Plasma Lipidomic Profiling Using Mass Spectrometry for Multiple Sclerosis Diagnosis and Disease Activity...

Area of Science:

• Neuroimmunology
• Metabolomics
• Biochemistry

Background:

• Multiple Sclerosis (MS) diagnosis and monitoring present challenges.
• Plasma lipid profiles are increasingly recognized for their potential as biomarkers.

Purpose of the Study:

• To investigate plasma lipidomic signatures for MS diagnosis.
• To correlate lipid profiles with clinical course and disease activity in MS patients.

Main Methods:

• Quantitative shotgun lipidomics on plasma samples from 60 MS patients and 60 controls.
• Multivariate statistical analyses including PCA, oPLS-DA, and Random Forest.
• Class Composition Visualization (CCV) to assess lipid class alterations.

Main Results:

• Identified 670 lipids across 16 classes; significant differences observed in MS patients.
• Increased diacylglycerols (DAG), particularly DAG 16:0;0_18:1;0, showed high predictive ability for MS.
• Distinct alterations in phosphatidylethanolamines (PE) and ether-bound PEs (PE O-) were associated with relapsing-remitting MS (RRMS) and chronic progressive MS (CPMS), respectively.
• Reduced cholesteryl esters (CE) in CPMS and triglycerides (TAG) in RRMS were noted.

Conclusions:

• Distinct plasma lipidomic signatures are associated with MS diagnosis and clinical phenotypes.
• Lipid profiles offer insights into MS pathology and disease activity.
• These findings support the potential for personalized MS therapy based on lipidomic data.