Keaton Jacob M, Gao Chuan, Guan Meijian, Hellwege Jacklyn N, Palmer Nicholette D, Pankow James S, Fornage Myriam, Wilson James G, Correa Adolfo, Rasmussen-Torvik Laura J, Rotter Jerome I, Chen Yii-Der I, Taylor Kent D, Rich Stephen S, Wagenknecht Lynne E, Freedman Barry I, Ng Maggie C Y, Bowden Donald W
Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America.
Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America.
Genet Epidemiol. 2018 Sep;42(6):559-570. doi: 10.1002/gepi.22126. Epub 2018 Apr 24.
Although type 2 diabetes (T2D) results from metabolic defects in insulin secretion and insulin sensitivity, most of the genetic risk loci identified to date relates to insulin secretion. We reported that T2D loci influencing insulin sensitivity may be identified through interactions with insulin secretion loci, thereby leading to T2D. Here, we hypothesize that joint testing of variant main effects and interaction effects with an insulin secretion locus increases power to identify genetic interactions leading to T2D. We tested this hypothesis with an intronic MTNR1B SNP, rs10830963, which is associated with acute insulin response to glucose, a dynamic measure of insulin secretion. rs10830963 was tested for interaction and joint (main + interaction) effects with genome-wide data in African Americans (2,452 cases and 3,772 controls) from five cohorts. Genome-wide genotype data (Affymetrix Human Genome 6.0 array) was imputed to a 1000 Genomes Project reference panel. T2D risk was modeled using logistic regression with rs10830963 dosage, age, sex, and principal component as predictors. Joint effects were captured using the Kraft two degrees of freedom test. Genome-wide significant (P < 5 × 10 ) interaction with MTNR1B and joint effects were detected for CMIP intronic SNP rs17197883 (P = 1.43 × 10 ; P = 4.70 × 10 ). CMIP variants have been nominally associated with T2D, fasting glucose, and adiponectin in individuals of East Asian ancestry, with high-density lipoprotein, and with waist-to-hip ratio adjusted for body mass index in Europeans. These data support the hypothesis that additional genetic factors contributing to T2D risk, including insulin sensitivity loci, can be identified through interactions with insulin secretion loci.
尽管2型糖尿病（T2D）是由胰岛素分泌和胰岛素敏感性的代谢缺陷引起的，但迄今为止确定的大多数遗传风险位点都与胰岛素分泌有关。我们报告称，影响胰岛素敏感性的T2D位点可能通过与胰岛素分泌位点的相互作用而被识别出来，从而导致T2D。在此，我们假设对变异主效应以及与胰岛素分泌位点的相互作用效应进行联合检测，可提高识别导致T2D的遗传相互作用的能力。我们用一个内含子MTNR1B单核苷酸多态性（SNP）rs10830963检验了这一假设，该SNP与对葡萄糖的急性胰岛素反应相关，这是一种胰岛素分泌的动态指标。在来自五个队列的非裔美国人（2452例病例和3772例对照）中，对rs10830963与全基因组数据的相互作用和联合（主效应+相互作用）效应进行了检测。全基因组基因型数据（Affymetrix人类基因组6.0芯片）被推算到千人基因组计划参考面板。使用逻辑回归模型，以rs10830963剂量、年龄、性别和主成分为预测因子，对T2D风险进行建模。联合效应通过Kraft两自由度检验来捕捉。检测到CMIP内含子SNP rs17197883与MTNR1B存在全基因组显著（P < 5×10⁻⁸）的相互作用和联合效应（P = 1.43×10⁻⁸；P = 4.70×10⁻⁸）。CMIP变异在东亚血统个体中已被名义上关联到T2D、空腹血糖和脂联素，在欧洲人中与高密度脂蛋白以及经体重指数调整的腰臀比有关。这些数据支持这样的假设，即通过与胰岛素分泌位点的相互作用，可以识别出导致T2D风险的其他遗传因素，包括胰岛素敏感性位点。
