Metabolic discrimination of synovial fluid between rheumatoid arthritis and osteoarthritis using gas chromatography/time-of-flight mass spectrometry

Metabolomics - 2022
Sooah Kim1, Jiwon Hwang2, Jungyeon Kim3, Sun-Hee Lee3, Yu Eun Cheong3, Seulkee Lee4, Kyoung Heon Kim3,5, Hoon-Suk Cha4
1Department of Environment Science & Biotechnology, Jeonju University, Jeonju, Republic of Korea
2Division of Rheumatology, Department of Internal Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Republic of Korea
3Department of Biotechnology, Graduate School, Korea University, Seoul, Republic of Korea
4Division of Rheumatology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
5Department of Food Bioscience and Technology, College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea

Tóm tắt

Rheumatoid arthritis (RA) and osteoarthritis (OA) are clinicopathologically different. We aimed to assess the feasibility of metabolomics in differentiating the metabolite profiles of synovial fluid between RA and OA using gas chromatography/time-of-flight mass spectrometry. We first compared the global metabolomic changes in the synovial fluid of 19 patients with RA and OA. Partial least squares-discriminant, hierarchical clustering, and univariate analyses were performed to distinguish metabolites of RA and OA. These findings were then validated using synovial fluid samples from another set of 15 patients with RA and OA. We identified 121 metabolites in the synovial fluid of the first 19 samples. The score plot of PLS-DA showed a clear separation between RA and OA. Twenty-eight crucial metabolites, including hypoxanthine, xanthine, adenosine, citrulline, histidine, and tryptophan, were identified to be capable of distinguishing RA metabolism from that of OA; these were found to be associated with purine and amino acid metabolism. Our results demonstrated that metabolite profiling of synovial fluid could clearly discriminate between RA and OA, suggesting that metabolomics may be a feasible tool to assist in the diagnosis and advance the comprehension of pathological processes for diseases.

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