| Budget Amount *help |
¥50,570,000 (Direct Cost: ¥38,900,000、Indirect Cost: ¥11,670,000)
Fiscal Year 2005: ¥14,820,000 (Direct Cost: ¥11,400,000、Indirect Cost: ¥3,420,000)
Fiscal Year 2004: ¥16,770,000 (Direct Cost: ¥12,900,000、Indirect Cost: ¥3,870,000)
Fiscal Year 2003: ¥18,980,000 (Direct Cost: ¥14,600,000、Indirect Cost: ¥4,380,000)
|
|---|
| Research Abstract |
We performed a genetic epidemiological study in 5,000 unrelated Japanese individuals to identify gene polymorphisms that confer susceptibility to myocardial infarction and to develop a risk diagnosis system for this condition. We selected 138 candidate genes that might be associated with myocardial infarction on the basis of a comprehensive overview of vascular biology (from the viewpoint of hypertension, atherosclerosis, arterial spasm, or arterial aneurysm); platelet function ; leukocyte, lymphocyte, and monocyte-macrophage biology ; coagulation and fibrinolysis cascades; neurological factors (from the viewpoint of regulation of the circulation, blood pressure, or endocrine function); as well as lipid and adipose tissue metabolism, insulin and glucose metabolism, and homocysteine metabolism and other metabolic factors. We further selected 164 polymorphisms of these genes-most located in the promoter region, exons, or splice donor or acceptor sites in introns-that might be expected to
… More
result in changes in function or expression of the encoded protein. We identified 14 polymorphisms significantly associated (P<0.05) with myocardial infarction by multivariable logistic regression analysis with adjustment for age, sex, body mass index, and the prevalence of smoking, hypertension, diabetes mellitus, and hypercholesterolemia. We confirmed that these polymorphisms significantly and independently affected the prevalence of myocardial infarction by a stepwise forward selection procedures. Among these polymorphismns, 4 polymorphisms were strongly associated (P<0.001) with this condition. By the use of 14 polymorphisms as well as age, sex, and the prevalence of smoking, hypertension, diabetes mellitus, and hypercholesterolemia, we developed the risk diagnosis system to predict a future risk for predisposition to myocardial infarction in each individual. In this system, the prediction probability was calculated from the results of multivariable logistic regression analysis. This probability reflects an individual's susceptibility to myocardial infarction. Identification of gene polymorphisms that confer susceptibility to myocardial infarction and development of genetic risk diagnosis systems may thus be expected to contribute to the personalized prevention of this condition. Less
|
