Immunological Analysis of Peripheral Artery Disease

Abstract Purpose: To explore the pathogenesis of Peripheral arterial disease (PAD) and provide bioinformatics basis for the prevention and treatment of PAD.Methods: R software is used to analyze differentially expressed genes (DEGs) in PAD patient and control blood samples in GSE27034 and screen for immune differential genes, and then perform GO and KEGG pathway enrichment analysis for immune differential genes. The protein-protein interaction (PPI) network was constructed by using STRING database, and functional modules were analyzed using Cytoscape software. Coexpedia database was used to analyze the gene co-expression network of immune differential genes. Finally, combined with CIBERSORT database, immune cells were obtained by R software.Results: The 21 immune differential genes screened in PAD were mainly involved in TNF signaling pathway, IL-17 signaling pathway, cytokine-cytokine receptor interaction, viral protein interaction with cytokines andcytokine receptor signaling pathways, and rheumatoid arthritis. Compared with the normal group, neutrophils were higher in number in the PAD group, while macrophages M0 were significantly lower (P<0.05).Conclusions: TNF signaling pathway, IL-17 signaling pathway and rheumatoid arthritis are most closely related to the occurrence and development of PAD, and immune differential genes may be the key molecules of PAD, which provides a new idea for further exploring the pathogenesis of PAD.

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Integrating Network Pharmacology with Molecular Docking to Unravel the Active Compounds and Potential Mechanism of Simiao Pill Treating Rheumatoid Arthritis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/5786053 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Mengshi Tang ◽

Xi Xie ◽

Pengji Yi ◽

Jin Kang ◽

Jiafen Liao ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Molecular Docking ◽

Signaling Pathway ◽

Target Genes ◽

Enrichment Analysis ◽

Binding Activity ◽

New Combination ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Potential Mechanism

Objective. To explore the main components and unravel the potential mechanism of simiao pill (SM) on rheumatoid arthritis (RA) based on network pharmacological analysis and molecular docking. Methods. Related compounds were obtained from TCMSP and BATMAN-TCM database. Oral bioavailability and drug-likeness were then screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Additionally, target genes related to RA were acquired from GeneCards and OMIM database. Correlations about SM-RA, compounds-targets, and pathways-targets-compounds were visualized through Cytoscape 3.7.1. The protein-protein interaction (PPI) network was constructed by STRING. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed via R packages. Molecular docking analysis was constructed by the Molecular Operating Environment (MOE). Results. A total of 72 potential compounds and 77 associated targets of SM were identified. The compounds-targets network analysis indicated that the 6 compounds, including quercetin, kaempferol, baicalein, wogonin, beta-sitosterol, and eugenol, were linked to ≥10 target genes, and the 10 target genes (PTGS1, ESR1, AR, PGR, CHRM3, PPARG, CHRM2, BCL2, CASP3, and RELA) were core target genes in the network. Enrichment analysis indicated that PI3K-Akt, TNF, and IL-17 signaling pathway may be a critical signaling pathway in the network pharmacology. Molecular docking showed that quercetin, kaempferol, baicalein, and wogonin have good binding activity with IL6, VEGFA, EGFR, and NFKBIA targets. Conclusion. The integrative investigation based on bioinformatics/network topology strategy may elaborate on the multicomponent synergy mechanisms of SM against RA and provide the way out to develop new combination medicines for RA.

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Uncovering the Mechanisms and Molecular Targets of Weibing Formula 1 against Gastritis: Coupling Network Pharmacology with GEO Database

BioMed Research International ◽

10.1155/2021/5533946 ◽

2021 ◽

Vol 2021 ◽

pp. 1-18

Author(s):

Ke Chen ◽

Luojian Zhang ◽

Zhen Qu ◽

Feng Wan ◽

Jia Li ◽

...

Keyword(s):

Real Time ◽

Signaling Pathway ◽

Quantitative Pcr ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Gene Expression Omnibus ◽

Network Pharmacology ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Real Time Quantitative Pcr

Weibing Formula 1, a classic traditional formula, has been widely used clinically to treat gastritis in recent years. However, the potential pharmacological mechanism of Weibing Formula 1 is still unclear to date. A network pharmacology-based strategy was performed to uncover the underlying mechanisms of Weibing Formula 1 against gastritis. Furthermore, we structured the drug-active ingredients-genes–disease network and PPI network of shared targets, and function enrichment analysis of these targets was carried out. Ultimately, Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR were used to verify the related genes. We found 251 potential targets corresponding to 135 bioactive components of Weibing Formula 1. Then, 327 gastritis-related targets were known gastritis-related targets. Among which, 60 common targets were shared between potential targets of Weibing Formula 1 and known gastritis-related targets. The results of pathway enrichment analysis displayed that 60 common targets mostly participated in various pathways related to Toll-like receptor signaling pathway, MAPK signaling pathway, cytokine-cytokine receptor interaction pathway, chemokine signaling pathway, and apoptosis. Based on the GSE60427 dataset, 15 common genes were shared between differentially expressed genes and 60 candidate targets. The verification results of the GSE5081 dataset showed that except for DUOX2 and VCAM1, the other 13 genes were significantly upregulated in gastritis, which was consistent with the results in the GSE60427 dataset. More importantly, real-time quantitative PCR results showed that the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly upregulated and NOS2, EGFR, and IL-10 were downregulated in gastritis patients, while the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly downregulated and NOS2, EGFR, and IL-10 were upregulated after the treatment of Weibing Formula 1. PTGS2, NOS2, EGFR, MMP9, CXCL2, CXCL8, and IL-10 may be the important direct targets of Weibing Formula 1 in gastritis treatment. Our study revealed the mechanism of Weibing Formula 1 in gastritis from an overall and systematic perspective, providing a theoretical basis for further knowing and application of this formula in the future.

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Bcl-2 Is Involved in Cardiac Hypertrophy through PI3K-Akt Pathway

BioMed Research International ◽

10.1155/2021/6615502 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Xianwei Meng ◽

Jun Cui ◽

Guibin He

Keyword(s):

Gene Expression ◽

Cardiac Hypertrophy ◽

Signaling Pathway ◽

Enrichment Analysis ◽

B Cell Lymphoma ◽

Akt Signaling ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Akt Signaling Pathway ◽

Upregulated Genes

Cardiac hypertrophy (CH) is a common cause of sudden cardiac death and heart failure, resulting in a significant medical burden. The present study is aimed at exploring potential CH-related pathways and the key downstream effectors. The gene expression profile of GSE129090 was obtained from the Gene Expression Omnibus database (GEO), and 1325 differentially expressed genes (DEGs) were identified, including 785 upregulated genes and 540 downregulated genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway enrichment analysis of DEGs were then performed. Although there were no pathways enriched by downregulated genes, many CH-related pathways were identified by upregulated genes, including PI3K-Akt signaling pathway, extracellular matrix- (ECM-) receptor interaction, regulation of actin cytoskeleton, and hypertrophic cardiomyopathy (HCM). In the deeper analysis of PI3K-Akt signaling pathway, we found all the signaling transduction pointed to B cell lymphoma-2- (Bcl-2-) mediated cell survival. We then demonstrated that PI3K-Akt signaling pathway was indeed activated in cardiac hypertrophy. Furthermore, no matter LY294002, an inhibitor of the PI3K/AKT signaling pathway, or Venetoclax, a selective Bcl-2 inhibitor, protected against cardiac hypertrophy. In conclusion, these data indicate that Bcl-2 is involved in cardiac hypertrophy as a key downstream effector of PI3K-Akt signaling pathway, suggesting a potential therapeutic target for the clinical management of cardiac hypertrophy.

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Network Pharmacology-Based Study on the Mechanism of Pinellia ternata in Asthma Treatment

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/9732626 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Yanmin Lyu ◽

Xiangjing Chen ◽

Qing Xia ◽

Shanshan Zhang ◽

Chengfang Yao

Keyword(s):

Candidate Genes ◽

Signaling Pathway ◽

Expression Profiles ◽

Animal Experiments ◽

Enrichment Analysis ◽

Th2 Cells ◽

Network Pharmacology ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Pinellia Ternata

Background. Pinellia ternata (PT), a medicinal plant, has had an extensive application in the treatment of asthma in China, whereas its underlying pharmacological mechanisms remain unclear. Methods. Firstly, a network pharmacology method was adopted to collect activated components of PT from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Targets of PT were assessed by exploiting the PharmMapper website; asthma-related targets were collected from the OMIM website, and target-target interaction networks were built. Secondly, critical nodes exhibiting high possibility were identified as the hub nodes in the network, which were employed to conduct Gene Ontology (GO) comment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis. Finally, the tissue expression profiles of key candidate genes were identified by the Gene Expression Omnibus (GEO) database, and the therapeutic effect of PT was verified by an animal experiment. Results. 57 achievable targets of PT on asthma were confirmed as hub nodes through using the network pharmacology method. As revealed from the KEGG enrichment analysis, the signaling pathways were notably enriched in pathways of the T-cell receptor signaling pathway, JAK-STAT signaling pathway, and cytokine-cytokine receptor interaction. The expression profiles of candidate genes including Mmp2, Nr3c1, il-10, il-4, il-13, il-17a, il-2, tlr4, tlr9, ccl2, csf2, and vefgα were identified. Moreover, according to transcriptome RNA sequencing data from lung tissues of allergic mice compared to normal mice, the mRNA level of Mmp2 and il-4 was upregulated ( P < 0.001 ). In animal experiments, PT could alleviate the allergic response of mice by inhibiting the activation of T-helper type 2 (TH2) cells and the expression of Mmp2 and il-4. Conclusions. Our study provides candidate genes that may be either used for future studies related to diagnosis/prognosis or as targets for asthma management. Besides, animal experiments showed that PT could treat asthma by regulating the expression of Mmp2 and il-4.

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Immunological analysis and differential genes screening of venous thromboembolism

Hereditas ◽

10.1186/s41065-020-00166-6 ◽

2021 ◽

Vol 158 (1) ◽

Author(s):

Li-Na Gao ◽

Qiang Li ◽

Jian-Qin Xie ◽

Wan-Xia Yang ◽

Chong-Ge You

Keyword(s):

Venous Thromboembolism ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

R Software ◽

Pathway Enrichment ◽

Protein Protein Interaction ◽

New Ideas ◽

Gene Expression Profile Data ◽

Differential Genes

Abstract Purpose To explore the pathogenesis of venous thromboembolism (VTE) and provide bioinformatics basis for the prevention and treatment of VTE. Methods The R software was used to obtain the gene expression profile data of GSE19151, combining with the CIBERSORT database, obtain immune cells and differentially expressed genes (DEGs) of blood samples of VTE patients and normal control, and analyze DEGs for GO analysis and KEGG pathway enrichment analysis. Then, the protein-protein interaction (PPI) network was constructed by using the STRING database, the key genes (hub genes) and immune differential genes were screened by Cytoscape software, and the transcription factors (TFs) regulating hub genes and immune differential genes were analyzed by the NetworkAnalyst database. Results Compared with the normal group, monocytes and resting mast cells were significantly expressed in the VTE group, while regulatory T cells were significantly lower. Ribosomes were closely related to the occurrence of VTE. 10 hub genes and immune differential genes were highly expressed in VTE. MYC, SOX2, XRN2, E2F1, SPI1, CREM and CREB1 can regulate the expressions of hub genes and immune differential genes. Conclusions Ribosomal protein family genes are most relevant to the occurrence and development of VTE, and the immune differential genes may be the key molecules of VTE, which provides new ideas for further explore the pathogenesis of VTE.

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Immunological Analysis and Differential Genes Screening of Venous Thromboembolism

10.21203/rs.3.rs-33006/v1 ◽

2020 ◽

Author(s):

Li-Na Gao ◽

Qiang Li ◽

Jian-Qin Xie ◽

Wan-Xia Yang ◽

Chong-Ge You

Keyword(s):

Venous Thromboembolism ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

R Software ◽

Pathway Enrichment ◽

Protein Protein Interaction ◽

New Ideas ◽

Gene Expression Profile Data ◽

Differential Genes

Abstract Purpose: To explore the pathogenesis of venous thromboembolism (VTE) and provide bioinformatics basis for the prevention and treatment of VTE. Methods: The R software was used to obtain the gene expression profile data of GSE19151, combining with the CIBERSORT database, obtain immune cells and differentially expressed genes (DEGs) of blood samples of VTE patients and normal control, and analyze DEGs for GO analysis and KEGG pathway enrichment analysis. Then, the protein-protein interaction (PPI) network was constructed by using the STRING database, the key genes (hub genes) and immune differential genes were screened by Cytoscape software, and the transcription factors (TFs) regulating hub genes and immune differential genes were analyzed by the NetworkAnalyst database. Results: Compared with the normal group, monocytes and resting mast cells were significantly expressed in the VTE group, while regulatory T cells were significantly lower. Ribosomes were closely related to the occurrence of VTE. 10 hub genes and immune differential genes were highly expressed in VTE. MYC, SOX2, XRN2, E2F1, SPI1, CREM and CREB1 can regulate the expressions of hub genes and immune differential genes. Conclusions: Ribosomal protein family genes are most relevant to the occurrence and development of VTE, and the immune differential genes may be the key molecules of VTE, which provides new ideas for further explore the pathogenesis of VTE.

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Bioinformatics Analysis of the Regulatory lncRNA-miRNA-mRNA Network in Patients with Neuropathic Pain

10.21203/rs.3.rs-54799/v1 ◽

2020 ◽

Author(s):

Huai-Gen Zhang ◽

Li Liu ◽

Zhi-Ping Song ◽

Da-Ying Zhang

Keyword(s):

Neuropathic Pain ◽

Signaling Pathway ◽

Interaction Analysis ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Biological Information ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Protein Protein Interaction ◽

Potential Therapeutic Application

Abstract Background: Neuropathic pain (NP) is the main form of chronic pain, caused by damage to the nervous system and dysfunction. Methods: Here, we explore the key molecules involved in the development of NP condition via identification of lncRNA-miRNA-mRNA expression pattern of patients with NP. We identified differentially expressed miRNAs, lncRNA and mRNA through a comprehensive analysis strategy. Subsequently, we used bioinformatics approach to perform pathway enrichment analysis on DEGs and protein-protein interaction analysis. Combined with the three datasets, the lncRNA-miRNA-mRNA network was constructed. It will then be used as targets for drug prediction. Results: The results showed that a total of 8,251 DEGs (4,193 upregulated and 4,058 downregulated) were identified from the three microarray datasets, 959 DEmiRs (455 upregulated and 504 downregulated), 2,848 DElncs (1,324 upregulated and 1,524 downregulated). GO analysis showed that DEGs are mainly enriched in blood circulation, regulation of membrane potential and regulation of ion transmembrane transport. KEGG results showed that DEGs are enriched in neuroactive ligand-receptor interaction, PI3K-Akt signaling pathway and MAPK signaling pathway. When the correlation is set to above 0.8, a total of 31 lncRNAs, 36 miRNAs and 24 mRNAs were screened in the lncRNA-miRNA-mRNAs network. The results of drug prediction indicated the targeted drugs mainly include INDOMETHACIN, GLUTAMIC ACID and PIRACETAM. Conclusion: The lncRNA-miRNA-mRNA network has been carried out a comprehensive biological information analysis and predicted the potential therapeutic application of drugs in patients with NP. The corresponding data has a certain reference for studying the pathological mechanism of NP.

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Identification of Potential Therapeutic Targets For Rheumatoid Arthritis By Bioinformatics

10.21203/rs.3.rs-538306/v1 ◽

2021 ◽

Author(s):

Yi-kuan Du ◽

Erbai Ye ◽

Xiaoling Xiao ◽

Senpeng Zhang ◽

XinNi Ye ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Transcription Factors ◽

Signaling Pathway ◽

Programming Language ◽

Enrichment Analysis ◽

R Programming Language ◽

Key Genes ◽

R Programming ◽

Geo Database ◽

Differential Genes

Abstract Objective: Based on GEO database, we performed bioinformatics analysis on rheumatoid arthritis (RA)-related gene chips to obtain key genes and signaling pathways of RA, understand the molecular mechanism of RA occurrence and development, and provide candidate targets for the diagnosis and treatment of RA.Methods: The chip GSE77298 related to rheumatoid arthritis in GEO database was retrieved, and the R Programming Language analyzed the differential genes. Subsequently, the differential gene protein-protein interaction (PPI) relationship was constructed. The hub gene was screened, and the DAVID database was used for GO enrichment analysis and KEGG pathway analysis of key differential genes. The miRNAs were then subjected to target gene prediction, and then a miRNA-mRNA visualization network map was constructed using Cytoscape. Finally, transcription factors were predicted by the AnimalTFDB database.Results: ①The chip with the serial number of GSE77298 was retrieved from GEO database, and 1539 differential genes were screened out using the R Programming language analysis, including 1156 up-regulated genes and 383 down-regulated genes. ②By DAVID online functional enrichment analysis of differential genes, it was shown that the signaling pathways were mainly rheumatoid arthritis, Staphylococcus aureus infection, chemokine signaling pathway, viral myocarditis, cytokine-cytokine receptor interaction, etc. ③PPI was constructed through String database. Its hub genes were CXCL12, CD44 and CDH2. The top 10 key differential genes in Degree were CXCL8, PTPRC, MMP9, TLR2, FN1, ITGB2, CXCL1, CCL5, CXCR4 and CXCL10. ④Ten important miRNAs such as hsa-miR-30a-3p, hsa-miR-34a-5p, hsa-miR-30d-3p were predicted. ⑤Transcription factors such as GTF3C2, GLYR1, TRIM24, YY1 were predicted.Conclusion: PI3K-AKT signaling pathway and many other pathways are involved in the occurrence and development of RA, and CXCL8, SOCS3, and TLR2 genes may be the key genes in RA. Ten important miRNAs such as has-miR-340-5p may participate in the pathogenesis of RA. Many transcription factors such as YY1 may be involved in RA's disease process, which will provide directions for further research on RA diagnosis and treatment targets of RA.

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Immunological analysis and differential genes screening of venous thromboembolism

10.21203/rs.3.rs-33006/v2 ◽

2020 ◽

Author(s):

Lina Gao ◽

Qiang Li ◽

Jianqin Xie ◽

Wanxia Yang ◽

Chongge You

Keyword(s):

Venous Thromboembolism ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

R Software ◽

Pathway Enrichment ◽

Protein Protein Interaction ◽

New Ideas ◽

Gene Expression Profile Data ◽

Differential Genes

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CircRNA/lncRNA-miRNA-mRNA network in the blood exosomes of patients with atherosclerosis

10.21203/rs.3.rs-496464/v1 ◽

2021 ◽

Author(s):

Wan Zhang ◽

Ting Zhu ◽

Li Li ◽

Zhenyu Guo

Keyword(s):

Signaling Pathway ◽

Area Under The Curve ◽

Interaction Network ◽

Enrichment Analysis ◽

Arterial Disease ◽

Differentially Expressed ◽

Estrogen Signaling ◽

Pathway Enrichment Analysis ◽

Clinical Value ◽

Positive Regulation

Abstract Background: Atherosclerosis (AS) is a systemic, chronic and multifocal disease and is the primary pathological basis of cardiovascular diseases, such as coronary heart disease (CHD) and peripheral arterial disease (PAD). Our study attempted to identify aberrant exosome-derived circRNAs in AS and determine their potential clinical value. Methods: The expression of mRNA, circRNA and lncRNA in the blood exosomes of CHD patients and healthy controls was obtained from the exoRBase database. The corresponding miRNAs of mRNA, circRNA and lncRNA were predicted via ENCORI and the miRcode database. The circRNA/lncRNA-miRNA-mRNA interaction network was established based on a competitive endogenous RNA regulatory mechanism. Aberrant circRNAs in the aforementioned network were validated in patients with PAD by real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). Results: Based on the cutoff criteria of P<0.05, we identified 85 differentially expressed circRNAs (4 up- and 81 downregulated), 43 differentially expressed lncRNAs (24 up- and 19 downregulated) and 312 differentially expressed genes (55 up- and 257 downregulated). Gene Ontology (GO) analysis revealed that the biological process (BP) terms of the DEGs were significantly enriched in the positive regulation of phosphoprotein phosphatase activity and the positive regulation of protein dephosphorylation. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis demonstrated that DEGs were closely related to the glucagon signaling pathway and estrogen signaling pathway. The relative expression level of hsa_circ_0001360 was significantly downregulated in blood exosomes from patients with PAD, exhibiting an area under the curve of 0.92 (P=0.0283). Conclusion: The circRNA/lncRNA-miRNA-mRNA interaction network might help to elucidate the pathogenesis of AS. Hsa_circ_0001360 was significantly downregulated in blood exosomes in patients with PAD, and this RNA might represent an important diagnostic biomarker of AS.

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