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Circulating exosomes with unique lipid signature in relapsing remitting multiple sclerosis
Claudia Palazzo1, Ilaria Asci1, Silvia Russo1
1Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.
Frontiers in Cellular Neuroscience
|July 14, 2025
Summary
Researchers identified distinct lipid profiles in exosomes from multiple sclerosis (MS) patients, revealing lower phosphatidic acid and altered phosphatidylcholine to lysophosphatidylcholine ratios, suggesting membrane lipid changes in MS.
Area of Science:
- Extracellular vesicles research
- Neuroimmunology
- Lipidomics
Background:
- Exosomes mediate intercellular communication via transported biomolecules.
- Multiple sclerosis (MS) involves central nervous system damage.
- Serum exosomes are increasingly studied for disease biomarkers.
Purpose of the Study:
- To characterize the lipid profiles of serum-derived exosomes from relapsing-remitting MS (RR-MS) patients.
- To identify potential lipid biomarkers for RR-MS using direct mass spectrometry.
- To compare exosomal lipid composition between RR-MS patients and healthy subjects (HS).
Main Methods:
- Isolation and purification of exosomes from serum of RR-MS patients and HS.
- Direct lipid profiling of intact exosomes using matrix-assisted laser desorption ionization-time-of-flight/mass spectrometry (MALDI-TOF/MS).
- Statistical analysis of mass spectra to identify differential lipid markers.
Main Results:
- No significant difference in bis(monoacylglycero)phosphate (BMP) levels between RR-MS and HS exosomes.
- Significantly lower phosphatidic acid (PA) levels in RR-MS exosomes compared to HS.
- Enrichment of lysophosphatidylcholine (LPC) species and a lower phosphatidylcholine (PC) to LPC ratio in RR-MS exosomes.
Conclusions:
- Serum-derived exosomes exhibit a distinct lipid signature in RR-MS patients.
- Altered lipid homeostasis, indicated by reduced PA and PC/LPC ratio, may contribute to MS pathology.
- Direct MALDI-TOF/MS analysis is a rapid method for exosome lipid profiling and biomarker discovery.

