Using Machine Learning to Study the Effects of Genetic Predisposition on Brain Aging in the UK Biobank

The influence of genetic predisposition on changes in brain morphology during aging remains largely unknown. This study explores the effects of genetic predisposition on three key brain regions: total brain volume (TBV), lateral ventricular volume (LVV), and total hippocampal volume (THV). The brain age gap estimate (BrainAGE) biomarker is used as an input to a genome-wide association study to determine which single nucleotide polymorphisms (SNPs) and genes are associated with accelerated brain aging. Six independent significant SNPs were found to contribute to accelerated morphological changes: TBV had associations on chromosome 17 linked with brain aging, and the total THV had independent significant associations in the APOC1 and TOMM40 gene regions related to neurodegeneration. Lastly, LVV presented a possible novel discovery in the gene NUAK1, known to play a role in cellular senescence. This study provides a framework to uncover complex associations between brain aging physiology and genetics.