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Abstract

Click to add/remove this article to your list of 'My Favorites' A Genetic Risk Score To Improve the Prediction of Coronary Heart Disease in Type 2 Diabetes

Year: 2010

Abstract Number: 798-P

Authors: LU QI, LAYLA PARAST, CHRISTINE POWERS, TIANXI CAI, FRANK HU, ALESSANDRO DORIA

Institutions: Boston, MA

Results: Several genetic variants have been recently found to be associated with an increased risk of coronary heart disease (CHD) in the general population. The goal of our study was to evaluate whether these genetic markers also predict CHD in the presence of a major cardiovascular risk factor such as diabetes. Three studies of US White individuals with type 2 diabetes were considered: the prospective Nurses' Health Study (NHS; 309 CHD cases and 544 controls) and Health Professional Follow-up Study (HPFS; 345 CHD cases and 451 controls), and the cross-sectional Joslin Heart Study (JHS; 422 CHD cases and 436 controls). All study subjects were typed for fifteen risk variants identified by genome-wide association studies (GWAS). Five SNPs (rs4977574 [CDKN2A/2B], rs12526453 [PHACTR1], rs646776 [CELSR2-PSRC1-SORT1], rs2259816 [HNF1A], and rs11206510 [PCSK9] showed consistent associations with CHD in the three studies, with adjusted odds ratios (ORs; 95% CI) of 1.21 (1.08-1.35), 1.25 (1.10-1.41), 1.17 (1.02-1.34), 1.17 (1.04-1.32), and 1.26 (1.09-1.47) in the combined analyses, respectively. A genotype risk score (GRS) was created based on the number of risk alleles carried at these five genetic loci. After adjusting for clinical risk factors such as age, gender, MI, smoking status, HbA1c, and history of hypertension and hypercholesterolemia, the OR of CHD per GRS unit was 1.19 (95% CI 1.13- 1.26). Individuals with GRS ≥8 (44% of diabetic subjects) had a two-fold increase in CHD risk (OR=1.94, 95% CI 1.60-2.35) as compared to individuals with GRS ≤5 (31% of diabetic subjects). Prediction of CHD was significantly improved (p<0.001) when the GRS was added to a model including clinical predictors. The incremental predictive value of GRS, measured as the increase in the area under the receiver-operating characteristic curve (AUC) after adding GRS, was 0.0136 (95% CI 0.0084-0.0191). In conclusion, our results indicate that a genetic score based on five SNPs significantly improves CHD prediction among individuals with type 2 diabetes. Cost-effectiveness analyses are needed to determine whether such improvement warrants the introduction of these genetic tests into clinical practice.