Regional brain aging trajectories vary among individuals. Inter-individual variability in regional brain aging dynamics can be mapped to gene variants, gene network architectures, and gene expression patterns, which can inform personalized interventions for the maintenance of brain health, as well as the prevention of age-related structural/functional deterioration. To address the hallmarks of brain aging in a personalized manner, our project will develop a multicomponent AI/ML model using cross-sectional and longitudinal brain imaging scans, annotated with person-level genome sequencing data, to infer the optimal intervention targets for specific brain aging signatures.
Precision medicine for brain health informed by gene-mapped MRI features