Genetic analyses identify widespread sex-differential participation bias.
Nature genetics 2020 ; 53: 663-671.
Pirastu N, Cordioli M, Nandakumar P, Mignogna G, Abdellaoui A, Hollis B, Kanai M, Rajagopal VM, Parolo PDB, Baya N, Carey CE, Karjalainen J, Als TD, van der Zee MD, Day FR, Ong KK, FinnGen Study, 23andMe Research Team, iPSYCH Consortium, Morisaki T, de Geus E, Bellocco R, Okada Y, Børglum AD, Joshi P, Auton A, Hinds D, Neale BM, Walters RK, Nivard MG, Perry JRB, and Ganna A
PubMed ID : 33888908
PMCID : PMC7611642
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 × 10). 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.