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Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis
BACKGROUND: Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although it is not life-threatening, the accompanying rapid and irregular ventricular rate can lead to hemodynamic deterioration and obvious symptoms, especially the risk of cerebrovascular embolism. Our study aimed to...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Scientific Literature, Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7989062/ https://www.ncbi.nlm.nih.gov/pubmed/33741890 http://dx.doi.org/10.12659/MSM.928366 |
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author | Liu, Liang Yu, Yun Hu, Long-long Dong, Quan-bin Hu, Feng Zhu, Ling-juan Liang, Qian Yu, Ling-ling Bao, Hui-hui Cheng, Xiao-shu |
author_facet | Liu, Liang Yu, Yun Hu, Long-long Dong, Quan-bin Hu, Feng Zhu, Ling-juan Liang, Qian Yu, Ling-ling Bao, Hui-hui Cheng, Xiao-shu |
author_sort | Liu, Liang |
collection | PubMed |
description | BACKGROUND: Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although it is not life-threatening, the accompanying rapid and irregular ventricular rate can lead to hemodynamic deterioration and obvious symptoms, especially the risk of cerebrovascular embolism. Our study aimed to identify novel and promising genes that could explain the underlying mechanism of AF development. MATERIAL/METHODS: Expression profiles GSE41177, GSE79768, and GSE14975 were acquired from the Gene Expression Omnibus Database. R software was used for identifying differentially expressed genes (DEGs), and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were subsequently performed. A protein–protein interaction network was constructed in Cytoscape software. Next, a least absolute shrinkage and selection operator (LASSO) model was constructed and receiver-operating characteristic curve analysis was conducted to assess the specificity and sensitivity of the key genes. RESULTS: We obtained 204 DEGs from the datasets. The DEGs were mostly involved in immune response and cell communication. The primary pathways of the DEGs were related to the course or maintenance of autoimmune and chronic inflammatory diseases. The top 20 hub genes (high scores in cytoHubba) were selected in the PPI network. Finally, we identified 6 key genes (FCGR3B, CLEC10A, FPR2, IGSF6, S100A9, and S100A12) via the LASSO model. CONCLUSIONS: We present 6 target genes that are potentially involved in the molecular mechanisms of AF development. In addition, these genes are likely to serve as potential therapeutic targets. |
format | Online Article Text |
id | pubmed-7989062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | International Scientific Literature, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79890622021-03-26 Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis Liu, Liang Yu, Yun Hu, Long-long Dong, Quan-bin Hu, Feng Zhu, Ling-juan Liang, Qian Yu, Ling-ling Bao, Hui-hui Cheng, Xiao-shu Med Sci Monit Database Analysis BACKGROUND: Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although it is not life-threatening, the accompanying rapid and irregular ventricular rate can lead to hemodynamic deterioration and obvious symptoms, especially the risk of cerebrovascular embolism. Our study aimed to identify novel and promising genes that could explain the underlying mechanism of AF development. MATERIAL/METHODS: Expression profiles GSE41177, GSE79768, and GSE14975 were acquired from the Gene Expression Omnibus Database. R software was used for identifying differentially expressed genes (DEGs), and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were subsequently performed. A protein–protein interaction network was constructed in Cytoscape software. Next, a least absolute shrinkage and selection operator (LASSO) model was constructed and receiver-operating characteristic curve analysis was conducted to assess the specificity and sensitivity of the key genes. RESULTS: We obtained 204 DEGs from the datasets. The DEGs were mostly involved in immune response and cell communication. The primary pathways of the DEGs were related to the course or maintenance of autoimmune and chronic inflammatory diseases. The top 20 hub genes (high scores in cytoHubba) were selected in the PPI network. Finally, we identified 6 key genes (FCGR3B, CLEC10A, FPR2, IGSF6, S100A9, and S100A12) via the LASSO model. CONCLUSIONS: We present 6 target genes that are potentially involved in the molecular mechanisms of AF development. In addition, these genes are likely to serve as potential therapeutic targets. International Scientific Literature, Inc. 2021-03-20 /pmc/articles/PMC7989062/ /pubmed/33741890 http://dx.doi.org/10.12659/MSM.928366 Text en © Med Sci Monit, 2021 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) ) |
spellingShingle | Database Analysis Liu, Liang Yu, Yun Hu, Long-long Dong, Quan-bin Hu, Feng Zhu, Ling-juan Liang, Qian Yu, Ling-ling Bao, Hui-hui Cheng, Xiao-shu Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis |
title | Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis |
title_full | Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis |
title_fullStr | Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis |
title_full_unstemmed | Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis |
title_short | Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis |
title_sort | potential target genes in the development of atrial fibrillation: a comprehensive bioinformatics analysis |
topic | Database Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7989062/ https://www.ncbi.nlm.nih.gov/pubmed/33741890 http://dx.doi.org/10.12659/MSM.928366 |
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