Identification of markers of relapse in a relapsing-remitting mouse model of multiple sclerosis

Abstract

Abstract Approximately 85 percent of individuals newly diagnosed with multiple sclerosis have the relapsing-remitting form of the disease characterized by attacks of neurologic symptoms that are both unpredictable in occurrence and duration. The lack of markers that reliably predict the occurrence of multiple sclerosis relapses hinders the ability for proactive therapeutic intervention. To address the urgent need for biomarkers of relapse we investigated proteome changes over the disease course of relapsing-remitting experimental autoimmune encephalomyelitis (EAE) in SJL mice as a preclinical model of the disease using a high-throughput quantitative proteomic technique. In this study, we utilized this established proteomic technique as well as bioinformatics tools to prioritize key proteins that were expressed differentially at different stages of disease including remission and relapse. Principal component analysis of protein expression shows that the remission and relapse phases of disease cluster separately, indicating distinguishable variation between the two disease states. Importantly, statistical testing identified proteins with differential expression in the CNS at different stages of disease, several of which are CNS specific. We are seeking 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 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.