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Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis
BACKGROUND: Thyroid eye disease (TED) is the most common orbital pathology that occurs in up to 50% of patients with Graves’ disease. Herein, we aimed at discovering the possible hub genes and pathways involved in TED based on bioinformatical approaches. RESULTS: The GSE105149 and GSE58331 datasets...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9461120/ https://www.ncbi.nlm.nih.gov/pubmed/36076300 http://dx.doi.org/10.1186/s40246-022-00412-0 |
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author | Hu, Jinxing Zhou, Shan Guo, Weiying |
author_facet | Hu, Jinxing Zhou, Shan Guo, Weiying |
author_sort | Hu, Jinxing |
collection | PubMed |
description | BACKGROUND: Thyroid eye disease (TED) is the most common orbital pathology that occurs in up to 50% of patients with Graves’ disease. Herein, we aimed at discovering the possible hub genes and pathways involved in TED based on bioinformatical approaches. RESULTS: The GSE105149 and GSE58331 datasets were downloaded from the Gene Expression Omnibus (GEO) database and merged for identifying TED-associated modules by weighted gene coexpression network analysis (WGCNA) and local maximal quasi-clique merger (lmQCM) analysis. EdgeR was run to screen differentially expressed genes (DEGs). Transcription factor (TF), microRNA (miR) and drug prediction analyses were performed using ToppGene suite. Function enrichment analysis was used to investigate the biological function of genes. Protein–protein interaction (PPI) analysis was performed based on the intersection between the list of genes obtained by WGCNA, lmQCM and DEGs, and hub genes were identified using the MCODE plugin. Based on the overlap of 497 genes retrieved from the different approaches, a robust TED coexpression network was constructed and 11 genes (ATP6V1A, PTGES3, PSMD12, PSMA4, METAP2, DNAJA1, PSMA1, UBQLN1, CCT2, VBP1 and NAA50) were identified as hub genes. Key TFs regulating genes in the TED-associated coexpression network, including NFRKB, ZNF711, ZNF407 and MORC2, and miRs including hsa-miR-144, hsa-miR-3662, hsa-miR-12136 and hsa-miR-3646, were identified. Genes in the coexpression network were enriched in the biological processes including proteasomal protein catabolic process and proteasome-mediated ubiquitin-dependent protein catabolic process and the pathways of endocytosis and ubiquitin-mediated proteolysis. Drugs perturbing genes in the coexpression network were also predicted and included enzyme inhibitors, chlorodiphenyl and finasteride. CONCLUSIONS: For the first time, TED-associated coexpression network was constructed and key genes and their functions, as well as TFs, miRs and drugs, were predicted. The results of the present work may be relevant in the treatment and diagnosis of TED and may boost molecular studies regarding TED. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-022-00412-0. |
format | Online Article Text |
id | pubmed-9461120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-94611202022-09-10 Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis Hu, Jinxing Zhou, Shan Guo, Weiying Hum Genomics Primary Research BACKGROUND: Thyroid eye disease (TED) is the most common orbital pathology that occurs in up to 50% of patients with Graves’ disease. Herein, we aimed at discovering the possible hub genes and pathways involved in TED based on bioinformatical approaches. RESULTS: The GSE105149 and GSE58331 datasets were downloaded from the Gene Expression Omnibus (GEO) database and merged for identifying TED-associated modules by weighted gene coexpression network analysis (WGCNA) and local maximal quasi-clique merger (lmQCM) analysis. EdgeR was run to screen differentially expressed genes (DEGs). Transcription factor (TF), microRNA (miR) and drug prediction analyses were performed using ToppGene suite. Function enrichment analysis was used to investigate the biological function of genes. Protein–protein interaction (PPI) analysis was performed based on the intersection between the list of genes obtained by WGCNA, lmQCM and DEGs, and hub genes were identified using the MCODE plugin. Based on the overlap of 497 genes retrieved from the different approaches, a robust TED coexpression network was constructed and 11 genes (ATP6V1A, PTGES3, PSMD12, PSMA4, METAP2, DNAJA1, PSMA1, UBQLN1, CCT2, VBP1 and NAA50) were identified as hub genes. Key TFs regulating genes in the TED-associated coexpression network, including NFRKB, ZNF711, ZNF407 and MORC2, and miRs including hsa-miR-144, hsa-miR-3662, hsa-miR-12136 and hsa-miR-3646, were identified. Genes in the coexpression network were enriched in the biological processes including proteasomal protein catabolic process and proteasome-mediated ubiquitin-dependent protein catabolic process and the pathways of endocytosis and ubiquitin-mediated proteolysis. Drugs perturbing genes in the coexpression network were also predicted and included enzyme inhibitors, chlorodiphenyl and finasteride. CONCLUSIONS: For the first time, TED-associated coexpression network was constructed and key genes and their functions, as well as TFs, miRs and drugs, were predicted. The results of the present work may be relevant in the treatment and diagnosis of TED and may boost molecular studies regarding TED. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-022-00412-0. BioMed Central 2022-09-08 /pmc/articles/PMC9461120/ /pubmed/36076300 http://dx.doi.org/10.1186/s40246-022-00412-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Primary Research Hu, Jinxing Zhou, Shan Guo, Weiying Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis |
title | Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis |
title_full | Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis |
title_fullStr | Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis |
title_full_unstemmed | Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis |
title_short | Construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis |
title_sort | construction of the coexpression network involved in the pathogenesis of thyroid eye disease via bioinformatics analysis |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9461120/ https://www.ncbi.nlm.nih.gov/pubmed/36076300 http://dx.doi.org/10.1186/s40246-022-00412-0 |
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