Characterizing Gene-Environment Interactions that Affect Individual Susceptibility to an Expanding Chemical Exposome

摘要 环境化学品暴露与癌症发病率、出生和发育的增加有关。 缺陷、认知发育受损和神经退行性疾病。然而，即使数量 环境中的制造化学品增长到成千上万，全面的数据， 人类和环境健康危害仍然很少甚至不存在。数据特别稀少 关于不同的易感性问题，其中基因-环境相互作用（GxE）的影响源于 个体遗传变异对健康结果起着重要作用。因此，了解 GxE对不断扩大的化学物质的敏感性是保护公众健康的关键- 特别是弱势群体的利益。我们提出了一种解决方案，将新颖的分析与强大的 新的高通量筛选技术，以检测GxE潜在的差异敏感性在不同的 斑马鱼的种群我们的三个具体目标是：（1）确定环境化学品， （2）确定关键接触浓度， 确认群体易感性差异的遗传性;（3）识别和实验验证 与化学暴露的不同易感性相关的基因组区域。这件事的直接影响是 该提案将是GxE在不同人群易感性中的作用的新的经验证据。持久 这一建议的意义将是一个可扩展的，可持续的系统，以迅速解决差异化的问题， 对不断扩大的化学物质的遗传易感性。数据驱动的生物信息学方法 这里开发的将可扩展到其他系统，用于识别表型变异的模式， GxE

ABSTRACT Environmental chemical exposure has been linked to increases in cancer incidence, birth and developmental defects, impaired cognitive development, and neurodegenerative disease. However, even as the number of manufactured chemicals in the environment grows into the hundreds-of-thousands, comprehensive data on the human and environmental health hazards remain sparse to nonexistent. The data are especially sparse regarding questions of differential susceptibility, where gene-environment interaction (GxE) effects stemming from individual genetic variation play an important role in health outcomes. Thus, understanding the role of GxE in differential susceptibility to an expanding chemical exposome is key to protecting public health— particularly that of vulnerable populations. We propose a solution that combines novel analytics with the power of new high-throughput screening technologies to detect GxE underlying differential susceptibility in a diverse population of zebrafish. Our three Specific Aims will (1) Identify environmental chemicals that induce the greatest differences in population disease susceptibility; (2) Identify critical exposure concentrations and confirm genetic heritability of population susceptibility differences; and (3) Identify and experimentally validate genomic regions associated with differential susceptibility to chemical exposure. The immediate impact of this proposal will be novel empirical evidence for the role of GxE in differential population susceptibility. The lasting significance of this proposal will be a scalable, sustainable system to rapidly address questions of differential genetic susceptibility to an expanding chemical exposome. The data-driven, bioinformatic approaches developed here will be extensible to other systems for identifying patterns of phenotypic variation suggesting GxE.