Identification of key microRNAs in the carotid arteries of ApoE−/− mice exposed to disturbed flow
Abstract Background Atherosclerosis (AS) is one of the main causes of cardiovascular disease. AS plaques often occur in blood vessels with oscillatory blood flow and their formation can be regulated by microRNAs (miRNAs). The aim of this study is to identify the key miRNAs and molecular pathways inv...
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BMC
2019-11-01
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Series: | Hereditas |
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Online Access: | http://link.springer.com/article/10.1186/s41065-019-0112-x |
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author | Xinzhou Wang Shuibo Gao Liping Dai Zhentao Wang Hong Wu |
author_facet | Xinzhou Wang Shuibo Gao Liping Dai Zhentao Wang Hong Wu |
author_sort | Xinzhou Wang |
collection | DOAJ |
description | Abstract Background Atherosclerosis (AS) is one of the main causes of cardiovascular disease. AS plaques often occur in blood vessels with oscillatory blood flow and their formation can be regulated by microRNAs (miRNAs). The aim of this study is to identify the key miRNAs and molecular pathways involved in this pathological process. Methods In this study, gene chip data obtained from the GEO database was analyzed using the LIMMA package to find differentially expressed miRNAs (DE miRNAs) in the carotid arteries of ApoE−/− mice exposed to different blood flow rates. Predicted targets of the DE miRNAs were identified using the TargetScan, miRDB, and DIANA databases respectively, and the potential target genes (PTGs) were found by analyzing the common results of three databases. The DAVID database was used to enrich the PTGs based on gene ontology (GO) and pathway (Kyoto Encyclopedia of Genes and Genomes, KEGG), and the STRING database was used to uncover any protein-protein interactions (PPI) of the PTGs. Results The networks of the DE miRNAs-PTGs, Pathway-PTGs-DE miRNAs, and PTGs PPI, were constructed using Cytoscape, and 11 up-regulated and 13 down-regulated DE miRNAs and 1479 PTGs were found. GO results showed that PTGs were significantly enriched in functions such as transcriptional regulation and DNA binding. KEGG results showed that PTGs were significantly enriched in inflammation-related mitogen-activated protein kinase (MAPK) and AS-related FOXO pathways. The PPI network revealed some key target genes in the PTGs. Conclusions The analysis of key miRNAs and molecular pathways that regulate the formation of AS plaques induced by oscillatory blood flow will provide new ideas for AS treatment. |
first_indexed | 2024-04-13T04:44:01Z |
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institution | Directory Open Access Journal |
issn | 1601-5223 |
language | English |
last_indexed | 2024-04-13T04:44:01Z |
publishDate | 2019-11-01 |
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series | Hereditas |
spelling | doaj.art-220d226bdbf8411b81c681107a96a5e52022-12-22T03:01:55ZengBMCHereditas1601-52232019-11-01156111010.1186/s41065-019-0112-xIdentification of key microRNAs in the carotid arteries of ApoE−/− mice exposed to disturbed flowXinzhou Wang0Shuibo Gao1Liping Dai2Zhentao Wang3Hong Wu4Laboratory of Cell Imaging, Henan University of Chinese MedicineLaboratory of Cell Imaging, Henan University of Chinese MedicineSchool of Pharmacy, Henan University of Chinese MedicineInstitute of Cardiovascular Disease, Henan University of Chinese MedicineLaboratory of Cell Imaging, Henan University of Chinese MedicineAbstract Background Atherosclerosis (AS) is one of the main causes of cardiovascular disease. AS plaques often occur in blood vessels with oscillatory blood flow and their formation can be regulated by microRNAs (miRNAs). The aim of this study is to identify the key miRNAs and molecular pathways involved in this pathological process. Methods In this study, gene chip data obtained from the GEO database was analyzed using the LIMMA package to find differentially expressed miRNAs (DE miRNAs) in the carotid arteries of ApoE−/− mice exposed to different blood flow rates. Predicted targets of the DE miRNAs were identified using the TargetScan, miRDB, and DIANA databases respectively, and the potential target genes (PTGs) were found by analyzing the common results of three databases. The DAVID database was used to enrich the PTGs based on gene ontology (GO) and pathway (Kyoto Encyclopedia of Genes and Genomes, KEGG), and the STRING database was used to uncover any protein-protein interactions (PPI) of the PTGs. Results The networks of the DE miRNAs-PTGs, Pathway-PTGs-DE miRNAs, and PTGs PPI, were constructed using Cytoscape, and 11 up-regulated and 13 down-regulated DE miRNAs and 1479 PTGs were found. GO results showed that PTGs were significantly enriched in functions such as transcriptional regulation and DNA binding. KEGG results showed that PTGs were significantly enriched in inflammation-related mitogen-activated protein kinase (MAPK) and AS-related FOXO pathways. The PPI network revealed some key target genes in the PTGs. Conclusions The analysis of key miRNAs and molecular pathways that regulate the formation of AS plaques induced by oscillatory blood flow will provide new ideas for AS treatment.http://link.springer.com/article/10.1186/s41065-019-0112-xAtherosclerosisOscillatory blood flowmicroRNAMicroarray analysisBioinformatics |
spellingShingle | Xinzhou Wang Shuibo Gao Liping Dai Zhentao Wang Hong Wu Identification of key microRNAs in the carotid arteries of ApoE−/− mice exposed to disturbed flow Hereditas Atherosclerosis Oscillatory blood flow microRNA Microarray analysis Bioinformatics |
title | Identification of key microRNAs in the carotid arteries of ApoE−/− mice exposed to disturbed flow |
title_full | Identification of key microRNAs in the carotid arteries of ApoE−/− mice exposed to disturbed flow |
title_fullStr | Identification of key microRNAs in the carotid arteries of ApoE−/− mice exposed to disturbed flow |
title_full_unstemmed | Identification of key microRNAs in the carotid arteries of ApoE−/− mice exposed to disturbed flow |
title_short | Identification of key microRNAs in the carotid arteries of ApoE−/− mice exposed to disturbed flow |
title_sort | identification of key micrornas in the carotid arteries of apoe mice exposed to disturbed flow |
topic | Atherosclerosis Oscillatory blood flow microRNA Microarray analysis Bioinformatics |
url | http://link.springer.com/article/10.1186/s41065-019-0112-x |
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