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Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis

Osteoarthritis (OA) is a major cause of pain, disability, and social burden in the elderly throughout the world. Although many studies focused on the molecular mechanism of OA, its etiology remains unclear. Therefore, more biomarkers need to be explored to help early diagnosis, clinical outcome meas...

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Autores principales: Wang, Yanchao, Zhou, Wenjun, Chen, Yan, He, Dong, Qin, Zhen, Wang, Zhao, Liu, Song, Zhou, Lei, Su, Jianwen, Zhang, Chi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718428/
https://www.ncbi.nlm.nih.gov/pubmed/36468029
http://dx.doi.org/10.3389/fgene.2022.1036156
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author Wang, Yanchao
Zhou, Wenjun
Chen, Yan
He, Dong
Qin, Zhen
Wang, Zhao
Liu, Song
Zhou, Lei
Su, Jianwen
Zhang, Chi
author_facet Wang, Yanchao
Zhou, Wenjun
Chen, Yan
He, Dong
Qin, Zhen
Wang, Zhao
Liu, Song
Zhou, Lei
Su, Jianwen
Zhang, Chi
author_sort Wang, Yanchao
collection PubMed
description Osteoarthritis (OA) is a major cause of pain, disability, and social burden in the elderly throughout the world. Although many studies focused on the molecular mechanism of OA, its etiology remains unclear. Therefore, more biomarkers need to be explored to help early diagnosis, clinical outcome measurement, and new therapeutic target development. Our study aimed to retrieve the potential hub genes of osteoarthritis (OA) by weighted gene co-expression network analysis (WGCNA) and assess their clinical utility for predicting OA. Here, we integrated WGCNA to identify novel OA susceptibility modules and hub genes. In this study, we first selected 477 and 834 DEGs in the GSE1919 and the GSE55235 databases, respectively, from the Gene Expression Omnibus (GEO) website. Genes with p-value<0.05 and | log(2)FC | > 1 were included in our analysis. Then, WGCNA was conducted to build a gene co-expression network, which filtered out the most relevant modules and screened out 23 overlapping WGCNA-derived hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses elucidated that these hub genes were associated with cell adhesion molecules pathway, leukocyte activation, and inflammatory response. In addition, we conducted the protein–protein interaction (PPI) network in 23 hub genes, and the top four upregulated hub genes were sorted out (CD4, SELL, ITGB2, and CD52). Moreover, our nomogram model showed good performance in predicting the risk of OA (C-index = 0.76), and this model proved to be efficient in diagnosis by ROC curves (AUC = 0.789). After that, a single-sample gene set enrichment (ssGSEA) analysis was performed to discover immune cell infiltration in OA. Finally, human primary synoviocytes and immunohistochemistry study of synovial tissues confirmed that those candidate genes were significantly upregulated in the OA groups compared with normal groups. We successfully constructed a co-expression network based on WGCNA and found out that OA-associated susceptibility modules and hub genes, which may provide further insight into the development of pre-symptomatic diagnosis, may contribute to understanding the molecular mechanism study of OA risk genes.
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spelling pubmed-97184282022-12-03 Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis Wang, Yanchao Zhou, Wenjun Chen, Yan He, Dong Qin, Zhen Wang, Zhao Liu, Song Zhou, Lei Su, Jianwen Zhang, Chi Front Genet Genetics Osteoarthritis (OA) is a major cause of pain, disability, and social burden in the elderly throughout the world. Although many studies focused on the molecular mechanism of OA, its etiology remains unclear. Therefore, more biomarkers need to be explored to help early diagnosis, clinical outcome measurement, and new therapeutic target development. Our study aimed to retrieve the potential hub genes of osteoarthritis (OA) by weighted gene co-expression network analysis (WGCNA) and assess their clinical utility for predicting OA. Here, we integrated WGCNA to identify novel OA susceptibility modules and hub genes. In this study, we first selected 477 and 834 DEGs in the GSE1919 and the GSE55235 databases, respectively, from the Gene Expression Omnibus (GEO) website. Genes with p-value<0.05 and | log(2)FC | > 1 were included in our analysis. Then, WGCNA was conducted to build a gene co-expression network, which filtered out the most relevant modules and screened out 23 overlapping WGCNA-derived hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses elucidated that these hub genes were associated with cell adhesion molecules pathway, leukocyte activation, and inflammatory response. In addition, we conducted the protein–protein interaction (PPI) network in 23 hub genes, and the top four upregulated hub genes were sorted out (CD4, SELL, ITGB2, and CD52). Moreover, our nomogram model showed good performance in predicting the risk of OA (C-index = 0.76), and this model proved to be efficient in diagnosis by ROC curves (AUC = 0.789). After that, a single-sample gene set enrichment (ssGSEA) analysis was performed to discover immune cell infiltration in OA. Finally, human primary synoviocytes and immunohistochemistry study of synovial tissues confirmed that those candidate genes were significantly upregulated in the OA groups compared with normal groups. We successfully constructed a co-expression network based on WGCNA and found out that OA-associated susceptibility modules and hub genes, which may provide further insight into the development of pre-symptomatic diagnosis, may contribute to understanding the molecular mechanism study of OA risk genes. Frontiers Media S.A. 2022-11-18 /pmc/articles/PMC9718428/ /pubmed/36468029 http://dx.doi.org/10.3389/fgene.2022.1036156 Text en Copyright © 2022 Wang, Zhou, Chen, He, Qin, Wang, Liu, Zhou, Su and Zhang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Wang, Yanchao
Zhou, Wenjun
Chen, Yan
He, Dong
Qin, Zhen
Wang, Zhao
Liu, Song
Zhou, Lei
Su, Jianwen
Zhang, Chi
Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis
title Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis
title_full Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis
title_fullStr Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis
title_full_unstemmed Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis
title_short Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis
title_sort identification of susceptibility modules and hub genes of osteoarthritis by wgcna analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718428/
https://www.ncbi.nlm.nih.gov/pubmed/36468029
http://dx.doi.org/10.3389/fgene.2022.1036156
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