Metabolomic profiles in relapsing–remitting and progressive multiple sclerosis compared to healthy controls: a five-year follow-up study

Introduction and objectives Multiple sclerosis (MS) is a disease of the central nervous system associated with immune dysfunction, demyelination, and neurodegeneration. The disease has heterogeneous clinical phenotypes such as relapsing–remitting MS (RRMS) and progressive multiple sclerosis (PMS), e...

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Published in:Metabolomics 2023-04, Vol.19 (5), p.44-44, Article 44
Main Authors: Shi, Tiange, Browne, Richard W., Tamaño-Blanco, Miriam, Jakimovski, Dejan, Weinstock-Guttman, Bianca, Zivadinov, Robert, Ramanathan, Murali, Blair, Rachael H.
Format: Article
Language:English
Subjects:
Biochemistry
Biomedical and Life Sciences
Biomedicine
Cell Biology
Central nervous system
Cohort Studies
Demyelination
Developmental Biology
Follow-Up Studies
Humans
Life Sciences
Liquid chromatography
Mass spectroscopy
Metabolites
Metabolomics
Molecular Medicine
Multiple Sclerosis
Multiple Sclerosis, Chronic Progressive
Neurodegeneration
Original Article
Phenotypes
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Summary:Introduction and objectives Multiple sclerosis (MS) is a disease of the central nervous system associated with immune dysfunction, demyelination, and neurodegeneration. The disease has heterogeneous clinical phenotypes such as relapsing–remitting MS (RRMS) and progressive multiple sclerosis (PMS), each with unique pathogenesis. Metabolomics research has shown promise in understanding the etiologies of MS disease. However, there is a paucity of clinical studies with follow-up metabolomics analyses. This 5-year follow-up (5YFU) cohort study aimed to investigate the metabolomics alterations over time between different courses of MS patients and healthy controls and provide insights into metabolic and physiological mechanisms of MS disease progression. Methods A cohort containing 108 MS patients (37 PMS and 71 RRMS) and 42 controls were followed up for a median of 5 years. Liquid chromatography–mass spectrometry (LC–MS) was applied for untargeted metabolomics profiling of serum samples of the cohort at both baseline and 5YFU. Univariate analyses with mixed-effect ANCOVA models, clustering, and pathway enrichment analyses were performed to identify patterns of metabolites and pathway changes across the time effects and patient groups. Results and conclusions Out of 592 identified metabolites, the PMS group exhibited the most changes, with 219 (37%) metabolites changed over time and 132 (22%) changed within the RRMS group (Bonferroni adjusted P 
ISSN:1573-3890
1573-3882
1573-3890
DOI:10.1007/s11306-023-02010-0