AIMS/HYPOTHESIS: We determined whether single nucleotide polymorphisms (SNPs) previously associated with diabetogenic traits improve the discriminative power of a type 2 diabetes genetic risk score. METHODS: Participants (n = 2,751) were genotyped for 73 SNPs previously associated with type 2 diabetes, fasting glucose/insulin concentrations, obesity or lipid levels, from which five genetic risk scores (one for each of the four traits and one combining all SNPs) were computed. Type 2 diabetes patients and non-diabetic controls (n = 1,327/1,424) were identified using medical records in addition to an independent oral glucose tolerance test. RESULTS: Model 1, including only SNPs associated with type 2 diabetes, had a discriminative power of 0.591 (p < 1.00 x 10(-20) vs null model) as estimated by the area under the receiver operator characteristic curve (ROC AUC). Model 2, including only fasting glucose/insulin SNPs, had a significantly higher discriminative power than the null model (ROC AUC 0.543; p = 9.38 x 10(-6) vs null model), but lower discriminative power than model 1 (p = 5.92 x 10(-5)). Model 3, with only lipid-associated SNPs, had significantly higher discriminative power than the null model (ROC AUC 0.565; p = 1.44 x 10(-9)) and was not statistically different from model 1 (p = 0.083). The ROC AUC of model 4, which included only obesity SNPs, was 0.557 (p = 2.30 x 10(-7) vs null model) and smaller than model 1 (p = 0.025). Finally, the model including all SNPs yielded a significant improvement in discriminative power compared with the null model (p < 1.0 x 10(-20)) and model 1 (p = 1.32 x 10(-5)); its ROC AUC was 0.626. CONCLUSIONS/INTERPRETATION: Adding SNPs previously associated with fasting glucose, insulin, lipids or obesity to a genetic risk score for type 2 diabetes significantly increases the power to discriminate between people with and without clinically manifest type 2 diabetes compared with a model including only conventional type 2 diabetes loci.
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机译：目的/假设：我们确定以前与糖尿病性状相关的单核苷酸多态性（SNP）是否能提高2型糖尿病遗传风险评分的判别力。方法：对参加者（n = 2,751）的73个SNP进行基因分型，先前与2型糖尿病，空腹血糖/胰岛素浓度，肥胖或血脂水平相关，从中获得5个遗传风险评分（4个特征中的每个特征和一个组合所有SNP的基因得分） ）进行了计算。除了独立的口服葡萄糖耐量测试外，还使用医疗记录确定了2型糖尿病患者和非糖尿病对照（n = 1,327 / 1,424）。结果：模型1仅包括与2型糖尿病相关的SNP，根据接收者操作者特征曲线（ROC AUC）下的面积估计，其判别力为0.591（相对于零模型，p <1.00 x 10（-20））。仅包含空腹葡萄糖/胰岛素SNP的模型2的判别力比无效模型高（ROC AUC 0.543；相对于无效模型，p = 9.38 x 10（-6）），但是判别力比模型1低（p = 5.92 x 10（-5））。仅与脂质相关的SNP的模型3的判别力比无效模型（ROC AUC 0.565; p = 1.44 x 10（-9））高得多，与模型1的统计学差异无统计学意义（p = 0.083）。仅包含肥胖SNP的模型4的ROC AUC为0.557（相对于零模型，p = 2.30 x 10（-7）），小于模型1（p = 0.025）。最后，与无效模型（p <1.0 x 10（-20））和模型1（p = 1.32 x 10（-5））相比，包括所有SNP的模型在判别力上有显着改善。其ROC AUC为0.626。结论/解释：与仅包括常规类型的模型相比，将先前与空腹血糖，胰岛素，脂质或肥胖症相关的SNPs添加到2型糖尿病的遗传风险评分中，显着提高了区分是否患有临床上明显的2型糖尿病的人的能力。 2个糖尿病位点。
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