Esther Herrera-Luis, Kelly Benke, Heather Volk, Christine Ladd-Acosta, Genevieve L. Wojcik
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引用次数: 0
Abstract
Gene–environment interactions (G × E), the interplay of genetic variation with environmental factors, have a pivotal impact on human complex traits and diseases. Statistically, G × E can be assessed by determining the deviation from expectation of predictive models based solely on the phenotypic effects of genetics or environmental exposures. Despite the unprecedented, widespread and diverse use of G × E analytical frameworks, heterogeneity in their application and reporting hinders their applicability in public health. In this Review, we discuss study design considerations as well as G × E analytical frameworks to assess polygenic liability dependent on the environment, to identify specific genetic variants exhibiting G × E, and to characterize environmental context for these dynamics. We conclude with recommendations to address the most common challenges and pitfalls in the conceptualization, methodology and reporting of G × E studies, as well as future directions. Despite their impact on human complex traits and diseases, gene–environment interactions (G × E) remain challenging to assess statistically. The authors review considerations for the conceptualization, methodology, interpretation and reporting of G × E studies, and provide recommendations on how to avoid common pitfalls.
基因与环境的相互作用(G×E),即遗传变异与环境因素的相互作用,对人类复杂的性状和疾病有着举足轻重的影响。从统计学角度看,G × E 可通过确定预测模型的预期偏差来评估,而预测模型的预期偏差则完全基于遗传或环境暴露的表型效应。尽管 G × E 分析框架得到了前所未有的广泛和多样化应用,但其应用和报告的异质性阻碍了其在公共卫生领域的适用性。在本综述中,我们将讨论研究设计的注意事项以及 G × E 分析框架,以评估依赖于环境的多基因责任,确定表现出 G × E 的特定遗传变异,并描述这些动态的环境背景。最后,我们针对 G × E 研究的概念化、方法学和报告中最常见的挑战和误区提出了建议以及未来的发展方向。
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