Search

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 patients Methods 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. H 1 NMR (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 H 1 NMR 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 IFI44 ; ρ=0.44, p TNSC ). Choline inversely correlated with SIG1 (ρ=-0.41; p=0.05) while Glycerophosphocholine correlated with mRSS (ρ=0.50, p Conclusions H 1 NMR 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. Disclosure of Interest None declared

Background Takayasu arteritis (TA) is a chronic large vessel vasculitis of unknown etiopathogenesis. The serological and radiological parameters currently used to assess the disease activity are not highly specific and there is a pertinent need for a biomarker discovery. In our previous study [1], NMR based serum metabolomics had revealed distinctive metabolic signatures in patients with TA compared to age/sex matched healthy controls. In this study we sought to investigate whether these distinctive metabolites correlate with disease activity. Objectives To identify the discriminatory serum metabolic profiles and their correlation with disease activity. Methods Patients with TA fulfilling ACR criteria were assessed for disease activity by ITAS 2010, with a score of 4 or more, considered as active. The serum metabolic profiles of active and inactive TA patients were obtained at 800 MHZ NMR spectrometer and were compared using multivariate orthogonal partial least-squares discriminant analysis (OPLS-DA) to identify metabolites that changed in response to disease activity [based on PLS-DA VIP (variable importance on projection) score >2.0 and permutation test, p-value Results 88 patients were categorized into active (34) and inactive (54) groups. Median age in active and inactive groups was 25 years and 27 years respectively. Female to male ratio was 3.4:1 in the active group and 5:1 in the inactive group. Majority had class V disease. Mean duration of illness was 4.0±3.5 years in active TA and 6.5±5.5 years in inactive TA group. An exquisite separation in OPLS-DA score plot showed metabolic differences between active and inactive TA patients (Fig. 1A). The key metabolite entities identified with highest discriminatory potential (VIP score >2) were glucose, glutamine, glycine, N-acetyl glycoprotein (NAG), choline, and low/very-low density lipoproteins (LDL/VLDL). Of them glucose, glycine, and NAGs were elevated in the sera of active TA patients, whereas glutamine, choline and LDL levels were decreased in these patients. Receiver operating characteristic (ROC) curve analysis revealed NAG has the highest potential to discriminate active from inactive TA patients (area under the ROC curve was 0.75 (p-value Conclusions The study revealed discriminatory metabolites between active and inactive TA patients and evaluated the possibility of NAG as a clinical biomarker for activity judgment in this disease. However, more work needs to be done to validate the results in a large cohort of patients in a longitudinal manner. References Guleria A, Misra DP, Rawat A, Dubey D, Khetrapal CL, Bacon PA, Misra R, and Kumar D, NMR based serum metabolomics discriminates Takayasu Arteritis from Healthy Individuals: A proof of principle study” Journal of Proteome Research (2015), 14 (8), 3372–3381. Disclosure of Interest None declared