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. 2018 Jul;111(1):50-61.
doi: 10.5935/abc.20180107. Epub 2018 Jul 2.

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

[Article in English, Portuguese]
Andreia Pereira  1 , Maria Isabel Mendonça  1 , Sofia Borges  1 , Sónia Freitas  1 , Eva Henriques  1 , Mariana Rodrigues  1 , Ana Isabel Freitas  2 , Ana Célia Sousa  1 , António Brehm  2 , Roberto Palma Dos Reis  3
Affiliations

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

[Article in English, Portuguese]
Andreia Pereira et al. Arq Bras Cardiol. 2018 Jul.

Abstract

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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Conflict of interest statement

Potential Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Figures

Figure 1
Figure 1
Distribution of the number of risk alleles by cases and controls. A logistic regression model was used to determine the coronary artery disease risk by the number of risk alleles compared to the number of reference alleles (23 alleles, in relation to the median value of the controls). Dots: regression analysis odds ratio for coronary artery disease.
Figure 2
Figure 2
Distribution of genetic risk score in deciles by cases and controls. A logistic regression model was used with the 5th decile of the controls as the reference class.
Figure 3
Figure 3
ROC curves based on the baseline model (traditional risk factors, TRFs) and after adding the genetic risk score (GRS) (quartiles) in predicting the risk for coronary artery disease. The two curves are based on logistic regression models incorporating conventional risk factors (diabetes, dyslipidemia, smoking and hypertension) with and without the GRS. AUC indicates area under curve. The Delong test compares the difference between the two AUCs (p < 0.0001).
See this image and copyright information in PMC

Comment in

  • Genetic Risk in Coronary Artery Disease.
    Martinez PF, Okoshi MP. Martinez PF, et al. Arq Bras Cardiol. 2018 Jul;111(1):62-63. doi: 10.5935/abc.20180130. Arq Bras Cardiol. 2018. PMID: 30110045 Free PMC article. No abstract available.

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