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Default Assessing the Metabolomic Profile of Multiple Sclerosis Patients Treated with Interferon Beta 1a by 1H-NMR Spectroscopy.

Assessing the Metabolomic Profile of Multiple Sclerosis Patients Treated with Interferon Beta 1a by 1H-NMR Spectroscopy.

Related Articles Assessing the Metabolomic Profile of Multiple Sclerosis Patients Treated with Interferon Beta 1a by 1H-NMR Spectroscopy.

Neurotherapeutics. 2019 07;16(3):797-807

Authors: Lorefice L, Murgia F, Fenu G, Frau J, Coghe G, Murru MR, Tranquilli S, Visconti A, Marrosu MG, Atzori L, Cocco E

Abstract
Metabolomic research has emerged as a promising approach to identify potential biomarkers in multiple sclerosis (MS). The aim of the present study was to determine the effect of interferon beta (IFN ß) on the metabolome of MS patients to explore possible biomarkers of disease activity and therapeutic response. Twenty-one MS patients starting IFN ß therapy (Rebif® 44*?g; s.c. 3 times per week) were enrolled. Blood samples were obtained at baseline and after 6, 12, and 24*months of IFN ß treatment and were analyzed by high-resolution nuclear magnetic resonance spectroscopy. Changes in metabolites were analyzed. After IFN ß exposure,*patients* were divided into responders and nonresponders according to the "no evidence of disease activity" (NEDA-3) definition (absence of relapses, disability progression, and magnetic resonance imaging activity), and samples obtained at baseline were analyzed to evaluate the presence of metabolic differences predictive of IFN ß response. The results of the investigation demonstrated differential distribution of baseline samples compared to those obtained during IFN ß exposure, particularly after 24*months of treatment (R2X = 0.812, R2Y = 0.797, Q2 = 0.613, p = 0.003). In addition, differences in the baseline metabolome between responder and nonresponder patients with respect to lactate, acetone, 3-OH-butyrate, tryptophan, citrate, lysine, and glucose levels were found (R2X = 0.442, R2Y = 0.768, Q2 = 0.532, p = 0.01). In conclusion, a metabolomic approach appears to be a promising, noninvasive tool that could potentially contribute to predicting the efficacy of MS therapies.


PMID: 30820880 [PubMed - indexed for MEDLINE]



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