title: Global metabolite profiling of synovial fluid for the specific diagnosis of rheumatoid arthritis from other inflammatory arthritis.
abstract: Currently, reliable biomarkers that can be used to distinguish rheumatoid arthritis (RA) from other inflammatory diseases are unavailable. To find possible distinctive metabolic patterns and biomarker candidates for RA, we performed global metabolite profiling of synovial fluid samples. Synovial fluid samples from 38 patients with RA, ankylosing spondylitis, Behçet's disease, and gout were analyzed by gas chromatography/time-of-flight mass spectrometry (GC/TOF MS). Orthogonal partial least-squares discriminant and hierarchical clustering analyses were performed for the discrimination of RA and non-RA groups. Variable importance for projection values were determined, and the Wilcoxon-Mann-Whitney test and the breakdown and one-way analysis of variance were conducted to identify potential biomarkers for RA. A total of 105 metabolites were identified from synovial fluid samples. The score plot of orthogonal partial least squares discriminant analysis showed significant discrimination between the RA and non-RA groups. The 20 metabolites, including citrulline, succinate, glutamine, octadecanol, isopalmitic acid, and glycerol, were identified as potential biomarkers for RA. These metabolites were found to be associated with the urea and TCA cycles as well as fatty acid and amino acid metabolism. The metabolomic analysis results demonstrated that global metabolite profiling by GC/TOF MS might be a useful tool for the effective diagnosis and further understanding of RA.
authors.affiliation: Department of Biotechnology, Korea University Graduate School, Seoul, Republic of Korea.
authors.forename: Sooah
authors.initials: S
authors.lastname: Kim
authors.affiliation: Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Jiwon
authors.initials: J
authors.lastname: Hwang
authors.affiliation: Department of Biotechnology, Korea University Graduate School, Seoul, Republic of Korea.
authors.forename: Jinhua
authors.initials: J
authors.lastname: Xuan
authors.affiliation: Department of Biotechnology, Korea University Graduate School, Seoul, Republic of Korea.
authors.forename: Young Hoon
authors.initials: YH
authors.lastname: Jung
authors.affiliation: Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
authors.forename: Hoon-Suk
authors.initials: HS
authors.lastname: Cha
authors.affiliation: Department of Biotechnology, Korea University Graduate School, Seoul, Republic of Korea.
authors.forename: Kyoung Heon
authors.initials: KH
authors.lastname: Kim
mesh_terms: D000328:Adult; D019540:Area Under Curve; D001172:Arthritis, Rheumatoid / Q000175:diagnosis* / Q000378:metabolism*; D015415:Biomarkers / Q000378:metabolism; D016022:Case-Control Studies; D016000:Cluster Analysis; D003937:Diagnosis, Differential; D016002:Discriminant Analysis; D005260:Female; D006801:Humans; D007249:Inflammation / Q000175:diagnosis* / Q000378:metabolism*; D016018:Least-Squares Analysis; D008297:Male; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D011237:Predictive Value of Tests; D012372:ROC Curve; D013582:Synovial Fluid / Q000378:metabolism*
chemical_list: D015415:Biomarkers