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 as it requires genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study (GWAS) contrasting one subgroup versus another. For example, we show that sex exhibits artefactual autosomal heritability in the presence of sex-differential participation bias. By performing a GWAS of sex in ∼3.3 million males and females, we identify over 158 autosomal loci spuriously associated with sex and highlight complex traits underpinning differences in study participation between sexes. For example, the body mass index-increasing allele at FTO was observed at higher frequency in males compared to females (OR 1.02, P = 4.4 × 10-36). Finally, we demonstrate 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.
Original language | English |
---|---|
Article number | 53 |
Pages (from-to) | 663 |
Number of pages | 671 |
Journal | Nature Genetics |
Volume | 53 |
DOIs | |
Publication status | Published - 22 May 2021 |