scholarly journals Identification of Differentially Expressed Genes Triggered by Aberrant Methylation in Idiopathic Pulmonary Fibrosis Using Integrated Bioinformatic Analysis

2020 ◽  
Author(s):  
Shuaijun Chen ◽  
Jun Zhang ◽  
Wanli Ma ◽  
Hong Ye
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Epigenetic Mechanism ◽  
Integrated Analysis ◽  
Aberrant Methylation ◽  
Mrna Levels

Abstract BackgroundIdiopathic pulmonary fibrosis (IPF) is a relentlessly progressive and fatal fibrotic lung disease all over the world, and specific pathogenesis is still not well understood. DNA methylation is an essential epigenetic mechanism, which likely contributes to the progress of IPF. The purpose of this study is to identify aberrantly methylated differentially expressed genes (DEGs) in IPF and to explore the underlying mechanisms of IPF by using integrated bioinformatics analysis.MethodGene expression profiles and gene methylation profile were downloaded and analyzed to identify the aberrantly methylated‐differentially expressed genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Search Tool for the Retrieval of Interacting Genes Database (STRING) and Gene set enrichment analysis (GSEA) were used to evaluate function of DEGs. RT-PCR was used to verify the mRNA levels of DEGs in mice with pulmonary fibrosis.ResultsBy analyzing the differentially expressed genes of the three IPF expression profiles, and taking the intersection, we got 143 co-upregulated genes and 104 co-downregulated genes; GO and KEGG pathway analysis of the DEGs suggested these genes involved in the extracellular matrix organization, multicellular organismal homeostasis. Combining the sequencing data of two IPF methylation chips, we have identified genes that may be regulated by methylation in IPF. Finally, we obtained the mRNA expression of DEGs using a mouse model of pulmonary fibrosis.ConclusionThrough integrated analysis and experimental verification, we found a series of biomarkers which were regulated by methylation should be potential therapeutic targets for IPF.

scholarly journals Identification of differentially expressed genes triggered by aberrant methylation in idiopathic pulmonary fibrosis using integrated bioinformatic analysis

2021 ◽  
Author(s):  
Shuaijun Chen ◽  
Jun Zhang ◽  
Wanli Ma ◽  
Hong Ye
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Epigenetic Mechanism ◽  
Integrated Analysis ◽  
Aberrant Methylation ◽  
Mrna Levels

Abstract Background Idiopathic pulmonary fibrosis (IPF) is a relentlessly progressive and fatal fibrotic lung disease all over the world, and specific pathogenesis is still not well understood. DNA methylation is an essential epigenetic mechanism, which likely contributes to the progress of IPF. The purpose of this study is to identify aberrantly methylated differentially expressed genes (DEGs) in IPF and to explore the underlying mechanisms of IPF by using integrated bioinformatics analysis.Methods Gene expression profiles and gene methylation profiles were downloaded and analyzed to identify the aberrantly methylated‐differentially expressed genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Search Tool for the Retrieval of Interacting Genes Database (STRING), and Gene set enrichment analysis (GSEA) were used to evaluate the function of DEGs. RT-PCR was used to verify the mRNA levels of DEGs in mice with pulmonary fibrosis.Results By analyzing the differentially expressed genes of the three IPF expression profiles, and taking the intersection, we got 143 co-upregulated genes and 104 co-downregulated genes; GO and KEGG pathway analysis of the DEGs suggested these genes involved in the extracellular matrix organization, multicellular organismal homeostasis. Combining the sequencing data of two IPF methylation chips, we have identified genes that may be regulated by methylation in IPF. Finally, we obtained the mRNA expression of DEGs using a mouse model of pulmonary fibrosis.Conclusions Through integrated analysis and experimental verification, we found a series of biomarkers that were regulated by methylation should be potential therapeutic targets for IPF.

scholarly journals The Effects of Epigallocatechin Gallate (EGCG) on Pulmonary Fibroblasts of Idiopathic Pulmonary Fibrosis (IPF)—A Next-Generation Sequencing and Bioinformatic Approach

2019 ◽  
Vol 20 (8) ◽  
pp. 1958 ◽  
Author(s):  
Ming-Ju Tsai ◽  
Wei-An Chang ◽  
Ssu-Hui Liao ◽  
Kuo-Feng Chang ◽  
Chau-Chyun Sheu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Next Generation Sequencing ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Epigallocatechin Gallate ◽  
Differentially Expressed ◽  
Pulmonary Fibroblasts ◽  
Generation Sequencing

Idiopathic pulmonary fibrosis (IPF) is a disabling and lethal chronic progressive pulmonary disease. Epigallocatechin gallate (EGCG) is a polyphenol, which is the major biological component of green tea. The anti-oxidative, anti-inflammatory, and anti-fibrotic effects of EGCG have been shown in some studies, whereas its effects in altering gene expression in pulmonary fibroblasts have not been systematically investigated. This study aimed to explore the effect of EGCG on gene expression profiles in fibroblasts of IPF. The pulmonary fibroblasts from an IPF patient were treated with either EGCG or water, and the expression profiles of mRNAs and microRNAs were determined by next-generation sequencing (NGS) and analyzed with the bioinformatics approach. A total of 61 differentially expressed genes and 56 differentially expressed microRNAs were found in EGCG-treated IPF fibroblasts. Gene ontology analyses revealed that the differentially expressed genes were mainly involved in the biosynthetic and metabolic processes of cholesterol. In addition, five potential altered microRNA–mRNA interactions were found, including hsa-miR-939-5p–PLXNA4, hsa-miR-3918–CTIF, hsa-miR-4768-5p–PDE5A, hsa-miR-1273g-3p–VPS53, and hsa-miR-1972–PCSK9. In summary, differentially expressed genes and microRNAs in response to EGCG treatment in IPF fibroblasts were identified in the current study. Our findings provide a scientific basis to evaluate the potential benefits of EGCG in IPF treatment, and warrant future studies to understand the role of molecular pathways underlying cholesterol homeostasis in the pathogenesis of IPF.

scholarly journals Potential function and molecular mechanism of circRNAs involved in idiopathic pulmonary fibrosis

2020 ◽  
Author(s):  
Fangwei Li ◽  
Hong Wang ◽  
Hongyan Tao ◽  
Fanqi Wu ◽  
Dan Wang ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Molecular Mechanism ◽  
Target Genes ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Circular Rnas

Abstract Background: Recent studies have found a regulatory role of circular RNAs (circRNAs) in the pathogenesis of idiopathic pulmonary fibrosis (IPF). However, the function and underlying molecular mechanism of circRNAs involved in IPF are uncertain and incomplete. This study aimed to further provide some critical information for the circRNA function in IPF using bioinformatic analysis. Methods: We searched in the NCBI (National Center for Biotechnology Information) Gene Expression Omnibus (GEO) database to find the circRNA expression profiles of human IPF. The microarray data GSE102660 was obtained and differentially expressed circRNAs were identified through R software. Results: 6 significantly up-regulated and 13 significantly down-regulated circRNAs were identified involved in the pathogenesis of IPF. The binding sites of miRNAs for each differentially expressed circRNA were also predicted and circRNA-miRNA-mRNA networks were constructed for the most up-regulated hsa_circ_0004099 and down-regulated hsa_circ_0029633. In addition, GO and KEGG enrichment analysis revealed the molecular function and enriched pathways of the target genes of circRNAs in IPF.Conclusion: These findings suggest that candidate circRNAs might serve an important role in the pathogenesis of IPF. Therefore, these circRNAs might be potential biomarkers for diagnosis and promising targets for treatment of IPF, which still need further verification in vivo and in vitro.

scholarly journals Identification of Key Genes Involved in Acute Myocardial Infarction by Comparative Transcriptome Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xiaodong Sheng ◽  
Tao Fan ◽  
Xiaoqi Jin
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Differentially Expressed Genes ◽  
Protein Interaction ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Protein Protein Interaction ◽  
Key Genes ◽  
Rna Interaction

Background. Acute myocardial infarction (AMI) is regarded as an urgent clinical entity, and identification of differentially expressed genes, lncRNAs, and altered pathways shall provide new insight into the molecular mechanisms behind AMI. Materials and Methods. Microarray data was collected to identify key genes and lncRNAs involved in AMI pathogenesis. The differential expression analysis and gene set enrichment analysis (GSEA) were employed to identify the upregulated and downregulated genes and pathways in AMI. The protein-protein interaction network and protein-RNA interaction analysis were utilized to reveal key long noncoding RNAs. Results. In the present study, we utilized gene expression profiles of circulating endothelial cells (CEC) from 49 patients of AMI and 50 controls and identified a total of 552 differentially expressed genes (DEGs). Based on these DEGs, we also observed that inflammatory response-related genes and pathways were highly upregulated in AMI. Mapping the DEGs to the protein-protein interaction (PPI) network and identifying the subnetworks, we found that OMD and WDFY3 were the hub nodes of two subnetworks with the highest connectivity, which were found to be involved in circadian rhythm and organ- or tissue-specific immune response. Furthermore, 23 lncRNAs were differentially expressed between AMI and control groups. Specifically, we identified some functional lncRNAs, including XIST and its antisense RNA, TSIX, and three lncRNAs (LINC00528, LINC00936, and LINC01001), which were predicted to be interacting with TLR2 and participate in Toll-like receptor signaling pathway. In addition, we also employed the MMPC algorithm to identify six gene signatures for AMI diagnosis. Particularly, the multivariable SVM model based on the six genes has achieved a satisfying performance ( AUC = 0.97 ). Conclusion. In conclusion, we have identified key regulatory lncRNAs implicated in AMI, which not only deepens our understanding of the lncRNA-related molecular mechanism of AMI but also provides computationally predicted regulatory lncRNAs for AMI researchers.

scholarly journals Integrated Analysis of a Gene Correlation Network Identifies Critical Regulation of Fibrosis by lncRNAs and TFs in Idiopathic Pulmonary Fibrosis

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Fan Wang ◽  
Pei Li ◽  
Feng-sen Li
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Pcr Analysis ◽  
Unknown Etiology ◽  
Integrated Analysis ◽  
Protein Protein Interaction ◽  
Lncrna Malat1 ◽  
Significant Difference

Idiopathic pulmonary fibrosis (IPF), the most frequent form of irreversible interstitial pneumonia with unknown etiology, is characterized by massive remodeling of lung architecture and followed by progressive loss of lung function. However, the key regulatory genes and the specific signaling pathways involved in the onset and progression of IPF still remain unclear. The present study is aimed at investigating the key role of long noncoding RNAs (lncRNAs) and transcription factors (TFs) involved in the pathogenesis of IPF through the integrated analysis of three gene expression profiles from the GEO dataset (GSE2052, GSE44723, and GSE24206). A total of 8483 differentially expressed genes (DEGs) including 988 upregulated and 7495 downregulated genes were filtered. Subsequently, following the intersection of these DEGs, 29 overlapping genes were identified and further analyzed using a bioinformatics approach. Furthermore, the protein-protein interaction (PPI) network was used to obtain 18 modules of related genes. The hub genes were identified through hypergeometric testing, which were closely associated with ubiquitin-mediated proteolysis, the spliceosome, and the cell cycle. The significant difference was observed in the expression of these key genes, such as lncRNA MALAT1, E2F1, and YBX1, in the peripheral blood of IPF patients when compared with those normal control subjects by real-time polymerase chain reaction (RT-PCR) analysis. This study indicated that lncRNA MALAT1, E2F1, and YBX1 may be key regulators for the pathogenesis of IPF.

scholarly journals Identification of Pyrvinium, an Anthelmintic Drug, as a Novel Anti-Adipogenic Compound Based on the Gene Expression Microarray and Connectivity Map

Molecules ◽  
2019 ◽  
Vol 24 (13) ◽  
pp. 2391 ◽  
Author(s):  
Zonggui Wang ◽  
Zhong Dai ◽  
Zhicong Luo ◽  
Changqing Zuo
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Drug Repositioning ◽  
Expression Profiles ◽  
Adipogenic Differentiation ◽  
Differentially Expressed ◽  
Mrna Levels ◽  
Dependent Manner ◽  
Connectivity Map ◽  
Obesity Drugs

Obesity is a serious health problem, while the current anti-obesity drugs are not very effective. The Connectivity Map (C-Map), an in-silico drug screening approach based on gene expression profiles, has recently been indicated as a promising strategy for drug repositioning. In this study, we performed mRNA expression profile analysis using microarray technology and identified 435 differentially expressed genes (DEG) during adipogenesis in both C3H10T1/2 and 3T3-L1 cells. Then, DEG signature was uploaded into C-Map, and using pattern-matching methods we discovered that pyrvinium, a classical anthelminthic, is a novel anti-adipogenic differentiation agent. Pyrvinium suppressed adipogenic differentiation in a dose-dependent manner, as evidenced by Oil Red O staining and the mRNA levels of adipogenic markers. Furthermore, we identified that the inhibitory effect of pyrvinium was resulted primarily from the early stage of adipogenesis. Molecular studies showed that pyrvinium downregulated the expression of key transcription factors C/EBPa and PPARγ. The mRNA levels of notch target genes Hes1 and Hey1 were obviously reduced after pyrvinium treatment. Taken together, this study identified many differentially expressed genes involved in adipogenesis and demonstrated for the first time that pyrvinium is a novel anti-adipogenic compound for obesity therapy. Meanwhile, we provided a new strategy to explore potential anti-obesity drugs.

scholarly journals A Bioinformatics Approach to Identifying Potential Biomarkers for Cryptosporidium parvum: A Coccidian Parasite Associated with Fetal Diarrhea

Vaccines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1427
Author(s):  
Mumdooh J. Sabir ◽  
Ross Low ◽  
Neil Hall ◽  
Majid Rasool Kamli ◽  
Md. Zubbair Malik
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Cryptosporidium Parvum ◽  
Early Stage ◽  
Expression Profiles ◽  
Interaction Network ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Data Sets ◽  
Gene Interaction Network

Cryptosporidium parvum (C. parvum) is a protozoan parasite known for cryptosporidiosis in pre-weaned calves. Animals and patients with immunosuppression are at risk of developing the disease, which can cause potentially fatal diarrhoea. The present study aimed to construct a network biology framework based on the differentially expressed genes (DEGs) of C. parvum infected subjects. In this way, the gene expression profiling analysis of C. parvum infected individuals can give us a snapshot of actively expressed genes and transcripts under infection conditions. In the present study, we have analyzed microarray data sets and compared the gene expression profiles of the patients with the different data sets of the healthy control. Using a network medicine approach to identify the most influential genes in the gene interaction network, we uncovered essential genes and pathways related to C. parvum infection. We identified 164 differentially expressed genes (109 up- and 54 down-regulated DEGs) and allocated them to pathway and gene set enrichment analysis. The results underpin the identification of seven significant hub genes with high centrality values: ISG15, MX1, IFI44L, STAT1, IFIT1, OAS1, IFIT3, RSAD2, IFITM1, and IFI44. These genes are associated with diverse biological processes not limited to host interaction, type 1 interferon production, or response to IL-gamma. Furthermore, four genes (IFI44, IFIT3, IFITM1, and MX1) were also discovered to be involved in innate immunity, inflammation, apoptosis, phosphorylation, cell proliferation, and cell signaling. In conclusion, these results reinforce the development and implementation of tools based on gene profiles to identify and treat Cryptosporidium parvum-related diseases at an early stage.

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