Associations Between Alcohol Use, Region-specific Gray Matter Volume Reductions, and Machine Learning-predicted Brain Aging in Young Adults
Year: 2026
Type: dissertation
Abstract: Alcohol use has been established as a contributor to accelerated biological aging, with emerging evidence of its impact on brain aging. Brain-predicted age difference (brain-PAD), calculated as the difference between machine learning-predicted brain age and chronological age, provides a biomarker for accelerated or delayed brain aging. However, the relationship between alcohol use and region-specific brain aging in healthy young adults remains unclear. To better parse this question, we applied brainageR to Human Connectome Project data to estimate brain-PAD and used voxel-based morphometry to identify regions where gray matter volume reductions overlapped between alcohol use and brain-PAD. We found three clusters with spatially overlapping reductions, most notably in the supplementary motor area and the middle frontal gyrus, suggesting that alcohol consumption may accelerate aging in specific brain regions in healthy young adults without a clinical alcohol use disorder.
DOI: 10.17615/0y34-3821
Author: Dhayagude, Pari
Institution: University of North Carolina at Chapel Hill
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7118417591
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