Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction

Acute myocardial infarction (AMI) is the most severe manifestation of coronary artery disease. Considerable efforts have been made to elucidate its etiology and pathology, but the genetic factors that play a decisive role in the occurrence of AMI are still unclear. To determine the molecular mechani...

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Autores principales:	Wei Dongmei, Li Rui, Si Tao, He Hankang, Wu Wei
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	acute myocardial infarction bioinformatics geo database Crystallography QD901-999
Acceso en línea:	https://doaj.org/article/665231d1d1304d2da719b8fab6ec5c04
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spelling	oai:doaj.org-article:665231d1d1304d2da719b8fab6ec5c042021-12-05T14:11:02ZScreening and bioinformatics analysis of key biomarkers in acute myocardial infarction2195-472010.1515/pteridines-2020-0031https://doaj.org/article/665231d1d1304d2da719b8fab6ec5c042021-10-01T00:00:00Zhttps://doi.org/10.1515/pteridines-2020-0031https://doaj.org/toc/2195-4720Acute myocardial infarction (AMI) is the most severe manifestation of coronary artery disease. Considerable efforts have been made to elucidate its etiology and pathology, but the genetic factors that play a decisive role in the occurrence of AMI are still unclear. To determine the molecular mechanism of the occurrence and development of AMI, four microarray datasets, namely, GSE29111, GSE48060, GSE66360, and GSE97320, were downloaded from the Gene Expression Omnibus (GEO) database. We analyzed the four GEO datasets to obtain the differential expression genes (DEGs) of patients with AMI and patients with non-AMI and then performed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Protein-protein interaction (PPI) network analysis. A total of 41 DEGs were identified, including 39 upregulated genes and 2 downregulated genes. The enriched functions and pathways of the DEGs included the inflammatory response, neutrophil chemotaxis, immune response, extracellular space, positive regulation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) transcription factor activity, response to lipopolysaccharide, receptor for advanced glycation end products (RAGE) receptor binding, innate immune response, defense response to bacterium, and receptor activity. The cytoHubba plug-in in Cytoscape was used to select the most significant hub gene from the PPI network. Ten hub genes were identified, and GO enrichment analysis revealed that these genes were mainly enriched in inflammatory response, neutrophil chemotaxis, immune response, RAGE receptor binding, and extracellular region. In conclusion, this study integrated four datasets and used bioinformatics methods to analyze the gene chips of AMI samples and control samples and identified DEGs that may be involved in the occurrence and development of AMI. The study provides reliable molecular biomarkers for AMI screening, diagnosis, and prognosis.Wei DongmeiLi RuiSi TaoHe HankangWu WeiDe Gruyterarticleacute myocardial infarctionbioinformaticsgeo databaseCrystallographyQD901-999ENPteridines, Vol 32, Iss 1, Pp 79-92 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	acute myocardial infarction bioinformatics geo database Crystallography QD901-999
spellingShingle	acute myocardial infarction bioinformatics geo database Crystallography QD901-999 Wei Dongmei Li Rui Si Tao He Hankang Wu Wei Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction
description	Acute myocardial infarction (AMI) is the most severe manifestation of coronary artery disease. Considerable efforts have been made to elucidate its etiology and pathology, but the genetic factors that play a decisive role in the occurrence of AMI are still unclear. To determine the molecular mechanism of the occurrence and development of AMI, four microarray datasets, namely, GSE29111, GSE48060, GSE66360, and GSE97320, were downloaded from the Gene Expression Omnibus (GEO) database. We analyzed the four GEO datasets to obtain the differential expression genes (DEGs) of patients with AMI and patients with non-AMI and then performed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Protein-protein interaction (PPI) network analysis. A total of 41 DEGs were identified, including 39 upregulated genes and 2 downregulated genes. The enriched functions and pathways of the DEGs included the inflammatory response, neutrophil chemotaxis, immune response, extracellular space, positive regulation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) transcription factor activity, response to lipopolysaccharide, receptor for advanced glycation end products (RAGE) receptor binding, innate immune response, defense response to bacterium, and receptor activity. The cytoHubba plug-in in Cytoscape was used to select the most significant hub gene from the PPI network. Ten hub genes were identified, and GO enrichment analysis revealed that these genes were mainly enriched in inflammatory response, neutrophil chemotaxis, immune response, RAGE receptor binding, and extracellular region. In conclusion, this study integrated four datasets and used bioinformatics methods to analyze the gene chips of AMI samples and control samples and identified DEGs that may be involved in the occurrence and development of AMI. The study provides reliable molecular biomarkers for AMI screening, diagnosis, and prognosis.
format	article
author	Wei Dongmei Li Rui Si Tao He Hankang Wu Wei
author_facet	Wei Dongmei Li Rui Si Tao He Hankang Wu Wei
author_sort	Wei Dongmei
title	Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction
title_short	Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction
title_full	Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction
title_fullStr	Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction
title_full_unstemmed	Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction
title_sort	screening and bioinformatics analysis of key biomarkers in acute myocardial infarction
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/665231d1d1304d2da719b8fab6ec5c04
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Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction

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