This project investigates how genetic predisposition interacts with lifestyle factors in non-communicable diseases (NCDs), focusing on diabetes, hypertension, and cancers. Leveraging the UK Biobank and the WuXi Taihu cohort!TBTB!, we will integrate genomic, lifestyle, and clinical data to uncover mechanisms and guide precision prevention.
Research Questions: (1) Which genetic variants drive susceptibility to these NCDs? (2) How do lifestyle factors (diet, activity, smoking) modify genetic risk and influence outcomes? (3) What epidemiological patterns and risk stratification emerge across UK and Chinese cohorts?
Objectives: (i) Identify and validate genetic determinants via genome-wide analyses; (ii) Quantify gene-environment interactions by combining risk scores with lifestyle/exposure data; (iii) Apply AI/ML (ensemble models, deep neural networks, interpretable SHAP) to predict risk and stratify populations; (iv) Compare UK Biobank and TBTB findings to assess generalizability.
Scientific Rationale: NCDs reflect complex gene-environment interplay not captured by traditional epidemiology. The UK Biobank provides unparalleled genomic and lifestyle data, while TBTB adds a regional Chinese perspective. Integrating these cohorts with AI-driven analytics will reveal hidden patterns, biomarkers, and causal pathways. Expected outcomes include insights into genetic and lifestyle contributions, improved early risk models, and evidence to guide tailored prevention, strengthening global understanding of NCD etiology.
