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Identifying key genes associated with acute myocardial infarction

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 heterogenei...

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Detalles Bibliográficos
Autores principales: Cheng, Ming, An, Shoukuan, Li, Junquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662349/
https://www.ncbi.nlm.nih.gov/pubmed/29049183
http://dx.doi.org/10.1097/MD.0000000000007741
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author Cheng, Ming
An, Shoukuan
Li, Junquan
author_facet Cheng, Ming
An, Shoukuan
Li, Junquan
author_sort Cheng, Ming
collection PubMed
description 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.
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spelling pubmed-56623492017-11-21 Identifying key genes associated with acute myocardial infarction Cheng, Ming An, Shoukuan Li, Junquan Medicine (Baltimore) 5700 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. Wolters Kluwer Health 2017-10-20 /pmc/articles/PMC5662349/ /pubmed/29049183 http://dx.doi.org/10.1097/MD.0000000000007741 Text en Copyright © 2017 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle 5700
Cheng, Ming
An, Shoukuan
Li, Junquan
Identifying key genes associated with acute myocardial infarction
title Identifying key genes associated with acute myocardial infarction
title_full Identifying key genes associated with acute myocardial infarction
title_fullStr Identifying key genes associated with acute myocardial infarction
title_full_unstemmed Identifying key genes associated with acute myocardial infarction
title_short Identifying key genes associated with acute myocardial infarction
title_sort identifying key genes associated with acute myocardial infarction
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662349/
https://www.ncbi.nlm.nih.gov/pubmed/29049183
http://dx.doi.org/10.1097/MD.0000000000007741
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