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Article: Application of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis

TitleApplication of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis
Authors
Editors
Editor(s):Sheikn, N
Issue Date2021
PublisherHindawi Publishing Corporation. The Journal's web site is located at http://www.hindawi.com/journals/jbb/index.html
Citation
BioMed Research International, 2021, v. 2021, p. article no. 9957569 How to Cite?
AbstractSystemic juvenile idiopathic arthritis (sJIA) is a severe autoinflammatory disorder with a still not clearly defined molecular mechanism. To better understand the disease, we used scattered datasets from public domains and performed a weighted gene coexpression network analysis (WGCNA) to identify key modules and hub genes underlying sJIA pathogenesis. Two gene expression datasets, GSE7753 and GSE13501, were used to construct the WGCNA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were applied to the genes and hub genes in the sJIA modules. Cytoscape was used to screen and visualize the hub genes. We further compared the hub genes with the genome-wide association study (GWAS) genes and used a consensus WGCNA to verify that our conclusions were conservative and reproducible across multiple independent datasets. A total of 5,414 genes were obtained for WGCNA, from which highly correlated genes were divided into 17 modules. The red module demonstrated the highest correlation with the sJIA module (r = 0.8, p = 3e -29), whereas the green-yellow module was found to be closely related to the non-sJIA module (r = 0.62, p = 1e -14). Functional enrichment analysis demonstrated that the red module was mostly enriched in the activation of immune responses, infection, nucleosomes, and erythrocytes, and the green-yellow module was mostly enriched in immune responses and inflammation. Additionally, the hub genes in the red module were highly enriched in erythrocyte differentiation, including ALAS2, AHSP, TRIM10, TRIM58, and KLF1. The hub genes from the green-yellow module were mainly associated with immune responses, as exemplified by the genes KLRB1, KLRF1, CD160, and KIRs. We identified sJIA-related modules and several hub genes that might be associated with the development of sJIA. Particularly, the modules may help understand the mechanisms of sJIA, and the hub genes may become biomarkers and therapeutic targets of sJIA in the future.
Persistent Identifierhttp://hdl.handle.net/10722/304739
ISSN
2021 Impact Factor: 3.246
2020 SCImago Journal Rankings: 0.772
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhou, M-
dc.contributor.authorGuo, R-
dc.contributor.authorWang, YF-
dc.contributor.authorYang, W-
dc.contributor.authorLi, R-
dc.contributor.authorLu, L-
dc.contributor.editorSheikn, N-
dc.date.accessioned2021-10-05T02:34:29Z-
dc.date.available2021-10-05T02:34:29Z-
dc.date.issued2021-
dc.identifier.citationBioMed Research International, 2021, v. 2021, p. article no. 9957569-
dc.identifier.issn2314-6133-
dc.identifier.urihttp://hdl.handle.net/10722/304739-
dc.description.abstractSystemic juvenile idiopathic arthritis (sJIA) is a severe autoinflammatory disorder with a still not clearly defined molecular mechanism. To better understand the disease, we used scattered datasets from public domains and performed a weighted gene coexpression network analysis (WGCNA) to identify key modules and hub genes underlying sJIA pathogenesis. Two gene expression datasets, GSE7753 and GSE13501, were used to construct the WGCNA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were applied to the genes and hub genes in the sJIA modules. Cytoscape was used to screen and visualize the hub genes. We further compared the hub genes with the genome-wide association study (GWAS) genes and used a consensus WGCNA to verify that our conclusions were conservative and reproducible across multiple independent datasets. A total of 5,414 genes were obtained for WGCNA, from which highly correlated genes were divided into 17 modules. The red module demonstrated the highest correlation with the sJIA module (r = 0.8, p = 3e -29), whereas the green-yellow module was found to be closely related to the non-sJIA module (r = 0.62, p = 1e -14). Functional enrichment analysis demonstrated that the red module was mostly enriched in the activation of immune responses, infection, nucleosomes, and erythrocytes, and the green-yellow module was mostly enriched in immune responses and inflammation. Additionally, the hub genes in the red module were highly enriched in erythrocyte differentiation, including ALAS2, AHSP, TRIM10, TRIM58, and KLF1. The hub genes from the green-yellow module were mainly associated with immune responses, as exemplified by the genes KLRB1, KLRF1, CD160, and KIRs. We identified sJIA-related modules and several hub genes that might be associated with the development of sJIA. Particularly, the modules may help understand the mechanisms of sJIA, and the hub genes may become biomarkers and therapeutic targets of sJIA in the future.-
dc.languageeng-
dc.publisherHindawi Publishing Corporation. The Journal's web site is located at http://www.hindawi.com/journals/jbb/index.html-
dc.relation.ispartofBioMed Research International-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleApplication of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis-
dc.typeArticle-
dc.identifier.emailWang, YF: yfwangbm@connect.hku.hk-
dc.identifier.emailYang, W: yangwl@hku.hk-
dc.identifier.authorityYang, W=rp00524-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1155/2021/9957569-
dc.identifier.pmid34435051-
dc.identifier.pmcidPMC8382540-
dc.identifier.scopuseid_2-s2.0-85114119212-
dc.identifier.hkuros326306-
dc.identifier.volume2021-
dc.identifier.spagearticle no. 9957569-
dc.identifier.epagearticle no. 9957569-
dc.identifier.isiWOS:000691096900008-
dc.publisher.placeUnited States-

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