Research Questions:
1.What genetic, metabolic, and environmental determinants contribute to the etiology, progression, and phenotypic heterogeneity of broad-spectrum Musculoskeletal (MSK) disorders ?
2.Can integrated multi-modal data (genomics, proteomics, imaging) from UK Biobank enhance the accuracy of risk stratification and early prediction for bone and joint diseases?
3.What are the shared molecular pathways and causal links between MSK disorders and systemic comorbidities?
4.Which modifiable lifestyle factors are robust predictors of long-term prognosis?
Objectives:
1.Identify Determinants: Systematically identify genetic variants, lifestyle behaviors, and environmental exposures associated with the susceptibility and subtypes of MSK disorders.
2.Model Development: Develop and validate predictive models using machine learning and polygenic risk scores by integrating clinical, genetic, imaging, and multi-omics data to forecast disease risk.
3.Mechanism Elucidation: Uncover causal mechanisms and novel therapeutic targets through multi-omics integration.
4. Outcome Assessment: Validate robust prognostic indicators for adverse outcomes (e.g., fractures, joint replacement) using long-term follow-up data.
Scientific Rationale:
MSK disorders, including osteoarthritis, osteoporosis,osteoportic fracture, rheumatoid arthritis and osteonecrosis, represent a leading cause of global disability in the aging population. Despite their prevalence, the precise interplay between genetic susceptibility, environmental exposures, and metabolic dysregulation remains incompletely understood. Furthermore, MSK disorders often co-occur with systemic conditions, suggesting shared underlying mechanisms. The UK Biobank, with its large-scale prospective cohort, deep phenotyping, imaging data, and multi-omics resources, offers a unique opportunity to unravel this complexity. This research leverages high-dimensional data to move beyond simple associations toward causal inference.
