Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction

Zhou, Jin; He, Shan; Wang, Boyuan; Yang, Wenling; Zheng, Yuqi; Jiang, Shijiu; Li, Dazhu; Lin, Jianwen

doi:10.3389/fgene.2022.854993

Cited by 8 publications

(5 citation statements)

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“…et al for AMI suggested that the hsa_circ_0009018/hsa-miR-139-3p/BCL6 axis was significantly positively correlated with upregulated immune cells in AMI, which may be represent potential therapeutic targets (47). All of these data suggest the importance of BCL6 in cardiovascular disease or senescence.…”

Section: Discussionmentioning

confidence: 91%

“…Moreover, Altieri et al found that BCL6 cooperates with PPARdelta to protect the heart from doxorubicin-induced senescence ( 46 ). Using bioinformatics, the circRNA-miRNA-mRNA network constructed by Zhou et al for AMI suggested that the hsa_circ_0009018/hsa-miR-139-3p/BCL6 axis was significantly positively correlated with upregulated immune cells in AMI, which may be represent potential therapeutic targets ( 47 ). All of these data suggest the importance of BCL6 in cardiovascular disease or senescence.…”

Section: Discussionmentioning

confidence: 99%

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Identification and validation of senescence-related genes in circulating endothelial cells of patients with acute myocardial infarction

Xiang

Shen

Zhang

et al. 2022

Front. Cardiovasc. Med.

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BackgroundAcute myocardial infarction (AMI) is the main clinical cause of death and cardiovascular disease and thus has high rates of morbidity and mortality. The increase in cardiovascular disease with aging is partly the result of vascular endothelial cell senescence and associated vascular dysfunction. This study was performed to identify potential key cellular senescence-related genes (SRGs) as biomarkers for the diagnosis of AMI using bioinformatics.MethodsUsing the CellAge database, we identified cellular SRGs. GSE66360 and GSE48060 for AMI patients and healthy controls and GSE19322 for mice were downloaded from the Gene Expression Omnibus (GEO) database. The GSE66360 dataset was divided into a training set and a validation set. The GSE48060 dataset was used as another validation set. The GSE19322 dataset was used to explore the evolution of the screened diagnostic markers in the dynamic process of AMI. Differentially expressed genes (DEGs) of AMI were identified from the GSE66360 training set. Differentially expressed senescence-related genes (DESRGs) selected from SRGs and DEGs were analyzed using Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) networks. Hub genes in DESRGs were selected based on degree, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. Finally, a miRNA-gene network of diagnostic genes was constructed and targeted drug prediction was performed.ResultsA total of 520 DEGs were screened from the GSE66360 training set, and 279 SRGs were identified from the CellAge database. The overlapping DEGs and SRGs constituted 14 DESRGs, including 4 senescence suppressor genes and 10 senescence inducible genes. The top 10 hub genes, including FOS, MMP9, CEBPB, CDKN1A, CXCL1, ETS2, BCL6, SGK1, ZFP36, and IGFBP3, were screened. Furthermore, three diagnostic genes were identified: MMP9, ETS2, and BCL6. The ROC analysis showed that the respective area under the curves (AUCs) of MMP9, ETS2, and BCL6 were 0.786, 0.848, and 0.852 in the GSE66360 validation set and 0.708, 0.791, and 0.727 in the GSE48060 dataset. In the GSE19322 dataset, MMP9 (AUC, 0.888) and ETS2 (AUC, 0.929) had very high diagnostic values in the early stage of AMI. Finally, based on these three diagnostic genes, we found that drugs such as acetylcysteine and genistein may be targeted for the treatment of age-related AMI.ConclusionThe results of this study suggest that cellular SRGs might play an important role in AMI. MMP9, ETS2, and BCL6 have potential as specific biomarkers for the early diagnosis of AMI.

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Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Identification and validation of senescence-related genes in circulating endothelial cells of patients with acute myocardial infarction

Xiang

Shen

Zhang

et al. 2022

Front. Cardiovasc. Med.

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“…In addition, we found that the myocardial infarction group contained higher proportions of macrophages (P<0.01), mast cells (P<0.01), monocytes (P<0.01), and neutrophils (P<0.01). Jin Zhou similarly found a trend of upregulation of neutrophils and macrophages in patients with myocardial infarction [25] . Zhang X showed a trend of upregulation of neutrophils and macrophages by established a myocardial infarction model by ligating the anterior descending branch of the left coronary artery in Syrian hamsters and found that the number of mast cells was much higher in the myocardial infarction group than in the control group [26] .…”

Section: Discussionmentioning

confidence: 90%

Comprehensive bioinformatics method to explore immune-related genes in the pathogenesis of myocardial infarction

Zhang¹

2022

Preprint

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Objective: Comprehensive bioinformatics methods were used to explore the immune-related genes and immune changes in myocardial infarction and to validate the immune-related genes.Methods: Gene expression data came from three datasets, GSE29111, GSE66360 and GSE48060. GSE29111 and GSE66360 were combined as training set and GSE48060 as the validation set. Differential gene, GO/KEGG enrichment, PPI, WCGNA, GSEA, and immune infiltration analyses were performed to find immune-related core genes for myocardial infarction. Diagnostic ability of core genes was assessed by ROC curves. RT-PCR was used to verify differences in expression of core genes between myocardial infarction and control patients. One of the immune-related core genes, BCL6, was selected for further study. The relationship between BCL6 and inflammatory response and oxidative stress was explored by detecting the inflammatory factors TNF-α, IL-1, IL-6, NADPH oxidase subunits p67 and gp91, SOD activity and MDA content.Results: The differential analysis identified 91 differential genes. GO and KEGG enrichment analysis involved response to lipopolysaccharide, IL-17 signaling pathway. Among the PPI network constructed by 91 differential genes, four core genes were identified. WCGNA analysis was performed and 13 core genes were identified. The final core genes obtained after taking the intersection were S100A12, BCL6. We verified the diagnostic ability of them, and the expression of them was significantly different between two groups(P<0.01) with AUCs of 0.809 (95% CI 0.733-0.874), 0.837 (95% CI 0.771-0.896). The diagnostic ability in the validation set was equally favorable, with AUCs of 0.789 (95% CI 0.662-0.908) and 0.733 (95% CI 0.573-0.866). The results of immune infiltration and correlation analysis showed a significant positive correlation between two core genes and immune cells. RT-PCR results showed a significant difference in the expression of S100A12 and BCL6 between two groups (P<0.001). The expression of the inflammatory factors were higher in the infarct group than in the control group after BCL6 knockdown (P<0.01), indicating that BCL6 knockdown exacerbated the inflammatory response. Similarly, the expression levels of NADPH oxidase subunits and MDA content were significantly higher in BCL6 knockdown than in the control group (P<0.01), and SOD activity was significantly lower than in the control group (P<0.01), indicating that BCL6 knockdown exacerbated the level of oxidative stress. Conclusion: S100A12 and BCL6 may serve as candidate biomarkers for early detection of myocardial infarction and have promise as new therapeutic targets.

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“…Furthermore, evidence of the role of circRNA-modulated miRNAs has been reported using in vitro hypoxia/reperfusion models as well as in vivo [ 191 , 192 ]. In an in vitro model of hypoxia/reperfusion, the administration of exosomes with high amounts of circ_0001747 partially recovered CM dysfunction by targeting the miR-199b/MCL1 (induced myeloid leukemia cell differentiation protein) signaling pathway.…”

Section: The Emerging Impact Of Non-coding Rnas’ Regulation Of Cardia...mentioning

confidence: 99%

“…In an in vitro model of hypoxia/reperfusion, the administration of exosomes with high amounts of circ_0001747 partially recovered CM dysfunction by targeting the miR-199b/MCL1 (induced myeloid leukemia cell differentiation protein) signaling pathway. Exosomes with high levels of circ_0001747 attenuate in vitro hypoxia/reperfusion-induced HL-1 dysfunction partly by targeting miR-199b-3p/MCL1 signaling [ 191 ]. Similarly, lncRNA-modulated miRNAs are also important in this context.…”

Section: The Emerging Impact Of Non-coding Rnas’ Regulation Of Cardia...mentioning

confidence: 99%

The Role of ncRNAs in Cardiac Infarction and Regeneration

Caño-Carrillo

Lozano-Velasco

Castillo-Casas

et al. 2023

JCDD

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Myocardial infarction is the most prevalent cardiovascular disease worldwide, and it is defined as cardiomyocyte cell death due to a lack of oxygen supply. Such a temporary absence of oxygen supply, or ischemia, leads to extensive cardiomyocyte cell death in the affected myocardium. Notably, reactive oxygen species are generated during the reperfusion process, driving a novel wave of cell death. Consequently, the inflammatory process starts, followed by fibrotic scar formation. Limiting inflammation and resolving the fibrotic scar are essential biological processes with respect to providing a favorable environment for cardiac regeneration that is only achieved in a limited number of species. Distinct inductive signals and transcriptional regulatory factors are key components that modulate cardiac injury and regeneration. Over the last decade, the impact of non-coding RNAs has begun to be addressed in many cellular and pathological processes including myocardial infarction and regeneration. Herein, we provide a state-of-the-art review of the current functional role of diverse non-coding RNAs, particularly microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), in different biological processes involved in cardiac injury as well as in distinct experimental models of cardiac regeneration.

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Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction

Cited by 8 publications

References 65 publications

Identification and validation of senescence-related genes in circulating endothelial cells of patients with acute myocardial infarction

Identification and validation of senescence-related genes in circulating endothelial cells of patients with acute myocardial infarction

Comprehensive bioinformatics method to explore immune-related genes in the pathogenesis of myocardial infarction

The Role of ncRNAs in Cardiac Infarction and Regeneration

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