Dataset Information
Personalized risk prediction for type 2 diabetes: the potential of genetic risk scores.
Ontology highlight
ABSTRACT: Purpose
Using effect estimates from genome-wide association studies (GWAS), we identified a genetic risk score (GRS) that has the strongest association with type 2 diabetes (T2D) status in a population-based cohort and investigated its potential for prospective T2D risk assessment.Methods
By varying the number of single-nucleotide polymorphisms (SNPs) and their respective weights, alternative versions of GRS can be computed. They were tested in 1,181 T2D cases and 9,092 controls of the Estonian Biobank cohort. The best-fitting GRS was chosen for the subsequent analysis of incident T2D (386 cases).Results
The best fit was provided by a novel doubly weighted GRS that captures the effect of 1,000 SNPs. The hazard for incident T2D was 3.45 times (95% CI: 2.31-5.17) higher in the highest GRS quintile compared with the lowest quintile, after adjusting for body mass index and other known predictors. Adding GRS to the prediction model for 5-year T2D risk resulted in continuous net reclassification improvement of 0.324 (95% CI: 0.211-0.444). In addition, a significant effect of the GRS on all-cause and cardiovascular mortality was observed.Conclusion
The proposed GRS would improve the accuracy of T2D risk prediction when added to the currently used set of predictors.Genet Med 19 3, 322-329.
SUBMITTER: Lall K
PROVIDER: S-EPMC5506454 | biostudies-literature | 2017 Mar
REPOSITORIES: biostudies-literature
Publications
Personalized risk prediction for type 2 diabetes: the potential of genetic risk scores.
Genetics in medicine : official journal of the American College of Medical Genetics 20160811 3
<h4>Purpose</h4>Using effect estimates from genome-wide association studies (GWAS), we identified a genetic risk score (GRS) that has the strongest association with type 2 diabetes (T2D) status in a population-based cohort and investigated its potential for prospective T2D risk assessment.<h4>Methods</h4>By varying the number of single-nucleotide polymorphisms (SNPs) and their respective weights, alternative versions of GRS can be computed. They were tested in 1,181 T2D cases and 9,092 controls ...[more]