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.
Toxicol Appl Pharmacol. 2013 Sep 15;271(3):395-404. doi: 10.1016/j.taap.2011.01.015. Epub 2011 Feb 1.
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.
个体和人群之间对环境化学物质的反应可能存在很大差异。在人类健康风险评估中,可以通过研究易感人群来利用易感性数据来确定风险水平,或者可以应用不确定性因素来考虑易感性信息的缺乏。在基于毒性途径的风险评估的新范式中,定义人类对环境化学物质的遗传易感性是 NAS 关注的一个领域。来自高通量/高内涵(HT/HC)的包括 -omics(如基因组学、转录组学、蛋白质组学、代谢组学)技术的数据对于鉴定和表征药物靶点和疾病基因座至关重要,并且已经成功地用于为许多环境化学物质提供作用机制的信息。大规模的人群基因分型研究可能有助于描述在与环境化学物质反应相关的已鉴定靶基因座中,人类群体之间的变异性水平。通过将特定环境化学物质的机制数据与提供人类群体变异信息的下一代测序数据相结合,可以开始描述由于遗传变异性导致的对环境化学物质的差异易感性,以及在遗传异质的人类群体中。整合这些数据源将为人类健康风险评估提供信息。