Identifying key genes associated with acute myocardial infarction. Issue 42 (October 2017)
- Record Type:
- Journal Article
- Title:
- Identifying key genes associated with acute myocardial infarction. Issue 42 (October 2017)
- Main Title:
- Identifying key genes associated with acute myocardial infarction
- Authors:
- Cheng, Ming
An, Shoukuan
Li, Junquan - Other Names:
- Lawen. Alfons section editor.
- Abstract:
- Abstract: Background: This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. Methods: Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P < .05 was used as the cutoff for a differentially expressed gene (DEG). The expression data matrices of DEGs were imported in ReactomeFIViz to construct a gene functional interaction (FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes. Result: A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21–5p and hsa-miR-30c-5p were obviously decreased in AMI. Conclusion: A total of 41Abstract: Background: This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. Methods: Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P < .05 was used as the cutoff for a differentially expressed gene (DEG). The expression data matrices of DEGs were imported in ReactomeFIViz to construct a gene functional interaction (FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes. Result: A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21–5p and hsa-miR-30c-5p were obviously decreased in AMI. Conclusion: A total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs. … (more)
- Is Part Of:
- Medicine. Volume 96:Issue 42(2017)
- Journal:
- Medicine
- Issue:
- Volume 96:Issue 42(2017)
- Issue Display:
- Volume 96, Issue 42 (2017)
- Year:
- 2017
- Volume:
- 96
- Issue:
- 42
- Issue Sort Value:
- 2017-0096-0042-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-10
- Subjects:
- acute myocardial infarction -- differentially expressed genes -- gene functional interaction -- pathway enrichment analysis -- transcription factor-miRNA-gene network
Medicine -- Periodicals
Medicine -- Periodicals
Médecine -- Périodiques
Geneeskunde
Medicine
Periodicals
Periodicals
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http://journals.lww.com ↗ - DOI:
- 10.1097/MD.0000000000007741 ↗
- Languages:
- English
- ISSNs:
- 0025-7974
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