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

Systemic 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 k...

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Autores principales: Zhou, Mi, Guo, Ruru, Wang, Yong-Fei, Yang, Wanling, Li, Rongxiu, Lu, Liangjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382540/
https://www.ncbi.nlm.nih.gov/pubmed/34435051
http://dx.doi.org/10.1155/2021/9957569
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author Zhou, Mi
Guo, Ruru
Wang, Yong-Fei
Yang, Wanling
Li, Rongxiu
Lu, Liangjing
author_facet Zhou, Mi
Guo, Ruru
Wang, Yong-Fei
Yang, Wanling
Li, Rongxiu
Lu, Liangjing
author_sort Zhou, Mi
collection PubMed
description Systemic 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.
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spelling pubmed-83825402021-08-24 Application of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis Zhou, Mi Guo, Ruru Wang, Yong-Fei Yang, Wanling Li, Rongxiu Lu, Liangjing Biomed Res Int Research Article Systemic 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. Hindawi 2021-08-13 /pmc/articles/PMC8382540/ /pubmed/34435051 http://dx.doi.org/10.1155/2021/9957569 Text en Copyright © 2021 Mi Zhou et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhou, Mi
Guo, Ruru
Wang, Yong-Fei
Yang, Wanling
Li, Rongxiu
Lu, Liangjing
Application of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis
title Application of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis
title_full Application of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis
title_fullStr Application of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis
title_full_unstemmed Application of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis
title_short Application of Weighted Gene Coexpression Network Analysis to Identify Key Modules and Hub Genes in Systemic Juvenile Idiopathic Arthritis
title_sort application of weighted gene coexpression network analysis to identify key modules and hub genes in systemic juvenile idiopathic arthritis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382540/
https://www.ncbi.nlm.nih.gov/pubmed/34435051
http://dx.doi.org/10.1155/2021/9957569
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