Additional value of a combined genetic risk score to standard cardiovascular stratification

The utility of genetic risk scores (GRS) as independent risk predictors remains inconclusive. Here, we evaluate the additive value of a multi-locus GRS to the Framingham risk score (FRS) in coronary artery disease (CAD) risk prediction. A total of 2888 individuals (1566 coronary patients and 1322 co...

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Published in:Genetics and molecular biology 2018-10, Vol.41 (4), p.766-774
Main Authors: Pereira, Andreia, Mendonca, Maria Isabel, Borges, Sofia, Sousa, Ana Célia, Freitas, Sónia, Henriques, Eva, Rodrigues, Mariana, Freitas, Ana Isabel, Guerra, Graça, Freitas, Carolina, Pereira, Décio, Brehm, António, Reis, Roberto Palma Dos
Format: Article
Language:English
Subjects:
BIOCHEMISTRY & MOLECULAR BIOLOGY
Cardiovascular disease
Cardiovascular diseases
Coronary artery
Coronary artery disease
Diabetes mellitus
Dyslipidemia
Framingham score
Genetic diversity
genetic risk score
Genetic variance
GENETICS & HEREDITY
Genotyping
Health risk assessment
Health risks
Heart diseases
Human and Medical Genetics
Hypertension
Multivariate analysis
Predictions
Reclassification
Regression analysis
Risk
risk factors
risk prediction
Smoking
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Summary:The utility of genetic risk scores (GRS) as independent risk predictors remains inconclusive. Here, we evaluate the additive value of a multi-locus GRS to the Framingham risk score (FRS) in coronary artery disease (CAD) risk prediction. A total of 2888 individuals (1566 coronary patients and 1322 controls) were divided into three subgroups according to FRS. Multiplicative GRS was determined for 32 genetic variants associated to CAD. Logistic Regression and Area Under the Curve (AUC) were determined first, using the TRF for each FRS subgroup, and secondly, adding GRS. Different models (TRF, TRF+GRS) were used to classify the subjects into risk categories for the FRS 10-year predicted risk. The improvement offered by GRS was expressed as Net Reclassification Index and Integrated Discrimination Improvement. Multivariate analysis showed that GRS was an independent predictor for CAD (OR = 1.87; p
ISSN:1415-4757
1678-4685
1678-4685
DOI:10.1590/1678-4685-GMB-2017-0173