Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods
Wei-Ping Hu, Ying-Ying Zeng, Yi-Hui Zuo, Jing Zhang Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Shanghai Medical College, Fudan University, Shanghai, China Purpose: By reanalyzing the gene expression profile GSE76925 in the Gene Expression Omnibus database using bioinfo...
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doaj-bde11377c23b4030a209d4d295ea07fa2020-11-24T22:05:11ZengDove Medical PressInternational Journal of COPD1178-20052018-11-01Volume 133733374742272Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methodsHu WPZeng YYZuo YHZhang JWei-Ping Hu, Ying-Ying Zeng, Yi-Hui Zuo, Jing Zhang Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Shanghai Medical College, Fudan University, Shanghai, China 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, FEV1%=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. Keywords: emphysema, chronic obstructive pulmonary disease, differentially expressed genes, protein–protein interaction network analysis, candidate geneshttps://www.dovepress.com/identification-of-novel-candidate-genes-involved-in-the-progression-of-peer-reviewed-article-COPDemphysemaChronic Obstructive Pulmonary DiseaseDifferentially Expressed Genesprotein-protein interaction network analysiscandidate genes |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hu WP Zeng YY Zuo YH Zhang J |
spellingShingle |
Hu WP Zeng YY Zuo YH Zhang J Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods International Journal of COPD emphysema Chronic Obstructive Pulmonary Disease Differentially Expressed Genes protein-protein interaction network analysis candidate genes |
author_facet |
Hu WP Zeng YY Zuo YH Zhang J |
author_sort |
Hu WP |
title |
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_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_sort |
identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods |
publisher |
Dove Medical Press |
series |
International Journal of COPD |
issn |
1178-2005 |
publishDate |
2018-11-01 |
description |
Wei-Ping Hu, Ying-Ying Zeng, Yi-Hui Zuo, Jing Zhang Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Shanghai Medical College, Fudan University, Shanghai, China 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, FEV1%=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. Keywords: emphysema, chronic obstructive pulmonary disease, differentially expressed genes, protein–protein interaction network analysis, candidate genes |
topic |
emphysema Chronic Obstructive Pulmonary Disease Differentially Expressed Genes protein-protein interaction network analysis candidate genes |
url |
https://www.dovepress.com/identification-of-novel-candidate-genes-involved-in-the-progression-of-peer-reviewed-article-COPD |
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