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Association of arginase 1 gene polymorphisms with the risk of myocardial infarction and common carotid intima media thickness.

ABSTRACT: BACKGROUND: Recently, it was suggested that arginase (ARG)1 plays an important role in atherogenesis. However, because of its complex functions depending on vascular cell type, its impact on atherogenesis remains unclear. OBJECTIVE: To evaluate the association between ARG1 polymorphisms and phenotypes related to atherosclerosis. METHODS: Among 10 ARG1 polymorphisms selected from databases, 4 single-nucleotide polymorphisms (rs2781666; rs2781667; rs2781668; rs17599586) were tested for association with myocardial infarction (MI) in a case-control study (350 cases vs 581 controls), and with common carotid artery (CCA) intima-media thickness (CCA-IMT) in an independent sample of 963 subjects (Etude du Vieillissement Artériel (EVA) study). RESULTS: The genotype distribution of the rs2781666 G/T polymorphism differed significantly between MI cases and controls (p = 0.005), and the risk of MI was consistently increased for both GT heterozygotes (OR (95% CI) 1.5 (1.1 to 2.0)) and TT homozygotes (OR (95% CI) 2.2 (1.1 to 4.4)). In the EVA study, the rs2781666 polymorphism was also associated with an increase in CCA-IMT (p = 0.010), a surrogate marker of MI. CONCLUSIONS: The ARG1 rs2781666 polymorphism was consistently associated with MI and an increased CCA-IMT. These findings reinforce the hypothesis of a significant role of ARG1 in vascular pathophysiology.

SUBMITTER: Dumont J

PROVIDER: S-EPMC2597928 | biostudies-literature | 2007 Aug

REPOSITORIES: biostudies-literature

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Association of arginase 1 gene polymorphisms with the risk of myocardial infarction and common carotid intima media thickness.

Dumont Julie J Zureik Mahmoud M Cottel Dominique D Montaye Michèle M Ducimetière Pierre P Amouyel Philippe P Brousseau Thierry T

Journal of medical genetics 20070316 8

<h4>Background</h4>Recently, it was suggested that arginase (ARG)1 plays an important role in atherogenesis. However, because of its complex functions depending on vascular cell type, its impact on atherogenesis remains unclear.<h4>Objective</h4>To evaluate the association between ARG1 polymorphisms and phenotypes related to atherosclerosis.<h4>Methods</h4>Among 10 ARG1 polymorphisms selected from databases, 4 single-nucleotide polymorphisms (rs2781666; rs2781667; rs2781668; rs17599586) were tes ...[more]

PMID: 17369504

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Project description:BackgroundPatients with acute ST-segment elevation myocardial infarction (STEMI) often have fewer identifiable traditional risk factors compared to other types of acute coronary syndrome. Therefore, it is necessary to explore more sensitive predictive models different from traditional cardiovascular scoring systems to identify high-risk populations. The retrospective case-control study aimed to investigate the predictive value of carotid intima-media thickness (CIMT) and homocysteine (Hcy) on the occurrence of STEMI.MethodsA total of 198 patients with first STEMI were continuously selected into the observation group, who received emergency coronary angiography in Hefei Hospital Affiliated to Anhui Medical University from January 2020 to January 2022, and a total of 129 patients with chest pain and chest tightness who received coronary angiography to exclude significant coronary artery disease were selected as the control group in the above hospitals during the same period. Hcy was biochemical index determined by fasting blood sampling within 48 h after admission, while CIMT and carotid plaque was measured using ultrasound. Univariate and multivariate logistic regression analysis was used to screen out independent risk factors including Hcy, CIMT and carotid plaque of STEMI. On the basis of traditional risk factors, Hcy, CIMT and carotid plaque were introduced in order to form different combined diagnosis models. The receiver operating characteristic (ROC) curve of single indicator and multi-indicator combined diagnosis were plotted to evaluate the clinical usefulness of the study factors or diagnostic models. Based on those, a Nomogram was constructed to predict STEMI.ResultsHcy (OR =1.161, 95% CI: 1.084-1.244, P<0.001), CIMT (OR =206.968, 95% CI: 22.375-1,914.468, P<0.001), carotid plaque (OR =2.499, 95% CI: 1.214-5.142, P=0.013) were independent risk factors for STEMI (P<0.01). ROC results suggested that the area under the curve (AUC) of Hcy was 0.729, the optimal cut-off value was 13.525 µmol/L. The AUC of CIMT is 0.763, and the optimal cut-off value is 0.875mm. Combined with the independent predictors including smoking, diabetes, high density lipoprotein cholesterol, low density lipoprotein cholesterol, Hcy, CIMT, carotid plaque, the AUC of the diagnosis model was 0.892 (95% CI: 0.856-0.928, P<0.001). Based on the above results, a Nomogram for predicting STEMI was constructed with a C-index of 0.892. The results of the H-L fitting test show that χ2=1.5049, df=2, P=0.4712; the calibration curve of the Nomogram is close to the ideal curve, and the internal validation C-index was 0.880. The clinical decision curve analysis (DCA) shows that the "nomogram line" of the model is far from the "All line" and the "None line".ConclusionsHcy, CIMT, and carotid artery plaque could be independent risk factors of STEMI. The inclusion of these factors in addition to traditional risk factors can more fully and accurately predict the risk of STEMI. The Nomogram based on the results of this study is feasible and can bring clinical net benefit.

Project description:BackgroundIntima-media thickness of the walls of the common carotid artery and internal carotid artery may add to the Framingham risk score for predicting cardiovascular events.MethodsWe measured the mean intima-media thickness of the common carotid artery and the maximum intima-media thickness of the internal carotid artery in 2965 members of the Framingham Offspring Study cohort. Cardiovascular-disease outcomes were evaluated for an average follow-up of 7.2 years. Multivariable Cox proportional-hazards models were generated for intima-media thickness and risk factors. We evaluated the reclassification of cardiovascular disease on the basis of the 8-year Framingham risk score category (low, intermediate, or high) after adding intima-media thickness values.ResultsA total of 296 participants had a cardiovascular event. The risk factors of the Framingham risk score predicted these events, with a C statistic of 0.748 (95% confidence interval [CI], 0.719 to 0.776). The adjusted hazard ratio for cardiovascular disease with a 1-SD increase in the mean intima-media thickness of the common carotid artery was 1.13 (95% CI, 1.02 to 1.24), with a nonsignificant change in the C statistic of 0.003 (95% CI, 0.000 to 0.007); the corresponding hazard ratio for the maximum intima-media thickness of the internal carotid artery was 1.21 (95% CI, 1.13 to 1.29), with a modest increase in the C statistic of 0.009 (95% CI, 0.003 to 0.016). The net reclassification index increased significantly after addition of intima-media thickness of the internal carotid artery (7.6%, P<0.001) but not intima-media thickness of the common carotid artery (0.0%, P=0.99). With the presence of plaque, defined as intima-media thickness of the internal carotid artery of more than 1.5 mm, the net reclassification index was 7.3% (P=0.01), with an increase in the C statistic of 0.014 (95% CI, 0.003 to 0.025).ConclusionsThe maximum internal and mean common carotid-artery intima-media thicknesses both predict cardiovascular outcomes, but only the maximum intima-media thickness of (and presence of plaque in) the internal carotid artery significantly (albeit modestly) improves the classification of risk of cardiovascular disease in the Framingham Offspring Study cohort. (Funded by the National Heart, Lung, and Blood Institute.).

Dataset Information

Association of arginase 1 gene polymorphisms with the risk of myocardial infarction and common carotid intima media thickness.

Publications

Association of arginase 1 gene polymorphisms with the risk of myocardial infarction and common carotid intima media thickness.

Similar Datasets

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