AB0173 Metabolomics in Primary SjÖgren's Syndrome: Data from the Assess Cohort. (9th June 2015)

• Record Type: Journal Article
• Authors: Gottenberg, J.E.; Moussalieh, F.; Seror, R.; Ravaud, P.; Benessiano, J.; Dieude, P.; Dernis, E.; Devauchelle-Pensec, V.; Dubost, J.J.; Fauchais, A.L.; Goeb, V.; Hachulla, E.; Morel, J.; Hatron, P.Y.; Larroche, C.; Le Guern, V.; Morel, J.; Perdriger, A.; Puéchal, X.; Rist, S.; Saraux, A.; Sene, D.; Sibilia, J.; Vittecoq, O.; Ravaud, P.; Elbayed, K.; Mariette, X.; Namer, I.
• Is Part Of: Annals of the rheumatic diseases. Volume 74(2015)Supplement 2
• Page Start: 948
• Page End: 948
• Publication Date: 2015-06-09
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2015-eular.3978
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: High throughput study of metabolic pathways might help identify new biomarkers and therapeutic targets in autoimmune diseases. Primary Sjögren's syndrome (pSS) currently lacks prognostic biomarkers and efficacious and specific treatments. We therefore assessed serum levels of 35 metabolites in pSS using high-resolution magic-angle spinning (HRMAS) proton magnetic resonance spectroscopy. Methods: The blood samples of 194 patients with pSS enrolled in the prospective multicenter ASSESS cohort and 41 blood donors were analysed in this study. After cryopreservation at -80°C, the samples were studied with HRMAS proton magnetic resonance spectroscopy (1H-MRS). Spectra were recorded on a Bruker Avance III 500 spectrometer operating at a proton frequency of 500 MHz. All the 1D NMR spectra were acquired during 76 min. Supervised clustering was performed on the spectral region between 0.5 and 4.7 ppm using partial least square discriminant analysis (PLS-DA). Results: Supervised clustering of the 194 samples allowed to discriminate all patients with pSS from healthy controls (R 2 Y=0.88 and Q 2 =0.86 (figure 1)). Interestingly, 4 serum metabolites were significantly increased in pSS compared to healthy controls: threonine, lactate, glutamine and acetate. 6 metabolites were significantly decreased in pSS compared to healthy controls: myo-inositol, creatine, lysine, aspartate, glutamate and alanine Conclusions: This first high-throughput analysis of metabolic pathways disclosed a specific metabolomic signature of pSS allowing discriminating all patients with pSS from controls. This new and very potent means of metabolic analysis may help to increase our knowledge on the pathogenesis of pSS, identify biomarkers, and new therapeutic targets. Disclosure of Interest: None declared