scholarly journals Bioinformatics Analysis of Genes and Mechanisms in Postherpetic Neuralgia

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yong Qiu ◽  
Meng-Lei Hao ◽  
Xu-Tao Cheng ◽  
Zhen Hua
Keyword(s):  
Neuropathic Pain ◽  
Postherpetic Neuralgia ◽  
Bioinformatics Analysis ◽  
Life Quality ◽  
Hub Genes ◽  
Comparative Toxicogenomics Database ◽  
Protein Protein Interaction ◽  
Receptor Interactions ◽  
Anxiety Depression

Objective. Elderly patients are prone to postherpetic neuralgia (PHN), which may cause anxiety, depression, and sleep disorders and reduce quality of life. As a result, the life quality of patients was seriously reduced. However, the pathogenesis of PHN has not been fully elucidated, and current treatments remain inadequate. Therefore, it is important to explore the molecular mechanism of PHN. Methods. We analyzed the GSE64345 dataset, which includes gene expression from the ipsilateral dorsal root ganglia (DRG) of PHN model rats. Differentially expressed genes (DEGs) were identified and analyzed by Gene Ontology. Protein-protein interaction (PPI) network was constructed. The miRNA associated with neuropathic pain and inflammation was found in miRNet. Hub genes were identified and analyzed in Comparative Toxicogenomics Database (CTD). miRNA-mRNA networks associated with PHN were constructed. Results. A total of 116 genes were up-regulated in the DRG of PHN rats, and 135 genes were down-regulated. Functional analysis revealed that variations were predominantly enriched for genes involved in neuroactive ligand-receptor interactions, the Jak-STAT signaling pathway, and calcium channel activity. Eleven and thirty-one miRNAs associated with neuropathic pain and inflammation, respectively, were found. Eight hub genes (S1PR1, OPRM1, PDYN, CXCL3, S1PR5, TBX5, TNNI3, MYL7, PTGDR2, and FBXW2) associated with PHN were identified. Conclusions. Bioinformatics analysis is a useful tool to explore the mechanism and pathogenesis of PHN. The identified hub genes may participate in the onset and development of PHN and serve as therapeutic targets.

scholarly journals Differential Expression of mRNAs in Peripheral Blood Related to Prodrome and Progression of Alzheimer’s Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Weishuang Xue ◽  
Jinwei Li ◽  
Kailei Fu ◽  
Weiyu Teng
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Bioinformatics Analysis ◽  
Gene Expression Omnibus ◽  
Venn Diagram ◽  
Ppi Network ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Ppi Networks

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. Methods. We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. Results. Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. Conclusions. Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.

scholarly journals Bioinformatic Analysis of Neuroimmune Mechanism of Neuropathic Pain

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Hao Yu ◽  
Yang Liu ◽  
Chao Li ◽  
Jianhao Wang ◽  
Bo Yu ◽  
...  
Keyword(s):  
Neuropathic Pain ◽  
Inflammatory Responses ◽  
Interaction Network ◽  
Gene Interaction ◽  
Bioinformatic Analysis ◽  
Venn Diagram ◽  
Hub Genes ◽  
Gene Interaction Network ◽  
Pathway Enrichment ◽  
Protein Protein Interaction

Background. Neuropathic pain (NP) is a devastating complication following nerve injury, and it can be alleviated by regulating neuroimmune direction. We aimed to explore the neuroimmune mechanism and identify some new diagnostic or therapeutic targets for NP treatment via bioinformatic analysis. Methods. The microarray GSE18803 was downloaded and analyzed using R. The Venn diagram was drawn to find neuroimmune-related differentially expressed genes (DEGs) in neuropathic pain. Gene Ontology (GO), pathway enrichment, and protein-protein interaction (PPI) network were used to analyze DEGs, respectively. Besides, the identified hub genes were submitted to the DGIdb database to find relevant therapeutic drugs. Results. A total of 91 neuroimmune-related DEGs were identified. The results of GO and pathway enrichment analyses were closely related to immune and inflammatory responses. PPI analysis showed two important modules and 8 hub genes: PTPRC, CD68, CTSS, RAC2, LAPTM5, FCGR3A, CD53, and HCK. The drug-hub gene interaction network was constructed by Cytoscape, and it included 24 candidate drugs and 3 hub genes. Conclusion. The present study helps us better understand the neuroimmune mechanism of neuropathic pain and provides some novel insights on NP treatment, such as modulation of microglia polarization and targeting bone resorption. Besides, CD68, CTSS, LAPTM5, FCGR3A, and CD53 may be used as early diagnostic biomarkers and the gene HCK can be a therapeutic target.

scholarly journals Spica Prunellae Extract Enhances Fluorouracil Sensitivity of 5-Fluorouracil-Resistant Human Colon Carcinoma HCT-8/5-FU Cells via TOP2α and miR-494

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yi Fang ◽  
Chi Yang ◽  
Ling Zhang ◽  
Lihui Wei ◽  
Jiumao Lin ◽  
...  
Keyword(s):  
Bioinformatics Analysis ◽  
Ethanol Extract ◽  
Human Colon ◽  
Protein Interaction Networks ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Beneficial Effects ◽  
Human Colon Carcinoma ◽  
Public Dataset ◽  
Protein Protein Interaction Networks

The use of 5-fluorouracil (5-FU) has been proven benefits, but it also has adverse events in colorectal cancer (CRC) chemotherapy. In this study, we explored the mechanism of 5-FU resistance by bioinformatics analysis of the NCBI public dataset series GSE81005. Fifteen hub genes were screened out of 582 different expressed genes. Modules of the hub genes in protein-protein interaction networks gathered to TOP2α showed a decrease in HCT-8 cells but an increase in 5-FU-resistant HCT-8/5-FU cells with 5-FU exposure. Downregulation of TOP2α with siRNA or miR-494 transfection resulted in an increase of cytotoxicity and decrease of cell colonies to 5-FU for HCT-8/5-FU cells. Moreover, we found that an ethanol extract of Spica Prunellae (EESP), which is a traditional Chinese medicine with clinically beneficial effects in various cancers, was able to enhance the sensitivity of 5-FU in HCT-8/5-FU cells and partly reverse the 5-FU resistance effect. It significantly helped suppress cell growth and induced cell apoptosis in HCT-8/5-FU cells with the expression of TOP2α being significantly suppressed, which increased by 5-FU. Consistently, miR-494, which reportedly regulates TOP2α, exhibited reverse trends in EESP/5-FU combination treatment. These results suggested that Spica Prunellae may be beneficial in the treatment of 5-FU-resistant CRC patients.

scholarly journals Identification of Hub Genes in Pancreatic Ductal Adenocarci-noma Using Bioinformatics Analysis

2021 ◽  
Author(s):  
Congcong Wang ◽  
Jianping Guo ◽  
Xiaoyang Zhao ◽  
Jia Jia ◽  
Wenting Xu ◽  
...  
Keyword(s):  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Omnibus ◽  
Receptor Interaction ◽  
Analysis Tool ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Kegg Analysis ◽  
Prognostic Assessment ◽  
Scheme Selection

Background: To address the biomarkers that correlated with the prognosis of patients with PDCA using bioinformatics analysis. Methods: The raw data of genes were obtained from the Gene Expression Omnibus. We screened differently expressed genes (DEGs) by Rstudio. Database for Annotation,Visualization and Intergrated Discovery was used to investigate their biological function by Gene Ontology(GO) and Kyoto Encyclopedia of Genes (KEGG) analysis. Protein-protein interaction of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database (STRING) and visualized by Cytoscape. Genes calculated by CytoHubba with degree >10 were identified as hub genes. Then, the identified hub genes were verified by UALCAN online analysis tool to evaluate the prognostic value in PDCA. Results: Three expression profiles (GSE15471, GSE16515 and GSE32676) were downloaded from GEO database. The three sets of DEGs exhibited an intersection consisting of 223 genes (214 upregulated DEGs and 9 downregulated DEGs). GO analysis showed that the 223 DEGs were significantly enriched in extracellular exosome, plasma membrane and extracellular space. ECM-receptor interaction, PI3K-Akt signaling pathway and Focal adhesion were the most significantly enriched pathway according to KEGG analysis. By combining the results of Cytohubba, 30 hub genes with a high degree of connectivity were picked out. Finally, we candidated 3 biomarkers by UALCAN online survival analysis, including CEP55, ANLN and PRC1. Conclusion: we identified CEP55, ANLN and PRC1 may be the potential biomarkers and therapeutic targets of PDCA, which used for prognostic assessment and scheme selection.

scholarly journals Neuropathic Pain: Biomolecular Intervention and Imaging via Targeting Microglia Activation

Biomolecules ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1343
Author(s):  
Aijun Ji ◽  
Jinbin Xu
Keyword(s):  
Neuropathic Pain ◽  
Molecular Imaging ◽  
Functional Imaging ◽  
Clinical Studies ◽  
Essential Role ◽  
Life Quality ◽  
Herbal Medicines ◽  
Active Components ◽  
Accompanying Symptoms

Many diseases, including cancer, can lead to neuropathic pain (NP). NP is one of the accompanying symptoms of suffering in many conditions and the life quality of NP patient is seriously affected. Due to complex causes, the effects of clinical treatments have been very unsatisfactory. Many experts have found that neuron-microglia interaction plays an essential role in NP occurrence and development. Therefore, the activation of microglia, related inflammatory mediators and molecular and cellular signaling pathways have become the focus of NP research. With the help of modern functional imaging technology, advanced pre-and clinical studies have been carried out and NP interventions have been attempted by using the different pharmaceuticals and the extracted active components of various traditional herbal medicines. In this communication, we review the mechanism of microglia on NP formation and treatment and molecular imaging technology’s role in the clinical diagnosis and evaluation of NP therapies.

scholarly journals Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Lei Shi ◽  
Zilu Wen ◽  
Hongwei Li ◽  
Yanzheng Song
Keyword(s):  
Gene Expression Analysis ◽  
Bioinformatics Analysis ◽  
Biological Process ◽  
Cell Component ◽  
Hub Genes ◽  
Nucleotide Sugar ◽  
Protein Protein Interaction ◽  
Differential Gene ◽  
Tuberculous Pleurisy ◽  
Therapy Strategies

Improving the understanding of the molecular mechanism of tuberculous pleurisy is required to develop diagnosis and new therapy strategies of targeted genes. The purpose of this study is to identify important genes related to tuberculous pleurisy. In this study, the expression profile obtained by sequencing the surgically resected pleural tissue was used to explore the differentially co-expressed genes between tuberculous pleurisy tissue and normal tissue. 29 differentially co-expressed genes were screened by weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis methods. According to the functional annotation analysis of R clusterProfiler software package, these genes are mainly enriched in nucleotide−sugar biosynthetic process (biological process), ficolin−1−rich granule lumen (cell component), and electron transfer activity (molecular function). In addition, in the protein-protein interaction (PPI) network, 20 hub genes of DEGs and WCGNA genes were identified using the CytoHubba plug-in of Cytoscape. In the end, RPL17 was identified as a gene that can be the biomarker of tuberculous pleurisy. At the same time, there are seven genes that may have relationship with the disease (UBA7, NDUFB8, UQCRFS1, JUNB, PSMC4, PHPT1, and MAPK11).

scholarly journals Putative Genes and Pathways Involved in the Acne Treatment of Isotretinoin via Microarray Data Analyses

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Biao Chen ◽  
Peishan Li ◽  
Jun Li ◽  
Jinping Chen
Keyword(s):  
Life Quality ◽  
Research Direction ◽  
Common Disease ◽  
Severe Acne ◽  
Protein Protein Interaction ◽  
Therapeutic Mechanism ◽  
Sebum Production ◽  
Acne Treatment ◽  
Microarray Datasets

Acne is the eighth most common disease worldwide. Disease burden of acne such as anxiety, reduced self-esteem, and facial scarring lowers the life quality of acne patients. Isotretinoin is the most potent treatment for moderate-severe acne. However, the adverse events of isotretinoin especially teratogenicity limit its use. This study aims at investigating the therapeutical mechanisms of isotretinoin using bioinformatics analysis. Differentially expressed genes (DEGs) were filtered from microarray datasets GSE10432, GSE10433, and GSE11792. Functional and pathway enrichment analyses of DEGs were performed. Protein–protein interaction (PPI) network and module analyses were also conducted based on DEGs. Using isotretinoin for 1 week, LCN2, PTGES, and GDF15 were upregulated and might mediate sebocytes apoptosis and thus decreased sebum production; CCL2 originated from activated TNF signaling pathway and S100A7 could be related with “acne-flare”. While treating with isotretinoin for 8 weeks, key genes were downregulated, including HMGCS1, HMGCR, FDFT1, MVD, IDI1, and FDPS, which may be associated with decreased sebum synthesis; HMGCS1, HMGCR, and FDFT1 also probably associated with apoptosis of sebocytes. There were only two common genes including ACSBG1 and BCAT2 which worked in both 1 week and 8 weeks and could associate with decreased sebum synthesis and apoptosis of sebocytes, respectively. These results indicate potential therapeutics and side effect mechanisms of isotretinoin in the acne treatment and provide a research direction to further investigate the therapeutic mechanism of isotretinoin and thus develop retinoid-like compounds with similar curative effect and without teratogenicity.

scholarly journals Identification of key genes in allergic rhinitis by bioinformatics analysis

2021 ◽  
Vol 49 (7) ◽  
pp. 030006052110295
Author(s):  
Yunfei Zhang ◽  
Yue Huang ◽  
Wen-xia Chen ◽  
Zheng-min Xu
Keyword(s):  
Allergic Rhinitis ◽  
Antigen Processing ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Validation Dataset ◽  
Ppi Network ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Pathway Analyses ◽  
Antigen Processing And Presentation

Objective This study aimed to explore the potential molecular mechanism of allergic rhinitis (AR) and identify gene signatures by analyzing microarray data using bioinformatics methods. Methods The dataset GSE19187 was used to screen differentially expressed genes (DEGs) between samples from patients with AR and healthy controls. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were applied for the DEGs. Subsequently, a protein–protein interaction (PPI) network was constructed to identify hub genes. GSE44037 and GSE43523 datasets were screened to validate critical genes. Results A total of 156 DEGs were identified. GO analysis verified that the DEGs were enriched in antigen processing and presentation, the immune response, and antigen binding. KEGG analysis demonstrated that the DEGs were enriched in Staphylococcus aureus infection, rheumatoid arthritis, and allograft rejection. PPI network and module analysis predicted seven hub genes, of which six ( CD44, HLA-DPA1, HLA-DRB1, HLA-DRB5, MUC5B, and CD274) were identified in the validation dataset. Conclusions Our findings suggest that hub genes play important roles in the development of AR.

scholarly journals Analysis of Potential Hub Genes and Related Transcription Factors in Rosacea Patients using Bioinformatics Analysis

2021 ◽  
Author(s):  
Xin Wang ◽  
Wenfang Dong ◽  
Huan Wang ◽  
Jianjun You ◽  
Ruobing Zheng ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Regulatory Network ◽  
Bioinformatics Analysis ◽  
Biological Functions ◽  
Ppi Network ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
String Databases ◽  
Cell Signaling Pathways

Abstract Objective The aim of this study is to discover the adipocyte genes and pathways involved in rosacea using bioinformatics analysis.Methods The GSE65914 gene expression profile was obtained. The GEO2R tool was used to screen out differentially expressed genes (DEGs). It was further analyzed with Gene Ontology (GO) to explore functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) to explore cell signaling pathways. Protein-protein interaction (PPI) networks among the DEGs were found by STRING databases and visualized in Cytoscape software. The related transcription factors regulatory network of the DEGs were also constructed.Results A total of 254 DEGs, including 72 up-regulated genes and 182 down-regulated genes, were obtained in rosacea samples. The biological functions of DEGs are mainly involved in the inflammatory response and chemokine activity. A PPI network consisting of 217 nodes and 710 edges was constructed using STRING, and ten hub genes were identified with Cytoscape software. Some transcriptional factors were also found to interact with these hub DEGs.Conclusion In this study, we obtained ten hub genes, including CXCL8, CCR5, CXCR4, CXCL10, MMP9, CD2, CCL19, CXCL9, CCL5, CD3D, which play an essential role in the pathology of rosacea, and these genes may provide a basis for the screening of treatment biomarkers for rosacea in the future.

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