Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma
Abstract Background Asthma is a heterogeneous disease that can be divided into four inflammatory phenotypes: eosinophilic asthma (EA), neutrophilic asthma (NA), mixed granulocytic asthma (MGA), and paucigranulocytic asthma (PGA). While research has mainly focused on EA and NA, the understanding of P...
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BMC
2021-11-01
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Online Access: | https://doi.org/10.1186/s12890-021-01711-3 |
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author | Min Li Wenye Zhu Chu Wang Yuanyuan Zheng Shibo Sun Yan Fang Zhuang Luo |
author_facet | Min Li Wenye Zhu Chu Wang Yuanyuan Zheng Shibo Sun Yan Fang Zhuang Luo |
author_sort | Min Li |
collection | DOAJ |
description | Abstract Background Asthma is a heterogeneous disease that can be divided into four inflammatory phenotypes: eosinophilic asthma (EA), neutrophilic asthma (NA), mixed granulocytic asthma (MGA), and paucigranulocytic asthma (PGA). While research has mainly focused on EA and NA, the understanding of PGA is limited. In this study, we aimed to identify underlying mechanisms and hub genes of PGA. Methods Based on the dataset from Gene Expression Omnibus(GEO), weighted gene coexpression network analysis (WGCNA), differentially expressed genes (DEGs) analysis and protein–protein interaction (PPI) network analysis were conducted to construct a gene network and to identify key gene modules and hub genes. Functional enrichment analyses were performed to investigate the biological process, pathways and immune status of PGA. The hub genes were validated in a separate dataset. Results Compared to non-PGA, PGA had a different gene expression pattern, in which 449 genes were differentially expressed. One gene module significantly associated with PGA was identified. Intersection between the differentially expressed genes (DEGs) and the genes from the module that were most relevant to PGA were mainly enriched in inflammation and immune response regulation. The single sample Gene Set Enrichment Analysis (ssGSEA) suggested a decreased immune infiltration and function in PGA. Finally six hub genes of PGA were identified, including ADCY2, CXCL1, FPRL1, GPR109B, GPR109A and ADCY3, which were validated in a separate dataset of GSE137268. Conclusions Our study characterized distinct gene expression patterns, biological processes and immune status of PGA and identified hub genes, which may improve the understanding of underlying mechanism and provide potential therapeutic targets for PGA. |
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issn | 1471-2466 |
language | English |
last_indexed | 2024-12-21T00:44:23Z |
publishDate | 2021-11-01 |
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spelling | doaj.art-eb64ae82e5a643e38060f29d686dd5832022-12-21T19:21:34ZengBMCBMC Pulmonary Medicine1471-24662021-11-0121111210.1186/s12890-021-01711-3Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthmaMin Li0Wenye Zhu1Chu Wang2Yuanyuan Zheng3Shibo Sun4Yan Fang5Zhuang Luo6Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan UniversityDepartment of Pharmacy, First Affiliated Hospital of Kunming Medical UniversityDepartment of Respiratory and Critical Care Medicine, First Affiliated Hospital of Kunming Medical UniversityDepartment of Respiratory and Critical Care Medicine, First Affiliated Hospital of Kunming Medical UniversityDepartment of Respiratory and Critical Care Medicine, First Affiliated Hospital of Kunming Medical UniversityDepartment of Respiratory and Critical Care Medicine, First Affiliated Hospital of Kunming Medical UniversityDepartment of Respiratory and Critical Care Medicine, First Affiliated Hospital of Kunming Medical UniversityAbstract Background Asthma is a heterogeneous disease that can be divided into four inflammatory phenotypes: eosinophilic asthma (EA), neutrophilic asthma (NA), mixed granulocytic asthma (MGA), and paucigranulocytic asthma (PGA). While research has mainly focused on EA and NA, the understanding of PGA is limited. In this study, we aimed to identify underlying mechanisms and hub genes of PGA. Methods Based on the dataset from Gene Expression Omnibus(GEO), weighted gene coexpression network analysis (WGCNA), differentially expressed genes (DEGs) analysis and protein–protein interaction (PPI) network analysis were conducted to construct a gene network and to identify key gene modules and hub genes. Functional enrichment analyses were performed to investigate the biological process, pathways and immune status of PGA. The hub genes were validated in a separate dataset. Results Compared to non-PGA, PGA had a different gene expression pattern, in which 449 genes were differentially expressed. One gene module significantly associated with PGA was identified. Intersection between the differentially expressed genes (DEGs) and the genes from the module that were most relevant to PGA were mainly enriched in inflammation and immune response regulation. The single sample Gene Set Enrichment Analysis (ssGSEA) suggested a decreased immune infiltration and function in PGA. Finally six hub genes of PGA were identified, including ADCY2, CXCL1, FPRL1, GPR109B, GPR109A and ADCY3, which were validated in a separate dataset of GSE137268. Conclusions Our study characterized distinct gene expression patterns, biological processes and immune status of PGA and identified hub genes, which may improve the understanding of underlying mechanism and provide potential therapeutic targets for PGA.https://doi.org/10.1186/s12890-021-01711-3Paucigranulocytic asthmaImmune statusWGCNAHub genes |
spellingShingle | Min Li Wenye Zhu Chu Wang Yuanyuan Zheng Shibo Sun Yan Fang Zhuang Luo Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma BMC Pulmonary Medicine Paucigranulocytic asthma Immune status WGCNA Hub genes |
title | Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma |
title_full | Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma |
title_fullStr | Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma |
title_full_unstemmed | Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma |
title_short | Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma |
title_sort | weighted gene co expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma |
topic | Paucigranulocytic asthma Immune status WGCNA Hub genes |
url | https://doi.org/10.1186/s12890-021-01711-3 |
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