芬兰赫尔辛基大学Andrea Ganna、英国剑桥大学John R. B. Perry等研究人员合作揭示性别差异对遗传分析的影响。该研究于2021年4月22日在线发表于国际一流学术期刊《自然—遗传学》。
研究人员证明可以通过对一个亚组与另一个亚组进行对比的全基因组关联研究来估计比较偏倚。例如，研究人员表明在存在性别差异参与偏倚的情况下，性别表现出人为的常染色体遗传性。通过在大约330万男性和女性中进行性别的全基因组关联研究，研究人员鉴定了超过158个与性别虚假相关的常染色体基因座，并强调了支持不同性别研究参与的复杂特征。例如，与女性相比，男性中FTO处的体重指数增加等位基因频率更高（几率=1.02，P=4.4×10-36）。
最后，研究人员展示了这些偏差可能如何导致下游分析中的错误推论，并提出了解决此类偏差的概念框架。这些发现凸显了随着样本量的不断增长，遗传研究可能面临的新挑战。
据介绍，遗传关联结果的解释通常是有假定前提的，即研究参与本身不影响下游分析。了解参与偏倚的遗传基础具有挑战性，因为它需要知道个体的基因型。
附：英文原文
Title: Genetic analyses identify widespread sex-differential participation bias
Author: Nicola Pirastu, Mattia Cordioli, Priyanka Nandakumar, Gianmarco Mignogna, Abdel Abdellaoui, Benjamin Hollis, Masahiro Kanai, Veera M. Rajagopal, Pietro Della Briotta Parolo, Nikolas Baya, Caitlin E. Carey, Juha Karjalainen, Thomas D. Als, Matthijs D. Van der Zee, Felix R. Day, Ken K. Ong, Takayuki Morisaki, Eco de Geus, Rino Bellocco, Yukinori Okada, Anders D. Brglum, Peter Joshi, Adam Auton, David Hinds, Benjamin M. Neale, Raymond K. Walters, Michel G. Nivard, John R. B. Perry, Andrea Ganna
Issue&Volume: 2021-04-22
Abstract: Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging since it requires the genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study contrasting one subgroup versus another. For example, we showed that sex exhibits artifactual autosomal heritability in the presence of sex-differential participation bias. By performing a genome-wide association study of sex in approximately 3.3 million males and females, we identified over 158 autosomal loci spuriously associated with sex and highlighted complex traits underpinning differences in study participation between the sexes. For example, the body mass index–increasing allele at FTO was observed at higher frequency in males compared to females (odds ratio=1.02, P=4.4×1036). Finally, we demonstrated how these biases can potentially lead to incorrect inferences in downstream analyses and propose a conceptual framework for addressing such biases. Our findings highlight a new challenge that genetic studies may face as sample sizes continue to grow.
DOI: 10.1038/s41588-021-00846-7
Source: https://www.nature.com/articles/s41588-021-00846-7
Nature Genetics：《自然—遗传学》，创刊于1992年。隶属于施普林格·自然出版集团，最新IF：41.307
官方网址：https://www.nature.com/ng/
投稿链接：https://mts-ng.nature.com/cgi-bin/main.plex
本期文章：《自然—遗传学》：Online/在线发表
