Diabetes Care · 2010 · 175 citations · 14 references
Life SciencesBiostatisticsGeneticsEpidemiologyGenetic EpidemiologyMedical GeneticsDiabetes MellitusGenetic RiskGenetic Risk AssessmentGenetic Risk FactorsGenetic Risk PredictionGenetic SusceptibilityDisease Risk PredictionGenetic Risk StratificationGenetic Risk VariantsLogistic RegressionReclassificationRisk Allele FrequencySingle Nucleotide Polymorphism-based PredictionType 2 Diabetes Risk Assessment
OBJECTIVE: To test if knowledge of type 2 diabetes genetic variants improves disease prediction. RESEARCH DESIGN AND METHODS: We tested 40 single nucleotide polymorphisms (SNPs) associated with diabetes in 3,471 Framingham Offspring Study subjects followed over 34 years using pooled logistic regression models stratified by age (<50 years, diabetes cases = 144; or ≥50 years, diabetes cases = 302). Models included clinical risk factors and a 40-SNP weighted genetic risk score. RESULTS: In people <50 years of age, the clinical risk factors model C-statistic was 0.908; the 40-SNP score increased it to 0.911 (P = 0.3; net reclassification improvement (NRI): 10.2%, P = 0.001). In people ≥50 years of age, the C-statistics without and with the score were 0.883 and 0.884 (P = 0.2; NRI: 0.4%). The risk per risk allele was higher in people <50 than ≥50 years of age (24 vs. 11%; P value for age interaction = 0.02). CONCLUSIONS: Knowledge of common genetic variation appropriately reclassifies younger people for type 2 diabetes risk beyond clinical risk factors but not older people.
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The Wellcome Trust Case Control Consortium, U.K.
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