Abstract

Carpal osteochondral fragmentation and subsequent post-traumatic osteoarthritis (PTOA) are leading causes of wastage in the equine athlete. Identification of synovial fluid biomarkers could contribute to the diagnosis and understanding of osteoarthritis (OA) pathophysiology. The aim of this study was to identify differentially expressed metabolic and glycosylation pathways in synovial fluid from healthy horses and horses with naturally occurring carpal OA. Cross-sectional, in vivo metabolomics and glycomics study. In cohort 1, carpal synovial fluid (n=12 horses; n=6 healthy, n=6 OA) was analysed using high-resolution liquid chromatography mass spectrometry (LC-MS). In cohort 2 (n=40 horses; n=20 healthy, n=20 OA), carpal synovial fluid was analysed using lectin microarrays and a lubricin sandwich ELISA. Metabolomic analysis identified >4900 LC-MS features of which 84 identifiable metabolites were differentially expressed (P<.05) between healthy and OA joints, including key pathways related to inflammation (histidine and tryptophan metabolism), oxidative stress (arginine biosynthesis) and collagen metabolism (lysine metabolism). Principle Component Analysis and Partial Least Squares Discriminant Analysis demonstrated separation between healthy and OA synovial fluid. Lectin microarrays identified distinct glycosylation patterns between healthy and OA synovial fluid, including increased Core 1/Core 3 O-glycosylation, increased α-2,3 sialylation and decreased α-1,2 fucosylation in OA. O-glycans predominated over N-glycans in all synovial fluid samples, and synovial fluid lubricin was increased in OA joints as compared to controls. The sample size in cohort 1 was limited, and there is inherent variation in severity and duration of joint injury in naturally occurring OA. However, LC-MS identified up to 5000 unique features. These data suggest new potential diagnostic and therapeutic targets for equine OA. Future targeted metabolomic and glycomic studies should be performed to verify these results. Lectin microarrays could be investigated as a potential screening tool for the diagnosis and therapeutic monitoring of equine OA.

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