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Identification of Atrial Fibrillation-Related lncRNA Based on Bioinformatic Analysis

BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia in the world. Long noncoding RNA (lncRNA) has been found to play an important role in cardiovascular diseases including heart failure, myocardial infarction, and atherosclerosis. However, the role of lncRNA in AF has rarely been stud...

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Autores principales: Xie, Liangzhen, Huang, GuanShen, Gao, Mingjian, Huang, Jianming, Li, Hai, Xia, Hao, Xiang, Xiuting, Wu, Saizhu, Ruan, Yunjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8837454/
https://www.ncbi.nlm.nih.gov/pubmed/35154514
http://dx.doi.org/10.1155/2022/8307975
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author Xie, Liangzhen
Huang, GuanShen
Gao, Mingjian
Huang, Jianming
Li, Hai
Xia, Hao
Xiang, Xiuting
Wu, Saizhu
Ruan, Yunjun
author_facet Xie, Liangzhen
Huang, GuanShen
Gao, Mingjian
Huang, Jianming
Li, Hai
Xia, Hao
Xiang, Xiuting
Wu, Saizhu
Ruan, Yunjun
author_sort Xie, Liangzhen
collection PubMed
description BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia in the world. Long noncoding RNA (lncRNA) has been found to play an important role in cardiovascular diseases including heart failure, myocardial infarction, and atherosclerosis. However, the role of lncRNA in AF has rarely been studied. The purpose of this study is to identify the expression profile of lncRNA in AF patients, explore the function of lncRNA in AF, and provide a potential scientific basis for the treatment of AF in the future. METHODS: The lncRNA and mRNA expression profiles were obtained from the atrial appendage samples of GSE31821, GSE411774, GSE79768, and GSE115574 in the Gene Expression Omnibus (GEO) database. Functional analysis was performed via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Variation Analysis (GSVA). The “CIBERSORT” R kit was used to analyze 22 immune cell infiltrates in AF and sinus rhythm (SR) patients. The “CORRPLOT” R package was used to analyze the immune correlation between lncRNA and immune cells. RESULTS: A total of 6 differentially expressed lncRNAs and 45 differentially expressed mRNAs were identified in the AF and SR groups. GO, KEGG, and GSVA results showed that abnormally expressed lncRNAs were involved in signaling pathways related to the atrium, including the Toll-like receptor signaling pathway and calcium signaling pathway. Immune cell infiltration analysis revealed that native B cells, follicular helper T cells, and resting dendritic cells may be involved in the AF process. In addition, LINC00844 was negatively correlated with resting dendritic cells. CONCLUSION: The expression profile of lncRNA in AF patients was different from that in normal controls. The physiological functions of these differentially expressed lncRNAs may be related to the pathogenesis of AF, which provide a scientific basis for the prognosis and treatment of patients with AF.
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spelling pubmed-88374542022-02-12 Identification of Atrial Fibrillation-Related lncRNA Based on Bioinformatic Analysis Xie, Liangzhen Huang, GuanShen Gao, Mingjian Huang, Jianming Li, Hai Xia, Hao Xiang, Xiuting Wu, Saizhu Ruan, Yunjun Dis Markers Research Article BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia in the world. Long noncoding RNA (lncRNA) has been found to play an important role in cardiovascular diseases including heart failure, myocardial infarction, and atherosclerosis. However, the role of lncRNA in AF has rarely been studied. The purpose of this study is to identify the expression profile of lncRNA in AF patients, explore the function of lncRNA in AF, and provide a potential scientific basis for the treatment of AF in the future. METHODS: The lncRNA and mRNA expression profiles were obtained from the atrial appendage samples of GSE31821, GSE411774, GSE79768, and GSE115574 in the Gene Expression Omnibus (GEO) database. Functional analysis was performed via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Variation Analysis (GSVA). The “CIBERSORT” R kit was used to analyze 22 immune cell infiltrates in AF and sinus rhythm (SR) patients. The “CORRPLOT” R package was used to analyze the immune correlation between lncRNA and immune cells. RESULTS: A total of 6 differentially expressed lncRNAs and 45 differentially expressed mRNAs were identified in the AF and SR groups. GO, KEGG, and GSVA results showed that abnormally expressed lncRNAs were involved in signaling pathways related to the atrium, including the Toll-like receptor signaling pathway and calcium signaling pathway. Immune cell infiltration analysis revealed that native B cells, follicular helper T cells, and resting dendritic cells may be involved in the AF process. In addition, LINC00844 was negatively correlated with resting dendritic cells. CONCLUSION: The expression profile of lncRNA in AF patients was different from that in normal controls. The physiological functions of these differentially expressed lncRNAs may be related to the pathogenesis of AF, which provide a scientific basis for the prognosis and treatment of patients with AF. Hindawi 2022-02-04 /pmc/articles/PMC8837454/ /pubmed/35154514 http://dx.doi.org/10.1155/2022/8307975 Text en Copyright © 2022 Liangzhen Xie 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
Xie, Liangzhen
Huang, GuanShen
Gao, Mingjian
Huang, Jianming
Li, Hai
Xia, Hao
Xiang, Xiuting
Wu, Saizhu
Ruan, Yunjun
Identification of Atrial Fibrillation-Related lncRNA Based on Bioinformatic Analysis
title Identification of Atrial Fibrillation-Related lncRNA Based on Bioinformatic Analysis
title_full Identification of Atrial Fibrillation-Related lncRNA Based on Bioinformatic Analysis
title_fullStr Identification of Atrial Fibrillation-Related lncRNA Based on Bioinformatic Analysis
title_full_unstemmed Identification of Atrial Fibrillation-Related lncRNA Based on Bioinformatic Analysis
title_short Identification of Atrial Fibrillation-Related lncRNA Based on Bioinformatic Analysis
title_sort identification of atrial fibrillation-related lncrna based on bioinformatic analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8837454/
https://www.ncbi.nlm.nih.gov/pubmed/35154514
http://dx.doi.org/10.1155/2022/8307975
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