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Expression profile and bioinformatics analysis of circular RNAs in acute ischemic stroke in a South Chinese Han population
Recent studies have found that circular RNAs (circRNAs) play crucial roles not only in the normal growth and the development of different tissues and organs but also in the pathogenesis and progression of various disorders. However, the expression patterns and the function of circRNAs in acute ische...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311391/ https://www.ncbi.nlm.nih.gov/pubmed/32576868 http://dx.doi.org/10.1038/s41598-020-66990-y |
Sumario: | Recent studies have found that circular RNAs (circRNAs) play crucial roles not only in the normal growth and the development of different tissues and organs but also in the pathogenesis and progression of various disorders. However, the expression patterns and the function of circRNAs in acute ischemic stroke (AIS) in the South Chinese Han population are unclear. In the present study, RNA sequencing (RNA-seq) data was generated from 3 AIS patients and 3 healthy controls. The circRNAs were detected and identified by CIRI2 and Find_circ software. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analyses were used to detect the expression of circRNAs. Meanwhile, the potential diagnostic value of the selected circRNAs for AIS was assessed by generating receiver operating characteristic (ROC) curve with area under curve (AUC). The bioinformatic analysis of the host genes of differentially expressed (DE) circRNAs was performed by gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, KOBAS for pathway analysis and regulatory network analysis. miRNA-circRNA and miRNA-mRNA interactions were predicted by using TargetScan, miRanda and starBase. CircRNA-miRNA-mRNA interaction networks were created with Cytoscape. Our result showed that there were 2270 DE circRNAs between AIS patients and healthy controls. Among them, 659 were found upregulated and 1611 were downregulated. Bioinformatic analysis showed that the DE circRNAs were related to the following biological processes: endocytosis, energy metabolism, apoptosis, FoxO signaling pathway, platelet activation, neurotrophin signaling pathway and VEGF signaling pathway, which may be associated with the pathological of AIS. Three randomly selected circRNAs were successfully validated by qRT‐PCR. The results show that hsa_circ_0005548 was significantly upregulated, while hsa_circ_0000607 and hsa_circ_0002465 were significantly downregulated in AIS. Furthermore, the AUC values for hsa_circ_005548, hsa_circ_0000607 and hsa_circ_0002465 were 0.51, 0.75 and 0.69, respectively, suggesting that hsa_circ_0000607 and hsa_circ_0002465 could be potential biomarkers for AIS. In addition, Bcl2 was predicted to be a direct target of miR-337-3p, and hsa_circRNA_0000607 was predicted to act as a sponge for miR-337-3p. Thus, hsa_circ_0000607 may be involved in AIS by regulating the miR-337-3p/Bcl2 axis. Collectively, our findings indicate that numerous dysregulated circRNAs may play pivotal functional roles in AIS and hsa_circ_0000607 may play a crucial role in the pathogenesis and progression of AIS by regulating the miR-337-3p/Bcl2 axis. |
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