Development of potential biomarkers to forecast treatment response and clinical relapses of multiple sclerosis by investigating the CNS-specific proteome fingerprint of experimental autoimmune encephalomyelitis

Despite extensive research, multiple sclerosis (MS) remains a disease that lacks a definitive prognostic test to predict imminent disease relapses. Thus, patients may undergo years of unnecessary treatments.

To address these issues, we developed a high-throughput quantitative proteomics method designated M2-proteomics to measure changes in proteome expression over the course of the preclinical experimental autoimmune encephalomyelitis (EAE) model of MS. Our studies revealed characteristic CNS-specific protein expression waves prior to the onset of clinical symptoms in EAE. Bioinformatics and statistical analyses revealed candidate predicative biomarkers to forecast the onset of clinical symptoms, and thereby onset of clinical relapses of MS. Importantly, we detected these proteins in serum and expression trajectories analysis identified a strong correlation of the CNS proteome to their levels in serum.

Prospective studies in the EAE model showed the effectiveness of these proteins in predicting clinical disease. Our studies suggest the utility for establishing homologous protein biomarkers in human MS patients. Finally, our work investigating the CNS proteome over the course of EAE provides us with unique insights and novel molecular targets for disease mechanisms and treatments of MS.