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Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA)

BACKGROUND: Increasing evidence has suggested that obesity affects the occurrence and progression of osteoarthritis (OA). However, the underlying molecular mechanism that obesity affects the course of OA is not fully understood and remains to be studied. METHODS: The gene expression profiles of the...

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Autores principales: Zhou, Quan, Sun, Huan, Jia, Jin, Jiang, Jun-liang, Li, Tao, Wu, Zhao-xiang, Chen, Zhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9293492/
https://www.ncbi.nlm.nih.gov/pubmed/35860189
http://dx.doi.org/10.1155/2022/8953807
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author Zhou, Quan
Sun, Huan
Jia, Jin
Jiang, Jun-liang
Li, Tao
Wu, Zhao-xiang
Chen, Zhong
author_facet Zhou, Quan
Sun, Huan
Jia, Jin
Jiang, Jun-liang
Li, Tao
Wu, Zhao-xiang
Chen, Zhong
author_sort Zhou, Quan
collection PubMed
description BACKGROUND: Increasing evidence has suggested that obesity affects the occurrence and progression of osteoarthritis (OA). However, the underlying molecular mechanism that obesity affects the course of OA is not fully understood and remains to be studied. METHODS: The gene expression profiles of the GSE117999 and GSE98460 datasets were derived from the Gene Expression Omnibus (GEO) database. Firstly, we explored the correlation between obesity and OA using chi-square test. Next, weighted gene coexpression network analysis (WGCNA) was executed to identify obesity patients with OA- (obesity OA-) related genes in the GSE117999 dataset by “WGCNA” package. Moreover, differential expression analysis was performed to select the hub genes by “limma” package. Furthermore, ingenuity pathway analysis (IPA) and functional enrichment analysis (“clusterProfiler” package) were conducted to investigate the functions of genes. Finally, the regulatory networks of hub genes and protein-protein interaction (PPI) network were created by the Cytoscape 3.5.1 software and STRING. RESULTS: A total of 15 differentially expressed obesity OA-related genes, including 9 lncRNAs and 6 protein coding genes, were detected by overlapping 66 differentially expressed genes (DEGs) between normal BMI samples and obesity OA samples and 451 obesity OA-related genes. Moreover, CCR10, LENG8, QRFPR, UHRF1BP1, and HLA-DRB4 were identified as hub genes. IPA results indicated that the hub genes were noticeably enriched in antimicrobial response, inflammatory response, and humoral immune response. PPI network showed that CCR10 interacted more with other proteins. Gene set enrichment analysis (GSEA) indicated that the hub genes were related to protein translation, cancer, chromatin modification, antigen processing, and presentation. CONCLUSION: Our results further demonstrated the role of obesity in OA and might provide new targets for the treatment of obesity OA.
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spelling pubmed-92934922022-07-19 Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA) Zhou, Quan Sun, Huan Jia, Jin Jiang, Jun-liang Li, Tao Wu, Zhao-xiang Chen, Zhong Comput Math Methods Med Research Article BACKGROUND: Increasing evidence has suggested that obesity affects the occurrence and progression of osteoarthritis (OA). However, the underlying molecular mechanism that obesity affects the course of OA is not fully understood and remains to be studied. METHODS: The gene expression profiles of the GSE117999 and GSE98460 datasets were derived from the Gene Expression Omnibus (GEO) database. Firstly, we explored the correlation between obesity and OA using chi-square test. Next, weighted gene coexpression network analysis (WGCNA) was executed to identify obesity patients with OA- (obesity OA-) related genes in the GSE117999 dataset by “WGCNA” package. Moreover, differential expression analysis was performed to select the hub genes by “limma” package. Furthermore, ingenuity pathway analysis (IPA) and functional enrichment analysis (“clusterProfiler” package) were conducted to investigate the functions of genes. Finally, the regulatory networks of hub genes and protein-protein interaction (PPI) network were created by the Cytoscape 3.5.1 software and STRING. RESULTS: A total of 15 differentially expressed obesity OA-related genes, including 9 lncRNAs and 6 protein coding genes, were detected by overlapping 66 differentially expressed genes (DEGs) between normal BMI samples and obesity OA samples and 451 obesity OA-related genes. Moreover, CCR10, LENG8, QRFPR, UHRF1BP1, and HLA-DRB4 were identified as hub genes. IPA results indicated that the hub genes were noticeably enriched in antimicrobial response, inflammatory response, and humoral immune response. PPI network showed that CCR10 interacted more with other proteins. Gene set enrichment analysis (GSEA) indicated that the hub genes were related to protein translation, cancer, chromatin modification, antigen processing, and presentation. CONCLUSION: Our results further demonstrated the role of obesity in OA and might provide new targets for the treatment of obesity OA. Hindawi 2022-07-11 /pmc/articles/PMC9293492/ /pubmed/35860189 http://dx.doi.org/10.1155/2022/8953807 Text en Copyright © 2022 Quan 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, Quan
Sun, Huan
Jia, Jin
Jiang, Jun-liang
Li, Tao
Wu, Zhao-xiang
Chen, Zhong
Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA)
title Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA)
title_full Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA)
title_fullStr Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA)
title_full_unstemmed Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA)
title_short Identification of Key Genes Related to the Obesity Patients with Osteoarthritis Based on Weighted Gene Coexpression Network Analysis (WGCNA)
title_sort identification of key genes related to the obesity patients with osteoarthritis based on weighted gene coexpression network analysis (wgcna)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9293492/
https://www.ncbi.nlm.nih.gov/pubmed/35860189
http://dx.doi.org/10.1155/2022/8953807
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