Title: Scoring disease in an animal model of multiple sclerosis using a novel infrared-based automated activity-monitoring system.

Authors: Shahi, Shailesh K; Freedman, Samantha N; Dahl, Rachel A; Karandikar, Nitin J; Mangalam, Ashutosh K

Published In Sci Rep, (2019 12 16)

Abstract: Multiple sclerosis (MS) is a chronic demyelinating disorder of the central nervous system (CNS). Its corresponding animal model, experimental autoimmune encephalomyelitis (EAE), is widely used to understand disease pathogenesis and test novel therapeutic agents. However, existing methods to score EAE disease severity are subjective and often vary between individual researchers, making it difficult to translate findings across different studies. An enhanced automated method of disease scoring would eliminate subjectivity and reduce operator-dependent errors. Here, we used an Infra-Red Activity Monitoring System (IRAMS) to measure murine locomotor activity as a surrogate measure of disease severity and compared it to standard EAE scoring methods. In mice immunized with CNS-specific myelin antigens, we observed an inverse correlation between disease severity and mouse activity, with the IRAMS showing enhanced disease scoring compared to standard EAE scoring methods. Relative to standard EAE scoring methods, IRAMS showed comparable measurement of disease relapses and remissions in the SJL/J-relapsing-remitting model of EAE, and could comparably assess the therapeutic efficiency of the MS drug, Copaxone (Glatiramer acetate-GA). Thus, the IRAMS is a method to measure disease severity in EAE without subjective bias and is a tool to consistently assess the efficacy of novel therapeutic agents for MS.

PubMed ID: 31844134

MeSH Terms: No MeSH terms associated with this publication