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Genetic predictors of participation in optional components of UK Biobank
Open accessPublished version of a preprint
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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“With individual level data and a continuous exposure, non-linear MR can be applied to estimate whether the causal effect of the exposure on the outcome varies across different levels of the exposure.30,108”
From Mendelian randomization (2022) · cites this paper as [30]
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Self-citationParticipation bias in the UK Biobank distorts genetic associations and downstream analyses
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BackgroundProspective study design and data analysis in UK Biobank
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“…correlated with participation (and ongoing engagement) as covariates in the exposure-disease model can be performed, and probability weighting, simulations, and multiple imputation can be used to explore the potential impact of missing values related to participation on effect estimates (31, 35).”
Metadata
- Authors
- Tyrrell, J., Zheng, J., Beaumont, R., Hinton, K., Richardson, T. G., Wood, A. R., Davey Smith, G., Frayling, T. M., & Tilling, K.
- Affiliations
- University of Exeter (GB)
- University of Bristol (GB)
- Corresponding author
- Tyrrell, Jessica
- Tilling, Kate
- ORCID
- Venue
- Nature Communications
- Published
- 2021-02-09
- Volume
- 12
- Issue
- 1
- Pages
- 886-886
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC7873270
- OpenAlex
- W3119247746
- Cited by
- 162
- References
- 43
- Citations by year
- 2026: 14 · 2025: 16 · 2024: 30 · 2023: 36 · 2022: 43 · 2021: 15
- FWCI
- 17.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Explore Bristol Research (acceptedVersion, cc-by)
- Bristol Research (University of Bristol) (acceptedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by)
- Funders
- Academy of Medical Sciences (SBF004\1079)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Keywords
- research participation, UK Biobank, genetic correlation, Mendelian randomization, educational attainment, age at menarche, height, adiposity, dyslipidemia, neuroticism, Alzheimer's disease, schizophrenia
- MeSH terms
- Community Participation, Female, United Kingdom, Humans, Male, Middle Aged, Risk Factors, Genetic Variation, Selection Bias, Biological Specimen Banks, Genetic Predisposition to Disease, Genome-Wide Association Study, Genetic Loci, Mendelian Randomization Analysis
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