Novel mouse models to dissect the role of genetics, sex, and environment in heterogeneous outcomes in CNS autoimmune disease

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PROJECT ABSTRACT/SUMMARY Multiple sclerosis (MS) is a chronic disease that is the leading cause of non-traumatic neurological disability in young adults. The disease is caused by an aberrant immune-mediated attack on the central nervous system, which causes tissue destruction and subsequent neurologic disability. Disease course varies greatly from individual to individual, from relapsing-remitting MS, to primary progressive MS, the latter highly debilitating and refractory to treatment. MS is three times more common in women, but tends to be more severe in men. MS has a significant heritable component, with up to 30% of the disease risk being genetically determined. While recent studies have identified candidate genes that are associated with MS risk, it remains unclear how these genes work and whether these are truly causative. Additionally, it is completely unknown why some individuals get different forms of this disease, and why there are differences between men and women. The other 70% of disease risk comes from environment or gene-by-environment interactions, representing an attractive avenue for presentation. However, how risk factors, in particular chronic gammaherpes virus infection, mechanistically impact MS risk or progression is unclear. These types of questions are very difficult, if not impossible, to address in studies in humans, and in this application, we propose to use animal models of MS. Mouse models offer powerful genetic tools, and allow for cause/effect mechanistic studies, but conventional mouse models are highly artificial and lack genetic diversity. We will use several novel mouse genetic models that are designed to better represent the complex genetic structure of human populations, which will allow us to dissect the complex genetic architecture underlying MS pathogenesis, to identify specific genes responsible for various poorly understood aspects of this disease, and to identify gene-by-environment interactions and novel mechanisms underlying environmental risk factors.