ACR Meeting Abstracts

ACR Meeting Abstracts

Abstract Number: 1326

Discriminative Metabolite Profiling Of Synovial Fluid In Rheumatoid Arthritis Compared To Osteoarthritis

Jiwon Hwang1, Joong Kyong Ahn2, Jaejoon Lee1, Inyoung Kim1, Seulkee Lee1, Chan Hong Jeon3, Eun-Mi Koh1 and Hoon-Suk Cha1, 1Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea, 2Department of Medicine, Kangbuk Samsung hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea, 3Internal Medicine, Soonchunhyang University College of Medicine, Bucheon, South Korea

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords:

Session Information

Title: Rheumatoid Arthritis - Clinical Aspects II: Predictors of Disease Course in Rheumatoid Arthritis - Treatment Approaches

Session Type: Abstract Submissions (ACR)

Background/Purpose: Metabolomics is the study of unique chemical imprints that represent specific cellular processes in a cell, tissue, organ or organism. Synovial fluid in pathologic conditions reflects the diseased process and its distinctive metabolite profiles could facilitate the diagnostic ability and the understanding of disease state. The aim of this study is to investigate the metabolites of synovial fluid in patients with rheumatoid arthritis (RA) and osteoarthritis (OA) and to identify characteristic metabolites to differentiate two diseases. Methods: Synovial fluid samples were obtained from patients with RA (n = 18, 17 females, mean age 50.3 ± 13.9 yr, disease duration 7.9 ± 6.8 yr) and OA (n = 11, 10 females, mean age 60.9 ± 8.4 yr, disease duration 2.8 ± 4.7 yr). The extracted metabolites from synovial fluid were analyzed by gas chromatography/time-of-flight mass spectrometry (GC/TOF MS). The identified metabolites from synovial fluid extracts of RA and OA were then subjected to multivariate statistical analysis by orthogonal partial least squares discriminant analysis (OPLS-DA): R2 indicates the fitting ability of total variation and Q2 designates the validity of discrimination. Both have range from 0 to 1, where the higher R2 or Q2 connotes a model with the higher predictive and discriminative value. Values of variable importance for projection (VIP) greater than 1 from OPLS-DA were used to identify potential biomarkers and the significance was defined by Welch’s test with level of p < 0.01. Results: Sixty-three metabolites were identified; 20 amino acids, 14 fatty acids, 10 sugars, 7 organic acids, 5 amines and 7 others. The OPLS-DA demonstrated a distinctive metabolite profile of synovial fluid between RA and OA (Figure 1), with the variation value (R2) of 0.88 and the predictive capability value (Q2) of 0.72. Twenty four metabolites were obtained by VIP values of greater than 1 and 17 of them were selected as specific biomarkers by Welch’s t-test. Of 17 metabolites, 6 were up-regulated in RA (maltose, lignoceric acid, uracil, mannitol, pyrophosphate and phosphoric acid) and 11 in OA (lysine, tyrosine, valine, glyceric acid, alanine, asparagines, hydroxylamine, tryptophan, glycerol, glutamine and citrulline). Conclusion: Our results demonstrated that metabolite profiling of synovial fluid clearly separates RA from OA. This study suggests that metabolomics could be a useful diagnostic tool by identifying discriminative biomarkers.

Disclosure:

J. Hwang,
None;

J. K. Ahn,
None;

J. Lee,
None;

I. Kim,
None;

S. Lee,
None;

C. H. Jeon,
None;

E. M. Koh,
None;

H. S. Cha,
None.

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