Article

The contribution of six polymorphisms to cardiovascular risk in a Dutch high-risk primary care population: the HIPPOCRATES project.

Department of General Practice, School for Public Health and Primary Care (CAPHRI), Maastricht University Medical Center, Maastricht, The Netherlands.
Journal of human hypertension (impact factor: 2.8). 03/2009; 23(10):659-67. DOI:10.1038/jhh.2009.6 pp.659-67
Source: PubMed

ABSTRACT This study was designed to examine the contribution of six polymorphisms to the occurrence of cardiovascular disease (CVD) in a Dutch primary care population with a high prevalence of cardiovascular risk factors. In this cross-sectional case-control study, 232 patients with CVD and 571 event-free controls were studied. Patients were genotyped for the AGTR1 (A1166C), AGT (M235T), ACE (4656rpt), NOS3 (E298D), GNB3 (C825T) and ADD1 (G460W) polymorphisms. Univariate and multivariate odds ratios (ORs) were calculated to assess the relationship between genotypes and CVD. Receiver operating characteristic (ROC) analysis was used to quantify the contribution of the polymorphisms to the prediction of CVD. No differences in either genotype or allele frequencies were found between CVD cases and controls. Multivariate analyses, corrected for multiple testing according to Bonferroni, showed significant protective associations for the T-allele of AGT (OR=0.55 (0.34-0.84)) and for the T-allele of ADD1 (OR=0.52 (0.31-0.82)). ROC analysis showed only a very small improvement of CVD risk prediction by adding the six polymorphisms to a model with traditional risk factors. Our data suggest that a major attribution of the six polymorphisms to the cardiovascular risk prediction in a primary care population such as HIPPOCRATES is unlikely.

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Keywords

571 event-free controls
 
allele frequencies
 
cardiovascular disease
 
cardiovascular risk factors
 
cardiovascular risk prediction
 
cross-sectional case-control study
 
CVD cases
 
CVD risk prediction
 
differences
 
Dutch primary care population
 
genotype
 
major attribution
 
multiple testing
 
Multivariate analyses
 
multivariate odds ratios
 
primary care population
 
significant protective associations
 
six polymorphisms
 
small improvement
 
traditional risk factors