title: Toxicogenomic profiling of chemically exposed humans in risk assessment.
abstract: Gene-environment interactions contribute to complex disease development. The environmental contribution, in particular low-level and prevalent environmental exposures, may constitute much of the risk and contribute substantially to disease. Systematic risk evaluation of the majority of human chemical exposures, has not been conducted and is a goal of regulatory agencies in the U.S. and worldwide. With the recent recognition that toxicological approaches more predictive of effects in humans are required for risk assessment, in vitro human cell line data as well as animal data are being used to identify toxicity mechanisms that can be translated into biomarkers relevant to human exposure studies. In this review, we discuss how data from toxicogenomic studies of exposed human populations can inform risk assessment, by generating biomarkers of exposure, early effect, and/or susceptibility, elucidating mechanisms of action underlying exposure-related disease, and detecting response at low doses. Good experimental design incorporating precise, individual exposure measurements, phenotypic anchors (pre-disease or traditional toxicological markers), and a range of relevant exposure levels, is necessary. Further, toxicogenomic studies need to be designed with sufficient power to detect true effects of the exposure. As more studies are performed and incorporated into databases such as the Comparative Toxicogenomics Database (CTD) and Chemical Effects in Biological Systems (CEBS), data can be mined for classification of newly tested chemicals (hazard identification), and, for investigating the dose-response, and inter-relationship among genes, environment and disease in a systems biology approach (risk characterization).
authors.affiliation: School of Public Health, Divisions of Environmental Health Sciences, and Biostatistics, University of California, Berkeley, CA 94720, USA. cmchale@berkeley.edu
authors.forename: Cliona M
authors.initials: CM
authors.lastname: McHale
authors.forename: Luoping
authors.initials: L
authors.lastname: Zhang
authors.forename: Alan E
authors.initials: AE
authors.lastname: Hubbard
authors.forename: Martyn T
authors.initials: MT
authors.lastname: Smith
mesh_terms: D000818:Animals; D001151:Arsenic / Q000633:toxicity; D001554:Benzene / Q000633:toxicity; D004781:Environmental Exposure; D044127:Epigenesis, Genetic; D005260:Female; D020869:Gene Expression Profiling; D023281:Genomics / Q000639:trends*; D006801:Humans; D008297:Male; D040901:Proteomics / Q000379:methods; D018570:Risk Assessment / Q000379:methods* / Q000639:trends*; D049490:Systems Biology; D043922:Toxicogenetics / Q000639:trends*; D014116:Toxicology / Q000639:trends*
chemical_list: D001554:Benzene; D001151:Arsenic
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