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

  • A. W. Plat
  • , H. E.J.H. Stoffers
  • , O. H. Klungel
  • , C. P. van Schayck
  • , P. W. de Leeuw
  • , F. L. Soomers
  • , P. M. Schiffers
  • , A. D.M. Kester
  • , A. A. Kroon*
  • *Corresponding author for this work
  • Maastricht University

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Pages (from-to)659-667
Number of pages9
JournalJournal of Human Hypertension
Volume23
Issue number10
DOIs
Publication statusPublished - 2009

Bibliographical note

Funding Information:
This work was funded by project grants from SOHO (Stichting Ondersteuning Hypertensie Onderzoek) Amsterdam, the Netherlands, and the University Hospital Maastricht (Profileringsfonds Grant no. PF194), Maastricht, the Netherlands. We thank Rob Janssen for his help in the genotyping part and for his valuable comments on the manuscript. We are grateful to Karin Aretz for her support with the statistical analyses.

Funding

This work was funded by project grants from SOHO (Stichting Ondersteuning Hypertensie Onderzoek) Amsterdam, the Netherlands, and the University Hospital Maastricht (Profileringsfonds Grant no. PF194), Maastricht, the Netherlands. We thank Rob Janssen for his help in the genotyping part and for his valuable comments on the manuscript. We are grateful to Karin Aretz for her support with the statistical analyses.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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