Journal of International Medical Research · 2020 · 11 citations · 30 references
Life SciencesBioinformaticsMolecular BiologyGene ExpressionGene Expression AnalysisPathway AnalysisDifferential Expression AnalysisDifferential Gene Expression AnalysisDisease Network BiologyGene Expression ProfilingMolecular Interaction NetworksProtein-protein Interaction AnalysisAtherosclerosis Molecular MechanismsAtherosclerotic ProgressionBiomarkersFunctional AnnotationGene Expression BiomarkersGene Expression Network AnalysisPathway-based Biomarker DiscoveryProtein-protein Interaction Network Analysis
Objective To use bioinformatics tools to screen for gene biomarkers from monocytes, which play an important role in the pathogenesis of atherosclerosis. Methods Two expression profiling datasets (GSE27034 and GSE10195) were obtained from the Gene Expression Omnibus dataset and the differentially expressed genes (DEGs) between atherosclerotic human peripheral blood mononuclear cells (PBMC) samples and control subjects were screened using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted for the DEGs. STRING and MCODE plug-in of Cytoscape were used for constructing a protein–protein interaction network and analysing hub genes. Results The two datasets had 237 DEGs in common between non-atherosclerotic- and atherosclerotic PBMC samples. Functional annotation demonstrated that these DEGs were mainly enriched in protein binding, positive regulation of transcription from RNA polymerase II promoter, nucleus and viral carcinogenesis. Five hub genes, FBXL4, UBOX5, KBTBD6, FZR1 and FBXO2, were identified. Conclusion This present bioinformatics analysis identified that the FBXL4, UBOX5, KBTBD6 and FBXO21 genes might play vital roles in the pathogenesis of atherosclerosis. These four genes might represent new biomarkers for the diagnosis and treatment of atherosclerosis.
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