Literature DB >> 33563987

Genetic predictors of participation in optional components of UK Biobank.

Jessica Tyrrell1, Jie Zheng2,3, Robin Beaumont4, Kathryn Hinton4, Tom G Richardson2,3, Andrew R Wood4, George Davey Smith2,3, Timothy M Frayling4, Kate Tilling5,6.   

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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Year:  2021        PMID: 33563987      PMCID: PMC7873270          DOI: 10.1038/s41467-021-21073-y

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  41 in total

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  22 in total

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6.  Genetic analyses identify widespread sex-differential participation bias.

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Review 7.  Dissecting polygenic signals from genome-wide association studies on human behaviour.

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