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Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis

Myocardial infarction (MI) is a heart disease with high morbidity and mortality rates, thus it is critical to identify genes that serve roles during its pathogenesis. The objective of the present study was to identify potentially relevant genes during the progression of the disease. Blood samples fr...

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Autores principales: Zhao, Qiang, Wu, Ke, Li, Nannan, Li, Zhengmei, Jin, Fenglin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774508/
https://www.ncbi.nlm.nih.gov/pubmed/29399125
http://dx.doi.org/10.3892/etm.2017.5580
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author Zhao, Qiang
Wu, Ke
Li, Nannan
Li, Zhengmei
Jin, Fenglin
author_facet Zhao, Qiang
Wu, Ke
Li, Nannan
Li, Zhengmei
Jin, Fenglin
author_sort Zhao, Qiang
collection PubMed
description Myocardial infarction (MI) is a heart disease with high morbidity and mortality rates, thus it is critical to identify genes that serve roles during its pathogenesis. The objective of the present study was to identify potentially relevant genes during the progression of the disease. Blood samples from patients with MI and normal controls (n=3/group) were obtained, the RNA was extracted and cDNA libraries were established. RNA sequencing (RNA-seq) was performed on a HiSeq 2500 platform and fragments per kilobase of exon per million fragments mapped was utilized to calculate the gene expression value following preprocessing of the RNA-seq data. Electronic validation of several identified differentially expressed genes (DEGs) was performed on a Gene Expression Omnibus (GEO) dataset GSE59867 (390 cases and 46 healthy controls). Functional enrichment and protein-protein interaction network analysis was conducted for DEGs. A total of 977 DEGs, including 817 upregulated and 160 downregulated genes were identified in patients with MI. These DEGs were significantly enriched for ‘positive regulation of the immune system process,’ ‘inflammatory response,’ ‘regulation of I-kappaB-kinase/NF-kappaB signaling’ and ‘TNF signaling pathway’. A protein-protein interaction network of the top 40 DEGs was used to identify high degree genes, including interferon induced protein with tetratricopeptide repeats 3 (IFIT3), MX dynamin like GTPase 1 (MX1), major histocompatibility complex, class II, DQ α1 (HLA-DQA1), RAR related orphan receptor A (RORA), prostaglandin D2 synthase (PTGDS), cysteine rich protein 2 (CRIP2), collagen type VI α 2 chain (COL6A2) and S100 calcium binding protein P (S100P). The results of validation in the GEO dataset were consistent with the sequencing analysis. A total of eight genes, including IFIT3, MX1, HLA-DQA1, RORA, PTGDS, CRIP2, COL6A2 and S100P may therefore be considered as potentially relevant genes in the pathology of MI.
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spelling pubmed-57745082018-02-02 Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis Zhao, Qiang Wu, Ke Li, Nannan Li, Zhengmei Jin, Fenglin Exp Ther Med Articles Myocardial infarction (MI) is a heart disease with high morbidity and mortality rates, thus it is critical to identify genes that serve roles during its pathogenesis. The objective of the present study was to identify potentially relevant genes during the progression of the disease. Blood samples from patients with MI and normal controls (n=3/group) were obtained, the RNA was extracted and cDNA libraries were established. RNA sequencing (RNA-seq) was performed on a HiSeq 2500 platform and fragments per kilobase of exon per million fragments mapped was utilized to calculate the gene expression value following preprocessing of the RNA-seq data. Electronic validation of several identified differentially expressed genes (DEGs) was performed on a Gene Expression Omnibus (GEO) dataset GSE59867 (390 cases and 46 healthy controls). Functional enrichment and protein-protein interaction network analysis was conducted for DEGs. A total of 977 DEGs, including 817 upregulated and 160 downregulated genes were identified in patients with MI. These DEGs were significantly enriched for ‘positive regulation of the immune system process,’ ‘inflammatory response,’ ‘regulation of I-kappaB-kinase/NF-kappaB signaling’ and ‘TNF signaling pathway’. A protein-protein interaction network of the top 40 DEGs was used to identify high degree genes, including interferon induced protein with tetratricopeptide repeats 3 (IFIT3), MX dynamin like GTPase 1 (MX1), major histocompatibility complex, class II, DQ α1 (HLA-DQA1), RAR related orphan receptor A (RORA), prostaglandin D2 synthase (PTGDS), cysteine rich protein 2 (CRIP2), collagen type VI α 2 chain (COL6A2) and S100 calcium binding protein P (S100P). The results of validation in the GEO dataset were consistent with the sequencing analysis. A total of eight genes, including IFIT3, MX1, HLA-DQA1, RORA, PTGDS, CRIP2, COL6A2 and S100P may therefore be considered as potentially relevant genes in the pathology of MI. D.A. Spandidos 2018-02 2017-11-28 /pmc/articles/PMC5774508/ /pubmed/29399125 http://dx.doi.org/10.3892/etm.2017.5580 Text en Copyright: © Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Zhao, Qiang
Wu, Ke
Li, Nannan
Li, Zhengmei
Jin, Fenglin
Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis
title Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis
title_full Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis
title_fullStr Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis
title_full_unstemmed Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis
title_short Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis
title_sort identification of potentially relevant genes for myocardial infarction using rna sequencing data analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774508/
https://www.ncbi.nlm.nih.gov/pubmed/29399125
http://dx.doi.org/10.3892/etm.2017.5580
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