Associations between alcohol use and accelerated biological ageing

Harmful alcohol use is a leading cause of premature death and is associated with age-related disease. Biological ageing is highly variable between individuals and may deviate from chronological ageing, suggesting that biomarkers of biological ageing (derived from DNA methylation or brain structural measures) may be clinically relevant. Here, we investigated the relationships between alcohol phenotypes and both brain and DNA methylation age estimates. First, using data from UK Biobank and Generation Scotland, we tested the association between alcohol consumption (units/week) or hazardous use (Alcohol Use Disorders Identification Test [AUDIT] scores) and accelerated brain and epigenetic ageing in 20,258 and 8051 individuals, respectively. Second, we used Mendelian randomisation (MR) to test for a causal effect of alcohol consumption levels and alcohol use disorder (AUD) on biological ageing. Alcohol use showed a consistent positive association with higher predicted brain age (AUDIT-C: β = 0.053, p = 3.16 × 10−13; AUDIT-P: β = 0.052, p = 1.6 × 10−13; total AUDIT score: β = 0.062, p = 5.52 × 10−16; units/week: β = 0.078, p = 2.20 × 10−16), and two DNA methylation-based estimates of ageing, GrimAge (units/week: β = 0.053, p = 1.48 × 10−7) and PhenoAge (units/week: β = 0.077, p = 2.18x10−10). MR analyses revealed limited evidence for a causal effect of AUD on accelerated brain ageing (β = 0.118, p = 0.044). However, this result should be interpreted cautiously as the significant effect was driven by a single genetic variant. We found no evidence for a causal effect of alcohol consumption levels on accelerated biological ageing. Future studies investigating the mechanisms associating alcohol use with accelerated biological ageing are warranted

Automated Classification of Depression from Structural Brain Measures across Two Independent Community-based Cohorts

ACKNOWLEDGEMENTS: This study was supported and funded by the Wellcome Trust Strategic Award ‘Stratifying Resilience and Depression Longitudinally’ (STRADL) (Reference 104036/Z/14/Z), and the Medical Research Council Mental Health Pathfinder Award ‘Leveraging routinely collected and linked research data to study the causes and consequences of common mental disorders’ (Reference MRC-MC_PC_17209). MAH is supported by research funding from the Dr Mortimer and Theresa Sackler Foundation. The research was conducted using the UK Biobank resource, with application number 4844. Structural brain imaging data from the UK Biobank was processed at the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE) http://www.ccace.ed.ac.uk/), which is a part of the crosscouncil Lifelong Health and Wellbeing Initiative (MR/K026992/1). CCACE received funding from Biotechnology and Biological Sciences Research Council (BBSRC), Medical Research Council (MRC), and was also supported by Age UK as part of The Disconnected Mind project. This work has made use of the resources provided by the Edinburgh Compute and Data Facility (ECDF) (http://www.ecdf.ed.ac.uk/)Peer reviewedPublisher PD