Genetic analyses identify widespread sex-differential participation bias
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, FinnGen Study, Michelle Agee, Stella Aslibekyan, Robert K. Bell, Katarzyna Bryc, Sarah Clark, Sarah L. Elson, Kipper Fletez‐Brant, Pierre Fontanillas, Nicholas A. Furlotte, Pooja Gandhi, Karl Heilbron, Barry Hicks, Karen E. Huber, Ethan M. Jewett, Yunxuan Jiang, Aaron Kleinman, Keng‐Han Lin, Nadia K. Litterman, Marie K. Luff, Matthew H. McIntyre, Kimberly F. McManus, Joanna L. Mountain, Sahar V. Mozaffari, Elizabeth S. Noblin, Carrie A. M. Northover, Jared O’Connell, Aaron A. Petrakovitz, Steven J. Pitts, G. David Poznik, J. Fah Sathirapongsasuti, Janie F. Shelton, Suyash Shringarpure, Chao Tian, Joyce Y. Tung, Robert J. Tunney, Vladimir Vacic, Xin Wang, Amir Zare, Preben Bo Mortensen, Ole Mors, Thomas Werge, Merete Nordentoft, David M. Hougaard, Jonas Bybjerg‐Grauholm, Marie Bækvad‐Hansen, Takayuki Morisaki, Eco J. C. de Geus, Rino Bellocco, Yukinori Okada, Anders D. Børglum, Peter K. Joshi, Adam Auton, David A. Hinds, Benjamin M. Neale, Raymond K. Walters, Michel G. Nivard, John R. B. Perry, Andrea Ganna
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 × 10−36). 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. Genetic analyses identify widespread sex-differential participation bias in population-based studies and show how this bias can lead to incorrect inferences. These findings highlight new challenges for association studies as sample sizes continue to grow.