Integration of Gene Expression Profile Data to Verify Hub Genes of Patients with Stanford A Aortic Dissection

Applying multi-omics techniques to the discovery of biomarkers for acute aortic dissection

Acute aortic dissection (AAD) is a cardiovascular disease that manifests suddenly and fatally. Due to the lack of specific early symptoms, many patients with AAD are often overlooked or misdiagnosed, which is undoubtedly catastrophic for patients. The particular pathogenic mechanism of AAD is yet unknown, which makes clinical pharmacological therapy extremely difficult. Therefore, it is necessary and crucial to find and employ unique biomarkers for Acute aortic dissection (AAD) as soon as possible in clinical practice and research. This will aid in the early detection of AAD and give clear guidelines for the creation of focused treatment agents. This goal has been made attainable over the past 20 years by the quick advancement of omics technologies and the development of high-throughput tissue specimen biomarker screening. The primary histology data support and add to one another to create a more thorough and three-dimensional picture of the disease. Based on the introduction of the main histology technologies, in this review, we summarize the current situation and most recent developments in the application of multi-omics technologies to AAD biomarker discovery and emphasize the significance of concentrating on integration concepts for integrating multi-omics data. In this context, we seek to offer fresh concepts and recommendations for fundamental investigation, perspective innovation, and therapeutic development in AAD.

Material basis and action mechanism of Euryale Ferox Salisb in preventing and treating diabetic kidney disease

The aim of this study was to determine the chemical structure and mechanism of action of Euryale ferox Salisb (ES) in the prevention and treatment of diabetic kidney disease (DKD). The TCMSP, SymMap V2, CTD, DisGeNET, and GeneCards databases were searched for ES components, targets, and DKD targets using the network pharmacology method to identify common drug-disease targets. PPI analysis was used to identify hub genes, which were then followed by DKD clinical relevance, GO, KEGG analysis, and transcription factor prediction. Finally, molecular docking was performed. We discovered 24 components of ES and 72 objectives of ES, 9 of which were clinically relevant and primarily regulated by transcription factors such as HNF4A and PPARG. They are involved primarily in signal transduction, inflammatory responses, TNF regulation, apoptosis, MAPK, and other signaling pathways. The main components are oleic acid targeting the protein encoded by PPARA, LPL, FABP1, and vitamin E binding the protein encoded by MAPK1, TGFB1. In general, this approach provides an effective strategy in which ES acts primarily against DKD through oleic acid and vitamin E, targeting the protein encoded by PPARA, LPL, FABP1, MAPK1 to regulate TNF, apoptosis, MAPK, and other signaling pathways. PRACTICAL APPLICATIONS: Euryale ferox Salisb (ES) is well known for its use in medicine and food. Furthermore, ES contains many nutrients, whose pharmacological properties, including antidepressant, antioxidant, and anti-diabetic action, have been extensively demonstrated by numerous studies. In this article, through network pharmacology combined with clinical correlation analysis and molecular docking, the target and mechanism of ES in the treatment of diabetic kidney disease (DKD) were discussed, which clarified its mechanism at the molecular level. Provides a reference for the further development and utilization of ES.

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.

A Network Pharmacology Approach to Explore the Mechanism of HuangZhi YiShen Capsule for Treatment of Diabetic Kidney Disease

BACKGROUND AND OBJECTIVE

HuangZhi YiShen Capsule (HZYS) is a Chinese patent herbal drug that protects kidney function in diabetic kidney disease (DKD) patients. However, the pharmacologic mechanisms of HZYS remain unclear. This study would use network pharmacology to explore the pharmacologic mechanisms of HZYS.

METHODS

Chemical constituents of HZYS were obtained through the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and literature search. Potential targets of HZYS were identified by using the TCMSP and the SwissTarget Prediction databases. DKD-related target genes were collected by using the Online Mendelian Inheritance in Man, Therapeutic Target Database, GeneCards, DisGeNET, and Drugbank databases. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to further explore the mechanisms of HZYS in treating DKD. Molecular docking was conducted to verify the potential interactions between the prime compounds and the hub genes.

RESULTS

179 active compounds and 620 target genes were obtained, and 571 common targets were considered potential therapeutic targets. The top 10 main active compounds of HZYS were heparin, quercetin, kaempferol, luteolin, methyl14-methylpentadecanoate, methyl (Z)-11-hexadecenoate, 17-hydroxycorticosterone, 4-pregnene-17α, 20β, 21-triol-3, 11-dione, wogonin, and hydroxyecdysone. Hub signaling pathways by which HZYS treating DKD were PI3K-Akt, MAPK, AGE-RAGE in diabetic complications, TNF, and apoptosis. The top 10 target genes associated with these pathways were IL6, MAPK1, AKT1, RELA, BCL2, JUN, MAPK3, MAP2K1, CASP3, and TNF. Quercetin and Luteolin were verified to have good binding capability with the hub potential targets IL6, MAPK1, AKT1 through molecular docking.

CONCLUSION

HZYS appeared to treat DKD by regulating the inflammatory, oxidative stress, apoptotic, and fibrosis signaling pathways. This study provided a novel perspective for further research of HZYS.

LINC01278 Sponges miR-500b-5p to Regulate the Expression of ACTG2 to Control Phenotypic Switching in Human Vascular Smooth Muscle Cells During Aortic Dissection

Background Phenotypic switching in vascular smooth muscle cells (VSMCs) is involved in the pathogenesis of aortic dissection (AD). This study aims to explore the potential mechanisms of linc01278 during VSMC phenotypic switching. Methods and Results Twelve samples (6 AD and 6 control) were used for lncRNA, microRNA, and mRNA microarray analysis. We integrated the mRNA microarray data set with GSE52093 to determine the differentially expressed genes. Bioinformatic analysis, including Gene Expression Omnibus 2R, Venn diagram analysis, gene ontology, pathway enrichment, and protein-protein interaction networks were used to identify the target lncRNA, microRNA, and mRNA involved in AD. Subsequently, we validated the bioinformatics data using techniques in molecular biology in human tissues and VSMCs. Linc01278, microRNA-500b-5p, and ACTG2 played an important role in the vascular smooth muscle contraction pathway. Linc01278 and ACTG2 were downregulated and miR-500b-5p was upregulated in AD tissues. Molecular markers of VSMC phenotypic switching, including SM22α, SMA, calponin, and MYH11, were downregulated in AD tissues. Plasmid-based overexpression and RNA interference-mediated downregulation of linc01278 weakened and enhanced VSMC proliferation and phenotypic switching, respectively. Dual-luciferase reporter assays confirmed that linc01278 regulated miR-500b-5p that directly targeted ACTG2 in HEK293T cells. Conclusions These data demonstrate that linc01278 regulates ACTG2 to control the phenotypic switch in VSMCs by sponging miR-500b-5p. This linc01278-miR-500b-5p-ACTG2 axis has a potential role in developing diagnostic markers and therapeutic targets for AD.

Bioinformatics Analysis Reveals MicroRNA-193a-3p Regulates ACTG2 to Control Phenotype Switch in Human Vascular Smooth Muscle Cells

Aortic dissection (AD) is among the most fatal cardiovascular diseases. However, the pathogenesis of AD remains poorly understood. This study aims to integrate the microRNAs (miRNA) and mRNA profiles and use bioinformatics analyses with techniques in molecular biology to delineate the potential mechanisms involved in the development of AD. We used the human miRNA and mRNA microarray datasets GSE98770, GSE52093, and GEO2R, Venn diagram analysis, gene ontology, and protein–protein interaction networks to identify target miRNAs and mRNAs involved in AD. RNA interference, western blotting, and luciferase reporter assays were performed to validate the candidate miRNAs and mRNAs in AD tissues and human vascular smooth muscle cells (VSMCs). Furthermore, we studied vascular smooth muscle contraction in AD. In silico analyses revealed that miR-193a-3p and ACTG2 were key players in the pathogenesis of AD. miR-193a-3p was upregulated in the AD tissues. We also found that biomarkers for the contractile phenotype in VSMCs were downregulated in AD tissues. Overexpression and depletion of miR-193a-3p enhanced and suppressed VSMC proliferation and migration, respectively. Dual luciferase reporter assays confirmed that ACTG2 was a target of miR-193a-3p. ACTG2 was also downregulated in human AD tissues and VMSCs overexpressing miR-193a-3p. Taken together, miR-193a-3p may be a novel regulator of phenotypic switching in VSMCs and the miR-193a-3p/ACTG2 axis may serve as a promising diagnostic biomarker and therapeutic candidate for AD.

Multiple Bioinformatics Analyses of Integrated Gene Expression Profiling Data and Verification of Hub Genes Associated with Diabetic Retinopathy

Background

Diabetic retinopathy (DR) is a serious complication of diabetes that can lead to blindness. This study aimed to identify the core genes and molecular functions involved in DR through multiple bioinformatics analyses.

Material/Methods

The mRNA gene profiles of human DR tissues from the GSE60436 and GSE53257 datasets were assessed with R software and integrated to identify the co-expressed differentially expressed genes (DEGs). Multiple bioinformatics analyses were used: Gene Ontology (GO) analysis, signaling pathway analysis, and hub gene prediction. Quantitative reverse transcription-PCR (qRT-PCR) was used to verify the hub genes.

Results

The Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool suggested that the biological processes of the DEGs focused on mitochondrial transport, the cellular components focused on mitochondria, and molecular functions focused on catalytic activity. The results provided by DAVID were consistent with those provided by STRING and the GeneMANIA online database. All the DEGs function in metabolic pathways, consistent with the g: Profiler online analysis results. The protein-protein interaction (PPI) networks forecasted by STRING and GeneMANIA were entered into Cytoscape for cytoHubba degree analysis. The hub genes predicted by cytoHubba suggested that fumarate hydratase (FH) might be relevant to DR. qRT-PCR suggested that the expression of FH was higher in DR retinal tissues than in normal control tissues.

Conclusions

Multiple bioinformatics analyses verified that FH could be used as a potential diagnostic marker and new therapeutic target of DR.

Uncovering the Mechanism of Astragalus membranaceus in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

BACKGROUND

Diabetic nephropathy (DN), characterized by hyperglycemia, hypertension, proteinuria, and edema, is a unique microvascular complication of diabetes. Traditional Chinese medicine (TCM) Astragalus membranaceus (AM) has been widely used for DN in China while the pharmacological mechanisms are still unclear. This work is aimed at undertaking a network pharmacology analysis to reveal the mechanism of the effects of AM in DN. Materials and Methods. In this study, chemical constituents of AM were obtained via Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), and the potential targets of AM were identified using the Therapeutic Target Database (TTD). DisGeNET and GeneCards databases were used to collect DN-related target genes. DN-AM common target protein interaction network was established by using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to further explore the DN mechanism and therapeutic effect of AM. The network diagrams of the active component-action target and protein-protein interaction (PPI) networks were constructed using Cytoscape software.

RESULTS

A total of 16 active ingredients contained and 78 putative identified target genes were screened from AM, of which 42 overlapped with the targets of DN and were considered potential therapeutic targets. The analysis of the network results showed that the AM activity of component quercetin, formononetin, calycosin, 7-O-methylisomucronulatol, and quercetin have a good binding activity with top ten screened targets, such as VEGFA, TNF, IL-6, MAPK, CCL3, NOS3, PTGS2, IL-1β, JUN, and EGFR. GO and KEGG analyses revealed that these targets were associated with inflammatory response, angiogenesis, oxidative stress reaction, rheumatoid arthritis, and other biological process.

CONCLUSIONS

This study demonstrated the multicomponent, multitarget, and multichannel characteristics of AM, which provided a novel approach for further research of the mechanism of AM in the treatment of DN.