Polygenetic risk for coronary artery disease increases hospitalization burden and mortality

BACKGROUND: Coronary artery disease (CAD) is a leading cause of death worldwide and increasing cost for society. Genome wide association studies (GWAS) have identified common variants associated with CAD. Combining single nucleotide polymorphisms (SNPs) into a genetic risk score (GRS) can estimate an individual's genetic burden. OBJECTIVES: To investigate whether GRS for CAD can predict hospitalization and mortality. METHODS: 23,594 individuals without CAD at baseline and with full data for all covariates from the population based prospective study Malmö diet and cancer study were investigated. The association between hospitalizations was calculated by negative binomial regression and risk of mortality was calculated by Cox proportional hazards regression. The GRS was constructed from 50 SNPs. RESULTS: The study population was divided into quintiles according to the value of GRS. During the mean follow-up time of 17.8 years, 17,254 individuals were hospitalized at least once. Individuals in the highest quintile of GRS were hospitalized 10% more often than individuals in the lowest quintile (IRR: 1.10 [95% CI 1.04–1.16], p = 0.001), mainly for cardiovascular reasons (IRR: 1.31 [95% CI 1.20–1.43], p = 5.17 × 10(−10)). These individuals had highly increased risk of CVD mortality (HR: 1.44 [1.25–1.66], p = 6.56 × 10(−7)) but not the risk of mortality due to other causes. CONCLUSION: Our results suggest that genetic predisposition for CAD can predict hospitalization burden and mortality, especially due to cardiovascular causes, independently of traditional risk factors. As the risk conferred by the GRS is partially modifiable, our results may help to reduce societal costs, individual suffering and prolong life.