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...

Full description

Bibliographic Details
Main Authors: Min Li, Wenye Zhu, Chu Wang, Yuanyuan Zheng, Shibo Sun, Yan Fang, Zhuang Luo
Format: Article
Language:English
Published: BMC 2021-11-01
Series:BMC Pulmonary Medicine
Subjects:
Online Access:https://doi.org/10.1186/s12890-021-01711-3
_version_ 1819008684326387712
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.
first_indexed 2024-12-21T00:44:23Z
format Article
id doaj.art-eb64ae82e5a643e38060f29d686dd583
institution Directory Open Access Journal
issn 1471-2466
language English
last_indexed 2024-12-21T00:44:23Z
publishDate 2021-11-01
publisher BMC
record_format Article
series BMC Pulmonary Medicine
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
work_keys_str_mv AT minli weightedgenecoexpressionnetworkanalysistoidentifykeymodulesandhubgenesassociatedwithpaucigranulocyticasthma
AT wenyezhu weightedgenecoexpressionnetworkanalysistoidentifykeymodulesandhubgenesassociatedwithpaucigranulocyticasthma
AT chuwang weightedgenecoexpressionnetworkanalysistoidentifykeymodulesandhubgenesassociatedwithpaucigranulocyticasthma
AT yuanyuanzheng weightedgenecoexpressionnetworkanalysistoidentifykeymodulesandhubgenesassociatedwithpaucigranulocyticasthma
AT shibosun weightedgenecoexpressionnetworkanalysistoidentifykeymodulesandhubgenesassociatedwithpaucigranulocyticasthma
AT yanfang weightedgenecoexpressionnetworkanalysistoidentifykeymodulesandhubgenesassociatedwithpaucigranulocyticasthma
AT zhuangluo weightedgenecoexpressionnetworkanalysistoidentifykeymodulesandhubgenesassociatedwithpaucigranulocyticasthma