HUMAN MULTI-OMICS ELUCIDATES THE COMORBIDITY MECHANISMS OF CEREBROVASCULAR DISEASES AND ALL-CAUSE DEMENTIA

Cerebrovascular disease (CVD) and all-cause dementia (ACD) cluster frequently, yet whether this reflects shared susceptibility as comorbidity or a directional cascade from CVD to ACD remains unresolved. We addressed this question by integrating large-scale phenotypes and multi-omics data from UK Biobank, encompassing CVD (n=31,663) and ACD (n=10,815), together with neuroimaging, cognitive assessments, and genetic, proteomic, and metabolomic measurements, to characterize CVD-to-ACD transitions and delineate putative mechanisms. Using cross-lagged panel modeling of longitudinal neuroimaging and cognition, we found that early CVD-associated brain alterations temporally preceded and predicted subsequent cognitive decline, consistent with a directional pathological trajectory. Genetic analyses provided convergent evidence for causal inference, demonstrating that genetic liability to CVD was associated with elevated risk of ACD beyond shared risk factors, supporting a partially causal contribution of CVD to ACD pathogenesis. Integrative proteomic and metabolomic profiling further partitioned molecular signatures into (i) biomarkers shared by CVD and ACD, consistent with overlapping neurodegenerative processes, and (ii) signals more specifically associated with progression from CVD to subsequent ACD, implicating pathway components that may differentiate comorbid from directional mechanisms. Finally, multimodal risk models combining genomic, proteomic, and metabolic markers demonstrated improved risk stratification for vascular dementia relative to conventional approaches. Together, these findings establish a scalable multi-omics framework for disentangling comorbidity from directional CVD–ACD relationships, provide mechanistic hypotheses linking vascular pathology to dementia, and inform biomarker-enabled strategies for risk prediction and early intervention.