Screening hub genes in coronary artery disease based on integrated analysis

Long, Fei; Yang, Lei; Ji, Zhou; Hu, YaGuang

doi:10.5603/cj.a2017.0106

Cited by 5 publications

(5 citation statements)

References 48 publications

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“…Additionally, we constructed the circRNA-miRNA-mRNA networks for hsa_circRPRD1A, hsa_circHERPUD2, hsa_circLMBR1, and hsa_circDHTKD1, aiming to explore the possible regulation mechanism in patients with CAD. It is interesting to note that the PRKX [ 44 ] and TFRC [ 45 ] expression was downregulated in CAD patients which has already been reported. Moreover, RPS3A, BCL6, and S100B play a critical role in coronary atherosclerosis [ 44 – 47 ].…”

Section: Discussionmentioning

confidence: 74%

“…It is interesting to note that the PRKX [ 44 ] and TFRC [ 45 ] expression was downregulated in CAD patients which has already been reported. Moreover, RPS3A, BCL6, and S100B play a critical role in coronary atherosclerosis [ 44 – 47 ]. This finding broadly supports other studies in this area linking circRNAs with CAD, and provides evidence that hsa_circRPRD1A, hsa_circHERPUD2, hsa_circLMBR1, and hsa_circDHTKD1 take part in the pathogenesis of atherosclerosis.…”

Section: Discussionmentioning

confidence: 74%

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Interaction between the expression of hsa_circRPRD1A and hsa_circHERPUD2 and classical coronary risk factors promotes the development of coronary artery disease

et al. 2023

BMC Med Genomics

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Background Recent studies suggest that classical coronary risk factors play a significant role in the pathogenesis of coronary artery disease. Our study aims to explore the interaction of circRNA with classical coronary risk factors in coronary atherosclerotic disease. Method Combined analysis of RNA sequencing results from coronary segments and peripheral blood mononuclear cells of patients with coronary atherosclerotic disease was employed to identify critical circRNAs. Competing endogenous RNA networks were constructed by miRanda-3.3a and TargetScan7.0. The relative expression quantity of circRNA in peripheral blood mononuclear cells was determined by qRT-PCR in a large cohort including 256 patients and 49 controls. Spearman’s correlation test, receiver operating characteristic curve analysis, multivariable logistic regression analysis, one-way analysis of variance, and crossover analysis were performed. Results A total of 34 circRNAs were entered into our study, hsa_circRPRD1A, hsa_circHERPUD2, hsa_circLMBR1, and hsa_circDHTKD1 were selected for further investigation. A circRNA-miRNA-mRNA network is composed of 20 microRNAs and 66 mRNAs. The expression of hsa_circRPRD1A (P = 0.004) and hsa_circHERPUD2 (P = 0.003) were significantly down-regulated in patients with coronary artery disease compared to controls. The area under the curve of hsa_circRPRD1A and hsa_circHERPUD2 is 0.689 and 0.662, respectively. Univariate and multivariable logistic regression analyses identified hsa_circRPRD1A (OR = 0.613, 95%CI:0.380–0.987, P = 0.044) as a protective factor for coronary artery disease. Based on the additive model, crossover analysis demonstrated that there was an antagonistic interaction between the expression of hsa_circHERPUD2 and alcohol consumption in subjects with coronary artery disease. Conclusion Our findings imply that hsa_circRPRD1A and hsa_circHERPUD2 could be used as biomarkers for the diagnosis of coronary artery disease and provide epidemiological support for the interactions between circRNAs and classical coronary risk factors.

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Section: Discussionmentioning

confidence: 74%

Section: Discussionmentioning

confidence: 74%

Interaction between the expression of hsa_circRPRD1A and hsa_circHERPUD2 and classical coronary risk factors promotes the development of coronary artery disease

et al. 2023

BMC Med Genomics

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“…It inhibited the activation of Wnt/βcatenin signaling pathway and inhibited ovarian cancer cell malignant, invasion, proliferation, and tumor growth (Chen et al 2022). PRKX was overexpressed in triple-negative breast cancer (Santuario-Facio et al 2017) and downregulated in coronary artery disease (Long et al 2018) which could be a predictor in these diseases. There are few studies MiR-483-5p plays an important role in cancer.…”

Section: Discussionmentioning

confidence: 99%

Identification of predictors for neurological outcome after cardiac arrest in peripheral blood mononuclear cells through integrated bioinformatics analysis and machine learning

Qin

Liu

et al. 2023

Funct Integr Genomics

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Neurological prognostication after cardiac arrest (CA) is important to avoid pursuing futile treatments for poor outcome and inappropriate withdrawal of life-sustaining treatment for good outcome. To predict neurological outcome after CA through biomarkers in peripheral blood mononuclear cells, four datasets were downloaded from the Gene Expression Omnibus database. GSE29546 and GSE74198 were used as training datasets, while GSE92696 and GSE34643 were used as verification datasets. The intersection of differentially expressed genes and hub genes from multiscale embedded gene co-expression network analysis (MEGENA) was utilized in the machine learning screening. Key genes were identified using support vector machine recursive feature elimination (SVM-RFE), least absolute shrinkage and selection operator (LASSO) logistic regression, and random forests (RF). The results were validated using receiver operating characteristic curve analysis. An mRNA-miRNA network was constructed. The distribution of immune cells was evaluated using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT). Five biomarkers were identified as predictors for neurological outcome after CA, with an area under the curve (AUC) greater than 0.7: CASP8 and FADD-like apoptosis regulator (CFLAR), human protein kinase X (PRKX), miR-483-5p, let-7a-5p, and let-7c-5p. Interestingly, the combination of CFLAR minus PRKX showed an even higher AUC of 0.814. The mRNA-miRNA network consisted of 30 nodes and 76 edges. Statistical differences were found in immune cell distribution, including neutrophils, NK cells active, NK cells resting, T cells CD4 memory activated, T cells CD4 memory resting, T cells CD8, B cells memory, and mast cells resting between individuals with good and poor neurological outcome after CA. In conclusion, our study identified novel predictors for neurological outcome after CA. Further clinical and laboratory studies are needed to validate our findings.

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“…There are also reports in the literature about the important role of PLAUR in this process. 63 For example, the functional genetic variation of the PLAUR gene may affect the susceptibility to myocardial infarction. 64 The involvement of thrombomodulin in CAD pathogenesis is confirmed as well.…”

Section: Discussionmentioning

confidence: 99%

Atherosclerosis Pathways are Activated in Pericoronary Adipose Tissue of Patients with Coronary Artery Disease

Konwerski¹,

Gromadka²,

Arendarczyk³

et al. 2021

JIR

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Screening hub genes in coronary artery disease based on integrated analysis

Abstract: Identified 7 differentially expressed genes (IL1R2, ARRB2, PRKX, PLAUR, HSPH1, ZMYND11 and S100A8) may play crucial roles in the development of CAD.

Cited by 5 publications

References 48 publications

Interaction between the expression of hsa_circRPRD1A and hsa_circHERPUD2 and classical coronary risk factors promotes the development of coronary artery disease

Interaction between the expression of hsa_circRPRD1A and hsa_circHERPUD2 and classical coronary risk factors promotes the development of coronary artery disease

Identification of predictors for neurological outcome after cardiac arrest in peripheral blood mononuclear cells through integrated bioinformatics analysis and machine learning

Atherosclerosis Pathways are Activated in Pericoronary Adipose Tissue of Patients with Coronary Artery Disease

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