Objective To screen the differentially expressed genes and pathways involved in rosacea using bioinformatics analysis. Methods The GSE65914 gene chipset was collected from the Gene Expression Omnibus (up to July 12th, 2021). It was searched according to the keyword “rosacea”. The data was analyzed by GEO2R platform. The common differential genes of three subtypes of rosacea were screened out. The online DAVID analysis tool was used to perform the gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Protein-protein interaction networks of differentially expressed genes were made by String and Cytoscape. The key modules and genes were screened by Mcode and Cytohubba. Results A total of 957 common differential genes were identified, including 533 up-regulated genes and 424 down-regulated genes. GO enrichment analysis showed that these genes were mainly involved in immune response, inflammatory response, intercellular signal transduction, positive regulation of T cell proliferation, chemokine signaling pathways, cell surface receptor signaling pathways, cellular response to interferon-γ, and other biological processes. KEGG pathway enrichment analysis mainly included cytokine-cytokine receptor interaction, rheumatoid arthritis, chemokine signaling pathway, PPAR signaling pathway, Toll-like receptor signaling pathway, nuclear transcription factor-κB signaling pathway, tumor necrosis factor signaling pathway and other signaling pathways. Cytohubba analysis revealed 10 key genes, including PTPRC, MMP9, CCR5, IL1B, TLR2, STAT1, CXCR4, CXCL10, CCL5 and VCAM1. Conclusion The key genes and related pathways may play an important role in the pathogenesis of rosacea.
ObjectiveTo conduct a bioinformatics analysis of gene expression profiles in frontal lobe of patients with Parkinson disease (PD), in order to explore the potential mechanism related to depression in PD.MethodsAll the bioinformatics data before March 20th 2019 were acquired from Gene Expression Omnibus (GEO) database, using " Parkinson disease” as the key word. The species was limited to human (Homo sapiens), and the detective method was limited to expression profiling by array. ImgGEO (Integrative Gene Expression Meta-Analysis from GEO database), DAVID (the Database for Annotation, Visualization and Integrated Discovery), STRING and Cytoscape 3.6.1 software were utilized for data analysis.ResultsTotally, 45 samples (24 PD cases and 21 healthy controls) were obtained from 2 datasets. We identified 236 differentially expressed genes (DEGs) in the post-mortem frontal lobe between PD cases and healthy controls, in which 146 genes were up-regulated and 90 genes were down-regulated. Based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis, the DEGs were mainly enriched in the structures of postsynaptic membrane, cell membrane component, postsynaptic membrane dense area, and myelin sheath, and were involved in the occurrence of PD, depression, and other diseases. These genes were involved in the biological processes of dopaminergic, glutamate-nergic, GABA-nergic synapses, and some other synapses, as well as several signaling pathways (e.g. mitogen- activated protein kinase signal pathway, p53 signal pathway, and Wnt signal pathway), which were associated with PD and depression pathogenesis. Besides, we found that NFKBIA, NRXN1, and RPL35A were the Hub proteins.ConclusionsGene expression in frontal lobe of patients with PD is associated with the pathogenesis of PD. This study provides a theoretical basis for understanding the mechanism of PD occurrence and progression, as well as the potential mechanism of depression in PD.
Objective To investigate specific changes of T cell repertoire in convalescent patients infected by influenza A (H7N9) virus. Methods Peripheral blood samples from 8 convalescent patients infected by H7N9 virus and 10 healthy donors were collected. After extracting whole DNA from these samples, arm-PCR were performed and the products were submitted to Illumina HiSeq2000 platform to produce deep sequencing data of the nucleotide sequences of complementary determining region 3 of T cell receptor β chain (TRB). Differences were compared in TRB diversity and V-D-J gene usage and similarities of sequences between the patients and the healthy donors. Results Frequency of V-D-J gene usage was different between the H7N9 patient group and the healthy group, such as TRBV30, TRBV27, and TRBV18 (Student's t test, P < 05). Main component analysis showed V-J pairing pattern was significantly different between two groups, which may have potential in identifying patients from healthy people. A considerable number of shared CDR3s were found in patient-patient pairs and normal-normal pairs, while seldom were found in patient-normal pairs. The similarity between patients was also confirmed by overlap distance analysis. Indexes for assessing diversity of immune repertoires, Shannon-Weiner index and Simpson index, were both lower in the patients (Student's t test, P < 05), suggesting that the immune system of the patients had not recovered 6 months after H7N9 infection. Compared with the healthy donors, the number of hyper-expression clones increased in the patient group, and some of them showed similarity among patients. Conclusions TRB repertoires are less diverse in patients with increased hyper-expressed clones and identifiable V-J usage pattern, which is identifiable from normal population. These results suggest that there are H7N9-specific changes in TRB repertoires of H7N9 infected patients in convalescent phase, which have potential implication in diagnosis and therapeutic T cell development.
Objective To validate the different expressions of human fxyd6 gene between normal bile duct tissues and malignant tumor tissues, and to observe the subcellular localization of human fxyd6 gene in human cholangiocarcinoma cells. MethodsThe different expressions between normal bile duct tissues and malignant tumor tissues were identified by RT-PCR. In situ polymerase chain reaction （IS-RT-PCR） was applied to detect the subcellular localization of fxyd6 gene in paraffin sections of human cholangiocarcinoma cells. Image analysis software was used to semiquantitatively determine the difference between normal and malignant tissues. ResultsHuman fxyd6 gene was highly expressed in cholangiocarcinoma tissues and lowly expressed in normal ones. There was a significant difference between the expressions of carcinoma cells and normal cells （P＜0.05）. IS-RT-PCR showed that fxyd6 gene localized in the kytoplasma of epithelial cells of human cholangiocarcinoma. ConclusionHuman fxyd6 gene may act as an essential component of the malignant transformation process in human cholangiocarcinoma.
Objective To study the expression of 4 circular RNA (circRNA) in peripheral blood mononuclear cells (PBMC) of patients with epilepsy and to predict its function by bioinformatics, so as to provide basis for exploring the pathogenesis of epilepsy. Methods From May 2020 to May 2021, 22 epilepsy patients were treated in the Department of Neurology of the First Affiliated Hospital of Baotou Medical College of Inner Mongolia University of Science and Technology, and 22 control group were selected. There were 13 males and 8 females in the epilepsy group, with an average age of (36.41±8.39)years. There were 11 males and 11 females in the control group, with an average age of (34.41±8.68) years. The expression levels of circRNA EFCAB2, C14orf159, PARG and TMEM39 in PBMC were detected by real-time fluorescence quantitative PCR, and their functions were predicted by bioinformatics. Results Compared with the control group, the relative expression of EFCAB2 and C14orf159 in PBMC of epileptic patients was 1.42±0.06 (t=29.41) and 1.31±0.03 (t=25.27), PARG and TMEM39 were not detected in peripheral blood PBMC. Bioinformatics analysis showed that three mirnas obtained by EFCAB2 were miR-6873-3p, miR-6739-3p and miR-7110-3p. Three mirnas were obtained by C14orf159: miR-1180-3p, miR-6501-3p, and miR-3622b-5p. The seizure-related genes were predicted by TargetScan database. EFCAB2: miR-6873-3p met the requirements of 11 downstream genes. A total of 7 downstream genes of miR-6739-3p met the requirements.A total of 14 downstream genes were eligible for miR-7110-3p and a total of 9 downstream genes were eligible for miR-6501-3p. A total of 14 downstream genes were eligible for miR-3622B-5p.miR-1180-3p has a total of 1 downstream genes that meet the requirements. Conclusions Studies have shown that two circrnas, EFCAB2 and C14orf159, may be important biological markers of epilepsy. Through bioinformatics analysis, these two circrnas may act as "molecular sponges" to regulate epilepsy. EFCAB2 has the potential to act as a "molecular sponge" for miR-6873-3p and miR-7110-3p, and it was found that miR-6873-3p and miR-7110-3 share a common downstream target gene MAP1B-which plays a role in epilepsy by regulating voltage-gated sodium channels. C14orf159 can act as a molecular sponge for miR-6501-3p to regulate the expression of CCL3 and play a role in epilepsy.
ObjectiveTo establish and validate the diagnostic model of ferroptosis genes for acute myocardial infarction (AMI) based on bioinformatics. MethodsFive AMI gene expression data were obtained from Gene Expression Omnibus (GEO), namely GSE66360, GSE48060, GSE60993, GSE83500, GSE34198. Among them, GSE66360 was used as the training set to perform differential analysis, and intersection of differential genes and ferroptosis genes was taken to obtain differentially expressed ferroptosis genes in AMI. GO and KEGG enrichment analysis was performed using Metascape website. Subsequently, random forest (RF) algorithm was used to screen out key genes with high classification performance according to the Keeny coefficient score, and artificial neural network (ANN) diagnostic model of AMI ferroptosis feature gene was constructed by model group GSE83500. The area under the receiver operating characteristic curve (AUC) of 10-fold cross-validation was used to evaluate the performance and generalization ability of the model, and 3 external independent datasets were used to verify the diagnostic performance of this model. The single sample gene setenrichment analysis was used to explore the difference in immune cell infiltration between infarcted myocardium and normal myocardium after AMI. In addition, correlation analysis between immune cells and key genes was also conducted. Finally, potential drugs that would prevent and treat AMI by regulating ferroptosis were screened out from the Coremin Medical platform. ResultsA total of 16 differentially expressed ferroptosis genes were obtained in the training set, GO enrichment analysis showed that they mainly participated in biological functions such as cellular response to biological stimuli and chemical stress, regulation of interleukin 17, etc. KEGG enrichment analysis showed that these genes were significantly enriched in NOD-like receptor signaling pathway, programmed cell necrosis, Leishmaniasis and other pathways. Four genes with good classification performance were screened out using RF algorithm, namely EPAS1, SLC7A5, FTH1, and ZFP36. The results of 10-fold cross-validation showed that the minimum AUC value was 0.746, the maximum value was 0.906, and the average value was 0.805. The AUC of the ANN model was 0.859, and the AUC values of the three independent validation sets were 0.763 (GSE48060), 0.673 (GSE60993), 0.698 (GSE34198). Immune cell infiltration found that macrophages, mast cells and monocytes were significantly active after AMI. Correlation analysis found that there were positive correlations between 4 key genes and activated dendritic cells, eosinophils and γδT cells. A total of 20 potential western medicines were predicted which could prevent and treat AMI by regulating ferroptosis, and the predicted potential Chinese medicine was mainly heat-clearing and detoxifying and blood-activating and removing blood stasis drugs. ConclusionThe identified AMI ferroptosis genes by bioinformatics method have certain diagnostic significance, which provides a reference for disease diagnosis and treatment.
ObjectiveTo explore the pathogenesis of tuberculosis and provide new ideas for its early diagnosis and treatment.MethodsGSE54992 gene expression profile was obtained from the gene expression database. Differentially expressed genes (DEGs) were screened using National Center forBiotechnology Information platform, and GO enrichment analysis, pathway analysis, pathway network analysis, gene network analysis, and co-expression analysis were performed to analyze the DEGs.ResultsCompared with the control group, a total of 3 492 genes were differentially expressed in tuberculosis. Among them, 1 686 genes were up-regulated and 1 806 genes were down-regulated. DEGs mainly involved small molecule metabolic processes, signal transduction, immune response, inflammatory response, and innate immune response. Pathway analysis revealed chemokine signaling pathway, tuberculosis, NF-Kappa B signaling pathway, cytokine-cytokine receptor interaction, and so on; gene signal network analysis found that the core genes were AKT3, PLCB1, MAPK8, and NFKB1; co-expression network analysis speculated that the core genes were PYCARD, TNFSF13, PHPT1, COMT, and GSTK1.ConclusionsAKT3, PYCARD, IRG1, CD36 and other genes and their related biological processes may be important participants in the occurrence and development of tuberculosis. Bioinformatics can help us to comprehensively study the mechanism of disease occurrence, which can provide potential targets for the diagnosis and treatment of tuberculosis.
ObjectiveTo bioinformatically analyze the gene chip data of chondrocytes from osteoarthritis patients from the Gene Expression Omnibus (GEO) database, and explore the molecular mechanisms of osteoarthritis.MethodsWe searched the GEO database (up to April 23rd, 2021) for data of chondrocytes and gene expression profiling in human knee osteoarthritis via the key words of “osteoarthritis OR cartilage OR chondrocyte*”. Then, we selected the samples by our inclusion criteria. The data were normalized before analysis. After differentially expressed genes were identified, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Search Tool for the Retrival of Interacting Genes/Proteinsm, R language, Perl language, Cytoscape software, and DAVID database were used to perform differentially expressed gene analysis, functional annotation, and enrichment analysis.ResultsThe differentially expressed genes were mostly enriched in cell components and some extracellular regions, which participated in cell division, mitosis, cell proliferation and inflammatory response mainly via the regulation of protein kinase activity. The differentially expressed genes were mainly involved in the cell proliferation signaling pathway, mitogen-activated protein kinase signaling pathway, oocyte meiosis, cell cycle and so on.ConclusionsMultiple signaling pathways are involved in the changes of chondrocytes in human knee osteoarthritis, mainly about cell cycle and protein metabolism genes/pathways. Inflammatory factors and cytokines may be the most important links in the pathogenesis of osteoarthritis.
Objective To explore the expression of yes-associated protein 1 (YAP1), as a key protein of Hippo signal pathway, in rats with brain injury. Methods A total of 18 Sprague Dawley rats were randomly divided into three groups: normal group, sham operation group and brain injury group. The expression of YAP1 in rats with brain injury was detected by immunochemistry, quantitative polymerase chainreaction and Western blotting. Result Seventy-two hours after the brain injury, the expression level of YAP1 in protein and gene increased significantly in brain injury group, compared with those in the normal and sham operation group (P<0.05). Conclusion The expression of YAP1 increases in rats with brain injury, which maybe a new target for therapy.
Circular RNA are one kind of non-coding RNA, charactered by covalently closed rings. They can influence biological functions such as cell transduction and protein synthesis. They are associated with pathogenesis of many diseases and become a novel family of biomarkers. Now we try to introduce the origin, structure, function of circular RNA and the involved research methodology. Furthermore, we primarily discuss their application in the tuberculosis research.