scholarly journals Construction of the gene expression subgroups of patients with coronary artery disease through bioinformatics approach

2021 ◽  
Vol 18 (6) ◽  
pp. 8622-8640
Author(s):  
Bin Zhang ◽  
◽  
Kuan Zeng ◽  
Rongzhen Li ◽  
Huiqi Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Learning Algorithm ◽  
Pearson Correlation ◽  
Genetic Diagnosis ◽  
Disease Diagnosis ◽  
Gene Expression Omnibus ◽  
Gene Modules ◽  
Artery Disease

<abstract> <p>Coronary artery disease (CAD) is a heterogeneous disease that has placed a heavy burden on public health due to its considerable morbidity, mortality and high costs. Better understanding of the genetic drivers and gene expression clustering behind CAD will be helpful for the development of genetic diagnosis of CAD patients. The transcriptome of 352 CAD patients and 263 normal controls were obtained from the Gene Expression Omnibus (GEO) database. We performed a modified unsupervised machine learning algorithm to group CAD patients. The relationship between gene modules obtained through weighted gene co-expression network analysis (WGCNA) and clinical features was identified by the Pearson correlation analysis. The annotation of gene modules and subgroups was done by the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Three gene expression subgroups with the clustering score of greater than 0.75 were constructed. Subgroup I may experience coronary artery disease of an in-creased severity, while subgroup III is milder. Subgroup I was found to be closely related to the upregulation of the mitochondrial autophagy pathway, whereas the genes of subgroup II were shown to be related to the upregulation of the ribosome pathway. The high expression of APOE, NOS1 and NOS3 in the subgroup I suggested that the patients had more severe coronary artery disease. The construction of genetic subgroups of CAD patients has enabled clinicians to improve their understanding of CAD pathogenesis and provides potential tools for disease diagnosis, classification and assessment of prognosis.</p> </abstract>

scholarly journals Analysis of pathways and networks influencing the differential expression of genes in coronary artery disease

2014 ◽  
Vol 66 (3) ◽  
pp. 983-988 ◽  
Author(s):  
Hui Li ◽  
Xiaolan Zhong ◽  
Chaomin Li ◽  
Lijing Peng ◽  
Wei Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Network Analyses ◽  
Artery Disease

Coronary artery disease (CAD) is the leading cause of death worldwide. Microarray analysis is a practical approach to study gene transcription changes that may reflect signatures that underlie the pathogenesis of CAD. Using gene expression profile data from the Gene Expression Omnibus database, we identified differentially expressed genes that can contribute to the pathology of CAD. Further pathway and network analyses were also implemented to identify pathways and hub genes related to the disease. We observed 466 downregulated and 560 upregulated genes. The ribosome pathway was the most significantly over-represented pathway with differentially expressed genes. Over 35% of the genes in this pathway were downregulated. Hub genes in the network, such as IL7R, FYN, CALM1 ESR1 and PLCG1, may play crucial roles in the pathogenesis of CAD. Our results facilitate the identification of molecular mechanisms that underlie CAD.

Are hypertensive patients with history of coronary artery disease at risk for silent lower extremity artery disease?

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Eka Prasetya Budi Mulia ◽  
Kevin Yuwono ◽  
Raden Mohammad Budiarto
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Lower Extremity ◽  
Pearson Correlation ◽  
Ankle Brachial Index ◽  
Chi Square ◽  
Hypertensive Patients ◽  
History Of ◽  
Artery Disease ◽  
Lower Extremity Artery Disease

Abstract Objectives We aimed to investigate the association between hypertension and asymptomatic lower extremity artery disease (LEAD) in outpatients with known history of coronary artery disease (CAD). Methods Patients with known history of CAD who have been undergone coronary angiography and have significant coronary artery stenosis (more than 60%) were included. LEAD was defined as ankle-brachial index (ABI) < 0.9 in either leg. The risk of LEAD in hypertensive group was analyzed using chi-square test, and correlation between blood pressure (BP) and ABI was analyzed using Pearson correlation test in SPSS v.25. Results One hundred and four patients were included. 82.7% of patients were male. Mean age was 57.05 ± 7.97. The prevalence of hypertension was 35.6%, and the prevalence of LEAD was 16.3%. A higher proportion of LEAD was found in hypertensive (18.9%) compared to non-hypertensive (14.9%), although not statistically significant (OR: 1.33; 95% CI: 0.46 to 3.85; p=0.598). There was an association between ABI and systolic BP (p=0.016), but not with diastolic BP (p=0.102). Conclusions Our study showed that the prevalence of LEAD in hypertension, especially in the CAD population, is relatively high. There was no association between hypertension and LEAD, but a higher prevalence of LEAD was found in hypertensive patients. Nevertheless, LEAD screening is still recommended in hypertensive patients, especially in the CAD population, given the fact that outcomes of health and mortality are worse for those with concomitants of these diseases.

Exerting Cost-Sensitive and Feature Creation Algorithms for Coronary Artery Disease Diagnosis

2012 ◽  
Vol 3 (1) ◽  
pp. 59-79 ◽  
Author(s):  
Roohallah Alizadehsani ◽  
Mohammad Javad Hosseini ◽  
Reihane Boghrati ◽  
Asma Ghandeharioun ◽  
Fahime Khozeimeh ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
High Sensitivity ◽  
Disease Diagnosis ◽  
Major Type ◽  
Support Vector ◽  
K Nearest Neighbors ◽  
Diagnostic Modality ◽  
Data Mining Algorithms ◽  
Artery Disease

One of the main causes of death the world over is the family of cardiovascular diseases, of which coronary artery disease (CAD) is a major type. Angiography is the principal diagnostic modality for the stenosis of heart arteries; however, it leads to high complications and costs. The present study conducted data-mining algorithms on the Z-Alizadeh Sani dataset, so as to investigate rule based and feature based classifiers and their comparison, and the reason for the effectiveness of a preprocessing algorithm on a dataset. Misclassification of diseased patients has more side effects than that of healthy ones. To this end, this paper employs 10-fold cross-validation on cost-sensitive algorithms along with base classifiers of Naïve Bayes, Sequential Minimal Optimization (SMO), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and C4.5 and the results show that the SMO algorithm yielded very high sensitivity (97.22%) and accuracy (92.09%) rates.

scholarly journals Expression of adipocytokine genes and their content in various adipose tissue sites in patients with heart diseases

2020 ◽  
Author(s):  
Olga Gruzdeva ◽  
Yulia Dyleva ◽  
Ekaterina Belik ◽  
Daria Borodkina ◽  
Maxim Sinitsky ◽  
...  
Keyword(s):  
Gene Expression ◽  
Coronary Artery Disease ◽  
Adipose Tissue ◽  
Coronary Artery ◽  
Mitral Valve ◽  
Valve Replacement ◽  
Mitral Valve Replacement ◽  
Biologically Active ◽  
Fat Depots ◽  
Artery Disease

Abstract Background Adipose tissue (AT) is an endocrine and paracrine organ that synthesizes biologically active adipocytokines, which affect inflammation, fibrosis, and atherogenesis. Epicardial and perivascular fat depots are of great interest owing to potential effects on the myocardium and blood vessels. Objective To assess expression and secretion of adipocytokine genes in adipose tissue in patients coronary artery disease (CAD) and patients with aortic or mitral valve replacement. Methods The study included 84 patients with CAD and 50 patients with aortic or mitral valve replacement. Adipocytes were isolated from subcutaneous (SAT), epicardial (EAT), and perivascular AT (PVAT) samples. Isolated adipocytes were cultured for 24 h after which, gene expression and secretion levels of selected adipokines and cytokines in the culture medium were determined. Results The study parameters differed depending on the adipose tissue location. EAT adipocytes in CAD patients were characterized by a pronounced imbalance in the adipokine system. EAT had the lowest adiponectin gene expression and secretion, regardless of nosology and high expression levels of the leptin gene, its receptor, and interleukin-6 (IL-6) were detected. High leptin and IL-6 levels resulted in increased pro-inflammatory activity, as observed in both EAT and PVAT adipocytes, especially in individuals with coronary artery disease. Conclusion The "protective" potential of adipose tissue depends on its location.

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