Disentangling osteoarthritis-specific genetic effects from obesity to identify novel therapeutic targets

作者：Chen‐Yang Su, Masashi Hasebe, Dandan Tan, Bangli Cao, Kevin Y. H. Liang, Takayoshi Sasako, Vincent Mooser, Wenmin Zhang, Sirui Zhou, Satoshi Yoshiji, Tianyuan Lu, Guillaume Butler‐Laporte · 发表于：medRxiv · 年份：2025 · DOI：10.1101/2025.09.23.25336398 · 被引用次数：3 · 研究领域：Cytokine Signaling Pathways and Interactions、Computational Drug Discovery Methods、Inflammatory mediators and NSAID effects

Abstract Osteoarthritis (OA) significantly impairs mobility and quality of life for hundreds of millions of individuals. Given the limited non-surgical treatment options for OA, genetics may help identify new strategies for treatment. However, many genetic associations with OA arise from its genetic correlation with obesity (measured by body mass index [BMI]), which makes it difficult to find OA-specific genetic associations. This study used a genome-wide association study (GWAS)-by-subtraction approach to separate genetic effects specific to OA from those shared with BMI, using GWAS of 12 OA traits from the Genetics of Osteoarthritis Consortium. Subsequent proteome-wide Mendelian randomization and colocalization analyses across four large proteomics cohorts identified 27 candidate causal proteins influencing OA via pathways not fully mediated by BMI. Among these, extracellular matrix and bone remodeling mediators such as COL6A2, SMAD3, SPP1, and TNFSF11 (RANKL) were highlighted as promising therapeutic targets. Colocalization with expression quantitative trait loci in osteoclasts and other relevant tissues provided additional biological support. Further, actionability assessments identified several proteins already targeted by existing therapies, such as the approved TNFSF11 (RANKL) inhibitor, denosumab, suggesting repurposing opportunities to modulate subchondral bone turnover in OA. This integrative proteogenomic framework clarifies biological mechanisms of OA beyond BMI-r...