Approved Research

Genetic and environmental factors associated with a neuroimaging-based biomarker of brain ageing: a longitudinal analysis of UK Biobank participants

Lay summary

As the ageing population increases, the burden of age-associated functional decline and neurodegenerative disease is becoming more prevalent. While the ageing brain can be accompanied by structural changes, cognitive decline, and an increased risk of dementia, not everyone is affected the same way. Therefore, the primary aim of this work is to identify genetic and environmental (non-genetic/modifiable) factors that may influence the rate of brain ageing. First, using the so-called 'brain age' paradigm we will employ a model for predicting whether someone's brain appears older or younger than expected for their chronological age, based on structural brain imaging scans from a large sample of participants and by building upon previous relevant work in UK Biobank. Having an older-appearing brain, as indexed by a greater discrepancy between brain-predicted age and chronological age (known as brain-predicted age difference [brain-PAD]), has previously been associated with a range of health-related factors and outcomes, including but not limited to smoking, alcohol consumption, systolic blood pressure, body mass index, depression, dementia, and mortality. However, previous studies (including those performed in UK Biobank) have mainly relied on brain-PAD estimates at a single point time, thereby limiting interpretation of findings in terms of structural brain changes over time. Therefore, in this study we will estimate brain-PAD in a subset of UK Biobank participants who were scanned twice over a period of time (~ 2 years). Finally, we will examine whether (and how) changes in brain-PAD over time is associated with a range of factors relating to genetics, socio-demographics, lifestyle, physical and mental health. The study is expected to last approximately 36 months. We hope to identify genetic and environmental factors that may predispose people to poorer brain ageing. This will help improve our understanding of individual differences in brain ageing and could be informative for developing interventions to preserve brain health in late life.