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Cumulative Effect of Common Genetic Variants Predicts Incident Type2 Diabetes: A Study of 21,183 Subjects from Three Large Prospective Cohorts

Jingyun Yang and Jinying Zhao

Recent genome-wide association studies (GWAS) and their meta-analyses have identified multiple genetic loci that are associated with type 2 diabetes (T2D). Except for variants in the TCF7L2 gene which had a modest effect on diabetic risk, most genetic variants identified so far have only a weak association with diabetes. It is possible that the combination of multiple variants may have a larger effect on disease risk and improve risk prediction. In this study, we focus on SNPs that had been robustly replicated in previous GWAS and were also genotyped in a large sample of 21,183 participants from three large prospective cohorts, including Atherosclerosis Risk in Communities (ARIC) Study, Framingham Offspring Study (FOS) and Multi-Ethnic Study of Atherosclerosis (MESA). Among these, we were able to successfully confirm the associations of 12 SNPs with baseline prevalent T2D in these two cohorts. A genotype risk score (GRS) using these12 risk variants was constructed to examine whether GRS predicts incident diabetes. In a combined meta-analysis, subjects in the highest tertile of GRS had a 1.62-fold increased risk of incident T2D (95% CI, 1.08-2.44, P=1.5×10-14) compared to those in the lowest tertile of GRS after adjustment for age, sex, race, smoking, body mass index (BMI), lipids (HDL and LDL) and systolic blood pressure. Moreover, GRS significantly improves risk prediction and reclassification in T2D beyond known risk factors.