Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.26/38669 |
Resumo: | 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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Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR populationTraditional risk factorsgenetic risk scoreevents risk discrimination and reclassificationNet Reclassification Indexsecondary prevention of coronary artery diseaseThe 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.Repositório ComumMendonca, Maria IsabelHenriques, EvaBorges, SofiaSousa, Ana CéliaPereira, AndreiaSantos, MarinaTemtem, MargaridaFreitas, SóniaMonteiro, JoelSousa, João AdrianoRodrigues, RicardoGuerra, GraçaPalma Reis, Roberto2022-01-06T14:47:38Z2021-062021-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.26/38669engMendonça MI, Henriques E, Borges S, et al. Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population. Genet Mol Biol. 2021;44(2):e20200448. Published 2021 Jun 11. doi:10.1590/1678-4685-GMB-2020-044810.1590/1678-4685-gmb-2020-0448info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-10T02:18:57Zoai:comum.rcaap.pt:10400.26/38669Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:34:37.269990Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
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 |
spellingShingle |
Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population Mendonca, Maria Isabel Traditional risk factors genetic risk score events risk discrimination and reclassification Net Reclassification Index secondary prevention of coronary artery disease |
title_short |
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_sort |
Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population |
author |
Mendonca, Maria Isabel |
author_facet |
Mendonca, 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 Palma Reis, Roberto |
author_role |
author |
author2 |
Henriques, Eva Borges, Sofia Sousa, Ana Célia Pereira, Andreia Santos, Marina Temtem, Margarida Freitas, Sónia Monteiro, Joel Sousa, João Adriano Rodrigues, Ricardo Guerra, Graça Palma Reis, Roberto |
author2_role |
author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório Comum |
dc.contributor.author.fl_str_mv |
Mendonca, 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 Palma Reis, Roberto |
dc.subject.por.fl_str_mv |
Traditional risk factors genetic risk score events risk discrimination and reclassification Net Reclassification Index secondary prevention of coronary artery disease |
topic |
Traditional risk factors genetic risk score events risk discrimination and reclassification Net Reclassification Index secondary prevention of coronary artery disease |
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. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06 2021-06-01T00:00:00Z 2022-01-06T14:47:38Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.26/38669 |
url |
http://hdl.handle.net/10400.26/38669 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Mendonça MI, Henriques E, Borges S, et al. Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population. Genet Mol Biol. 2021;44(2):e20200448. Published 2021 Jun 11. doi:10.1590/1678-4685-GMB-2020-0448 10.1590/1678-4685-gmb-2020-0448 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799134908009938944 |