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

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 controversia...

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Autores principales: Mendonça, Maria Isabel, Henriques, Eva, Borges, Sofia, Sousa, Ana Célia, Pereira, Andreia, Santos, Marina, Temtem, Margarida, Freitas, Sónia, Monteiro, Joel, Sousa, João Adriano, Rodrigues, Ricardo, Guerra, Graça, dos Reis, Roberto Palma
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sociedade Brasileira de Genética 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201463/
https://www.ncbi.nlm.nih.gov/pubmed/34137427
http://dx.doi.org/10.1590/1678-4685-GMB-2020-0448
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author Mendonça, Maria Isabel
Henriques, Eva
Borges, Sofia
Sousa, Ana Célia
Pereira, Andreia
Santos, Marina
Temtem, Margarida
Freitas, Sónia
Monteiro, Joel
Sousa, João Adriano
Rodrigues, Ricardo
Guerra, Graça
dos Reis, Roberto Palma
author_facet Mendonça, Maria Isabel
Henriques, Eva
Borges, Sofia
Sousa, Ana Célia
Pereira, Andreia
Santos, Marina
Temtem, Margarida
Freitas, Sónia
Monteiro, Joel
Sousa, João Adriano
Rodrigues, Ricardo
Guerra, Graça
dos Reis, Roberto Palma
author_sort Mendonça, Maria Isabel
collection PubMed
description 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.
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spelling pubmed-82014632021-06-24 Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population Mendonça, Maria Isabel Henriques, Eva Borges, Sofia Sousa, Ana Célia Pereira, Andreia Santos, Marina Temtem, Margarida Freitas, Sónia Monteiro, Joel Sousa, João Adriano Rodrigues, Ricardo Guerra, Graça dos Reis, Roberto Palma Genet Mol Biol Human and Medical Genetics 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. Sociedade Brasileira de Genética 2021-06-11 /pmc/articles/PMC8201463/ /pubmed/34137427 http://dx.doi.org/10.1590/1678-4685-GMB-2020-0448 Text en https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License
spellingShingle Human and Medical Genetics
Mendonça, Maria Isabel
Henriques, Eva
Borges, Sofia
Sousa, Ana Célia
Pereira, Andreia
Santos, Marina
Temtem, Margarida
Freitas, Sónia
Monteiro, Joel
Sousa, João Adriano
Rodrigues, Ricardo
Guerra, Graça
dos Reis, Roberto Palma
Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population
title Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population
title_full Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population
title_fullStr Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population
title_full_unstemmed Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population
title_short Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population
title_sort genetic information improves the prediction of major adverse cardiovascular events in the genemacor population
topic Human and Medical Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201463/
https://www.ncbi.nlm.nih.gov/pubmed/34137427
http://dx.doi.org/10.1590/1678-4685-GMB-2020-0448
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