Back to Search Start Over

Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population.

Authors :
Mendonça MI
Henriques E
Borges S
Sousa AC
Pereira A
Santos M
Temtem M
Freitas S
Monteiro J
Sousa JA
Rodrigues R
Guerra G
Reis RPD
Source :
Genetics and molecular biology [Genet Mol Biol] 2021 Jun 11; Vol. 44 (2), pp. e20200448. Date of Electronic Publication: 2021 Jun 11 (Print Publication: 2021).
Publication Year :
2021

Abstract

The inclusion of a genetic risk score (GRS) can modify the risk prediction of coronary artery disease (CAD), providing an advantage over the use of traditional models. The predictive value of the genetic information on the recurrence of major adverse cardiovascular events (MACE) remains controversial. A total of 33 genetic variants previously associated with CAD were genotyped in 1587 CAD patients from the GENEMACOR study. Of these, 18 variants presented an hazard ratio >1, so they were selected to construct a weighted GRS (wGRS). MACE discrimination and reclassification were evaluated by C-Statistic, Net Reclassification Index and Integrated Discrimination Improvement methodologies. After the addition of wGRS to traditional predictors, the C-index increased from 0.566 to 0.572 (p=0.0003). Subsequently, adding wGRS to traditional plus clinical risk factors, this model slightly improved from 0.620 to 0.622 but with statistical significance (p=0.004). NRI showed that 17.9% of the cohort was better reclassified when the primary model was associated with wGRS. The Kaplan-Meier estimator showed that, at 15-year follow-up, the group with a higher number of risk alleles had a significantly higher MACE occurrence (p=0.011). In CAD patients, wGRS improved MACE risk prediction, discrimination and reclassification over the conventional factors, providing better cost-effective therapeutic strategies.

Details

Language :
English
ISSN :
1415-4757
Volume :
44
Issue :
2
Database :
MEDLINE
Journal :
Genetics and molecular biology
Publication Type :
Academic Journal
Accession number :
34137427
Full Text :
https://doi.org/10.1590/1678-4685-GMB-2020-0448