Dataset Information

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

ABSTRACT: 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, disease onset.This paper assessed 18 recently identified T2D loci for their potential role in diabetes prediction. We built a new predictive genetic test for T2D using the Framingham Heart Study dataset. Using logistic regression and 15 additional loci, the new test was slightly improved over the existing test using just three loci. A formal comparison between the two tests suggests no significant improvement. We further formed a predictive genetic test for identifying early onset T2D and found higher classification accuracy for this test, not only indicating that these 18 loci have great potential for predicting early onset T2D, but also suggesting that they may play important roles in causing early-onset T2D.To further improve the test's accuracy, we applied a newly developed nonparametric method capable of capturing high order interactions to the data, but it did not outperform a logistic regression that only considers single-locus effects. This could be explained by the absence of gene-gene interactions among the 18 loci.

SUBMITTER: Lu Q

PROVIDER: S-EPMC2795948 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Lu Qing Q Song Yeunjoo Y Wang Xuefeng X Won Sungho S Cui Yuehua Y Elston Robert C RC

BMC proceedings 20091215

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 fac ...[more]

PMID: 20018041

Similar Datasets

Project description:Type 2 diabetes mellitus incidence is increased in HIV-infected persons. We examined the associations of diabetes mellitus with known diabetes mellitus-risk alleles from the general population in the context of HIV infection, and explored effect modification by combination antiretroviral therapy (cART).The Women's Interagency HIV Study is a prospective cohort of HIV-infected women. Seventeen European-derived diabetes mellitus-risk polymorphisms were genotyped in the eligible participants of the Women's Interagency HIV Study. Analyses were run separately for non-African Americans (Whites, Hispanics, Asians, and other; n?=?378, 49 with incident diabetes mellitus) and African Americans (n?=?591, 49 with incident diabetes mellitus). Cox proportional-hazards models were fit to estimate hazard ratios for diabetes mellitus overall and within strata of cART.In non-African Americans, heterogeneity across cART regimen was observed for nine of the 14 polymorphisms (phet?<?0.05). One polymorphism was statistically significantly inversely associated with diabetes mellitus risk among women taking two nucleotide reverse transcriptase inhibitors (NRTIs) + non-nucleotide reverse transcriptase inhibitor (NNRTI). Five polymorphisms were statistically significantly associated with diabetes mellitus among women treated with at least two NRTIs?+?at least one protease inhibitor and one polymorphism was associated with diabetes mellitus among those treated with at least three NRTIs?±?NNRTI. The hazard ratio per risk allele for IGF2BP2 rs1470579 was 2.67 (95% confidence interval 1.67-4.31) for women taking cART with at least two NRTIs?+?at least one protease inhibitor and 2.45 (95% confidence interval 1.08-5.53) in women taking at least three NRTIs?±?NNRTI (phet?=?2.50?×?10?³). No such associations were observed in the African Americans.Genetic susceptibility to diabetes mellitus, based on the variants studied, is substantially elevated among HIV-infected women using cART containing three or more NRTI/protease inhibitor components. A personalized medicine approach to cART selection may be indicated for HIV-infected persons carrying these diabetes mellitus-risk variants.

Project description:BackgroundStatin treatment and variants in the gene encoding HMG-CoA reductase are associated with reductions in both the concentration of LDL cholesterol and the risk of coronary heart disease, but also with modest hyperglycaemia, increased bodyweight, and modestly increased risk of type 2 diabetes, which in no way offsets their substantial benefits. We sought to investigate the associations of LDL cholesterol-lowering PCSK9 variants with type 2 diabetes and related biomarkers to gauge the likely effects of PCSK9 inhibitors on diabetes risk.MethodsIn this mendelian randomisation study, we used data from cohort studies, randomised controlled trials, case control studies, and genetic consortia to estimate associations of PCSK9 genetic variants with LDL cholesterol, fasting blood glucose, HbA1c, fasting insulin, bodyweight, waist-to-hip ratio, BMI, and risk of type 2 diabetes, using a standardised analysis plan, meta-analyses, and weighted gene-centric scores.FindingsData were available for more than 550 000 individuals and 51 623 cases of type 2 diabetes. Combined analyses of four independent PCSK9 variants (rs11583680, rs11591147, rs2479409, and rs11206510) scaled to 1 mmol/L lower LDL cholesterol showed associations with increased fasting glucose (0·09 mmol/L, 95% CI 0·02 to 0·15), bodyweight (1·03 kg, 0·24 to 1·82), waist-to-hip ratio (0·006, 0·003 to 0·010), and an odds ratio for type diabetes of 1·29 (1·11 to 1·50). Based on the collected data, we did not identify associations with HbA1c (0·03%, -0·01 to 0·08), fasting insulin (0·00%, -0·06 to 0·07), and BMI (0·11 kg/m2, -0·09 to 0·30).InterpretationPCSK9 variants associated with lower LDL cholesterol were also associated with circulating higher fasting glucose concentration, bodyweight, and waist-to-hip ratio, and an increased risk of type 2 diabetes. In trials of PCSK9 inhibitor drugs, investigators should carefully assess these safety outcomes and quantify the risks and benefits of PCSK9 inhibitor treatment, as was previously done for statins.FundingBritish Heart Foundation, and University College London Hospitals NHS Foundation Trust (UCLH) National Institute for Health Research (NIHR) Biomedical Research Centre.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets