Domingue Benjamin W, Trejo Sam, Armstrong-Carter Emma, Tucker-Drob Elliot M
Stanford University.
University of Wisconsin-Madison.
Sociol Sci. 2020 Sep;7:465-486. doi: 10.15195/v7.a19. Epub 2020 Sep 21.
Interest in the study of gene-environment interaction has recently grown due to the sudden availability of molecular genetic data-in particular, polygenic scores-in many long-running longitudinal studies. Identifying and estimating statistical interactions comes with several analytic and inferential challenges; these challenges are heightened when used to integrate observational genomic and social science data. We articulate some of these key challenges, provide new perspectives on the study of gene-environment interactions, and end by offering some practical guidance for conducting research in this area. Given the sudden availability of well-powered polygenic scores, we anticipate a substantial increase in research testing for interaction between such scores and environments. The issues we discuss, if not properly addressed, may impact the enduring scientific value of gene-environment interaction studies.
由于在许多长期进行的纵向研究中突然能够获取分子遗传学数据，特别是多基因分数，近来人们对基因-环境相互作用的研究兴趣日益浓厚。识别和估计统计相互作用面临若干分析和推断方面的挑战；当用于整合观测基因组学和社会科学数据时，这些挑战会更加突出。我们阐述其中一些关键挑战，为基因-环境相互作用的研究提供新视角，并最后为该领域的研究提供一些实用指导。鉴于强大的多基因分数突然变得可用，我们预计对这类分数与环境之间相互作用进行检验的研究将大幅增加。我们所讨论的问题若未得到妥善解决，可能会影响基因-环境相互作用研究的持久科学价值。
