Convergent imaging and genetic signatures of gray matter atrophy in Parkinson's disease.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by widespread structural brain alterations, yet the specific patterns of brain atrophy and their underlying genetic mechanisms remain incompletely understood. Here, we integrated large-scale neuroimaging meta-analysis with population-scale imaging genetics to systematically characterize the genetic architecture linking gray matter volume (GMV) abnormalities to PD. We first performed a meta-analysis of structural MRI studies comprising 3212 patients with PD and 2056 controls, identifying robust patterns of GMV reduction and assessing differences across medication states. Using these meta-analytically defined regions as imaging phenotypes, we extracted GMV measures from the UK Biobank and conducted genome-wide association analysis (GWAS). This analysis identified 12 significant SNPs associated with PD-related GMV atrophy. Furthermore, we performed pleiotropy analysis and identified 22 SNPs jointly associated with PD risk and GMV reduction. Functional enrichment analyses revealed that these shared genes converge on pathways involved in clathrin-mediated endocytosis and synaptic vesicle recycling. Spatiotemporal transcriptomic profiling further characterized the developmental expression patterns of these genes, while molecular docking analyses suggested potential therapeutic targets. Together, these findings provide a comprehensive characterization of the genetic architecture linking brain structural abnormalities to PD, offering new molecular insights into the mechanisms underlying neurodegenerative brain damage and potential avenues for therapeutic intervention.