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

Andreia Pereira,Sónia Freitas,Eva Henriques,Roberto Palma Dos Reis,Décio Pereira,Sofia Borges,Ana Célia Sousa,António Brehm,Mariana Rodrigues,Carolina Freitas,Maria Isabel Mendonca,Graça Guerra,Ana Isabel Freitas

doi:10.1590/1678-4685-gmb-2017-0173

Andreia Pereira, Sónia Freitas + Show 11 more

Open Access

https://doi.org/10.1590/1678-4685-gmb-2017-0173

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Abstract

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<0.0001). Diabetes, arterial hypertension, dyslipidemia and smoking status were also independent CAD predictors (p<0.05). GRS added predictive value to TRF across all risk subgroups. NRI showed a significant improvement in all categories. In conclusion, GRS provided a better incremental value in intermediate subgroup. In this subgroup, inclusion of genotyping may be considered to better stratify cardiovascular risk.

Highlights

The most important Traditional Risk factors (TRF) for Coronary Artery Disease (CAD) include dyslipidemia, arterial hypertension, diabetes, obesity, smoking, lack of physical activity and stress (Chan and Boerwinkle, 1994)
Using the Net Reclassification Index (NRI) and Integrated Discrimination Index (IDI), we investigate the performance of combined stratification including TRF and genetic risk scores (GRS) in CAD risk assessment
Across all Framingham score subgroups, the GRS was significantly lower in controls that CAD patients (p

Summary

Introduction

The most important Traditional Risk factors (TRF) for Coronary Artery Disease (CAD) include dyslipidemia, arterial hypertension, diabetes, obesity, smoking, lack of physical activity and stress (Chan and Boerwinkle, 1994). There is an increasing interest in the potential use of GRS in cardiovascular disease, because this could increase the number of preventive and therapeutic interventions in individuals and groups with high genetic risk that are not obvious candidates to these interventions using the current standard stratification. Usual cardiovascular risk stratification uses family history, TRF evaluation, and is quantified into scores like Framingham risk score and EuroSCORE (Pencina et al, 2011). Due to the potential financial and medical costs associated with measuring these new markers like GRS, their ability in improving the prediction of CAD outcomes over existing risk models needs to be rigorously accessed. Effective statistical tools for evaluating the incremental value of the novel markers over the routine clinical risk factors are crucial in the field of outcome prediction

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