PT - JOURNAL ARTICLE AU - S Ahmed AU - MK Rai AU - D Dubey AU - A Rawat AU - DP Misra AU - D Kumar AU - V Agarwal TI - SAT0375 Metabolomics of sera reveals potential biomarkers of skin fibrosis in systemic sclerosis that correlate with pro-fibrotic gene expression in skin biopsies AID - 10.1136/annrheumdis-2017-eular.3715 DP - 2017 Jun 01 TA - Annals of the Rheumatic Diseases PG - 913--913 VI - 76 IP - Suppl 2 4099 - http://ard.bmj.com/content/76/Suppl_2/913.1.short 4100 - http://ard.bmj.com/content/76/Suppl_2/913.1.full SO - Ann Rheum Dis2017 Jun 01; 76 AB - Background There is an unmet need for biomarkers in Systemic Sclerosis (SSc). Despite its shortcomings, the modified Rodnan skin score (mRSS) has remained the standard disease assessment tool for SSc. Expression of certain genes, cartilage oligomeric matrix protein (COMP), thrombospondin-1 (THS1), interferon-induced 44 (IFI44) and sialoadhesin (SIG1), and, more recently, Tenascin-C (TNSC), have been shown to correlate with skin fibrosis. However, assessment of the expression of these genes requires a skin biopsy. Hence, we used an open-ended approach to identify a serum-based biomarker of SSc.Objectives To identify small molecules in serum that correlate with mRSS and profibrotic genes that are upregulated in skin of SSc patientsMethods We obtained serum and skin biopsies from 25 consenting adult patients with SSc and serum from 25 age- and sex-similar controls. mRNA levels of five genes: COMP, THS1, IFI44, SIG1, and TNSC were estimated as fold-change relative to Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), a housekeeping gene. H1NMR (Nuclear Magnetic Resonance) based metabolomics studies were performed on the sera using standard protocols. Principal component analysis (PCoA) and Partial Least Squares Discriminant Analysis (PLSDA) were used to delineate metabolites that were different between patients and healthy controls. Then spearman correlations (ρ) of these metabolites with mRSS and the fold-expression of the five pro-fibrotic genes were estimated.Results H1NMR based metabolomics identified 126 peaks that were different between patients and controls. Out of these, the levels of glycine had the best correlation with pro-fibrotic gene expression (ρ=0.5, p<0.05 for IFI44; ρ=0.44, p<0.05 for TNSC). Choline inversely correlated with SIG1 (ρ=-0.41; p=0.05) while Glycerophosphocholine correlated with mRSS (ρ=0.50, p<0.05).Conclusions H1NMR based metabolomics identified glycine, choline and their metabolites as potential biomarkers for skin fibrosis in SSc. These findings require validation in a larger cohort.References Farina G, Lafyatis D, Lemaire R, Lafyatis R. A four-gene biomarker predicts skin disease in patients with diffuse cutaneous systemic sclerosis. Arthritis Rheum. 2010 Feb;62(2):580–8.Bhattacharyya S, Wang W, Morales-Nebreda L, Feng G, Wu M, Zhou X, Lafyatis R, Lee J, Hinchcliff M, Feghali-Bostwick C, Lakota K, Budinger GR, Raparia K, Tamaki Z, Varga J.Tenascin-C drives persistence of organ fibrosis. Nat Commun. 2016 Jun 3;7:11703.References Disclosure of Interest None declared