Genome-Wide Association Study for Incident Myocardial Infarction and Coronary Heart Disease in Prospective Cohort

Abbas Dehghan1, Joshua C Bis2, Charles C White3

  • 1Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.

Plos One
|March 8, 2016
PubMed

Insights

Genome-wide association studies identified a new locus near QKI associated with coronary heart disease (CHD) risk. The 9p21 locus influences myocardial infarction (MI) risk and survival post-MI.

Area of Science:

  • Genetics
  • Cardiovascular Disease Epidemiology

Background:

  • Limited genome-wide association studies (GWAS) data exists for incident coronary heart disease (CHD).
  • The association of previously identified genetic variants with prospective CHD risk remains unclear.

Purpose of the Study:

  • To conduct a two-stage GWAS for incident myocardial infarction (MI) and CHD.
  • To investigate whether known GWAS single nucleotide polymorphisms (SNPs) associate with mortality risk after MI.

Main Methods:

  • A two-stage GWAS was performed on 64,297 individuals, including 3898 MI and 5465 CHD cases.
  • SNPs surpassing a 5×10-6 threshold in Stage I proceeded to Stage II for discovery.
  • Prognostic analysis examined associations between known GWAS SNPs and mortality in MI survivors.

Main Results:

  • Fifteen loci met the Stage I significance threshold; 8 for MI and 8 for CHD, with one overlapping locus not previously reported.
  • Four SNPs near QKI showed nominal association with MI, with one (rs6941513) reaching genome-wide significance (p = 6.2×10-9) after combining stages.
  • The 9p21 locus SNP (rs1333049) showed modest association with MI risk (HR=1.09) and marginal association with CHD risk (HR=1.06).
  • In MI survivors, the rs1333049 risk allele was linked to decreased subsequent mortality (HR=0.90).

Conclusions:

  • The QKI locus is a novel predictor for incident CHD in prospective studies.
  • The 9p21 locus's dual role in MI risk and post-MI survival underscores the importance of study design in genetic research for complex diseases.
Abstract

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