Combined effects of 17 common genetic variants on type 2 diabetes risk in a Han Chinese population

Q. Qi; H. Li; Y. Wu; C. Liu; H. Wu; Z. Yu; L. Qi; F. B. Hu; R. J.F. Loos; X. Lin

doi:10.1007/s00125-010-1826-5

Combined effects of 17 common genetic variants on type 2 diabetes risk in a Han Chinese population

Q. Qi, H. Li, Y. Wu, C. Liu, H. Wu, Z. Yu, L. Qi, F. B. Hu, R. J.F. Loos, X. Lin

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

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Resumen

Aims/hypothesis The recent advent of genome-wide association studies has considerably accelerated the identification of type 2 diabetes loci. We aimed to investigate the combined effects of multiple genetic variants, alone or in combination with conventional risk factors, on type 2 diabetes and diabetes-related traits in Han Chinese. Methods We genotyped17variantsin17lociina population-based Han Chinese cohort including 3,210 unrelated individuals. A genetic risk score (GRS) was calculated on the basis of these variants. The discriminatory ability was assessed by the area under the receiver operating characteristics curve. Results The odds ratio for type 2 diabetes and hyperglycaemia with each GRS point (per risk allele) was 1.18 (95% CI 1.12-1.23, p = 1.3x 10^-12) and 1.12 (95% CI 1.091.16, p=7.5 x10^-14), respectively. Compared with participants with GRS ≤11.0 (7.63%), those with GRS ≥19.0 (8.87%) had a 4.58-fold higher risk (95% CI 2.49-8.42) of type 2 diabetes. The GRS also showed a significant association with lower beta cell function estimated by HOMA of beta cell function (p=8.4 x10^-10). In addition, we observed significant interactive effects between GRS and BMI on fasting glucose and HbA_1c levels (p=0.04 and p=0.03 for interaction, respectively). Discrimination of diabetes risk was improved (p<0.001) when the GRS was added to a model including clinical risk factors. The AUCs were 0.62 and 0.77, respectively, for the GRS and conventional clinic risk factors alone, and 0.79 when the GRS was added. Conclusions/interpretation In this Han Chinese population, the GRS of 17 combined variants modestly but significantly improved discrimination of the conventional risk factors for type 2 diabetes.

Idioma original	English
Páginas (desde-hasta)	2163-2166
Número de páginas	4
Publicación	Diabetologia
Volumen	53
N.º	10
DOI	https://doi.org/10.1007/s00125-010-1826-5
Estado	Published - oct. 2010
Publicado de forma externa	Sí

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Funding Information:
Acknowledgements This study was financially supported by the Chief Scientist Program of Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences (SIBS2008006), the National Natural Science Foundation of China (30930081), the Ministry of Science and Technology of China (973 Program, Grant number 2006CB503900; 863 Program, Grant number 2007AA02Z332; and International Collaboration Program, Grant number 2008DFA31960) and the Chinese Academy of Sciences (The Knowledge Innovation Program, Grant number KSCX1-YW-02). We are grateful to all participants of the Study on Nutrition and Health of Aging Population in China. We also thank X. Pang, Z. Zhang, S. Jiao, H. Liu and S. Zhou from the Beijing and Shanghai Centers for Disease Control and Prevention for participating in the field work, and our colleagues W. Gan and G. Zong from the Institute for Nutritional Sciences for their part in the laboratory analyses.

ASJC Scopus Subject Areas

Internal Medicine
Endocrinology, Diabetes and Metabolism

PubMed: MeSH publication types

Journal Article
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title = "Combined effects of 17 common genetic variants on type 2 diabetes risk in a Han Chinese population",

abstract = "Aims/hypothesis The recent advent of genome-wide association studies has considerably accelerated the identification of type 2 diabetes loci. We aimed to investigate the combined effects of multiple genetic variants, alone or in combination with conventional risk factors, on type 2 diabetes and diabetes-related traits in Han Chinese. Methods We genotyped17variantsin17lociina population-based Han Chinese cohort including 3,210 unrelated individuals. A genetic risk score (GRS) was calculated on the basis of these variants. The discriminatory ability was assessed by the area under the receiver operating characteristics curve. Results The odds ratio for type 2 diabetes and hyperglycaemia with each GRS point (per risk allele) was 1.18 (95% CI 1.12-1.23, p = 1.3x 10-12) and 1.12 (95% CI 1.091.16, p=7.5 x10-14), respectively. Compared with participants with GRS ≤11.0 (7.63%), those with GRS ≥19.0 (8.87%) had a 4.58-fold higher risk (95% CI 2.49-8.42) of type 2 diabetes. The GRS also showed a significant association with lower beta cell function estimated by HOMA of beta cell function (p=8.4 x10-10). In addition, we observed significant interactive effects between GRS and BMI on fasting glucose and HbA1c levels (p=0.04 and p=0.03 for interaction, respectively). Discrimination of diabetes risk was improved (p<0.001) when the GRS was added to a model including clinical risk factors. The AUCs were 0.62 and 0.77, respectively, for the GRS and conventional clinic risk factors alone, and 0.79 when the GRS was added. Conclusions/interpretation In this Han Chinese population, the GRS of 17 combined variants modestly but significantly improved discrimination of the conventional risk factors for type 2 diabetes.",

author = "Q. Qi and H. Li and Y. Wu and C. Liu and H. Wu and Z. Yu and L. Qi and Hu, {F. B.} and Loos, {R. J.F.} and X. Lin",

note = "Funding Information: Acknowledgements This study was financially supported by the Chief Scientist Program of Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences (SIBS2008006), the National Natural Science Foundation of China (30930081), the Ministry of Science and Technology of China (973 Program, Grant number 2006CB503900; 863 Program, Grant number 2007AA02Z332; and International Collaboration Program, Grant number 2008DFA31960) and the Chinese Academy of Sciences (The Knowledge Innovation Program, Grant number KSCX1-YW-02). We are grateful to all participants of the Study on Nutrition and Health of Aging Population in China. We also thank X. Pang, Z. Zhang, S. Jiao, H. Liu and S. Zhou from the Beijing and Shanghai Centers for Disease Control and Prevention for participating in the field work, and our colleagues W. Gan and G. Zong from the Institute for Nutritional Sciences for their part in the laboratory analyses.",

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T1 - Combined effects of 17 common genetic variants on type 2 diabetes risk in a Han Chinese population

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AU - Li, H.

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AU - Liu, C.

AU - Wu, H.

AU - Yu, Z.

AU - Qi, L.

AU - Hu, F. B.

AU - Loos, R. J.F.

AU - Lin, X.

N1 - Funding Information: Acknowledgements This study was financially supported by the Chief Scientist Program of Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences (SIBS2008006), the National Natural Science Foundation of China (30930081), the Ministry of Science and Technology of China (973 Program, Grant number 2006CB503900; 863 Program, Grant number 2007AA02Z332; and International Collaboration Program, Grant number 2008DFA31960) and the Chinese Academy of Sciences (The Knowledge Innovation Program, Grant number KSCX1-YW-02). We are grateful to all participants of the Study on Nutrition and Health of Aging Population in China. We also thank X. Pang, Z. Zhang, S. Jiao, H. Liu and S. Zhou from the Beijing and Shanghai Centers for Disease Control and Prevention for participating in the field work, and our colleagues W. Gan and G. Zong from the Institute for Nutritional Sciences for their part in the laboratory analyses.

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N2 - Aims/hypothesis The recent advent of genome-wide association studies has considerably accelerated the identification of type 2 diabetes loci. We aimed to investigate the combined effects of multiple genetic variants, alone or in combination with conventional risk factors, on type 2 diabetes and diabetes-related traits in Han Chinese. Methods We genotyped17variantsin17lociina population-based Han Chinese cohort including 3,210 unrelated individuals. A genetic risk score (GRS) was calculated on the basis of these variants. The discriminatory ability was assessed by the area under the receiver operating characteristics curve. Results The odds ratio for type 2 diabetes and hyperglycaemia with each GRS point (per risk allele) was 1.18 (95% CI 1.12-1.23, p = 1.3x 10-12) and 1.12 (95% CI 1.091.16, p=7.5 x10-14), respectively. Compared with participants with GRS ≤11.0 (7.63%), those with GRS ≥19.0 (8.87%) had a 4.58-fold higher risk (95% CI 2.49-8.42) of type 2 diabetes. The GRS also showed a significant association with lower beta cell function estimated by HOMA of beta cell function (p=8.4 x10-10). In addition, we observed significant interactive effects between GRS and BMI on fasting glucose and HbA1c levels (p=0.04 and p=0.03 for interaction, respectively). Discrimination of diabetes risk was improved (p<0.001) when the GRS was added to a model including clinical risk factors. The AUCs were 0.62 and 0.77, respectively, for the GRS and conventional clinic risk factors alone, and 0.79 when the GRS was added. Conclusions/interpretation In this Han Chinese population, the GRS of 17 combined variants modestly but significantly improved discrimination of the conventional risk factors for type 2 diabetes.

AB - Aims/hypothesis The recent advent of genome-wide association studies has considerably accelerated the identification of type 2 diabetes loci. We aimed to investigate the combined effects of multiple genetic variants, alone or in combination with conventional risk factors, on type 2 diabetes and diabetes-related traits in Han Chinese. Methods We genotyped17variantsin17lociina population-based Han Chinese cohort including 3,210 unrelated individuals. A genetic risk score (GRS) was calculated on the basis of these variants. The discriminatory ability was assessed by the area under the receiver operating characteristics curve. Results The odds ratio for type 2 diabetes and hyperglycaemia with each GRS point (per risk allele) was 1.18 (95% CI 1.12-1.23, p = 1.3x 10-12) and 1.12 (95% CI 1.091.16, p=7.5 x10-14), respectively. Compared with participants with GRS ≤11.0 (7.63%), those with GRS ≥19.0 (8.87%) had a 4.58-fold higher risk (95% CI 2.49-8.42) of type 2 diabetes. The GRS also showed a significant association with lower beta cell function estimated by HOMA of beta cell function (p=8.4 x10-10). In addition, we observed significant interactive effects between GRS and BMI on fasting glucose and HbA1c levels (p=0.04 and p=0.03 for interaction, respectively). Discrimination of diabetes risk was improved (p<0.001) when the GRS was added to a model including clinical risk factors. The AUCs were 0.62 and 0.77, respectively, for the GRS and conventional clinic risk factors alone, and 0.79 when the GRS was added. Conclusions/interpretation In this Han Chinese population, the GRS of 17 combined variants modestly but significantly improved discrimination of the conventional risk factors for type 2 diabetes.

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Combined effects of 17 common genetic variants on type 2 diabetes risk in a Han Chinese population

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