Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection

Biomimetic-Structured Cobalt Nanocatalyst Suppresses Aortic Dissection Progression by Catalytic Antioxidation

As one of the most lethal cardiovascular diseases, aortic dissection (AD) is initiated by overexpression of reactive oxygen species (ROS) in the aorta that damages the vascular structure and finally leads to massive hemorrhage and sudden death. Current drugs used in clinics for AD treatment fail to efficiently scavenge ROS to a large extent, presenting undesirable therapeutic effect. In this work, a nanocatalytic antioxidation concept has been proposed to elevate the therapeutic efficacy of AD by constructing a cobalt nanocatalyst with a biomimetic structure that can scavenge pathological ROS in an efficient and sustainable manner. Theoretical calculations demonstrate that the antioxidation reaction is catalyzed by the redox transition between hydroxocobalt(III) and oxo-hydroxocobalt(V) accompanied by inner-sphere proton-coupled two-electron transfer, forming a nonassociated activation catalytic cycle. The efficient antioxidation action of the biomimetic nanocatalyst in the AD region effectively alleviates oxidative stress, which further modulates the aortic inflammatory microenvironment by promoting phenotype transition of macrophages. Consequently, vascular smooth muscle cells are also protected from inflammation in the meantime, suppressing AD progression. This study provides a nanocatalytic antioxidation approach for the efficient treatment of AD and other cardiovascular diseases.

Transketolase drives the development of aortic dissection by impairing mitochondrial bioenergetics

AIM

Aortic dissection (AD) is a disease with rapid onset but with no effective therapeutic drugs yet. Previous studies have suggested that glucose metabolism plays a critical role in the progression of AD. Transketolase (TKT) is an essential bridge between glycolysis and the pentose phosphate pathway. However, its role in the development of AD has not yet been elucidated. In this study, we aimed to explore the role of TKT in AD.

METHODS

We collected AD patients' aortic tissues and used high-throughput proteome sequencing to analyze the main factors influencing AD development. We generated an AD model using BAPN in combination with angiotensin II (Ang II) and pharmacological inhibitors to reduce TKT expression. The effects of TKT and its downstream mediators on AD were elucidated using human aortic vascular smooth muscle cells (HAVSMCs).

RESULTS

We found that glucose metabolism plays an important role in the development of AD and that TKT is upregulated in patients with AD. Western blot and immunohistochemistry confirmed that TKT expression was upregulated in mice with AD. Reduced TKT expression attenuated AD incidence and mortality, maintained the structural integrity of the aorta, aligned elastic fibers, and reduced collagen deposition. Mechanistically, TKT was positively associated with impaired mitochondrial bioenergetics by upregulating AKT/MDM2 expression, ultimately contributing to NDUFS1 downregulation.

CONCLUSION

Our results provide new insights into the role of TKT in mitochondrial bioenergetics and AD progression. These findings provide new intervention options for the treatment of AD.

Progression of Thoracic Aortic Dissection Is Aggravated by the hsa_circ_0007386/miR-1271-5P/IGF1R/AKT Axis via Induction of Arterial Smooth Muscle Cell Apoptosis

BACKGROUND

The molecular mechanisms associated with thoracic aortic dissection (TAD) remain poorly understood. A comprehensive high-throughput sequencing-based analysis of the circRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) regulatory network in TAD has not been conducted. The purpose of this study is to identify and verify the key ceRNA networks which may have crucial biological functions in the pathogenesis of TAD.

METHODS

Gene expression profiles of the GSE97745, GSE98770, and GSE52093 datasets were acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the GEO2R tools. Protein-protein interaction (PPI) networks of the hub genes were constructed using STRING; the hub genes and modules were identified by MCODE and CytoHubba plugins of the Cytoscape. We analyzed the hub genes using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. The functions of these hub genes were assessed using Cytoscape software. Our data-along with data from GSE97745, GSE98770, and GSE52093-were used to verify the findings.

RESULTS

Upon combined biological prediction, a total of 11 ce-circRNAs, 11 ce-miRNAs, and 26 ce-mRNAs were screened to construct a circRNA-miRNA-mRNA ceRNA network. PPI network and module analysis identified four hub nodes, including IGF1R, JAK2, CSF1, and GAB1. Genes associated with the Ras and PI3K-Akt signaling pathways were clustered in the four hub node modules in TAD. The node degrees were most significant for IGF1R, which were also the most significant in the two modules (up module and hub module). IGF1R was selected as a key gene, and the hsa_circ_0007386/miR-1271-5P/IGF1R/AKT regulatory axis was established. The relative expression levels of the regulatory axis members were confirmed by RT-PCR in 12 samples, including TAD tissues and normal tissues. Downregulation of IGF1R expression in smooth muscle cells (SMCs) was found to induce apoptosis by regulating the AKT levels. In addition, IGF1R showed high diagnostic efficacy in both AD tissue and blood samples.

CONCLUSIONS

The hsa_circ_0007386/miR-1271-5P/IGF1R/AKT axis may aggravate the progression of TAD by inducing VSMCs apoptosis. CeRNA networks could provide new insights into the underlying molecular mechanisms of TAD. In addition, IGF1R showed high diagnostic efficacy in both tissue and plasma samples in TAD, which can be considered as a diagnostic marker for TAD.

MicroRNA-126-3p/5p and Aortic Stiffness in Patients with Turner Syndrome

Background: Turner Syndrome (TS) is a relatively rare X-chromosomal disease with increased cardiovascular morbidity and mortality. This study aimed to identify whether the circulating miR-126-3p/5p are involved in the pathophysiology of vascular dysfunction in TS. Methods: Using the RT-qPCR, the abundance levels of miR-126-3p and miR-126-5p were determined in 33 TS patients and 33 age-matched healthy volunteers (HVs). Vascular screening, including the assessment of blood pressure, pulse wave velocity, augmentation index, aortic deformation, arterial distensibility, and arterial elastance, was conducted in TS patients and HVs. Results: The abundance levels of miR-126-3p and miR-126-5p were significantly higher in TS patients compared to HVs (p < 0.0001). Within the TS cohort, miR-126-3p/5p correlated significantly with aortic deformation (r = 0.47, p = 0.01; r = 0.48, p < 0.01) and arterial distensibility (r = 0.55, p < 0.01; r = 0.48, p < 0.01). In addition, a significant negative correlation was demonstrated between miR-126-3p and arterial elastance (r = −0.48, p = 0.01). The receiver operating characteristic analysis showed that miR-126-3p and miR-126-5p separated the tested groups with high sensitivity and specificity. Conclusions: The abundance levels of miR-126-3p and miR-126-5p were significantly higher in TS patients compared to HVs. Within the TS cohort, a lower abundance level of miR-126-3p and miR-126-5p was linked with a significantly higher aortic stiffness.

Identification of novel potential biomarkers in infantile hemangioma via weighted gene co-expression network analysis

Background

Infantile hemangioma (IH) is the most common benign tumor in children and is characterized by endothelial cells proliferation and angiogenesis. Some hub genes may play a critical role in angiogenesis. This study aimed to identify the hub genes and analyze their biological functions in IH.

Methods

Differentially expressed genes (DEGs) in hemangioma tissues, regardless of different stages, were identified by microarray analysis. The hub genes were selected through integrated weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) network. Subsequently, detailed bioinformatics analysis of the hub genes was performed by gene set enrichment analysis (GSEA). Finally, quantitative real-time polymerase chain reaction (qRT-PCR) analysis was conducted to validate the hub genes expression in hemangioma-derived endothelial cells (HemECs) and human umbilical vein endothelial cells (HUVECs).

Results

In total, 1115 DEGs were identified between the hemangiomas and normal samples, including 754 upregulated genes and 361 downregulated genes. Two co-expression modules were identified by WGCNA and green module eigengenes were highly correlated with hemangioma (correlation coefficient = 0.87). Using module membership (MM) > 0.8 and gene significance (GS) > 0.8 as the cut-off criteria, 108 candidate genes were selected and put into the PPI network, and three most correlated genes (APLN, APLNR, TMEM132A) were identified as the hub genes. GSEA predicted that the hub genes would regulate endothelial cell proliferation and angiogenesis. The differential expression of these genes was validated by qRT-PCR.

Conclusions

This research suggested that the identified hub genes may be associated with the angiogenesis of IH. These genes may improve our understanding of the mechanism of IH and represent potential anti-angiogenesis therapeutic targets for IH.

Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models

Thoracic aortic aneurysm and dissection (TAAD) is a high-risk aortic disease. Mouse models are usually used to explore the pathological progression of TAAD. In our studies, we performed bioinformatics analysis on a microarray dataset (GSE36778) and verified experiments to define the integrated hub genes of TAAD in three different mouse models. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) network analyses, and histological and quantitative reverse transcription-PCR (qRT-PCR) experiments were used in our study. First, differentially expressed genes (DEGs) were identified, and twelve common differentially expressed genes were found. Second, genes related to the cell cycle and inflammation were enriched by using GO and PPI. We focused on filtering and validating eighteen hub genes that were upregulated. Then, expression data from human ascending aortic tissues in the GSE153434 dataset were also used to verify our findings. These results indicated that cell cycle-related genes participate in the pathological mechanism of TAAD and provide new insight into the molecular mechanisms of TAAD.

Crucial Genes in Aortic Dissection Identified by Weighted Gene Coexpression Network Analysis

Background

Aortic dissection (AD) is a lethal vascular disease with high mortality and morbidity. Though AD clinical pathology is well understood, its molecular mechanisms remain unclear. Specifically, gene expression profiling helps illustrate the potential mechanism of aortic dissection in terms of gene regulation and its modification by risk factors. This study was aimed at identifying the genes and molecular mechanisms in aortic dissection through bioinformatics analysis.

Method

Nine patients with AD and 10 healthy controls were enrolled. The gene expression in peripheral mononuclear cells was profiled through next-generation RNA sequencing. Analyses including differential expressed gene (DEG) via DEGseq, weighted gene coexpression network (WGCNA), and VisANT were performed to identify crucial genes associated with AD. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was also utilized to analyze Gene Ontology (GO).

Results

DEG analysis revealed that 1,113 genes were associated with AD. Of these, 812 genes were markedly reduced, whereas 301 genes were highly expressed, in AD patients. DEGs were rich in certain categories such as MHC class II receptor activity, MHC class II protein complex, and immune response genes. Gene coexpression networks via WGCNA identified 3 gene hub modules, with one positively and 2 negatively correlated with AD, respectively. Specifically, module 37 was the most strongly positively correlated with AD with a correlation coefficient of 0.72. Within module 37, five hub genes (AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D) displayed high connectivity and may have clinical significance in the pathogenesis of AD.

Conclusion

Our analysis provides the possible association of specific genes and gene modules for the involvement of the immune system in aortic dissection. AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D in module M37 were highly connected and strongly linked with AD, suggesting that these genes may help understand the pathogenesis of aortic dissection.

Analysis of Hub Genes and the Mechanism of Immune Infiltration in Stanford Type a Aortic Dissection

Background: Stanford type A aortic dissection (AAD) is a catastrophic disease. An immune infiltrate has been found within the aortic wall of dissected aortic specimens. The recall and activation of macrophages are key events in the early phases of AAD. Herein, the immune filtration profile of AAD was uncovered.

Methods: Gene expression data from the GSE52093, GSE98770 and GSE153434 datasets were downloaded from the Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) of each dataset were calculated and then integrated. A protein-protein interaction (PPI) network was established with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and the hub genes were identified in Cytoscape. Furthermore, gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of hub genes were performed. Finally, we set GSE52093 and GSE98770 as the training set and GSE153434 as the validation set to assess immune infiltration in AAD using CIBERSORTx and analyzed the correlations between immune cells and hub genes in both the training and validation sets.

Results: Sixty-one integrated DEGs were identified. The top 10 hub genes were selected from the PPI network, and 140 biological process (BP) terms and 12 pathways were enriched among the top 10 hub genes. The proportions of monocytes and macrophages were significantly higher in AAD tissues than in normal tissues. Notably, this result was consistent in the training set and the validation set. In addition, we found that among the hub genes, CA9, CXCL5, GDF15, VEGFA, CCL20, HMOX1, and SPP1 were positively correlated with CD14, a cell marker of monocytes, while CA9, CXCL5, GDF15, and VEGFA were positively correlated with CD68, a cell marker of macrophages in the training set. Finally, according to the results of the GO and KEGG analysis of hub genes, we found that the monocyte/macrophage-related genes were involved in immune-inflammatory responses through degradation of the extracellular matrix, endothelial cell apoptosis, hypoxia and the interaction of cytokines and chemokines.

Conclusion: The monocyte-macrophage system plays a major role in immune-inflammatory responses in the development of AAD. Several hub genes are involved in this process via diverse mechanisms.

MiR-4787-5p regulates vascular smooth muscle cell apoptosis by targeting PKD1 and inhibiting the PI3K/Akt/FKHR pathway

ABSTRACT

Vascular smooth muscle cell (VSMC) dysfunction is the main cause of aortic dissection (AD). In this study, we focused on the role and mechanism of miR-4787-5p in regulating VSMC apoptosis. RT-qPCR was used to detect the expression of miR-4787-5p in aorta tissues of AD (n=10) and normal aortic tissues of donors (n=10). Cell apoptosis was tested by TUNEL assay and Annexin V FITC/PI staining flow cytometry. The expression of PC1 and the PI3K/Akt/FKHR signaling pathway associated proteins in VSMCs was measured by Western blot. We found that the miR-4787-5p was highly expressed in aorta tissues of AD compared with 10 healthy volunteers. Meanwhile, PI3K/Akt/FKHR signaling pathway was inactive in the aortic tissue of AD. The overexpression of miR-4787-5p significantly induced VSMC apoptosis, and miR-4787-5p knockdown showed the opposite results. In addition, polycystic kidney disease 1 gene (PKD1), which encodes polycystin-1(PC1), was found to be a direct target of miR-4787-5p in the VSMCs and this was validated using a luciferase reporter assay. Overexpression of PC1 by LV-PC1 plasmids markedly eliminated the promotion of miR-4787-5p overexpression on VSMC apoptosis. Finally, it was found that miR-4787-5p deactivated the PI3K/Akt/FKHR pathway, as demonstrated by the down-regulation of phosphorylated (p-)PI3K, p-Akt, and p-FKHR. In conclusion, these findings confirm an important role for the miR-4787-5p/PKD1 axis in AD pathobiology.