Dataset Information

Identification of candidate genes in ischemic cardiomyopathy by gene expression omnibus database.

ABSTRACT: BACKGROUND:Ischemic cardiomyopathy (ICM) is one of the most usual causes of death worldwide. This study aimed to find the candidate gene for ICM. METHODS:We studied differentially expressed genes (DEGs) in ICM compared to healthy control. According to these DEGs, we carried out the functional annotation, protein-protein interaction (PPI) network and transcriptional regulatory network constructions. The expression of selected candidate genes were confirmed using a published dataset and Quantitative real time polymerase chain reaction (qRT-PCR). RESULTS:From three Gene Expression Omnibus (GEO) datasets, we acquired 1081 DEGs (578 up-regulated and 503 down-regulated genes) between ICM and healthy control. The functional annotation analysis revealed that cardiac muscle contraction, hypertrophic cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy and dilated cardiomyopathy were significantly enriched pathways in ICM. SNRPB, BLM, RRS1, CDK2, BCL6, BCL2L1, FKBP5, IPO7, TUBB4B and ATP1A1 were considered the hub proteins. PALLD, THBS4, ATP1A1, NFASC, FKBP5, ECM2 and BCL2L1 were top six transcription factors (TFs) with the most downstream genes. The expression of 6 DEGs (MYH6, THBS4, BCL6, BLM, IPO7 and SERPINA3) were consistent with our integration analysis and GSE116250 validation results. CONCLUSIONS:The candidate DEGs and TFs may be related to the ICM process. This study provided novel perspective for understanding mechanism and exploiting new therapeutic means for ICM.

SUBMITTER: Dang H

PROVIDER: S-EPMC7336680 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Identification of candidate genes in ischemic cardiomyopathy by gene expression omnibus database.

Dang Haiming H Ye Yicong Y Zhao Xiliang X Zeng Yong Y

BMC cardiovascular disorders 20200706 1

<h4>Background</h4>Ischemic cardiomyopathy (ICM) is one of the most usual causes of death worldwide. This study aimed to find the candidate gene for ICM.<h4>Methods</h4>We studied differentially expressed genes (DEGs) in ICM compared to healthy control. According to these DEGs, we carried out the functional annotation, protein-protein interaction (PPI) network and transcriptional regulatory network constructions. The expression of selected candidate genes were confirmed using a published dataset ...[more]

PMID: 32631246

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Project description:Sepsis is a life-threatening condition in which an uncontrolled inflammatory host response is triggered. The exact pathogenesis of sepsis remains unclear. The aim of the present study was to identify key genes that may aid in the diagnosis and treatment of sepsis. mRNA expression data from blood samples taken from patients with sepsis and healthy individuals was downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) between the two groups were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein‑protein interaction (PPI) network construction, was performed to investigate the function of the identified DEGs. Furthermore, for validation of these results, the expression levels of several DEGs were analyzed by reverse transcription quantitative‑polymerase chain reaction (RT‑qPCR) in three patients with sepsis and three healthy blood samples to support the results obtained from the bioinformatics analysis. Receiver operating characteristic analyses were also used to analyze the diagnostic ability of the identified DEGs for sepsis. The results demonstrated that a total of 4,402 DEGs, including 1,960 upregulated and 2,442 downregulated genes, were identified between patients with sepsis and healthy individuals. KEGG pathway analysis revealed that 39 DEGs were significantly enriched in toll‑like receptor signaling pathways. The top 20 upregulated and downregulated DEGs were used to construct the PPI network. Hub genes with high degrees, including interleukin 1 receptor‑associated kinase 3 (IRAK3), S100 calcium‑binding protein (S100)A8, angiotensin II receptor‑associated protein (AGTRAP) and S100A9, were demonstrated to be associated sepsis. Furthermore, RT‑qPCR results demonstrated that IRAK3, adrenomedullin (ADM), arachidonate 5‑lipoxygenase (ALOX5), matrix metallopeptidase 9 (MMP9) and S100A8 were significantly upregulated, while ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1) was upregulated but not significantly, in blood samples from patients with sepsis compared with healthy individuals, which was consistent with bioinformatics analysis results. Therefore, AGTRAP, IRAK3, ADM, ALOX5, MMP9, S100A8 and ENTPD1 were identified to have potential diagnostic value in sepsis. In conclusion, dysregulated levels of the AGTRAP, IRAK3, ADM, ALOX5, MMP9, S100A8 and ENTPD1 genes may be involved in sepsis pathophysiology and may be utilized as potential diagnostic biomarkers or therapeutic targets.

Project description:BackgroundPatients with severe burns continue to display a high mortality rate during the initial shock period. The precise molecular mechanism underlying the change in host response during severe burn shock remains unknown. This study aimed to identify key genes leading to the change in host response during burn shock.MethodsThe GSE77791 dataset, which was utilized in a previous study that compared hydrocortisone administration to placebo (NaCl 0.9%) in the inflammatory reaction of severe burn shock, was downloaded from the Gene Expression Omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs). Functional enrichment analyses of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed. The protein-protein interaction (PPI) network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and then visualized in Cytoscape. In addition, important modules in this network were selected using the Molecular Complex Detection (MCODE) algorithm, and hub genes were identified in cytoHubba, a Cytoscape plugin.ResultsA total of 1059 DEGs (508 downregulated genes and 551 upregulated genes) were identified from the dataset. The DEGs enriched in GO terms and KEGG pathways were related to immune response. The PPI network contained 439 nodes and 2430 protein pairs. Finally, important modules and hub genes were identified using the different Cytoscape plugins. The key genes in burn shock were identified as arginase 1 (ARG1), cytoskeleton-associated protein (CKAP4), complement C3a receptor (C3AR1), neutrophil elastase (ELANE), gamma-glutamyl hydrolase (GGH), orosomucoid (ORM1), and quiescin sulfhydryl (QSOX1).ConclusionThe DEGs, functional terms and pathways, and hub genes identified in the present study can help shed light on the molecular mechanism underlying the changes in host response during burn shock and provide potential targets for early detection and treatment of burn shock.

Dataset Information

Identification of candidate genes in ischemic cardiomyopathy by gene expression omnibus database.

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Identification of candidate genes in ischemic cardiomyopathy by gene expression omnibus database.

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