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Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants

Bibliographic Details
Main Author: Pereira, Andreia
Publication Date: 2018
Other Authors: Mendonça, Maria Isabel, Borges, Sofia, Freitas, Sónia, Henriques, Eva, Rodrigues, Mariana, Freitas, Ana Isabel, Sousa, Ana Célia, Brehm, António, Reis, Roberto Palma Dos
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/41346
Summary: BACKGROUND: Genetic risk score can quantify individual's predisposition to coronary artery disease; however, its usefulness as an independent risk predictor remains inconclusive. OBJECTIVE: To evaluate the incremental predictive value of a genetic risk score to traditional risk factors associated with coronary disease. METHODS: Thirty-three genetic variants previously associated with coronary disease were analyzed in a case-control population with 2,888 individuals. A multiplicative genetic risk score was calculated and then divided into quartiles, with the 1st quartile as the reference class. Coronary risk was determined by logistic regression analysis. Then, a second logistic regression was performed with traditional risk factors and the last quartile of the genetic risk score. Based on this model, two ROC curves were constructed with and without the genetic score and compared by the Delong test. Statistical significance was considered when p values were less than 0.05. RESULTS: The last quartile of the multiplicative genetic risk score revealed a significant increase in coronary artery disease risk (OR = 2.588; 95% CI: 2.090-3.204; p < 0.0001). The ROC curve based on traditional risk factors estimated an AUC of 0.72, which increased to 0.74 when the genetic risk score was added, revealing a better fit of the model (p < 0.0001). CONCLUSIONS: In conclusion, a multilocus genetic risk score was associated with an increased risk for coronary disease in our population. The usual model of traditional risk factors can be improved by incorporating genetic data.
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spelling Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 VariantsCoronary artery disease/HistoryCoronary artery disease/morbidityEpidemiologyMortalityPolymorphism, GeneticRisk factorsBACKGROUND: Genetic risk score can quantify individual's predisposition to coronary artery disease; however, its usefulness as an independent risk predictor remains inconclusive. OBJECTIVE: To evaluate the incremental predictive value of a genetic risk score to traditional risk factors associated with coronary disease. METHODS: Thirty-three genetic variants previously associated with coronary disease were analyzed in a case-control population with 2,888 individuals. A multiplicative genetic risk score was calculated and then divided into quartiles, with the 1st quartile as the reference class. Coronary risk was determined by logistic regression analysis. Then, a second logistic regression was performed with traditional risk factors and the last quartile of the genetic risk score. Based on this model, two ROC curves were constructed with and without the genetic score and compared by the Delong test. Statistical significance was considered when p values were less than 0.05. RESULTS: The last quartile of the multiplicative genetic risk score revealed a significant increase in coronary artery disease risk (OR = 2.588; 95% CI: 2.090-3.204; p < 0.0001). The ROC curve based on traditional risk factors estimated an AUC of 0.72, which increased to 0.74 when the genetic risk score was added, revealing a better fit of the model (p < 0.0001). CONCLUSIONS: In conclusion, a multilocus genetic risk score was associated with an increased risk for coronary disease in our population. The usual model of traditional risk factors can be improved by incorporating genetic data.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)RUNPereira, AndreiaMendonça, Maria IsabelBorges, SofiaFreitas, SóniaHenriques, EvaRodrigues, MarianaFreitas, Ana IsabelSousa, Ana CéliaBrehm, AntónioReis, Roberto Palma Dos2018-07-10T22:08:03Z2018-072018-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article11application/pdfhttp://hdl.handle.net/10362/41346eng0066-782XPURE: 5410428https://doi.org/10.5935/abc.20180107info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:33:48Zoai:run.unl.pt:10362/41346Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:04:46.838209Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants
title Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants
spellingShingle Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants
Pereira, Andreia
Coronary artery disease/History
Coronary artery disease/morbidity
Epidemiology
Mortality
Polymorphism, Genetic
Risk factors
title_short Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants
title_full Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants
title_fullStr Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants
title_full_unstemmed Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants
title_sort Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants
author Pereira, Andreia
author_facet Pereira, Andreia
Mendonça, Maria Isabel
Borges, Sofia
Freitas, Sónia
Henriques, Eva
Rodrigues, Mariana
Freitas, Ana Isabel
Sousa, Ana Célia
Brehm, António
Reis, Roberto Palma Dos
author_role author
author2 Mendonça, Maria Isabel
Borges, Sofia
Freitas, Sónia
Henriques, Eva
Rodrigues, Mariana
Freitas, Ana Isabel
Sousa, Ana Célia
Brehm, António
Reis, Roberto Palma Dos
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
RUN
dc.contributor.author.fl_str_mv Pereira, Andreia
Mendonça, Maria Isabel
Borges, Sofia
Freitas, Sónia
Henriques, Eva
Rodrigues, Mariana
Freitas, Ana Isabel
Sousa, Ana Célia
Brehm, António
Reis, Roberto Palma Dos
dc.subject.por.fl_str_mv Coronary artery disease/History
Coronary artery disease/morbidity
Epidemiology
Mortality
Polymorphism, Genetic
Risk factors
topic Coronary artery disease/History
Coronary artery disease/morbidity
Epidemiology
Mortality
Polymorphism, Genetic
Risk factors
description BACKGROUND: Genetic risk score can quantify individual's predisposition to coronary artery disease; however, its usefulness as an independent risk predictor remains inconclusive. OBJECTIVE: To evaluate the incremental predictive value of a genetic risk score to traditional risk factors associated with coronary disease. METHODS: Thirty-three genetic variants previously associated with coronary disease were analyzed in a case-control population with 2,888 individuals. A multiplicative genetic risk score was calculated and then divided into quartiles, with the 1st quartile as the reference class. Coronary risk was determined by logistic regression analysis. Then, a second logistic regression was performed with traditional risk factors and the last quartile of the genetic risk score. Based on this model, two ROC curves were constructed with and without the genetic score and compared by the Delong test. Statistical significance was considered when p values were less than 0.05. RESULTS: The last quartile of the multiplicative genetic risk score revealed a significant increase in coronary artery disease risk (OR = 2.588; 95% CI: 2.090-3.204; p < 0.0001). The ROC curve based on traditional risk factors estimated an AUC of 0.72, which increased to 0.74 when the genetic risk score was added, revealing a better fit of the model (p < 0.0001). CONCLUSIONS: In conclusion, a multilocus genetic risk score was associated with an increased risk for coronary disease in our population. The usual model of traditional risk factors can be improved by incorporating genetic data.
publishDate 2018
dc.date.none.fl_str_mv 2018-07-10T22:08:03Z
2018-07
2018-07-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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format article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/41346
url http://hdl.handle.net/10362/41346
dc.language.iso.fl_str_mv eng
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dc.relation.none.fl_str_mv 0066-782X
PURE: 5410428
https://doi.org/10.5935/abc.20180107
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eu_rights_str_mv openAccess
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dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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