Scientific rationale!Obesity is a key modifiable osteoarthritis (OA) risk factor involving both biomechanical and metabolic-inflammatory mechanisms, though exact molecular pathways remain unclear. Large-scale plasma proteomic profiling offers a powerful approach to characterize systemic metabolic dysregulation, inflammatory signatures, and tissue remodeling processes associated with obesity-related OA pathogenesis. The UK Biobank’s extensive proteomic data, when combined with its rich phenotypic and genomic resources, provides a unique opportunity to identify novel protein biomarkers and elucidate disease mechanisms. Furthermore, established genetic associations from genome-wide association studies (GWAS) enable the application of Mendelian randomization (MR) approaches to strengthen causal inference while minimizing confounding, particularly through the use of obesity-associated genetic variants as instrumental variables.
Aims!(1) Quantify the independent contributions of mechanical loading (evaluated by BMI and body composition) versus metabolic-inflammatory pathways (assessed through adipokines, systemic inflammatory markers, and fat distribution patterns) to OA pathogenesis; (2) Characterize effect modification by sex, age, and other demographic/clinical factors in the obesity-OA relationship using stratified and interaction analyses; (3) Systematically identify obesity-associated plasma protein signatures and their implicated biological pathways implicated in OA development through large-scale proteomic profiling; (4) Employ GWAS and MR frameworks to both determine the causal effect of obesity on OA risk and investigate proteomic mediators of this relationship through mediation MR-based mediation analyses. Public health impact!This study will predict OA risk in obesity, evaluate weight management benefits, and uncover obesity-OA mechanisms to guide targeted prevention and reduce disease burden.
