Abstract
Background Although epidemiologic studies have suggested that several genetic variants increase the risk of myocardial infarction, large-scale association studies that examine many polymorphisms simultaneously are required to allow reliable prediction of the genetic risk of myocardial infarction. Methods We used a fluorescence- or colorimetry-based allele-specific DNA-primer-probe assay system to determine the genotypes of 112 polymorphisms of 71 candidate genes in 2819 unrelated Japanese patients with myocardial infarction (2003 men and 816 women) and 2242 unrelated Japanese controls (1306 men and 936 women). Results In an initial screening of the 112 polymorphisms for an association with myocardial infarction in 909 subjects, 19 polymorphisms were selected in men and 18 in women by means of logistic-regression analysis, after adjustment for age, body-mass index, and the prevalence of smoking, hypertension, diabetes mellitus, hypercholesterolemia, and hyperuricemia. In a large-scalestudy involving the selected polymorphisms and the remaining 4152 subjects, similar logistic-regression analysis revealed that the risk of myocardial infarction was significantly associated with the C1019T polymorphism in the connexin 37 gene (P<0.001) in men and the 4G-668/5G polymorphism in the plasminogen-activator inhibitor type 1 gene (P< 0.001) and the 5A-1171/6A polymorphism in the stromelysin-1 gene (P<0.001) in women. Conclusions Determination of the genotypes of the connexin 37, plasminogen-activator inhibitor type 1, and stromelysin-1 genes may prove reliable in predicting the genetic risk of myocardial infarction and might thus contribute to the primary prevention of this condition.
| Original language | English |
|---|---|
| Pages (from-to) | 1916-1923 |
| Number of pages | 8 |
| Journal | New England Journal of Medicine |
| Volume | 347 |
| Issue number | 24 |
| DOIs | |
| Publication status | Published - 12-12-2002 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- General Medicine
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