publication . Article . 2009

the effect of multiple genetic variants in predicting the risk of type 2 diabetes

Lu, Qing; Song, Yeunjoo; Wang, Xuefeng; Won, Sungho; Cui, Yuehua; Elston, Robert C;
Open Access
  • Published: 01 Dec 2009 Journal: BMC Proceedings, volume 3 (eissn: 1753-6561, Copyright policy)
  • Publisher: Springer Nature
While recently performed genome-wide association studies have advanced the identification of genetic variants predisposing to type 2 diabetes (T2D), the potential application of these novel findings for disease prediction and prevention has not been well studied. Diabetes prediction and prevention have become urgent issues owing to the rapidly increasing prevalence of diabetes and its associated mortality, morbidity, and health care cost. New prediction approaches using genetic markers could facilitate early identification of high risk sub-groups of the population so that appropriate prevention methods could be effectively applied to delay, or even prevent, dise...
free text keywords: General Biochemistry, Genetics and Molecular Biology, General Medicine, Disease, Bioinformatics, Type 2 diabetes, medicine.disease, medicine, Diabetes mellitus, Health care, business.industry, business, Genetic marker, Population, education.field_of_study, education, Genetic association, Framingham Heart Study, Proceedings
Funded by
  • Funder: Wellcome Trust (WT)
NIH| Genetic Analysis of Common Diseases: An Evaluation
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM031575-22
NSF| Statistical methods for mapping imprinted genes underlying complex traits
  • Funder: National Science Foundation (NSF)
  • Project Code: 0707031
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Mathematical Sciences
NIH| Case Comprehensive Cancer Center Support Grant
  • Funder: National Institutes of Health (NIH)
  • Project Code: 3P30CA043703-20S1

Larkin, M. Diet and exercise delay onset of type 2 diabetes, say US experts. Lancet. 2001; 358: 565 [PubMed] [DOI]

Weedon, MN, McCarthy, MI, Hitman, G, Walker, M, Groves, CJ, Zeggini, E, Rayner, NW, Shields, B, Owen, KR, Hattersley, AT, Frayling, TM. Combining information from common type 2 diabetes risk polymorphisms improves disease prediction. PLoS Med. 2006; 3: e374 [OpenAIRE] [PubMed] [DOI]

Lango, H, Palmer, CN, Morris, AD, Zeggini, E, Hattersley, AT, McCarthy, MI, Frayling, TM, Weedon, MN. Assessing the combined impact of 18 common genetic variants of modest effect sizes on type 2 diabetes risk. Diabetes. 2008; 57: 3129-3135 [OpenAIRE] [PubMed] [DOI]

van Hoek, M, Dehghan, A, Witteman, JC, van Duijn, CM, Uitterlinden, AG, Oostra, BA, Hofman, A, Sijbrands, EJ, Janssens, AC. Predicting type 2 diabetes based on polymorphisms from genome-wide association studies: a population-based study. Diabetes. 2008; 57: 3122-3128 [OpenAIRE] [PubMed] [DOI]

Lu, Q, Obuchowski, N, Won, S, Zhu, X, Elston, RC. Using the optimal robust receiver operating characteristic curve for predictive genetic tests. Biometrics.

Hanson, RL, Elston, RC, Pettitt, DJ, Bennett, PH, Knowler, WC. Segregation analysis of non-insulin-dependent diabetes mellitus in Pima Indians: evidence for a major-gene effect. Am J Hum Genet. 1995; 57: 160-170 [OpenAIRE] [PubMed]

Peduzzi, P, Concato, J, Kemper, E, Holford, TR, Feinstein, AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996; 49: 1373-1379 [OpenAIRE] [PubMed] [DOI]

Egan, JP. Signal Detection Theory and ROC Analysis. 1975

Lu, Q, Elston, RC. Using the optimal receiver operating characteristic curve to design a predictive genetic test, exemplified with type 2 diabetes. Am J Hum Genet. 2008; 82: 641-651 [OpenAIRE] [PubMed] [DOI]

Aguilar-Salinas, CA, Reyes-Rodríguez, E, Ordóñez-Sánchez, ML, Torres, MA, Ramírez-Jiménez, S, Domínguez-López, A, Martínez-Francois, JR, Velasco-Pérez, ML, Alpizar, M, García-García, E, Gómez-Pérez, F, Rull, J, Tusié-Luna, MT. Early-onset type 2 diabetes: metabolic and genetic characterization in the Mexican population. J Clin Endocrinol Metab. 2001; 86: 220-226 [OpenAIRE] [PubMed] [DOI]

Zeggini, E, Weedon, MN, Lindgren, CM, Frayling, TM, Elliott, KS, Lango, H, Timpson, NJ, Perry, JR, Rayner, NW, Freathy, RM, Barrett, JC, Shields, B, Morris, AP, Ellard, S, Groves, CJ, Harries, LW, Marchini, JL, Owen, KR, Knight, B, Cardon, LR, Walker, M, Hitman, GA, Morris, AD, Doney, AS, McCarthy, MI, Hattersley, AT. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007; 316: 1336-1341 [OpenAIRE] [PubMed] [DOI]

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