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Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis

BACKGROUND: Nonspecific orbital inflammation is a common ophthalmopathy with a high prevalence among adult females. Yet, its molecular mechanisms behind are poorly understood. Regulation of gene expression probably plays an important role in this disease. Thus, we utilized gene coexpression networks...

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Autores principales: Liu, Hanhan, Chen, Lu, Lei, Xiang, Ren, Hong, Li, Gaoyang, Deng, Zhihong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9166965/
https://www.ncbi.nlm.nih.gov/pubmed/35669499
http://dx.doi.org/10.1155/2022/7588084
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author Liu, Hanhan
Chen, Lu
Lei, Xiang
Ren, Hong
Li, Gaoyang
Deng, Zhihong
author_facet Liu, Hanhan
Chen, Lu
Lei, Xiang
Ren, Hong
Li, Gaoyang
Deng, Zhihong
author_sort Liu, Hanhan
collection PubMed
description BACKGROUND: Nonspecific orbital inflammation is a common ophthalmopathy with a high prevalence among adult females. Yet, its molecular mechanisms behind are poorly understood. Regulation of gene expression probably plays an important role in this disease. Thus, we utilized gene coexpression networks to identify key modules and hub genes involved in nonspecific orbital inflammation. METHODS: Data of gene expression in nonspecific orbital inflammation samples (n = 61) and healthy samples (n = 28) were obtained from the public Gene Expression Omnibus database. Afterward, differentially expressed genes were performed. Then, weighted correlation network analysis was done to define the key modules. Next, functional enrichment analysis was conducted by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway in key modules. Finally, a protein-protein interaction network and Cytohubba plugin were used to screen hub genes. RESULTS: Differential expression of 716 genes was identified, among which 169 genes were upregulated and 547 genes were downregulated in the nonspecific orbital inflammation group. In weighted correlation network analysis, we clarified 2 key modules (MEturquoise and MEblue) that are likely to play key roles in nonspecific orbital inflammation. Functional enrichment analysis indicated that these genes are predominately involved in immune response and matrix homeostasis. In addition, among 2 key modules, there are 20 hub genes identified. CONCLUSION: With this new approach, we identified several genes that could be critical to pathologies of nonspecific orbital inflammation. These findings may contribute to further therapeutic target development.
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spelling pubmed-91669652022-06-05 Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis Liu, Hanhan Chen, Lu Lei, Xiang Ren, Hong Li, Gaoyang Deng, Zhihong Dis Markers Research Article BACKGROUND: Nonspecific orbital inflammation is a common ophthalmopathy with a high prevalence among adult females. Yet, its molecular mechanisms behind are poorly understood. Regulation of gene expression probably plays an important role in this disease. Thus, we utilized gene coexpression networks to identify key modules and hub genes involved in nonspecific orbital inflammation. METHODS: Data of gene expression in nonspecific orbital inflammation samples (n = 61) and healthy samples (n = 28) were obtained from the public Gene Expression Omnibus database. Afterward, differentially expressed genes were performed. Then, weighted correlation network analysis was done to define the key modules. Next, functional enrichment analysis was conducted by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway in key modules. Finally, a protein-protein interaction network and Cytohubba plugin were used to screen hub genes. RESULTS: Differential expression of 716 genes was identified, among which 169 genes were upregulated and 547 genes were downregulated in the nonspecific orbital inflammation group. In weighted correlation network analysis, we clarified 2 key modules (MEturquoise and MEblue) that are likely to play key roles in nonspecific orbital inflammation. Functional enrichment analysis indicated that these genes are predominately involved in immune response and matrix homeostasis. In addition, among 2 key modules, there are 20 hub genes identified. CONCLUSION: With this new approach, we identified several genes that could be critical to pathologies of nonspecific orbital inflammation. These findings may contribute to further therapeutic target development. Hindawi 2022-05-27 /pmc/articles/PMC9166965/ /pubmed/35669499 http://dx.doi.org/10.1155/2022/7588084 Text en Copyright © 2022 Hanhan Liu 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
Liu, Hanhan
Chen, Lu
Lei, Xiang
Ren, Hong
Li, Gaoyang
Deng, Zhihong
Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis
title Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis
title_full Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis
title_fullStr Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis
title_full_unstemmed Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis
title_short Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis
title_sort identification of hub genes associated with nonspecific orbital inflammation by weighted gene coexpression network analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9166965/
https://www.ncbi.nlm.nih.gov/pubmed/35669499
http://dx.doi.org/10.1155/2022/7588084
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