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Diabetes | 2015

Sixty-Five Common Genetic Variants and Prediction of Type 2 Diabetes

Philippa J. Talmud; Jackie A. Cooper; Richard Morris; Frank Dudbridge; Tina Shah; Jorgen Engmann; Caroline Dale; Jon White; Stela McLachlan; Delilah Zabaneh; Andrew Wong; Ken K. Ong; Tom R. Gaunt; Michael V. Holmes; Debbie A. Lawlor; Marcus Richards; Rebecca Hardy; Diana Kuh; Nicholas J. Wareham; Claudia Langenberg; Yoav Ben-Shlomo; S. Goya Wannamethee; Mark W. J. Strachan; Meena Kumari; John C. Whittaker; Fotios Drenos; Mika Kivimäki; Aroon D. Hingorani; Jacqueline F. Price; Steve E. Humphries

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/m2, 27.6% [95% CI 17.7–37.5], P = 4.82 × 10−8; 24.5–27.5 kg/m2, 11.6% [95% CI 5.8–17.4], P = 9.88 × 10−5; >27.5 kg/m2, 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.

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Andrew Wong

University College London

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Delilah Zabaneh

University College London

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Diana Kuh

University College London

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