Identifying biomarkers for monitoring 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 ultimately 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 novel high-throughput quantitative proteomic technique which we used to quantify expression levels of central nervous system (CNS) proteins over the course of monophasic EAE in C57.BL/6 mice. We utilized bioinformatics tools to prioritize key proteins whose expression level correlated specifically with the progressive phase of disease in the NOD EAE model. Importantly, we were able to detect corollary changes in these 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.