Identification of CNS-specific biomarkers for monitoring the progression of multiple sclerosis

Abstract

Abstract There are currently no reliable methods for assessing the progression of multiple sclerosis (MS) from the relapsing-remitting to the secondary progressive form. This gap in knowledge hinders the ability for therapeutic intervention and results in continued relapses and physiological deterioration. To begin to address the urgent need for biomarkers of progressive MS we investigated proteome changes over the disease course of progressive experimental autoimmune encephalomyelitis (EAE) in NOD mice as a preclinical model of the disease. Our lab has pioneered a high-throughput quantitative proteomic technique, which we have previously used to quantify expression levels of central nervous system (CNS) proteins over the course of monophasic EAE in C57BL/6 mice, producing a predictive protein biomarker fingerprint for clinical relapses. In this study, we utilized this established proteomic technique as well as bioinformatics tools to prioritize key proteins whose expression level in the CNS correlated specifically with the progressive phase of disease in the NOD EAE model. Bioinformatics analysis identified 11 proteins with differential expression in the CNS of mice across the time course of NOD EAE, three of which are CNS specific. We are seeking to detect corollary changes in these three CNS-specific proteins in the serum, pointing to a minimally invasive means of monitoring disease progress and measuring drug efficacy. Our studies will provide a proof-of-concept for identifying homologous human biomarkers to guide treatment in individual patients. Furthermore, our results may provide insights into mechanisms that contribute to disease pathology and offer additional therapeutic targets for slowing the progression of MS.