Association of gene variants with incident myocardial infarction in the Cardiovascular Health Study

Arterioscler Thromb Vasc Biol. 2008 Jan;28(1):173-9. doi: 10.1161/ATVBAHA.107.153981. Epub 2007 Nov 1.

Abstract

Objective: We asked whether single nucleotide polymorphisms (SNPs) that had been nominally associated with cardiovascular disease in antecedent studies were also associated with cardiovascular disease in a population-based prospective study of 4522 individuals aged 65 or older.

Methods and results: Based on antecedent studies, we prespecified a risk allele and an inheritance model for each of 74 SNPs. We then tested the association of these SNPs with myocardial infarction (MI) in the Cardiovascular Health Study (CHS). The prespecified risk alleles of 8 SNPs were nominally associated (1-sided P<0.05) with increased risk of MI in White CHS participants. The false discovery rate for these 8 was 0.43, suggesting that about 4 of these 8 are likely to be true positives. The 4 of these 8 SNPs that had the strongest evidence for association with cardiovascular disease before testing in CHS (association in 3 antecedent studies) were in KIF6 (CHS HR=1.29; 90%CI 1.1 to 1.52), VAMP8 (HR=1.2; 90%CI 1.02 to 1.41), TAS2R50 (HR=1.13; 90%CI 1 to 1.27), and LPA (HR=1.62; 90%CI 1.09 to 2.42).

Conclusions: Although most of the SNPs investigated were not associated with MI in CHS, evidence from this investigation combined with previous studies suggests that 4 of these SNPs are likely associated with MI.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Black or African American
  • Coronary Disease / genetics*
  • Female
  • Genetic Predisposition to Disease / epidemiology
  • Genetic Predisposition to Disease / genetics*
  • Humans
  • Longitudinal Studies
  • Male
  • Myocardial Infarction / genetics*
  • National Heart, Lung, and Blood Institute (U.S.)
  • Polymorphism, Single Nucleotide / genetics*
  • Proportional Hazards Models
  • United States / epidemiology
  • White People