Abstract

DA and LEW inbred rats are extraordinarily susceptible to a wide range of experimental autoimmune diseases. These diseases include rheumatoid arthritis models such as collagen-induced arthritis (CIA) and adjuvant-induced arthritis (AIA), multiple sclerosis models such as myelin-basic-protein (MBP)-induced experimental autoimmune encephalomyelitis (MBP-EAE), and autoimmune uveitis models such as retinal S antigen (SAG) and interphotoreceptor-retinoid-binding-protein (IRBP)-induced experimental autoimmune uveitis (SAG-EAU and IRBP-EAU, respectively). DA and LEW rats are also addiction-prone to various drugs of abuse, such as cocaine. Moreover, they exhibit a variety of behavioral and biochemical characteristics that appear to be related to their susceptibility to addiction. By contrast, F344 and BN rats show quite different phenotypes. They are relatively resistant to CIA, AIA, MBP-EAE, SAG-EAU, and IRBP-EAU, and they are relatively resistant to addiction. Interestingly, both DA and LEW rats, in contrast to F344 and BN rats, have abnormalities in hypothalamic-pituitary-adrenal (HPA) axis function. For example, circadian production of corticosteroids is very abnormal in DA and LEW rats; that is, they exhibit minimal circadian variation in corticosterone levels. Since corticosteroids potentially have significant influences on immune function and autoimmune disease susceptibility and may also influence sensitivity to drugs of abuse, we have begun to dissect genetic control of these various phenotypic differences, focusing initially on the regulation of autoimmune disease expression. Using genomewide scanning techniques involving F2 crosses of DA x F344 (CIA and AIA), DA x BN (CIA), and LEW x F344 [IRBP-EAU and streptococcal-cell-wall arthritis (SCWA)], we have identified, to date, 14 genomic regions [quantitative trait loci (QTL)] that regulate disease expression in these crosses. Development and analysis of QTL-congenic rats involving these loci are in progress and should permit us to address the relationships among autoimmune disease susceptibility, drug addiction, and HPA axis and stress response function. These initial data, however, indicate that the genetic control of the autoimmune disease traits is highly complex.

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