Disease progression shapes circadian and locomotor disruption in a model of multiple sclerosis

Abstract

Multiple sclerosis (MS) is an autoimmune demyelinating disease of the central nervous system featuring a wide range of debilitating symptoms. Wearable activity recording devices have recently been adopted to improve symptom monitoring in MS, capturing symptoms related to sleep/wake cycles, circadian disruption, and fatigue. However, comparable measures of activity have yet been established in pre-clinical models of MS, the most widely used being experimental autoimmune encephalomyelitis (EAE). We therefore sought to characterize changes in continual home-cage activity over the course of EAE, and establish whether home-cage monitoring can be used as an observer-independent measure of disease progression. Our results showed that locomotor activity in the mid-active/dark phase was most severely affected by EAE. Disrupted circadian (24-hour) activity was observed during the peak and onset stages of disease. Bout activity analysis revealed >40-minute long activity bouts as a sensitive indicator of non-motor symptoms independent of clinical score-based motor deficits. Current assessment of disease progression in EAE relies on clinical scores, which primarily assess motor deficits through visual observation prone to observer bias. Various computed activity parameters were found to be altered during key disease stages, suggesting that a combination of activity measures can serve as objective indicators of disease progression. Overall, our results show that home-cage activity effectively captures signs of non-motor symptoms in the EAE model of MS and can serve as an observer-independent measure of EAE disease progression.