Investigation of the Association between 45 Tag SNPs and Type 2 Diabetes Mellitus in Han Chinese Adults: A Prospective Cohort Study.

IF 1.3 4区医学 Q4 GENETICS & HEREDITY

Public Health Genomics Pub Date : 2021-01-01 Epub Date: 2021-03-11 DOI:10.1159/000513891

Yun Chen, Xiao-Ying Chen, Xiao-Lian Dong, Yu-Zhuo Wang, Na Wang, Jian-Fu Zhu, Yue Chen, Qing-Wu Jiang, Chao-Wei Fu

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引用次数: 2

Abstract

Introduction: The objective of this study was to examine the association between type 2 diabetes mellitus (T2DM) and genes identified in previous genome-wide association studies (GWASs) in rural Han Chinese adults.

Methods: This prospective study included 1,832 adults aged ≥18 years in Deqing without diabetes at baseline. The subjects were followed up for 8.7 years on average. We selected 45 susceptible tag single-nucleotide polymorphisms (SNPs) for T2DM that have been identified in GWASs and genotyped. A Cox model was constructed to calculate the adjusted hazard ratios (aHRs) for the association between SNPs and incident T2DM.

Results: The incidence rate of T2DM was 12.0 per 1,000 person-years. After adjustment for covariates and a Bonferroni correction, rs17584499 of protein tyrosine phosphatase, receptor-type D (PTPRD), rs11257655 and rs10906115 of cell division cycle 123 gene (CDC123), and rs12970134 of melanocortin-4 receptor (MC4R) were significantly associated with incident T2DM. The aHRs for incident T2DM were 1.75 (95% confidence interval [CI]: 1.28-2.40) and 1.61 (95% CI: 1.27-2.04) in association with an increasing number of T alleles in rs17584499 and rs11257655 under an additive genetic model, and the aHR was 1.72 (95% CI: 1.33-2.22) with an increasing number of A alleles in rs10906115. The aHRs under the dominant model were 1.82 (95% CI: 1.25-2.66) for TT + CT versus CC of rs17584499 and 2.04 (95% CI: 1.47-2.86) for AA + AG versus GG of rs10966115. The aHRs under the recessive model were 2.99 (95% CI: 1.30-6.89) for TT versus CT + CC of rs17584499, 1.92 (95% CI: 1.39-2.70) for TT versus CT + CC of rs11257655, and 2.54 (95% CI:1.22-5.29) for AA versus AG + GG of rs12970134. In addition, an increased incidence of T2DM was significantly associated with the TA haplotype of rs11257655 and rs10906115 (aHR = 1.81, 95% CI: 1.12-2.92), while a decreased incidence was associated with the CG haplotype (aHR = 0.49, 95% CI: 0.35-0.68) and the CT haplotype of rs1111875 and rs5015480 (aHR = 0.61, 95% CI: 0.37-0.98).

Conclusion: Variants of the PTPRD, CDC123, and MC4R genes were associated with the T2DM incidence in a rural Han Chinese population.

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45个标签snp与汉族成人2型糖尿病的相关性研究:一项前瞻性队列研究

前言:本研究的目的是研究中国农村汉族成人2型糖尿病(T2DM)与先前全基因组关联研究(GWASs)中鉴定的基因之间的关系。方法:本前瞻性研究纳入1832名年龄≥18岁的德清市无糖尿病患者。这些研究对象的平均随访时间为8.7年。我们选择了在GWASs中发现的45个T2DM易感标签单核苷酸多态性(snp)并进行了基因分型。构建Cox模型计算snp与T2DM发病之间的校正风险比(aHRs)。结果:T2DM的发病率为12.0 / 1000人年。在协变量调整和Bonferroni校正后，蛋白酪氨酸磷酸酶、受体D型(PTPRD) rs17584499、细胞分裂周期123基因(CDC123) rs11257655和rs10906115、黑素皮素-4受体(MC4R) rs12970134与T2DM的发生显著相关。在加性遗传模型下，与rs17584499和rs11257655中T等位基因数量增加相关的T2DM发病aHR分别为1.75(95%可信区间[CI]: 1.28-2.40)和1.61 (95% CI: 1.27-2.04)，与rs10906115中A等位基因数量增加相关的aHR为1.72 (95% CI: 1.33-2.22)。优势模型下，rs17584499的TT + CT与CC的ahr为1.82 (95% CI: 1.25 ~ 2.66)， rs10966115的AA + AG与GG的ahr为2.04 (95% CI: 1.47 ~ 2.86)。rs17584499的TT与CT + CC的ahr为2.99 (95% CI: 1.30 ~ 6.89)， rs11257655的TT与CT + CC的ahr为1.92 (95% CI: 1.39 ~ 2.70)， rs12970134的AA与AG + GG的ahr为2.54 (95% CI:1.22 ~ 5.29)。此外，T2DM发病率增加与rs11257655和rs10906115的TA单倍型显著相关(aHR = 1.81, 95% CI: 1.12-2.92)，而发病率降低与CG单倍型相关(aHR = 0.49, 95% CI: 0.35-0.68)，与rs1111875和rs5015480的CT单倍型相关(aHR = 0.61, 95% CI: 0.37-0.98)。结论:PTPRD、CDC123和MC4R基因变异与农村汉族人群T2DM发病率相关。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Public Health Genomics 医学-公共卫生、环境卫生与职业卫生

CiteScore

2.90

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： ''Public Health Genomics'' is the leading international journal focusing on the timely translation of genome-based knowledge and technologies into public health, health policies, and healthcare as a whole. This peer-reviewed journal is a bimonthly forum featuring original papers, reviews, short communications, and policy statements. It is supplemented by topic-specific issues providing a comprehensive, holistic and ''all-inclusive'' picture of the chosen subject. Multidisciplinary in scope, it combines theoretical and empirical work from a range of disciplines, notably public health, molecular and medical sciences, the humanities and social sciences. In so doing, it also takes into account rapid scientific advances from fields such as systems biology, microbiomics, epigenomics or information and communication technologies as well as the hight potential of ''big data'' for public health.