Genetic characterization to dissect the phenotypic complexity of autoimmunity

University dissertation from Medical Inflammation Research, Department of Experimental Medicine, Faculty of Medicine, Lund University

Abstract: Autoimmune diseases are dependent on multiple genes and unknown environmental factors. Great efforts in the identification of genes conferring susceptibility to autoimmune diseases like Rheumatoid Arthritis (RA) and Multiple Sclerosis (MS) have recently been rewarding. A few genes have so far been associated to several autoimmune disorders and the understanding of the role of these genes in the pathogenesis and the identification of additional genes will be of great use in the designing of new and better therapies. The fine characterization of each disease is of importance in order to define sub-groups, which may respond differently to treatments.

The work in this thesis was done in mouse models for RA and MS and is based on four papers where the aim was to identify genes associated with these diseases. We have studied crosses between a susceptible and a resistant mouse strain to assess the genetic context for a disease-linked locus to appear. In an F2 intercross between the two strains, the Eae2 locus on chromosome 15 was previously linked to disease in the MS model Experimental Autoimmune Encephalomyelitis (EAE) through interaction with Eae3 on chromosome 3. The locus homologous to Eae2 on human chromosome 5 was later associated with MS in a Finnish population. In order to identify additional loci, EAE was studied in an F2 intercross where the Eae2 locus was neutralized (paper I) and in a N2 backcross (paper II). In paper III and IV a new strategy to study the interaction between Eae2 and Eae3 is described. Mice congenic for the Eae2 and Eae3 regions were bred in a Partial Advanced Intercross (PAI), which allows for the segregation of genes in the congenic intervals. More than 1000 PAI mice were investigated for Collagen Induced Arthritis (CIA). Different traits of disease were linked to seven sub-QTL within Eae2 and Eae3. Furthermore, the importance of sub-phenotypes in order to identify disease-modifying genes was investigated and is discussed.