From disease to genes in animal models of rheumatoid arthritis and multiple sclerosis
Sammanfattning: Rheumatoid arthritis (RA) and multiple sclerosis (MS) are complex inflammatory autoimmune diseases. The aetiology is largely unknown but the risk of developing disease is dependent on both genetic and environmental factors. Extensive efforts have been done to identify the underlying genes in order to understand the molecular mechanisms of the diseases. Until recently, only a few genes have been qualified as risk genes in human RA and MS, due to the complexity, but with new genetic tools, additional strong candidate genes for complex diseases have been reported. However, there are still more susceptibility genes to be identified. Animal models of autoimmune diseases are an attractive alternative to overcome some of the complexity of the human autoimmune diseases. In the papers presented in this thesis, a combination of genetic strategies to identify susceptibility genes controlling collagen-induced arthritis and/or experimental autoimmune encephalomyelitis, have been used. These are the commonly used animal models of RA and MS. Three loci, originally identified in two-generation crosses, have been confirmed by investigating congenic strains, sub-interval congenic mice and/or a heterogeneous stock inbred-outbred cross. Eae41 was found to control EAE development in male mice and two genes, differentially expressed between the congenic mice and littermate controls, are located in the loci. The Eae39 and Cia26 loci, both regulating CIA susceptibility with male and female predominance, respectively, were mapped down to a single gene level. The candidate genes in Eae39 are Med13l and 5S rRNA. In Cia26, two genes are located in the linked region, Trps1 and Csmd3, where the Trps1 is the most likely candidate. The homologous regions of both gene fragments are associated with RA in humans. These findings demonstrate a successful approach to identify susceptibility genes and the relevance of mapping complex traits in animal models.
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