Genetic predictors of participation in optional components of UK Biobank

Abstract

Large studies (e.g. UK Biobank) are increasingly used for GWAS and Mendelian randomization (MR) studies. 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<6x10 -9 ), including loci with known 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.

Factors associated with participation over time in the Avon Longitudinal Study of Parents and Children: a study using linked education and primary care data

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Collider bias undermines our understanding of COVID-19 disease risk and severity

“…Medical and scientific interest: Studies recruiting voluntary samples may be biased as they are likely to contain a disproportionate amount of people who have a strong medical or scientific interest. It is likely that these people will themselves have greater health awareness, healthier behaviour, be more educated, and have higher incomes 31,52 .…”

Reduced reproductive success is associated with selective constraint on human genes

“…Analysis of psychiatric disorders in UK Biobank is complicated by both recruitment bias away from more severe psychiatric disorders and incomplete data on participants 10,[33][34][35] . The most comprehensive data are available on a subset of UK Biobank individuals from a mental health questionnaire for which participants were invited by email (n = 157,366) 34 .…”

“…When possible, we used independent estimates from population level or external data to alleviate biases in UK Biobank phenotype ascertainment ( Supplementary Figure 18) 35 . As such, data on cognitive ability and fertility are collected from Swedish population-level government administrative registers that have been linked to Swedish conscription registers 65 .…”