Uncovering of Key Pathways and miRNAs for Intracranial Aneurysm Based on Weighted Gene Co-Expression Network Analysis

2022 ◽  
pp. 1-12
Zhengfei Ma ◽  
Ping Zhong ◽  
Peidong Yue ◽  
Zhongwu Sun

<b><i>Background:</i></b> Intracranial aneurysm (IA) is a serious cerebrovascular disease. The identification of key regulatory genes can provide research directions for early diagnosis and treatment of IA. <b><i>Methods:</i></b> Initially, the miRNA and mRNA data were downloaded from the Gene Expression Omnibus database. Subsequently, the limma package in R was used to screen for differentially expressed genes. In order to investigate the function of the differentially expressed genes, a functional enrichment analysis was performed. Moreover, weighted gene co-expression network analysis (WGCNA) was performed to identify the hub module and hub miRNAs. The correlations between miRNAs and mRNAs were assessed by constructing miRNA-mRNA regulatory networks. In addition, in vitro validation was performed. Finally, diagnostic analysis and electronic expression verification were performed on the GSE122897 dataset. <b><i>Results:</i></b> In the present study, 955 differentially expressed mRNAs (DEmRNAs, 480 with increased and 475 with decreased expression) and 46 differentially expressed miRNAs (DEmiRNAs, 36 with increased and 10 with decreased expression) were identified. WGCNA demonstrated that the yellow module was the hub module. Moreover, 16 hub miRNAs were identified. A total of 1,124 negatively regulated miRNA-mRNA relationship pairs were identified. Functional analysis demonstrated that DEmRNAs in the targeted network were enriched in vascular smooth muscle contraction and focal adhesion pathways. In addition, the area under the curve of 16 hub miRNAs was &#x3e;0.8. It is implied that 16 hub miRNAs may be used as potential diagnostic biomarkers of IA. <b><i>Conclusion:</i></b> Hub miRNAs and key signaling pathways were identified by bioinformatics analysis. This evidence lays the foundation for understanding the underlying molecular mechanisms of IA and provided potential therapeutic targets for the treatment of this disease.

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Siying He ◽  
Hui Sun ◽  
Yifang Huang ◽  
Shiqi Dong ◽  
Chen Qiao ◽  

Purpose. MiRNAs have been widely analyzed in the occurrence and development of many diseases, including pterygium. This study aimed to identify the key genes and miRNAs in pterygium and to explore the underlying molecular mechanisms. Methods. MiRNA expression was initially extracted and pooled by published literature. Microarray data about differentially expressed genes was downloaded from Gene Expression Omnibus (GEO) database and analyzed with the R programming language. Functional and pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network was constructed with the STRING database. The associations between chemicals, differentially expressed miRNAs, and differentially expressed genes were predicted using the online resource. All the networks were constructed using Cytoscape. Results. We found that 35 miRNAs and 301 genes were significantly differentially expressed. Functional enrichment analysis showed that upregulated genes were significantly enriched in extracellular matrix (ECM) organization, while downregulated genes were mainly involved in cell death and apoptotic process. Finally, we concluded the chemical-gene affected network, miRNA-mRNA interacted networks, and significant pathway network. Conclusion. We identified lists of differentially expressed miRNAs and genes and their possible interaction in pterygium. The networks indicated that ECM breakdown and EMT might be two major pathophysiological mechanisms and showed the potential significance of PI3K-Akt signalling pathway. MiR-29b-3p and collagen family (COL4A1 and COL3A1) might be new treatment target in pterygium.

2021 ◽  
Vol 11 (1) ◽  
Negin Sheybani ◽  
Mohammad Reza Bakhtiarizadeh ◽  
Abdolreza Salehi

AbstractIn dairy cattle, endometritis is a severe infectious disease that occurs following parturition. It is clear that genetic factors are involved in the etiology of endometritis, however, the molecular pathogenesis of endometritis is not entirely understood. In this study, a system biology approach was used to better understand the molecular mechanisms underlying the development of endometritis. Forty transcriptomic datasets comprising of 20 RNA-Seq (GSE66825) and 20 miRNA-Seq (GSE66826) were obtained from the GEO database. Next, the co-expressed modules were constructed based on RNA-Seq (Rb-modules) and miRNA-Seq (mb-modules) data, separately, using a weighted gene co-expression network analysis (WGCNA) approach. Preservation analysis was used to find the non-preserved Rb-modules in endometritis samples. Afterward, the non-preserved Rb-modules were assigned to the mb-modules to construct the integrated regulatory networks. Just highly connected genes (hubs) in the networks were considered and functional enrichment analysis was used to identify the biological pathways associated with the development of the disease. Furthermore, additional bioinformatic analysis including protein–protein interactions network and miRNA target prediction were applied to enhance the reliability of the results. Thirty-five Rb-modules and 10 mb-modules were identified and 19 and 10 modules were non-preserved, respectively, which were enriched in biological pathways related to endometritis like inflammation and ciliogenesis. Two non-preserved Rb-modules were significantly assigned to three mb-modules and three and two important sub-networks in the Rb-modules were identified, respectively, including important mRNAs, lncRNAs and miRNAs genes like IRAK1, CASP3, CCDC40, CCDC39, ZMYND10, FOXJ1, TLR4, IL10, STAT3, FN1, AKT1, CD68, ENSBTAG00000049936, ENSBTAG00000050527, ENSBTAG00000051242, ENSBTAG00000049287, bta-miR-449, bta-miR-484, bta-miR-149, bta-miR-30b and bta-miR-423. The potential roles of these genes have been previously demonstrated in endometritis or related pathways, which reinforced putative functions of the suggested integrated regulatory networks in the endometritis pathogenesis. These findings may help further elucidate the underlying mechanisms of bovine endometritis.

2020 ◽  
Zeyi Zhang ◽  
Ou Chen ◽  
Jingjing Wang

Abstract BackgroundSevere asthma is a heterogeneous inflammatory disease. The rise of precise immunotherapy for severe asthmatics underlines more understanding of molecular mechanisms and biomarkers. In this study, we aim to identify underlying mechanisms and hub genes that define asthma severity.MethodsDifferentially expressed genes were screened out based on bronchial epithelial brushings from mild and severe asthmatics. Then, the weighted gene co-expression network analysis was adopted to identify gene networks and the most significant module associated with asthma severity. Meanwhile, hub genes screening and functional enrichment analysis was performed. Receiver operating characteristic was conducted to validate the hub genes.ResultsWeighted gene co-expression network analysis identified 6 modules associated with asthma severity. Three modules were positively correlated (P < 0.001) with asthma severity, containing genes upregulated in severe asthmatics. Functional enrichment analysis found genes in the highlighted module mainly enriched in neutrophil degranulation and activation, leukocyte migration and chemotaxis. Hub genes identified in the module were CXCR1, CXCR2, CCR1, CCR7, TLR2, FPR1, FCGR3B, FCGR2A, ITGAM, and PLEK. Combining these hub genes possessed a moderate ability for discriminating between severe asthmatics and mild-moderate asthmatics with an area under the curve of 0.75.ConclusionOur results identified biomarkers and potential pathogenesis of severe asthma, which provides sight into treatment targets and prognostic markers.

2019 ◽  
Vol 14 (7) ◽  
pp. 591-601 ◽  
Aravind K. Konda ◽  
Parasappa R. Sabale ◽  
Khela R. Soren ◽  
Shanmugavadivel P. Subramaniam ◽  
Pallavi Singh ◽  

Background: Chickpea is a nutritional rich premier pulse crop but its production encounters setbacks due to various stresses and understanding of molecular mechanisms can be ascribed foremost importance. Objective: The investigation was carried out to identify the differentially expressed WRKY TFs in chickpea in response to herbicide stress and decipher their interacting partners. Methods: For this purpose, transcriptome wide identification of WRKY TFs in chickpea was done. Behavior of the differentially expressed TFs was compared between other stress conditions. Orthology based cofunctional gene networks were derived from Arabidopsis. Gene ontology and functional enrichment analysis was performed using Blast2GO and STRING software. Gene Coexpression Network (GCN) was constructed in chickpea using publicly available transcriptome data. Expression pattern of the identified gene network was studied in chickpea-Fusarium interactions. Results: A unique WRKY TF (Ca_08086) was found to be significantly (q value = 0.02) upregulated not only under herbicide stress but also in other stresses. Co-functional network of 14 genes, namely Ca_08086, Ca_19657, Ca_01317, Ca_20172, Ca_12226, Ca_15326, Ca_04218, Ca_07256, Ca_14620, Ca_12474, Ca_11595, Ca_15291, Ca_11762 and Ca_03543 were identified. GCN revealed 95 hub genes based on the significant probability scores. Functional annotation indicated role in callose deposition and response to chitin. Interestingly, contrasting expression pattern of the 14 network genes was observed in wilt resistant and susceptible chickpea genotypes, infected with Fusarium. Conclusion: This is the first report of identification of a multi-stress responsive WRKY TF and its associated GCN in chickpea.

2021 ◽  
Vol 12 ◽  
Maryam Heidari ◽  
Abbas Pakdel ◽  
Mohammad Reza Bakhtiarizadeh ◽  
Fariba Dehghanian

Johne’s disease is a chronic infection of ruminants that burdens dairy herds with a significant economic loss. The pathogenesis of the disease has not been revealed clearly due to its complex nature. In order to achieve deeper biological insights into molecular mechanisms involved in MAP infection resulting in Johne’s disease, a system biology approach was used. As far as is known, this is the first study that considers lncRNAs, TFs, and mRNAs, simultaneously, to construct an integrated gene regulatory network involved in MAP infection. Weighted gene coexpression network analysis (WGCNA) and functional enrichment analysis were conducted to explore coexpression modules from which nonpreserved modules had altered connectivity patterns. After identification of hub and hub-hub genes as well as TFs and lncRNAs in the nonpreserved modules, integrated networks of lncRNA-mRNA-TF were constructed, and cis and trans targets of lncRNAs were identified. Both cis and trans targets of lncRNAs were found in eight nonpreserved modules. Twenty-one of 47 nonpreserved modules showed significant biological processes related to the immune system and MAP infection. Some of the MAP infection’s related pathways in the most important nonpreserved modules comprise “positive regulation of cytokine-mediated signaling pathway,” “negative regulation of leukocyte migration,” “T-cell differentiation,” “neutrophil activation,” and “defense response.” Furthermore, several genes were identified in these modules, including SLC11A1, MAPK8IP1, HMGCR, IFNGR1, CMPK2, CORO1A, IRF1, LDLR, BOLA-DMB, and BOLA-DMA, which are potentially associated with MAP pathogenesis. This study not only enhanced our knowledge of molecular mechanisms behind MAP infection but also highlighted several promising hub and hub-hub genes involved in macrophage-pathogen interaction.

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8831 ◽  
Xiaojiao Guan ◽  
Yao Yao ◽  
Guangyao Bao ◽  
Yue Wang ◽  
Aimeng Zhang ◽  

Esophageal cancer is a common malignant tumor in the world, and the aim of this study was to screen key genes related to the development of esophageal cancer using a variety of bioinformatics analysis tools and analyze their biological functions. The data of esophageal squamous cell carcinoma from the Gene Expression Omnibus (GEO) were selected as the research object, processed and analyzed to screen differentially expressed microRNAs (miRNAs) and differential methylation genes. The competing endogenous RNAs (ceRNAs) interaction network of differentially expressed genes was constructed by bioinformatics tools DAVID, String, and Cytoscape. Biofunctional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of the screened genes and the survival of the patients were verified. By analyzing GSE59973 and GSE114110, we found three down-regulated and nine up-regulated miRNAs. The gene expression matrix of GSE120356 was calculated by Pearson correlation coefficient, and the 11696 pairs of ceRNA relation were determined. In the ceRNA network, 643 lncRNAs and 147 mRNAs showed methylation difference. Functional enrichment analysis showed that these differentially expressed genes were mainly concentrated in the FoxO signaling pathway and were involved in the corresponding cascade of calcineurin. By analyzing the clinical data in The Cancer Genome Atlas (TCGA) database, it was found that four lncRNAs had an important impact on the survival and prognosis of esophageal carcinoma patients. QRT-PCR was also conducted to identify the expression of the key lncRNAs (RNF217-AS1, HCP5, ZFPM2-AS1 and HCG22) in ESCC samples. The selected key genes can provide theoretical guidance for further research on the molecular mechanism of esophageal carcinoma and the screening of molecular markers.

2021 ◽  
Nana Yang ◽  
Qianghua Wang ◽  
Biao Ding ◽  
Yinging Gong ◽  
Yue Wu ◽  

Abstract Background: The accumulation of ROS resulting from upregulated levels of oxidative stress is commonly implicated in preeclampsia (PE). Ferroptosis is a novel form of iron-dependent cell death instigated by lipid peroxidation likely plays important role in PE pathogenesis. This study aims to investigate expression profiles and functions of the ferroptosis-related genes (FRGs) in early- and late-onset preeclampsia.Methods: The gene expression data and clinical information were downloaded from GEO database. The “limma” R package was used for screening differentially expressed genes. GO(Gene Ontology), Kyoto Encyclopedia of Genes and Genomes(KEGG) and protein protein interaction (PPI) network analyses were conducted to investigate the bioinformatics functions and molecular interactions of significantly different FRGs. Quantitative real-time reverse transcriptase PCR was used to verify the expression of hub FRGs in PE.Results: A total number of 4,215 DEGs were identified between EOPE and preterm cases and 3,356 DEGs were found between EOPE and LOPE subtypes. 20 significantly different FRGs were identified in EOPE, while only 3 in LOPE. Functional enrichment analysis revealed that the differentially expressed FRGs was mainly involved in EOPE and enriched in hypoxia- and iron-related pathways, such as response to hypoxia, iron homeostasis and iron ion binding process. The PPI network analysis and verification by RT-qPCR resulted in the identification of the following six interesting FRGs: FTH1, HIF1A, FTL, IREB2, MAPK8 and PLIN2. Conclusions: EOPE and LOPE owned distinct underlying molecular mechanisms and ferroptosis may be mainly implicated in pathogenesis of EOPE. Further studies are necessary for deeper inquiry into placental ferroptosis and its role in the pathogenesis of EOPE.

2020 ◽  
Na Li ◽  
Ru-feng Bai ◽  
Chun Li ◽  
Li-hong Dang ◽  
Qiu-xiang Du ◽  

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

2020 ◽  
Xi Pan ◽  
Jian-Hao Liu

Abstract Background Nasopharyngeal carcinoma (NPC) is a heterogeneous carcinoma that the underlying molecular mechanisms involved in the tumor initiation, progression, and migration are largely unclear. The purpose of the present study was to identify key biomarkers and small-molecule drugs for NPC screening, diagnosis, and therapy via gene expression profile analysis. Methods Raw microarray data of NPC were retrieved from the Gene Expression Omnibus (GEO) database and analyzed to screen out the potential differentially expressed genes (DEGs). The key modules associated with histology grade and tumor stage was identified by using weighted correlation network analysis (WGCNA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of genes in the key module were performed to identify potential mechanisms. Candidate hub genes were obtained, which based on the criteria of module membership (MM) and high connectivity. Then we used receiver operating characteristic (ROC) curve to evaluate the diagnostic value of hub genes. The Connectivity map database was further used to screen out small-molecule drugs of hub genes. Results A total of 430 DEGs were identified based on two GEO datasets. The green gene module was considered as key module for the tumor stage of NPC via WGCNA analysis. The results of functional enrichment analysis revealed that genes in the green module were enriched in regulation of cell cycle, p53 signaling pathway, cell part morphogenesis. Furthermore, four DEGs-related hub genes in the green module were considered as the final hub genes. Then ROC revealed that the final four hub genes presented with high areas under the curve, suggesting these hub genes may be diagnostic biomarkers for NPC. Meanwhile, we screened out several small-molecule drugs that have provided potentially therapeutic goals for NPC. Conclusions Our research identified four potential prognostic biomarkers and several candidate small-molecule drugs for NPC, which may contribute to the new insights for NPC therapy.

2020 ◽  
Vol 9 (2) ◽  
pp. LMT30
Chuanli Ren ◽  
Weixiu Sun ◽  
Xu Lian ◽  
Chongxu Han

Aim: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD). Materials & methods: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID. Results: Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD. Conclusion: 23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

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