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

摘要 环境化学物质暴露与癌症发病率、出生和发育的增加有关 缺陷、认知发育障碍和神经退行性疾病。然而，即使是随着 环境中的人造化学品增长到数十万，关于 人类和环境健康危害仍然很少，甚至根本不存在。数据特别稀疏 关于差异易感性的问题，基因-环境相互作用(GxE)的影响起源于哪里 从个体来看，遗传变异对健康结局起着重要作用。因此，理解 GxE对不断扩大的化学暴露的不同敏感性是保护公众健康的关键- 尤其是弱势群体的问题。我们提出了一种结合了新颖分析和强大功能的解决方案 新的高通量筛查技术检测GxE潜在的差异易感性 斑马鱼的数量。我们的三个具体目标将(1)确定导致 人群疾病易感性的最大差异；(2)确定临界暴露浓度和 确认群体易感性差异的遗传遗传力；以及(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。这一事件的直接影响 该提议将为GxE在不同人群易感性中的作用提供新的经验证据。永恒的 这项提议的意义将是一个可扩展、可持续的系统，以快速解决差异问题 对不断扩大的化学暴露组的遗传易感性。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，用于识别表型变异模式，提示 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.