Synovial transcriptomic biomarkers predict structural severity in equine osteochondral fragment-induced experimental osteoarthritis.

Transcriptomic biomarkers outperform clinical and biochemical markers in predicting structural OA severity in horses.

This retrospective study investigated biomarkers of osteoarthritis (OA) severity in 104 young horses (2–5 years) undergoing experimental OA induction via surgical osteochondral fragment creation in the middle carpal joint, combined with high-speed treadmill exercise over 70 days. Researchers developed a Global Joint Score (GJS) integrating macroscopic and histopathologic data to quantify structural OA severity. Longitudinal clinical parameters—including subjective lameness scores, effusion, flexion responses, synovial fluid (SF) and serum glycosaminoglycan (GAG) concentrations, and SF prostaglandin E2 (PGE2)—were assessed every 14 days. Synovial membrane biopsies were collected on days 0 and 70 for mRNA sequencing. Statistical modeling revealed that standard clinical and biochemical markers (lameness examination, GAG, PGE2) were poor predictors of structural OA severity, likely due to inherent disease heterogeneity. Conversely, transcriptomic analysis identified 46 differentially expressed genes in SF cells and 8 in synovial tissue with high predictive value for GJS scores, alongside significant expression changes at study endpoint. These gene subsets represent candidate biomarkers and potential therapeutic targets implicated in early OA pathophysiology. The findings highlight the limitations of single clinical markers in disease monitoring and suggest that transcriptomic biomarkers offer superior sensitivity for detecting and predicting OA progression. This work advances understanding of molecular mechanisms underlying equine joint disease and provides a foundation for future diagnostic tool development and targeted therapeutic intervention strategies in equine OA management.

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