Meta-analysis of Transcriptomic Data Reveals Pathophysiological Modules Involved with Atrial Fibrillation

Complex Disease ◽

Meta Analysis ◽

Differential Expression Analysis ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment ◽

P Value

Atrial fibrillation (AF) is a complex disease and affects millions of people around the world. The biological mechanisms that are involved with AF are complex and still need to be fully elucidated. Therefore, we performed a meta-analysis of transcriptome data related to AF to explore these mechanisms aiming at more sensitive and reliable results. Public transcriptomic datasets were downloaded, analyzed for quality control, and individually pre-processed. Differential expression analysis was carried out for each individual dataset, and the results were meta-analytically aggregated using the r-th ordered p-value method. We analyzed the final list of differentially expressed genes through network analysis, namely topological and modularity analysis, and functional enrichment analysis. The meta-analysis of transcriptomes resulted in 589 differentially expressed genes, whose protein-protein interaction network presented 11 hubs-bottlenecks and four main identified functional modules. These modules were enriched for, respectively, 23, 54, 33, and 53 biological pathways involved with the pathophysiology of AF, especially with the disease's structural and electrical remodeling processes. Stress of the endoplasmic reticulum, protein catabolism, oxidative stress, and inflammation are some of the enriched processes. Among hubs-bottlenecks genes, which are highly connected and probably have a key role in regulating these processes, we found HSPA5, ANK2, CTNNB1, and VWF. Further experimental investigation of our findings may shed light on the pathophysiology of the disease and contribute to the identification of new therapeutic targets and treatments.

Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

Lung Cancer Management ◽

10.2217/lmt-2020-0009 ◽

2020 ◽

Vol 9 (2) ◽

pp. LMT30

Author(s):

Chuanli Ren ◽

Weixiu Sun ◽

Xu Lian ◽

Chongxu Han

Keyword(s):

Lung Adenocarcinoma ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Kaplan Meier ◽

Key Genes ◽

Core Genes

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.

Multiple-Tissue and Multilevel Analysis on Differentially Expressed Genes and Differentially Correlated Gene Pairs for HFpEF

Frontiers in Genetics ◽

10.3389/fgene.2021.668702 ◽

2021 ◽

Vol 12 ◽

Author(s):

Guofeng Zhou ◽

Shaoyan Sun ◽

Qiuyue Yuan ◽

Run Zhang ◽

Ping Jiang ◽

...

Keyword(s):

Adipose Tissue ◽

Complex Disease ◽

Cerebral Arteries ◽

Interaction Network ◽

Functional Enrichment ◽

Hub Genes ◽

Tissue Specific ◽

Gene Pairs

Heart failure with preserved ejection fraction (HFpEF) is a complex disease characterized by dysfunctions in the heart, adipose tissue, and cerebral arteries. The elucidation of the interactions between these three tissues in HFpEF will improve our understanding of the mechanism of HFpEF. In this study, we propose a multilevel comparative framework based on differentially expressed genes (DEGs) and differentially correlated gene pairs (DCGs) to investigate the shared and unique pathological features among the three tissues in HFpEF. At the network level, functional enrichment analysis revealed that the networks of the heart, adipose tissue, and cerebral arteries were enriched in the cell cycle and immune response. The networks of the heart and adipose tissues were enriched in hemostasis, G-protein coupled receptor (GPCR) ligand, and cancer-related pathway. The heart-specific networks were enriched in the inflammatory response and cardiac hypertrophy, while the adipose-tissue-specific networks were enriched in the response to peptides and regulation of cell adhesion. The cerebral-artery-specific networks were enriched in gene expression (transcription). At the module and gene levels, 5 housekeeping DEGs, 2 housekeeping DCGs, 6 modules of merged protein–protein interaction network, 5 tissue-specific hub genes, and 20 shared hub genes were identified through comparative analysis of tissue pairs. Furthermore, the therapeutic drugs for HFpEF-targeting these genes were examined using molecular docking. The combination of multitissue and multilevel comparative frameworks is a potential strategy for the discovery of effective therapy and personalized medicine for HFpEF.

Integrative Analysis for Elucidating Transcriptomics Landscapes of Systemic Lupus Erythematosus

Frontiers in Genetics ◽

10.3389/fgene.2021.782005 ◽

2021 ◽

Vol 12 ◽

Author(s):

Haihong Zhang ◽

Yanli Wang ◽

Jinghui Feng ◽

Shuya Wang ◽

Yan Wang ◽

...

Keyword(s):

Systemic Lupus Erythematosus ◽

Lupus Erythematosus ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Integrated Analysis ◽

Potential Candidate ◽

Systemic Lupus

Systemic lupus erythematosus (SLE) is a complex and heterogeneous autoimmune disease that the immune system attacks healthy cells and tissues. SLE is difficult to get a correct and timely diagnosis, which makes its morbidity and mortality rate very high. The pathogenesis of SLE remains to be elucidated. To clarify the potential pathogenic mechanism of SLE, we performed an integrated analysis of two RNA-seq datasets of SLE. Differential expression analysis revealed that there were 4,713 and 2,473 differentially expressed genes, respectively, most of which were up-regulated. After integrating differentially expressed genes, we identified 790 common differentially expressed genes (DEGs). Gene functional enrichment analysis was performed and found that common differentially expressed genes were significantly enriched in some important immune-related biological processes and pathways. Our analysis provides new insights into a better understanding of the pathogenic mechanisms and potential candidate markers for systemic lupus erythematosus.

Identification and Interaction Analysis of Significant Genes and MicroRNAs in Pterygium

BioMed Research International ◽

10.1155/2019/2767512 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Siying He ◽

Hui Sun ◽

Yifang Huang ◽

Shiqi Dong ◽

Chen Qiao ◽

...

Keyword(s):

Molecular Mechanisms ◽

Interaction Analysis ◽

Interaction Network ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Differentially Expressed Mirnas

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.

Based on bioinformatics analysis, NF1, BTRC and MAPK14 are the potential biomarkers in the progression of osteoarthritis synovitis

10.21203/rs.3.rs-349764/v1 ◽

2021 ◽

Author(s):

Mingyi Yang ◽

Yani Su ◽

Yao Ma ◽

Yirixiati Aihaiti ◽

Peng Xu

Keyword(s):

Interaction Network ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Hub Genes ◽

Hub Gene ◽

Potential Biomarkers

Abstract Objective: To study the potential biomarkers and related pathways in osteoarthritis (OA) synovial lesions, and to provide theoretical basis and research directions for the pathogenesis and treatment of OA. Methods: Download the microarray data sets GSE12021 and GSE82107 from Gene Expression Omnibus. GEO2R recognizes differentially expressed genes. Perform functional enrichment analysis of differentially expressed genes and construct protein-protein interaction network. Cytoscape performs module analysis and enrichment analysis of top-level modules. Further identify the Hub gene and perform functional enrichment analysis. TargetScan, miRDB and miRWalk three databases predict the target miRNAs of Hub gene and identify key miRNAs. Results: Finally, 10 Hub genes and 17 key miRNAs related to the progression of OA synovitis were identified. NF1, BTRC and MAPK14 may play a vital role in OA synovial disease. Conclusion: The Hub genes and key miRNAs discovered in this study may be potential biomarkers in the development of OA synovitis, and provide research methods and target basis for the pathogenesis and treatment of OA.

Diagnostic model of combined ceRNA and DNA methylation related genes in esophageal carcinoma

PeerJ ◽

10.7717/peerj.8831 ◽

2020 ◽

Vol 8 ◽

pp. e8831 ◽

Cited By ~ 1

Author(s):

Xiaojiao Guan ◽

Yao Yao ◽

Guangyao Bao ◽

Yue Wang ◽

Aimeng Zhang ◽

...

Keyword(s):

Gene Expression ◽

Esophageal Cancer ◽

Esophageal Carcinoma ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Diagnostic Model ◽

Link Type ◽

Key Genes

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.

Potential genes and pathways along with immune cells infiltration in the progression of atherosclerosis identified via microarray gene expression dataset re-analysis

Vascular ◽

10.1177/1708538120922700 ◽

2020 ◽

Vol 28 (5) ◽

pp. 643-654 ◽

Cited By ~ 1

Author(s):

Jing Xu ◽

Yuejin Yang

Keyword(s):

Immune Cells ◽

Interaction Network ◽

Wilcoxon Test ◽

P Value ◽

The Novel ◽

Microarray Gene Expression ◽

Progression Of Atherosclerosis ◽

Geo Database

Objective Atherosclerosis is a chronic inflammatory process characterized by the accumulation and formation of lipid-rich plaques within the layers of the arterial wall. Although numerous studies have reported the underlying pathogenesis, no data-based studies have been conducted to analyze the potential genes and immune cells infiltration in the different stages of atherosclerosis via bioinformatics analysis. Methods In this study, we downloaded GSE100927 and GSE28829 from NCBI-GEO database. Gene ontology and pathway enrichment were performed via the DAVID database. The protein interaction network was constructed via STRING. Enriched hub genes were analyzed by the Cytoscape software. The evaluation of the infiltrating immune cells in the dataset samples was performed by the CIBERSORT algorithm. Results We identified 114 common upregulated differentially expressed genes and 22 common downregulated differentially expressed genes. (adjust p value < 0.01 and log FC ≥ 1). A cluster of 10 genes including CYBA, SLC11A1, FCER1G, ITGAM, ITGB2, CD53, ITGAX, VAMP8, CLEC5A, and CD300A were found to be significant. Through the deconvolution algorithm CIBERSORT, we analyzed the significant alteration of immune cells infiltration in the progression of atherosclerosis with the threshold of the Wilcoxon test at p value <0.05. Conclusions These results may reveal the underlying correlations between genes and immune cells in atherosclerosis, which enable us to investigate the novel insights for the development of treatments and drugs.

System Analysis of MIRNAs in Maize Internode Elongation

Biomolecules ◽

10.3390/biom9090417 ◽

2019 ◽

Vol 9 (9) ◽

pp. 417

Author(s):

Chuanxi Peng ◽

Xing Wang ◽

Tianyu Feng ◽

Rui He ◽

Mingcai Zhang ◽

...

Keyword(s):

Target Genes ◽

System Analysis ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Internode Elongation ◽

Differentially Expressed Mirnas ◽

Post Transcriptional Regulation

MicroRNAs (miRNAs), the post-transcriptional gene regulators, are known to play an important role in plant development. The identification of differentially expressed miRNAs could better help us understand the post-transcriptional regulation that occurs during maize internode elongation. Accordingly, we compared the expression of MIRNAs between fixed internode and elongation internode samples and classified six differentially expressed MIRNAs as internode elongation-responsive miRNAs including zma-MIR160c, zma-MIR164b, zma-MIR164c, zma-MIR168a, zma-MIR396f, and zma-MIR398b, which target mRNAs supported by transcriptome sequencing. Functional enrichment analysis for predictive target genes showed that these miRNAs were involved in the development of internode elongation by regulating the genes respond to hormone signaling. To further reveal how miRNA affects internode elongation by affecting target genes, the miRNA–mRNA–PPI (protein and protein interaction) network was constructed to summarize the interaction of miRNAs and these target genes. Our results indicate that miRNAs regulate internode elongation in maize by targeting genes related to cell expansion, cell wall synthesis, transcription, and regulatory factors.

Comparative transcriptomic analysis of porcine peripheral blood reveals differentially expressed genes from the cytokine–cytokine receptor interaction pathway related to health status

Genome ◽

10.1139/gen-2017-0074 ◽

2017 ◽

Vol 60 (12) ◽

pp. 1021-1028 ◽

Cited By ~ 2

Author(s):

M.H. Ye ◽

H. Bao ◽

Y. Meng ◽

L.L. Guan ◽

P. Stothard ◽

...

Keyword(s):

Health Status ◽

Peripheral Blood ◽

Enrichment Analysis ◽

Cytokine Receptor ◽

Functional Enrichment ◽

Receptor Interaction ◽

Marker Genes

While some research has looked into the host genetic response in pigs challenged with specific viruses or bacteria, few studies have explored the expression changes of transcripts in the peripheral blood of sick pigs that may be infected with multiple pathogens on farms. In this study, the architecture of the peripheral blood transcriptome of 64 Duroc sired commercial pigs, including 18 healthy animals at entry to a growing facility (set as a control) and 23 pairs of samples from healthy and sick pen mates, was generated using RNA-Seq technology. In total, 246 differentially expressed genes were identified to be specific to the sick animals. Functional enrichment analysis for those genes revealed that the over-represented gene ontology terms for the biological processes category were exclusively immune activity related. The cytokine–cytokine receptor interaction pathway was significantly enriched. Nine functional genes from this pathway encoding members (as well as their receptors) of the interleukins, chemokines, tumor necrosis factors, colony stimulating factors, activins, and interferons exhibited significant transcriptional alteration in sick animals. Our results suggest a subset of novel marker genes that may be useful candidate genes in the evaluation and prediction of health status in pigs under commercial production conditions.

Identification of novel genes and pathways in carotid atheroma using integrated bioinformatic methods

Scientific Reports ◽

10.1038/srep18764 ◽

2016 ◽

Vol 6 (1) ◽

Cited By ~ 10

Author(s):

Wenqing Nai ◽

Diane Threapleton ◽

Jingbo Lu ◽

Kewei Zhang ◽

Hongyuan Wu ◽

...

Keyword(s):

Signaling Pathway ◽

Transforming Growth Factor ◽

Interaction Network ◽

Enrichment Analysis ◽

Transforming Growth Factor Β ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Atheromatous Plaques

Abstract Atherosclerosis is the primary cause of cardiovascular events and its molecular mechanism urgently needs to be clarified. In our study, atheromatous plaques (ATH) and macroscopically intact tissue (MIT) sampled from 32 patients were compared and an integrated series of bioinformatic microarray analyses were used to identify altered genes and pathways. Our work showed 816 genes were differentially expressed between ATH and MIT, including 443 that were up-regulated and 373 that were down-regulated in ATH tissues. GO functional-enrichment analysis for differentially expressed genes (DEGs) indicated that genes related to the “immune response” and “muscle contraction” were altered in ATHs. KEGG pathway-enrichment analysis showed that up-regulated DEGs were significantly enriched in the “FcεRI-mediated signaling pathway”, while down-regulated genes were significantly enriched in the “transforming growth factor-β signaling pathway”. Protein-protein interaction network and module analysis demonstrated that VAV1, SYK, LYN and PTPN6 may play critical roles in the network. Additionally, similar observations were seen in a validation study where SYK, LYN and PTPN6 were markedly elevated in ATH. All in all, identification of these genes and pathways not only provides new insights into the pathogenesis of atherosclerosis, but may also aid in the development of prognostic and therapeutic biomarkers for advanced atheroma.