Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Nat Rev Genet. 2024 Nov;25(11):768-784. doi: 10.1038/s41576-024-00731-z. Epub 2024 May 28.
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.
基因-环境相互作用(G×E),即遗传变异与环境因素的相互作用,对人类复杂特征和疾病有着至关重要的影响。从统计学上讲,可以通过确定仅基于遗传或环境暴露的表型效应的预测模型的预期偏差来评估 G×E。尽管基因-环境相互作用分析框架得到了前所未有的广泛应用,但由于其应用和报告的异质性,限制了其在公共卫生中的适用性。在这篇综述中,我们讨论了研究设计的注意事项,以及用于评估依赖于环境的多基因风险、识别表现出 G×E 的特定遗传变异以及描述这些动态的环境背景的 G×E 分析框架。最后,我们提出了一些建议,以解决基因-环境相互作用研究在概念化、方法和报告方面最常见的挑战和陷阱,以及未来的方向。