Talmud Philippa J, Cooper Jackie A, Morris Richard W, Dudbridge Frank, Shah Tina, Engmann Jorgen, Dale Caroline, White Jon, McLachlan Stela, Zabaneh Delilah, Wong Andrew, Ong Ken K, Gaunt Tom, Holmes Michael V, Lawlor Debbie A, Richards Marcus, Hardy Rebecca, Kuh Diana, Wareham Nicholas, Langenberg Claudia, Ben-Shlomo Yoav, Wannamethee S Goya, Strachan Mark W J, Kumari Meena, Whittaker John C, Drenos Fotios, Kivimaki Mika, Hingorani Aroon D, Price Jacqueline F, Humphries Steve E
Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, U.K.
Department of Primary Care and Population Health, University College London, Royal Free Campus, London, U.K.
Diabetes. 2015 May;64(5):1830-40. doi: 10.2337/db14-1504. Epub 2014 Dec 4.
We developed a 65 type 2 diabetes (T2D) variant-weighted gene score to examine the impact on T2D risk assessment in a U.K.-based consortium of prospective studies, with subjects initially free from T2D (N = 13,294; 37.3% women; mean age 58.5 [38-99] years). We compared the performance of the gene score with the phenotypically derived Framingham Offspring Study T2D risk model and then the two in combination. Over the median 10 years of follow-up, 804 participants developed T2D. The odds ratio for T2D (top vs. bottom quintiles of gene score) was 2.70 (95% CI 2.12-3.43). With a 10% false-positive rate, the genetic score alone detected 19.9% incident cases, the Framingham risk model 30.7%, and together 37.3%. The respective area under the receiver operator characteristic curves were 0.60 (95% CI 0.58-0.62), 0.75 (95% CI 0.73 to 0.77), and 0.76 (95% CI 0.75 to 0.78). The combined risk score net reclassification improvement (NRI) was 8.1% (5.0 to 11.2; P = 3.31 × 10(-7)). While BMI stratification into tertiles influenced the NRI (BMI ≤24.5 kg/m(2), 27.6% [95% CI 17.7-37.5], P = 4.82 × 10(-8); 24.5-27.5 kg/m(2), 11.6% [95% CI 5.8-17.4], P = 9.88 × 10(-5); >27.5 kg/m(2), 2.6% [95% CI -1.4 to 6.6], P = 0.20), age categories did not. The addition of the gene score to a phenotypic risk model leads to a potentially clinically important improvement in discrimination of incident T2D.
我们开发了一种包含65个2型糖尿病(T2D)变异加权基因得分,用于在一个英国前瞻性研究联盟中检验其对T2D风险评估的影响,研究对象最初无T2D(N = 13294;37.3%为女性;平均年龄58.5[38 - 99]岁)。我们将基因得分的性能与基于表型的弗雷明汉后代研究T2D风险模型进行了比较,然后又将两者结合起来进行比较。在中位10年的随访期内,804名参与者患了T2D。T2D的优势比(基因得分最高五分位数与最低五分位数相比)为2.70(95%置信区间2.12 - 3.43)。在假阳性率为10%的情况下,单独的基因得分检测到19.9%的新发病例,弗雷明汉风险模型检测到30.7%,两者结合检测到37.3%。受试者工作特征曲线下的面积分别为0.60(95%置信区间0.58 - 0.62)、0.75(95%置信区间0.73至0.77)和0.76(95%置信区间0.75至0.78)。联合风险评分的净重新分类改善(NRI)为8.1%(5.0至11.2;P = 3.31×10⁻⁷)。虽然将体重指数分层为三分位数会影响NRI(体重指数≤24.5 kg/m²,27.6%[95%置信区间17.7 - 37.5],P = 4.82×10⁻⁸;24.5 - 27.5 kg/m²,11.6%[95%置信区间5.8 - 17.4],P = 9.88×10⁻⁵;>27.5 kg/m²,2.6%[95%置信区间 - 1.4至6.6],P = 0.20),但年龄类别不会。将基因得分添加到表型风险模型中可在区分新发性T2D方面带来潜在的临床重要改善。