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Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods

PURPOSE: By reanalyzing the gene expression profile GSE76925 in the Gene Expression Omnibus database using bioinformatic methods, we attempted to identify novel candidate genes promoting the development of emphysema in patients with COPD. PATIENTS AND METHODS: According to the Quantitative CT data i...

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Autores principales: Hu, Wei-Ping, Zeng, Ying-Ying, Zuo, Yi-Hui, Zhang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241693/
https://www.ncbi.nlm.nih.gov/pubmed/30532529
http://dx.doi.org/10.2147/COPD.S183100
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author Hu, Wei-Ping
Zeng, Ying-Ying
Zuo, Yi-Hui
Zhang, Jing
author_facet Hu, Wei-Ping
Zeng, Ying-Ying
Zuo, Yi-Hui
Zhang, Jing
author_sort Hu, Wei-Ping
collection PubMed
description PURPOSE: By reanalyzing the gene expression profile GSE76925 in the Gene Expression Omnibus database using bioinformatic methods, we attempted to identify novel candidate genes promoting the development of emphysema in patients with COPD. PATIENTS AND METHODS: According to the Quantitative CT data in GSE76925, patients were divided into mild emphysema group (%LAA-950<20%, n=12) and severe emphysema group (%LAA-950>50%, n=11). Differentially expressed genes (DEGs) were identified using Agilent GeneSpring GX v11.5 (corrected P-value <0.05 and |Fold Change|>1.3). Known driver genes of COPD were acquired by mining literatures and retrieving databases. Direct protein–protein interaction network (PPi) of DEGs and known driver genes was constructed by STRING.org to screen the DEGs directly interacting with driver genes. In addition, we used STRING.org to obtain the first-layer proteins interacting with DEGs’ products and constructed the indirect PPi of these interaction proteins. By merging the indirect PPi with driver genes’ PPi using Cytoscape v3.6.1, we attempted to discover potential pathways promoting emphysema’s development. RESULTS: All the patients had COPD with severe airflow limitation (age=62±8, FEV(1)%=28±12). A total of 57 DEGs (including 12 pseudogenes) and 135 known driving genes were identified. Direct PPi suggested that GPR65, GNB4, P2RY13, NPSR1, BCR, BAG4, and IMPDH2 were potential pathogenic genes. GPR65 could regulate the response of immune cells to the acidic microenvironment, and NPSR1’s expression on eosinophils was associated with asthma’s severity and IgE level. Indirect merging PPi demonstrated that the interacting network of TP53, IL8, CCR2, HSPA1A, ELANE, PIK3CA was associated with the development of emphysema. IL8, ELANE, and PIK3CA were molecules involved in the pathological mechanisms of emphysema, which also in return proved the role of TP53 in emphysema. CONCLUSION: Candidate genes such as GPR65, NPSR1, and TP53 may be involved in the progression of emphysema.
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spelling pubmed-62416932018-12-07 Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods Hu, Wei-Ping Zeng, Ying-Ying Zuo, Yi-Hui Zhang, Jing Int J Chron Obstruct Pulmon Dis Original Research PURPOSE: By reanalyzing the gene expression profile GSE76925 in the Gene Expression Omnibus database using bioinformatic methods, we attempted to identify novel candidate genes promoting the development of emphysema in patients with COPD. PATIENTS AND METHODS: According to the Quantitative CT data in GSE76925, patients were divided into mild emphysema group (%LAA-950<20%, n=12) and severe emphysema group (%LAA-950>50%, n=11). Differentially expressed genes (DEGs) were identified using Agilent GeneSpring GX v11.5 (corrected P-value <0.05 and |Fold Change|>1.3). Known driver genes of COPD were acquired by mining literatures and retrieving databases. Direct protein–protein interaction network (PPi) of DEGs and known driver genes was constructed by STRING.org to screen the DEGs directly interacting with driver genes. In addition, we used STRING.org to obtain the first-layer proteins interacting with DEGs’ products and constructed the indirect PPi of these interaction proteins. By merging the indirect PPi with driver genes’ PPi using Cytoscape v3.6.1, we attempted to discover potential pathways promoting emphysema’s development. RESULTS: All the patients had COPD with severe airflow limitation (age=62±8, FEV(1)%=28±12). A total of 57 DEGs (including 12 pseudogenes) and 135 known driving genes were identified. Direct PPi suggested that GPR65, GNB4, P2RY13, NPSR1, BCR, BAG4, and IMPDH2 were potential pathogenic genes. GPR65 could regulate the response of immune cells to the acidic microenvironment, and NPSR1’s expression on eosinophils was associated with asthma’s severity and IgE level. Indirect merging PPi demonstrated that the interacting network of TP53, IL8, CCR2, HSPA1A, ELANE, PIK3CA was associated with the development of emphysema. IL8, ELANE, and PIK3CA were molecules involved in the pathological mechanisms of emphysema, which also in return proved the role of TP53 in emphysema. CONCLUSION: Candidate genes such as GPR65, NPSR1, and TP53 may be involved in the progression of emphysema. Dove Medical Press 2018-11-14 /pmc/articles/PMC6241693/ /pubmed/30532529 http://dx.doi.org/10.2147/COPD.S183100 Text en © 2018 Hu et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Hu, Wei-Ping
Zeng, Ying-Ying
Zuo, Yi-Hui
Zhang, Jing
Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods
title Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods
title_full Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods
title_fullStr Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods
title_full_unstemmed Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods
title_short Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods
title_sort identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241693/
https://www.ncbi.nlm.nih.gov/pubmed/30532529
http://dx.doi.org/10.2147/COPD.S183100
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