Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics Analysis
Background: Acute ischemic stroke (AIS) is the second leading cause of death and the third leading cause of disability worldwide. Long noncoding RNAs (lncRNAs) are promising biomarkers for the early diagnosis of AIS and closely participate in the mechanism of stroke onset. However, studies focusing...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-01-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.779923/full |
| _version_ | 1819364777319727104 |
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| author | Xiuqi Chen Danhong Wu |
| author_facet | Xiuqi Chen Danhong Wu |
| author_sort | Xiuqi Chen |
| collection | DOAJ |
| description | Background: Acute ischemic stroke (AIS) is the second leading cause of death and the third leading cause of disability worldwide. Long noncoding RNAs (lncRNAs) are promising biomarkers for the early diagnosis of AIS and closely participate in the mechanism of stroke onset. However, studies focusing on lncRNAs functioning as microRNA (miRNA) sponges to regulate the mRNA expression are rare and superficial.Methods: In this study, we systematically analyzed the expression profiles of lncRNA, mRNA (GSE58294), and miRNA (GSE110993) from the GEO database. Gene ontology (GO) analysis was performed to reveal the functions of differentially expressed genes (DEGs), and we used weighted gene co-expression network analysis (WGCNA) to investigate the relationships between clinical features and expression profiles and the co-expression of miRNA and lncRNA. Finally, we constructed a lncRNA–miRNA–mRNA competing endogenous RNA (ceRNA) network with selected DEGs using bioinformatics methods and obtained ROC curves to assess the diagnostic efficacy of differentially expressed lncRNAs (DElncRNAs) and differentially expressed mRNAs (DEmRNAs) in our network. The GSE22255 dataset was used to confirm the diagnostic value of candidate genes.Results: In total, 199 DElncRNAs, 2068 DEmRNAs, and 96 differentially expressed miRNAs were detected. The GO analysis revealed that DEmRNAs primarily participate in neutrophil activation, neutrophil degranulation, vacuolar transport, and lysosomal transport. WGCNA screened out 16 lncRNAs and 195 mRNAs from DEGs, and only eight DElncRNAs maintained an area under the curve higher than 0.9. By investigating the relationships between lncRNAs and mRNAs, a ceRNA network containing three lncRNAs, three miRNAs, and seven mRNAs was constructed. GSE22255 confirmed that RP1-193H18.2 is more advantageous for diagnosing stroke, whereas no mRNA showed realistic diagnostic efficacy.Conclusion: The ceRNA network may broaden our understanding of AIS pathology, and the candidate lncRNA from the ceRNA network is assumed to be a promising therapeutic target and diagnostic biomarker for AIS. |
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| language | English |
| last_indexed | 2024-12-24T23:04:20Z |
| publishDate | 2022-01-01 |
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| series | Frontiers in Genetics |
| spelling | doaj.art-ded651ba5208470aaba4ad8adbebaaaf2022-12-21T16:35:03ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-01-011210.3389/fgene.2021.779923779923Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics AnalysisXiuqi ChenDanhong WuBackground: Acute ischemic stroke (AIS) is the second leading cause of death and the third leading cause of disability worldwide. Long noncoding RNAs (lncRNAs) are promising biomarkers for the early diagnosis of AIS and closely participate in the mechanism of stroke onset. However, studies focusing on lncRNAs functioning as microRNA (miRNA) sponges to regulate the mRNA expression are rare and superficial.Methods: In this study, we systematically analyzed the expression profiles of lncRNA, mRNA (GSE58294), and miRNA (GSE110993) from the GEO database. Gene ontology (GO) analysis was performed to reveal the functions of differentially expressed genes (DEGs), and we used weighted gene co-expression network analysis (WGCNA) to investigate the relationships between clinical features and expression profiles and the co-expression of miRNA and lncRNA. Finally, we constructed a lncRNA–miRNA–mRNA competing endogenous RNA (ceRNA) network with selected DEGs using bioinformatics methods and obtained ROC curves to assess the diagnostic efficacy of differentially expressed lncRNAs (DElncRNAs) and differentially expressed mRNAs (DEmRNAs) in our network. The GSE22255 dataset was used to confirm the diagnostic value of candidate genes.Results: In total, 199 DElncRNAs, 2068 DEmRNAs, and 96 differentially expressed miRNAs were detected. The GO analysis revealed that DEmRNAs primarily participate in neutrophil activation, neutrophil degranulation, vacuolar transport, and lysosomal transport. WGCNA screened out 16 lncRNAs and 195 mRNAs from DEGs, and only eight DElncRNAs maintained an area under the curve higher than 0.9. By investigating the relationships between lncRNAs and mRNAs, a ceRNA network containing three lncRNAs, three miRNAs, and seven mRNAs was constructed. GSE22255 confirmed that RP1-193H18.2 is more advantageous for diagnosing stroke, whereas no mRNA showed realistic diagnostic efficacy.Conclusion: The ceRNA network may broaden our understanding of AIS pathology, and the candidate lncRNA from the ceRNA network is assumed to be a promising therapeutic target and diagnostic biomarker for AIS.https://www.frontiersin.org/articles/10.3389/fgene.2021.779923/fullischemic strokelncRNAbioinformatics analysisceRNAbiomarkers |
| spellingShingle | Xiuqi Chen Danhong Wu Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics Analysis Frontiers in Genetics ischemic stroke lncRNA bioinformatics analysis ceRNA biomarkers |
| title | Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics Analysis |
| title_full | Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics Analysis |
| title_fullStr | Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics Analysis |
| title_full_unstemmed | Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics Analysis |
| title_short | Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics Analysis |
| title_sort | comprehensive analysis of hub genes associated with competing endogenous rna networks in stroke using bioinformatics analysis |
| topic | ischemic stroke lncRNA bioinformatics analysis ceRNA biomarkers |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2021.779923/full |
| work_keys_str_mv | AT xiuqichen comprehensiveanalysisofhubgenesassociatedwithcompetingendogenousrnanetworksinstrokeusingbioinformaticsanalysis AT danhongwu comprehensiveanalysisofhubgenesassociatedwithcompetingendogenousrnanetworksinstrokeusingbioinformaticsanalysis |