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Identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis

Chronic obstructive pulmonary disease (COPD) is a multifactorial and heterogeneous disease that creates public health challenges worldwide. The underlying molecular mechanisms of COPD are not entirely clear. In this study, we aimed to identify the critical genes and potential molecular mechanisms of...

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Autores principales: Huang, Xinwei, Li, Yunwei, Guo, Xiaoran, Zhu, Zongxin, Kong, Xiangyang, Yu, Fubing, Wang, Qiang
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/PMC6823288/
https://www.ncbi.nlm.nih.gov/pubmed/31419078
http://dx.doi.org/10.1002/2211-5463.12719
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author Huang, Xinwei
Li, Yunwei
Guo, Xiaoran
Zhu, Zongxin
Kong, Xiangyang
Yu, Fubing
Wang, Qiang
author_facet Huang, Xinwei
Li, Yunwei
Guo, Xiaoran
Zhu, Zongxin
Kong, Xiangyang
Yu, Fubing
Wang, Qiang
author_sort Huang, Xinwei
collection PubMed
description Chronic obstructive pulmonary disease (COPD) is a multifactorial and heterogeneous disease that creates public health challenges worldwide. The underlying molecular mechanisms of COPD are not entirely clear. In this study, we aimed to identify the critical genes and potential molecular mechanisms of COPD by bioinformatic analysis. The gene expression profiles of lung tissues of COPD cases and healthy control subjects were obtained from the Gene Expression Omnibus. Differentially expressed genes were analyzed by integration with annotations from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, followed by construction of a protein‐protein interaction network and weighted gene coexpression analysis. We identified 139 differentially expressed genes associated with the progression of COPD, among which 14 Hub genes were identified and found to be enriched in certain categories, including immune and inflammatory response, response to lipopolysaccharide and receptor for advanced glycation end products binding; in addition, these Hub genes are involved in multiple signaling pathways, particularly hematopoietic cell lineage and cytokine‐cytokine receptor interaction. The 14 Hub genes were positively or negatively associated with COPD by wgcna analysis. The genes CX3CR1,PTGS2,FPR1,FPR2, S100A12,EGR1,CD163, S100A8 and S100A9 were identified to mediate inflammation and injury of the lung, and play critical roles in the pathogenesis of COPD. These findings improve our understanding of the underlying molecular mechanisms of COPD.
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spelling pubmed-68232882019-11-06 Identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis Huang, Xinwei Li, Yunwei Guo, Xiaoran Zhu, Zongxin Kong, Xiangyang Yu, Fubing Wang, Qiang FEBS Open Bio Research Articles Chronic obstructive pulmonary disease (COPD) is a multifactorial and heterogeneous disease that creates public health challenges worldwide. The underlying molecular mechanisms of COPD are not entirely clear. In this study, we aimed to identify the critical genes and potential molecular mechanisms of COPD by bioinformatic analysis. The gene expression profiles of lung tissues of COPD cases and healthy control subjects were obtained from the Gene Expression Omnibus. Differentially expressed genes were analyzed by integration with annotations from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, followed by construction of a protein‐protein interaction network and weighted gene coexpression analysis. We identified 139 differentially expressed genes associated with the progression of COPD, among which 14 Hub genes were identified and found to be enriched in certain categories, including immune and inflammatory response, response to lipopolysaccharide and receptor for advanced glycation end products binding; in addition, these Hub genes are involved in multiple signaling pathways, particularly hematopoietic cell lineage and cytokine‐cytokine receptor interaction. The 14 Hub genes were positively or negatively associated with COPD by wgcna analysis. The genes CX3CR1,PTGS2,FPR1,FPR2, S100A12,EGR1,CD163, S100A8 and S100A9 were identified to mediate inflammation and injury of the lung, and play critical roles in the pathogenesis of COPD. These findings improve our understanding of the underlying molecular mechanisms of COPD. John Wiley and Sons Inc. 2019-09-29 /pmc/articles/PMC6823288/ /pubmed/31419078 http://dx.doi.org/10.1002/2211-5463.12719 Text en © 2019 The Authors. Published by FEBS Press and John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Huang, Xinwei
Li, Yunwei
Guo, Xiaoran
Zhu, Zongxin
Kong, Xiangyang
Yu, Fubing
Wang, Qiang
Identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis
title Identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis
title_full Identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis
title_fullStr Identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis
title_full_unstemmed Identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis
title_short Identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis
title_sort identification of differentially expressed genes and signaling pathways in chronic obstructive pulmonary disease via bioinformatic analysis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823288/
https://www.ncbi.nlm.nih.gov/pubmed/31419078
http://dx.doi.org/10.1002/2211-5463.12719
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