Objective biomarkers for clinical relapse in multiple sclerosis: a metabolomics approach. Issue 4 (12th October 2021)

• Record Type: Journal Article
• Authors: Yeo, Tianrong; Probert, Fay; Sealey, Megan; Saldana, Luisa; Geraldes, Ruth; Höckner, Sebastian; Schiffer, Eric; Claridge, Timothy D W; Leppert, David; DeLuca, Gabriele; Kuhle, Jens; Palace, Jacqueline; Anthony, Daniel C
• Is Part Of: Brain communications. Volume 3:Issue 4(2021)
• Publication Date: 2021-10-12
• Subjects: multiple sclerosis -- relapse -- metabolomics -- metabolites -- biomarker; 616
• DOI: 10.1093/braincomms/fcab240
• Languages: English
• ISSNs: 2632-1297

Abstract

Abstract: Accurate determination of relapses in multiple sclerosis is important for diagnosis, classification of clinical course and therapeutic decision making. The identification of biofluid markers for multiple sclerosis relapses would add to our current diagnostic armamentarium and increase our understanding of the biology underlying the clinical expression of inflammation in multiple sclerosis. However, there is presently no biofluid marker capable of objectively determining multiple sclerosis relapses although some, in particular neurofilament-light chain, have shown promise. In this study, we sought to determine if metabolic perturbations are present during multiple sclerosis relapses, and, if so, identify candidate metabolite biomarkers and evaluate their discriminatory abilities at both group and individual levels, in comparison with neurofilament-light chain. High-resolution global and targeted 1 H nuclear magnetic resonance metabolomics as well as neurofilament-light chain measurements were performed on the serum in four groups of relapsing-remitting multiple sclerosis patients, stratified by time since relapse onset: (i) in relapse (R); (ii) last relapse (LR) ≥ 1 month (M) to < 6 M ago; (iii) LR ≥ 6 M to < 24 M ago; and (iv) LR ≥ 24 M ago. Two hundred and one relapsing-remitting multiple sclerosis patients were recruited: R ( n = 38), LR 1–6 M ( n = 28), LR 6–24 M ( n = 34), LR ≥ 24 M ( n = 101). Using supervised multivariate analysis, we found that the global metabolomics profile of R patients was significantly perturbed compared to LR ≥ 24 M patients. Identified discriminatory metabolites were then quantified using targeted metabolomics. Lysine and asparagine (higher in R), as well as, isoleucine and leucine (lower in R), were shortlisted as potential metabolite biomarkers. ANOVA of these metabolites revealed significant differences across the four patient groups, with a clear trend with time since relapse onset. Multivariable receiver operating characteristics analysis of these four metabolites in discriminating R versus LR ≥ 24 M showed an area under the curve of 0.758, while the area under the curve for serum neurofilament-light chain was 0.575. Within individual patients with paired relapse–remission samples, all four metabolites were significantly different in relapse versus remission, with the direction of change consistent with that observed at group level, while neurofilament-light chain was not discriminatory. The perturbations in the identified metabolites point towards energy deficiency and immune activation in multiple sclerosis relapses, and the measurement of these metabolites, either singly or in combination, are useful as biomarkers to differentiate relapse from remission at both group and individual levels. Abstract : Yeo et al. used a metabolomics approach to identify serum metabolite biomarkers for relapses in multiple sclerosis, at both group and individual levels. Four identified metabolites, used individually or in combination, significantly outperformed serum neurofilament-light chain for differentiating relapse from non-relapse. Graphical Abstract: