INTRODUCTION: Coronary artery disease (CAD), characterized by an atherogenic process in the coronary arteries, is one of the leading causes of death in Madeira. The GENEMACOR (GENEs in MAdeira and CORonary Disease) study sought to investigate the main risk factors - environmental and genetic - and estimate whether a genetic risk score (GRS) improves CAD prediction, discrimination and reclassification.
METHODS: Traditional risk factors and 33 CAD genetic variants were considered in a case-control study with 3139 individuals (1723 patients and 1416 controls). The multivariate analysis assessed the likelihood of CAD. A multiplicative GRS (mGRS) was created, and two models (with and without mGRS) were prepared. Two areas under receiver operating characteristic curve (area under curve (AUC)) were analyzed and compared to discriminate CAD likelihood. Net reclassification improvement (NRI) and integrated discrimination index (IDI) were used to reclassify the population.
RESULTS: All traditional risk factors were strong and independent predictors of CAD, with smoking being the most significant (OR 3.25; p<0.0001). LPA rs3798220 showed a higher CAD likelihood (odds ratio 1.45; p<0.0001). Individuals in the fourth mGRS quartile had an increased CAD probability of 136% (p<0.0001). A traditional risk factor-based model estimated an AUC of 0.73, rising to 0.75 after mGRS inclusion (p<0.0001), revealing a better fit. Continuous NRI better reclassified 28.1% of the population, and categorical NRI mainly improved the reclassification of the intermediate risk group.
CONCLUSIONS: CAD likelihood was influenced by traditional risk factors and genetic variants. Incorporating GRS into the traditional model improved CAD predictive capacity, discrimination and reclassification. These approaches may provide helpful diagnostic and therapeutic advances, especially in the intermediate risk group.