Considerations for Using Genetic and Epigenetic Information in Occupational Health Risk Assessment and Standard Setting

Journal of Occupational and Environmental Hygiene

Volumn 12, Issue , 2015, Pages S69-S81

  Schulte, P A ^a   Whittaker, C ^a   Curran, C P ^b  

^a NATIONAL INSTITUTE FOR OCCUPATIONAL SAFETY AND HEALTH   (United States)

^b NORTHERN KENTUCKY UNIVERSITY   (United States)

Author keywords

gene environment interaction; genotype; molecular epidemiology; polymorphisms; xenobiotic

Indexed keywords

DANGEROUS GOODS;

ANALYSIS; DANGEROUS GOODS; GENETIC EPIGENESIS; GENETIC POLYMORPHISM; GENETICS; GENOTYPE ENVIRONMENT INTERACTION; HUMAN; OCCUPATIONAL EXPOSURE; OCCUPATIONAL HEALTH; PROCEDURES; RISK ASSESSMENT; STANDARDS; TOXICITY; TOXICOGENETICS;

EPIGENESIS, GENETIC; GENE-ENVIRONMENT INTERACTION; GENETICS; HAZARDOUS SUBSTANCES; HUMANS; OCCUPATIONAL EXPOSURE; OCCUPATIONAL HEALTH; POLYMORPHISM, GENETIC; RISK ASSESSMENT; TOXICOGENETICS;

EID: 84947601278     PISSN: 15459624     EISSN: 15459632     Source Type: Journal    
DOI: 10.1080/15459624.2015.1060323     Document Type: Article

References (148)

1. Bois, F.Y., G. Krowech, L. Zeise.: Modeling human interindividual variability in metabolism and risk: the example of 4-aminobiphenyl. Risk Anal. 15 (2): 205-213 (1995).
2. Ingelman-Sundberg, M.: Genetic variability in susceptibility and response to toxicants. Toxicol Lett. 120 (1-3): 259-268 (2001).
3. Henry, C.J., R. Phillips., F. Carpanini., et al.: Use of genomics in toxicology and epidemiology: findings and recommendations of a workshop. Environ. Health Perspect. 110 (10): 1047-1050 (2002).
4. Jonsson, F, G. Johanson.: A Bayesian analysis of the influence of GSTT1 polymorphism on the cancer risk estimate for dichloromethane. Toxicol. Appl. Pharmacol. 174 (2): 99-112 (2001).
5. Nebert, D.W.: Inter-individual susceptibility to environmental toxicants-a current assessment. Toxicol. Appl. Pharmacol. 207 (2 Suppl): 34-42 (2005).
6. Faustman E.M, Omenn, G.: Risk Assessment and the Impact of Ecogenetics. In Gene-environment Interactions: Fundamentals of Ecogenetics, L.G. Costa. and D.l. Eaton. (eds.). Hoboken, NJ: John Wiley & Sons, 2006. pp. 427-450.
7. Yu, X., W.C. Griffith., K. Hanspers. et al.: A system-based approach to interpret dose-and time-dependent microarray data: Quantitative integration of gene ontology analysis for risk assessment. Toxicol. Sci. 92 (2): 560-577 (2006).
8. Kuppsamy, S.P., J.P. Kaiser, S.C. Wesselkamper.: Epigenetic regulation in environmental chemical carcinogenesis and its applicability in human health risk assessment. Int. J. Toxicol. 34 (5): 384-392 (2015).
9. Christiani, D.C., A.J. Mehta, C.L. Yu.: Genetic susceptibility to occupational exposures. Occup. Environ. Med. 65 (6): 430-436 (2008).
10. Ginsberg, G., S. Smolenski., P. Neafsey. et al.: The influence of genetic polymorphisms on population variability in six xenobiotic-metabolizing enzymes. J. Toxicol. Environ. Health Part B Crit. Rev. 12 (5-6): 307-333 (2009).
11. Gohlke, J.M., R. Thomas., Y. Zhang. et al.: Genetic and environmental pathways to complex diseases. BMC Syst. Biol. 3 (2009).
12. Bollati, V, A. Baccarelli.: Environmental epigenetics. Heredity 105 (1): 105-112 (2010).
13. Chiu, W.A., S.Y. Euling., C.S. Scott, R.P. Subramaniam.: Approaches to advancing quantitative human health risk assessment of environmental chemicals in the post-genomic era. Toxicol. Appl. Pharmacol. (2010).
14. U.S. Department of Health and Human Services.: Genetics in the Workplace: Implications for Occupational Safety and Health. Cincinnati, OH: Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health 2009.
15. Bernstein, D.I., G.E. Kissling., G.K. Hershey. et al.: Hexamethylene diisocyanate asthma is associated with genetic polymorphisms of CD14, IL-13, and IL-4 receptor alpha. J. Allergy Clin. Immunol. 128 (2): 418-420 (2011).
16. Ginsberg, G., K. Angle., K. Guyton, B. Sonawane.: Polymorphism in the DNA repair enzyme XRCC1: Utility of current database and implications for human health risk assessment. Mutat. Res. Rev. Mutat. Res. 727 (1-2): 1-15 (2011).
17. Mansi, A., R. Bruni., P. Capone. et al.: Low occupational exposure to benzene in a petrochemical plant: Modulating effect of genetic polymorphisms and smoking habit on the urinary t,t-MA/SPMA ratio. Toxicol. Lett. 213 (1): 57-62 (2011).
18. McHale, C.M., L. Zhang, M.T. Smith.: Current understanding of the mechanism of benzene-induced leukemia in humans: implications for risk assessment. Carcinogenesis 33 (2): 240-252 (2012).
19. Patel, C.J., R. Chen, A.J. Butte.: Data-driven integration of epidemiological and toxicological data to select candidate interacting genes and environmental factors in association with disease. Bioinformatics 28 (12): I121-I126 (2012).
20. Owen, R., T.S. Galloway., J.A. Hagger., M.B. Jones, M.H. Depledge.: Biomarkers and environmental risk assessment: Guiding principles from the human health field. Mar. Pollut. Bull. 56 (4): 613-619 (2008).
21. Schulte, P.A, J.E. Hauser.: The use of biomarkers in occupational health research, practice, and policy. Toxicol. Lett. 213 (1): 91-99 (2012).
22. U.S. EPA.: Next Generation Risk Assessment: Incorporation of Recent Advances in Molecular, Computational, and Systems Biology (Final Report). Washington, D.C.: U.S. Environmental Protection Agency,. EPA/600/R-14/004, 2014.
23. Bailar, J.C, A.J. Bailer.: Risk assessment-the mother of all uncertainties-Disciplinary perspectives on uncertainty in risk assessment. In Uncertainty in the Risk Assessment of Environmental and Occupational Hazards, A.J. Bailer., C. Maltoni., J.C. Bailar. (eds.), 1999. pp. 273-285.
24. Neumann, D.A, C.A. Kimmel.: Human Variability in Response to Chemical Exposures, Measures, Modeling, and Risk Assessment. Boca Raton, FL: CRC Press, 1998.
25. Schwartz, J., D. Bellinger, T. Glass.: Expanding the scope of risk assessment: methods of studying differential vulnerability and susceptibility. Am. J. Public Health 101: S102-S109 (2011).
26. Rothstein, M.A., Y. Cai, G.E. Marchant.: The ghost in our genes: legal and ethical implications of epigenetics. Health Matrix Clevel. 19 (1): 1-62 (2009).
27. Cortessis, V.K., D.C. Thomas., A.J. Levine. et al.: Environmental epigenetics: prospects for studying epigenetic mediation of exposure-response relationships. Hum. Genet. 131 (10): 1565-1589 (2012).
28. National Research Council (NRC).: Toxicity Testing in the 21st Century: A Vision and a Strategy. Washington, D.C.: National Academies Press, 2007.
29. National Research Council (NRC).: Toxicity-Pathway-based Risk Assessment: Preparing for a Paradigm Change. Washington, D.C.: National Academies Press, 2010.
30. U.S. Environmental Protection Agency.: Advancing the Next Generation (NextGen) of Risk Assessment: Public Dialogue Conference, 2011.
31. Zeise, L., F.Y. Bois., W.A. Chiu., D. Hattis., I. Rusyn, K.Z. Guyton.: Addressing human variability in next-generation human health risk assessments of environmental chemicals. Environ. Health Perspect. 121: 23-31 (2013).
32. Bush, W.S., J. Boston., S.A. Pendergrass. et al.: Enabling high-throughput genotype-phenotype associations in the epidemiologic architecture for genes linked to environment (eagle) project as part of the population architecture using genomics and epidemiology (page) study. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 373-384 (2013).
33. Curran, C.P., R.M. Park., S.M. Ho, E.N. Haynes.: Incorporating genetics and genomics in risk assessment for inhaled manganese: From data to policy. Neurotoxicology 30 (5): 754-760 (2009).
34. Schulte, P.A.: Framework for considering genetics in the workplace. Med. Lav. 97 (2): 339-347 (2006).
35. Knudsen, L.E., S.H. Loft, H. Autrup.: Risk assessment: the importance of genetic polymorphisms in man. Mutat. Res. Fund. Molec. Mechan. Mutagen. 482 (1-2): 83-88 (2001).
36. McKinzie, P.B., R.R. Delongchamp., R.H. Heflich, B.L. Parsons.: Prospects for applying genotypic selection of somatic oncomutation to chemical risk assessment. Mutat. Res. Rev. Mutat. Res. 489 (1): 47-78 (2001).
37. McCanlies, E., D.P. Landsittel., B. Yucesoy., V. Vallyathan., M.L. Luster, D.S. Sharp.: Significance of genetic information in risk assessment and individual classification using silicosis as a case model. Ann. Occup. Hyg. 46 (4): 375-381 (2002).
38. Naumann, B.D., D.G. Dolan, E.V. Sargent.: Rationale for the chemical-specific adjustment factors used to derive an occupational exposure limit for timolol maleate. Hum. Ecol. Risk Assess. 10 (1): 99-111 (2004).
39. Demchuk, E., B. Yucesoy., V.J. Johnson. et al.: A statistical model for assessing genetic susceptibility as a risk factor in multifactorial diseases: Lessons from occupational asthma. Environ. Health Perspect. 115 (2): 231-234 (2007).
40. Herceg, Z.: Epigenetics and cancer: towards an evaluation of the impact of environmental and dietary factors. Mutagen 22 (2): 91-103 (2007).
41. Moore, M.M., R.H. Heflich., L.T. Haber., B.C. Allen., A.M. Shipp, R.L. Kodell.: Analysis of in vivo mutation data can inform cancer risk assessment. Regul. Toxicol. Pharmacol. 51 (2): 151-161 (2008).
42. Vlaanderen, J., L.E. Moore., M.T. Smith. et al.: Application of omics technologies in occupational and environmental health research: current status projections. Occup. Environ. Med. 67 (2): 136-143 (2010).
43. Bhattacharya, S., Q. Zhang., P.L. Carmichael., K. Boekelheide, M.E. Andersen.: Toxicity testing in the 21(st) century: defining new risk assessment approaches based on perturbation of intracellular toxicity pathways. PLoS One 6 (6):(2011).
44. Vineis, P, D. Kriebel.: Causal models in epidemiology: past inheritance and genetic future. Environ. Health. 5:21 (2006).
45. Pohl, H.R, F. Scinicariello.: The impact of CYP2E1 genetic variability on risk assessment of VOC mixtures. Regul. Toxicol. Pharmacol. 59 (3): 364-374 (2011).
46. National Academy of Science (NAS).: Identifying and estimating the genetic impact of chemical mutagens. In Committee on Environmental Mutagens. Washington, D.C.: National Academy Press, 1962.
47. National Research Council (NRC).: The effects on population of exposure to low levels of ionizing radiation (BEIR 1). In Advisory Committee on the Biological Effects of Ionizing Radiation. Washington, D.C.: National Academy of Sciences, 1972.
48. Ehling, U.H, A. Neuhauser.: Procarbazine-induced specific-locus mutations in male mice. Mutat. Res. 59 (2): 245-256 (1979).
49. National Research Council (NRC).: Considerations of health benefit-cost analysis for activities involving ionizing radiation exposure and alternatives (BEIR II). In Advisory Committee on Biological Effects of Ionizing Radiations. Washingtion, D.C.: National Academy of Sciences, 1977.
50. U.S. EPA.: Guidelines for carcinogen risk assessment. EPA/630/P-03/001B, March 2005 (2005).
51. Palma, G.D, M. Manno.: Metabolic polymorphisms and biomarkers of effect in the biomonitoring of occupational exposure to low-levels of benzene: State of the art. Toxicol. Lett. 231 (2): 194-204 (2014).
52. Meek, M.E., J.R. Bucher., S.M. Cohen. et al.: A framework for human relevance analysis of information on carcinogenic modes of action. Crit. Rev. Toxicol. 33 (6): 591-653 (2003).
53. Toraason, M., D.W. Lynch., D.G. DeBord. et al.: DNA damage in leukocytes of workers occupationally exposed to 1-bromopropane. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 603 (1): 1-14 (2006).
54. Grigorenko, E.L.: The inherent complexities of gene-environment interactions. J. Gerontol. Ser. B Psychol. Sci. Soc. Sci. 60: 53-64 (2005).
55. Derkenne, S., C.P. Curran., H.G. Shertzer., T.P. Dalton., N. Dragin, D.W. Nebert.: Theophylline pharmacokinetics: comparison of Cyp1a1(-/-) and Cyp1a2(-/-) knockout mice, humanized hCYP1A1-1A2 knock-in mice lacking either the mouse Cyp1a1 or Cyp1a2 gene, and Cyp1(+/+) wild-type mice. Pharmacogene Genom. 15 (7): 503-511 (2005).
56. Barry, K.H., Y. Zhang., Q. Lan. et al.: Genetic variation in metabolic genes, occupational solvent exposure, and risk of non-hodgkin lymphoma. Am. J. Epidemiol. 173 (4): 404-413 (2011).
57. Ramos, G, K. Olden.: Gene-environment interactions in the development of complex disease phenotypes. Int. J. Environ. Res. Public Health 5 (1): 4-11 (2008).
58. Patel, C.J., R. Chen., K. Kodama., J.P.A. Ioannidis, A.J. Butte.: Systematic identification of interaction effects between genome-and environment-wide associations in type 2 diabetes mellitus. Hum. Genet. 132: 495-508 (2013).
59. Kraft, P., Y.C. Yen., D.O. Stram., J. Morrison, W.J. Gauderman.: Exploiting gene-environment interaction to detect genetic associations. Hum. Hered. 63 (2): 111-119 (2007).
60. Guengerich, F.P.: The Environmental Genome Project: Functional analysis of polymorphisms-Commentary. Environ. Health Perspect. 106 (7): 365-368 (1998).
61. Collins, F.S., E.D. Green., A.E. Guttmacher., M.S. Guyer, US National Human Genome Research Institute.: A vision for the future of genomics research. Nature 422 (6934): 835-847 (2003).
62. International HapMap Project.: "International HapMap Project Homepage." [Online] Available at http://hapmap.ncbi.nlm.nih.gov/. 2005).
63. Hunter, D.J.: Gene-environment interactions in human diseases. Nat. Rev. Genet. 6 (4): 287-298 (2005).
64. Rothman, N., P. Hainaut., P. Schulte., M. Smith., P. Boffetta, P.M. Perea.: Molecular Epidemiology Principles and Practices. Lyon: International Agency for Research on Cancer, 2012.
65. Schulte, P.A, F.P. Perea.: Molecular Epidemiology: Principles and Practices. San Diego, CA: Academic Press Inc., 1993.
66. Garte, S.: Individual susceptibility and gene environment interaction. In Molecular Epidemiology of Chronic Diseases, C.P. Wild., P. Vineis, S. Garte. (eds.). West Sussex, UK: John Wiley and Sons, Ltd., 2008.
67. Thomas, D.: Gene-environment-wide association studies: emerging approaches. Nat. Rev. Genet. 11 (4): 259-272 (2010).
68. Thomas, D.: Methods for investigating gene-environment interactions in candidate pathway and genome-wide association studies. In Annual Review of Public Health, J.E. Fielding., R.C. Brownson, L.W. Green. (eds.). Palo Alto: Annual Reviews, 2010. pp. 21-36.
69. Ioannidis, J.P.A., T.A. Trikalinos, M.J. Khoury.: Implications of small effect sizes of individual genetic variants on the design and interpretation of genetic association studies of complex diseases. Am. J. Epidemiol. 164 (7): 609-614 (2006).
70. Cordell, H.J.: Detecting gene-gene interactions that underlie human diseases. Nat. Rev. Genet. 10 (6): 392-404 (2009).
71. Edwards, T.L., K. Lewis., D.R. Velez., S. Dudek, M.D. Ritchie.: Exploring the performance of Multifactor Dimensionality Reduction in large scale SNP studies and in the presence of genetic heterogeneity among epistatic disease models. Hum. Hered. 67 (3): 183-192 (2009).
72. Patel, C.J., J. Bhattacharya, A.J. Butte.: An environment-wide association study (EWAS) on Type 2 diabetes mellitus. PLoS One 5 (5):(2010).
73. Sachidanandam, R., D. Weissman., S.C. Schmidt. et al.: A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. Nature 409 (6822): 928-933 (2001).
74. Edwards, S.W, R.J. Preston.: Systems biology and mode of action based risk assessment. Toxicol. Sci. 106 (2): 312-318 (2008).
75. Wild, C.P.: Complementing the genome with an "exposome": The outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol. Biomark. Prev. 14 (8): 1847-1850 (2005).
76. Rappaport, S, L.L. Kupper.: Quantitative Exposure Assessment. El Cerrito, CA: Lulu Press, 2008.
77. Armstrong, B.K., E. White, R. Saracci.: Principles of Exposure Measurement in Epidemiology. New York: Oxford University Press 1992.
78. Smith, M.T, S.M. Rappaport.: Building Exposure Biology Centers to Put the E into "G x E" Interaction Studies. Environ. Health Perspect. 117 (8): A334-A335 (2009).
79. Rappaport, S.M.: Implications of the exposome for exposure science. J. Exposure Sci. Environ. Epidemiol. 21 (1): 5-9 (2011).
80. Rubino, F.M., M. Pitton., D. Di Fabio, A. Colombi.: Toward an "omic" physiopathology of reactive chemicals: thirty years of mass spectrometric study of the protein adducts with endogenous and xenobiotic compounds. Mass Spect. Rev. 28 (5): 725-784 (2009).
81. Stockton, A.M., T.N. Chiesl., J.R. Scherer, R.A. Mathies.: Polycyclic aromatic hydrocarbon analysis with the Mars organic analyzer microchip capillary electrophoresis system. Anal. Chem. 81 (2): 790-796 (2009).
82. Soltow, Q.A.: High-performance metabolic profiling with dual chromatography-Fourier-transform mass spectrometry (DC-FTMS) for study of the exposome. Metabolomics 9 (0): 132-143 (2013).
83. Weis, B.K., D. Balshawl., J.R. Barr. et al.: Personalized exposure assessment: Promising approaches for human environmental health research. Environ. Health Perspect. 113 (7): 840-848 (2005).
84. Brunekreef, B.: Exposure science, the exposome, and public health. Environ. Molec. Mutagen. 00: n/a-n/a (2013).
85. Lioy, P.J, Smith, K.R.: A discussion of exposure science in the 21st century: a vision and strategy. Environ. Health Perspect. 121: 405-409 (2013).
86. Chadeau-Hyam, M., T.J. Athersuch., H.C. Keun. et al.: Meeting-in-the-middle using metabolic profiling-a strategy for the identification of intermediate biomarkers in cohort studies. Biomarkers 16 (1): 83-88 (2011).
87. Vineis, P., K. van Veldhoonk., M. Chadeau-Hyam, T. Athersuch.: Advancing application of omics-based biomarkers in environmental epidemiology. Environ. Molec. Mutagen. 54 (7): 461-467 (2013).
88. Schulte, P.A, G. DeBord.: Public health assessment of genetic information in the occupational setting. In Genetics and Public Health in the 21st Century, M.J. Khoury., W. Burke, T. EJ. (eds.), New York: Oxford University Press, 2000. pp. 203-219.
89. Dankovic, D.A., B.D. Naumann., M.L. Dourson., A.M. Maier, L. Levy.: The scientific basis of uncertainty factors used in setting occupational exposure limits. J. Occup. Environ. Hyg. 12 (0): S55-S68 (2015).
90. Kramer, C.B., A.C. Cullen, E.M. Faustman.: Policy implications of genetic information on regulation under the Clean Air Act: The case of particulate matter and asthmatics. Environ. Health Perspect. 114 (3): 313-319 (2006).
91. Schulte, P, J. Howard.: Genetic Susceptibility and the Setting of Occupational Health Standards. In Annual Review of Public Health, Vol 32, J.E. Fielding., R.C. Brownson, L.W. Green. (eds.),. Palo Alto, Annual Reviews: 2011. pp. 149-159.
92. ODriscoll, M.: Diseases Associated with Defective Responses to DNA Damage. Cold Spring Harbor Perspect. Biol. 4 (12), (2012).
93. Jenkitkasemwong, S., C.Y. Wang., B. Mackenzie, M.D. Knutson.: Physiologic implications of metal-ion transport by ZIP14 and ZIP8. Biometals 25 (4): 643-655 (2012).
94. Nebert, D.W.: Extreme discordant phenotype methodology: an intuitive approach to clinical pharmacogenetics. Eur. J. Pharmacol. 410 (2-3): 107-120 (2000).
95. Haber, L.T., A. Maier., P.R. Gentry., H.J. Clewell, M.L. Dourson.: Genetic Polymorphisms in assessing interindividual variability in delivered dose. Regul. Toxicol. Pharmacol. 35 (2): 177-197 (2002).
96. Shen, M., L. Zhang., K.-M. Lee. et al.: Polymorphisms in genes involved in innate immunity and susceptibility to benzene-induced hematotoxicity. Exper. Molec. Med. 43 (6): 374-378 (2011).
97. Mörk, A.K., F. Jonsson, G. Johanson.: Adjustment factors for toluene, styrene and methyl chloride by population modeling of toxicokinetic variability. Regul. Toxicol. Pharmacol. 69 (1): 78-90 (2014).
98. Berg, K.: Inherited Variation in Susceptibility and Resistance to Environmental Agents. San Diego, CA: Academic Press, 1979.
99. Albertini, R.J.: Developing sustainble studies on environmental health. Mutat. Res. 480 (317-331):(2000).
100. Jones, I.M., H. Galick., P. Kato. et al.: Three somatic genetic biomarkers and covariates in radiation-exposed Russian cleanup workers of the Chernobyl nuclear reactor 6-13 years after exposure. Rad. Res. 158 (4): 424-442 (2002).
101. Bonassi, S., A. Znaor., H. Norppa, L. Hagmar.: Chromosomal aberrations and risk of cancer in humans: an epidemiologic perspective. Cytogen. Genome Res. 104 (1-4): 376-382 (2004).
102. Hagmar, L., U. Stromberg., S. Bonassi. et al.: Impact of types of lymphocyte chromosomal aberrations on human cancer risk: Results from Nordic and Italian cohorts. Cancer Res. 64 (6): 2258-2263 (2004).
103. Lan, Q., R. Cawthon., M. Shen. et al.: A prospective study of telomere length measured by monochrome multiplex quantitative PCR and Risk of non-Hodgkin lymphoma. Clin. Cancer Res. 15 (23): 7429-7433 (2009).
104. Cassini, C., C. Calloni., G. Bortolini. et al.: Occupational risk assessment of oxidative stress and genotoxicity in workers exposed to paints during a working week. Int. J. Occup. Med. Environ. Health 24 (3): 308-319 (2011).
105. Zeiger, E., B. Gollapudi., M.J. Aardema. et al.: Opportunities to integrate new approaches in genetic toxicology: An ILSI-HESI workshop report. Environ. Molec. Mutagen. 56: 277-285 (2015).
106. International Programme on Chemical Safety (IPCS).: Biomarkers in Risk Assessment: Validity and Validation. Geneva: World Health Organization, 2001.
107. Dary, C.C., J.J. Quachenboss., C.H. Nauman, S.C. Hein.: Relationship of biomarkers of exposure to risk assessment and risk management. In Biomarkers for Agrochemicals and Toxic Substances, J.W. Blancato., R.N. Brown., C.C. Dary, M.A. Saleh. (eds.). ACS Symposium Series 643, Washington, DC: ACS, 1990. pp. 2-23.
108. Lobenhofer, E.K., X. Cui., L. Bennett. et al.: Exploration of low-dose estrogen effects: identification of No Observed Transcriptional Effect Level (NOTEL). Toxicol. Pathol. 32 (4): 482-492 (2004).
109. Judson, R.S., R.J. Kavlock., R.W. Setzer. et al.: Estimating toxicity-related biological pathway altering doses for high-throughput chemical risk assessment. Chem. Res. Toxicol. 24 (4): 451-462 (2011).
110. Judson, R., R. Kavlock., M. Martin. et al.: Perspectives on validation of high-throughput assays supporting 21st century toxicity testing. Altex-Altern Exper. 30 (1): 51-66 (2013).
111. Wang, I.M., B. Zhang., X. Yang. et al.: Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers. Molec. Syst. Biol. 8 (2012).
112. Waddington, C.H.: The epigenotype. Endeavour 18 (18-20),(1942).
113. Morange, M.: The relations between genetics and epigenetics-A historical point of view. Ann. NY Acad. Sci. 981: 50-60 (2002).
114. Feinberg, A.P.: Epigenetics at the epicenter of modern medicine. J. Am. Med. Assoc. 299 (11): 1345-1350 (2008).
115. Foley, D.L., J.M. Craig., R. Morley. et al.: Prospects for epigenetic epidemiology. Amer. J. Epidemiol. 169 (4): 389-400 (2009).
116. Stein, R.A.: Epigenetics and environmental exposures. J. Epidemiol. Comm. Health 66 (1): 8-13 (2012).
117. Michels, K.B.: Epigenetic Epidemiology. Dodrecht: Springer, 2012.
118. Flanagan, J.M.: Human methylome variation and the rise of epigenetic epidemiology. Curr. Pharmacogen. Personalized Med. 8: 89-91 (2010).
119. Relton, C.L, G.D. Smith.: Epigenetic epidemiology of common complex disease: prospects for prediction, prevention, and treatment. Plos Med. 7 (10), (2010).
120. Ho, S.M, W.Y. Tang.: Techniques used in studies of epigenome dysregulation due to aberrant DNA methylation: An emphasis on fetal-based adult diseases. Reprod. Toxicol. 23 (3): 267-282 (2007).
121. Goodman, J.I., K.A. Augustine., M.L. Cunnningham. et al.: What do we need to know prior to thinking about incorporating an epigenetic evaluation into safety assessments Toxicol. Sci. 116 (2): 375-381 (2010).
122. Jablonka, E.: Epigenetic epidemiology. Int. J. Epidemiol. 33 (5): 929-935 (2004).
123. Talens, R.P., D.I. Boomsma., E.W. Tobi. et al.: Variation, patterns, and temporal stability of DNA methylation: considerations for epigenetic epidemiology. Faseb J. 24 (9): 3135-3144 (2010).
124. Cantone, L., F. Nordio., L. Hou. et al.: Inhalable metal-rich air particles and histone H3K4 dimethylation and H3K9 acetylation in a cross-sectional study of steel workers. Environ. Health Perspect. 119 (7): 964-969 (2011).
125. Arita, A., J. Niu., Q. Qu. et al.: Global levels of histone modifications in peripheral blood mononuclear cells of subjects with exposure to nickel. Environ. Health Perspect. 120 (2): 198 (2012).
126. Ray, P.D., A. Yosim, R.C. Fry.: Incorporating epigenetic data into the risk assessment process for the toxic metals arsenic, cadmium, chromium, lead, and mercury: strategies and challenges. Front. Genet. 5, (2014).
127. Rozek, L.S., D.C. Dolinoy., M.A. Sartor, G.S. Omenn.: Epigenetics: relevance and implications for public health. Ann. Rev. Public Health 35: 105-122 (2014).
128. Boekelheide, K., B. Blumberg., R.E. Chapin. et al.: Predicting later-life outcomes of early-life exposures. Environ. Health Perspect. 120 (10): 1353-1361 (2012).
129. Rasoulpour, R.J., M.J. LeBaron., R.G. Ellis-Hutchings., J. Klapacz, B.B. Gollapudi.: Epigenetic screening in product safety assessment: are we there yet Toxicol. Mech. Meth. 21 (4): 298-311 (2011).
130. Ryan, P.B., T.A. Burke., E.A.C. Hubal., J.J. Cura, T.E. McKone.: Using biomarkers to inform cumulative risk assessment. Environ. Health Perspect. 115 (5): 833-840 (2007).
131. Butte, A.J, I.S. Kohane.: Creation and implications of a phenome-genome network. Nat. Biotechnol. 24 (1): 55-62 (2006).
132. Basu, N., J.M. Goodrich, J. Head.: Ecogenetics of mercury: From genetic polymorphisms and epigenetics to risk assessment and decision-making. Environ. Toxicol. Chem. 33 (6): 1248-1258 (2014).
133. National Research Council (NRC).: Science and Decisions: Advancing Risk Assessment. Washington, D.C.: National Academies Press, 2009.
134. EPA.: Interim Policy on Genomics. Washington, D.C.: U.S. EPA, 2002.
135. EPA.: Potential implications of genomics for regulatory and risk assessment applications at EPA. Genomics Task Force Workgroup. EPA/100/B-04/002 (2004).
136. El-Masri, H.A., D.A. Bell, C.J. Portier.: Effects of glutathione transferase theta polymorphism on the risk estimates of dichloromethane to humans. Toxicol. Appl. Pharmacol. 158 (3): 221-230 (1999).
137. David, R.M., H.J. Clewell., P.R. Gentry., T.R. Covington., D.A. Morgott, D.J. Marino.: Revised assessment of cancer risk to dichloromethane II. Application of probabilistic methods to cancer risk determinations. Regul. Toxicol. Pharmacol. 45 (1): 55-65 (2006).
138. Ioannidis, J.P., P. Boffetta., J. Little. et al.: Assessment of cumulative evidence on genetic associations: interim guidelines. Int. J. Epidemiol. 37 (1): 120-132 (2008).
139. von Elm, E., D.G. Altman., M. Egger., S.J. Pocock., P.C. Gotzsche, J.P. Vandenbroucke.: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 370 (9596): 1453-1457 (2007).
140. Little, J., J.P.T. Higgins., J.P.A. Ioannidis. et al.: STrengthening the REporting of Genetic Association Studies (STREGA)-An Extension of the STROBE Statement. Plos Med. 6 (2): 151-163 (2009).
141. Gallo, V., M. Egger., V. McCormack. et al.: STrengthening the Reporting of OBservational studies in Epidemiology-Molecular Epidemiology STROBE-ME: an extension of the STROBE statement. J. Clin. Epidemiol. 64 (12): 1350-1363 (2011).
142. Jennings, P.: Stress response pathways, toxicity pathways and adverse outcome pathways. Arch. Toxicol. 87 (1): 13-14 (2013).
143. MacKay, C., M. Davies., V. Summerfield, G. Maxwell.: From Pathways to People: Applying the Adverse Outcome Pathway (AOP) for skin sensitization to risk assessment. Altex-Alter. Animal Exper. 30 (4): 473-486 (2013).
144. Bergeson LL.: Toxicogenomics and the workplace: what you need to know. Manufact. Today. Jan/Feb: 8-9 (2003).
145. Samuels, S.W.: Occupational medicine and its moral discontents. J. Occup. Environ. Med. 45 (12): 1226-1233 (2003).
146. Hansson, S.O.: Should we protect the most sensitive people J. Radiol. Protect. 29 (2): 211-218 (2009).
147. Grodsky, J.A.: Genetics and environmental law: redefining public health. Calif. Law Rev. 93 (1): 171-270 (2005).
148. Rothstein, M.A.: Legal conceptions of equality in the genomic age. Law Inequal. 25 (2): 429 (2007).