Genetic predictors of participation in optional components of UK Biobank

Tyrrell, Jess; Zheng, Jie; Beaumont, Robin N; Hinton, Kathryn; Richardson, Tom G; Wood, Andrew R.; Smith, George Davey; Frayling, Timothy M.; Tilling, Kate

doi:10.1038/s41467-021-21073-y

Cited by 141 publications

(129 citation statements)

References 41 publications

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“…Second, there is ‘healthy selection’ into the UK Biobank; only approximately 5% of those invited to participate in the study accepted the invitation, 41 and there is evidence that genetic liability to AD is associated with lower participation rates in the optional components of UK Biobank. 42 This makes it less likely that participants with an existing AD diagnosis or undiagnosed prodromal disease would have been recruited into the study, and again, may induce bias in the causal effect estimates.…”

Section: Discussionmentioning

confidence: 99%

Is disrupted sleep a risk factor for Alzheimer’s disease? Evidence from a two-sample Mendelian randomization analysis

Anderson

Richmond

Jones

et al. 2020

International Journal of Epidemiology

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Background It is established that Alzheimer’s disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD. Methods We used the largest published genome-wide association studies of self-reported and accelerometer-measured sleep traits (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness), and AD. Mendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters on AD risk. Results Overall, there was little evidence to support a causal effect of sleep traits on AD risk. There was some suggestive evidence that self-reported daytime napping was associated with lower AD risk [odds ratio (OR): 0.70, 95% confidence interval (CI): 0.50–0.99). Some other sleep traits (accelerometer-measured ‘eveningness’ and sleep duration, and self-reported daytime sleepiness) had ORs of a similar magnitude to daytime napping, but were less precisely estimated. Conclusions Overall, we found very limited evidence to support a causal effect of sleep traits on AD risk. Our findings provide tentative evidence that daytime napping may reduce AD risk. Given that this is the first MR study of multiple self-report and objective sleep traits on AD risk, findings should be replicated using independent samples when such data become available.

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Section: Discussionmentioning

confidence: 99%

Is disrupted sleep a risk factor for Alzheimer’s disease? Evidence from a two-sample Mendelian randomization analysis

Anderson

Richmond

Jones

et al. 2020

International Journal of Epidemiology

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“…However, UK Biobank does appear to provide valid assessments of risk factor associations that appear to be widely generalisable [53]. Second, both the actigraphy and MHQ data were only analysed in a subset of individuals and this may introduce further biases that could influence our observational and MR findings [54,55]. Third, the diurnal preference variants utilised in MR were discovered using UK Biobank, which has the potential to induce biases into the data, especially "winner's curse", which can lead to underestimation of the true causal effects.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Using Mendelian Randomisation methods to understand whether diurnal preference is causally related to mental health

et al. 2021

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Late diurnal preference has been linked to poorer mental health outcomes, but the understanding of the causal role of diurnal preference on mental health and wellbeing is currently limited. Late diurnal preference is often associated with circadian misalignment (a mismatch between the timing of the endogenous circadian system and behavioural rhythms), so that evening people live more frequently against their internal clock. This study aims to quantify the causal contribution of diurnal preference on mental health outcomes, including anxiety, depression and general wellbeing and test the hypothesis that more misaligned individuals have poorer mental health and wellbeing using an actigraphy-based measure of circadian misalignment. Multiple Mendelian Randomisation (MR) approaches were used to test causal pathways between diurnal preference and seven well-validated mental health and wellbeing outcomes in up to 451,025 individuals. In addition, observational analyses tested the association between a novel, objective measure of behavioural misalignment (Composite Phase Deviation, CPD) and seven mental health and wellbeing outcomes. Using genetic instruments identified in the largest GWAS for diurnal preference, we provide robust evidence that early diurnal preference is protective for depression and improves wellbeing. For example, using one-sample MR, a twofold higher genetic liability of morningness was associated with lower odds of depressive symptoms (OR: 0.92, 95% CI: 0.88, 0.97). It is possible that behavioural factors including circadian misalignment may contribute in the chronotype depression relationship, but further work is needed to confirm these findings.

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“…At these visits, most of the baseline questionnaires and clinical assessments are also repeated 3 . In addition to the participation bias already noted in the cohort in baseline assessments at recruitment, 2 it has been shown that there is further participation bias with regard to completing additional online assessments (vs. attending only baseline) and that, to some extent, this participation bias has genetic contributions which vary by male/female sex 4,5 .…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies of bias in the UK Biobank population have focused on participation at all, and/or predictors of additional participation in subsequent online assessments 4,5 . We are not aware of research which has explored differences in participants who subsequently attended for imaging studies.…”

Section: Introductionmentioning

confidence: 99%

Quantifying bias in psychological and physical health in the UK Biobank imaging sub-sample.

Lyall¹,

Quinn²,

Lyall³

et al. 2021

Preprint

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Background: UK Biobank is a prospective cohort study of around half-a-million general population participants, recruited between 2006 and 2010, with baseline studies at recruitment and multiple assessments since. From 2014 to date magnetic resonance imaging (MRI) has been pursued in a participant sub-sample, with the aim to scan around n=100k. This sub-sample are studied widely and therefore understanding their relative characteristics is important for future reports. We aimed to quantify psychological and physical health in the UK Biobank imaging sub-sample, compared with the rest of the cohort. Methods: We used t-tests and chi-squares for continuous/categorical variables respectively, to estimate average differences on a range of cognitive, mental and physical health phenotypes. We contrasted baseline values of participants who attended imaging (vs. had not), and compared their values at the imaging visit vs. baseline values of participants who were not scanned. We also tested the hypothesis that the associations of established risk factors with worse cognition would be underestimated in the (hypothesized) healthier imaging group compared with the full cohort. We tested these interactions using linear regression models.Results: On a range of cognitive, mental health, cardiometabolic, inflammatory and neurological phenotypes we found that the 47,920 participants who were scanned by January 2021 showed consistent statistically significant ‘healthy’ bias compared with the ~450,000 who were not scanned. These effect sizes were small to moderate based on Cohen’s d/Cramer’s V metrics. We found evidence of interaction, where stratified analysis demonstrated that associations of established cognitive risk factors were smaller in the imaging sub-sample compared with the full cohort. Conclusion: Of the ~100,000 participants who ultimately will undergo MRI assessment within UK Biobank, the first ~50,000 showed some ‘healthy’ bias on a range of metrics at baseline. Those differences largely remained at the subsequent imaging visit, and we provide evidence that testing associations in the imaging sub-sample alone could lead to potential underestimation of exposure/outcome estimates.

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Genetic predictors of participation in optional components of UK Biobank

Cited by 141 publications

References 41 publications

Is disrupted sleep a risk factor for Alzheimer’s disease? Evidence from a two-sample Mendelian randomization analysis

Is disrupted sleep a risk factor for Alzheimer’s disease? Evidence from a two-sample Mendelian randomization analysis

Using Mendelian Randomisation methods to understand whether diurnal preference is causally related to mental health

Quantifying bias in psychological and physical health in the UK Biobank imaging sub-sample.

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