Abstract MP58: Type 2 Diabetes Prediction with 17-, 40-, and 62-variant Genotype Risk Scores: The Framingham Offspring Study

Abstract

Background A recent genome-wide association study (GWAS) meta-analysis for type 2 diabetes (T2D) increased by 50% the number of common T2D-associated single-nucleotide polymorphisms (SNPs). We hypothesized that a genotype risk score (GRS) consisting of more SNPs improves T2D prediction achieved by published 17-SNP and 40-SNP scores. Methods We used data from four 8-year periods of the Framingham Offspring Study to test the association between effect-weighted 17-SNP, 40-SNP, and 62-SNP GRSs and incident T2D, defined by medication use and fasting glucose criteria. We used pooled logistic regression models with generalized estimating equations adjusted for 1) age and sex and 2) age, sex, parental T2D, BMI, systolic blood pressure, fasting glucose, HDL cholesterol, and triglyceride levels. Model improvement by the addition of each GRS was assessed with C statistics, integrated discrimination improvement (IDI) indices, and net reclassification improvement (NRI) indices with category thresholds at 2% and 8% cumulative incidence. Results Mean baseline age was 46, and 46.5% were men. There were 446 cases of incident T2D among 11,358 person-exams. In all models, the inclusion of a GRS resulted in significant T2D risk reclassification (NRI range 22.3-29.8%, see Table). The inclusion of a greater number of SNPs in the GRS increased the C statistics and relative IDI of the age- and sex-adjusted model, but the 62-SNP GRS did not result in a higher NRI than the 40-SNP GRS (28.6% vs. 29.8%). Similarly, the 62-SNP score did not result in a higher NRI for the fully adjusted clinical model than the 40-SNP score (25.6% vs. 29.0%). Conclusions A GRS of common susceptibility SNPs from GWAS improves T2D risk reclassification in a prospective study of adults, but incorporating a greater number of SNPs with smaller individual effect sizes may not result in additional reclassification improvement. Further advances in genotype prediction of T2D may require the identification and incorporation of functional risk variants putatively tagged by GWAS SNPs.