Musculoskeletal disorders (MSDs) are a leading cause of global disability but rarely occur in isolation. We aim to answer:
What are the shared genetic and metabolic mechanisms linking MSDs (e.g., osteoarthritis, fractures, spinal injuries) with cardiometabolic and neurological diseases?
How do “cross-system” interactions, such as the neuro-skeletal axis and muscle-bone crosstalk (osteosarcopenia), influence disease progression?
Can AI-driven analysis of imaging and wearable data improve risk stratification?
Objectives:
Broad Profiling: Systematically identify risk factors for a full spectrum of MSDs, ranging from common degenerative conditions to rare orthopedic phenotypes.
Multimorbidity Networks: Investigate the “Bone-Vascular-Metabolic Axis” to understand how diabetes, vascular calcification, and obesity affect skeletal integrity.
Neuro-Skeletal Interaction: Explore how chronic pain and neurological dysfunction impact brain structure (MRI) and mental health.
Therapeutic Discovery: Apply drug repurposing strategies (e.g., evaluating statins/metformin) for orthopedic outcomes.
Digital Phenotyping: Develop deep learning models using MRI/DXA images and accelerometer data to predict functional decline.
Scientific Rationale:
Current research often treats the skeletal system in isolation, overlooking its systemic connections. However, clinical evidence suggests that bone health is tightly regulated by metabolic and neurological homeostasis. Traditional studies lack the scale to dissect these complex multimorbidity patterns. UK Biobank’s massive cohort and deep phenotyping (genomics, proteomics, imaging) provide a unique opportunity to conduct Phenome-Wide Association Studies (PheWAS). By integrating multi-omics data with clinical outcomes, we aim to uncover upstream regulators of orthopedic comorbidities, ultimately guiding holistic prevention strategies for the aging population.