Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network
Background: The mortality and disability rates of acute coronary syndrome (ACS) are quite high. Circular RNA (circRNA) is a competitive endogenous RNA (ceRNA) that plays an important role in the pathophysiology of ACS. Our goal is to screen circRNA-associated ceRNA networks for biomarker genes that...
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.1030510/full |
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| author | Hengliang Zhang Hengliang Zhang Daphne Merkus Daphne Merkus Pei Zhang Huifeng Zhang Yanyu Wang Laijing Du Lakshme Kottu |
| author_facet | Hengliang Zhang Hengliang Zhang Daphne Merkus Daphne Merkus Pei Zhang Huifeng Zhang Yanyu Wang Laijing Du Lakshme Kottu |
| author_sort | Hengliang Zhang |
| collection | DOAJ |
| description | Background: The mortality and disability rates of acute coronary syndrome (ACS) are quite high. Circular RNA (circRNA) is a competitive endogenous RNA (ceRNA) that plays an important role in the pathophysiology of ACS. Our goal is to screen circRNA-associated ceRNA networks for biomarker genes that are conducive to the diagnosis or exclusion of ACS, and better understand the pathology of the disease through the analysis of immune cells.Materials and methods: RNA expression profiles for circRNAs (GSE197137), miRNAs (GSE31568), and mRNAs (GSE95368) were obtained from the GEO database, and differentially expressed RNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs) were identified. The circRNA-miRNA and miRNA-mRNA regulatory links were retrieved from the CircInteractome database and TargetScan databases, respectively. As a final step, a regulatory network has been designed for ceRNA. On the basis of the ceRNA network, hub mRNAs were verified by quantitative RT-PCR. Hub genes were validated using a third independent mRNA database GSE60993, and ROC curves were used to evaluate their diagnostic values. The correlation between hub genes and immune cells associated with ACS was then analyzed using single sample gene set enrichment analysis (ssGSEA).Results: A total of 17 DEcircRNAs, 229 DEmiRNAs, and 27 DEmRNAs were found, as well as 52 circRNA-miRNA pairings and 10 miRNA-mRNA pairings predicted. The ceRNA regulatory network (circRNA-miRNA-mRNA) was constructed, which included 2 circRNA (hsa_circ_0082319 and hsa_circ_0005654), 4 miRNA (hsa-miR-583, hsa-miR-661, hsa-miR-671-5p, hsa-miR-578), and 5 mRNA (XPNPEP1, UCHL1, DBNL, GPC6, and RAD51). The qRT-PCR analysis result showed that the XPNPEP1, UCHL1, GPC6 and RAD51 genes had a significantly decreased expression in ACS patients. Based on ROC curve analysis, we found that XPNPEP1 has important significance in preventing ACS occurrence and excluding ACS diagnosis. ACS immune infiltration analysis revealed significant correlations between the other 3 hub genes (UCHL1, GPC6, RAD51) and the immune cells (Eosinophils, T folliculars, Type 2 T helper cells, and Imumature dendritic cells).Conclusion: Our study constructed a circRNA-related ceRNA network in ACS. The XPNPEP1 gene could be a protective gene biomarker for ACS. The UCHL1, GPC6 and RAD51 genes were significantly correlated with immune cells in ACS. |
| first_indexed | 2024-04-12T12:28:28Z |
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| id | doaj.art-34e90b97cc6e44a88c89534b89fa87e0 |
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| language | English |
| last_indexed | 2024-04-12T12:28:28Z |
| publishDate | 2022-10-01 |
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| spelling | doaj.art-34e90b97cc6e44a88c89534b89fa87e02022-12-22T03:33:06ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-10-011310.3389/fgene.2022.10305101030510Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory networkHengliang Zhang0Hengliang Zhang1Daphne Merkus2Daphne Merkus3Pei Zhang4Huifeng Zhang5Yanyu Wang6Laijing Du7Lakshme Kottu8The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, ChinaWalter-Brendel-Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-University München, Munich, GermanyWalter-Brendel-Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-University München, Munich, GermanyDepartment of Experimental Cardiology, Erasmus University Medical Center, Rotterdam, NetherlandsThe First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, ChinaThe First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, ChinaThe First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, ChinaThe First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, ChinaDepartment of Experimental Cardiology, Erasmus University Medical Center, Rotterdam, NetherlandsBackground: The mortality and disability rates of acute coronary syndrome (ACS) are quite high. Circular RNA (circRNA) is a competitive endogenous RNA (ceRNA) that plays an important role in the pathophysiology of ACS. Our goal is to screen circRNA-associated ceRNA networks for biomarker genes that are conducive to the diagnosis or exclusion of ACS, and better understand the pathology of the disease through the analysis of immune cells.Materials and methods: RNA expression profiles for circRNAs (GSE197137), miRNAs (GSE31568), and mRNAs (GSE95368) were obtained from the GEO database, and differentially expressed RNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs) were identified. The circRNA-miRNA and miRNA-mRNA regulatory links were retrieved from the CircInteractome database and TargetScan databases, respectively. As a final step, a regulatory network has been designed for ceRNA. On the basis of the ceRNA network, hub mRNAs were verified by quantitative RT-PCR. Hub genes were validated using a third independent mRNA database GSE60993, and ROC curves were used to evaluate their diagnostic values. The correlation between hub genes and immune cells associated with ACS was then analyzed using single sample gene set enrichment analysis (ssGSEA).Results: A total of 17 DEcircRNAs, 229 DEmiRNAs, and 27 DEmRNAs were found, as well as 52 circRNA-miRNA pairings and 10 miRNA-mRNA pairings predicted. The ceRNA regulatory network (circRNA-miRNA-mRNA) was constructed, which included 2 circRNA (hsa_circ_0082319 and hsa_circ_0005654), 4 miRNA (hsa-miR-583, hsa-miR-661, hsa-miR-671-5p, hsa-miR-578), and 5 mRNA (XPNPEP1, UCHL1, DBNL, GPC6, and RAD51). The qRT-PCR analysis result showed that the XPNPEP1, UCHL1, GPC6 and RAD51 genes had a significantly decreased expression in ACS patients. Based on ROC curve analysis, we found that XPNPEP1 has important significance in preventing ACS occurrence and excluding ACS diagnosis. ACS immune infiltration analysis revealed significant correlations between the other 3 hub genes (UCHL1, GPC6, RAD51) and the immune cells (Eosinophils, T folliculars, Type 2 T helper cells, and Imumature dendritic cells).Conclusion: Our study constructed a circRNA-related ceRNA network in ACS. The XPNPEP1 gene could be a protective gene biomarker for ACS. The UCHL1, GPC6 and RAD51 genes were significantly correlated with immune cells in ACS.https://www.frontiersin.org/articles/10.3389/fgene.2022.1030510/fullacute coronary syndromecircular RNAcompetitive endogenous RNAprotective gene biomarkersimmune cellsXPNPEP1 gene |
| spellingShingle | Hengliang Zhang Hengliang Zhang Daphne Merkus Daphne Merkus Pei Zhang Huifeng Zhang Yanyu Wang Laijing Du Lakshme Kottu Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network Frontiers in Genetics acute coronary syndrome circular RNA competitive endogenous RNA protective gene biomarkers immune cells XPNPEP1 gene |
| title | Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network |
| title_full | Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network |
| title_fullStr | Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network |
| title_full_unstemmed | Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network |
| title_short | Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network |
| title_sort | predicting protective gene biomarker of acute coronary syndrome by the circrna associated competitive endogenous rna regulatory network |
| topic | acute coronary syndrome circular RNA competitive endogenous RNA protective gene biomarkers immune cells XPNPEP1 gene |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.1030510/full |
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