4.5 Article

Urinary and Plasma Metabolomics Identify the Distinct Metabolic Profile of Disease State in Chronic Mouse Model of Multiple Sclerosis

Journal

JOURNAL OF NEUROIMMUNE PHARMACOLOGY
Volume 14, Issue 2, Pages 241-250

Publisher

SPRINGER
DOI: 10.1007/s11481-018-9815-4

Keywords

Metabolomics; EAE; Multiple sclerosis; Metabolomics; Urine; Biomarkers; GC-MS/LC-MS; Metabolic pathways

Funding

  1. Henry Ford Health System [A20020]
  2. National Multiple Sclerosis Society [RG 4311A4/4]

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Identification of non-invasive biomarkers of disease progression in multiple sclerosis (MS) is critically needed for monitoring the disease progression and for effective therapeutic interventions. Urine is an attractive source for non-invasive biomarkers because it is easily obtained in the clinic. In search of a urine metabolite signature of progression in chronic experimental autoimmune encephalomyelitis (EAE), we profiled urine at the chronic stage of the disease (day 45 post immunization) by global untargeted metabolomics. Using a combination of high-throughput liquid-and-gas chromatography with mass spectrometry, we found 105 metabolites (P < 0.05) significantly altered at the chronic stage, indicating a robust alteration in the urine metabolite profile during disease. Assessment of altered metabolites against the Kyoto Encyclopedia of Genes and Genomes revealed distinct non-overlapping metabolic pathways and revealed phenylalanine-tyrosine and associated metabolism being the most impacted. Combined with previously performed plasma profiling, eight common metabolites were significantly altered in both of the biofluids. Metaboanalyst analysis of these common metabolites revealed that phenylalanine metabolism and Valine, leucine, and isoleucine biosynthetic pathways are central metabolic pathways in both bio-fluids and could be analyzed further, either for the discovery of therapeutics or biomarker development. Overall, our study suggests that urine and plasma metabolomics may contribute to the identification of a distinct metabolic fingerprint of EAE disease discriminating from the healthy control which may aid in the development of an objective non-invasive monitoring method for progressive autoimmune diseases like MS.

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