Investigation of 89 candidate gene variants for effects on all-cause mortality following acute coronary syndrome

Abstract

Background: Many candidate genes have been reported to be risk factors for acute coronary syndrome (ACS), but their impact on clinical prognosis following ACS is unknown.

Methods: We examined the association of putative genetic risk factors with 3-year post-ACS mortality in 811 ACS survivors at university-affiliated hospitals in Kansas City, Missouri. Through a systematic literature search, we first identified genetic variants reported as susceptibility factors for atherosclerosis or ACS. Restricting our analysis to whites, so as to avoid confounding from racial admixture, we genotyped ACS cases for 89 genetic variants in 72 genes, and performed individual Kaplan-Meier survival analyses. We then performed Cox regression to create multivariate risk prediction models that further minimized potential confounding.

Results: Of 89 variants tested, 16 were potentially associated with mortality (P < 0.1 for all), of which 6 were significantly associated (P < 0.05) with mortality following ACS. While these findings are not more than what would be expected by chance (P = 0.28), even after Bonferroni correction and adjustment for traditional cardiac risk factors, the IRS1 972Arg variant association (P = 0.001) retained borderline statistical significance (P < 0.1).

Conclusion: With the possible exception of IRS1, we conclude that multiple candidate genes were not associated with post-ACS mortality in our patient cohort. Because of power limitations, the 16 gene variants with P values < 0.1 may warrant further study. Our data do not support the hypothesis that the remaining 73 genes have substantial, clinically significant association with mortality after an ACS.

Figure 1

Q-Q plot of Kaplan-Meier P values for 89 genetic variants. Observed log-rank P values for individual Kaplan-Meier analyses are plotted against random expectations under the null hypothesis of no effect.

Figure 2

Mean P value differences (observed-random) in 50,000 simulations. The right panel shows a skewed distribution of simulated random minus actual Kaplan-Meier log-rank P values (N = 89), indicating that observed P values collectively were lower than expected. With the removal of 16 positive associations (P < 0.1), the remaining genetic variables closely approximated a random distribution, as shown in the left panel.