Genetics of rheumatoid arthritis: GWAS and beyond

Kate McAllister, Stephen Eyre, Gisela OrozcoArthritis Research United Kingdom Epidemiology Unit, Manchester Academic Health Science Centre, University of Manchester, UKAbstract: The study of complex genetics in autoimmune diseases has progressed at a tremendous pace over the last 4 years, as a direc...

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Autores principales: McAllister KM, Eyre S, Orozco G
Formato: article
Lenguaje:EN
Publicado: Dove Medical Press 2011
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Acceso en línea:https://doaj.org/article/53f6db705e124916984eb0f1cf128df6
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Sumario:Kate McAllister, Stephen Eyre, Gisela OrozcoArthritis Research United Kingdom Epidemiology Unit, Manchester Academic Health Science Centre, University of Manchester, UKAbstract: The study of complex genetics in autoimmune diseases has progressed at a tremendous pace over the last 4 years, as a direct result of the enormous gains made by genome wide association studies (GWAS). Novel genetic findings are continuously being reported alongside the rapid development of genetic technologies, sophisticated statistical analysis, and larger sample collections. It is now becoming clear that multiple genes contribute to disease risk in many complex genetic disorders including rheumatoid arthritis (RA) and that there are common genetic risk factors that underlie a spectrum of autoimmune diseases. This review details the current genetic landscape of RA, and describes what GWAS has taught us in terms of missing heritability, subsets of disease, existence of genetic heterogeneity, and shared autoimmune risk loci. Finally, this review addresses the initial challenges faced in translating the wealth of genetic findings into determining the biological mechanisms that contribute to the relationship between genotype and phenotype. Unraveling the mechanism of how genes directly influence the cause of RA will lead to a better understanding of the disease and will ultimately have a direct clinical impact, informing the development of new therapies that can be utilized in the treatment of RA.Keywords: rheumatoid arthritis, GWAS, fine mapping, immunochip, bioinformatics