Combined effects of 17 common genetic variants on type 2 diabetes risk in a Han Chinese population
Combined effects of 17 common genetic variants on type 2 diabetes risk in a Han Chinese population
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17种常见遗传变异对中国汉族人群2型糖尿病风险的综合影响
DOI：
10.1007/s00125-010-1826-5
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发表时间：
2010-10-01
期刊：
影响因子：
8.2
通讯作者：
Lin, X.
中科院分区：
文献类型：
--
作者：
Qi, Q.;Li, H.;Lin, X.
目的/假设最近出现的全基因组关联研究大大加快了2型糖尿病位点的识别。我们的目的是调查多种遗传变异的综合影响，单独或与传统的危险因素相结合，对2型糖尿病和糖尿病相关的characteristics in Han Chinese.MethodsWe基因分型17个变异在17个位点在一个基于人群的汉族队列，包括3,210无关的个人。根据这些变异计算遗传风险评分（GRS）。结果2型糖尿病和高脂血症与每个GRS点（每个危险等位基因）的比值比分别为1.18（95%CI 1.12- 1.23，p = 1.3 × 10 - 12）和1.12（95%CI 1.09- 1.16，p = 7.5 × 10 - 14）。与GRS ≤11.0（7.63%）的参与者相比，GRS ≥19.0（8.87%）的参与者患2型糖尿病的风险高4.58倍（95%CI 2.49-8.42）。GRS还显示与β细胞功能的HOMA估计的较低β细胞功能显著相关（p= 8.4 × 10−10）。此外，我们观察到GRS和BMI对空腹血糖和HbA 1c水平的显著交互作用（交互作用分别为p= 0.04和p = 0.03）。当将GRS加入到包括临床危险因素的模型中时，糖尿病风险的区分度得到改善（p< 0.001）。AUC分别为0.62和0.77，单独为GRS和传统的临床危险因素，和0.79时，GRS被added.Conclusions/interpretationIn此汉族人群中，GRS的17个联合变异适度，但显着提高了2型糖尿病的传统危险因素的歧视。
Aims/hypothesisThe recent advent of genome-wide association studies has considerably accelerated the identification of type 2 diabetes loci. We aimed to investigate the combined effects of multiple genetic variants, alone or in combination with conventional risk factors, on type 2 diabetes and diabetes-related traits in Han Chinese.MethodsWe genotyped 17 variants in 17 loci in a population-based Han Chinese cohort including 3,210 unrelated individuals. A genetic risk score (GRS) was calculated on the basis of these variants. The discriminatory ability was assessed by the area under the receiver operating characteristics curve.ResultsThe odds ratio for type 2 diabetes and hyperglycaemia with each GRS point (per risk allele) was 1.18 (95% CI 1.12–1.23,p= 1.3 × 10−12) and 1.12 (95% CI 1.09–1.16,p= 7.5 × 10−14), respectively. Compared with participants with GRS ≤11.0 (7.63%), those with GRS ≥19.0 (8.87%) had a 4.58-fold higher risk (95% CI 2.49–8.42) of type 2 diabetes. The GRS also showed a significant association with lower beta cell function estimated by HOMA of beta cell function (p= 8.4 × 10−10). In addition, we observed significant interactive effects between GRS and BMI on fasting glucose and HbA1clevels (p= 0.04 andp= 0.03 for interaction, respectively). Discrimination of diabetes risk was improved (p< 0.001) when the GRS was added to a model including clinical risk factors. The AUCs were 0.62 and 0.77, respectively, for the GRS and conventional clinic risk factors alone, and 0.79 when the GRS was added.Conclusions/interpretationIn this Han Chinese population, the GRS of 17 combined variants modestly but significantly improved discrimination of the conventional risk factors for type 2 diabetes.