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The analysis of microRNA expression profiling for coronary artery disease

Authors :
Qinchuan Li
Kefei Li
Jan Torzewski
Zhongmin Liu
Tao Zhang
Wulf Ito
Jian-Hua Guo
Huimin Fan
Source :
Cardiology. 127(1)
Publication Year :
2013

Abstract

Objectives: To investigate the underlying molecular mechanisms of coronary artery disease (CAD) using microarray expression profiles. Methods: The microRNA (miRNA) expression-profiling dataset GSE28858 was obtained from the Gene Expression Omnibus database, including 24 samples from 12 patients with CAD and 12 age- and sex-matched healthy controls. Differentially expressed miRNAs were identified with false discovery rate (FDR) = 1% by the SAM (Significant Analysis of Microarray) algorithm. The target genes of selected differentials expressed miRNAs that were not only related to CAD, but were also in two databases (TargetScan, miRanda). Then, the interactive objects of selected target genes were predicted using the STRING database to construct an interaction network (confidence score = 0.4). These target genes and interactive objects were put into the KEGG (Kyoto Encyclopedia of Genes and Genomes) database, and the significant signaling pathway was obtained by hypergeometric function enrichment analysis (p < 0.05). Results: MiRNA-526b was the only differentially expressed miRNA that was upregulated in patients with CAD (FDR = 1%). Toll-like receptor 4 (TLR4) was the target gene of miRNA-526b that occurred with the highest frequency. The objects that interacted with TLR4 were predicted using the STRING database and the interaction network was obtained. The vascular endothelial growth factor (VEGF) signaling pathway was the only selected significant pathway related with CAD in the interaction network (p < 0.05). Conclusion: The miRNA-526b is significantly upregulated in patients with CAD and the target gene of miRNA-526b participates in the VEGF signaling pathway. Whether or not the miRNA-526b can be used as a biomarker remains to be elucidated in a larger prospective study.

Details

ISSN :
14219751
Volume :
127
Issue :
1
Database :
OpenAIRE
Journal :
Cardiology
Accession number :
edsair.doi.dedup.....eb8fd35c6e2953c1351dade7be844ce1