P055 Genetically informed search for potential osteoarthritis drug targets across the proteome

Abstract Background/Aims Osteoarthritis (OA) is the most common form of arthritis and a major cause of disability. Current treatments are symptomatic, and no drugs prevent its onset or progression. Drug development has been challenging, with most trials unsuccessful. As most drug targets are proteins, large-scale proteomic studies can identify candidate targets and pathways, but observational associations may not reflect causality. Mendelian randomization (MR) using protein quantitative trait loci (pQTLs) improves causal inference, though MR alone has limitations. To address this, we combined differential protein association analysis (DPE) and MR analyses to identify and prioritise therapeutic targets for OA. Methods MR was conducted using cis-pQTLs from three European plasma proteomic datasets (UKB-PPP, deCODE, Fenland) and OA GWAS data source from the Genetics of Osteoarthritis (GO) Consortium 2.0 (11 OA types). DPE analysis was performed across 2,920 proteins in 44,789 UK Biobank participants. Proteins identified through both approaches were assessed for druggability, interactions, pathway involvement, and potential drug repurposing using over-representation analysis. Results A total of 6,137 cis-pQTLs were included in MR analysis. Across datasets, 305 proteins showed MR evidence of association with OA after multiple tests correction, of which 81 had colocalisation support. DPE analysis identified 605 unique proteins, with 5 overlapping between MR and DPE results when OA type was matched. Of the 81 MR-significant proteins, 51 were druggable, including 17 with Tier 1 evidence (Table 1), representing potential disease-modifying OA drug (DMOAD) targets. Fourteen proteins were central in the PPI network, with MAPK3 acting as a key connector. Gene ontology (GO) over-representation analysis highlighted positive regulation of ERK1/ERK2 cascade, collagen-containing extracellular matrix, and protein tyrosine kinase activity. In WikiPathways, the most enriched pathways were Osteoarthritic Chondrocyte Hypertrophy, Focal Adhesion, and PI3K-Akt-mTOR Signaling. Drug enrichment (DSigDB) identified NVP-TAE684 and HG-9-91-01 as top hits. Conclusion This large-scale study integrates observational and genetic evidence to identify and refine potential DMOAD targets, reinforcing known findings and revealing novel, cross-validated proteins linked to OA pathogenesis. Several pathways converging on extracellular matrix (ECM) remodelling were highlighted, suggesting that future studies should focus on these pathways and their associated proteins as priorities for DMOAD development. Disclosure W. Liu: Grants/research support; WL is supported by the Guangzhou Elite Project (project no. JY202314). B. Zuckerman: None. A. Schuermans: None. G. Orozco: Grants/research support; Centre of Excellence in Genetics and Genomics Versus Arthritis grant number 21754. M. Honigberg: Grants/research support; American Heart Association (25SFRNCCKMS1443062, 25SFRNPCKMS1463898, 24RGRSG1275749), U.S. NHLBI (R01HL173028, R01HL148565). Other; M.C.H. reports site principal investigator work for Novartis and research support from Genentech. J. Bowes: None. T. O’Neill: None. S.S. Zhao: Grants/research support; The University of Manchester Dean’s Prize, Versus Arthritis Career Development Fellowship (grant no. 23258).