Journal
NATURE GENETICS
Volume 53, Issue 5, Pages 663-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41588-021-00846-7
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Funding
- Academy of Finland Fellowship [323116]
- Medical Research Council [MC_UU_12015/2]
- ZonMw grant [849200011]
- Netherlands Organization for Health Research and Development [531003014]
- VENI grant - Dutch Research Council [VI.Veni.191 G.030]
- Foundation Volksbond Rotterdam
- ZonMw grant from the Netherlands Organization for Health Research and Development [849200011]
- Business Finland [HUS 4685/31/2016, UH 4386/31/2016]
- AbbVie
- AstraZeneca UK
- Biogen MA
- Celgene Corporation
- Celgene International II Sarl
- Genentech
- Merck Sharp Dohme Corp
- Pfizer
- GlaxoSmithKline
- Sanofi
- Maze Therapeutics
- Janssen Biotech
- Academy of Finland (AKA) [323116, 323116] Funding Source: Academy of Finland (AKA)
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Genetic analyses have revealed widespread sex-differential participation bias in population-based studies, potentially leading to incorrect inferences; the study demonstrated artifactual autosomal heritability of sex in the presence of sex-differential participation bias; through conducting a genome-wide association study contrasting one subgroup versus another, it is possible to estimate comparative biases.
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. 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 x 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.
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