AB0156 NMR-BASED MUSCLE METABOLOMICS IN INFLAMMATORY MYOSITIS- UNDERSTANDING CHANGES IN SERUM AS A REFLECTION OF THE MUSCLE. (2nd June 2020) - Gupta, L.; Kumar, U.; Anuja, A.; Sharma, P.; Guleria, A.; Kumar, D.; Agarwal, V.
Abstract : Background: We have previously found promise in NMR as a tool to distinguish sera of active from inactive inflammatory myositis (IIM)1. To understand the changes previously found in sera and urine we studied muscle tissue of patients with myositis. Objectives: To identify differences in metabolome on inflamed muscle tissues of patients with active myositis from that of healthy controls and infectious polymyositis. Methods: Muscle (n=17) from patients classifiable as myositis by the ACR-EULAR criteria [34 years (23.5 - 50.5 IQR), M/F 1:3] were compared with healthy controls [n=11, age= 44 (35-50) years, M/F-1:1]. Two disease controls with infectious polymyositis were also compared. Findings were applied to muscle biopsy tissues of two patients with established myositis and superadded infections (HBV, Histoplasmosis) to assess discriminatory potential. Metabolic profiles were obtained at 800 MHZ NMR spectrometer and compared using multivariate partial least-squares discriminant analysis (PLS-DA). The discriminatory metabolites were identified based on variable importance in projection (VIP) statistics and further evaluated for statistical significance (p-value <0.05). Paired T tests, ANNOVA and correlation of individual metabolites were done after normalizing for formate. Results: Metabolomics profiles in IIM were distinct from healthy controls (Fig. 1 A). Of the various discriminatory metabolites (Fig. 1 B ), Succinate had the highest discriminatory potential (AUC 0.8, P=0.01) followed by citrate, glycine, glycerol, glucose, creatine and lactate. (Fig. 1 C ) Both glucose and creatine were decreased in IIM (Fig. 1 D, E ) and this was uniform across all types of IIM. However, glycine levels differed across different myositis subsets supporting the fact that they might differ in pathogenesis. (Fig. 1 E ) Amongst various serum biomarkers of muscle disease and damage, serum Aspartate Transaminase correlated with glutamate (r=0.6, p=0.01), and serum creatinine correlated negatively with glycerol (r-0.8, p=0.04), Biopsies of infectious polymyositis suggested difference in spectra from IIM (Fig. 2A ). Trends were observed towards lower succinate and higher citrate levels suggesting metabolomics could possibly be useful to differentiate the two. Muscle of both patients with IIM with superadded infectious polymyositis also exhibited low succinate and elevated citrate. Conclusion: Muscle metabolomics of active myositis is distinctive. Amino acids and creatine are lower in diseases muscle suggesting active breakdown and loss, in turn explaining previous findings of low levels in serum in active disease. Certain metabolite composition differ in different types of myositis supporting different pathogenesis. Infectious polymyositis might exhibit different metabolome from IIM with potential as a biomarker though this needs to be confirmed in larger numbers. Disclosures: Funded by APLAR research grant 2017 awarded to Dr Latika Gupta. References: [1]Gupta L, Kumar D, Gulerai A, Kumar U, Misra R. "NMR-Based Serum, Urine and Muscle Metabolomics in Inflammatory Myositis for Diagnosis and Activity Assessment: Serum Metabolomics Can Differentiate Active from Inactive Myositis" Oral presentation at the ACR, Atlanta 2019. Acknowledgments: MSA and metabolomics supported by APLAR research grant. Disclosure of Interests: None declared