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Cumulative Effect and Predictive Value of Genetic Variants Associated with Type 2 Diabetes in Han Chinese: A Case-Control Study

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NIAID Data Ecosystem2026-03-07 收录
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https://figshare.com/articles/dataset/_Cumulative_Effect_and_Predictive_Value_of_Genetic_Variants_Associated_with_Type_2_Diabetes_in_Han_Chinese_A_Case_Control_Study_/1323571
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Background Genome-wide association studies (GWAS) have identified dozens of single nucleotide polymorphisms (SNPs) associated with type 2 diabetes risk. We have previously confirmed the associations of genetic variants in HHEX, CDKAL1, VEGFA and FTO with type 2 diabetes in Han Chinese. However, the cumulative effect and predictive value of these GWAS identified SNPs on the risk of type 2 diabetes in Han Chinese are largely unknown. Methodology/Principal Findings We conducted a two-stage case-control study consisting of 2,925 cases and 3,281controls to examine the association of 30 SNPs identified by GWAS with type 2 diabetes in Han Chinese. Significant associations were found for proxy SNPs at KCNQ1 [odds ratio (OR) = 1.41, P = 9.91 × 10–16 for rs2237897], CDKN2A/CDKN2B (OR = 1.30, P = 1.34 × 10–10 for rs10811661), CENTD2 (OR = 1.28, P = 9.88 × 10-4 for rs1552224) and SLC30A8 (OR = 1.19, P = 1.43 × 10-5 for rs13266634). We further evaluated the cumulative effect on type 2 diabetes of these 4 SNPs, in combination with 5 SNPs at HHEX, CDKAL1, VEGFA and FTO reported previously. Individuals carrying 12 or more risk alleles had a nearly 4-fold increased risk for developing type 2 diabetes compared with those carrying less than 6 risk alleles [adjusted OR = 3.68, 95% confidence interval (CI): 2.76–4.91]. Adding the genetic factors to clinical factors slightly improved the prediction of type 2 diabetes, with the area under the receiver operating characteristic curve increasing from 0.76 to 0.78. However, the difference was statistically significant (P < 0.0001). Conclusions/Significance We confirmed associations of SNPs in KCNQ1, CDKN2A/CDKN2B, CENTD2 and SLC30A8 with type 2 diabetes in Han Chinese. The utilization of genetic information may improve the accuracy of risk prediction in combination with clinical characteristics for type 2 diabetes.
创建时间:
2016-01-15
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