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Effects of CPAP on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis

A growing number of studies provide epidemiological evidence linking obstructive sleep apnea (OSA) with a number of chronic disorders. Transcriptional analyses have been conducted to analyze the gene expression data. However, the weighted gene coexpression network analysis (WGCNA) method has not bee...

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Autores principales: Peng, Juxiang, Song, Jukun, Zhou, Jing, Yin, Xinhai, Song, Jinlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593761/
https://www.ncbi.nlm.nih.gov/pubmed/30719767
http://dx.doi.org/10.1002/jcb.28203
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author Peng, Juxiang
Song, Jukun
Zhou, Jing
Yin, Xinhai
Song, Jinlin
author_facet Peng, Juxiang
Song, Jukun
Zhou, Jing
Yin, Xinhai
Song, Jinlin
author_sort Peng, Juxiang
collection PubMed
description A growing number of studies provide epidemiological evidence linking obstructive sleep apnea (OSA) with a number of chronic disorders. Transcriptional analyses have been conducted to analyze the gene expression data. However, the weighted gene coexpression network analysis (WGCNA) method has not been applied to determine the transcriptional consequence of continuous positive airway pressure (CPAP) therapy in patients with severe OSA. The aim of this study was to identify key pathways and genes in patients with OSA that are influenced by CPAP treatment and uncover/unveil potential molecular mechanisms using WGCNA. We analyzed the microarray data of OSA (GSE 49800) listed in the Gene Expression Omnibus database. Coexpression modules were constructed using WGCNA. In addition, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were also conducted. After the initial data processing, 5101 expressed gene profiles were identified. Next, a weighted gene coexpression network was established and 16 modules of coexpressed genes were identified. The interaction analysis demonstrated a relative independence of gene expression in these modules. The black module, tan module, midnightblue module, pink module, and greenyellow module were significantly associated with the alterations in circulating leukocyte gene expression at baseline and after exposure to CPAP. The five hub genes were considered to be candidate OSA‐related genes after CPAP treatment. Functional enrichment analysis revealed that steroid biosynthesis, amino sugar and nucleotide sugar metabolism, protein processing in the endoplasmic reticulum, and the insulin signaling pathway play critical roles in the development of OSA in circulating leukocyte gene expression at baseline and after exposure to CPAP. Using this new systems biology approach, we identified several genes and pathways that appear to be critical to OSA after CPAP treatment, and these findings provide a better understanding of OSA pathogenesis.
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spelling pubmed-65937612019-07-10 Effects of CPAP on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis Peng, Juxiang Song, Jukun Zhou, Jing Yin, Xinhai Song, Jinlin J Cell Biochem Research Articles A growing number of studies provide epidemiological evidence linking obstructive sleep apnea (OSA) with a number of chronic disorders. Transcriptional analyses have been conducted to analyze the gene expression data. However, the weighted gene coexpression network analysis (WGCNA) method has not been applied to determine the transcriptional consequence of continuous positive airway pressure (CPAP) therapy in patients with severe OSA. The aim of this study was to identify key pathways and genes in patients with OSA that are influenced by CPAP treatment and uncover/unveil potential molecular mechanisms using WGCNA. We analyzed the microarray data of OSA (GSE 49800) listed in the Gene Expression Omnibus database. Coexpression modules were constructed using WGCNA. In addition, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were also conducted. After the initial data processing, 5101 expressed gene profiles were identified. Next, a weighted gene coexpression network was established and 16 modules of coexpressed genes were identified. The interaction analysis demonstrated a relative independence of gene expression in these modules. The black module, tan module, midnightblue module, pink module, and greenyellow module were significantly associated with the alterations in circulating leukocyte gene expression at baseline and after exposure to CPAP. The five hub genes were considered to be candidate OSA‐related genes after CPAP treatment. Functional enrichment analysis revealed that steroid biosynthesis, amino sugar and nucleotide sugar metabolism, protein processing in the endoplasmic reticulum, and the insulin signaling pathway play critical roles in the development of OSA in circulating leukocyte gene expression at baseline and after exposure to CPAP. Using this new systems biology approach, we identified several genes and pathways that appear to be critical to OSA after CPAP treatment, and these findings provide a better understanding of OSA pathogenesis. John Wiley and Sons Inc. 2019-02-05 2019-06 /pmc/articles/PMC6593761/ /pubmed/30719767 http://dx.doi.org/10.1002/jcb.28203 Text en © 2019 The Authors. Journal of Cellular Biochemistry Published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Peng, Juxiang
Song, Jukun
Zhou, Jing
Yin, Xinhai
Song, Jinlin
Effects of CPAP on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis
title Effects of CPAP on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis
title_full Effects of CPAP on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis
title_fullStr Effects of CPAP on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis
title_full_unstemmed Effects of CPAP on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis
title_short Effects of CPAP on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis
title_sort effects of cpap on the transcriptional signatures in patients with obstructive sleep apnea via coexpression network analysis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593761/
https://www.ncbi.nlm.nih.gov/pubmed/30719767
http://dx.doi.org/10.1002/jcb.28203
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