Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population

• Autor(a) principal: Mendonça,Maria Isabel
• Data de Publicação: 2021
• Outros Autores: Henriques,Eva, Borges,Sofia, Sousa,Ana Célia, Pereira,Andreia, Santos,Marina, Temtem,Margarida, Freitas,Sónia, Monteiro,Joel, Sousa,João Adriano, Rodrigues,Ricardo, Guerra,Graça, Reis,Roberto Palma dos
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Genetics and Molecular Biology
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572021000300113
• topic: Traditional risk factors; genetic risk score; events risk discrimination and reclassification; Net Reclassification Index; secondary prevention of coronary artery disease

Abstract The inclusion of a genetic risk score (GRS) can modify the risk prediction of coronary artery disease (CAD), providing an advantage over the use of traditional models. The predictive value of the genetic information on the recurrence of major adverse cardiovascular events (MACE) remains controversial. A total of 33 genetic variants previously associated with CAD were genotyped in 1587 CAD patients from the GENEMACOR study. Of these, 18 variants presented an hazard ratio >1, so they were selected to construct a weighted GRS (wGRS). MACE discrimination and reclassification were evaluated by C-Statistic, Net Reclassification Index and Integrated Discrimination Improvement methodologies. After the addition of wGRS to traditional predictors, the C-index increased from 0.566 to 0.572 (p=0.0003). Subsequently, adding wGRS to traditional plus clinical risk factors, this model slightly improved from 0.620 to 0.622 but with statistical significance (p=0.004). NRI showed that 17.9% of the cohort was better reclassified when the primary model was associated with wGRS. The Kaplan-Meier estimator showed that, at 15-year follow-up, the group with a higher number of risk alleles had a significantly higher MACE occurrence (p=0.011). In CAD patients, wGRS improved MACE risk prediction, discrimination and reclassification over the conventional factors, providing better cost-effective therapeutic strategies.