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.
ObjectiveTo investigate the expression of Yes-associated protein (YAP) screened by bioinformatics in rats with myocardial-ischemia reperfusion injury and establish the base for further research. MethodsThe difference of gene spectrum of rats with myocardial-ischemia reperfusion injury was analyzed by bioinformatics technique. The related signaling pathways and key genes were screened by KOBAS2.0 and KEGG. Eighteen Sprague Dawley rats were randomly divided into three groups: normal group (n=6), sham operation group (n=6) and myocardial-ischemia reperfusion injury group (n=6). The expression of target gene was detected by immunochemistry, quantitive reverse transcription polymerase chain reaction and western blotting. ResultsA total of 345 differentially expressed genes were found by bioinformatics, among which 181 were up-regulated and 164 were down-regulated. The differential genes were mainly enriched in Wnt, HIPPO, MAPK, Jak-STAT and other signaling pathways. We focused on HIPPO pathway and found that the expression of YAP increased significantly in myocardial-ischemia reperfusion injury group, compared with the normal group and sham operation group (P＜0.05). ConclusionsThe expression of YAP of HIPPO signal pathway is increased in rats with myocardial-ischemia reperfusion injury.
现已认识到免疫反应、转录因子核因子κB( NF-κB) 的激活、细胞因子、中性粒细胞的激活和肺泡渗入、凝血级联反应、肾素-血管紧张素系统等多种因素构成的复杂网络参与急性肺损伤/急性呼吸窘迫综合征( ALI/ARDS) 的发病过程[ 1-5] 。虽然脓毒症、创伤、肺炎等ALI/ARDS诱发因素很常见, 但仅有部分病人发生ALI/ARDS, 并且具有相似临床特征的ALI/ARDS病人可有截然不同的结果, 这种异质性引起研究者对影响ALI/ARDS 易感性和预后的遗传因子进行鉴别的浓厚兴趣[ 6] 。由于数量庞大的表现型变异, 不完全的基因外显率、复杂的基因-环境相互作用及高度可能的基因座不均一性而使ALI 遗传学的研究受到挑战[ 7] 。近年来基因组学技术被应用于ALI/ARDS 发病机制的研究, 加深了人们对ALI/ARDS的认识并有可能发展出新的治疗策略以降低其发病率和病死率。
Chronic cerebral hypoperfusion (CCH) plays an important role in the occurrence and development of vascular dementia (VD). Recent studies have indicated that multiple stages of immune-inflammatory response are involved in the process of cerebral ischemia, drawing increasing attention to immune therapies for cerebral ischemia. This study aims to identify potential immune therapeutic targets for CCH using bioinformatics methods from an immunological perspective. We identified a total of 823 differentially expressed genes associated with CCH, and further screened for 9 core immune-related genes, namely RASGRP1, FGF12, SEMA7A, PAK6, EDN3, BPHL, FCGRT, HSPA1B and MLNR. Gene enrichment analysis showed that core genes were mainly involved in biological functions such as cell growth, neural projection extension, and mesenchymal stem cell migration. Biological signaling pathway analysis indicated that core genes were mainly involved in the regulation of T cell receptor, Ras and MAPK signaling pathways. Through LASSO regression, we identified RASGRP1 and BPHL as key immune-related core genes. Additionally, by integrating differential miRNAs and the miRwalk database, we identified miR-216b-5p as a key immune-related miRNA that regulates RASGRP1. In summary, the predicted miR-216b-5p/RASGRP1 signaling pathway plays a significant role in immune regulation during CCH, which may provide new targets for immune therapy in CCH.
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.
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.
Objective To explore the pathogenesis of acute respiratory disease syndrome (ARDS) by bioinformatics analysis of neutrophil gene expression profile in order to find new therapeutic targets. Methods The gene expression chips include ARDS patients and healthy volunteers were screened from the Gene Expression Omnibus (GEO) database. The differentially expressed genes were carried out through GEO2R, OmicsBean, STRING, and Cytoscape, then enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathways was conducted to investigate the biological processes involved in ARDS via DAVID website. Results Bioinformatics analysis showed 86 differential genes achieved through the GEO2R website. Eighty-one genes were included in the STRING website for protein interaction analysis. The results of the interaction were further analyzed by Cytoscape software to obtain 11 hub genes: AHSP, ALAS2, CD177, CLEC4D, EPB42, GPR84, HBD, HVCN1, KLF1, SLC4A1, and STOM. GO analysis showed that the differential gene was enriched in the cellular component, especially the integrity of the plasma membrane. KEGG analysis showed that multiple pathways especially the cytokine receptor pathway involved in the pathogenesis of ARDS. Conclusions A variety of genes and pathways have been involved in the pathogenesis of ARDS. Eleven hub genes are screened, which may be involved in the pathogenesis of ARDS and can be used in subsequent studies.
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.
Lung cancer is one of the malignant tumors with the greatest threat to human health, and studies have shown that some genes play an important regulatory role in the occurrence and development of lung cancer. In this paper, a LightGBM ensemble learning method is proposed to construct a prognostic model based on immune relate gene (IRG) profile data and clinical data to predict the prognostic survival rate of lung adenocarcinoma patients. First, this method used the Limma package for differential gene expression, used CoxPH regression analysis to screen the IRG to prognosis, and then used XGBoost algorithm to score the importance of the IRG features. Finally, the LASSO regression analysis was used to select IRG that could be used to construct a prognostic model, and a total of 17 IRG features were obtained that could be used to construct model. LightGBM was trained according to the IRG screened. The K-means algorithm was used to divide the patients into three groups, and the area under curve (AUC) of receiver operating characteristic (ROC) of the model output showed that the accuracy of the model in predicting the survival rates of the three groups of patients was 96%, 98% and 96%, respectively. The experimental results show that the model proposed in this paper can divide patients with lung adenocarcinoma into three groups [5-year survival rate higher than 65% (group 1), lower than 65% but higher than 30% (group 2) and lower than 30% (group 3)] and can accurately predict the 5-year survival rate of lung adenocarcinoma patients.
The rapid development of high-throughput chromatin conformation capture (Hi-C) technology provides rich genomic interaction data between chromosomal loci for chromatin structure analysis. However, existing methods for identifying topologically associated domains (TADs) based on Hi-C data suffer from low accuracy and sensitivity to parameters. In this context, a TAD identification method based on spatial density clustering was designed and implemented in this paper. The method preprocessed the raw Hi-C data to obtain normalized Hi-C contact matrix data. Then, it computed the distance matrix between loci, generated a reachability graph based on the core distance and reachability distance of loci, and extracted clustering clusters. Finally, it extracted TAD boundaries based on clustering results. This method could identify TAD structures with higher coherence, and TAD boundaries were enriched with more ChIP-seq factors. Experimental results demonstrate that our method has advantages such as higher accuracy and practical significance in TAD identification.