Gene-environment dependencies lead to collider bias in models with polygenic scores.
Gene-environment dependencies lead to collider bias in models with polygenic scores.
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DOI：
10.1038/s41598-021-89020-x
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发表时间：
2021-05-04
影响因子：
4.6
通讯作者：
Mills MC
中科院分区：
文献类型：
--
作者：
Akimova ET;Breen R;Brazel DM;Mills MC
多基因评分的应用改变了我们研究遗传和环境因素是否以及如何共同影响复杂性状变异的能力。然而，对基因和环境之间复杂的相互作用进行建模，提出了严重的方法学挑战。在这里，我们说明了很大程度上未被认识到的影响，基因环境依赖性的影响，基因和它们的变化，跨环境的识别。我们发现，控制遗传协变量的回归模型，包括多基因得分作为自变量引入内源性选择偏差时，这些协变量中的一个或多个依赖于不可测量的因素，也影响结果。这导致了对碰撞器的条件作用问题，这反过来又导致了虚假的关联和效应大小。使用图形和模拟方法，我们证明了偏倚的程度取决于基因-协变量相关性的强度以及将协变量与结果联系起来的隐藏异质性的强度，无论主要分析焦点是中介、混杂还是基因×协变量（通常是基因×环境）相互作用。我们提供了潜在的解决方案，强调因果推理的重要性。我们还敦促在拟合和解释具有多基因评分和非外源性环境或表型的模型时进一步谨慎，并证明虚假关联可能会出现，从而促进我们对此类结果的理解。
The application of polygenic scores has transformed our ability to investigate whether and how genetic and environmental factors jointly contribute to the variation of complex traits. Modelling the complex interplay between genes and environment, however, raises serious methodological challenges. Here we illustrate the largely unrecognised impact of gene-environment dependencies on the identification of the effects of genes and their variation across environments. We show that controlling for heritable covariates in regression models that include polygenic scores as independent variables introduces endogenous selection bias when one or more of these covariates depends on unmeasured factors that also affect the outcome. This results in the problem of conditioning on a collider, which in turn leads to spurious associations and effect sizes. Using graphical and simulation methods we demonstrate that the degree of bias depends on the strength of the gene-covariate correlation and of hidden heterogeneity linking covariates with outcomes, regardless of whether the main analytic focus is mediation, confounding, or gene × covariate (commonly gene × environment) interactions. We offer potential solutions, highlighting the importance of causal inference. We also urge further caution when fitting and interpreting models with polygenic scores and non-exogenous environments or phenotypes and demonstrate how spurious associations are likely to arise, advancing our understanding of such results.
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影响因子：
9.8
作者：
Dudbridge F;Fletcher O
通讯作者：
Fletcher O
影响因子：
1.3
作者：
Conley, Dalton
通讯作者：
Conley, Dalton
影响因子：
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作者：
Fletcher, Jason M.;Conley, Dalton
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通讯作者：
Winship C
影响因子：
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Bulik-Sullivan B;Finucane HK;Anttila V;Gusev A;Day FR;Loh PR;ReproGen Consortium;Psychiatric Genomics Consortium;Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3;Duncan L;Perry JR;Patterson N;Robinson EB;Daly MJ;Price AL;Neale BM
通讯作者：
Neale BM