New math model sheds light on multiple sclerosis relapse and recovery cycles

A new mathematical model developed by researchers at Queensland University of Technology (QUT) provides insight into the relapsing-remitting pattern of multiple sclerosis (MS). The model, published in the Journal of the Royal Society Interface, effectively reproduces the disease's cycles of inflammation and myelin damage. Dr. Adrianne Jenner, the lead author, explains that MS is notoriously difficult to understand due to its unpredictable nature.

The disease affects the brain and spinal cord by attacking myelin, the protective layer around nerve cells, disrupting communication and causing symptoms. MS patients typically experience periods of worsening symptoms, followed by recovery and remission. Understanding the factors behind the frequency of relapses is crucial, as almost half of these episodes result in lasting disability.

The two-variable model tracks changes in healthy myelin and inflammation over time. It transitions through three stages: a healthy state, a stable disease state, and an oscillating state that mirrors the relapse and remission cycles seen in many MS patients. The model suggests that increased disease activity or a reduction in the body's resilience to inflammation can drive the disease into recurring cycles of relapse and remission.

Additionally, the duration of inflammation may influence the time between relapses. When compared to existing data from people living with MS, the model accurately reproduced patterns observed in contrast-enhancing lesions, a common MRI marker of inflammatory disease. Jenner believes the model can aid in understanding disease activity and the biological mechanisms underlying relapses, potentially guiding future studies on biomarkers of MS activity and relapse mechanisms.