Onengut-Gumuscu Suna, Chen Wei-Min, Burren Oliver, Cooper Nick J, Quinlan Aaron R, Mychaleckyj Josyf C, Farber Emily, Bonnie Jessica K, Szpak Michal, Schofield Ellen, Achuthan Premanand, Guo Hui, Fortune Mary D, Stevens Helen, Walker Neil M, Ward Lucas D, Kundaje Anshul, Kellis Manolis, Daly Mark J, Barrett Jeffrey C, Cooper Jason D, Deloukas Panos, Todd John A, Wallace Chris, Concannon Patrick, Rich Stephen S
1] Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA. [2] Department of Medicine, Division of Endocrinology, University of Virginia, Charlottesville, Virginia, USA.
1] Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA. [2] Department of Public Health Sciences, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, Virginia, USA.
Nat Genet. 2015 Apr;47(4):381-6. doi: 10.1038/ng.3245. Epub 2015 Mar 9.
Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10(-8)). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34(+) stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal.
1型糖尿病（T1D）的基因研究已确定了50个易感区域，发现了导致患病风险的主要途径，其中一些基因座在免疫疾病中是共享的。为了使跨自身免疫性疾病的基因比较尽可能具有信息价值，开发了一种高密度基因分型芯片——免疫芯片，我们从中确定了四个新的T1D相关区域（P < 5 × 10^(-8)）。与15种免疫疾病的比较分析表明，T1D在基因上与其他自身抗体阳性疾病更为相似，与青少年特发性关节炎最为相似，与溃疡性结肠炎最不相似，并为另外三个新的T1D风险基因座提供了支持。使用贝叶斯方法，我们定义了T1D相关单核苷酸多态性（SNP）的可信集。相关的SNP定位于在胸腺、T细胞和B细胞以及CD34(+)干细胞中活跃的增强子序列。现在可以在这些细胞类型中分析增强子与启动子的相互作用，以确定哪些特定基因和调控序列是致病的。
