
B-288 DRAFT- DO NOT CITE OR QUOTE 

 

Test 6: Zymbal gland tumors in female Sprague-Dawley rats 

Tumor incidence data (Johannsen and Levinskas, 2002a): 

• 0 ppm (0 mg/kg-day): 1/79 

• 1 ppm (0.11 mg/kg-day): 0/75 

• 100 ppm (10.80 mg/kg-day): 12/78 

Best-fit model: 1-stage multistage 

Log (likelihood) = –39.6428 

Tumor incidence data (Quast, 2002): 

• 0 ppm (0 mg/kg-day): 1/80 

• 35 ppm (4.36 mg/kg-day): 5/48 

• 100 ppm (10.80 mg/kg-day): 9/48 

• 300 ppm (25.00 mg/kg-day): 18/48 

Best-fit model: 1-stage multistage 

Log (likelihood) = –76.3975 

Tumor incidence data (combined): 

• 0 ppm (0 mg/kg-day): 1/159 

• 1 ppm (0.11 mg/kg-day): 0/75 

• 35 ppm (4.36 mg/kg-day): 5/48 

• 100 ppm (10.80 mg/kg-day): 21/126 

• 300 ppm (25.00 mg/kg-day): 18/48 

Best-fit model: 1-stage multistage 

Log (likelihood) = –111.439 

Conclusion: Based on the likelihood ratio test statistic, –2 ln Λ = 2[111.439 – (76.3975 + 

39.6428)] = 2 × (–4.6013) = –9.20 = 9.20, the data sets are not compatible with a common doseresponse model at p = 0.002. 
B-289 DRAFT- DO NOT CITE OR QUOTE 

APPENDIX B-6. ESTIMATION OF COMPOSITE CANCER RISK FROM EXPOSURE 

TO AN BY COMBINING RISK ESTIMATES ACROSS MULTIPLE TUMOR SITES 

Increased tumor incidences were observed at multiple sites in male and female rats 

following exposure to AN both orally and by inhalation. With this multiplicity of tumors, the 

concern is that a potency or risk estimate based solely on one tumor site (e.g., the most sensitive 

site) may underestimate the overall cancer risk associated with exposure to this chemical. The 

most recent EPA cancer guidelines (U.S. EPA, 2005a) identified two ways to approach this 

issue: 1) analyze the incidence of tumor-bearing animals, or 2) combine the potencies associated 

with significantly elevated tumors at each site. The NRC (1994) concluded that an approach 

based on counts of animals with one or more tumors would tend to underestimate overall risk 

when tumor types occur independently, and thus an approach based on combining the risk 

estimates from each separate tumor type should be used. 

Because potencies are typically upper bound estimates, summing such upper bound 

estimates across tumor sites is likely to overstate the overall risk. Therefore, following the 

recommendations of the NRC (1994) and the Guidelines for Carcinogen Risk Assessment (U.S. 

EPA, 2005a), a statistically valid upper bound on combined risk was derived in order to gain 

some understanding of the overall risk resulting from tumors occurring at multiple sites. It is 

important to note that this estimate of overall potency describes the risk of developing tumors at 

any combination of the sites considered and is not the risk of developing tumors at all three sites 

simultaneously. 

For modeling individual tumor data, the multistage model is specified as follows: 

(1) P(d) = 1 - exp[-(q0 + q1d + q2d

2

 + ... + qmd

m

)].

The model for the combined (or composite) tumor risk is still multistage, with a 

functional form that has the sum of stage-specific multistage coefficients as the corresponding 

multistage coefficient. 

(2) Pc(d) = 1 - exp[-(Σq0i + dΣq1i + d2Σq2i + ... + dmΣqmi)], for i=1,..., k, 

where k = total number of sites 

The resulting equation for fixed extra risk (BMR) is polynomial in dose (when logarithms 

of both sides are taken) and can be straightforwardly solved for the combined BMD. However, 

confidence bounds for this BMD are not able to be estimated by the current version of BMDS. 

Therefore, a Bayesian approach to finding confidence bounds on the combined BMD was 

implemented using WinBugs (Spiegelhalter et al., 2003). WinBugs software is freely available 

and implements Markov chain Monte Carlo (MCMC) computations. Use of WinBugs has been 
B-290 DRAFT- DO NOT CITE OR QUOTE 

demonstrated for derivation of a distribution of BMDs for a single multistage model (Kopylev et 

al., 2007) and can be straightforwardly generalized to derive the distribution of BMDs for the 

combined tumor load, following the NRC (1994) methodology described above. The advantage 

of a Bayesian approach is that it produces a distribution of BMDs that allows better 

characterization of statistical uncertainty. For the current analysis, a diffuse (high variance or 

low tolerance) Gaussian prior restricted to be nonnegative was used. The posterior distribution 

was based on three chains with 50,000 burn-in (i.e., the initial 50,000 simulations were dropped) 

and a thinning rate of 20, resulting in 150,000 simulations total. The median and 5th percentile of 

the posterior distribution provided the BMD10 (central estimate) and BMDL10 (lower bound) for 

combined tumor load, respectively. 

The methodology above was applied to the dose-response data for the male and female 

Sprague-Dawley (Quast, 2002) and F344 (Johannsen and Levinskas, 2002b) rat drinking water 

studies, as well as to the data from male and female Sprague-Dawley rats in the Quast et al. 

(1980b) inhalation study. As with the risk estimates generated for individual tumor sites, the 

combined analysis used the internal dose metric CEO in blood (see Appendices B-3 and B-4). 

The human equivalent PODs are presented in Tables B-37 (episodic oral exposure) and B-38 

(continuous inhalation exposure). Estimates of composite risk were estimated by dividing the 

BMR of 10% extra risk by the composite BMDL10s (0.1/BMDL10). Human equivalent 

composite CSFs are presented in Table B-39, and composite unit risks are presented in 

Table B-40. The slopes derived from the composite BMD10s (0.1/ BMD10) are also included in 

these tables for comparison. 
B-291 DRAFT- DO NOT CITE OR QUOTE 

 

Table B-37. Summary of PODs for composite cancer risk associated with 

episodic oral exposure to AN, using CEO-AUC levels in blood as dose metric 

and multiple tumor incidence data in rats 

PODs based on rat dose-response 

using internal dose metric CEOAUC in blood (mg/L) Human equivalent PODsa

Rat strain, sex (mg/kg-d)

Tumor site BMD10 BMDL10 BMD10 BMDL10

Sprague-Dawley, male 

Forestomach, CNS, Zymbal gland, 

tongue 

4.2 × 10-4 3.6 × 10-4 0.042 0.036 

Sprague-Dawley, female 

Forestomach, CNS, Zymbal gland, 

tongue, mammary gland

2.6 × 10-4 2.0 × 10-4 0.026 0.020 

F344, male 

Forestomach, CNS, Zymbal gland 4.6 × 10-4 3.3 × 10-4 0.046 0.033 

F344, female 

Forestomach, CNS, Zymbal gland, 

mammary gland

6.7 × 10-4 5.2 × 10-4 0.066 0.051 

aConverted using human PBPK model. 

Table B-38. Summary of PODs for composite cancer risk associated with 

inhalation exposure to AN, based on multiple tumor incidence data in rats 

and CEO-AUC levels in blood 

PODs for rat dose-response in 

terms of CEO-AUC in blood 

(mg/L) 

 Human equivalent PODs: 

AN in aira 

(mg/m3

Rat strain, sex ) 

Tumor site BMC10 BMCL10 BMC10 BMCL10

Sprague-Dawley, male 

Intestine, CNS, Zymbal gland, tongue 1.4 × 10-3 1.1 × 10-3 1.9 1.5 

Sprague-Dawley, female 

CNS, Zymbal gland, mammary gland 1.7 × 10-3 1.3 × 10-3 2.3 1.8 

aConverted using human PBPK model. 
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Table B-39. Estimated human oral CSFs for AN based on multiple tumor 

incidence data in rats and CEO-AUC levels in blood 

Rat strain, sex 

Tumor site 

Slope derived from composite 

BMD10

a 

(mg/kg-d)-1

Composite CSFb

(mg/kg-d)-1

Sprague-Dawley, male 

Forestomach, CNS, Zymbal gland, tongue 2.4 2.8 

Sprague-Dawley, female 

Forestomach, CNS, Zymbal gland, tongue, 

mammary gland

3.8 5.0 

F344, male 

Forestomach, CNS, Zymbal gland 2.2 3.1 

F344, female 

Forestomach, CNS, Zymbal gland, 

mammary gland

1.5 1.9 

a

Slope estimated by 0.1/BMD10. 

bCSF = 0.1/BMDL10. 

Table B-40. Estimated human IURs for AN based on multiple tumor 

incidence data in rats and CEO-AUC levels in blood 

Rat strain, sex

Tumor site 

Slope to background from 

overall BMC10

a 

(mg/m3)

-1

Overall IURb 

(mg/m3)

-1

Sprague-Dawley, male 

Intestine, CNS, Zymbal gland, 

tongue 

5.4 × 10-2 6.8 × 10-2

Sprague-Dawley, female 

CNS, Zymbal gland, mammary gland 4.4 × 10-2 5.7 × 10-2

a

Slope estimated by 0.1/BMD10. 

b

IUR = 0.1/BMDL10. 
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APPENDIX B-7. STATISTICAL ANALYSIS OF BLAIR ET AL. (1998) 

The Data 

 The data used in this analysis came from the best available epidemiological study (see 

Section 5.4.1) by Blair et al. (1998). The raw data from the study were provided to EPA 

courtesy of NCI. The process of data collection is described in Blair et al. (1998) and in more 

detail in Stewart et al. (1998). The full raw data set contains 363 variables on 25,460 subjects. 

The variables include demographic information, employment information, vital status, and 

various measures of exposure per study year (1942–1983), including maximum and minimum 

estimates, “best estimate,” frequency of peaks, and several other ways of measuring exposure. 

The raw data provided by NCI did not include the smoking data that were collected for 

approximately 10% of the subjects. Therefore, smoking information was not part of the EPA's 

statistical analysis. The uncertainty connected to lack of smoking information is discussed in 

Section 5.4.5.2. The data on dates of exposure and corresponding exposure amounts, dates of 

mortality due to lung cancer and other causes, a plant worked, and the birth year were retained 

for the statistical analysis. Biological age was chosen as a time scale. Data handling and 

statistical analysis were performed using S-PlusTM statistical software. 

The Statistical Model 

 The semi-parametric Cox proportional hazards model (Cox, 1972) is a widely used model 

in hazard regression. The Cox model with time-dependent covariates was chosen to model the 

data for to two main reasons. Primarily, it allows taking into account individual covariate 

history, allowing utilization of the extensive exposure data collected by Blair et al. (1998). 

Additionally, the Cox model uses internal controls. Internal controls constitute an appropriate 

comparison group, given the healthy worker effect observed by Blair et al. (1998) and further 

demonstrated by Marsh et al. (2001). 

 In the Cox model, the conditional hazard function, given the covariate process Z(t), is 

assumed to have the form: 

λ( | ( )) ( )exp( ( )) t Z t t Z t = λ0 β

T

where β is the vector of regression coefficients and λ0(t) denotes the baseline hazard function. 

No particular shape is assumed for the baseline hazard; it is estimated nonparametrically. The 

contributions of covariates to the hazard are multiplicative. When β

T

Z(t) is small and Z(t) 

represents exposure, the Cox proportional model is consistent with linearity of dose-response for 

low doses. When no time-dependent covariates are present, the cumulative hazard function Λ0(t) 

is estimated using a Breslow (Breslow, 1974) estimator: 
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$

exp( $)

( )

{ : }

Λ0 =

∈

≤ ∑

∑

d

Z

i

T

j

j R t

i t t

i

i β

where Zj

 is the (time-independent) covariate vector of the j

th individual at age ti

, 

$β is an estimate 

of β from the Cox model, di is the number of deaths at the age ti, and R(ti) is the risk set at age ti. 

Risk set is defined as all the individuals who are under observation and at risk of death at age ti

. 

The Breslow estimator is piecewise constant with discrete jumps at times of death. The 

corresponding estimate of the baseline hazard function is the size of the jump of the cumulative 

hazard at ages of death and zero otherwise. The survival function S(t) = exp(-Λ(t)) is estimated 

by plugging in the Breslow estimator: 

S(t) = exp(- (t)) $ Λ$

The cumulative probability of death R(t) = 1-S(t) is estimated by: 

R(t) = 1- S(t) $ $

With time-dependent covariates, EPA followed the suggestion by Starr (2004) of a modified 

Breslow estimator: 

d

Z t

i

T

j i

j R t

i t t

i

i exp( $

( ))

( )

{ : } β

∈

≤ ∑

∑

 The survival function and cumulative probability of death are then estimated using the 

modified cumulative hazard estimator. The modified estimator only approximates the true 

cumulative hazard since a covariate path is not encountered in the estimator. Therneau and 

Grambsch (2000) discuss clinical examples when this estimator could lead to inappropriate 

results, but the occupational case is very different from clinical examples, since at the baseline, 

not all workers are exposed and exposure is nondecreasing and often ends well before death. 
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Calculations of Excess Risk 

 Following Starr et al. (2004), EPA defined hazard functions for lung cancer mortality 

λ

lc(t) and other causes of death λoc(t), with the corresponding cause-specific cumulative hazard 

functions, Λ

lc (t) and Λoc(t). The sum of Λlc(t) and Λoc(t) is the all-causes mortality hazard 

Λ

ac(t) with corresponding survival function Sac(t). Then, the cumulative risk of lung cancer 

mortality by age t, given covariate path Z(t)=z(t) is: 

R t z t u z t S u z t lc lc ac

u t

( | ( )) ( | ( )) ( | ( )) =

≤

∑λ

The cumulative risk of lung cancer mortality by age t in the absence of exposure: 

R t Z t u Z t S u Z t lc lc ac

u t

( | ( ) ) ( | ( ) ) ( | ( ) ) = = = =

≤

0 0 0 ∑λ

Excess risk, given covariate path Z(t)=z(t), is calculated by: 

R t Z t z t R t Z t

R t Z t

lc lc

lc

( | ( ) ( )) ( | ( ) )

( | ( ) )

= − =

− =

0

1 0

When z t T lc ( ) β << 1 and β

oc

≈ 0 , the first order expansion of the numerator simplifies into 

approximately: 

β λ λ

lc lc ac

u t

lc

v u

( | ( ) ) ( | ( ) ) ( ) ( ) ( | ( ) ) u z t S u z t z u z v v z t = = − =











≤ ≤ 

∑ ∑ 0 0 0

Plugging in estimates of β, hazard rate, and survival function into the equation above, an estimate 

of excess risk is obtained. Using estimated UCL on β instead of β results in the upper confidence 

bound on the estimated risk. 

Results 

 Model Choice. There were not enough lung cancer deaths in other than white males sexrace groups, so sex and race were not included as covariates. Including time-independent 

covariates, such as duration and average exposure, was investigated, but time-dependent 

cumulative exposure was used since it allows taking into account individual exposure history. 

Neither the birth year (p = 0.77) nor the plant worked on (p = 0.061) was significant, so 

cumulative AN exposure was the only (time-dependent) covariate used in the model. 
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 Mortality and Risk Estimates. The coxph function of S-PlusTM was used to obtain 

estimates of β. The estimate of β

lc was equal to 1.24 × 10-3with the standard error of 2.47 × 10-2

(p = 0.61). The estimate of β

oc was equal to 6.7 × 10-4 with a standard error of 9.66 × 10-4

(p = 0.49). The estimates, covariates, and event times were then used to construct estimates of 

cumulative hazard and risks, as described in the previous section. The exposures corresponding 

to excess risks were divided by 2 to account for differences in volume of air inhaled during a 

working day and during a whole day (10 vs. 20 m3

/day). Resulting exposure estimates (by age 

80): EC01 = 0.992 ppm and LEC01 = 0.238 ppm. The corresponding unit risk was calculated to 

equal 4.2 × 10-2 ppm

-1

.

Limitations of the Statistical Approach 

 The statistical approach followed the approach of Starr et al. (2004), and it shares the 

limitations and uncertainties described there. The limitations and uncertainties include the 

following: 

• The Cox model fit the data adequately, but it was an empirical model fit rather than a 

biologically based model. 

• The estimator of the cumulative hazard does not account for the covariate path and hence, 

is only an approximation. 

• The estimate of risk is obtained using the first-order “linearized” approximation. 

However, the results are consistent with assumptions of the first-order approximation 

validity.

• The Cox model uses internal controls and hence, it is much more vulnerable than SMR 

computation to contamination of pool of workers who are free of lung cancer by lung 

cancer cases. That is caused by misdiagnosis of lung cancer as not a lung cancer. 

Selikoff and Seidman (1992) showed based on histopathological analysis of a 

comparably large industrial cohort (17,800 asbestos workers) that as much as 13.7% of 

lung cancer cases are misdiagnosed on death certificates, both as neoplasms and 

nonmalignant diseases, with about 3% as asbestos only diseases (mesothelioma and 

asbestosis). Therefore, the Blair cohort may have as much as 10% of internal controls 

that are actually lung cancers. That would cause a strong bias against finding a 

statistically significant relationship. 
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APPENDIX C. PBPK MODEL DESCRIPTIONS AND SOURCE CODE 

Model Description

The PBPK models used to calculate rat and human internal doses for the development of 

candidate RfDs, oral CSFs, and IURs were those revised from Kedderis et al. (1996) (rat, with 

EH activity towards CEO added and other parameters revised) and Sweeney et al. (2003) 

(human). Both models are flow limited, lumped compartment models that predict amounts and 

concentrations of AN and its metabolite of toxicological interest, CEO, in blood and seven 

tissues: lung, brain, fat, stomach, liver, and rapidly and slowly perfused tissues. Both models 

include portals of entry for oral, inhalation, and i.v. routes of exposure. Drinking water is 

modeled as a continuous infusion to the GI lumen. (The model code allows one to define 

episodic oral exposure as a series of boluses up to 6 times/day, but the simpler approach of 

treating the exposure as continuous was chosen.) For rats, the infusion rate is set such that the 

total amount consumed equals the average total amount ingested during the bioassays as 

determined from water consumption and administered AN concentration. Inhalation duration 

and frequency can be explicitly defined. Simulated metabolism of AN and CEO occur only in 

the liver. Elimination of both compounds is accomplished via second-order GSH conjugation in 

various tissues, saturable hepatic metabolism, and pulmonary excretion into exhaled air. 

The rat and human models are based on the same structural framework but have two 

primary differences: (1) physiological and metabolic parameters for each are species specific, 

and (2) the human model simulates saturable, enzyme-mediated hydrolysis of CEO, a metabolic 

process not observed in rats. In the absence of human in vivo data for metabolism, human 

metabolic parameters were estimated from in vitro values extrapolated to in vivo values by using 

in vitro/in vivo ratios in rats, which is described fully in Sweeney et al. (2003). In the Sweeney 

et al. (2003) model, a conversion factor for in vitro to in vivo extrapolation of human metabolic 

constants is implicitly defined in the calculation of Vmax values for AN oxidation and CEO 

hydrolysis. Model parameter values used for both species are given in Table C-1. 

The acslXtreme model code as used to calculate the various dose metrics, followed by the 

corresponding Matlab model code used to perform the optimizations for fitting of the revised 

parameters, are given at the end of this appendix. The Matlab code is divided into three .m files: 

the top-level “optACN2.m” file, a secondary “RunACN.m” file that is called by the opt file and 

returns the value of the objective function, and an “EqACN.m” file that defines the set of 

differential equations. 
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Table C-1. Rat and human PBPK model parameter values 

Parameter Rat valuea Human valuea

Total BW (kg) 0.25 70 

Percentage of BW 

Liver 4 2.57 

Brain 0.6 2.00 

Stomach 0.63 0.21 

Fat 7 21.42 

Rapidly perfused 3.77 5.22 

Slowly perfused 75 58.58 

Venous blood 3.9 4.35 

Arterial blood 2.1 2.74 

Blood flows (L/h/kg0.74) 

Cardiac output 14.0 13.4 

Alveolar ventilation 14.0 12.9 

Percentage of cardiac output 

Liver 25 21.4 

Brain 2.4 11.4 

Stomach 1.3 1.3 

Fat 9 5.2 

Rapidly perfused 47.3 32.5 

Slowly perfused 15 28.2 

GSH content (mmol/L) 

Liver 8.53 5.63 

Brain 2.00 2.99 

Stomach 4.59 3.61 

Rapidly perfused 2.65 2.59 

Slowly perfused 0.75 1.13 

PCs AN CEO AN CEO

Blood:air 512 1,658 154 1,658 

Liver:blood 0.46 0.274 1.51 0.274 

Brain:blood 0.40 1.407 1.34 1.407 

Stomach:blood 0.46 0.274 1.51 0.274 

Fat:blood 0.28 0.785 0.94 0.785 

Rapidly perfused:blood 0.46 0.274 1.51 0.274 

Slowly perfused:blood 0.35 1.853 1.16 1.853 

Blood binding (h-1) 

Hb (kBC, kBC2) 1.245 (3.66) 1.134 (3.33) 1.245 (3.66) 1.134 (3.33) 

Blood sulfhydryls (kFBC, kFBC2) 2.54 0.68 0.0008 0.84 

AN oxidation 

VmaxC (mg/h/kg0.7) 5.0 (7.1) 15.6 (22.1) 

Km (mg/L) 1.5 (2.76) 0.8 
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Table C-1. Rat and human PBPK model parameter values 

Parameter Rat valuea Human valuea

CEO hydrolysis 

VmaxcC2 (mg/h/kg0.7) --- 841 (---) 

Km2 (mg/L) --- 113 (---) 

kEHC (L/h/kg0.7) --- (3.92) --- (2.20) 

AN-GSH conjugation 

Enzymatic: kFC (h/kg0.3)

-1 73 (50) 113 (77) 

Spontaneous: kSO (mmol/h)-1 0.2584 0.2584 

CEO-GSH conjugation 

Liver: kFC2 (h/kg0.3)

-1 500 197 

Brain/liver (kFBRC/kFC2) 0.0234 0.0531 

Stomach/liver (kFSTC/kFC2) 0.0538 0.0641 

Rapidly perfused/liver (kFRC/kFC2) 0.0311 0.0460 

Slowly perfused/liver (kFSC/kFC2) 0.00879 0.0201 

Oral absorption: Ka (h-1) 8.0 (4.2) 8.0 (4.2) 

aRevised values used in this assessment are italicized in parentheses. 

Sources: Sweeney et al. (2003); Kedderis et al. (1996). 

Estimation of Internal Doses Corresponding to Bioassay Exposures 

 The model code from Sweeney et al. (2003) was modified to enable the explicit 

definition of desired daily oral intake of AN either as a continuous infusion or in an episodic 

pattern of up to six episodes (or both continuous and episodic). The continuous-infusion oral 

exposure rate (STDOSE) is simply calculated as being equal to the total daily exposure 

(STEADYODOSE*BW, by continuous oral dosing) divided by 24 hours. The episodic exposure 

is calculated as the drinking water concentration (DRCONC) times the standard drinking water 

volume (DRVOL, based on BW) times the ratio of actual water consumption to standard 

consumption (FRACVOL) times the fraction of daily water consumed at episode “I” (DRP(I)), 

with that quantity added as a bolus to the GI lumen compartment at episode time “I” (DRT(I)). 

The first episodic exposure time is assumed to be TIME = 0, the same time at which a daily 

gavage dose (ODOSE*BW) is also administered. 

 To simulate inhalation exposures as described in Quast (1980b), the model was run to 

provide 6-hour continuous inhalation exposures, repeating every 24 hours (by setting model 

variable TCHNG1 = 6.0) for 5 days/week (by setting model variable TCHNG2 = 120, the 

number of hours in 5 days). Inhalation simulations were run for 800 continuous simulated hours 

so that the effect of the 5 day/week exposures would be included in the calculation of average 

lifetime daily AUCs. Study-specific rat BWs were used. In this way the PBPK model accounted 

for the dynamics of concentration rise at the beginning of each exposure and clearance at the end 
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of each exposure. The resulting internal dose metrics for inhalation exposure of the rat are listed 

in Table 5-16. 

Rat to Human Extrapolations

For inhalation and oral cancer and oral noncancer effects, similar approaches were used 

to extrapolate PODs from rats to humans. Following derivation of PODs for noncancer and 

cancer endpoints, as weekly average concentrations of AN and CEO in rat blood tissue 

(CI,tissue,rat(BMCL10) in mg/L), HECs were then calculated using the human PBPK model and a 

standard human BW of 70 kg, as the blood or brain concentration, assuming steady-state 

exposure for a set of predefined exposure levels and that equal internal metrics in rats and 

humans are associated with the same degree of response. The relationship between exposure 

level and internal metric as predicted by the human PBPK model was then plotted in Excel and a 

second-order polynomial of the form, HEC = a × CI

2

 + b × CI, where CI is the internal dose 

metric, was fit to the relationship for each metric (blood and brain AN and CEO). 

Inhalation Exposure 

The relationship between inhalation exposure level and internal metric as predicted by the 

human PBPK model is shown in Figures C-1 and C-2 for AN and CEO, respectively. This 

polynomial form gave an excellent fit and was fit over a range of concentrations that bracketed 

the range of CI,tissue,rat(BMCL10) for various cases. The resulting polynomials were then used to 

convert the rat CI values to human equivalent exposures, reported in Chapter 5 for each toxicity 

value. 
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AN dosimetry

0.1

1

10

100

1000

0.0001 0.001 0.01 0.1 1 10 100

Internal average / steady state concentration (mg/L)

Inhalaion exposure (ppm)

ACN blood

ACN brain

AN blood fit

AN brain fit

y = 38.6031·C + [4305.55·C/(26.6520+ C)]

y = 68.3045·C + [1162.47·C/(26.6520 + C)]

Points are steady-state internal AN concentrations predicted by the human PBPK 

model for given inhalation exposure concentrations. Curves are polynomial 

regressions. 

Figure C-1. Human inhalation exposure level vs. internal AN concentration. 
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y = 26.838x2 + 503.27x

R

2

 = 1

y = 41.103x2 + 618.54x

R

2

 = 1

0.1

1

10

100

0.0001 0.001 0.01 0.1

Internal average / steady state concentration (mg/L)

Inhalaion exposure (ppm)

CEO blood

CEO brain

Poly. (CEO brain)

Poly. (CEO blood)

Points are steady-state internal CEO concentrations predicted by the human PBPK 

model for given inhalation exposure concentrations. Curves are polynomial 

regressions. 

Figure C-2. Human inhalation exposure level vs. internal CEO 

concentrations. 

Oral Cancer Risks

For extrapolation of oral cancer risks from exposure in drinking water, the exact pattern 

of ingestion of drinking water by the rats in the bioassay was not measured and will be variable 

among humans. Therefore, the rat PBPK model was used to estimate the internal doses of AN 

and CEO at the exposure levels of the PODs as determined above (in mg/kg-day ingested), while 

assuming two distinct exposure patterns that are expected to bound the truth: continuous 

ingestion and ingestion in six boluses (“episodic”). 

The continuous pattern is simply described as continuous infusion to the stomach lumen 

compartment (i.e., 24 hours/day) at a rate equal to the total daily ingestion (at the BMDL10). 

This pattern leads to the lowest predicted peak concentration of any possible pattern that would 

have the same total ingestion and, therefore, the least saturation of metabolism. The episodic 

pattern assumes that rats consume their drinking water in six boluses, spaced at 4-hour intervals 

during each day. The fraction of their total daily ingestion at each of these events is 23.3, 10, 10,

10, 23.3, and 23.4%, respectively. For continuous exposures, the steady-state blood and brain 

concentrations of AN and CEO were calculated as internal dose metrics, while for the episodic 

pattern, the daily average concentrations were determined. 
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Stricker et al. (2003) measured water and food intake by Sprague-Dawley rats on diets 

containing normal (1%) and high (8%) levels of NaCl. On days 5 and 10 of control exposure, 

the rats were observed to consume water in 15.9 ± 2.0 and 19.3 ± 2.4 bouts, with amount 

consumed per bout being 2.1 ± 0.3 and 1.8 ± 0.3 mL, respectively. Thus, actual consumption by 

rats occurs in many more than six bouts, and the amount consumed per bout is much more 

uniform than the episodic pattern. The data also show that most of the consumption occurs 

during the 12-hour dark/waking period (represented by the first and final two boluses in the 

EPA's pattern), with much less consumed during the light/sleeping period (represented by the 

second to fourth boluses). Further, data on water consumption relative to controlled meal 

delivery showed that drinking bouts can last as long as 80 seconds, rather than occurring in an 

instantaneous bolus. Thus, actual consumption lies between an assumed continuous pattern and 

the idealized episodic pattern. Because episodic consumption will lead to model prediction of 

the greatest metabolic saturation, to obtain the desired prediction that represents an upper bound 

of that behavior (including the possibility that water consumption in the bioassays, which 

included F344 as well as Sprague-Dawley rats, may have differed from those observed by 

Stricker at al. [2003]), this idealized episodic pattern rather than one designed to more closely 

match that reported by Stricker et al. (2003) was chosen. The results of the PBPK simulations 

for continuous oral infusion vs. an idealized episodic ingestion pattern for various oral BMDL 

values differed by no more than 7%, indicating that for the rat internal dose metrics, the exact 

exposure pattern was not significant. 

To calculate the HEDs, similarly two alternate assumptions of continuous and episodic 

exposure to the corresponding rat metrics were applied. For the episodic pattern, it was again 

assumed that this occurred in six bolus doses but occurring at 0, 3, 5, 8, 11, and 15 hours 

computation time (i.e., from the time of first ingestion in the morning, assumed to occur at 

breakfast), with the amount consumed in each bolus being 25, 10, 25, 10, 25, and 5% of the total 

daily intake, respectively. As with the inhalation extrapolation, the human PBPK model was run 

using a range of fixed input dose rates (using both continuous and episodic regimens), the 

resulting internal doses calculated, and then an empirical regression performed in Excel to 

interpolate between those doses. The resulting simulation values (points) and regressions (lines) 

are shown in Figures C-3 to C-6. 
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Continuous Exposure Model

0.01

0.1

1

10

100

0.00001 0.0001 0.001 0.01 0.1 1

Internal steady state concentration (mg/L)

Oral exposure rate (mg/kg BW/day)

AN blood fits

ACN blood

AN brain fits

ACN brain

y = 27.0624·C + [161.3074·C/(0.569868 + C)]

y = 35.6015·C + [138.101·C/(0.657976 + C)]

Points are PBPK model predictions; curves are polynomial regressions. 

Figure C-3. Human oral exposure level vs. internal AN concentration for 

continuous exposure. 

Continuous Exposure Model

y = 10.185x2 + 98.2x

R

2

 = 1

y = 6.7418x2 + 79.895x

R

2

 = 1

0.01

0.1

1

10

100

0.0001 0.001 0.01 0.1 1

Internal steady state concentration (mg/L)

Oral exposure rate (mg/kg BW/day)

CEO blood

CEO brain

Poly. (CEO blood)

Poly. (CEO brain)

Points are PBPK model predictions; curves are polynomial regressions. 

Figure C-4. Human oral exposure level vs. internal CEO concentration for 

continuous exposure. 
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Episodic Exposure Model -- AN

0.01

0.1

1

10

100

0.00001 0.0001 0.001 0.01 0.1 1

Internal average concentration (mg/L)

Oral exposure rate (mg/kg BW/day)

AN blood fit

AN blood

AN brain fit

AN brain

y = 51.3757·C + [15.2250·C/(0.0586390 + C)]

y = 40.6491·C + [15.2251·C/(0.074113 + C)]

Points are PBPK model predictions; curves are nonlinear regressions. 

Figure C-5. Human oral exposure level vs. internal AN concentration for 

episodic exposure. 

Episodic Exposure Model -- CEO

y = 62.272x2 + 98.857x

R

2

 = 1

y = 41.22x2 + 80.43x

R

2

 = 1

0.01

0.1

1

10

0.0001 0.001 0.01 0.1

Internal average concentration (mg/L)

Oral exposure rate (mg/kg BW/day)

CEO blood

CEO brain

Poly. (CEO blood)

Poly. (CEO brain)

s

Points are PBPK model predictions; curves are polynomial regressions. 

Figure C-6. Human oral exposure level vs. internal CEO concentration for 

episodic exposure. 
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acslXtreme Model Source Code 

PROGRAM 

! ACRYLONITRILE and CYANOETHYLENE OXIDE MODEL w/ 1st order epoxide hydrolase 

! Model of ACN administration and CEO production! 

! Revised model of G.L. Kedderis! 

! Original by M.L. Gargas 10/9/89, revised 5/6/92! 

! Revised 2/21/94 by G.L. Kedderis! 

! Refined 6/28-7/12/95, 8/8/95 by G.L. Kedderis! 

! Modified by SMH - 5/2/97! 

! Modified for continuous oral dose by LMS 3/7/00! 

!pst2, pr2, and pb2 revised to Kedderis et al 1996 values! 

!periodic drinking water reinstated! 

!modified for revised human scaling by LMS 7/26/01!

!built blood flow mass balance into equations LMS 7/27/01! 

!built blood mass balance into equations, made blood binding! 

!rates equal in venous and arterial blood LMS 7/31/01! 

!modified to explicitly define DW conc. and daily ACN intake MHL 08/05! 

!statement added to calculate daily ACN intake (mg/kg/day) ml 08/05! 

! Modified 05/05/06 by Paul Schlosser and Allan Marcus to include! 

! Linear-range approximation to epoxide hydrolase model of ACN to CEO! 

!and to simplify the oral dosing calculations -- to avoid divide-by-zero! 

!errors and allow for either or both continuous and/or periodic exposure! 

! June '06 - Jan '07: Other modifications by P. Schlosser to allow both 

!continuous and episodic drinking water dosing, and to update default 

!parameters for rat 

INTEGER I !counter for drinking water arrays! 

REAL DRT(6), DRP(6) !store drink water times, percents in array! 

DIMENSION A0(16) !Set of zeros to force values to be >/= 0! 

CONSTANT A0 = 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 

CONSTANT QPC = 14. ! Alveolar ventilation rate (L/hr)! 

CONSTANT QCC = 14. ! Cardiac output (L/hr)! 

CONSTANT QLC = 0.25 ! Fractional blood flow to liver! 

CONSTANT QFC = 0.09 ! Fractional blood flow to fat! 

CONSTANT QBRC = 0.024 ! Fractional blood flow to brain! 

CONSTANT QSTC = 0.013 ! Fractional blood flow to the stomach! 

CONSTANT QSC = 0.15 ! Fractional blood flow to slowly perfused tissue 

CONSTANT BW = 0.523 ! Body weight (kg) male rat! 

CONSTANT VLC = 0.04 ! Fraction of liver tissue to total body! 

CONSTANT VRC = 0.0377 ! Fraction of richly perfused tissue to total! 

CONSTANT VSC = 0.75 ! Fraction of slowly perfused tissue to total! 

CONSTANT VBRC = 0.006 ! Fraction of brain tissue!

CONSTANT VFC = 0.07 ! Fraction of fat tissue! 

CONSTANT VSTC = 0.0063! Fraction of stomach tissue! 

CONSTANT BVC = 0.06 ! Fraction of blood volume! 

CONSTANT VVBC = 0.65 ! Fraction of venous blood volume! 

CONSTANT PBR = 0.40 ! AN brain/blood partition coefficient! 

CONSTANT PBR2 = 1.407 ! CEO brain/blood partition coefficient! 

CONSTANT PL = 0.46 ! AN liver/blood partition coefficient! 

CONSTANT PL2 = 0.274 ! CEO liver/blood partition coefficient! 

CONSTANT PST = 0.46 ! AN stomach/blood partition coefficient! 

CONSTANT PST2 = 0.274 ! CEO stomach/blood partition coefficient! 

CONSTANT PF = 0.28 ! AN fat/blood partition coefficient! 

CONSTANT PF2 = 0.785 ! CEO fat/blood partition coefficient! 

CONSTANT PS = 0.35 ! AN slowly perfused tissue/blood partition! 

CONSTANT PS2 = 1.853 ! CEO slowly perfused tissue/blood partition! 
C-11 DRAFT - DO NOT CITE OR QUOTE 

CONSTANT PR = 0.46 ! AN rapidly perfused tissue/blood partition! 

CONSTANT PR2 = 0.274 ! CEO rapidly perfused tissue/blood partition! 

CONSTANT PB = 512 ! AN blood/air partition coefficient! 

CONSTANT PB2 = 1658 ! CEO blood/air partition coefficient! 

CONSTANT MW = 53.06 ! ACN molecular weight (g/mol)! 

CONSTANT MW2 = 69.05 ! CEO molecular weight (g/mol)! 

CONSTANT KEHC = 3.92 ! Effective 1st-order EH rate, liter/hr/kg^0.7 

CONSTANT VMAXC = 7.1 ! Maximum velocity of metabolism (mg/hr-1kg)! 

CONSTANT VMAXC2 = 0.0 ! Maximum velocity of metabolism, CEO (mg/hr-1kg)! 

CONSTANT KM = 2.76 ! Michaelis-Menten constant (mg/L)! 

CONSTANT KM2 = 113. ! Michaelis-Menten constant, CEO (mg/L)! 

CONSTANT KFC = 50 ! ACN first order metabolism rate const (/hr-1kg)! 

CONSTANT KFC2 = 500 ! CEO first order metabolism rate const (/hr-1kg)! 

CONSTANT KSO = 0.2584 ! ACN second order reaction with GSH (L/mMol/hr)! 

CONSTANT GSHL = 8.53 ! Liver GSH conc (mMol/L)! 

CONSTANT GSHBR = 2. ! Brain GSH (mMol/L)! 

CONSTANT GSHST = 4.59 ! Stomach GSH (mMol/L)! 

CONSTANT GSHS = 0.75 ! Slowly perfused (muscle) GSH (mMol/L)! 

CONSTANT GSHR = 2.65 ! Rapidly perfused GSH (mMol/L)! 

CONSTANT KBC = 3.66 ! ACN 1ST order binding to blood hb (/hr)! 

CONSTANT KBC2 = 3.33 ! CEO 1ST order binding to blood hb (/hr)! 

CONSTANT KFBC = 2.54 ! ACN 1ST order binding to blood RSH (/hr)! 

CONSTANT KFBC2 = 0.68 ! CEO 1ST order binding to blood RSH (/hr)! 

CONSTANT KA = 4.2 ! Oral uptake rate (/hr)! 

CONSTANT IVDOSE = 0. ! IV dose (mg/kg)! 

CONSTANT CONC = 0. ! Inhaled concentration (ppm) ACN! 

CONSTANT CONC2 = 0. ! Inhaled concentration (ppm) CEO! 

CONSTANT ODOSE= 0. ! Oral dose in mg/kg-day, assumed given at t=0, 24, etc. 

 

 ! Timing commands! 

CONSTANT TCHNG1 = 24.0 ! Length of exposure (hrs)! 

CONSTANT TCHNG2 = 120.0 ! Allows for 5 day/week exposure! 

CONSTANT TINF = .003 ! Length of IV infusion (hrs)! 

 

CONSTANT STEADYODOSE = 0 

!daily dose mg/kg-day, if assuming continuous oral infusion 

!periodic drinking water section! 

CONSTANT DRCONC=0.0 ! Conc. of ACN in drinking water (mg/L) 

CONSTANT DRT=0,2,4,6,8,10 

 ! Times for multiple oral drinks/day *after* 0 

 ! Must be ascending, 0 <= times < 24 hr 

 ! DRTIME(1) assumed = 0 and not used 

CONSTANT DRP=1,0,0,0,0,0 !Percent consumed by drinking at those times 

 ! Bolus of ODOSE*BW + DRPCT(1)*DRDOSE will be given at t=0,24,48, etc. 

CONSTANT FRACVOL = 1.0 

 ! Actual daily water consumption / nominal or control volume 

 ! used when calculating DRDOSE 

INITIAL 

 DRVOL = 0.102*BW**0.7 ! Water consumption (L/d) 

 ! 2L/d water consumption for a 70kg human 

 DRDOSE = DRCONC*DRVOL*FRACVOL 

 DAYDOSE = ODOSE*BW + DRP(1)*DRDOSE 

 ! Once daily oral dose; given at t=0 via initial condition 
C-12 DRAFT - DO NOT CITE OR QUOTE 

 STDOSE = STEADYODOSE*BW/24 ! Steady oral dosing rate in mg/hr 

 IVR = IVDOSE*BW/TINF 

 NEWDAY = 0; I = 2 ! First dose given as initial condition 

 SCHEDULE ORALDOSE.AT.DRT(2) 

 ! Scaled parameters! 

 

 QC = QCC*BW**0.74 

 QP = QPC*BW**0.74 

 QL = QLC*QC 

 QF = QFC*QC 

 QBR = QBRC*QC 

 QST = QSTC*QC 

 QS = QSC*QC 

 QR = QC-QL-QF-QBR-QS-QST 

 VL = VLC*BW 

 VF = VFC*BW 

 VBR = VBRC*BW 

 VST = VSTC*BW 

 VS = VSC*BW 

 VR = VRC*BW 

 BV = BVC*BW 

 VAB = BV*(1-VVBC) !volume arterial blood! 

 VVB = BV*VVBC 

 GSHRB = GSHBR/GSHL !ratio of brain GSH to liver GSH! 

 GSHRST = GSHST/GSHL !ratio of stomach GSH to liver GSH! 

 GSHRS = GSHS/GSHL !ratio of slowly perfused GSH to liver GSH! 

 GSHRR = GSHR/GSHL !ratio of richly perfused GSH to liver GSH! 

 VMAX = VMAXC*BW**0.7 ! Liver P450 ACN to CEO! 

 VMAX2 = VMAXC2*BW**0.7 ! Liver CEO Hydrolysis! 

 KF = KFC/BW**0.3 ! Liver ACN-GSH rate!

 KF2 = KFC2/BW**0.3 ! Liver CEO-GSH/RSH rate! 

 KEH = KEHC*BW**0.7 ! Approx. first-order rate in liver! 

 KFBRC = KFC2*.1*GSHRB ! CEO brain reaction - 10% GSH ratio! 

 KFSTC = KFC2*.1*GSHRST ! CEO stomach reaction - 10% GSH ratio! 

 KFSC = KFC2*.1*GSHRS ! CEO slowly perfused reaction - 10% GSH ratio! 

 KFRC = KFC2*.1*GSHRR ! CEO richly perfused reaction - 10% GSH ratio! 

 KFBR = KFBRC/BW**.3 ! CEO brain RSH rate!

 KFST = KFSTC/BW**.3 ! CEO stomach RSH rate! 

 KFS = KFSC/BW**.3 ! CEO SPT RSH rate! 

 KFR = KFRC/BW**.3 ! CEO RPT RSH rate! 

 KFB = KFBC 

 KFB2 = KFBC2 

 KB = KBC 

 KB2 = KBC2 

DAILYDOSE = ODOSE+STEADYODOSE+(DRDOSE/BW)+(AI/BW/(TSTOP/24)) 

 !daily dose mg/kg-day via oral and/or inhalation routes! 

END !of INITIAL 

 

DYNAMIC 

 ALGORITHM IALG = 2 !Gear method for stiff systems!

 MAXTERVAL MAXT = 1.0e-3 

 MINTERVAL MINT = 1.0e-9 

 CINTERVAL CINT = 0.5 

 

DERIVATIVE 
C-13 DRAFT - DO NOT CITE OR QUOTE 

!-----------------------------------! 

!--------- ACRYLONITRILE ---------! 

!-----------------------------------! 

 

 ! CI = Concentration in inhaled air (mg/L)! 

 CIZONE = PULSE(0.0,24.0,TCHNG1) * PULSE(0.0,168.0,TCHNG2) 

 CI = CIZONE*CONC*MW/24450. 

 

 ! AI = Amount inhaled (mg)! 

 RAI = QP*CI 

 AI = INTEG(RAI,0) 

 ! MR = Amount in stomach lumen (mg)! 

 RMR = STDOSE - KA*MR 

 AMR = INTEG(RMR,DAYDOSE) 

 MR = MAX(AMR, A0(1)) !no negative values! 

 ! CAL = Concentration in arterial lung blood (mg/L)! 

 CAL = (QC*CVB+QP*CI)/(QC+(QP/PB)) 

 

 ! CA = Conc. in systemic arterial blood (mg/l)! 

 RAB = QC*(CAL-CA)-(KB+KFB)*AB 

 AB = INTEG(RAB,A0(2)) 

 CA = AB/VAB 

 

 ! AX = Amount exhaled (mg)! 

 CX = CAL/PB 

 CXPPM = (0.7*CX+0.3*CI)*24450./MW 

 RAX = QP*CX 

 AX = INTEG(RAX,A0(3)) 

 ! AST = Amount in stomach tissue (mg)! 

 RAST = QST*(CA-CVST) - STGSH + KA*MR 

 AST = INTEG(RAST,A0(4)) 

 CVST = AST/(VST*PST) 

 CST = AST/VST 

 STGSH = KSO*CVST*GSHST*VST 

 ASTG = INTEG(STGSH,A0(5)) 

 

 ! AS = Amount in slowly perfused tissues (mg)! 

 RAS = QS*(CA-CVS) - SGSH 

 AS = INTEG(RAS,A0(6)) 

 CVS = AS/(VS*PS) 

 CS = AS/VS 

 SGSH = KSO*CVS*GSHS*VS 

 ASG = INTEG(SGSH,A0(7)) 

 

 ! AR = Amount in rapidly perfused tissues (mg)! 

 RAR = QR*(CA-CVR) - RGSH 

 AR = INTEG(RAR,A0(8)) 

 CVR = AR/(VR*PR) 

 CR = AR/VR 

 RGSH = KSO*CVR*GSHR*VR 

 ARG = INTEG(RGSH,A0(9)) 

 

 ! AF = Amount in fat tissue (mg)! 

 RAF = QF*(CA-CVF) 

 AF = INTEG(RAF,A0(10)) 

 CVF = AF/(VF*PF) 

 CF = AF/VF 
C-14 DRAFT - DO NOT CITE OR QUOTE 

 

 ! ABR = Amount in brain tissue (mg)! 

 RABR = QBR*(CA-CVBR) - BRGSH 

 ABR = INTEG(RABR,A0(11)) 

 CVBR = ABR/(VBR*PBR) 

 CBR = ABR/VBR 

 BRGSH = KSO*CVBR*GSHBR*VBR 

 ABRG = INTEG(BRGSH,A0(12)) 

 

 ! AL = Amount in liver tissue (mg) 

 RAL = QL*CA + QST*CVST - (QL+QST)*CVL - RAM1 - RAM2 - LGSH 

 AL = INTEG(RAL,A0(13)) 

 CVL = AL/(VL*PL) 

 CL = AL/VL 

 AUCL = INTEG(CL,0.) 

 LGSH = KSO*CVL*GSHL*VL 

 ALG = INTEG((LGSH+RAM2+(KB*CVB*VVB)+(KFB*CVB*VVB)),A0(14)) 

 

 ! AM1 = Amount metabolized, saturable (P450) and linear pathways (mg)! 

 RAM1 = VMAX*CVL/(KM+CVL) 

 RAM1M = RAM1*1000/MW 

 AM1 = INTEG(RAM1,A0(15)) 

 ! AM2 = Amount metabolized, first-order pathway (GST) (mg)! 

 RAM2 = KF*CVL*VL 

 AM2 = INTEG(RAM2,0) 

 

 ! CV = Mixed venous blood concentration (mg/L)! 

 IV = IVR*(T<=TINF) ! PULSE(0,24,TINF) 

 CV = (QF*CVF + (QL+QST)*CVL + QS*CVS + QR*CVR + QBR*CVBR + IV)/QC 

 

 ! CVB = Mixed venous ACN conc. after binding (mg/L)! 

 RVB = QC*(CV-CVB) - (KB+KFB)*VB 

 VB = INTEG(RVB,A0(16)) 

 CVB = VB/VVB 

 

 ! TMASS = mass balance (mg)! 

 TMASS = ABR+AF+AL+AS+AR+AST+AM1+AM2+AX+MR+ASTG+ASG+ARG+ABRG+ALG 

 

!----------------------------------------! 

!----------------- CEO ----------------! 

!----------------------------------------! 

 

 ! CI2 = Concentration in inhaled air (mg/L)! 

 CI2 = CIZONE*CONC2*MW2/24450. 

 

 ! CAL2 = Concentration in arterial lung blood (mg/L)! 

 CAL2 = (QC*CVB2+QP*CI2)/(QC+(QP/PB2)) 

 

 ! CA2 = Conc. in systemic arterial blood (mg/l)! 

 RAB2 = QC*(CAL2-CA2)-(KB2+KFB2)*AB2 

 AB2 = INTEG(RAB2,0.) 

 CA2 = AB2/VAB 

 

 ! AS2 = Amount in slowly perfused tissues (mg)! 

 RAS2 = QS*(CA2-CVS2) - KFS*CVS2*VS 

 AS2 = INTEG(RAS2,0.) 

 CVS2 = AS2/(VS*PS2) 

 CS2 = AS2/VS 

 
C-15 DRAFT - DO NOT CITE OR QUOTE 

 ! AR2 = Amount in rapidly perfused tissues (mg)! 

 RAR2 = QR*(CA2-CVR2) - KFR*CVR2*VR 

 AR2 = INTEG(RAR2,0.) 

 CVR2 = AR2/(VR*PR2) 

 CR2 = AR2/VR 

 

 ! AST2 = Amount in stomach (mg)! 

 RAST2 = QST*(CA2-CVST2) - KFST*CVST2*VST 

 AST2 = INTEG(RAST2,0.) 

 CVST2 = AST2/(VST*PST2) 

 CST2 = AST2/VST 

 ! AF2 = Amount in fat tissue (mg)! 

 RAF2 = QF*(CA2-CVF2) 

 AF2 = INTEG(RAF2,0.) 

 CVF2 = AF2/(VF*PF2) 

 CF2 = AF2/VF 

 

 ! ABR2 = Amount in brain tissue (mg)! 

 RABR2 = QBR*(CA2-CVBR2) - KFBR*CVBR2*VBR 

 ABR2 = INTEG(RABR2,0.) 

 CVBR2 = ABR2/(VBR*PBR2) 

 CBR2 = ABR2/VBR 

 ! CEO Hydrolysis! 

 ! VMAX2 = maximum velocity of metabolism (mg/hr-1kg)! 

 ! KM2 = Michaelis-Menten constant (mg/L)! 

 ! KEH is parameter for linear metabolism in liver to replace saturable 

 ! AL2 = Amount CEO in liver tissue (mg)! 

 RAM = RAM1M*MW2/1000. 

 RAL2ADD = QL*CA2 + QST*CVST2 + RAM 

 RAL2M = VMAX2*CVL2/(KM2+CVL2) + KEH*CVL2 

 RAL2 = RAL2ADD - (QL+QST)*CVL2 - KF2*CVL2*VL - RAL2M 

 AL2 = INTEG(RAL2,0.) 

 CVL2 = AL2/(VL*PL2) 

 CL2 = AL2/VL 

 ! CV2 = Mixed venous blood concentration (mg/L)! 

 CV2 = (QF*CVF2 + (QL+QST)*CVL2 + QS*CVS2 + QR*CVR2 + QBR*CVBR2)/QC 

 

 ! CVB2 = Mixed venous CEO conc. after binding! 

 RVB2 = QC*(CV2-CVB2) - (KB2+KFB2)*VB2 

 VB2 = INTEG(RVB2,0.) 

 CVB2 = VB2/VVB 

 

 ! Calculation of the AUC for ACN and CEO in the brain and blood! 

 AUCBR = INTEG(CBR,0.) ! AUC for ACN brain conc.! 

 AUCBR2 = INTEG(CBR2,0.) ! AUC for CEO brain conc.! 

 AUCB = INTEG(CVB,0.) ! AUC for ACN blood conc.! 

 AUCB2 = INTEG(CVB2,0.) ! AUC for CEO blood conc.! 

 DAILYSTAUC = INTEG(CST,0.)/(TSTOP/24) !Mean daily stomach AN 

 DAILYST2AUC = INTEG(CST2,0.)/(TSTOP/24) !Mean daily stomach CEO 

 END ! Derivative 

 ! Code that is executed once at each communication interval goes here 

CONSTANT TSTOP = 24.0 ! Length of experiment (hrs)! 

TERMT(T.GE.TSTOP, 'checked on communication interval: REACHED TSTOP') 

DISCRETE ORALDOSE 

 IF (I.EQ.1) THEN 
C-16 DRAFT - DO NOT CITE OR QUOTE 

 AMR = AMR + DAYDOSE ! Initial dose of day/daily dose 

 ELSE 

 AMR = AMR + DRP(I)*DRDOSE ! Drinking percent 

 END IF 

 I = MOD((I+1),6) 

 IF (I.EQ.1) THEN 

 SCHEDULE ORALDOSE.AT.NEWDAY ! Go to start of the next day 

 NEWDAY = NEWDAY + 24 

 ELSE 

 SCHEDULE ORALDOSE.AT.(NEWDAY+DRT(I)) ! Go to next drink time 

 END IF 

END ! DISCRETE ORALDOSE 

END ! Dynamic 

 TERMINAL ! Metrics calculated below! 

 DAILYBRAUC = AUCBR/(TSTOP/24) ! Mean daily stomach ACN 

 DAILYBR2AUC = AUCBR2/(TSTOP/24) ! Mean daily stomach CEO 

 DAILYBAUC = AUCB/(TSTOP/24) ! Mean daily blood ACN 

 DAILYB2AUC = AUCB2/(TSTOP/24) ! Mean daily blood CEO 

 

 PEAKPBR = MAX(0, CBR) ! Peak conc. parent compound in brain! 

 PEAKPB = MAX(0, CV) ! Peak conc. parent compound in blood! 

 PEAKMBR = MAX(0, CBR2) ! Peak conc. metabolite in brain! 

 PEAKMB = MAX(0, CV2) ! Peak conc. metabolite in blood! 

 ! Calc. of the avg. values of ACN and CEO in the brain and blood! 

 AVEBR = AUCBR/TSTOP ! Average of ACN brain conc.! 

 AVEBR2 = AUCBR2/TSTOP ! Average of CEO brain conc.! 

 AVEB = AUCB/TSTOP ! Average of ACN blood conc.! 

 AVEB2 = AUCB2/TSTOP ! Average of CEO blood conc.! 

 END ! TERMINAL 

END ! PROGRAM 
C-17 DRAFT - DO NOT CITE OR QUOTE 

Matlab source code – 3 programs (.m files)

% ACN / CEO PBPK model optimization file 

% 

% Main program, or SHELL for PBPK model. 

% 

% P = optACN2(pin, pvn, datfilename, switch) 

% 

% swtch = optimization choice (see below) 

% pin = values of *all* parameters (input) 

% pvn = cell-vector of parameter names TO BE VARIED

% datfilename = name of data file (.csv) to use 

% P = values of the output parameters (optimized) 

% 

% where pin is the vector of paramters to input and swtch determines whether 

% to run the simulation (swtch = 0), or to optimize (swtch = 1 neld2 

search). 

% 

% pvn = {'name1' ; 'name2' ; ... } Note: use curly brackets and semi-colons 

 

%----------------------------------------------------------------------------

- 

function P = optACN(pin,pvn,dfn,sw) 

format long 

%-----------------------------------globalize data sets----------------------

- 

global quan phys prs Ypt pv yname itr datfile pvar pbl j1 jf ncv tsp pex 

global ICs Ccafpt Ccafc nv Cost C0 ps MW MW2 nv 

%-------------------load dat set--------------------- 

quan.dat=load([dfn,'.csv']); 

swtch=sw; 

%close all 

% The sequence of columns in the data sets are as follows: 

% tspan, CVB, CL, CBR, CVB2, CL2, CBR2, ODOSE(initial), IVDOSE(initial) ... 

% % AN-GSH in urine, % CEO-GSH in urine, % Hb-bound material 

yname={'CVB';'CL';'CBR';'CVB2';'CL2';'CBR2';'AGSHU';'CGSHU';'PBH';'MassBal'}; 

ncv=32; 

%--------------------------find indeces of parameters to be varied-----------

- 

 

pname={'VmaxC';'Km';'VmaxC2';'Km2';'kEHC';'kFC';'kFC2';'kA';'gammA';'gammC';'

kH';'kH2'}; 

%prs = [5.0; 1; 1.e-18; 113.; 3.9; 73.; 500.; 8.; 1; 1]; 

%prs = [3.27;.000425; 1.e-18; 113.; 3.9; 95.7; 500.; 8.; .0107; 1]; 

prs = [.102; 2.76; 1.e-18; 113.; 0.98; 82.3; 14.1; 4.94; .0107; 0.941; 

1.245; 1.134]; 

prs = [2.24; 2.76; 1.e-18; 113.; 0.98; 82.3; 14.1; 4.94; .0107; 0.941; 

1.245; 1.134]; 

%prs = [1.86; 1.5; 1.e-18; 113.; 3.9; 15.7; 2240.; 8.; .425; 1.10]; 

%those above are default values 

pbl={', ';', ';', ';', ';', ';', ';', ';', ';', ';', ';', ';', '}; 

% KEHC = %Effective 1st-order EH rate, liter/hr/kg^0.7 

% VMAXC = %Maximum velocity of metabolism (mg/hr-1kg)% 

% VMAXC2 = %Max. vel. of metabolism, CEO (mg/hr-1kg)% 

% KM = %Michaelis-Menten constant (mg/L)% 

% KM2 = %Michaelis-Menten constant, CEO (mg/L)%

% KFC = %ACN first order metab rate const (/hr-1kg)% 

% KFC2 = %CEO first order metab rate const (/hr-1kg)% 

% KA = %Oral uptake rate (/hr)% 
C-18 DRAFT - DO NOT CITE OR QUOTE 

fname='EqACN'; % file with set of model equations to use is fname.m 

runfn='RunACN'; % Run file runfn.m 

quan.ns = length(pname); pv = 1:quan.ns; pvar = pname; 

if length(pin)>quan.ns 

 error('input parameter vector is too long') 

end 

if sum(pin) % if pin =[], then no optimization, use default params 

 popt=reshape(log(pin),length(pin),1); 

 if strmatch('all',pvn,'exact') 

 if length(pin)~=quan.ns 

 error('length of pin is wrong; must be ',num2str(quan.ns),' to 

match pvn = all') 

 end 

 prs=pin; 

 else 

 pvar = pvn; 

 quan.ns = length(pvn); 

 pv = zeros(1,quan.ns); 

 if (length(pin)~=quan.ns)&(length(pin)~=length(pname)) 

 error(['Length of pin is wrong; must be ',num2str(quan.ns),... 

 ' to match pvn or ',num2str(length(pname)),' to match 

pname.']) 

 else 

 for i = 1:quan.ns 

 if strmatch(pvn(i),pname,'exact') 

 pv(i) = strmatch(pvn(i),pname,'exact'); 

 else 

 error([char(pvn{i}),' is not in the named list of 

parameters.']) 

 end 

 end 

 end 

 if length(pin)==length(pname) 

 prs=pin; popt=popt(pv); 

 end 

 end 

else 

 popt=log(prs); swtch=0; 'No pin so running simulation only with default 

params.' 

end 

 

save pv pv 

%--------------------------find indeces of start times---------------- 

quan.t = quan.dat(:,1); 

tci = (quan.t > 0); 

datc=quan.dat(:,[2:7,12:14]); % data columns used for fitting 

nv = size(datc,2); % number of variables to plot, etc 

Ccafc=zeros(length(quan.t),(nv+1)); 

nplt=0; 

for i=1:6 

 quan.ic{i} = find((datc(:,i)>0) & tci); 

 quan.datc{i} = datc(quan.ic{i},i); 

 if quan.datc{i} 

 nplt=nplt+1; 

 end 

 quan.tc{i} = quan.t(quan.ic{i}); 

 quan.nc(i) = sum((datc(:,i)>0) & tci); 

end 

nplt2=0; 

for i=7:nv 
C-19 DRAFT - DO NOT CITE OR QUOTE 

 quan.ic{i} = find((datc(:,i)>0) & tci); 

 quan.datc{i} = datc(quan.ic{i},i); 

 if quan.datc{i} 

 nplt2=nplt2+1; 

 end 

 quan.tc{i} = quan.t(quan.ic{i}); 

 quan.nc(i) = sum((datc(:,i)>0) & tci); 

end 

 

C0=sum(quan.nc)*(log(2*pi)+1); 

quan.mc=datc>0; 

sz=length(quan.t); 

quan.yc=0*[datc,datc(:,1)]; 

quan.jt = find(quan.t == 0); 

% jt = vector of indeces of rows in data file starting with "0" 

quan.idf= length(quan.jt); 

quan.jt = [quan.jt;(sz+1)]; 

% add a pseudo-index to mark the end of the data file 

%------------------------constant parameters---------------------------- 

ps.KSO = 0.2584; %ACN second order rxn with GSH (L/mMol/hr)% 

ps.GSHL = 8.53; %Liver GSH conc (mMol/L)% 

ps.GSHBR = 2.; %Brain GSH (mMol/L)% 

ps.GSHST = 4.59; %Stomach GSH (mMol/L)% 

ps.GSHS = 0.75; %Slowly perfused (muscle) GSH (mMol/L)% 

ps.GSHR = 2.65; %Rapidly perfused GSH (mMol/L)% 

 

%ps.KB = 1.245 + 2.54; %ACN 1ST order binding to blood hb + RSH (/hr)% 

ps.KB0 = 2.54; %ACN 1ST order binding to blood hb + RSH (/hr)% 

ps.KB0 

%ps.KH = 1.245; 

ps.KFB = 2.54; 

%ps.KB2 = 1.134 + 0.68 + 0.413; 

ps.KB20 = 0.68 + 0.413; 

%ps.KH2 = 1.134; 

phys.KHR = 1.134/1.245; 

ps.KFB2 = 0.68; 

 %CEO 1ST order binding to blood hb + RSH + chem. hydrol. (/hr)% 

 

ps.tinf=.003; %blood infusion time (hr) 

% ACN PCs 

phys.PL = 0.46; % liver:blood PC 

phys.PST = 0.46; % stomach tissue:blood PC, also used for GI 

phys.PBR = 0.40; % brain tissue:blood PC 

phys.PF = 0.28; % fat tissue:blood PC 

phys.PS = 0.35; % slowly tissue:blood PC 

phys.PR = 0.46; % richly tissue:blodd PC 

phys.PB = 512; % blood tissue:blodd PC 

 

%CEO PCs 

phys.PL2 = 0.274; % liver:blood PC 

phys.PST2 = 0.274; % stomach tissue:blood PC, also used for GI 

phys.PBR2 = 1.407; % brain tissue:blood PC 

phys.PF2 = 0.785; % fat tissue:blood PC 

phys.PS2 = 1.853; % slowly tissue:blood PC 

phys.PR2 = 0.274; % richly tissue:blodd PC 

phys.PB2 = 1658; % blood tissue:blodd PC 

 

QPC = 14.; %Alveolar ventilation rate (L/hr)% 

QCC = 14.; %Cardiac output (L/hr)% 

 
C-20 DRAFT - DO NOT CITE OR QUOTE 

QBRC = 0.024; % blood flow to brain 

QSTC = 0.013; % Blood flow rate for stomach tissue (portal vein) 

QFC = 0.09; % blood flow to fat tissue 

QLC = 0.25; % Blood flow rate for liver ) 

QSC = 0.15; % Blood flow rate for slowly 

 

phys.BW=0.25; %body weight 

VLC = 0.04; %Fraction of liver tissue to total body% 

VRC = 0.0377; %Fraction of richly perf tiss to total% 

VSC = 0.75; %Fraction of sloly perf tiss to total% 

VBRC = 0.006; %Fraction of brain tissue% 

VFC = 0.07; %Fraction of fat tissue% 

VSTC = 0.0063; %Fraction of stomach tissue% 

BV = 0.06*phys.BW; %Blood vol% 

VVBC = 0.65; %Fraction of venous blood vol% 

 

MW = 53.06; %ACN molecular weight (g/mol)% 

MW2 = 69.05; %CEO molecular weight (g/mol)% 

 

%---------------- preset varying parameters --------------------------- 

phys.QC = QCC*phys.BW^0.74; 

phys.QP = QPC*phys.BW^0.74; 

phys.QBR = QBRC*phys.QC; % blood flow to brain 

phys.QST = QSTC*phys.QC; % Blood flow rate for stomach tissue (portal 

vein) 

phys.QS = QSC*phys.QC; % Blood flow rate for slowly 

phys.QL = QLC*phys.QC; % Blood flow rate for liver (hepatic artery) 

phys.QF = QFC*phys.QC; % blood flow to fat 

phys.QR = phys.QC-phys.QL-phys.QF-phys.QBR-phys.QS-phys.QST; 

phys.VBR = VBRC*phys.BW; % brain volume (L) 

phys.VST = VSTC*phys.BW; % GI volume (use RP density) 

phys.VL = VLC*phys.BW; 

phys.VF = VFC*phys.BW; 

phys.VBR = VBRC*phys.BW; 

phys.VST = VSTC*phys.BW; 

phys.VS = VSC*phys.BW; 

phys.VR = VRC*phys.BW; 

phys.VAB = BV*(1-VVBC); %volume arterial blood% 

phys.VVB = BV*VVBC; 

phys.GSHRB = 0.1*ps.GSHBR/ps.GSHL; %ratio of brain GSH*GST to liver GSH% 

phys.GSHRST = 0.1*ps.GSHST/ps.GSHL; %ratio of stomach GSH*GST to liver GSH% 

phys.GSHRS = 0.1*ps.GSHS/ps.GSHL; %ratio of spt GSH*GST to liver GSH% 

phys.GSHRR = 0.1*ps.GSHR/ps.GSHL %ratio of rpt GSH*GST to liver GSH% 

 

ICs=[]; 

for i=1:quan.idf % idf is the number of simulations/initial conditions in 

 j1(i) = quan.jt(i); % index of initial data row for this 

experiment/simulation 

 jf(i) = quan.jt(i+1)-1; % index of final data row for this 

expt./simulation 

 tsp{i} = quan.t(j1(i):jf(i)); 

 oral0=quan.dat(j1(i),8)*phys.BW; 

 ps.blood0(i)=quan.dat(j1(i),9)*phys.BW/ps.tinf;

 ps.cinh(i)=quan.dat(j1(i),10)*MW/24450; ps.tinh(i)=quan.dat(j1(i),11); 

 ICs=[ICs;[oral0,zeros(1,ncv-1)]]; % initial conditions 

end 

save ICs ICs 

 

%----------call simulation or optimization procedure------------------ 

 
C-21 DRAFT - DO NOT CITE OR QUOTE 

quan.pt=0; itr=0; P=prs; 

if swtch==0 

 quan.pt=1; 

 y=eval([runfn,'(popt)']); 

elseif swtch==1 

 pnew = exp(neld2(popt, runfn, 1e-6, 1000, 50000)); 

else 

 options = optimset('MaxFunEvals',8000,'MaxIter',8000); 

 pnew = exp(fminsearch(runfn,popt,options)); 

end 

 

if swtch>0 

 P(pv) = pnew(1:quan.ns); 

 'Initial Parameter Values, Jinit =' 

 Cst=eval([runfn,'(popt)']); 

 'Final Parameters, Jopt =' 

 quan.pt=1; 

 Cst=eval([runfn,'(log(P(pv)))']); 

end 

 

%----------------- final results/plots ------------------- 

co = 

['rbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbk

gmcrbkgmcrbkgmcrbkgmc']; 

%co = ['kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk']; 

pc = 

['+o*xsd^v<>ph+o*xsd^v<>ph+o*xsd^v<>ph+o*xsd^v<>ph+o*xsd^v<>ph+o*xsd^v<>ph+o*

xsd^v<>ph+o*xsd^v<>ph']; 

linet = ['- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'--';': ';'-.';... 

 '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'--';': ';'-.';... 

 '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'--';': ';'-.';... 

 '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'--';': ';'-.';... 

 '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'--';': ';'-.';... 

 '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'--';': ';'-.';... 

 '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'--';': ';'-.';... 

 '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'--';': ';'-.']; 

np=min(quan.idf,96); 

quan.jtp = [find(quan.tp == 0);(length(quan.tp)+1)]; 

% jt = vector of indeces of rows in data file starting with "0"; plus one 

%close all 

kf0=30; 

kf=1+kf0; 

figure(kf) 

rows=ceil(nplt/2); 

set(kf,'Units','inches','Position',[0.1, 0.5, 6.3, (0.1+2.5*rows)]); 

set(gcf,'DefaultTextFontSize',10,'DefaultAxesFontSize',12,'DefaultTextFontNam

e','Arial'); 

npt = -1; 

for k = 1:6 

 if quan.datc{k} 

 npt=npt+2; 

 pos=mod(npt,(rows*2))+(npt>(rows*2)); 

 h=subplot(rows,2,pos); 

 set(h,'Units','inches','Position',[(3.5-

2.95*mod(pos,2)),(0.45+2.35*(rows-ceil(pos/2))),2.7,2.1]) 

 box on 

 j1=quan.jt(1); 

 j2=quan.jt(2)-1; 

 p1=quan.jtp(1); 

 p2=quan.jtp(2)-1; 
C-22 DRAFT - DO NOT CITE OR QUOTE 

 dt=quan.t(j1:j2); 

 dp = datc(j1:j2,k); 

 dj = find(dp > 0); 

 dk=find(datc(:,k)>0); 

 xm=ceil(1.01*max(quan.t( dk ))*10)/10; 

 xl=floor(0.99*min(quan.t( dk )*10)-1)/10; 

 if xl<0 

 xl = - round(2.5*xm)/100; 

 end 

 ym=max(log10(1.1*[Ccafpt(find(Ccafpt(:,k)>0),k);datc(dk,k)])); 

 if (10^ceil(ym))/(10^ym) > 2 

 ym = (10^ceil(ym))/2; 

 else 

 ym = 10^ceil(ym); 

 end 

 set(gca,'YScale','log') 

 if k==1 

 axis([xl,xm,.03,ym]) 

 end 

 if k==2 

 axis([xl,xm,.01,ym]) 

 end 

 if k==3 

 axis([xl,xm,.01,ym]) 

 end 

 if k==4 

 axis([xl,xm,.001,ym]) 

 end 

 if k==5 

 axis([xl,xm,.001,ym]) 

 end 

 if k==6 

 axis([xl,xm,.001,ym]) 

 end 

 hold on 

 if dj 

 plot(dt(dj),dp(dj),['k',pc(1)]); %,[co(1),pc(1)]) 

 plot(quan.tp(p1:p2),Ccafpt(p1:p2,k),['k',linet(1,:)]); 

%[co(1),linet(1,:)]); 

 end 

 if np > 1 

 for i = 2:np 

 j1=quan.jt(i); 

 j2=quan.jt(i+1)-1; 

 dt=quan.t(j1:j2); 

 p1=quan.jtp(i); 

 p2=quan.jtp(i+1)-1; 

 dp = datc(j1:j2,k); 

 dj = find(dp > 0); 

 if dj 

 plot(dt(dj),dp(dj),['k',pc(i)]); %,[co(1),pc(1)]) 

 plot(quan.tp(p1:p2),Ccafpt(p1:p2,k),['k',linet(i,:)]); 

%[co(1),linet(1,:)]); 

 end 

 end 

 end 

 yl=0.1*get(gca,'YLim'); 

 title(yname(k),'Position',[mean(get(gca,'XLim')),yl(2)],'FontSize',14, 

... 

 'EdgeColor','k','BackgroundColor','w','Fontname','Arial'); 
C-23 DRAFT - DO NOT CITE OR QUOTE 

 if k==2 

 legend('show') 

 end 

 hold off 

 end 

end 

 

kf=2+kf0; 

if quan.datc{7} 

 figure(kf); 

 set(kf,'Units','inches','Position',[0.1, 0.5, 3.3, 7.6]); 

 

set(gcf,'DefaultTextFontSize',14,'DefaultAxesFontSize',12,'DefaultTextFontNam

e','Arial'); 

 for k = 7:9 

 h=subplot(3,1,k-6); 

 set(h,'Units','inches','Position',[.55,(0.45+2.35*(9-k)),2.7,2.1]) 

 box on; hold on 

 dk=find(datc(:,k)>0); 

 plot(quan.dat(dk-1,8),datc(dk,k),['k',pc(k-6)]); %,[co(1),pc(1)]) 

 plot(quan.dat(dk-1,8),Ccafc(dk,k),['k',linet(k-6,:)]); 

%[co(1),linet(1,:)]); 

 yl=0.3*get(gca,'YLim'); 

 title(yname(k),'Position',[mean(get(gca,'XLim')),yl(2)],'FontSize',14, 

... 

 'EdgeColor','k','BackgroundColor','w','Fontname','Arial'); 

 hold off 

 end 

end 

 

 

k=nv+1; % show mass balance 

figure(k) 

set(k,'Units','inches','Position',[1,1,4.1,4.1]); 

hold on 

title(yname(k)); 

p1=quan.jtp(1); 

p2=quan.jtp(2)-1; 

plot(quan.tp(p1:p2),Ccafpt(p1:p2,k),[co(1),linet(1,:)]); 

for i = 2:np 

 p1=quan.jtp(i); 

 p2=quan.jtp(i+1)-1; 

 plot(quan.tp(p1:p2),Ccafpt(p1:p2,k),[co(i),linet(i,:)]); 

end 

 

if swtch>0 

'optimized params = ' 

[num2str([1:length(P)]'),char(pbl),char(pname),char(pbl),num2str(P)] 

end 

%RunACN file to return value of objective function, given input parameters

function Cost = RunACN(popt)

%----------------------------globals------------------------

global phys prs yname quan itr pv pvar pbl j1 jf ian ICs ncv tsp Ccafpt C0 

global Cost Ccafc MW MW2 VMAX VMAX2 KF KF2 KEH KFBRC KFSTC KFSC KFRC KFBR 

global KFST KFS KFR KA KM KM2 Ccafpt nv ps

tol=1.e-8;

options = odeset('RelTol',tol,'AbsTol',tol);

itr=itr+1;
C-24 DRAFT - DO NOT CITE OR QUOTE 

comp=0;

p = reshape(exp(popt),length(popt),1);

pu=prs;

pu(pv)=p;

save ptemp pu

[num2str(pv'),char(pbl(pv)),char(pvar),char(pbl(pv)),num2str(p)]

%quan.gam(1:5)=2./exp(exp(-popt((quan.ns+1):(quan.ns+5)) ));

%quan.gam(6:11)=quan.gam(5);

%quan.gam(1:5)

% display current values of parameters being valued (retransformed)

Ccafpt=[];Ccafw=[];

quan.tp=[];

comp=comp+1;

VMAXC = pu(1); %Max. vel. of metabolism, CEO (mg/hr-kg^0.7)%

KM = pu(2); %Michaelis-Menten constant (mg/L)%

VMAXC2=pu(3); %Max. vel of metabolism, CEO (mg/hr-jg^0.7)

KM2=pu(4); %CEO M-M constant (mg/L)

KEHC = pu(5); %Effective 1st-order EH rate, liter/hr/kg^0.7

KFC = pu(6); %ACN first order metab rate const (/hr-1kg)%

KFC2 = pu(7); %CEO first order metab rate const (/hr-1kg)%

KA = pu(8); %Oral uptake rate (/hr)%

gA = min(pu(9),2); % gammA

gC = min(pu(10),2); % gammC

ps.KH = pu(11);

ps.KHR2 = pu(12);

ps.KB = ps.KH + ps.KB0; %ACN 1ST order binding to blood hb + RSH (/hr)%

ps.KH2 = ps.KH*phys.KHR*ps.KHR2;

ps.KB2 = ps.KH2 + ps.KB20 

% VMAX = VMAXC*(phys.BW^0.7); %Liver P450 ACN to CEO%

 VMAX2 = VMAXC2*(phys.BW^0.7); %Liver CEO Hydrolysis%

 KF = KFC/(phys.BW^0.3); %Liver ACN-GSH rate%

 KF2 = KFC2/(phys.BW^0.3); %Liver CEO-GSH/RSH rate%

 KEH = KEHC*(phys.BW^0.7); % Approx. first-order rate in liver %

 %CEO rxn rates%

 KFBR = KF2*phys.GSHRB; %CEO brain RSH rate%

 KFST = KF2*phys.GSHRST; %CEO stomach RSH rate%

 KFS = KF2*phys.GSHRS; %CEO SPT RSH rate%

 KFR = KF2*phys.GSHRR; %CEO RPT RSH rate%

%-------------------------------loop for running equations-------------------

-

% figure(15)

% set(15,'Units','inches','Position',[1,1,4.1,4.1]);

% hold on

% title('RAM1');

for i=1:quan.idf % idf is the number of simulations/initial conditions in

 % the data file this was computed in optACN.m

ian=i;

tsc = [0:1050]'*quan.t(jf(i))/1000;

%ICs(i,[1,16])

[ts,Ys] = ode15s(@EqACN2,tsc,ICs(i,:),options); %

%[ts(1:4),Ys(1:4,1:16)]'

%[Ys(1:10,13),VMAX*Ys(1:10,13)./(KM+Ys(1:10,13)),(Ys(2:11,15)-Ys(1:10,15))]

massb=sum(Ys(:,1:16),2);

% plot(ts,Ys(:,15)); %VMAX*Ys(:,13)./(KM+Ys(:,13)));

% The sequence of columns in the data sets are as follows:
C-25 DRAFT - DO NOT CITE OR QUOTE 

% tspan, CVB, CL, CBR, CVB2, CL2, CBR2, ODOSE(initial), IVDOSE(initial)

Yp=[Ys(:,16)/phys.VVB, Ys(:,13)/phys.VL, Ys(:,11)/phys.VBR, ...

 Ys(:,24)/phys.VVB, Ys(:,23)/phys.VL, Ys(:,22)/phys.VBR, ...

 Ys(:,30:32)/phys.BW, massb];

Ccafc(j1(i):jf(i),:)=interp1(ts,Yp,tsp{i});

quan.tp=[quan.tp;ts]; 

Ccafpt=[Ccafpt;Yp];

Ccafw=[Ccafw;[tsp{i},Ccafc(j1(i):jf(i),:)]];

%--------------------------------end loop----------------------------------- 

end

%----------------------------------------------------------------------------

-

if quan.pt==1

 yname = {'AN in blood'; 'AN in liver'; 'AN in brain'; ...

 'CEO in blood'; 'CEO in liver'; 'CEO in brain'; ...

 'AN-GSH in urine'; 'CEO-GSH in urine'; 'Hb binding'; 'mass 

balance'};

 fid=fopen(['ACN.txt'],'w');

 fprintf(fid,['time','\t','CVB','\t','CL','\t','CBR','\t',...

 'CVB2','\t','CL2','\t','CBR2','\t','mball','\r']);

 fprintf(fid,'%g\t%g\t%g\t%g\t%g\t%g\t%g\t%g\r',Ccafw'); 

%[quan.tp,Ccafpt]');

 status=fclose(fid);

end

%Ccafpt=Ccafc;quan.tp=quan.t; % uncomment this line to plot only the fitted

%values

%----------------------------------cost function-----------------------------

-

Cost=C0+max(0,pu(9)-2)+max(0,pu(10)-2);gamm=[gA gA gA gC gC gC gC gC gC];

for i=1:nv

 if quan.datc{i}

 Cost = Cost + gamm(i)*sum(quan.datc{i}) + ...

 quan.nc(i)*log( sum( ((quan.datc{i} - Ccafc(quan.ic{i},i)).^2)./...

 (Ccafc(quan.ic{i},i).^gamm(i)) )/quan.nc(i) );

 end

end

['itr = ',num2str(itr),'; Cost = ',num2str(Cost)]

% ACN PBPK model equation file -- returns derivatve dx = dx/dt, given

% state variable x and parameters passed through global statements

%

%-----------------------------function defined---------------------------

function dx = eqs(t,x)

%------------------------------globals-----------------------------

global prs phys ICs quan ps ian MW2 MW CINH TINH

global VMAX VMAX2 KF KF2 KEH KFBRC KFSTC KFSC KFRC KFBR KFST KFS KFR KA KM 

KM2

%---------------------------assign parameters to names-----------------------

dx=zeros(size(x));

% "dx" = dx/dt, where x is the state vector

%-----------------------------------!

%--------- ACRYLONITRILE ---------!

%-----------------------------------!
C-26 DRAFT - DO NOT CITE OR QUOTE 

% MR = x(1); %MR = Amount in stomach lumen (mg)!

% AB = x(2); %Amount in systemic arterial blood (mg)!

 CA = x(2)/phys.VAB; %concentration

%AX = x(3); % ACN exhaled (mg)!

%AST = x(4); % ACN in stomach tissue tissue (mg)!

 CST = x(4)/phys.VST; CVST = CST/phys.PST; % tissue/venous concn's 

%ASTG = x(5); % ACN GSH conjugated in stomach tissue (mg)

%AS = x(6); % ACN in slowly perfused (mg)

 CVS = x(6)/(phys.VS*phys.PS); % venous concentration

%ASG = x(7); % ACN-GSH conjugated in slowly (mg)

%AR = x(8); % ACN in richly (mg)

 CVR = x(8)/(phys.VR*phys.PR); % venous concentration

%ARG = x(9); % ACN-GSH conjugated in richly

%AF = x(10); % ACN in fat (mg)

 CVF = x(10)/(phys.VF*phys.PF); % venous concentration

%ABR = x(11); % ACN in brain (mg)

 CBR = x(11)/phys.VBR; CVBR = CBR/phys.PBR; % tissue/venous concn's 

%ABRG = x(12); % ACN-GSH conjugated in brain 

%AL = x(13); % ACN in liver (mg)

 CL = x(13)/phys.VL; CVL = CL/phys.PL; % tissue/venous concn's 

% ALG = x(14); ACN-GSH conjugated in liver (mg)

% AM1 = x(15); ACN metabolized by P450 in liver (mg)

% AVB = x(16); ACN in mixed venous blood (mg)

 CVB = x(16)/phys.VVB; % concentration

RMR = KA*x(1); % rate of absorption from stomach

CI=ps.cinh(ian)*(t<=ps.tinh(ian)); %Inhaled concentration

CAL = (phys.QC*CVB+phys.QP*CI)/(phys.QC+(phys.QP/phys.PB)); 

 %CAL = Concentration in arterial lung blood (mg/L)!

%CX = CAL/phys.PB; % concentration in exiting pulmonary air

% CXPPM = (0.7*CX+0.3*CI)*24450./ps.MW

%RAB = ps.KB*x(2)CA*phys.VAB; % ACN binding in arterial blood

STGSH = ps.KSO*CVST*ps.GSHST*phys.VST; % stomach GSH conjugation of ACN

SGSH = ps.KSO*CVS*ps.GSHS*phys.VS; % slowly GSH conjugation of ACN

RGSH = ps.KSO*CVR*ps.GSHR*phys.VR; % richly GSH conjugation of ACN

BRGSH = ps.KSO*CVBR*ps.GSHBR*phys.VBR; % brain GSH conjugation of ACN

LGSH = ps.KSO*CVL*ps.GSHL*phys.VL; % liver GSH conjugation of ACN

% ACN metabolized,saturable (P450) and linear pathways (mg)! 

 RAM1 = VMAX*CVL/(KM+CVL); % (mg/hr)

 %VMAX,KM,RAM1

%ACN metabolized,first-order pathway (GST) (mg)!

 RAM2 = KF*CVL*phys.VL; % (mg/hr)

RTV = 

phys.QF*CVF+(phys.QL+phys.QST)*CVL+phys.QS*CVS+phys.QR*CVR+phys.QBR*CVBR;

 % mixed venous blood concentration

%RVB = ps.KB*CV*phys.VVB; % ACN binding in venous blood

 %[t,CVB/(RTV/phys.QC),CAL/CVB,CA/CAL,x(1),RMR]

 dx(1) = - RMR; % ACN stomach lumen

 dx(2) = phys.QC*(CAL - CA) - ps.KB*x(2); % ACN arterial blood after binding

 dx(3) = phys.QP*CAL/phys.PB; % ACN exiting pulmonary air

 dx(4) = phys.QST*(CA-CVST) - STGSH + RMR; % ACN stomach tissue

 dx(5) = STGSH; % ACN-GSH conjugated in stomach tissue

 dx(6) = phys.QS*(CA-CVS) - SGSH; % ACN slowly

 dx(7) = SGSH; % ACN-GSH conjugated in slowly 

 dx(8) = phys.QR*(CA-CVR) - RGSH; % ACN in richly (mg)

 dx(9) = RGSH; % ACN-GSH conjugated in richly 

dx(10) = phys.QF*(CA-CVF); % ACN in fat (mg)!

dx(11) = phys.QBR*(CA-CVBR) - BRGSH; % ACN in brain (mg)!
C-27 DRAFT - DO NOT CITE OR QUOTE 

dx(12) = BRGSH; % ACN-GSH conjugated in brain

dx(13) = phys.QL*CA + phys.QST*CVST -(phys.QL+phys.QST)*CVL -RAM1 -RAM2 -

LGSH;

dx(14) = LGSH + RAM2 + ps.KB*(x(2)+x(16)); 

 % ACN-GSH conjugated in liver + bound in blood

dx(15) = RAM1; % ACN metabolized by P450 in liver

dx(16) = RTV - phys.QC*CVB - ps.KB*x(16) + ps.blood0(ian)*(t<=ps.tinf); 

 %Mixed ven. ACN conc after binding (mg/L)

dx(30) = STGSH + SGSH + RGSH + BRGSH + LGSH + RAM2 + ps.KFB*(x(2)+x(16));

 % amount of AN binding to GSH

 % [x(1:16),dx(1:16)]'

%----------------------------------------!

%----------------- CEO ----------------!

%----------------------------------------!

%AB2 = x(17); % CEO in arterial blood (mg)

 CA2 = x(17)/phys.VAB; % concentration

%AS2 = x(18); % CEO in slowly perfused (mg)

 CVS2 = x(18)/(phys.VS*phys.PS2); % venous concn

 SGSH2 = KFS*CVS2*phys.VS;

%AR2 = x(19); % CEO in richly (mg)

 CVR2 = x(19)/(phys.VR*phys.PR2); % venous concn

 RGSH2 = KFR*CVR2*phys.VR;

%AST2 = x(20); % CEO in stomach tissue tissue (mg)!

 CST2 = x(20)/phys.VST; CVST2 = CST2/phys.PST2; % tissue/venous concn's 

 STGSH2 = KFST*CVST2*phys.VST;

%AF2 = x(21); % CEO in fat (mg)

 CVF2 = x(21)/(phys.VF*phys.PF2); % venous concn

%ABR2 = x(22); % CEO in brain (mg)

 CBR2 = x(22)/phys.VBR; CVBR2 = CBR2/phys.PBR2; % tissue/venous concn's 

 BRGSH2 = KFBR*CVBR2*phys.VBR;

%AL2 = x(23); % CEO in liver (mg)

 CL2 = x(23)/phys.VL; CVL2 = CL2/phys.PL2; % tissue/venous concn's 

% AVB2 = x(24); % Mixed ven. CEO conc after binding!

 CVB2 = x(24)/phys.VVB; % concentration

RALG2 = (VMAX2*CVL2/(KM2+CVL2)) + KF2*CVL2*phys.VL;

 % CEO hydrolysis, saturable + linear terms

 % For fitting, either saturable or linear is set to zero

CV2 = (phys.QF*CVF2 + (phys.QL+phys.QST)*CVL2 + phys.QS*CVS2 + phys.QR*CVR2 

...

 + phys.QBR*CVBR2)/phys.QC; % CEO mixed venous blood conc. (mg/L)

CAL2 = (phys.QC*CVB2)/(phys.QC+(phys.QP/phys.PB2)); % CEO in arterial lung 

blood (mg/L)!

dx(17) = (phys.QC*CAL2)-(phys.QC*CA2)-(ps.KB2*x(17)); 

 % CEO in systemic arterial after binding

dx(18) = phys.QS*(CA2-CVS2) - SGSH2; % CEO in slowly perfused tissues (mg)!

dx(19) = phys.QR*(CA2-CVR2) - RGSH2; % CEO in rapidly perfused tissues (mg)! 

dx(20) = phys.QST*(CA2-CVST2) - STGSH2; % CEO in stomach (mg)!

dx(21) = phys.QF*(CA2-CVF2); % CEO in fat tissue (mg)!

dx(22) = phys.QBR*(CA2-CVBR2) - BRGSH2; % CEO in brain tissue (mg)!

dx(23) = phys.QL*(CA2-CVL2) + phys.QST*(CVST2-CVL2) - KEH*CVL2*phys.VL + ... 

 (RAM1*MW2/MW) - RALG2; 

dx(24) = phys.QC*CV2 - phys.QC*CVB2 - ps.KB2*x(24);

 % CEO mixed venous after binding

 

%Calculation of the AUC for ACN and CEO in liver, brain, and blood! 
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dx(25) = CL; % AUC for ACN liver concentration

dx(26) = CBR; % AUC for ACN brain conc.!

dx(27) = CBR2; % AUC for CEO brain conc.!

dx(28) = CVB; % AUC for ACN blood conc.!

dx(29) = CVB2; % AUC for CEO blood conc.!

dx(31) = STGSH2 + SGSH2 + RGSH2 + BRGSH2 + RALG2 + ps.KFB2*(x(17)+x(24));

 % amount of CEO binding to GSH

 

dx(32) = (ps.KH*(x(2)+x(16))) + (ps.KH2*(x(17)+x(24)));

% had problems with state variables going < 0 at one point (stiff system);

% the following is a fix for this.

%dx=(dx.*(x>=0))+(abs(dx).*(x<0));
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APPENDIX D. UNCERTAINTIES ASSOCIATED WITH CHEMICAL-SPECIFIC 

PARAMETERS EMPLOYED IN THE PBPK MODEL FOR AN DOSIMETRY 

IN HUMANS 

 PBPK models are computational tools used to predict chemical/drug disposition. Models 

are comprised of three distinct types of information: physiological, physicochemical, and 

biochemical. The physiological data are chemically independent and describe such parameters 

as organ volumes and blood flows. Physicochemical parameters are chemical specific and 

specify parameters, such as PCs or permeability. Biochemical parameters define the rates of 

chemical transformation or binding. In Appendix D, the EPA evaluates uncertainties in the 

chemical-specific parameters employed in the PBPK model used to predict AN dosimetry in 

humans, which is adapted from that of Sweeney et al. (2003). Only a small number of 

(metabolic) parameters were changed in the EPA's adaptation, which will be noted below. 

Otherwise, it should be understood that any discussion of the model of Sweeney et al. (2003) 

applies to the one used in this assessment.

PCs 

 PCs describe the extent of distribution of chemical into the body, including target tissues 

such as the brain and lungs. PCs employed in the model of Sweeney et al. (2003) were derived 

from rat tissue:air PCs and human blood:air PC for AN or CEO in the following way: 

 Ptissue:blood(human) = Ptissue:air(rat)/ Pblood:air(human) 

 This equation assumes that the relative difference in PCs between tissues is the same in 

rats as in humans. The systematic difference between the two is accounted for by the blood:air 

PC; for humans, the experimentally determined value for AN (154) differed from the value for 

the rat (512) by threefold. Due to the absence of experimental data, Sweeney et al. (2003) set the 

human blood:air PC for CEO equal to the rat value (1,658). 

It may be asked whether the estimates produced by the above equation are reasonable 

considering the chemical characteristics of AN and CEO and the distribution of AN- and 

CEO-soluble components in human tissue. To address these issues, the method of Poulin and 

Theil (2002) was used to estimate the Ptissue:blood(human). The method is based on the additive 

solubilities of a chemical in lipid and water, and the relative distribution of these substances in 

tissues. Sensitivity analysis conducted by Sweeney et al. (2003) identified the Pstomach:blood and 

Pbrain:blood for AN as influential on AN-related dose metrics and the Pbrain:blood for CEO as 

influential on CEO-related dose metrics. Table D-1 provides estimates of PCs for AN and CEO. 

Note that the critical PCs, the Pstomach:blood for AN and the Pbrain:blood for AN and CEO, as 

predicted by the method of Poulin and Theil were within a factor of about 1.5 of the values 

employed by Sweeney et al. (2003). 
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Table D-1. Tissue:blood PCs 

PCs for AN PCs for CEO 

 Compa Expb Exp:comp ratio Compa Expb Exp:comp ratio

Adipose tissue 0.30 0.94 3.11 Adipose tissue 0.22 0.79 3.52 

Brain 1.12 1.34 1.19 Brain 0.99 1.40 1.41 

Stomach 1.00 1.51 1.52 Stomach 0.89 0.27 0.31 

Liver 1.02 1.51 1.48 Liver 0.94 0.27 0.31 

Muscle 0.98 1.16 1.19 Muscle 0.83 1.84 1.97 

Richly perfused 1.00 1.51 1.51 Richly perfused 0.97 0.27 0.28 

aComputationally derived by Poulin and Theil (2002).

bExperimentally obtained/reported by Sweeney et al. (2003). 

To evaluate the influence of the PC in the model, the revised human PBPK model was 

implemented with both sets of PCs (Table D-1, with Pblood:air as measured for AN using human 

blood and for CEO using rat blood). For three different exposure scenarios, the peak AN and 

CEO did not change by more than 30% of initial value (Table D-2). This finding may be 

explained by consistency between both estimates of PC and a general lack of sensitivity to the 

PC (see Sweeney et al., 2003). Indeed, the only PCs with normalized sensitivity coefficients that 

exceeded 0.2 were the Pstomach:blood (AN), Pbrain:blood (AN), and the Pbrain:blood (CEO). Consistent 

with these results, Table D-2 shows a greater impact of changing the PC in the brain than the 

blood (an averaged effect of other PCs). All of the predicted concentration in brain tended to 

decrease when the model was implemented with PC as per the method of Poulin and Theil 

(2002). 
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Table D-2. Impact of method of estimation of PCs on the peak AN and CEO 

model predictions

Peak AN (μg/L) Peak CEO (μg/L) 

Exposure PC methoda

Blood Brain Blood Brain 

S 4.87 11.4 0.998 1.23 

PT 4.87 9.56 0.998 0.863 

Inhalation 

2 ppm, 8 h 

 0.0% -16.4% 0.0% -29.6% 

S 0.975 2.29 0.200 0.245 

PT 0.975 1.91 0.200 0.173 Inhalation 

0.4 ppm, 1 wk 

 0% -16.4% 0% -29.6% 

S 2.50 3.11 8.36 10.14 

PT 2.68 2.77 8.64 7.44 

Oral 

6 pulses in 24 h, 

0.2 mg/kg total 7.3% -10.9% 3.4% -26.7% 

a

S = PCs as estimated by Sweeney et al. (2003) (listed in Appendix C); PT = PCs estimated using the method of 

Poulin and Theil (2002). AN and CEO are from model simulations using other human parameters as listed in 

Appendix C. 

Parameters of metabolic clearance

Sweeney et al. (2003) developed a PBPK model of AN and CEO disposition in humans 

based on human in vitro data and the rat model of Kedderis et al. (1996). Human in vivo

pharmacokinetic data were not available for model development; therefore, the authors proposed 

a rodent-human parallelogram approach to consider uncertainties in the scaling of in vitro 

metabolism data. Critical metabolic pathways included the oxidation of AN to CEO, the 

conjugation of AN and CEO, and the hydrolysis of CEO. 

With the exception of the latter, the scaling of in vitro rate constants for these pathways 

was first investigated by Kedderis et al. (1996), who observed that the scaled rate constants (rat 

model) derived from rat liver microsomes, did not match those constants fit from in vivo rat data. 

Sweeney et al. (2003) employed both in vitro and in vivo data to derive an empirical correction 

factor (CF) to account for uncertainties in scaling (rat). The scaling constant was assumed to be 

constant across species; thus, the preexisting rat model, the empirical CF, and human in vitro 

data were employed to specify a human PBPK model. 

Because EPA altered a number of the rat metabolic parameters to accommodate the rate 

constant for AN hydrolysis extrapolated from in vitro data and to obtain parameters in a way that 

was computationally reproducible, while following the same approach as Sweeney et al. (2003) 

for metabolic parameter extrapolation, the EPA obtained different values for humans. First, we 

describe the derivation of the human VmaxC for the oxidation of AN to CEO in the following 

equations. The ratio of rates determined by human in vitro data and rat in vitro data is 

considered (Kedderis et al. 1993c), as well as the allometrically scaled in vivo rate constant for 

oxidation of AN in the rat. 
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in vitro

V

V

VLC

VLC

[mgMSP / g liver]

[mgMSP / g liver]

BW

BW

in vivo

(mg / h kg/ )

V (rat)

in vivo

(mg / h kg/ )

V (human)

max,human

max,human

rat

human

rat

human

3.0

rat

7.0 human

max C

7.0

maxC

















×

















×

















×

















= ×

 22.1 = 7.1 × 5.422 × 1.4225 × 0.6425 × 0.626 

Next, the value (and calculations) of the empirical CF = 5.785 is shown. This value represents 

what is not accounted for in the in vitro to in vivo scaling in the rat. 





















= × × × ×

3.0

3

7.0

max

7.0

max

/

10 ( / / ) [ / ]

( )

( / / )

( )

rat rat rat

C C

in vivo in vitro VLC BW

kg

g

mgMSP g liver

in vitro

mg h kg

V rat

in vivo

mg h kg

V rat

CF

 5.785 = 7.1 / (0.001164 × 40 × 1000 × 0.04 × 0.659) 

 The allometrically scaled in vivo rate constant for human pseudo first-order GSH 

conjugation of AN and CEO was calculated in the same way (not shown). 

The parallelogram method was applied differently to estimate the rate constant for 

enzymatic hydrolysis by EH in humans. Because the EPA extrapolated the EH rate constant in 

rats from in vitro to in vivo without use of an adjustment factor, the same was done for humans. 

Kedderis and Batra (1993) determined a Vmax and Km EH-mediated hydrolysis of CEO using 

liver microsome samples from six individual humans. The lowest estimated Km in the group was 

600 μM, so the EPA chose to describe the metabolism as first-order since in vivo concentrations 

are expected to stay well below that value, using the ratio of Vmax/Km. The ratio of Vmax/Km was 

first calculated for each individual since Vmax and Km tend to be statistically correlated due to the 

way they are estimated, and an average value for the ratio was then determined to be 7.02 × 10-6

L/minute/mg MP. We can then apply the value of 56.9 mg MP/g liver from Lipscomb et al. 

(2003), the liver fraction of 25.7 g/kg BW, and the standard value of 70 kg BW for a human. 

The rate constant for a standard human is then kEH = (7.02 × 10-6 L/minute/mg EH) × (56.9 mg 

MP/g liver) × (25.7 g liver/kg BW) × (70 kg BW) × (60 minutes/hour) = 43.1 L/hour, and 

assuming it also scales as BW0.7 (because it represents Vmax/Km, with Km assumed constant), 

kEHC = kEH ÷ (0.70 kg)0.7 = 2.20 L/hour-kg0.7. 

The parallelogram approach described by Sweeney et al. (2003) is provocative, 

considering that human in vivo pharmacokinetic data are sparse for many compounds. What 

special assurances are required in using this approach? 

First, what is the basis of the empirical CF? It is the basis to account for: (1) artifacts of 

microsomes that may bias the estimation of rate constants (as suggested by Kedderis et al., 1996) 

or (2) decay in activity due to handling and storage. An analysis by Lipscomb et al. (1998) 

compared the in vivo Vmax that would be obtained by directly extrapolating the in vitro 

metabolism of trichloroethylene to the value obtained by fitting in vivo data and found that the 
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in-vitro-derived value came out to about one half of an in-vivo-fitted value. Thus, it appears that 

a CF is appropriate to account for either or both of these factors. Sweeney et al. (2003) applied 

the same approach to the enzyme-catalyzed GSH conjugation (cytosolic in origin). One concern 

that had existed is that Sweeney et al. (2003) had been forced to assume that the same factor 

holds for distinct enzymes (P450 and EH) that are membrane bound, because EH activity in the 

rat was taken to be zero in the original model of Kedderis et al. (1996), but that assumption is no 

longer required since the EPA was able to extrapolate the EH-mediated activity without 

adjustment. The EPA must still assume that the factors for P450 and GST hold across species, 

but, given that the in-vitro enzyme preparations and measurements of activity were made in the 

same way for both animals and humans, this seems a reasonable assumption. Nevertheless, it 

does represent a source of uncertainty. 

The human PBPK model (with the EPA's revised parameters) can be tested by comparing 

the data of Jakubowski et al. (1987) with mass-balance calculations from the PBPK model 

(Table D-3). Unfortunately, there are some significant discrepancies between the data of 

Jakubowski et al. (1987) and these simulations. The respiratory retention (nominally in the lung) 

of AN from subjects exposed through a face mask ranged from 44 to 58%, with an average of 

51.8%. The PBPK model predicts 99% uptake of AN inhaled to the pulmonary region. 

Recognizing that ~30% of inhaled air only enters the conducting airways (so-called “dead 

space”), the PBPK model effectively predicts a retention of 69%, which is considerably higher 

than measured. The respiration rates of the subjects in the Jakubowski et al. (1987) experiment 

ranged from 366 to 625 L/hour, with an average of 508 L/hour, which corresponds to an alveolar 

ventilation rate of 356 L/hour, while the PBPK model utilized a rate of 300 L/hour (for a 70-kg 

person), but increasing the respiration rate in the model by this amount (while holding all other 

parameters constant) only decreases the alveolar uptake fraction from 98.7 to 98.5%. A possible 

explanation is that AN is subject to a considerable “wash-in/wash-out” effect, where some of the 

material inhaled deposits temporarily in the conducting airways and then desorbs on expiration, 

which is not accounted for in the model. 
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Table D-3. PBPK mass balance predictions for an 8-hour human exposure 

to 2 ppm AN 

Parameter Metric Amount (mg) Percent 

AI AN mass inhaled 10.389 

AX AN mass exhaled 0.133 1.3 

ATi AN final tissue mass (including blood) 0.725 7.0 

AMt AN metabolized by ... 5.102 49.1 

AMo AN oxidized 3.904 37.6 

AMgt AN enzymatically conjugated (in liver) 0.280 2.7 

AMgn AN non-enzymatically conjugated 0.918 8.8 

Metabolic mass balance 

(AMo + AMgt + AMgn)/AMt 100.00% 

ABD AN bound to Hb and sulfhydrils 4.429 42.6 

Total AN mass balance 

(AX + ATi + AMt + ABD)/AI 100.00% 

CMo CEO formed from AN oxidationa 5.080 

CX CEO mass exhaled 0.001 0.0 

CTi CEO final tissue mass 0.097 1.9 

CEH CEO hydrolyzed 1.128 22.2 

CCl CEO conjugated in liver 2.596 51.1 

Ccti CEO conjugated in other tissues 0.283 5.6 

CBD CEO bound to Hb and sulfhydrils 0.975 19.2 

CEO mass balance 

(Cti + CEH + CCl + Ccti + CBD)/CMo 100.00%

aCMo = AMo × MWCEO ÷ MWAN.

The subjects of Jakubowski et al. (1987) were then exposed in a chamber for 8 hours to 

an average of 10.8 or 5.6 mg/m3

 (5 or 2.6 ppm), and the total excretion of CEO in the urine was 

found to be an average of 26.4 or 16.3% of the retained dose (portion not exhaled) at those 

respective exposure levels. The PBPK model predicts that 38% of the retained AN is oxidized to 

CEO and that 22% of that CEO is hydrolyzed, with these fractions being fairly constant at 

≤8 ppm. Assuming that all the hydrolysis product was excreted in the urine, that the acidextraction method of Jakubowski et al. (1987) would have reversed the hydrolysis, and that the 

extraction/HPLC technique would have separated that product from the GSH conjugates and 

other metabolites, the predicted urinary excretion of “CEO” would then be 8.4% of the retained 

dose. Alternately, if it is assumed that all CEO conjugated with GSH was excreted in the urine 

and that the method of Jakubowski et al. (1987) had cleaved the GSH conjugates, then the total 

CEO predicted in the urine would be 79% of the CEO formed or 30% of the retained AN. 

Therefore, the measured CEO excretion as a fraction of the retained dose is bracketed by the 

predicted levels, depending on what is assumed about the assay method. These results indicate 

that the model predictions of AN and CEO metabolism in humans subsequent to absorption are 

at least in the right range. 

Kedderis et al. (1996) suggest that the overestimation of CEO by the rat model at the 

early time points (which also occurs in the EPA's revision) may be due to an intrahepatic first 
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pass effects, as occurs with other epoxides formed in situ from their parent olefins (Filser and 

Bolt, 1984). The introduction of such a structure (“privileged access” as coined by Kohn and 

Melnick, 2000) would contribute to the efficient clearance of CEO; however, whether the needed 

differential reduction of CEO levels in the early phase would also be accomplished is not clear. 

The issue is that the model predicts a very rapid rise for CEO in blood to peak/plateau levels 

(Figure 3-5a, top panels), while the data show a gradual rise over the first ~10 minutes. It is not 

evident that a privileged access model would account for this dynamic difference since the 

current model allows for reaction of AN with GSH in stomach tissue and liver before reaching 

the general circulation. Further, the same lack-of-fit occurs vs. the CEO i.v.-exposure data 

shown in Figure 3-3, which could not be explained by a first-pass effect from GI absorption. 

An alternate explanation is that the model currently assumes constant GSH levels, while 

GSH may be depleted during the early part of the exposure. A model that includes this depletion 

could predict that at very short times when GSH is near control levels, relatively little AN would 

remain unconjugated for conversion to CEO, but, as the depletion occurs, more and more AN 

would be available for oxidative conversion to CEO, hence the gradual rise. To accurately 

calibrate parameters that accomplish intrahepatic clearance would require a description of GSH 

kinetics. 

Thus, the inability to fit the rat blood CEO levels over the entire time course and the lack 

of understanding of the biological basis for those kinetics indicate a level of uncertainty in the 

model that could be addressed through further research. While the model’s overprediction of 

AN absorption in humans indicates that the description of gas uptake could be improved, this 

discrepancy is only 10–30% (much less than the apparent 3- to 10-fold overprediction of blood 

and brain CEO levels in rats and [likely] in humans by the oral route). However the model does 

predict AN and CEO blood and tissue levels from inhalation exposure in rats at the lowest 

concentration measured (186 ppm) quite well (Figure 3-4a), indicating that the gas-uptake 

description is adequate for prediction of rat dosimetry, and an adjustment of the description in 

humans would lower the predicted uptake and hence the extrapolated risk. Therefore, the use of 

the model to predict CEO levels after AN inhalation in humans should be adequately protective. 

For oral exposures, however, the greater accuracy of the AN predictions vs. CEO (Figure 3-5b 

vs. 3-5a), suggests greater certainty in the use of AN, although the mode of action suggests that 

CEO is the active metabolite. 

Sensitivity and Uncertainty Analysis

 Sensitivity and uncertainty analyses were performed to investigate the dependence of 

PBPK model predictions for AN and CEO on specific model parameters and to estimate the 

overall uncertainty in those predictions, given estimates of uncertainty in specific model 

parameters. 
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 The first step was to perform a sensitivity analysis on PBPK model predictions to identify 

the degree to which model dose metric predictions depend on model parameters. For this 

purpose, normalized sensitivity coefficients were calculated. For example, the sensitivity of a 

model prediction of concentration (e.g., AN concentration in blood) to parameter P (e.g., 

metabolic VmaxC for AN oxidation), the normalized sensitivity coefficient is: 

S = (dC/dP) × (P/C) 

The first term is the derivative of C with respect to P. (C is generally a function of time, so this 

derivative will also depend on time.) This derivative is approximated by alternately increasing 

and decreasing P by a small fraction, ∆P (taken to be 1% of P here) and calculating [C(P + ∆P) – 

C(P – ∆P)] ÷ (2 × ∆P). The second term normalizes the sensitivity with respect to the value of C 

at the normal value of P and with respect to P, essentially yielding the percent change in C given 

a 1% change in P. These sensitivities typically vary between ±1, where values near 1 show high 

sensitivity and values near 0 show low sensitivity.

 Sensitivities were determined for four dose metrics, the blood and brain concentrations of 

AN and CEO, under an inhalation and an oral exposure scenario for the human PBPK model. 

For simplicity, the EPA considered continuous exposures to either 0.4 ppm AN by inhalation or 

an oral absorption rate equal to 1 mg/kg-day and analyzed the values of these metrics at 

24 hours, by which time, the human body is predicted to reach steady state. Under such 

conditions, the AUC for each metric is just 24 hours times the steady-state concentration 

(subsequent to reaching steady state), and hence, the sensitivity of the AUC is identical to the 

sensitivity of the concentration, given that the coefficients are normalized as described above. 

Since these concentrations are in the linear range of the model, they apply across the low-dose, 

linear range of concentrations. The sensitivity coefficients for each parameter for which at least 

one coefficient had absolute value greater than 0.1 are listed in Tables D-4 and D-5 for the 

inhalation and oral scenarios, respectively. 
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Table D-4. Sensitivity of AN and CEO metrics for continuous inhalation 

exposure 

Dose metricsa (concentrations) 

Parameter AN in blood AN in brain CEO in blood CEO in brain 

QCC -0.49 -0.57 0.51 0.64 

QPC 0.99 0.99 0.99 0.98 

VLC -0.01 -0.01 -0.64 -0.64 

VBRC -0.01 -0.04 -0.04 -0.14 

VSC -0.14 -0.10 -0.28 -0.28 

VABC -0.07 -0.07 -0.12 -0.15 

VVBC -0.12 -0.08 -0.20 -0.20 

QLC -0.76 -0.53 0.65 0.65 

QBRC 0.00 0.03 0.00 0.10 

QSC -0.02 -0.01 -0.10 -0.10 

GSHL 0.00 0.00 0.27 0.38 

GSHBR -0.01 -0.04 -0.04 -0.14 

GSHS -0.13 -0.09 -0.27 -0.27 

VmaxC -0.09 -0.06 0.11 0.11 

Km 0.09 0.06 -0.11 -0.11 

kFC2 0.00 0.00 -0.86 -0.96 

kEHC 0.00 0.00 -0.25 -0.25 

kBC -0.19 -0.16 -0.16 -0.16 

kBC2 0.00 0.00 -0.13 -0.15 

PBR 0.00 0.97 0.00 0.00 

PBR2 0.00 0.00 0.00 1.00 

aValues are normalized sensitivity coefficients (i.e., (dC/dP) × (P/C), for sensitivity of concentration C to parameter 

P) for steady state blood and brain concentrations predicted for humans during an exposure to 0.4 ppm AN. 

Sensitivities are approximated by increasing and decreasing each parameter by 1% of its default value. Values of 

0.2 or greater are indicated in bold and values between 0.1 and 0.2 in italics. Parameters for which all coefficients 

are less than 0.1 are omitted.
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Table D-5. Sensitivity of AN and CEO metrics for continuous oral exposure 

Dose metricsa (concentrations) 

Parameter AN in blood AN in brain CEO in blood CEO in brain 

BW 0.21 0.20 0.24 0.24 

QCC 0.30 0.36 0.27 0.39 

VLC -0.07 -0.07 -0.64 -0.64 

VBRC -0.01 -0.04 -0.03 -0.13 

VSC -0.10 -0.10 -0.19 -0.19 

VVBC -0.12 -0.12 -0.13 -0.13 

QLC 0.29 0.29 0.35 0.35 

GSHL 0.00 0.00 0.27 0.38 

GSHBR -0.01 -0.04 -0.03 -0.13 

GSHS -0.09 -0.09 -0.18 -0.18 

VmaxC -0.89 -0.89 0.11 0.11 

Km 0.89 0.89 -0.11 -0.11 

kFC2 0.00 0.00 -0.86 -0.96 

kEHC 0.00 0.00 -0.25 -0.25 

kBC -0.17 -0.19 -0.01 -0.01 

kBC2 0.00 0.00 -0.13 -0.15 

PBR 0.00 0.97 0.00 0.00 

PBR2 0.00 0.00 0.00 1.00 

aValues are normalized sensitivity coefficients (i.e., (dC/dP) × (P/C), for sensitivity of concentration C to parameter 

P), for steady state blood and brain concentrations predicted for humans during a continuous oral infusion equal to 

1 mg/kg-d. Sensitivities are approximated by increasing and decreasing each parameter by 1% of its default value. 

Values of 0.2 or greater are indicated in bold, and values between 0.1 and 0.2 in italics. Parameters for which all 

coefficients are less than 0.1 are omitted.

 The EPA’s results can be compared to those of Sweeney et al. (2003), derived for the 

original model, with previous parameter values. For the inhalation scenario (Table D-4), the 

EPA's results for AN are essentially identical to those of Sweeney et al. (2003), and those for 

CEO show the same qualitative pattern and only have a few notable differences. The sensitivity 

to the rate constant for CEO hydrolysis (kEHC in the EPA’s model; VmaxC2 in Sweeney et al., 

2003) is -0.25 in the revised model and −0.5 in their previous model, indicating somewhat less 

importance for this parameter now. On the other hand, the sensitivity to CEO-GSH conjugation 

in the liver parameterized by kFC2 increased from ~0.6−0.7 for Sweeney et al. (2003) to ~0.9 with 

the revised model, showing more significance now. Thus, there is a shift in the relative 

importance of these two parameters and the rate constant for GSH conjugation in humans is an 

especially important factor in the EPA’s predictions, while the exact rate of CEO hydrolysis is 

less influential, though still somewhat important. 
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 Important factors in comparing the EPA’s results for an oral exposure to those of 

Sweeney et al. (2003) are that the EPA held the dose in mg/kg-day constant, so that it varied in 

proportion to BW when that parameter was varied, while Sweeney et al. (2003) held the dose in 

mg/day constant, and they calculated sensitivities of the AUC and peak concentrations for only 

the AN metrics, while the EPA used steady-state concentrations of AN and CEO. Thus, it is not 

surprising that Sweeney et al. (2003) had a negative sensitivity to BW, since the same total dose 

given to a larger body would result in a lower concentration, while the EPA's is positive, 

reflecting that a proportionately higher dose is expected to yield higher-than-proportional 

concentrations because the rates of metabolic elimination scale as BW0.7. 

 It is interesting to note that the liver volume (fraction), which effects the rates of firstand second-order reactions in the model, and the rate constants for CEO removal but not CEO 

production (VmaxC) significantly affect the CEO metrics (absolute values from Sweeney et al. 

(2003) are about 0.17–0.18 for sensitivity of CEO metrics to Vmax and Km). The EPA’s lack of 

significant dependence on blood flow rates to stomach (QStC) and slowly-perfused tissues (QSC) 

is due to the fact that the EPA is analyzing a continuous infusion, as these do significantly affect 

the peak concentration after a bolus exposure. Thus, these are only important for specific dosing 

scenarios. 

 Likewise the rate of absorption (kA) from the stomach significantly affects the peak 

concentration (verified but not shown for the revised model) but has a much smaller affect on the 

AUC. These results for absorption are not surprising, since changes in kA do not alter the fact 

that the entirety of an oral bolus is predicted to be absorbed. Whether or not there is an impact 

on the steady-state concentrations depends on what one believes about oral absorption. In 

particular, if one assumes 100% absorption, where the rate of absorption increases with the 

amount in the GI tract, then at steady state, the rate of absorption must equal the rate of ingestion 

and the exact rate of absorption is unimportant. It is only if orally ingested material may be 

eliminated in the feces or otherwise transformed in the gut without absorption that the exact rate 

constant for absorption would be important. 

 Finally, uncertainty in these steady-state model predictions was estimated using the 

equation of Sweeney et al. (2003) for the approximate coefficient of variation (CV): 

= ∑( ⋅ )

i

m mi CVi CV S

2

where CVm is the estimated CV for metric “m,” Smi is the sensitivity coefficient of metric “m” to 

parameter pi, as tabulated above, and CVi is the CV of pi. For this calculation, the EPA decided 

to use the individual parameter CV values as estimated and used by Sweeney et al. (2003, see 

Table 3-5 in that paper). The CVs for physiological parameters (e.g., blood flow rates, tissue 

fractions) would indeed be identical, and, while the EPA reestimated some metabolic parameters 
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and kA, the underlying in vitro data on which the human extrapolation is based are the same, and 

hence, they are expected to be approximately the same. 

 The resulting CV values for the EPA’s four metrics under the two exposure scenarios are 

listed in Table D-6. 

Table D-6. Estimated CVs for AN and CEO metrics 

Dose metrics (concentrations) 

Exposure scenario AN in blood AN in brain CEO in blood CEO in brain 

0.4 ppm inhalation 0.620 0.656 0.893 1.15 

1 mg/kg-d oral 0.790 0.873 0.711 1.01 

The overall CVs in Table D-6 are interesting in themselves, in that they indicate the 

overall level of confidence in the model’s prediction of those dose metrics. But even more 

interesting is the contribution of the individual parameters to each of these metrics, as listed in 

Tables D-7 and D-8. What those contributions show is that the vast majority of the uncertainty 

arises from a small number of parameters and that most of those parameters are physiological 

values—alveolar ventilation (QCC), cardiac output (QPC), and blood flow to the liver (VLC)—and 

the brain:blood PC in the case of the brain metrics. 
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Table D-7. Parameter contributions to overall CVs for inhalation exposure 

Dose metricsa (concentrations) 

Parameter AN in blood AN in brain CEO in blood CEO in brain 

QCC 9.3 11.5 5.0 4.6 

QPC 37.9 33.9 18.2 11.0 

VLC 0.0 0.0 7.7 4.6 

VBRC 0.0 0.1 0.1 0.5 

VSC 0.7 0.3 1.4 0.9 

VABC 0.4 0.4 0.6 0.5 

VVBC 1.1 0.5 1.5 0.9 

QLC 44.4 19.8 15.9 9.6 

QBRC 0.0 0.1 0.0 0.2 

QSC 0.0 0.0 0.4 0.2 

GSHL 0.0 0.0 1.1 1.3 

GSHBR 0.0 0.2 0.1 0.7 

GSHS 0.9 0.4 1.8 1.1 

VmaxC 1.1 0.5 0.7 0.4 

Km 0.4 0.2 0.3 0.2 

kFC2 0.0 0.0 39.2 29.8 

kEHC 0.0 0.0 3.4 2.1 

kBC 2.9 1.8 1.0 0.6 

kBC2 0.0 0.0 0.7 0.5 

PBR 0.0 30.0 0.0 0.0 

PBR2 0.0 0.0 0.0 29.9 

aValues are 100 × Smk

2 × CVk/Σ(Smi2 × CVi). Values >5 (i.e., 5% contribution) are in bold.
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Table D-8. Parameter contributions to overall CVs for oral exposure 

Dose metricsa (concentrations) 

Parameter AN in blood AN in brain CEO in blood CEO in brain 

BW 1.1 0.8 1.7 0.8 

QCC 2.2 2.5 2.1 2.3 

VLC 0.1 0.1 12.1 6.0 

VBRC 0.0 0.1 0.1 0.5 

VSC 0.2 0.2 1.0 0.5 

VVBC 0.7 0.5 0.9 0.5 

QLC 4.1 3.4 7.1 3.5 

GSHL 0.0 0.0 1.8 1.7 

GSHBR 0.0 0.1 0.1 0.8 

GSHS 0.3 0.2 1.3 0.6 

VmaxC 66.1 54.1 1.2 0.6 

Km 23.1 18.9 0.4 0.2 

kFC2 0.0 0.0 61.9 38.6 

kEHC 0.0 0.0 5.4 2.7 

kBC 1.4 1.5 0.0 0.0 

kBC2 0.0 0.0 1.0 0.7 

PBR 0.0 16.9 0.0 0.0 

PBR2 0.0 0.0 0.0 38.7 

aValues are 100 × Smk2 × CVk/Σ(Smi2 × CVi). Values >5 (i.e., 5% contribution) are in bold.

Since the PCs are expected to be similar in rats and humans, and the extrapolation really 

depends on the rat:human ratio of those, the true resulting uncertainty is likely to be very small. 

The nominal uncertainty in cardiac ventilation and blood flows is expected to be a composite of 

uncertainty and inter-individual variability. And the only metabolic parameter to contribute 

significantly to the uncertainty for inhalation exposure is the CEO-GSH conjugation rate. Thus, 

a significant improvement in the overall uncertainty can be gained by further investigation of 

only a small number of parameters, half of which are applicable to every PBPK model that might 

be considered for gases. 

 The distribution of parameter influence for the oral simulation scenario, as shown in 

Table D-8, is similar to that for inhalation in that most of the influence is distributed among a 

few parameters, with the brain:blood PCs strongly influencing brain concentrations. Also similar 

is that the CEO-GSH conjugation rate (kFC2) is a significant factor for the CEO metrics. Unlike 

the inhalation case, alveolar ventilation (QPC) has negligible influence, which is to be expected, 

but also cardiac output (QCC) has only small influence. This later case occurs because of the 

strong first-pass effect for AN as it is absorbed through the liver, which also explains the very 

high influence of the oxidation parameters, VmaxC and Km, on the AN metrics. 
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 These results for oral exposure are quite similar to the results obtained by Sweeney et 

al. (2003), except that their results indicate somewhat higher influence by blood flow to the liver 

(i.e., 8–12% on AN metrics), liver GSH (6%), and a much higher influence of CEO hydrolysis 

(kEHC here, parameterized by a Vmax and Km with influence of 12–30%) on CEO metrics. The 

shift of influence from hydrolysis to GSH conjugation for CEO metrics between Sweeney et al. 

(2003) and the EPA's results arises from the shift in the relative rates through those two 

pathways, but in both, the rate of CEO removal is a strong determinant of the CEO metric.