This study aims to examine how internal and external environmental exposures-such as pollution, lifestyle, and genetic risk-individually and synergistically influence the onset and prognosis of chronic diseases and multimorbidity. Prior research has mostly focused on single exposures and disease incidence, lacking a comprehensive analysis of multi-exposure interactions and long-term health outcomes. Leveraging the UK Biobank’s rich longitudinal data, we will investigate: (1) How do multiple internal and external exposures affect chronic disease risk and progression? (2) How do gene-environment interactions influence disease outcomes, including survival and complications? (3) Do exposure combinations impact multimorbidity trajectories differently than single diseases? (4) Do multi-omics biomarkers mediate these relationships?
Our objectives are to: (1) quantify the effects of exposures on chronic disease incidence and prognosis (e.g., mortality, recurrence); (2) build interaction networks to identify high-risk exposure combinations and vulnerable populations; (3) compare exposure patterns in single vs. comorbid conditions; and (4) integrate omics data to uncover biological mechanisms and develop risk prediction models.
Chronic diseases pose a major public health burden, with complex gene-environment interactions influencing their development and clinical course. The UK Biobank’s multidimensional data enables a systems-level exposome approach to evaluate internal and external exposures, along with genomics, metabolomics, and other biomarkers. By revealing multi-level exposure pathways and prognostic mechanisms, this research aims to support precision prevention and disease management strategies, ultimately reducing chronic disease burden.
