A General Approach to Adjusting Genetic Studies for Assortative Mating.
A General Approach to Adjusting Genetic Studies for Assortative Mating.
复制标题
调整选型交配遗传研究的一般方法。
DOI：
10.1101/2023.09.01.555983
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Turley,Patrick
中科院分区：
文献类型：
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作者：
Bilghese,Marta;Manansala,Regina;Jaishankar,Dhruva;Jala,Jonathan;Benjamin,DanielJ;Kimball,Miles;Auer,PaulL;Livermore,MichaelA;Turley,Patrick
近几年来，人工交配（AM）对遗传估计值的影响越来越受到人们的关注。我们将现有的AM理论扩展到更一般的排序模型，并得出结论，正确的基于理论的AM调整需要复杂的，未知的历史排序模式的知识。我们提出了一个简单的，通用的方法，使用多基因指数（PGIs）。我们的方法可以估计遗传方差和遗传相关性的比例，是由AM驱动。我们的方法是不太有效时，适用于孟德尔随机化（MR）的研究有两个原因：AM可以诱导一种形式的选择偏差，在MR研究中，仍然在我们的调整后，和，在MR的背景下，调整是特别敏感的PGI估计误差。使用英国生物银行的数据，我们发现AM将健康特征和教育之间的遗传相关性估计平均提高了14%。我们的研究结果表明，谨慎解释遗传相关性或MR估计性状受AM。
The effects of assortative mating (AM) on estimates from genetic studies has been receiving increasing attention in recent years. We extend existing AM theory to more general models of sorting and conclude that correct theory-based AM adjustments require knowledge of complicated, unknown historical sorting patterns. We propose a simple, general-purpose approach using polygenic indexes (PGIs). Our approach can estimate the fraction of genetic variance and genetic correlation that is driven by AM. Our approach is less effective when applied to Mendelian randomization (MR) studies for two reasons: AM can induce a form of selection bias in MR studies that remains after our adjustment; and, in the MR context, the adjustment is particularly sensitive to PGI estimation error. Using data from the UK Biobank, we find that AM inflates genetic correlation estimates between health traits and education by 14% on average. Our results suggest caution in interpreting genetic correlations or MR estimates for traits subject to AM.