Cargando…
Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction
BACKGROUND: ST-elevation myocardial infarction (STEMI) is a myocardial infarction (MI) with ST-segment exaltation of electrocardiogram (ECG) caused by vascular occlusion of the epicardium. However, the diagnostic markers of STEMI remain little. METHODS: STEMI raw microarray data are acquired from th...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9010175/ https://www.ncbi.nlm.nih.gov/pubmed/35475279 http://dx.doi.org/10.1155/2022/7343412 |
_version_ | 1784687427037691904 |
---|---|
author | Liang, Yingliang Wang, Wandang Huang, Qiufang Chen, Hui |
author_facet | Liang, Yingliang Wang, Wandang Huang, Qiufang Chen, Hui |
author_sort | Liang, Yingliang |
collection | PubMed |
description | BACKGROUND: ST-elevation myocardial infarction (STEMI) is a myocardial infarction (MI) with ST-segment exaltation of electrocardiogram (ECG) caused by vascular occlusion of the epicardium. However, the diagnostic markers of STEMI remain little. METHODS: STEMI raw microarray data are acquired from the Gene Expression Omnibus (GEO) database. Based on GSE60993 and GSE61144, differentially expressed genes (DEGs) are verified via R software, and key modules associated with pathological state of STEMI are verified by weighted correlation network analysis (WGCNA). Take the intersection gene of key module and DEGs to perform the pathway enrichment analyses by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Construct the protein-protein interaction (PPI) network by Cytoscape. Then, select and identify the diagnostic biomarkers of STEMI by least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Finally, assess the infiltration of immune cells of STEMI by CIBERSORT and analyze the correlation between diagnostic markers and infiltrating immune cells. RESULTS: We get 710 DEGs in the STEMI group and 376 genes associated with STEMI in blue module. 92 intersection genes were concentrated in 30 GO terms and 2 KEGG pathways. 28 hub genes involved in the development of STEMI. Moreover, upregulated ALOX5AP (AUC = 1.00) and BST1 (AUC = 1.00) are confirmed as diagnostic markers of STEMI. CD8+T cells, regulatory T (Treg) cells, resting natural killer (NK) cells, M0 macrophages, resting mast cells, and neutrophils are related to the procession of STEMI. Moreover, ALOX5AP and BST1 are positively related to resting NK cells, M0 macrophages, and neutrophils, while ALOX5AP and BST1 are negatively related to CD8+ T cells, Treg cells, and resting mast cells. CONCLUSION: ALOX5AP and BST1 may be the diagnostic markers of STEMI. Immune cell infiltration plays a key role in the development of STEMI. |
format | Online Article Text |
id | pubmed-9010175 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-90101752022-04-25 Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction Liang, Yingliang Wang, Wandang Huang, Qiufang Chen, Hui Contrast Media Mol Imaging Research Article BACKGROUND: ST-elevation myocardial infarction (STEMI) is a myocardial infarction (MI) with ST-segment exaltation of electrocardiogram (ECG) caused by vascular occlusion of the epicardium. However, the diagnostic markers of STEMI remain little. METHODS: STEMI raw microarray data are acquired from the Gene Expression Omnibus (GEO) database. Based on GSE60993 and GSE61144, differentially expressed genes (DEGs) are verified via R software, and key modules associated with pathological state of STEMI are verified by weighted correlation network analysis (WGCNA). Take the intersection gene of key module and DEGs to perform the pathway enrichment analyses by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Construct the protein-protein interaction (PPI) network by Cytoscape. Then, select and identify the diagnostic biomarkers of STEMI by least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Finally, assess the infiltration of immune cells of STEMI by CIBERSORT and analyze the correlation between diagnostic markers and infiltrating immune cells. RESULTS: We get 710 DEGs in the STEMI group and 376 genes associated with STEMI in blue module. 92 intersection genes were concentrated in 30 GO terms and 2 KEGG pathways. 28 hub genes involved in the development of STEMI. Moreover, upregulated ALOX5AP (AUC = 1.00) and BST1 (AUC = 1.00) are confirmed as diagnostic markers of STEMI. CD8+T cells, regulatory T (Treg) cells, resting natural killer (NK) cells, M0 macrophages, resting mast cells, and neutrophils are related to the procession of STEMI. Moreover, ALOX5AP and BST1 are positively related to resting NK cells, M0 macrophages, and neutrophils, while ALOX5AP and BST1 are negatively related to CD8+ T cells, Treg cells, and resting mast cells. CONCLUSION: ALOX5AP and BST1 may be the diagnostic markers of STEMI. Immune cell infiltration plays a key role in the development of STEMI. Hindawi 2022-04-07 /pmc/articles/PMC9010175/ /pubmed/35475279 http://dx.doi.org/10.1155/2022/7343412 Text en Copyright © 2022 Yingliang Liang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liang, Yingliang Wang, Wandang Huang, Qiufang Chen, Hui Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction |
title | Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction |
title_full | Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction |
title_fullStr | Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction |
title_full_unstemmed | Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction |
title_short | Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction |
title_sort | integrated multichip analysis and wgcna identify potential diagnostic markers in the pathogenesis of st-elevation myocardial infarction |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9010175/ https://www.ncbi.nlm.nih.gov/pubmed/35475279 http://dx.doi.org/10.1155/2022/7343412 |
work_keys_str_mv | AT liangyingliang integratedmultichipanalysisandwgcnaidentifypotentialdiagnosticmarkersinthepathogenesisofstelevationmyocardialinfarction AT wangwandang integratedmultichipanalysisandwgcnaidentifypotentialdiagnosticmarkersinthepathogenesisofstelevationmyocardialinfarction AT huangqiufang integratedmultichipanalysisandwgcnaidentifypotentialdiagnosticmarkersinthepathogenesisofstelevationmyocardialinfarction AT chenhui integratedmultichipanalysisandwgcnaidentifypotentialdiagnosticmarkersinthepathogenesisofstelevationmyocardialinfarction |