Identification of distinct metabolic fingerprint of EAE disease discriminating from the healthy control using urine and plasma metabolomics
Cerghet M, Poisson L, Singh J, Datta I, Suhail H, Rattan R, and Giri S. Identification of distinct metabolic fingerprint of EAE disease discriminating from the healthy control using urine and plasma metabolomics. Multiple Sclerosis Journal 2019; 25(Suppl 1):24-25.
Mult Scler J
Background: 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. Objectives: 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. Methods: Using ultra-performance liquid chromatography linked to gas chromatography and tandem mass spectrometry (Metabolon, Durham, NC), we measured urine and plasma metabolites from control complete Freund's adjuvant (CFA)/PT without peptide named as CFA/PT control and EAE, immunized with MOG35-55 peptide at the day of 45 post immunization. Results: 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. Conclusion: 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.