title: Integrating mechanistic and polymorphism data to characterize human genetic susceptibility for environmental chemical risk assessment in the 21st century.
abstract: Response to environmental chemicals can vary widely among individuals and between population groups. In human health risk assessment, data on susceptibility can be utilized by deriving risk levels based on a study of a susceptible population and/or an uncertainty factor may be applied to account for the lack of information about susceptibility. Defining genetic susceptibility in response to environmental chemicals across human populations is an area of interest in the NAS' new paradigm of toxicity pathway-based risk assessment. Data from high-throughput/high content (HT/HC), including -omics (e.g., genomics, transcriptomics, proteomics, metabolomics) technologies, have been integral to the identification and characterization of drug target and disease loci, and have been successfully utilized to inform the mechanism of action for numerous environmental chemicals. Large-scale population genotyping studies may help to characterize levels of variability across human populations at identified target loci implicated in response to environmental chemicals. By combining mechanistic data for a given environmental chemical with next generation sequencing data that provides human population variation information, one can begin to characterize differential susceptibility due to genetic variability to environmental chemicals within and across genetically heterogeneous human populations. The integration of such data sources will be informative to human health risk assessment.
authors.affiliation: Office of Research and Development, US Environmental Protection Agency, National Center for Computational Toxicology, US EPA, 109 TW Alexander Dr., Mailcode B205-01, Research Triangle Park, NC 27711, USA. Electronic address: mortensen.holly@epa.gov.
authors.forename: Holly M
authors.initials: HM
authors.lastname: Mortensen
authors.forename: Susan Y
authors.initials: SY
authors.lastname: Euling
mesh_terms: D016208:Databases, Factual; D004785:Environmental Pollutants / Q000633:toxicity*; D020022:Genetic Predisposition to Disease; D006801:Humans; D011110:Polymorphism, Genetic; D018570:Risk Assessment / Q000379:methods
chemical_list: D004785:Environmental Pollutants