Multi-locus candidate gene polymorphisms and risk of myocardial infarction: a population-based, prospective genetic analysis.
Keywords
Abstract
BACKGROUND
Polymorphisms in candidate genes related to lipid metabolism, thrombosis, hemostasis, cell-matrix adhesion, and inflammation have been suggested clinically useful in risk assessment of cardiovascular disease.
METHODS
We evaluated a panel of 92 candidate gene polymorphisms, using a multiplex polymerase chain reaction-immobilized probe assay amongst 523 individuals who subsequently developed myocardial infarction (MI), and amongst 2092 individuals who remained free of reported cardiovascular disease over a mean follow-up period of 13.2 years.
RESULTS
Of the 92 polymorphisms tested, three that we previously reported on were associated with risk of MI, [pro12ala in the peroxisome proliferator activated-receptor gamma gene (odds ratio, OR = 0.75, P = 0.02); thr164ile in the beta-2 adrenergic receptor gene (OR = 0.14, P = 0.007); and ala23thr polymorphism in the eotaxin gene (OR = 1.87, P = 0.01)]. However, when adjusted for the other 89 polymorphisms evaluated, these findings were no longer statistically significant. Further, in contrast to reports from other investigators, we found little evidence for association of a C677T polymorphism in the 5,10-methylenetetrahydrofolate reductase gene, the angiotensin-I-converting enzyme 1 insertion/deletion polymorphism, a 4G/5G polymorphism in the serine/cysteine proteinase inhibitor-clade E-member 1 gene, the factor V Leiden mutation, the G20210A factor II mutation, a -455G>A polymorphism in the beta-fibrinogen gene, the cys112arg/arg158cys apolipoprotein E gene polymorphism, a gly460trp polymorphism in the alpha-adducin gene, and a -629C>A polymorphism in the cholesteryl ester transfer protein gene with risk of MI.
CONCLUSIONS
After correction for multiple comparisons, the addition of genetic information observed in the present study had little impact on risk prediction models for MI. The present investigation highlights the importance of replication and validation of findings from genetic association studies.
