Neuroimaging-derived brain endophenotypes link molecular mechanisms to Alzheimer's disease and aging.

ABSTRACT: Alzheimer's disease (AD) genome-wide association studies (GWAS), typically based on clinical phenotypes, have identified numerous risk loci, yet linking these variants to brain changes and molecular processes remains challenging. We developed a DNE-xQTL framework integrating deep learning-derived dimensional neuroimaging endophenotypes (DNEs) with comprehensive brain molecular quantitative trait loci (xQTL) to dissect genetic pathways underlying AD- and aging-related brain variation. By performing GWAS on seven DNEs and applying integrative computational analyses, we biologically annotated each DNE and prioritized xQTL-supported gene targets. This approach both enhanced interpretation of established AD loci through DNE-mediated annotations and revealed underexplored regulatory pathways, or

SUBMITTER: Li R 

PROVIDER: S-EPMC12676415 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature