Toward a Combination of Biomarkers for Molecular Characterization of Multiple Sclerosis

Int J Mol Sci. 2022 Nov 13;23(22):14000. doi: 10.3390/ijms232214000.

Abstract

Multiple sclerosis (MS) is an autoimmune disease affecting the central nervous system associated with chronic inflammation, demyelination, and axonal damage. MS is a highly heterogeneous disease that leads to discrepancies regarding the clinical appearance, progression, and therapy response of patients. Therefore, there is a strong unmet need for clinically relevant biomarkers capable of recapitulating the features of the disease. Experimental autoimmune encephalomyelitis (EAE) is a valuable model for studying the pathophysiology of MS as it recapitulates the main hallmarks of the disease: inflammation, blood-brain barrier (BBB) disruption, gliosis, myelin damage, and repair mechanisms. In this study, we used the EAE-PLP animal model and established a molecular RNA signature for each phase of the disease (onset, peak, remission). We compared variances of expression of known biomarkers by RT-qPCR in the brain and spinal cord of sham and EAE animals monitoring each of the five hallmarks of the disease. Using magnetic cell isolation technology, we isolated microglia and oligodendrocytes of mice of each category, and we compared the RNA expression variations. We identify genes deregulated during a restricted time frame, and we provide insight into the timing and interrelationships of pathological disease processes at the organ and cell levels.

Keywords: RNA; biomarkers; experimental autoimmune encephalomyelitis; multiple sclerosis.

MeSH terms

  • Animals
  • Biomarkers
  • Encephalomyelitis, Autoimmune, Experimental* / metabolism
  • Inflammation
  • Mice
  • Multiple Sclerosis* / metabolism
  • RNA

Substances

  • Biomarkers
  • RNA

Grants and funding

This work of the Strasbourg drug discovery and development Institute (IMS) is part of the Interdisciplinary Thematic Institute (ITI) 2021-2028 program of the University of Strasbourg, CNRS and Inserm, was supported by IdEx Unistra (ANR-10-IDEX-0002) and by SFRI-STRAT’US project (ANR-20-SFRI-0012) under the framework of the French Investments for the Future Program.