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Interaction of dietary patterns with rs28362491 on severity of coronary artery stenosis in patients undergoing coronary angiography.

ABSTRACT: Coronary artery disease (CAD) is one of the most important cardiovascular diseases. Lifestyle and genetic factors play important roles in the development of CAD. The aim of the study is to examine the interaction of dietary patterns and genes on the likelihood of abnormal lipid profile and coronary artery stenosis in Iranians undergoing coronary angiography. This cross-sectional study was performed on 440 patients who underwent coronary angiography. The factor analysis method was used to extract dietary patterns. Commercial kits have been used to assess biochemical parameters. The detection of the rs28362491 genotype was carried out by the method of restriction fragment length polymorphism. Traditional (TDP) and western dietary pattern (WDP) were extracted. We observed an interaction of adherence to TDP and rs28362491 on the odds of having a high Gensini score. These interactions indicated that higher adherence to TDP was associated with higher odds of having a high Gensini score for patients with DD genotype than for those with II genotype. (OR 2.33, 95%CI 1.00-5.44; P = 0.05). These interactions remained statistically significant even after confounder variables. We observed an interaction between higher adherence to TDP and rs28362491 variants on the odds of high low-density lipoprotein cholesterol levels (P = 0.04) in the unadjusted model. We found a significant interaction of this polymorphism and higher adherence to WDP on the odds of having a high Gensini score in the unadjusted model (P = 0.04). This study provides a basis for future research on NF-KB1 gene and diet interaction. More large-scale longitudinal studies are needed to validate these findings.

SUBMITTER: Darabi Z

PROVIDER: S-EPMC10480227 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Interaction of dietary patterns with rs28362491 on severity of coronary artery stenosis in patients undergoing coronary angiography.

Darabi Zahra Z Seyed Hosseini Seyed Mostafa SM Sarebanhassanabadi Mohammadtaghi M Jambarsang Sara S Vahidi Mehrjardi Mohammad Yahya MY Hosseinzadeh Mahdieh M Beigrezaei Sara S Vasmehjani Azam Ahmadi AA Taftian Marzieh M Arabi Vahid V Motallaei Maryam M Yazdi Faezeh Golvardi FG Salehi-Abargouei Amin A Nadjarzadeh Azadeh A

Scientific reports 20230905 1

Coronary artery disease (CAD) is one of the most important cardiovascular diseases. Lifestyle and genetic factors play important roles in the development of CAD. The aim of the study is to examine the interaction of dietary patterns and genes on the likelihood of abnormal lipid profile and coronary artery stenosis in Iranians undergoing coronary angiography. This cross-sectional study was performed on 440 patients who underwent coronary angiography. The factor analysis method was used to extract ...[more]

PMID: 37669998

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Project description:AimEvidence indicates there are still conflicts regarding CETP Taq1B polymorphism and coronary artery disease risk factors. Current findings about whether dietary patterns can change the relationship of the Taq1B on lipid profile and the severity of coronary arteries stenosis appears to be limited. The present research made an attempt to investigate this possible relationship.MethodsThis cross-sectional study involved 453 male and female participants with a mean age of 57 years. A validated 178-item food frequency questionnaire (FFQ) was used to assess dietary usual intake. Dietary patterns were extracted through principal component analysis (PCA). Taq1B variant was genotyped by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Two-way ANOVA was used to test the interaction between Taq1B polymorphism and dietary patterns.ResultsTwo dietary patterns were detected: the western dietary pattern (WDP) and the traditional dietary pattern (TDP). The frequency of Taq1B genotypes turned out to be 10.4, 72.4, and 17.2% for B1B1, B1B2, and B2B2, respectively. A significant difference was observed in TG and TG/HDL-C levels among TaqIB genotypes in higher adherence to TDP (P = 0.01 and P = 0.03, respectively). Taq1B showed a significant interaction with TDP for modulating TG levels and TG/HDL-C ratio (P = 0.02 and P = 0.04, respectively). Greater compliance to WDP demonstrated a significant difference in TG and TG/HDL-C levels across rs708272 genotypes (P = 0.03) after adjusting for confounding factors. Other lipid components and coronary arteries stenosis scores failed to show any relationship or significant difference across Taq1B genotypes or dietary patterns.ConclusionAdherence to TDP may adjust the association between the Taq1B variant and TG and TG/HDL-C levels in patients undergoing coronary angiography. To better understand the relationships, we suggest prospective studies in different race groups with multivariate approaches.

Project description:BackgroundAlthough coronary computed tomography angiography (CCTA) is currently utilized as the frontline test to accurately diagnose coronary artery disease (CAD) in clinical practice, there are still debates regarding its use as a screening tool for the asymptomatic population. Using deep learning (DL), we sought to develop a prediction model for significant coronary artery stenosis on CCTA and identify the individuals who would benefit from undergoing CCTA among apparently healthy asymptomatic adults.MethodsWe retrospectively reviewed 11,180 individuals who underwent CCTA as part of routine health check-ups between 2012 and 2019. The main outcome was the presence of coronary artery stenosis of ≥70% on CCTA. We developed a prediction model using machine learning (ML), including DL. Its performance was compared with pretest probabilities, including the pooled cohort equation (PCE), CAD consortium, and updated Diamond-Forrester (UDF) scores.ResultsIn the cohort of 11,180 apparently healthy asymptomatic individuals (mean age 56.1 years; men 69.8%), 516 (4.6%) presented with significant coronary artery stenosis on CCTA. Among the ML methods employed, a neural network with multi-task learning (19 selected features), one of the DL methods, was selected due to its superior performance, with an area under the curve (AUC) of 0.782 and a high diagnostic accuracy of 71.6%. Our DL-based model demonstrated a better prediction than the PCE (AUC, 0.719), CAD consortium score (AUC, 0.696), and UDF score (AUC, 0.705). Age, sex, HbA1c, and HDL cholesterol were highly ranked features. Personal education and monthly income levels were also included as important features of the model.ConclusionWe successfully developed the neural network with multi-task learning for the detection of CCTA-derived stenosis of ≥70% in asymptomatic populations. Our findings suggest that this model may provide more precise indications for the use of CCTA as a screening tool to identify individuals at a higher risk, even in asymptomatic populations, in clinical practice.

Project description:BackgroundThe commercial coronary computed tomographic angiography artificial intelligence (CCTA-AI) platform has made great progress in clinical application. However, research is needed to elucidate the current stage of commercial AI platforms and the role of radiologists. This study compared the diagnostic performance of the commercial CCTA-AI platform with that of a reader based on a multicenter and multidevice sample.MethodsA total of 318 patients with suspected coronary artery disease (CAD) who underwent both CCTA and invasive coronary angiography (ICA) were included in a multicenter and multidevice validation cohort between 2017 and 2021. The commercial CCTA-AI platform was used to automatically assess coronary artery stenosis by using ICA findings as the gold standard. The CCTA reader was completed by radiologists. The diagnostic performance of the commercial CCTA-AI platform and CCTA reader was evaluated at the patient and segment levels. The cutoff values of models 1 and 2 were 50% and 70% stenosis, respectively.ResultsIt took 20.4 seconds to accomplish post-processing per patient when using the CCTA-AI platform, which was significantly shorter than the time taken to complete this task with the CCTA reader (1,112.1 s). In the patient-based analysis, the area under the curve (AUC) was 0.85 using the CCTA-AI platform and 0.61 using the CCTA reader in model 1 (stenosis ratio: 50%). In contrast, the AUC was 0.78 using the CCTA-AI platform and 0.64 using the CCTA reader in model 2 (stenosis ratio: 70%). In the segment-based analysis, the AUCs of CCTA-AI were slightly better than those of the readers. The negative predictive value (NPV) increased from model 1 to model 2. Furthermore, the diagnostic performance was better for larger-diameter arteries.ConclusionsThe commercial CCTA-AI platform may provide a feasible solution for the diagnosis of coronary artery stenosis, and it has a diagnostic performance that is slightly better than that of a radiologist with a moderate level of experience (5-10 years of experience).

Project description:PurposeAn important aspect in the prevention and treatment of coronary artery disease is the functional evaluation of narrowed blood vessels. Medical image-based Computational Fluid Dynamic methods are currently increasingly being used in the clinical setting for flow studies of cardio vascular system. The aim of our study was to confirm the feasibility and functionality of a non-invasive computational method providing information about hemodynamic significance of coronary stenosis.MethodsA comparative method was used to simulate the flow energy losses in real (stenotic) and reconstructed models without (reference) stenosis of the coronary arteries under stress test conditions, i.e. for maximum blood flow and minimal, constant vascular resistance. In addition to the absolute pressure drop in the stenotic arteries (FFRsten) and in the reconstructed arteries (FFRrec), a new energy flow reference index (EFR) was also defined, which expresses the total pressure changes caused by stenosis in relation to the pressure changes in normal coronary arteries, which also allows a separate assessment of the haemodynamic significance of the atherosclerotic lesion itself. The article presents the results obtained from flow simulations in coronary arteries, reconstructed on the basis of 3D segmentation of cardiac CT images of 25 patients from retrospective data collection, with different degrees of stenoses and different areas of their occurrence.ResultsThe greater the degree of narrowing of the vessel, the greater drop of flow energy. Each parameter introduces an additional diagnostic value. In contrast to FFRsten, the EFR indices that are calculated on the basis of a comparison of stenosed and reconstructed models, are associated directly with localization, shape and geometry of stenosis only. Both FFRsten and EFR showed very significant positive correlation (P < 0.0001) with coronary CT angiography-derived FFR, with a correlation coefficient of 0.8805 and 0.9011 respectively.ConclusionThe study presented promising results of non-invasive, comparative test to support of prevention of coronary disease and functional evaluation of stenosed vessels.

Project description:BackgroundThe relationship between galectin-3 (Gal-3) and coronary artery disease (CAD) has not been fully elucidated.AimThis study aimed to determine the relationship between the presence and severity of CAD and serum Gal-3 levels.Patients and methodsThree-hundred thirty-one consecutive CAD patients were enrolled as the study group. An additional 62 patients without CAD were enrolled as the control group. Serum Gal-3 levels were separately compared between the non-CAD and CAD groups, among the stable CAD and Acute coronary syndrome (ACS) groups, and between CAD patients with low and high SYNTAX scores (SSs). The 1-year cumulative rate of major adverse cardiac events (MACEs) was also compared among ACS patients by Gal-3 levels.ResultsSerum Gal-3 was significantly higher in the CAD group than in the non-CAD group 3.89 (0.16-63.67) vs. 2.07 (0.23-9.38) ng/ml, P < 0.001. Furthermore, serum Gal-3 was significantly higher in the non-ST-segment elevation ACS (NSTE-ACS) group than that in the stable CAD group, 4.72 (1.0-16.14) vs. 2.23 (0.65-23.8) ng/ml, P = 0.04 and higher in the ST-segment elevation myocardial infarction (STEMI) group than that in the stable CAD group 7.87 (0.59-63.67) vs. 2.23 (0.65-23.8) ng/ml, P < 0.001. Serum Gal-3 level was an independent predictor of ACS compared with stable CAD group (OR = 1.131, 95% CI: 1.051-1.217, P = 0.001) as well as high SS (OR = 1.030, 95% CI: 1.021-1.047, P = 0.038) after adjust other confounding risk factors. Acute coronary syndrome patients with Gal-3 levels above the median (gal-3 = 4.78 ng/ml) showed a higher cumulative MACE rate than those with Gal-3 levels below the median. After adjusting other confounding risk factors, Gal-3 remained an independent risk factor for the cumulative rate of MACEs in ACS patients (6% higher rate of MACEs incidence per 1 ng/ml increment of Gal-3).ConclusionGalectin-3 correlated with the presence of CAD as well as coronary stability and complexity. Galectin-3 may be valuable in predicting mid-term prognosis in ACS patients.

Dataset Information

Interaction of dietary patterns with rs28362491 on severity of coronary artery stenosis in patients undergoing coronary angiography.

Publications

Interaction of dietary patterns with rs28362491 on severity of coronary artery stenosis in patients undergoing coronary angiography.

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