Bridging the gap from genetic association to functional understanding: the next generation of mouse models of multiple sclerosis

Multiple sclerosis (MS) is a disabling autoimmune disease of the central nervous system, which affects approximately 0.1% of the population with variable degrees of severity. Disease susceptibility is jointly determined by genetic predisposition and environmental contribution. However, as only a handful of genetic risk factors have been investigated beyond initial genome-wide association studies and environmental factors are largely unidentified, the exact mechanism of how these associations interact remains speculative. Our current understanding of this complex and heterogeneous disease has been advanced by experimental data obtained from animal modeling, with particular focus on the mouse MS model, experimental autoimmune encephalomyelitis. Manipulation of the mouse genome to study genetic risk factors has largely proved informative, but it also has limitations. Integration effects of transgene insertion, gene copy number, and expression variation, as well as differences in regulatory elements between mouse and human, are some of the hurdles faced when using such models to understand human gene variants in mice. Furthermore, as the list of MS disease-associated genetic variants continues to increase, so does the demand to find new approaches to study them. A new generation of humanized mice aims to tighten the gap between mouse and human, such that MS-associated genetic variants can be modeled more physiologically and systematically.