Abstract #1500

Genetic Influences on Brain Aging: Analyzing Sex Differences in the UK Biobank using Structural MRI

Karen Ardila^1,2,3, Aashka Mohite^2,3,4, Abdoljalil Addeh^1,2,3, Amanda V. Tyndall^2,3,5, Cindy K. Barha^2,3,6, Quan Long^2,3,5,7, and M. Ethan MacDonald^1,2,3,4,8

¹Department of Biomedical Engineering, University of Calgary, Calgary, AB, Canada, ²Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada, ³Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada, ⁴Department of Electrical and Software Engineering, University of Calgary, Calgary, AB, Canada, ⁵Department of Medical Genetics, University of Calgary, Calgary, AB, Canada, ⁶Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada, ⁷Department of Biochemistry & Molecular Biology, University of Calgary, Calgary, AB, Canada, ⁸Department of Radiology, University of Calgary, Calgary, AB, Canada

Synopsis

Keywords: Aging, Brain, Neurogenetics, GWAS

Motivation: Brain aging varies significantly between sexes, yet genetic contributions to these differences remain under-explored.

Goal(s): Identify sex-specific genetic variants linked to accelerated brain aging using structural MRI data.

Approach: This study proposes implementing Brain Age Gap Estimates (BrainAGE) with sex-stratified GWAS to uncover genetic associations in T1-weighted MRI data from the UK Biobank, complemented by PostGWAS analyses to explore biological pathways and gene expression.

Results: Sex-stratified analyses revealed neurotransmitter and mitochondrial response to cellular stress genes linked to brain aging in females and immune-related genes in males. Shared genes suggest common neurostructural roles, advancing understanding of sex-specific genetic determinants in brain aging.

Impact: This study highlights the importance of sex-stratified analysis in understanding the genetic associations with brain aging. Findings pave the way for future work on personalized treatments and preventative measures for neurodegeneration based on individual genetic profiles and sex-specific risks.

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