Central nervous system (CNS) diseases, particularly stroke, represent a leading cause of mortality and long-term disability, yet their multifactorial etiology remains incompletely understood. This project leverages UK Biobank’s unprecedented scale of multi-modal data to elucidate the complex determinants of stroke and other CNS disorders while examining their interconnections within disease networks.
We’ll address these questions:
(1) How do genetic variants and environmental exposures independently and interactively influence stroke risk across its subtypes? And could these factors served as intervention targets.
(2) Can quantitative radiomic features derived from brain imaging serve as novel biomarkers for CNS diseases susceptibility, prognosis and mediate genetic/environmental effects?
(3) What are the causal relationships and shared pathophysiological pathways among CNS diseases?
(4) Can multi-modal data integration enhance the early identification of individuals at high risk of CNS diseases compared to uni-modal models?
Expected outcomes include novel genetic loci, quantifiable imaging biomarkers, and causal inference maps of disease relationships. These will advance precision prevention strategies, enable earlier risk stratification, and inform multi-target interventions. Our result will presented as predictive model and genetic hints to mechaism research.
The scientific rationale is that no single data modality can fully illustrste the nature of these conditions. The prevalence of these diseases places high demands on the cohort size. UKB’s unparalleled data scale make it ideal for our research. This study will provide actionable insights to support precision prevention and provide directions to investigate disease mechanisms.
