Participation bias in the UK Biobank distorts genetic associations and downstream analyses

While volunteer-based studies such as the UK Biobank have become the cornerstone of genetic epidemiology, the participating individuals are rarely representative of their target population. To evaluate the impact of selective participation, here we derived UK Biobank participation probabilities on the basis of 14 variables harmonized across the UK Biobank and a representative sample. We then conducted weighted genome-wide association analyses on 19 traits. Comparing the output from weighted genome-wide association analyses (n(effective) = 94,643 to 102,215) with that from standard genome-wide association analyses (n = 263,464 to 283,749), we found that increasing representativeness led to changes in SNP effect sizes and identified novel SNP associations for 12 traits. While heritability estimates were less impacted by weighting (maximum change in h(2), 5%), we found substantial discrepancies for genetic correlations (maximum change in r(g), 0.31) and Mendelian randomization estimates (maximum change in beta(STD), 0.15) for socio-behavioural traits. We urge the field to increase representativeness in biobank samples, especially when studying genetic correlates of behaviour, lifestyles and social outcomes. The authors use information on 14 traits and create a representative pseudo-sample of the UK Biobank population, showing that participation bias distorts behavioural genome-wide association study and Mendelian randomization findings.