scholarly journals Novel Signature Genes for Human Left Ventricle Cardiomyopathies Identified by Weighted Co-expression Network Analysis (WGCNA)

2020 ◽  
Author(s):  
Jiao Tian ◽  
Zhengyuan Wu ◽  
Yaqi Zhang ◽  
Yingying He ◽  
SHUBAI LIU
Keyword(s):  
Post Partum ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Clinical Diagnostics ◽  
Hub Genes ◽  
Signature Genes ◽  
Ppi Networks ◽  
The Common ◽  
Human Left Ventricle ◽  
Key Pathways

Abstract BackgroundCardiomyopathy, a heart disease that arises from different etiologies, brings a huge healthcare burden to the global society. Identification of biomarkers can be very useful for early diagnosis of cardiomyopathy, interruption of the disease procession to heart failure, and decrement of the mortality. MethodsClinical cases of cardiomyopathy were screened out of independently investigations from the genomic database. Exploration of its whole transcription disorder pattern by WGCNA (Weighted Gene Co-expression Network Analysis) to discover the signature genes for different subtypes of cardiomyopathy. The hub genes and key pathways, which are correlated to cardiomyopathy traits, were identified through co-expression and protein-protein interaction (PPI) networks enrichment analysis. Discovered hub genes were blast through the Cardiovascular Disease Portal to verify functions related to human cardiomyopathies.ResultsThree common axes of signature genes were discovered for five subtypes of cardiomyopathy: 1) Four genes (MDM4, CFLAR, RPS6KB1, PKD1L2) were common for ischemic and ischemic cardiomyopathy subgroups; 2) Subtypes of cardiomyopathy (ischemic, post. partum, familiar and idiopathic) shared eight genes (MAPK1, MAPK11, MAPK14, LMNA, RAC1, PECAM1, XIAP, CREB1); 3) TFAM and RHEB were the common signature genes for subtypes of cardiomyopathy (viral, post. partum, familiar, and idiopathic). Major pathways enriched were including MAPK signaling pathway, the pathway of protein processing in endoplasmic reticulum, and pathway of regulatory actin cytoskeleton. Aberrant in these pathways caused disorders metabolic process and cellular malfunctions that generally contributes to cardiac dysregulation and functional relapse into cardiomyopathies.ConclusionThis study identified the key signaling pathways, functions and biological process related to cardiomyopathies and will give a light to better understand the molecular mechanism of processes of cardiomyopathies and figure out the rational clinical interference way to cure the patients. Therein, these novel signature genes may work as potential promising biomarkers for cardiomyopathy diagnosis, and will benefit for the better clinical diagnostics and outcome for patients with cardiomyopathies. 


scholarly journals Co-expression network analysis identified novel potential Signature Genes Associated with human left ventricle cardiomyopathies arises from different etiologies

2020 ◽  
Author(s):  
Jiao Tian ◽  
Zhengyuan Wu ◽  
Yingying He ◽  
SHUBAI LIU
Keyword(s):  
Network Analysis ◽  
Ischemic Cardiomyopathy ◽  
Heart Diseases ◽  
Post Partum ◽  
Mapk Signaling ◽  
Clinical Diagnostics ◽  
Signature Genes ◽  
Ppi Networks ◽  
Idiopathic Cardiomyopathy ◽  
Disease Signature

Abstract Background: Heat disease is worldwide pandemic and brings huge healthcare burden to global society. However, it is still illusive that the whole transcription disorder pattern of cardiomyopathies arises from different etiologies. We applied Weighted Gene Co-Expression Network Analysis (WGCNA) to construct and screen functional gene significantly related to 8 subtypes of cardiomyopathies. Through co-expression and protein-protein interaction (PPI) networks enrichment analysis, the hub genes and key pathways were identified, which highly correlated with pathologic traits. Compared with expression profile of healthy group, potential disease signature genes were validated through another independently investigations of cardiomyopathies via cardiovascular disease bioportal. Results: The novel potential disease signature genes were identified and assembled into three axes that shared among five cardiomyopathies groups, including idiopathic cardiomyopathy, familial cardiomyopathy, post-partum cardiomyopathy, Ischemic cardiomyopathy and viral cardiomyopathy. Four disease signature genes (MDM4, CFLAR, RPS6KB1, PKD1L2) were shared by ischemic and ischemic cardiomyopathy group. Eight signature genes (MAPK1, MAPK11, MAPK14, LMNA, RAC1, PECAM1, XIAP, CREB1) were overlapped by Ischemic Cardiomyopathy with Post. Partum/Familiar/Idiopathic Cardiomyopathy groups. The signature genes (TFAM, RHEB) were common genes among Viral Cardiomyopathy and Post. Partum / Familiar /Idiopathic Cardiomyopathy groups. These some novel signature genes were highlighted as potential biomarkers for cardiomyopathies. The majority disorder functions and pathways enriched in metabolic processes and concentrated on MAPK signaling pathway, protein processing in endoplasmic reticulum, regulation of actin cytoskeleton pathway. Conclusion: It strongly suggests that expression disorder of these signature genes may contribute the cardiac dysregulation and relapse into cardiomyopathies. Taken together, these novel signature genes could be utilized as diagnostic biomarkers or therapy targets and benefit the precise clinical diagnostics with better outcome. In summary, this study will attract great interest of clinical research scientists as well as medical scientists that work on heart diseases.

scholarly journals Co-expression network analysis identified novel potential Signature Genes Associated with human left ventricle cardiomyopathies arises from different etiologies

2020 ◽  
Author(s):  
Jiao Tian ◽  
Zhengyuan Wu ◽  
Yingying He ◽  
SHUBAI LIU
Keyword(s):  
Network Analysis ◽  
Ischemic Cardiomyopathy ◽  
Post Partum ◽  
Mapk Signaling ◽  
Clinical Diagnostics ◽  
Pathological Feature ◽  
Signature Genes ◽  
Ppi Networks ◽  
Idiopathic Cardiomyopathy ◽  
Disease Signature

Abstract Background: Heart disease is global pandemic and causes huge healthcare burden to society. However, it is still illusive that the whole transcription disorder pattern of cardiomyopathies arises from different etiologies. The Weighted Gene Co-Expression Network Analysis (WGCNA) was applied to construct and screen functional gene that be significantly related to different cardiomyopathies pathological feature. Through co-expression and protein-protein interaction (PPI) networks enrichment analysis, the hub genes and key pathways were screened, which were correlated to cardiomyopathy traits. To discover the novel disease signature genes, cardiovascular disease bioportal database and were employed to blast and validate, which contained independently investigations of clinical cardiomyopathies cases. Results: The potential disease signature genes were identified and assorted into three common axes shared among five subtype of cardiomyopathies. Four genes (MDM4, CFLAR, RPS6KB1, PKD1L2) were shared by ischemic and ischemic cardiomyopathy group. The secondary axe contained eight signature genes (MAPK1, MAPK11, MAPK14, LMNA, RAC1, PECAM1, XIAP, CREB1) and was overlapped by Ischemic Cardiomyopathy, Post. Partum Cardiomyopathy, Familiar Cardiomyopathy and Idiopathic Cardiomyopathy. The third axe consisted of two common signature genes (TFAM, RHEB) that shared among the subgroups of Viral Cardiomyopathy, Post. Partum Cardiomyopathy, Familiar Cardiomyopathy and Idiopathic Cardiomyopathy. The majority of disorder functions and pathways were enriched in metabolic processes and pathways of MAPK signaling, protein processing in endoplasmic reticulum, regulation of actin cytoskeleton. Conclusion: These results strongly suggest that expression disorder of signature genes contribute to the cardiac dysregulation and functional relapse into cardiomyopathies. Taken together, these novel signature genes could be utilized as potential diagnostic biomarkers or therapy targets. It will be benefit the cardiomyopathy precise clinical diagnostics with better outcome. In summary, this study will attract great interest of clinical research scientists as well as medical scientists that work on heart diseases.

scholarly journals Screening the Hub Genes and Analyzing the Mechanisms in Discharged COVID-19 Patients Retesting Positive through Bioinformatics Analysis

2021 ◽  
Author(s):  
Ke-Ying Fang ◽  
Gui-Ning Liang ◽  
Zhuo-Qing Zhuang ◽  
Yong-Xin Fang ◽  
Yu-Qian Dong ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Social Order ◽  
Expression System ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Virus Reactivation ◽  
Hub Genes ◽  
Messenger Ribonucleic Acid ◽  
Ppi Networks ◽  
Significant Enrichment

Abstract Background: With the worldwide spread of COVID-19, people’s health and social order have been exposed to enormous risks. After encountering patients who test positive again after discharge, our study analyzed the pathogenesis to further assess the risk and possibility of virus reactivation.Methods: A separate microarray was acquired from the Integrated Gene Expression System (GEO), and its samples were divided into two groups: a “convalescent-RTP” group consisting of recovery and “retesting-positive” (RTP) patients (group CR) and a “health-RTP” group consisting of healthy control and RTP patients (group HR). The enrichment analysis was performed with R software, obtaining the gene ontology (GO) and Kyoto pluripotent stem cells (KEGG) of the genes and genomes. Subsequently, the protein–protein interaction (PPI) networks of each group were established and the hub genes were discovered using the cytoHubba plug-in.Results: In this study, 20 differentially expressed genes were identified, and 6622 genes were identified in the group CR, consisting of 5003 up-regulated and 1619 down-regulated genes. Meanwhile, 7335 genes were screened in the group HR, including 4323 up-regulated and 3012 down-regulated ones. The GO and KEGG analysis of the two groups revealed significant enrichment of these differentially expressed genes in pathways associated with immune response and apoptosis. In the PPI network constructed, 10 hub genes in group CR were identified, including TP53BP1, SNRPD1, SNRPD2, SF3B1, SNRNP200, MRPS16, MRPS9, CALM1, PPP2R1A, YWHAZ. Similarly, TP53BP1, RPS15, EFTUD2, MRPL16, MRPL17, MRPS14, RPL35A, MRPL32, MRPS6, POLR2G were selected as hub genes.Conclusions: Using the messenger ribonucleic acid (mRNA) expression data from GSE166253, we explore the pathogenesis of retesting positive in COVID-19 from the immune mechanism and molecular level. We found TP53BP1, SNRPD1 and SNRPD2 as hub genes in RTP patients. Hence, their regulatory pathway is vital to the management and prognostic prediction of RTP patients, rendering the further study of these hub genes necessary.

scholarly journals Molecular mechanisms of fat deposition: <i>IL-6</i> is a hub gene in fat lipolysis, comparing thin-tailed with fat-tailed sheep breeds

2021 ◽  
Vol 64 (1) ◽  
pp. 53-68
Author(s):  
Sana Farhadi ◽  
Jalil Shodja Ghias ◽  
Karim Hasanpur ◽  
Seyed Abolghasem Mohammadi ◽  
Esmaeil Ebrahimie
Keyword(s):  
Fatty Acid ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Structural Classification ◽  
Hub Genes ◽  
Sheep Breeds ◽  
Ppi Networks ◽  
Structural Classification Of Proteins

Abstract. Tail fat content affects meat quality and varies significantly among different breeds of sheep. Ghezel (fat-tailed) and Zel (thin-tailed) are two important Iranian local sheep breeds with different patterns of fat storage. The current study presents the transcriptome characterization of tail fat using RNA sequencing in order to get a better comprehension of the molecular mechanism of lipid storage in the two mentioned sheep breeds. Seven (Zel = 4 and Ghezel = 3) 7-month-old male lambs were used for this experiment. The results of sequencing were analyzed with bioinformatics methods, including differentially expressed genes (DEGs) identification, functional enrichment analysis, structural classification of proteins, protein–protein interaction (PPI) and network and module analyses. Some of the DEGs, such as LIPG, SAA1, SOCS3, HIF-1α, and especially IL-6, had a close association with lipid metabolism. Furthermore, functional enrichment analysis revealed pathways associated with fat deposition, including “fatty acid metabolism”, “fatty acid biosynthesis” and “HIF-1 signaling pathway”. The structural classification of proteins showed that major down-regulated DEGs in the Zel (thin-tailed) breed were classified under transporter class and that most of them belonged to the solute carrier transporter (SLC) families. In addition, DEGs under the transcription factor class with an important role in lipolysis were up-regulated in the Zel (thin-tailed) breed. Also, network analysis revealed that IL-6 and JUNB were hub genes for up-regulated PPI networks, and HMGCS1, VPS35 and VPS26A were hub genes for down-regulated PPI networks. Among the up-regulated DEGs, the IL-6 gene seems to play an important role in lipolysis of tail fat in thin-tailed sheep breeds via various pathways such as tumor necrosis factor (TNF) signaling and mitogen-activated protein kinase (MAPK) signaling pathways. Due to the probable role of the IL-6 gene in fat lipolysis and also due to the strong interaction of IL-6 with the other up-regulated DEGs, it seems that IL-6 accelerates the degradation of lipids in tail fat cells.

scholarly journals Identification of biomarkers associated with synovitis in rheumatoid arthritis by bioinformatics analyses

2020 ◽  
Vol 40 (9) ◽  
Author(s):  
Zhaoyan Li ◽  
Meng Xu ◽  
Ronghang Li ◽  
Zhengqing Zhu ◽  
Yuzhe Liu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Epidermal Growth Factor Receptor ◽  
Growth Factor ◽  
Epidermal Growth Factor ◽  
Growth Factor Receptor ◽  
Enrichment Analysis ◽  
Hub Genes ◽  
Ppi Networks ◽  
Epidermal Growth ◽  
Potential Biomarkers

Abstract Objectives: Rheumatoid arthritis (RA) is the most common inflammatory arthritis in the world, but its underlying mechanism is still unclear. The present study aims to screen and verify the potential biomarkers of RA. Methods: We searched the Gene Expression Omnibus (GEO) database for synovial expression profiling from different RA microarray studies to perform a systematic analysis. Functional annotation of differentially expressed genes (DEGs) was conducted, including GO enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The protein–protein interaction (PPI) networks of the DEGs were constructed based on data from the STRING database. The expression levels of the hub genes in normal membranes and RA synovium were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot system. Results: A total of 444 differential expression genes were identified, including 172 up-regulated and 272 down-regulated genes in RA synovium compared with normal controls. The top ten hub genes; protein tyrosine phosphatase receptor type C (PTPRC), LCK proto-oncogene (LCK), cell division cycle 20 (CDC20), Jun proto-oncogene (JUN), cyclin-dependent kinase 1 (CDK1), kinesin family member 11 (KIF11), epidermal growth factor receptor (epidermal growth factor receptor (EGFR), vascular endothelial growth factor A (VEGFA), mitotic arrest deficient 2 like 1 (MAD2L1), and signal transducer and activator of transcription 1 (STAT1) were identified from the PPI network, and the expression level of VEGFA and EGFR was significantly increased in RA membranes (P&lt;0.05). Conclusion: Our results indicate that the hub genes VEGFA and EGFR may have essential effects during the development of RA and can be used as potential biomarkers of RA.

scholarly journals Screening of Hub Genes Associated with Lung Adenocarcinoma by Integrated Bioinformatic Analysis

2021 ◽  
Author(s):  
Zimeng Wei ◽  
Min Zhao ◽  
Linnan Zang
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Analysis Tool ◽  
Hub Genes ◽  
Kegg Analysis ◽  
Ppi Networks

Abstract Background Lung adenocarcinoma (LUAD) is the main histological subtype of lung cancer. However, the molecular mechanism underlying LUAD is not yet clearly defined, but elucidating this process in detail would be of great significance for clinical diagnosis and treatment. Methods Gene expression profiles were retrieved from Gene Expression Omnibus database (GEO), and the common differentially expressed genes (DEGs) were identified by online GEO2R analysis tool. Subsequently, the enrichment analysis of function and signaling pathways of DEGs in LUAD were performed by gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomics (KEGG) analysis. The protein-protein interaction (PPI) networks of the DEGs were established through the Search Tool for the Retrieval of Interacting Genes (STRING) database and hub genes were screened by plug-in CytoHubba in Cytoscape. Afterwards, we detected the expression of hub genes in LUAD and other cancers via GEPIA, Oncomine and HPA databases. Finally, Kaplan-Meier plotter were performed to analyze the prognosis efficacy of hub genes. Results 74 up-regulated and 238 down-regulated DEGs were identified. As for the up-regulated DEGs, KEGG analysis results revealed they were mainly enrolled in protein digestion and absorption. However, the down-regulated DEGs were primarily enriched in cell adhesion molecules. Subsequently, 9 hub genes: KIAA0101, CDCA7, TOP2A, CDC20, ASPM, TPX2, CENPF, UBE2T and ECT2, were identified and showed higher expression in both LUAD and other cancers. Finally, all these hub genes were found significantly related to the prognosis of LUAD (p < 0.05). Conclusions Our results screened out the hub genes and pathways that were related to the development and prognosis of LUAD, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of LUAD.

scholarly journals Identification of the Crucial Gene in Overflow Arteriovenous Fistula by Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhengde Zhao ◽  
Qining Fu ◽  
Liangzhu Hu ◽  
Yangdong Liu
Keyword(s):  
Signaling Pathways ◽  
Signaling Pathway ◽  
Intimal Hyperplasia ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Mapk Signaling Pathway ◽  
Biological Processes ◽  
Hub Genes ◽  
Av Fistula ◽  
Core Genes

Objective: The aim was to study the preliminary screening of the crucial genes in intimal hyperplasia in the venous segment of arteriovenous (AV) fistula and the underlying potential molecular mechanisms of intimal hyperplasia with bioinformatics analysis.Methods: The gene expression profile data (GSE39488) was analyzed to identify differentially expressed genes (DEGs). We performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of DEGs. Gene set enrichment analysis (GSEA) was used to understand the potential activated signaling pathway. The protein–protein interaction (PPI) network was constructed with the STRING database and Cytoscape software. The Venn diagram between 10 hub genes and gene sets of 4 crucial signaling pathways was used to obtain core genes and relevant potential pathways. Furthermore, GSEAs were performed to understand their biological functions.Results: A total of 185 DEGs were screened in this study. The main biological function of the 111 upregulated genes in AV fistula primarily concentrated on cell proliferation and vascular remodeling, and the 74 downregulated genes in AV fistula were enriched in the biological function mainly relevant to inflammation. GSEA found four signaling pathways crucial for intimal hyperplasia, namely, MAPK, NOD-like, Cell Cycle, and TGF-beta signaling pathway. A total of 10 hub genes were identified, namely, EGR1, EGR2, EGR3, NR4A1, NR4A2, DUSP1, CXCR4, ATF3, CCL4, and CYR61. Particularly, DUSP1 and NR4A1 were identified as core genes that potentially participate in the MAPK signaling pathway. In AV fistula, the biological processes and pathways were primarily involved with MAPK signaling pathway and MAPK-mediated pathway with the high expression of DUSP1 and were highly relevant to cell proliferation and inflammation with the low expression of DUSP1. Besides, the biological processes and pathways in AV fistula with the high expression of NR4A1 similarly included the MAPK signaling pathway and the pathway mediated by MAPK signaling, and it was mainly involved with inflammation in AV fistula with the low expression of NR4A1.Conclusion: We screened four potential signaling pathways relevant to intimal hyperplasia and identified 10 hub genes, including two core genes (i.e., DUSP1 and NR4A1). Two core genes potentially participate in the MAPK signaling pathway and might serve as the therapeutic targets of intimal hyperplasia to prevent stenosis after AV fistula creation.

scholarly journals A Comprehensive Network Pharmacology-Based Strategy to Investigate Multiple Mechanisms of HeChan Tablet on Lung Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Zhenjie Zhuang ◽  
Qianying Chen ◽  
Cihui Huang ◽  
Junmao Wen ◽  
Haifu Huang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Therapeutic Target ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Network Pharmacology ◽  
Hub Genes ◽  
Lung Cancer Patients ◽  
Ppi Networks

Background. HeChan tablet (HCT) is a traditional Chinese medicine preparation extensively prescribed to treat lung cancer in China. However, the pharmacological mechanisms of HCT on lung cancer remain to be elucidated. Methods. A comprehensive network pharmacology-based strategy was conducted to explore underlying mechanisms of HCT on lung cancer. Putative targets and compounds of HCT were retrieved from TCMSP and BATMAN-TCM databases; related genes of lung cancer were retrieved from OMIM and DisGeNET databases; known therapeutic target genes of lung cancer were retrieved from TTD and DrugBank databases; PPI networks among target genes were constructed to filter hub genes by STRING. Furthermore, the pathway and GO enrichment analysis of hub genes was performed by clusterProfiler, and the clinical significance of hub genes was identified by The Cancer Genome Atlas. Result. A total of 206 compounds and 2,433 target genes of HCT were obtained. 5,317 related genes of lung cancer and 77 known therapeutic target genes of lung cancer were identified. 507 unique target genes were identified among HCT-related genes of lung cancer and 34 unique target genes were identified among HCT-known therapeutic target genes of lung cancer. By PPI networks, 11 target genes AKT1, TP53, MAPK8, JUN, EGFR, TNF, INS, IL-6, MYC, VEGFA, and MAPK1 were identified as major hub genes. IL-6, JUN, EGFR, and MYC were shown to associate with the survival of lung cancer patients. Five compounds of HCT， quercetin, luteolin, kaempferol, beta-sitosterol, and baicalein were recognized as key compounds of HCT on lung cancer. The gene enrichment analysis implied that HCT probably benefitted patients with lung cancer by modulating the MAPK and PI3K-Akt pathways. Conclusion. This study predicted pharmacological and molecular mechanisms of HCT against lung cancer and could pave the way for further experimental research and clinical application of HCT.

scholarly journals Bioinformatics analysis of common key genes and pathways of intracranial, abdominal, and thoracic aneurysms

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Siwei Bi ◽  
Ruiqi Liu ◽  
Linfeng He ◽  
Jingyi Li ◽  
Jun Gu
Keyword(s):  
Aortic Aneurysm ◽  
Enrichment Analysis ◽  
Cytosolic Calcium ◽  
Gene Expression Omnibus ◽  
Ion Concentration ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Thoracic Aneurysms ◽  
Calcium Ion Concentration

Abstract Background Aneurysm is a severe and fatal disease. This study aims to comprehensively identify the highly conservative co-expression modules and hub genes in the abdominal aortic aneurysm (AAA), thoracic aortic aneurysm (TAA) and intracranial aneurysm (ICA) and facilitate the discovery of pathogenesis for aneurysm. Methods GSE57691, GSE122897, and GSE5180 microarray datasets were downloaded from the Gene Expression Omnibus database. We selected highly conservative modules using weighted gene co‑expression network analysis before performing the Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway and Reactome enrichment analysis. The protein–protein interaction (PPI) network and the miRNA-hub genes network were constructed. Furtherly, we validated the preservation of hub genes in three other datasets. Results Two modules with 193 genes and 159 genes were identified as well preserved in AAA, TAA, and ICA. The enrichment analysis identified that these genes were involved in several biological processes such as positive regulation of cytosolic calcium ion concentration, hemostasis, and regulation of secretion by cells. Ten highly connected PPI networks were constructed, and 55 hub genes were identified. In the miRNA-hub genes network, CCR7 was the most connected gene, followed by TNF and CXCR4. The most connected miRNAs were hsa-mir-26b-5p and hsa-mir-335-5p. The hub gene module was proved to be preserved in all three datasets. Conclusions Our study highlighted and validated two highly conservative co-expression modules and miRNA-hub genes network in three kinds of aneurysms, which may promote understanding of the aneurysm and provide potential therapeutic targets and biomarkers of aneurysm.

scholarly journals Bioinformatics Analysis to Identify Key Genes and Pathways Associated with Sex Differences in Rheumatoid Arthritis

2021 ◽  
Author(s):  
Siwei Su ◽  
Wenjun Jiang ◽  
Xiaoying Wang ◽  
Sen Du ◽  
Lu Zhou ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Kegg Pathways ◽  
Ppi Networks ◽  
Males And Females ◽  
Key Genes

Abstract ObjectiveThis study aims to explore the key genes and investigated the different signaling pathways of rheumatoid arthritis (RA) between males and females.Data and MethodsThe gene expression data of GSE55457, GSE55584, and GSE12021 were obtained from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using R software. Then, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were conducted via Database for Annotation, Visualization, and Integrated Discovery (DAVID). The protein-protein interaction (PPI) networks of DEGs were constructed by Cytoscape 3.6.0. ResultsA total of 416 upregulated DEGs and 336 downregulated DEGs were identified in males, and 744 upregulated DEGs and 309 downregulated DEGs were identified in females.IL6, MYC, EGFR, FOS and JUN were considered as hub genes in RA pathogenesis in males, while IL6, ALB, PTPRC, CXCL8 and CCR5 were considered as hub genes in RA pathogenesis in females. ConclusionIdentified DEG may be involved in the different mechanisms of RA disease progression between males and females, and they are treated as prognostic markers or therapeutic targets for males and females. The pathogenesis mechanism of RA is sex-dependent.

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