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Genetic predictors of participation in optional components of UK Biobank

Jessica Tyrrell, Jie Zheng, Robin Beaumont and 6 more

Nature Communications · 2021 · CC BY

Abstract

Large studies such as UK Biobank are increasingly used for GWAS and Mendelian randomization (MR) studies. However, selection into and dropout from studies may bias genetic and phenotypic associations. We examine genetic factors affecting participation in four optional components in up to 451,306 UK Biobank participants. We used GWAS to identify genetic variants associated with participation, MR to estimate effects of phenotypes on participation, and genetic correlations to compare participation bias across different studies. 32 variants were associated with participation in one of the optional components ( P < 6 × 10 −9 ), including loci with links to intelligence and Alzheimer’s disease. Genetic correlations demonstrated that participation bias was common across studies. MR showed that longer educational duration, older menarche and taller stature increased participation, whilst higher levels of adiposity, dyslipidaemia, neuroticism, Alzheimer’s and schizophrenia reduced participation. Our effect estimates can be used for sensitivity analysis to account for selective participation biases in genetic or non-genetic analyses.

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Cited by papers we hold 4

Participation bias in the UK Biobank distorts genetic associations and downstream analyses · 2023
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Mendelian imputation of parental genotypes improves estimates of direct genetic effects · 2022
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Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues · 2020
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Collider bias undermines our understanding of COVID-19 disease risk and severity · 2020
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