Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Potential role of Akkermansia massiliensis in multiple sclerosis protection by the FcRL3 gene.

Genes and immunity·2026
Same author

Preventing frailty in multiple sclerosis is a realistic goal-Commentary.

Multiple sclerosis (Houndmills, Basingstoke, England)·2026
Same author

Profiling the long-term risk of severe adverse events in a cohort of multiple sclerosis patients treated with different treatment sequences: Results from the Italian Multiple Sclerosis and Related Disorders Registry (I-MS&RD) (ProSA study).

Multiple sclerosis (Houndmills, Basingstoke, England)·2026
Same author

Predictive factors of response to anti-CGRP pathway drugs in people with multiple sclerosis.

The journal of headache and pain·2026
Same author

Quality of life domains revised by people with multiple sclerosis and healthcare professionals for adaptive measure development.

PloS one·2026
Same author

A predictive tool for early treatment escalation after initiation of moderate-efficacy therapy in pediatric-onset multiple sclerosis.

Multiple sclerosis (Houndmills, Basingstoke, England)·2026

Related Experiment Video

Updated: Feb 26, 2026

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

1.4K

Metabolomic analysis identifies altered metabolic pathways in Multiple Sclerosis.

Simone Poddighe1, Federica Murgia2, Lorena Lorefice3

  • 1Department of Biomedical Sciences, University of Cagliari, Italy; Unité de Chimie Environnementale et Interactions sur le Vivant, Université du Littoral Côte d'Opale, France.

The International Journal of Biochemistry & Cell Biology
|July 20, 2017
PubMed
Summary

Metabolomics analysis reveals distinct metabolic profiles in multiple sclerosis (MS) patients compared to healthy individuals. These findings highlight potential new biomarkers for MS diagnosis and monitoring, aiding in a better understanding of the disease.

Keywords:
Biomarker discoveryBiomarkersGas cromatography–mass spectrometryMetabolite profilingMetabolomicsMultiple sclerosis

More Related Videos

Sample Preparation for Metabolic Profiling using MALDI Mass Spectrometry Imaging
09:08

Sample Preparation for Metabolic Profiling using MALDI Mass Spectrometry Imaging

Published on: December 22, 2020

7.3K
A Strategy for Sensitive, Large Scale Quantitative Metabolomics
14:18

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

21.8K

Related Experiment Videos

Last Updated: Feb 26, 2026

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

1.4K
Sample Preparation for Metabolic Profiling using MALDI Mass Spectrometry Imaging
09:08

Sample Preparation for Metabolic Profiling using MALDI Mass Spectrometry Imaging

Published on: December 22, 2020

7.3K
A Strategy for Sensitive, Large Scale Quantitative Metabolomics
14:18

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

21.8K

Area of Science:

  • Biochemistry and Molecular Biology
  • Neuroscience
  • Clinical Chemistry

Background:

  • Multiple sclerosis (MS) is a chronic central nervous system disease with complex pathogenesis and challenging management.
  • Accurate diagnosis and monitoring of MS require novel biomarkers.
  • Metabolomics provides a snapshot of the molecular phenotype, offering potential insights into MS.

Purpose of the Study:

  • To characterize metabolomic profiles in plasma from MS patients.
  • To identify metabolic differences between MS patients and healthy controls (HC).
  • To explore the potential of metabolomics for discovering new MS biomarkers.

Main Methods:

  • Plasma samples from MS patients and HC were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS).
  • Multivariate statistical analysis, including Partial Least Squares Discriminant Analysis (PLS-DA), was employed.
  • Receiver Operating Characteristic (ROC) curve analysis was used to evaluate discriminant metabolite performance.

Main Results:

  • A significant metabolic difference was identified between MS patients and HC (PLS-DA model: R2X=0.223, R2Y=0.82, Q2=0.562, p<0.001).
  • Key discriminant metabolites included phosphate, fructose, myo-inositol, pyroglutamate, threonate, l-leucine, l-asparagine, l-ornithine, l-glutamine, and l-glutamate.
  • The ROC curve analysis showed strong model performance (AUC 0.84, p=0.01).

Conclusions:

  • Metabolomics is a valuable approach for understanding MS pathogenesis.
  • The study identified potential metabolic biomarkers for MS diagnosis and monitoring.
  • Pathway analysis suggests asparagine and citrulline biosynthesis are involved in MS, with potential links to oxidative stress.