Genetic predictors of participation in optional components of UK Biobank

Jessica Tyrrell (), Jie Zheng, Robin Beaumont, Kathryn Hinton, Tom G. Richardson, Andrew R. Wood, George Davey Smith, Timothy M. Frayling and Kate Tilling ()
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Jessica Tyrrell: University of Exeter
Jie Zheng: University of Bristol
Robin Beaumont: University of Exeter
Kathryn Hinton: University of Exeter
Tom G. Richardson: University of Bristol
Andrew R. Wood: University of Exeter
George Davey Smith: University of Bristol
Timothy M. Frayling: University of Exeter
Kate Tilling: University of Bristol

Nature Communications, 2021, vol. 12, issue 1, 1-13

Abstract: 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

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21073-y

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DOI: 10.1038/s41467-021-21073-y

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