Mathematical modeling of regulatory T cell mechanisms in experimental autoimmune encephalomyelitis

The study of T cell mediation of the adaptive immune response during multiple sclerosis (MS) can lead to development of treatments and therapies for this demyelinating disease. A prominent mouse model for MS is experimental autoimmune encephalomyelitis (EAE). EAE is mediated by populations of CD4+ T cells: regulatory T cells (Tregs), which prevent the immune system from attacking self proteins, and other effector T cells (Teffs) that are activated against myelin oligodendrocyte glycoprotein. The disease can result in either relapsing remitting or constant symptoms which can be either mild, medium, or severe for extended periods of time. These differences in severity are influenced by the numbers of precursor T cells, and by the initial dose of antigen in the system. We have developed an ODE model of Treg and Teff populations over time that incorporates immune regulatory mechanisms in order to make testable predictions about EAE disease course. This model exhibits three stable steady states (a state with all cell populations near 0, an intermediate state, and a high Teff state) for realistic parameter values, and biologically plausible initial conditions lie in the basins of attraction for all three stable steady states. Thus this model can explain biologically observed disease outcomes, and mathematical analysis can provide specific, biologically testable predictions about the cause of each outcome.