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Bioinformatics analysis to identify potential biomarkers and therapeutic targets for ST-segment–elevation myocardial infarction-related ischemic stroke
BACKGROUND: Acute myocardial infarction (AMI) is one of the major causes of mortality and disability worldwide, and ischemic stroke (IS) is a serious complication after AMI. In particular, patients with ST-segment–elevation myocardial infarction (STEMI) are more susceptible to IS. However, the inter...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403764/ https://www.ncbi.nlm.nih.gov/pubmed/36034287 http://dx.doi.org/10.3389/fneur.2022.894289 |
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author | Feng, Shuo Li, Rui Zhou, Qingqing Qu, Fengling Hu, Wei Liu, Xinfeng |
author_facet | Feng, Shuo Li, Rui Zhou, Qingqing Qu, Fengling Hu, Wei Liu, Xinfeng |
author_sort | Feng, Shuo |
collection | PubMed |
description | BACKGROUND: Acute myocardial infarction (AMI) is one of the major causes of mortality and disability worldwide, and ischemic stroke (IS) is a serious complication after AMI. In particular, patients with ST-segment–elevation myocardial infarction (STEMI) are more susceptible to IS. However, the interrelationship between the two disease mechanisms is not clear. Using bioinformatics tools, we investigated genes commonly expressed in patients with STEMI and IS to explore the relationship between these diseases, with the aim of uncovering the underlying biomarkers and therapeutic targets for STEMI-associated IS. METHODS: Differentially expressed genes (DEGs) related to STEMI and IS were identified through bioinformatics analysis of the Gene Expression Omnibus (GEO) datasets GSE60993 and GSE16561, respectively. Thereafter, we assessed protein-protein interaction networks, gene ontology term annotations, and pathway enrichment for DEGs using various prediction and network analysis methods. The predicted miRNAs targeting the co-expressed STEMI- and IS-related DEGs were also evaluated. RESULTS: We identified 210 and 29 DEGs in GSE60993 and GSE16561, respectively. CD8A, TLR2, TLR4, S100A12, and TREM1 were associated with STEMI, while the hubgenes, IL7R, CCR7, FCGR3B, CD79A, and ITK were implicated in IS. In addition, binding of the transcripts of the co-expressed DEGs MMP9, ARG1, CA4, CRISPLD2, S100A12, and GZMK to their corresponding predicted miRNAs, especially miR-654-5p, may be associated with STEMI-related IS. CONCLUSIONS: STEMI and IS are related and MMP9, ARG1, CA4, CRISPLD2, S100A12, and GZMK genes may be underlying biomarkers involved in STEMI-related IS. |
format | Online Article Text |
id | pubmed-9403764 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94037642022-08-26 Bioinformatics analysis to identify potential biomarkers and therapeutic targets for ST-segment–elevation myocardial infarction-related ischemic stroke Feng, Shuo Li, Rui Zhou, Qingqing Qu, Fengling Hu, Wei Liu, Xinfeng Front Neurol Neurology BACKGROUND: Acute myocardial infarction (AMI) is one of the major causes of mortality and disability worldwide, and ischemic stroke (IS) is a serious complication after AMI. In particular, patients with ST-segment–elevation myocardial infarction (STEMI) are more susceptible to IS. However, the interrelationship between the two disease mechanisms is not clear. Using bioinformatics tools, we investigated genes commonly expressed in patients with STEMI and IS to explore the relationship between these diseases, with the aim of uncovering the underlying biomarkers and therapeutic targets for STEMI-associated IS. METHODS: Differentially expressed genes (DEGs) related to STEMI and IS were identified through bioinformatics analysis of the Gene Expression Omnibus (GEO) datasets GSE60993 and GSE16561, respectively. Thereafter, we assessed protein-protein interaction networks, gene ontology term annotations, and pathway enrichment for DEGs using various prediction and network analysis methods. The predicted miRNAs targeting the co-expressed STEMI- and IS-related DEGs were also evaluated. RESULTS: We identified 210 and 29 DEGs in GSE60993 and GSE16561, respectively. CD8A, TLR2, TLR4, S100A12, and TREM1 were associated with STEMI, while the hubgenes, IL7R, CCR7, FCGR3B, CD79A, and ITK were implicated in IS. In addition, binding of the transcripts of the co-expressed DEGs MMP9, ARG1, CA4, CRISPLD2, S100A12, and GZMK to their corresponding predicted miRNAs, especially miR-654-5p, may be associated with STEMI-related IS. CONCLUSIONS: STEMI and IS are related and MMP9, ARG1, CA4, CRISPLD2, S100A12, and GZMK genes may be underlying biomarkers involved in STEMI-related IS. Frontiers Media S.A. 2022-08-11 /pmc/articles/PMC9403764/ /pubmed/36034287 http://dx.doi.org/10.3389/fneur.2022.894289 Text en Copyright © 2022 Feng, Li, Zhou, Qu, Hu and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Feng, Shuo Li, Rui Zhou, Qingqing Qu, Fengling Hu, Wei Liu, Xinfeng Bioinformatics analysis to identify potential biomarkers and therapeutic targets for ST-segment–elevation myocardial infarction-related ischemic stroke |
title | Bioinformatics analysis to identify potential biomarkers and therapeutic targets for ST-segment–elevation myocardial infarction-related ischemic stroke |
title_full | Bioinformatics analysis to identify potential biomarkers and therapeutic targets for ST-segment–elevation myocardial infarction-related ischemic stroke |
title_fullStr | Bioinformatics analysis to identify potential biomarkers and therapeutic targets for ST-segment–elevation myocardial infarction-related ischemic stroke |
title_full_unstemmed | Bioinformatics analysis to identify potential biomarkers and therapeutic targets for ST-segment–elevation myocardial infarction-related ischemic stroke |
title_short | Bioinformatics analysis to identify potential biomarkers and therapeutic targets for ST-segment–elevation myocardial infarction-related ischemic stroke |
title_sort | bioinformatics analysis to identify potential biomarkers and therapeutic targets for st-segment–elevation myocardial infarction-related ischemic stroke |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403764/ https://www.ncbi.nlm.nih.gov/pubmed/36034287 http://dx.doi.org/10.3389/fneur.2022.894289 |
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