Osteoarthritis affects over 250 million individuals worldwide. Currently, there are no options for early diagnosis of osteoarthritis, demonstrating the need for biomarker discovery. To find biomarkers of osteoarthritis in human synovial fluid, we used high performance liquid-chromatography mass spectrometry for global metabolomic profiling. Metabolites were extracted from human osteoarthritic (n = 5), rheumatoid arthritic (n = 3), and healthy (n = 5) synovial fluid, and a total of 1233 metabolites were detected. Principal components analysis clearly distinguished the metabolomic profiles of diseased from healthy synovial fluid. Synovial fluid from rheumatoid arthritis patients contained expected metabolites consistent with the inflammatory nature of the disease. Similarly, unsupervised clustering analysis found that each disease state was associated with distinct metabolomic profiles and clusters of co-regulated metabolites. For osteoarthritis, co-regulated metabolites that were upregulated compared to healthy synovial fluid mapped to known disease processes including chondroitin sulfate degradation, arginine and proline metabolism, and nitric oxide metabolism. We utilized receiver operating characteristic analysis to determine the diagnostic value of each metabolite and identified 35 metabolites as potential biomarkers of osteoarthritis, with an area under the receiver operating characteristic curve >0.9. These metabolites included phosphatidylcholine, lysophosphatidylcholine, ceramides, myristate derivatives, and carnitine derivatives. This pilot study provides strong justification for a larger cohort-based study of human osteoarthritic synovial fluid using global metabolomics. The significance of these data is the demonstration that metabolomic profiling of synovial fluid can identify relevant biomarkers of joint disease.

Objective: Osteoarthritis (OA) is a multifactorial disease with etiological heterogeneity. The objective of this study was to classify OA subgroups by generating metabolomic phenotypes from human synovial fluid. Design: Post mortem synovial fluids (n ¼ 75) were analyzed by high performance-liquid chromatography mass spectrometry (LC-MS) to measure changes in the global metabolome. Comparisons of healthy (grade 0), early OA (grades I-II), and late OA (grades III-IV) donor populations were considered to reveal phenotypes throughout disease progression. Results: Global metabolomic profiles in synovial fluid were distinct between healthy, early OA, and late OA donors. Pathways differentially activated among these groups included structural deterioration, glycerophospholipid metabolism, inflammation, central energy metabolism, oxidative stress, and vitamin metabolism. Within disease states (early and late OA), subgroups of donors revealed distinct phenotypes. Synovial fluid metabolomic phenotypes exhibited increased inflammation (early and late OA), oxidative stress (late OA), or structural deterioration (early and late OA) in the synovial fluid. Conclusion: These results revealed distinct metabolic phenotypes in human synovial fluid, provide insight into pathogenesis, represent novel biomarkers, and can move toward developing personalized interventions for subgroups of OA patients.

Objective: Although joint injury itself damages joint tissues, a substantial amount of secondary damage is mediated by the cellular responses to the injury. Cellular responses include the production and activation of proteases (MMPs, ADAMTSs, Cathepsins), and the production of inflammatory cytokines. The trajectory of cellular responses is driven by the transcriptional activation of early response genes, which requires Cdk9-dependent RNA Polymerase II phosphorylation. Our objective was to determine whether inhibition of cdk9-dependent early response gene activation affects changes in the joint metabolome. Design: To model post-traumatic osteoarthritis, we subjected mice to non-invasive Anterior Cruciate Ligament (ACL)-rupture joint injury. Following injury, mice were treated with flavopiridol e a potent and selective inhibitor of Cdk9 kinase activity e to inhibit Cdk9-dependent transcriptional activation, or vehicle control. Global joint metabolomics were analyzed 1 h after injury. Results: We found that injury induced metabolomic changes, including increases in Vitamin D3 metabolism, anandamide, and others. Inhibition of primary response gene activation immediately after injury largely prevented the global changes in the metabolomics profiles. Cluster analysis of joint metabolomes identified groups of injury-induced and drug-responsive metabolites. Conclusions: Metabolomic profiling provides an instantaneous snapshot of biochemical activity representing cellular responses. We identified two sets of metabolites that change acutely after joint injury: those that require transcription of primary response genes, and those that do not. These data demonstrate the potential for inhibition of early response genes to alter the trajectory of cell-mediated degenerative changes following joint injury, which may offer novel targets for cell-mediated secondary joint damage.

Objective: Osteoarthritis (OA) is a multifactorial disease with etiological heterogeneity. The objective of this study was to classify OA subgroups by generating metabolic phenotypes of OA from human synovial fluid.Design: Post mortem synovial fluids (n=75) were analyzed by high performance-liquid chromatography mass spectrometry (HPLC-MS) to measure changes in the global metabolome. Comparisons of healthy (grade 0), early OA (grades I-II), and late OA (grades III-IV) donor populations were considered to reveal phenotypes throughout disease progression.Results: Global metabolomic profiles in synovial fluid were distinct between healthy, early OA, and late OA donors. Pathways differentially activated among these groups included structural deterioration, glycerophospholipid metabolism, inflammation, central energy metabolism, oxidative stress, and vitamin metabolism. Within disease states (early and late OA), subgroups of donors revealed distinct phenotypes. Phenotypes of OA exhibited increased inflammation (early and late OA), oxidative stress (late OA), or structural deterioration (early and late OA) in the synovial fluid.Conclusion: These results revealed distinct metabolic phenotypes of OA in human synovial fluid, provide insight into pathogenesis, represent novel biomarkers and assist in developing personalized interventions for subgroups of OA patients.