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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

2018-07Artigo científico Acesso aberto
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dc.contributor.authorPereira, Andreia
dc.contributor.authorMendonça, Maria Isabel
dc.contributor.authorBorges, Sofia
dc.contributor.authorFreitas, Sónia
dc.contributor.authorHenriques, Eva
dc.contributor.authorRodrigues, Mariana
dc.contributor.authorFreitas, Ana Isabel
dc.contributor.authorSousa, Ana Célia
dc.contributor.authorBrehm, António
dc.contributor.authorPalma dos Reis, Roberto
dc.contributor.institutionNOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
dc.contributor.pblSociedade Brasileira de Cardiologia - SBC
dc.date.accessioned2018-07-10T22:08:03Z
dc.date.available2018-07-10T22:08:03Z
dc.date.issued2018-07
dc.description.abstractBACKGROUND: 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.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent11
dc.format.extent420897
dc.identifier.doi10.5935/abc.20180107
dc.identifier.issn0066-782X
dc.identifier.otherPURE: 5410428
dc.identifier.otherPURE UUID: d5ec3e13-1795-4c64-8e23-62be9b96a5f5
dc.identifier.otherPubMed: 29972410
dc.identifier.otherScopus: 85052297736
dc.identifier.otherWOS: 000441438000010
dc.identifier.urihttp://hdl.handle.net/10362/41346
dc.language.isoeng
dc.peerreviewedyes
dc.subjectCoronary artery disease/History
dc.subjectCoronary artery disease/morbidity
dc.subjectEpidemiology
dc.subjectMortality
dc.subjectPolymorphism, Genetic
dc.subjectRisk factors
dc.titleGenetic Risk Analysis of Coronary Artery Disease in a Population-based Study in Portugal, Using a Genetic Risk Score of 31 Variantsen
dc.typejournal article
degois.publication.firstPage50
degois.publication.issue1
degois.publication.lastPage61
degois.publication.titleArquivos Brasileiros De Cardiologia
degois.publication.volume111
dspace.entity.typePublication
rcaap.rightsopenAccess

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