This project aims to leverage multi-modal data (clinical, genomic, proteomic, imaging, biochemical) from UK Biobank to advance understanding of urological diseases (e.g., urological cancers, chronic kidney disease, urolithiasis).
Research questions: 1. Which genetic, metabolic, and environmental factors contribute to disease onset, progression, and subtypes? 2. What is the bidirectional association between urological diseases and other systemic conditions (i.e., which diseases increase urological disease risk, and which diseases are subsequent risks of urological diseases.? 3. What are the underlying genetic bases and molecular mechanisms (e.g., key proteins, metabolic pathways) driving these associations? 4. Can integrated multi-modal data improve early diagnosis and prognosis prediction? 5. What molecular pathways and cross-system interactions drive pathogenesis and outcomes? 6. Which genetic and environmental factors are robust predictors of long-term prognosis?
Objectives: 1. Examine impact of lifestyle/environmental factors (diet, activity, smoking, pollution) on risk/prognosis. 2. Identify key genetic variants linked to susceptibility/progression. 3. Investigate gene-environment interactions modifying disease risk. 4. Assess if interventions can modulate genetic susceptibility. 5. Quantify relative contributions of modifiable vs. genetic factors. 6. Explore the genetic foundations and molecular pathways (including proteomic and metabolomic networks) underlying disease etiology and comorbidities. 7. Develop integrated predictive models for early detection and prognosis.
Scientific rationale: Urological diseases are prevalent and burdensome, with rising incidence. Current research is limited by small samples, single data types, and short follow-up. UK Biobank uniquely addresses these gaps through its long-term follow-up, large scale, and multi-modal integration, enabling robust investigation of risk factors, mechanisms, and prediction.
