ABC | Volume 111, Nº1, July 2018

Original Article Pereira et al. Genes and coronary artery disease risk Arq Bras Cardiol. 2018; 111(1):50-61 Table 5 – Reclassification table comparing predicted coronary artery disease (CAD) risk with and without genetic risk score (GRS) quartiles Predicted risk (without GRS) Reclassified predicted risk (with GRS) % Increase %/ Decrease CAD patients (n = 1,566) < 25% 25-50% 50-75% 75-100% < 25% 6 11 0 0 0,7% 0% 25-50% 44 335 123 0 7,9% 2.8% 50-75% 0 59 471 305 19,5% 3.8% 75-100% 0 0 9 203 0% 0.6% NRI CAD patients 20.9% Healthy controls (n = 1,322) < 25% 65 36 0 0 2,7% 0% 25-50% 186 504 88 0 6,7% 14.1% 50-75% 0 60 268 79 6% 4.5% 75-100% 0 0 1 35 0% 0.1% NRI controls 3.3% NRI total 24.2% NRI: net reclassification improvement (categorical NRI); CAD: coronary artery disease. In our study, we found a gradual and continual increase in CAD risk with increasing number of CAD risk alleles carried. Individuals in the bottom decile are naturally protected and subjects in top decile of the GRS had a CAD risk of 2.472 (1.755 – 3.482). Even though the score distribution overlaps between cases and controls, the GRS is significantly associated with CAD risk and can be used to identify subjects at highest risk in terms of lifestyle or therapeutic interventions. Our results are similar to others reports in Caucasians populations where GRS with 13, 29 or 109 SNPs 22-24 were independent and marginally increased the predictive power of TRF conferred either by AUC increases, C-index changes or more modern discriminative statistical methods like reclassification measures or improved discrimination. We report a higher OR for the 4 th quartile of GRS (2.59) compared to 1.66 reported by Ripatti et al. in the highest quintile. 22 When comparing the relative weight of the GRS in the multivariate logistic analysis we found slightly lower OR than smoking, hypertension, and dyslipidemia. In Ripatti´s 22 cohort, a weighted GRS was also an independent predictor even after adjusting for age, sex and TRFs in a Northern European population-based trial. The relative risk of the GRS based on 13-SNP was also lower than that of dyslipidemia and comparable to the effects of hypertension. 22 An increased power to TRFs definition has been given in this study. For instance, we have used a broad dyslipidemia term including Apo B levels as indicated by 2016 lipid guidelines. 7 Moreover, we have not considered ex-smokers until 5 years of cessation to account for the risk for CV disease events decrease be comparable to a nonsmoker. 5 Thanassoulis et al. 24 demonstrated that adding to a 13 SNP-based GRS, 89 SNPs associated with modifiable risk factors did not increase the power of the GRS reporting a HR of 1.01 (95% CI 0.99 –1.03; p = 0.48). This revealed that the weak association of polymorphisms with CAD risk factors in GRS analysis could be masked by the relative stronger effect of other polymorphisms. Considering the lack of a significant association of lipid profiles with CAD risk, Jansen et al. reported in 2015 that several SNPs associated with type 2 diabetes mellitus were related with CAD risk. 25 Recently, Webb et al. identified 6 new loci associated with CAD at genome-wide significance. The study confirmed a pleiotropy between lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior. 26 Our GRS is an assembly of risk factors and non-risk factors-related SNP, reinforcing the genotype-phenotype interactions. Limitations of this study The main clinical utility of the GRS in our population is a modest improvement in risk stratification. GRS seems to be a better indicator of patients at a higher than average risk for DAC as compared with TRF stratification. The number and type of SNPs included is limited in our study and a larger number of GWAS hit SNPs should be included in further studies. Nevertheless, the increasing capability of analyzing multiple SNPs in GRS so far have not been translated into increasing ability of risk prediction. Finally, this study did not include a gene-gene (G-G) and gene-environment (G-E) analysis. It is expected that, as better statistical significance arises from those interplays, the G-G and G-E incorporation in GRS plus TRF will increase our ability to accurately and individually predict risk. Conclusions We conclude that a multilocus GRS based on multiple variants of genetic risk was associated to an increased cardiovascular risk in a Portuguese population. We found that a GRS calculated with the 31 studied SNPs was significantly associated to CAD and that 25% of individuals who carry the greatest risk alleles have, approximately, 57