Skip to navigation Skip to main content Skip to footer

Approved research

Genetic, environmental and lifestyle predictors of brain/cognitive-related outcomes.

Principal Investigator: Dr Donald Lyall
Approved Research ID: 17689
Approval date: February 1st 2016

Lay summary

The project aims to integrate genetic, biomarker, brain imaging and cognitive/mood data to give a complete 'picture' of what predicts, mediates and moderates worse mental ability and mood disorder in UK Biobank, cross-sectionally and prospectively using follow-up data. We will research this question using UK Biobank cognitive test, brain MRI (structural and functional), biomarker (i.e. assay), mood-related and cognitive data, using formal tests of association, mediation and moderation. We will use the primary care and HES data in order to ascertain follow-up mood disorders. Our project meets UK Biobank?s stated purpose of improving the prevention, diagnosis and treatment of illnesses by identifying risk factors for lower cognitive ability and mood disorder; important risk factors for physical ill health, earlier mortality and lower quality of life. Insights from this work will lead to a better understanding of disease processes in cognitive decline and Alzheimer's disease (dementia) and mood disorders such as depression, including better approaches to diagnosis and ultimately the development of new treatments. The work will consist of using genome-wide association (GWA) data in the UK Biobank, together with environmental variables e.g. sociodemographics, and lifestyle variables e.g. health related behaviours like smoking status, alcohol intake etc., to test for independent associations with cognitive abilities and mood disorders, both at baseline and at follow-up, based on NHS record linkage. We will test for how these associations are mediated by brain MRI variables, and/or moderated by biomarker variables (e.g. lipid levels, inflammatory markers). The project will make full use of phenotypic, genetic, raw/derived brain MRI/fMRI and biomarker data in the full cohort (as and when each aspect becomes available).