Global metabolomic profiling of human synovial fluid for rheumatoid arthritis biomarkers.

OBJECTIVES: The objective of this study was to analyse the metabolomic profiles of rheumatoid arthritis synovial fluid to test the use of global metabolomics by liquid chromatography-mass spectrometry for clinical analysis of synovial fluid. METHODS: Metabolites were extracted from rheumatoid arthritis (n=3) and healthy (n=5) synovial fluid samples using 50:50 water: acetonitrile. Metabolite extracts were analysed in positive mode by normal phase liquid chromatography-mass spectrometry for global metabolomics. Statistical analyses included hierarchical clustering analysis, principal component analysis, Student's t-test, and volcano plot analysis. Metabolites were matched with known metabolite identities using METLIN and enriched for relevant pathways using IMPaLA. RESULTS: 1018 metabolites were detected by LC-MS analysis in synovial fluid from rheumatoid arthritis and healthy patients, with 162 metabolites identified as significantly different between diseased and control. Pathways upregulated with disease included ibuprofen metabolism, glucocorticoid and mineralocorticoid metabolism, alpha-linolenic acid metabolism, and steroid hormone biosynthesis. Pathways downregulated with disease included purine and pyrimidine metabolism, biological oxidations, arginine and proline metabolism, the citrulline-nitric oxide cycle, and glutathione metabolism. Receiver operating characteristic analysis identified 30 metabolites as putative rheumatoid arthritis biomarkers including various phospholipids, diol and its derivatives, arsonoacetate, oleananoic acid acetate, docosahexaenoic acid methyl ester, and linolenic acid and eicosatrienoic acid derivatives. CONCLUSIONS: This study supports the use of global metabolomic profiling by liquid chromatography-mass spectrometry for synovial fluid analysis to provide insight into the aetiology of disease.

Application of global metabolomic profiling of synovial fluid for osteoarthritis biomarkers.

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.

Mechanobiological implications of articular cartilage crystals.

PURPOSE OF REVIEW: Calcium crystals exist in both pathological and normal articular cartilage. The prevalence of these crystals dramatically increases with age, and crystals are typically found in osteoarthritic cartilage and synovial fluid. Relatively few studies have examined the effects of crystals on cartilage biomechanics or chondrocyte mechanotransduction. The purpose of this review is to describe how crystals could influence cartilage biomechanics and mechanotransduction in osteoarthritis. RECENT FINDINGS: Crystals are found in both loaded and unloaded regions of articular cartilage. Exogenous crystals, in combination with joint motion, result in substantial joint inflammation. Articular cartilage vesicles promote crystal formation, and these vesicles are found near the periphery of chondrocytes. Crystallographic studies report monoclinic symmetry for synthetic crystals, suggesting that crystals will have a large stiffness compared with the cartilage extracellular matrix, the pericellular matrix, or the chondrocyte. This stiffness imbalance may cause crystal-induced dysregulation of chondrocyte mechanotransduction promoting both aging and osteoarthritis chondrocyte phenotypes. SUMMARY: Because of their high stiffness compared with cartilage matrix, crystals likely alter chondrocyte mechanotransduction, and high concentrations of crystals within cartilage may alter macroscale biomechanics. Future studies should focus on understanding the mechanical properties of joint crystals and developing methods to understand how crystals affect chondrocyte mechanotransduction.