Identification of chromosomal regions linked to premature myocardial infarction: a meta-analysis of whole-genome searches

Abstract

Myocardial infarction (MI) is a complication of coronary artery disease and the leading cause of death in the Western world. MI is considered a distinct phenotype with an increased genetic component for its premature type. MI's exact inheritance pattern is still unknown. Genome searches for identifying susceptibility loci for premature MI produced inconclusive or inconsistent results. Thus, a genome search meta-analysis (GSMA) was applied to available genome search data on premature MI. GSMA is a non-parametric method to identify genetic regions that rank high, on average in terms of linkage statistics across genome searches unweighted or weighted by study size. The significance of each region's average and heterogeneity, unadjusted or adjusted by neighbouring average simulated ranks, was calculated using a Monte Carlo test. The meta-analysis involved five genome searches in Caucasians. Eight regions (6p22.3-6p21.1, 14p13-14q13.1, 13q33.1-13q34, 5p15.33-5p15.1, 8q13.2-8q22.2, 1p36.21-1p35.2, 12q24.31-12q24.33, 8q24.21-8q24.3) were found to have significant average rank by either unweighted or weighted analyses. In addition, region 8q24.21-8q24.3 produced significant low heterogeneity (P (unadjusted)=0.03 and P (adjusted)=0.05). Four regions (6p22.3-6p21.1, 14p13-14q13.1, 8q13.2-8q22.2, 8q24.21-8q24.3) were not identified by the individual studies. The meta-analysis suggests that these four regions should be further investigated for genes that confer susceptibility to MI.