Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics.

<h4>Background</h4>Myocardial infarction (MI), one of the most serious cardiovascular diseases, is also affected by altered mitochondrial metabolism and immune status, but their crosstalk is poorly understood. In this paper, we use bioinformatics to explore key targets associated with mi...

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Main Authors: Wenlong Kuang, Jianwu Huang, Yulu Yang, Yuhua Liao, Zihua Zhou, Qian Liu, Hailang Wu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0316463
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author Wenlong Kuang
Jianwu Huang
Yulu Yang
Yuhua Liao
Zihua Zhou
Qian Liu
Hailang Wu
author_facet Wenlong Kuang
Jianwu Huang
Yulu Yang
Yuhua Liao
Zihua Zhou
Qian Liu
Hailang Wu
author_sort Wenlong Kuang
collection DOAJ
description <h4>Background</h4>Myocardial infarction (MI), one of the most serious cardiovascular diseases, is also affected by altered mitochondrial metabolism and immune status, but their crosstalk is poorly understood. In this paper, we use bioinformatics to explore key targets associated with mitochondrial metabolic function in MI.<h4>Methods</h4>The datasets (GSE775, GSE183272 and GSE236374) were from National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) in conjunction with mitochondrial gene data that were downloaded from the MitoCarta 3.0 database. Differentially expressed genes (DEGs) in the dataset were screened by ClusterGVis, Weighted Gene Co-Expression Network Analysis (WGCNA) and GEO2R, and functional enrichment was performed by Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genomes (KEGG). Then mitochondria-associated DEGs (MitoDEGs) were obtained. Protein-protein interaction (PPI) networks were constructed to identify central MitoDEGs that are strongly associated with MI. The Cytoscape and miRWalk databases were then used to predict the transcription factors and target miRNAs of the central MitoDEG, respectively. Finally, the mouse model has been established to demonstrate the expression of MitoDEGs and their association with cardiac function.<h4>Results</h4>MitoDEGs in MI were mainly involved in mitochondrial function and adenosine triphosphate (ATP) synthesis pathways. The 10 MI-related hub MitoDEGs were then obtained by eight different algorithms. Immunoassays showed a significant increase in monocyte macrophage and T cell infiltration. According to animal experiments, the expression trends of the four hub MitoDEGs (Aco2, Atp5a1, Ndufs3, and Ndufv1) were verified to be consistent with the bioinformatics results.<h4>Conclusion</h4>Our study identified key genes (Aco2, Atp5a1, Ndufs3, and Ndufv1) associated with mitochondrial function in myocardial infarction.
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spelling doaj-art-e2cd95f1ee8d4caeaffa11e5c281c43d2025-01-17T05:31:50ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-011912e031646310.1371/journal.pone.0316463Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics.Wenlong KuangJianwu HuangYulu YangYuhua LiaoZihua ZhouQian LiuHailang Wu<h4>Background</h4>Myocardial infarction (MI), one of the most serious cardiovascular diseases, is also affected by altered mitochondrial metabolism and immune status, but their crosstalk is poorly understood. In this paper, we use bioinformatics to explore key targets associated with mitochondrial metabolic function in MI.<h4>Methods</h4>The datasets (GSE775, GSE183272 and GSE236374) were from National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) in conjunction with mitochondrial gene data that were downloaded from the MitoCarta 3.0 database. Differentially expressed genes (DEGs) in the dataset were screened by ClusterGVis, Weighted Gene Co-Expression Network Analysis (WGCNA) and GEO2R, and functional enrichment was performed by Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genomes (KEGG). Then mitochondria-associated DEGs (MitoDEGs) were obtained. Protein-protein interaction (PPI) networks were constructed to identify central MitoDEGs that are strongly associated with MI. The Cytoscape and miRWalk databases were then used to predict the transcription factors and target miRNAs of the central MitoDEG, respectively. Finally, the mouse model has been established to demonstrate the expression of MitoDEGs and their association with cardiac function.<h4>Results</h4>MitoDEGs in MI were mainly involved in mitochondrial function and adenosine triphosphate (ATP) synthesis pathways. The 10 MI-related hub MitoDEGs were then obtained by eight different algorithms. Immunoassays showed a significant increase in monocyte macrophage and T cell infiltration. According to animal experiments, the expression trends of the four hub MitoDEGs (Aco2, Atp5a1, Ndufs3, and Ndufv1) were verified to be consistent with the bioinformatics results.<h4>Conclusion</h4>Our study identified key genes (Aco2, Atp5a1, Ndufs3, and Ndufv1) associated with mitochondrial function in myocardial infarction.https://doi.org/10.1371/journal.pone.0316463
spellingShingle Wenlong Kuang
Jianwu Huang
Yulu Yang
Yuhua Liao
Zihua Zhou
Qian Liu
Hailang Wu
Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics.
PLoS ONE
title Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics.
title_full Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics.
title_fullStr Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics.
title_full_unstemmed Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics.
title_short Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics.
title_sort identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics
url https://doi.org/10.1371/journal.pone.0316463
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