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

Multiple sclerosis (MS) is an autoimmune demyelinating disease impacting the central nervous system, causing a wide array of debilitating symptoms. Recent studies have employed wearable activity recording devices to monitor MS symptoms, including sleep/wake cycle disruptions and fatigue. However, comparable activity measures have not been systematically established in pre-clinical MS models, such as experimental autoimmune encephalomyelitis (EAE).

To address this gap, the researchers aimed to analyze continual home-cage activity during EAE progression and determine if home-cage monitoring could serve as an unbiased measure of disease progression. The findings indicated that EAE had a significant impact on locomotor activity during the mid-active/dark phase. Circadian disruption was observed during the peak and onset stages of the disease.

The researchers noted that 40-minute-long activity bouts were particularly sensitive to non-motor symptom indicators, independent of motor deficits measured by clinical scores. Traditionally, EAE disease progression has been assessed using clinical scores, which focus on motor deficits and are susceptible to observer bias. Distinct activity parameters were altered across various disease stages, implying that a combination of activity measures could function as objective indicators of disease progression.

Ultimately, the study demonstrates that home-cage activity effectively captures non-motor symptoms in the EAE model of MS and provides an observer-independent assessment of EAE disease progression.