Objective:To identify differences in the metabolomic profile in the serum of patients with multiple sclerosis (MS) compared to controls and to identify biomarkers of disease severity.Methods:We studied 2 cohorts of patients with MS: a retrospective longitudinal cohort of 238 patients and 74 controls and a prospective cohort of 61 patients and 41 controls with serial serum samples. Patients were stratified into active or stable disease based on 2 years of prospective assessment accounting for presence of clinical relapses or changes in disability measured with the Expanded Disability Status Scale (EDSS). Metabolomic profiling (lipids and amino acids) was performed by ultra-high-performance liquid chromatography coupled to mass spectrometry in serum samples. Data analysis was performed using parametric methods, principal component analysis, and partial least square discriminant analysis for assessing the differences between cases and controls and for subgroups based on disease severity.Results:We identified metabolomics signatures with high accuracy for classifying patients vs controls as well as for classifying patients with medium to high disability (EDSS >3.0). Among them, sphingomyelin and lysophosphatidylethanolamine were the metabolites that showed a more robust pattern in the time series analysis for discriminating between patients and controls. Moreover, levels of hydrocortisone, glutamic acid, tryptophan, eicosapentaenoic acid, 13S-hydroxyoctadecadienoic acid, lysophosphatidylcholines, and lysophosphatidylethanolamines were associated with more severe disease (non-relapse-free or increase in EDSS).Conclusions:We identified metabolomic signatures composed of hormones, lipids, and amino acids associated with MS and with a more severe course.

IMPORTANCE Before using brain volume loss (BVL) as a marker of therapeutic response in multiple sclerosis (MS), certain biological and methodological issues must be clarified. OBJECTIVES To assess the dynamics of BVL as MS progresses and to evaluate the repeatability and exchangeability of BVL estimates with Jacobian Integration (JI) and Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) (specifically, the Structural Image Evaluation, Using Normalisation, of Atrophy-Cross-Sectional [SIENA-X] tool or FMRIB's Integrated Registration and Segmentation Tool [FIRST]). DESIGN, SETTING, AND PARTICIPANTS A cohort of patients who had either clinically isolated syndrome or MS was enrolled from February 2011 through October 2015. All underwent a series of annual magnetic resonance imaging (MRI) scans. Images from 2 cohorts of healthy volunteers were used to evaluate short-term repeatability of the MRI measurements (n = 34) and annual BVL (n = 20). Data analysis occurred from January to May 2017. MAIN OUTCOMES AND MEASURES The goodness of fit of different models to the dynamics of BVL throughout the MS disease course was assessed. The short-term test-retest error was used as a measure of JI and FSL repeatability. The correlations (R 2) of the changes quantified in the brain using JI and FSL, together with the accuracy of the annual BVL cutoffs to discriminate patients with MS from healthy volunteers, were used to measure compatibility of imaging methods. RESULTS A total of 140 patients with clinically isolated syndrome or MS were enrolled, including 95 women (67.9%); the group had a median (interquartile range) age of 40.7 (33.6-48.1) years. Patients underwent 4 MRI scans with a median (interquartile range) interscan period of 364 (351-379) days. The 34 healthy volunteers (of whom 18 [53%] were women; median [IQR] age, 33.5 [26.2-42.5] years) and 20 healthy volunteers (of whom 10 [50%] were women; median [IQR] age, 33.0 [28.7-39.2] years) underwent 2 MRI scans within a median (IQR) of 24.5 (0.0-74.5) days and 384.5 (366.3-407.8) days for the short-term and long-term MRI follow-up, respectively. The BVL rates were higher in the first 5 years after MS onset (R 2 = 0.65 for whole-brain volume change and R 2 = 0.52 for gray matter volume change) with a direct association with steroids (β = 0.280; P = .02) and an inverse association with age at MS onset, particularly in the first 5 years (β = 0.015; P = .047). The reproducibility of FSL (SIENA) and JI was similar for whole-brain volume loss, while JI gave more precise, less biased estimates for specific brain regions than FSL (SIENA-X and FIRST). The correlation between whole-brain volume loss using JI and FSL was high (R 2 = 0.92), but the same correlations were poor for specific brain regions. The area under curve of the whole-brain volume change to discriminate between patients with MS and healthy volunteers was similar, although the thresholds and accuracy index were distinct for JI and FSL. CONCLUSIONS AND RELEVANCE The proposed BVL threshold of...

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