Identification of Potential Genetic Biomarkers and Target Genes of Peri-Implantitis Using Bioinformatics Tools

Objectives. To investigate potential genetic biomarkers of peri-implantitis and target genes for the therapy of peri-implantitis by bioinformatics analysis of publicly available data. Methods. The GSE33774 microarray dataset was downloaded from the Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) between peri-implantitis and healthy gingival tissues were identified using the GEO2R tool. GO enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the DAVID database and the Metascape tool, and the results were expressed as a bubble diagram. The protein-protein interaction network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized using Cytoscape. The hub genes were screened by the cytoHubba plugin of Cytoscape. The potential target genes associated with peri-implantitis were obtained from the DisGeNET database and the Open Targets Platform. The intersecting genes were identified using the Venn diagram web tool. Results. Between the peri-implantitis group and the healthy group, 205 DEGs were investigated including 140 upregulated genes and 65 downregulated genes. These DEGs were mainly enriched in functions such as the immune response, inflammatory response, cell adhesion, receptor activity, and protease binding. The results of KEGG pathway enrichment analysis revealed that DEGs were mainly involved in the cytokine-cytokine receptor interaction, pathways in cancer, and the PI3K-Akt signaling pathway. The intersecting genes, including IL6, TLR4, FN1, IL1β, CXCL8, MMP9, and SPP1, were revealed as potential genetic biomarkers and target genes of peri-implantitis. Conclusions. This study provides supportive evidence that IL6, TLR4, FN1, IL1β, CXCL8, MMP9, and SPP1 might be used as potential target biomarkers for peri-implantitis which may provide further therapeutic potentials for peri-implantitis.

Download Full-text

Identification of differentially expressed genes and signalling pathways related to ovarian endometriosis based on integrated bioinformatic analysis

10.21203/rs.3.rs-161050/v2 ◽

2021 ◽

Author(s):

Kainan Lin ◽

Zhenyan Pan ◽

Renke He ◽

Hanchu Wang ◽

Kai Zhou ◽

...

Keyword(s):

Endoplasmic Reticulum ◽

Kegg Pathway ◽

Expression Profiles ◽

Enrichment Analysis ◽

Protein Processing ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Channel Activity ◽

Voltage Gated ◽

Pathway Enrichment

Abstract Purpose Endometriosis is a common gynaecological disease; however, the specific mechanism and the key molecules involved in endometriosis have not been elucidated. This study aimed to identify key genes associated with poor prognosis and further uncover underlying mechanisms. Methods Data regarding mRNA expression profiles used in this study were retrieved from the Gene Expression Omnibus (GEO) database, and a total of three mRNA expression profiles were included in subsequent analyses (GSE31515, GSE58178 and GSE120103). We divided all differentially expressed genes (DEGs) into up-regulated and down-regulated groups. Then, we conducted Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) analysis using R software.Results A total of 304 DEGs were identified between endometriosis tissues and normal endometrium tissues using integrated analysis, including 185 up-regulated genes and 119 down-regulated genes. GO analysis revealed that the up-regulated DEGs of endometriosis were closely associated with voltage-gated calcium channel activity, whereas the down-regulated DEGs were enriched in uterus development. KEGG pathway enrichment analysis indicated that the up-regulated DEGs were mainly involved in cytokine-cytokine receptor interaction, whereas down-regulated DEGs were enriched in protein processing in the endoplasmic reticulum. In addition, PPIs of these DEGs were visualized using the Cytoscape platform and the Search Tool for the Retrieval of Interacting Genes (STRING). PPI analysis identified 10 potential DEG-related protein targets, including CCND1, IL6, CCL2, COL1A2, PTGS2, VCAM1, COL3A1, ELN, SERPINE1, and HSP90B1. Conclusion In conclusion, the present study reveals that voltage-gated calcium channel activity, uterus development, cytokine-cytokine receptor interaction and protein processing in the endoplasmic reticulum may be involved in the development of endometriosis. In addition, these identified DEGs may exhibit clinical significance for the diagnosis and treatment of endometriosis.

Download Full-text

Mechanism of YuPingFeng in the Treatment of COPD Based on Network Pharmacology

BioMed Research International ◽

10.1155/2020/1630102 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Yunhong Yin ◽

Jianyu Liu ◽

Mengyu Zhang ◽

Rui Li ◽

Xiao Liu ◽

...

Keyword(s):

Clinical Practice ◽

Target Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Signalling Pathways ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Herbal Formula ◽

Pathway Enrichment ◽

Topological Parameters

YuPingFeng (YPF) granules are a classic herbal formula extensively used in clinical practice in China for the treatment of COPD. However, the pathological mechanisms of YPF in COPD remain undefined. In the present research, a network pharmacology-based strategy was implemented to elucidate the underlying multicomponent, multitarget, and multipathway modes of action of YPF against COPD. First, we identified putative YPF targets based on TCMSP databases and constructed a network containing interactions between putative YPF targets and known therapeutic targets of COPD. Next, two topological parameters, “degree” and “closeness,” were calculated to identify target genes in the network. The major hubs were imported to the MetaCore database for pathway enrichment analysis. In total, 23 YPF active ingredients and 83 target genes associated with COPD were identified. Through protein interaction network analysis, 26 genes were identified as major hubs due to their topological importance. GO and KEGG enrichment analysis results revealed YPF to be mainly associated with the response to glucocorticoids and steroid hormones, with apoptotic and HIF-1 signalling pathways being dominant and correlative pathways. The promising utility of YPF in the treatment of COPD has been demonstrated by a network pharmacology approach.

Download Full-text

Identification of Differentially Expressed Genes and Signalling Pathways Related to Ovarian Endometriosis Based on Integrated Bioinformatic Analysis

10.21203/rs.3.rs-161050/v1 ◽

2021 ◽

Author(s):

Kainan Lin ◽

Zhenyan Pan ◽

Renke He ◽

Hanchu Wang ◽

Kai Zhou ◽

...

Keyword(s):

Endoplasmic Reticulum ◽

Kegg Pathway ◽

Expression Profiles ◽

Enrichment Analysis ◽

Protein Processing ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Channel Activity ◽

Voltage Gated ◽

Pathway Enrichment

Abstract Purpose: Endometriosis is a common gynaecological disease; however, the specific mechanism and the key molecules involved in endometriosis have not been elucidated. This study aimed to identify key genes associated with poor prognosis and further uncover underlying mechanisms.Methods: Data regarding mRNA expression profiles used in this study were retrieved from the Gene Expression Omnibus (GEO) database, and a total of three mRNA expression profiles were included in subsequent analyses (GSE31515, GSE58178 and GSE120103). We divided all differentially expressed genes (DEGs) into up-regulated and down-regulated groups. Then, we conducted Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) analysis using R software.Results: A total of 304 DEGs were identified between endometriosis tissues and normal endometrium tissues using integrated analysis, including 185 up-regulated genes and 119 down-regulated genes. GO analysis revealed that the up-regulated DEGs of endometriosis were closely associated with voltage-gated calcium channel activity, whereas the down-regulated DEGs were enriched in uterus development. KEGG pathway enrichment analysis indicated that the up-regulated DEGs were mainly involved in cytokine-cytokine receptor interaction, whereas down-regulated DEGs were enriched in protein processing in the endoplasmic reticulum. In addition, PPIs of these DEGs were visualized using the Cytoscape platform and the Search Tool for the Retrieval of Interacting Genes (STRING). PPI analysis identified 10 potential DEG-related protein targets, including CCND1, IL6, CCL2, COL1A2, PTGS2, VCAM1, COL3A1, ELN, SERPINE1, and HSP90B1. Conclusion: In conclusion, the present study reveals that voltage-gated calcium channel activity, uterus development, cytokine-cytokine receptor interaction and protein processing in the endoplasmic reticulum may be involved in the development of endometriosis. In addition, these identified DEGs may exhibit clinical significance for the diagnosis and treatment of endometriosis.

Download Full-text

Mechanism Prediction of Astragalus membranaceus against Cisplatin-Induced Kidney Damage by Network Pharmacology and Molecular Docking

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/9516726 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Congchao Jia ◽

Xianchao Pan ◽

Binyou Wang ◽

Pengyu Wang ◽

Yiwei Wang ◽

...

Keyword(s):

Molecular Docking ◽

Signaling Pathways ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Kidney Damage ◽

Astragalus Membranaceus ◽

Venn Diagram ◽

Pathway Enrichment Analysis ◽

Active Components ◽

Pathway Enrichment

Background. Cisplatin is a frequently used and effective chemotherapy drug in clinical practice, but severe side effects limit its use, among which nephrotoxicity is considered the most serious and prolonged damage to the body. Astragalus membranaceus (AM) is a well-known herbal medicine, and modern pharmacological studies have confirmed its antioxidant, immunomodulatory, and antiapoptotic effects. Clinical studies have shown that AM and its active components can attenuate cisplatin-induced kidney damage, but the molecular mechanism has not been fully expounded. Materials and Methods. First, the components and targets information of AM were collected from the TCMSP, and the relevant targets of cisplatin-induced kidney damage were accessed from the GeneCards and OMIM databases. Then, the core targets were selected by the Venn diagram and network topology analysis, which was followed by GO and KEGG pathway enrichment analysis. Finally, we construct a component-target-pathway network. Furthermore, molecular docking was carried out to identify the binding activity between active components and key targets. Results. A total of 20 active components and 200 targets of AM and 646 targets related to cisplatin-induced kidney damage were obtained. 91 intersection targets were found between AM and cisplatin-induced kidney damage. Then, 16 core targets were identified, such as MAPK1, TNF-α, and p53. Furthermore, GO and KEGG pathway enrichment analysis suggested that MAPK, Toll-like receptor, and PI3K-Akt signaling pathways may be of significance in the treatment of cisplatin-induced kidney damage by AM. Molecular docking indicated that quercetin and kaempferol had high binding affinities with many core targets. Conclusion. In summary, the active components, key targets, and signaling pathways of AM in the treatment of cisplatin-induced kidney damage were predicted in this study, which contributed to the development and application of AM.

Download Full-text

Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207322666190717124507 ◽

2019 ◽

Vol 22 (6) ◽

pp. 411-420 ◽

Cited By ~ 5

Author(s):

Xian-Jun Wu ◽

Xin-Bin Zhou ◽

Chen Chen ◽

Wei Mao

Keyword(s):

Cardiovascular Disease ◽

Cardiovascular Diseases ◽

Signaling Pathway ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Therapeutic Effects ◽

Pathway Enrichment ◽

Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

Download Full-text

Decoding the molecular mechanism of parthenocarpy in Musa spp. through protein–protein interaction network

Scientific Reports ◽

10.1038/s41598-021-93661-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Suthanthiram Backiyarani ◽

Rajendran Sasikala ◽

Simeon Sharmiladevi ◽

Subbaraya Uma

Keyword(s):

Candidate Genes ◽

Protein Interaction ◽

Target Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Auxin Signaling ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Protein Protein Interaction ◽

The Difference

AbstractBanana, one of the most important staple fruit among global consumers is highly sterile owing to natural parthenocarpy. Identification of genetic factors responsible for parthenocarpy would facilitate the conventional breeders to improve the seeded accessions. We have constructed Protein–protein interaction (PPI) network through mining differentially expressed genes and the genes used for transgenic studies with respect to parthenocarpy. Based on the topological and pathway enrichment analysis of proteins in PPI network, 12 candidate genes were shortlisted. By further validating these candidate genes in seeded and seedless accession of Musa spp. we put forward MaAGL8, MaMADS16, MaGH3.8, MaMADS29, MaRGA1, MaEXPA1, MaGID1C, MaHK2 and MaBAM1 as possible target genes in the study of natural parthenocarpy. In contrary, expression profile of MaACLB-2 and MaZEP is anticipated to highlight the difference in artificially induced and natural parthenocarpy. By exploring the PPI of validated genes from the network, we postulated a putative pathway that bring insights into the significance of cytokinin mediated CLAVATA(CLV)–WUSHEL(WUS) signaling pathway in addition to gibberellin mediated auxin signaling in parthenocarpy. Our analysis is the first attempt to identify candidate genes and to hypothesize a putative mechanism that bridges the gaps in understanding natural parthenocarpy through PPI network.

Download Full-text

Is There a Relationship Between Psoriasis and Hepatitis C?: a Meta-analysis and Bioinformatics Investigation

10.21203/rs.3.rs-249926/v1 ◽

2021 ◽

Author(s):

Yong Liu ◽

Sheng Nan Cui ◽

Meng Yao Duan ◽

Zhi Li Dou ◽

Yi Zhen Li ◽

...

Keyword(s):

Hepatitis C ◽

Meta Analysis ◽

Enrichment Analysis ◽

Case Control ◽

Cochrane Library ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Overlapping Genes ◽

Cross Sectional ◽

Pathway Enrichment

Abstract Background: The relationship between psoriasis and hepatitis C was previously controversial, so our purpose is to investigate this connection.Methods: We conducted a systematic review of the case-control, cross-sectional and cohort studies examining the association between psoriasis and hepatitis C in PubMed, EMBASE and Cochrane library databases and investigated the overlapping genes between psoriasis targets and hepatitis C targets using bioinformatics analysis. Based on overlapping genes and hub nodes, we also constructed the protein-protein interaction (PPI) network and module respectively, followed by the pathway enrichment analysis. Results: We included 11 publications that reported a total of 11 studies (8 cross-sectional and 3 case-control). The case–control and cross-sectional studies included 25,047 psoriasis patients and 4,091,631 controls in total. Psoriasis was associated with a significant increase of prevalent hepatitis C (OR 1.72; 95% confidence interval [CI] (1.17-2.52)). A total of 389 significant genes were common to both hepatitis C and psoriasis, which mainly involved IL6, TNF, IL10, ALB, STAT3 and CXCL8. The module and pathway enrichment analyses showed that the common genes had the potential to influence varieties of biological pathways, including the inflammatory response, cytokine activity, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, which play an important role in the pathogenesis of hepatitis C and psoriasis.Conclusion: Patients with psoriasis display increased prevalence of hepatitis C and the basic related mechanisms between hepatitis C and psoriasis had been preliminarily clarified.

Download Full-text

Network Pharmacology and Molecular Docking Suggest the Mechanism for Biological Activity of Rosmarinic Acid

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/5190808 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Minglong Guan ◽

Lan Guo ◽

Hengli Ma ◽

Huimei Wu ◽

Xiaoyun Fan

Keyword(s):

Biological Activity ◽

Molecular Docking ◽

Protein Interaction ◽

Protein Interaction Network ◽

Rosmarinic Acid ◽

Target Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis

Rosmarinic acid (RosA) is a natural phenolic acid compound, which is mainly extracted from Labiatae and Arnebia. At present, there is no systematic analysis of its mechanism. Therefore, we used the method of network pharmacology to analyze the mechanism of RosA. In our study, PubChem database was used to search for the chemical formula and the Chemical Abstracts Service (CAS) number of RosA. Then, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to evaluate the pharmacodynamics of RosA, and the Comparative Toxicogenomics Database (CTD) was used to identify the potential target genes of RosA. In addition, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes were carried out by using the web-based gene set analysis toolkit (WebGestalt). At the same time, we uploaded the targets to the STRING database to obtain the protein interaction network. Then, we carried out a molecular docking about targets and RosA. Finally, we used Cytoscape to establish a visual protein-protein interaction network and drug-target-pathway network and analyze these networks. Our data showed that RosA has good biological activity and drug utilization. There are 55 target genes that have been identified. Then, the bioinformatics analysis and network analysis found that these target genes are closely related to inflammatory response, tumor occurrence and development, and other biological processes. These results demonstrated that RosA can act on a variety of proteins and pathways to form a systematic pharmacological network, which has good value in drug development and utilization.

Download Full-text

System Pharmacological Mechanism and Compatibility Laws of Jianghuang from Traditional Chinese Medicine In Blood-Regulating Formulae

10.21203/rs.3.rs-29958/v1 ◽

2020 ◽

Author(s):

Zhiqiang Liu ◽

Bolong Wang

Keyword(s):

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Kegg Pathway ◽

Inflammatory Diseases ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Pharmacological Effects ◽

Ppi Network ◽

Pathway Enrichment ◽

Pharmacological Mechanism

Abstract Background: Jianghuang (JH) is a popular ingredient in blood-regulating traditional Chinese Medicine (TCM) that could be effective for the treatment of various diseases. We demonstrate the compatibility laws and system pharmacological mechanisms of the key formula containing JH by leveraging data mining of bioinformatics databases.Material/Methods: The compatibility laws of blood-regulating formulae containing JH from the Chinese Traditional Medicine Formula Dictionary were analyzed using a generalized rule induction (GRI) algorithm implemented. The putative target gene and miRNA were retrieved via a combination of the Arrowsmith knowledge discovery tool and FunRich 3.1.3. System pharmacological mechanisms are traced by their protein-protein interaction (PPI) network, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted using Uniprot, the Human Protein Atlas (HPA), STRING 11.0, and KOBAS 3.0.Results: We found that the JH-CX-DG formula (Ligusticum chuanxiong-Angelica sinensis) could represent a key formula containing JH in blood-regulating TCM formulae. The JH-CX-DG formula was observed to directly target AKT, TLR4, caspase-3, PI3K, mTOR, p38 MAPK, VEGF, iNOS, Nrf2, BDNF, NF-κB, Bcl-2, and Bax 13 targets and regulate targets through 13 miRNA. The PPI network and KEGG pathway enrichment analysis showed that the JH-CX-DG formula possess potential pharmacological effects including anti-inflammatory, improving microcirculation, and anti-tumor through the regulation of multiple pathways including PI3K/Akt, MAPK, Toll-like receptor, T cell receptor, EGFR, VEGFR, Apoptosis, HIF-1 (p < 0.05).Conclusion: The JH-CX-DG formula can exert beneficial pharmacological effects through multi-target and multi-pathway interactions. It can be effectively administered for the treatment of inflammatory diseases, microcirculation disorders, cardiovascular disease, and cancer. We found a new effective drug formula through analyzing the compatibility law and systemic pharmacological mechanism of JH. Our study provides a theoretical basis and directions for subsequent research on the JH-CX-DG formula.

Download Full-text

Transcriptomic analysis of Procambarus clarkii affected by “Black May” disease

Scientific Reports ◽

10.1038/s41598-020-78191-8 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Guoqing Shen ◽

Xiao Zhang ◽

Jie Gong ◽

Yang Wang ◽

Pengdan Huang ◽

...

Keyword(s):

Procambarus Clarkii ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Apoptosis Pathway ◽

Pathway Enrichment ◽

Cellular Processes ◽

Expression Of Genes ◽

Muscle Tissues

AbstractEach year from April to May, high mortality rates are reported in red swamp crayfish (Procambarus clarkii) cultured in Jiangsu and other regions, in China, and this phenomenon has come to be known as “Black May” disease (BMD). Therefore, in order to investigate the possible causes of this disease, this study gathered BMD-affected P. clarkii samples and performed transcriptome analysis on hepatopancreas, gill, and muscle tissues. A total of 19,995,164, 149,212,804, and 222,053,848 clean reads were respectively obtained from the gills, muscle, and hepatopancreas of BMD-affected P. clarkii, and 114,024 unigenes were identified. The number of differentially expressed genes (DEGs) in gill, muscle, and hepatopancreas was 1703, 964, and 476, respectively. GO and KEGG enrichment analyses of the DEGs were then conducted. Based on KEGG pathway enrichment analysis, the most significantly differentially expressed pathways were mainly those involved with metabolism, human disease, and cellular processes. Further analysis of the significantly DEGs revealed that they were mainly related to the mitochondrial-mediated apoptosis pathway and that the expression of these DEGs was mostly down-regulated. Moreover, the expression of genes related to immune and metabolism-related pathways was also significantly down-regulated, and these significantly-inhibited pathways were the likely causes of P. clarkii death. Therefore, our results provide a basis for the identification of BMD causes.

Download Full-text