| Title: | Genetic predictors of participation in optional components of UK Biobank |
| Journal: | Nature Communications |
| Published: | 9 Feb 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/33563987/ |
| DOI: | https://doi.org/10.1038/s41467-021-21073-y |
| URL: | https://www.nature.com/articles/s41467-021-21073-y.pdf |
| Citations: | 127 (54 in last 2 years) as of 8 Aug 2024 |
Publication 4928
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
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.</p>
9 Authors
- Jessica Tyrrell
- Jie Zheng
- Robin Beaumont
- Kathryn Hinton
- Tom G. Richardson
- Andrew R. Wood
- George Davey Smith
- Timothy M. Frayling
- Kate Tilling
Enabling scientific discoveries that improve human health