La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI, United States of America.
Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI, United States of America.
PLoS One. 2024 Feb 15;19(2):e0282212. doi: 10.1371/journal.pone.0282212. eCollection 2024.
Researchers often claim that sibling analysis can be used to separate causal genetic effects from the assortment of biases that contaminate most downstream genetic studies (e.g. polygenic score predictors). Indeed, typical results from sibling analysis show large (>50%) attenuations in the associations between polygenic scores and phenotypes compared to non-sibling analysis, consistent with researchers' expectations about bias reduction. This paper explores these expectations by using family (quad) data and simulations that include indirect genetic effect processes and evaluates the ability of sibling analysis to uncover direct genetic effects of polygenic scores. We find that sibling analysis, in general, fail to uncover direct genetic effects; indeed, these models have both upward and downward biases that are difficult to sign in typical data. When genetic nurture effects exist, sibling analysis creates "measurement error" that attenuates associations between polygenic scores and phenotypes. As the correlation between direct and indirect effect changes, this bias can increase or decrease. Our findings suggest that interpreting results from sibling analysis aimed at uncovering direct genetic effects should be treated with caution.
研究人员经常声称，同胞分析可用于分离因果遗传效应与大多数下游遗传研究中混杂的偏倚（例如多基因评分预测因子）。实际上，与非同胞分析相比，同胞分析的典型结果表明，多基因评分与表型之间的关联大幅减弱（>50%），这与研究人员对减少偏倚的预期一致。本文通过使用包含间接遗传效应过程的家庭（四元组）数据和模拟来探讨这些预期，并评估同胞分析揭示多基因评分直接遗传效应的能力。我们发现，同胞分析通常无法揭示直接遗传效应；实际上，这些模型存在难以在典型数据中判断的向上和向下偏差。当存在遗传养育效应时，同胞分析会产生“测量误差”，从而减弱多基因评分与表型之间的关联。随着直接效应和间接效应之间的相关性变化，这种偏差会增加或减少。我们的研究结果表明，对于旨在揭示直接遗传效应的同胞分析结果的解释应该谨慎对待。
