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Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease, characterized by a decline in lung function. To date, the pathophysiologic mechanisms associated with lung dysfunction remain unclear, and no effective therapy has been identified to improve lung...

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Autores principales: Xia, Yuechong, Lei, Cheng, Yang, Danhui, Luo, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485506/
https://www.ncbi.nlm.nih.gov/pubmed/33194355
http://dx.doi.org/10.7717/peerj.9848
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author Xia, Yuechong
Lei, Cheng
Yang, Danhui
Luo, Hong
author_facet Xia, Yuechong
Lei, Cheng
Yang, Danhui
Luo, Hong
author_sort Xia, Yuechong
collection PubMed
description BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease, characterized by a decline in lung function. To date, the pathophysiologic mechanisms associated with lung dysfunction remain unclear, and no effective therapy has been identified to improve lung function. METHODS: In the present study, we used weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes associated with lung function in IPF. Three datasets, containing clinical information, were downloaded from Gene Expression Omnibus. WGCNA was performed on the GSE32537 dataset. Differentially expressed gene s (DEGs) between IPF patients and healthy controls were also identified to filter hub genes. The relationship between hub genes and lung function was then validated using the GSE47460 and GSE24206 datasets. RESULTS: The red module, containing 267 genes, was positively correlated with the St. George’s Respiratory Questionnaire score (r = 0.37, p < 0.001) and negatively correlated with the percent predicted forced vital capacity (FVC% predicted) (r =  − 0.46, p < 0.001) and the percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) (r =  − 0.42, p < 0.001). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis suggested that the genes in the red module were primarily involved in inflammation and immune pathways. Based on Module Membership and Gene Significance, 32 candidate hub genes were selected in the red module to construct a protein-protein interaction network . Based on the identified DEGs and the degree of connectivity in the network, we identified three hub genes, including interleukin 6 (IL6), suppressor of cytokine signaling-3 (SOCS3), and serpin family E member 1 (SERPINE1). In the GSE47460 dataset, Spearman correlation coefficients between Dlco% predicted and expression levels of IL6, SERPINE1, SOCS3 were –0.32, –0.41, and –0.46, respectively. Spearman correlation coefficients between FVC% predicted and expression levels of IL6, SERPINE1, SOCS3 were –0.29, –0.33, and –0.27, respectively. In the GSE24206 dataset, all three hub genes were upregulated in patients with advanced IPF. CONCLUSION: We identified three hub genes that negatively correlated with the lung function of IPF patients. Our results provide insights into the pathogenesis underlying the progressive disruption of lung function, and the identified hub genes may serve as biomarkers and potential therapeutictargets for the treatment of IPF patients.
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spelling pubmed-74855062020-11-12 Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis Xia, Yuechong Lei, Cheng Yang, Danhui Luo, Hong PeerJ Bioinformatics BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease, characterized by a decline in lung function. To date, the pathophysiologic mechanisms associated with lung dysfunction remain unclear, and no effective therapy has been identified to improve lung function. METHODS: In the present study, we used weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes associated with lung function in IPF. Three datasets, containing clinical information, were downloaded from Gene Expression Omnibus. WGCNA was performed on the GSE32537 dataset. Differentially expressed gene s (DEGs) between IPF patients and healthy controls were also identified to filter hub genes. The relationship between hub genes and lung function was then validated using the GSE47460 and GSE24206 datasets. RESULTS: The red module, containing 267 genes, was positively correlated with the St. George’s Respiratory Questionnaire score (r = 0.37, p < 0.001) and negatively correlated with the percent predicted forced vital capacity (FVC% predicted) (r =  − 0.46, p < 0.001) and the percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) (r =  − 0.42, p < 0.001). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis suggested that the genes in the red module were primarily involved in inflammation and immune pathways. Based on Module Membership and Gene Significance, 32 candidate hub genes were selected in the red module to construct a protein-protein interaction network . Based on the identified DEGs and the degree of connectivity in the network, we identified three hub genes, including interleukin 6 (IL6), suppressor of cytokine signaling-3 (SOCS3), and serpin family E member 1 (SERPINE1). In the GSE47460 dataset, Spearman correlation coefficients between Dlco% predicted and expression levels of IL6, SERPINE1, SOCS3 were –0.32, –0.41, and –0.46, respectively. Spearman correlation coefficients between FVC% predicted and expression levels of IL6, SERPINE1, SOCS3 were –0.29, –0.33, and –0.27, respectively. In the GSE24206 dataset, all three hub genes were upregulated in patients with advanced IPF. CONCLUSION: We identified three hub genes that negatively correlated with the lung function of IPF patients. Our results provide insights into the pathogenesis underlying the progressive disruption of lung function, and the identified hub genes may serve as biomarkers and potential therapeutictargets for the treatment of IPF patients. PeerJ Inc. 2020-09-08 /pmc/articles/PMC7485506/ /pubmed/33194355 http://dx.doi.org/10.7717/peerj.9848 Text en ©2020 Xia et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Xia, Yuechong
Lei, Cheng
Yang, Danhui
Luo, Hong
Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis
title Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis
title_full Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis
title_fullStr Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis
title_full_unstemmed Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis
title_short Identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis
title_sort identification of key modules and hub genes associated with lung function in idiopathic pulmonary fibrosis
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485506/
https://www.ncbi.nlm.nih.gov/pubmed/33194355
http://dx.doi.org/10.7717/peerj.9848
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