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First Genome-Wide Association Study of Latent Autoimmune Diabetes in Adults Reveals Novel Insights Linking Immune and Metabolic Diabetes

机译:第一个全基因组关联研究成人潜在的自身免疫性糖尿病揭示了联系免疫和代谢糖尿病的新颖见解

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OBJECTIVELatent autoimmune diabetes in adults (LADA) shares clinical features with both type 1 and type 2 diabetes; however, there is ongoing debate regarding the precise definition of LADA. Understanding its genetic basis is one potential strategy to gain insight into appropriate classification of this diabetes subtype.RESEARCH DESIGN AND METHODSWe performed the first genome-wide association study of LADA in case subjects of European ancestry versus population control subjects (n = 2,634 vs. 5,947) and compared against both case subjects with type 1 diabetes (n = 2,454 vs. 968) and type 2 diabetes (n = 2,779 vs. 10,396).RESULTSThe leading genetic signals were principally shared with type 1 diabetes, although we observed positive genetic correlations genome-wide with both type 1 and type 2 diabetes. Additionally, we observed a novel independent signal at the known type 1 diabetes locus harboring PFKFB3, encoding a regulator of glycolysis and insulin signaling in type 2 diabetes and inflammation and autophagy in autoimmune disease, as well as an attenuation of key type 1-associated HLA haplotype frequencies in LADA, suggesting that these are factors that distinguish childhood-onset type 1 diabetes from adult autoimmune diabetes.CONCLUSIONSOur results support the need for further investigations of the genetic factors that distinguish forms of autoimmune diabetes as well as more precise classification strategies.
机译:成人的客观性自身免疫糖尿病(LADA)患有1型和2型糖尿病的临床特征;但是,有关LADA的确切定义,还有较令人行的争论。理解其遗传基础是一种潜在的策略,以了解患糖尿病患者的适当分类。研究设计和方法在欧洲祖先与人口控制受试者的情况下,Lada的第一个基因组关联研究(n = 2,634与5,947 )并与患有1型糖尿病(n = 2,454与968)的病例进行比较,并且2型糖尿病(n = 2,779与10,396)。虽然我们观察到阳性遗传相关性,但主要分享遗传信号。虽然我们观察到阳性遗传相关性基因组,型1型和2型糖尿病。另外,我们观察到涉及PFKFB3的已知1型糖尿病基因座的新型独立信号,编码糖酵解和自身免疫疾病中2型糖尿病和炎症和自噬中的糖醇分析和胰岛素信号传导的调节器,以及关键类型1相关HLA的衰减LADA中的单倍型频率,表明这些是区分儿童发病1型糖尿病的因素,从成人自身免疫糖尿病.Cluclionsour结果支持进一步调查区分自身免疫性糖尿病形式的遗传因素以及更精确的分类策略。

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