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

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 sc...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Diabetes Association 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4407866/
https://www.ncbi.nlm.nih.gov/pubmed/25475436
http://dx.doi.org/10.2337/db14-1504
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author 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.
author_facet 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.
author_sort Talmud, Philippa J.
collection PubMed
description 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.
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spelling pubmed-44078662016-05-01 Sixty-Five Common Genetic Variants and Prediction of Type 2 Diabetes 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. Diabetes Genetics/Genomes/Proteomics/Metabolomics 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. American Diabetes Association 2015-05 2014-12-04 /pmc/articles/PMC4407866/ /pubmed/25475436 http://dx.doi.org/10.2337/db14-1504 Text en © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
spellingShingle Genetics/Genomes/Proteomics/Metabolomics
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.
Sixty-Five Common Genetic Variants and Prediction of Type 2 Diabetes
title Sixty-Five Common Genetic Variants and Prediction of Type 2 Diabetes
title_full Sixty-Five Common Genetic Variants and Prediction of Type 2 Diabetes
title_fullStr Sixty-Five Common Genetic Variants and Prediction of Type 2 Diabetes
title_full_unstemmed Sixty-Five Common Genetic Variants and Prediction of Type 2 Diabetes
title_short Sixty-Five Common Genetic Variants and Prediction of Type 2 Diabetes
title_sort sixty-five common genetic variants and prediction of type 2 diabetes
topic Genetics/Genomes/Proteomics/Metabolomics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4407866/
https://www.ncbi.nlm.nih.gov/pubmed/25475436
http://dx.doi.org/10.2337/db14-1504
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