The complex genetics of experimental autoimmune neuroinflammation

Abstract

Experimental autoimmune encephalomyelitis (EAE) is an animal model for multiple sclerosis (MS), a chronic inflammatory and demyelinating disease of the central nervous system (CNS). MS is the second most common cause of neurological disability among young adults in the western world.

Identification of susceptibility genes is important in view of both the largely unknown etiology of MS and the modest effects of current therapies. Multiple genes and environmental factors involved in complex interactions govern disease expression in both EAE and MS. EAE induced with myelin oligodendrocyte glycoprotein (MOG) in rats closely resembles the clinical and pathological features of MS. We here studied three quantitative trait loci (QTL) that regulate MOG-EAE on rat chromosomes 4, 10 and 12.

We established congenic lines, DA.PVG-Eae20, DA.ACI-Eae18 and BN.DA-Eae5, encompassing the previously identified EAE-susceptibility regions on rat chromosomes 4, 10 and 12, respectively. The inbred DA rat strain is highly susceptible to MOG-EAE, whereas PVG and ACI are resistant and BN is relatively resistant. PVG alleles at Eae20 and ACI alleles at Eae18 conferred less severe MOG-EAE compared to DA alleles. Accordingly, DA alleles at Eae5 conferred more severe disease compared to BN alleles. The phenotypic differences demonstrated between the congenic and the respective parental strains confirm that alleles in the isolated regions are capable of regulating MOG-EAE.

We then performed high resolution mapping of these regions using an advanced intercross line (AIL) between DA and PVG.1AV1 in the 7th and 10th generations. AIL mapping proved to be an efficient approach i) to narrow down QTLs, ii) to resolve adjacent QTLs, and iii) to detect epistatic interactions between QTLs. A key finding in this AIL study was that initially broad regions resolved into multiple QTLs, suggesting clustering of EAE-susceptibility genes. The initial mapping of Eae18 in the F7 AIL cohort resolved this region into two QTLs, 5.5Mb Eae18a and 3Mb Eae18b. These QTLs were confirmed and further narrowed down in the F 10 AIL. Eae5 was mapped to a single 1.4 Mb QTL encompassing the arthritis-regulating gene, Ncf-1. The F10 AIL was also used to dissect a region on rat chromosome 4 into three QTLs, i.e. Eae20, Eae21 and Eae22, and to identify an epistatic interaction between Eae20 and Eae22.

Furthermore, owing to the considerable improvement in resolution and precision when using the AIL mapping approach, interesting candidate genes emerged, such as a cluster of chemokine genes comprising CCL1, CCL2, CCL7 and CCL11 within Eae18b and Ncf-1 within Eae5.

In conclusion, we have identified several discrete QTLs which contain a restricted number of genes and which overlap human MS regions as well as regions regulating other chronic inflammatory diseases. Our data set the stage for definition of the role of the candidate genes residing in the QTLs. Identification of the susceptibility genes may provide targets for design of more efficient therapies for NIS and other chronic inflammatory diseases.