Genetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variants
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
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/10362/41346 |
Resumo: | 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. |
id |
RCAP_b59b458e54ba04bf5c60643f04712a09 |
---|---|
oai_identifier_str |
oai:run.unl.pt:10362/41346 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
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:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:22:18Zoai:run.unl.pt:10362/41346Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:31:20.928343Repositório 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 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 |
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/10362/41346 |
url |
http://hdl.handle.net/10362/41346 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0066-782X PURE: 5410428 https://doi.org/10.5935/abc.20180107 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
11 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) |
collection |
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 |
repository.mail.fl_str_mv |
|
_version_ |
1799137936526016512 |