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Mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study

BACKGROUND: Osteoarthritis is a chronic degenerative joint disease, and increasing evidences suggest that the pathogenic mechanism involves immune system and inflammation. AIMS: The aim of current study was to uncover hub genes linked to immune infiltration in osteoarthritis synovial tissue using co...

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Autores principales: Zhang, Qingyu, Sun, Chao, Liu, Xuchang, Zhu, Chao, Ma, Chuncheng, Feng, Rongjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9862811/
https://www.ncbi.nlm.nih.gov/pubmed/36681837
http://dx.doi.org/10.1186/s13018-023-03541-x
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author Zhang, Qingyu
Sun, Chao
Liu, Xuchang
Zhu, Chao
Ma, Chuncheng
Feng, Rongjie
author_facet Zhang, Qingyu
Sun, Chao
Liu, Xuchang
Zhu, Chao
Ma, Chuncheng
Feng, Rongjie
author_sort Zhang, Qingyu
collection PubMed
description BACKGROUND: Osteoarthritis is a chronic degenerative joint disease, and increasing evidences suggest that the pathogenic mechanism involves immune system and inflammation. AIMS: The aim of current study was to uncover hub genes linked to immune infiltration in osteoarthritis synovial tissue using comprehensive bioinformatics analysis and experimental confirmation. METHODS: Multiple microarray datasets (GSE55457, GSE55235, GSE12021 and GSE1919) for osteoarthritis in Gene Expression Omnibus database were downloaded for analysis. Differentially expressed genes (DEGs) were identified using Limma package in R software, and immune infiltration was evaluated by CIBERSORT algorithm. Then weighted gene co-expression network analysis (WGCNA) was performed to uncover immune infiltration-associated gene modules. Protein–protein interaction (PPI) network was constructed to select the hub genes, and the tissue distribution of these genes was analyzed using BioGPS database. Finally, the expression pattern of these genes was confirmed by RT-qPCR using clinical samples. RESULTS: Totally 181 DEGs between osteoarthritis and normal control were screened. Macrophages, mast cells, memory CD4 T cells and B cells accounted for the majority of immune cell composition in synovial tissue. Osteoarthritis synovial showed high abundance of infiltrating resting mast cells, B cells memory and plasma cells. WGCNA screened 93 DEGs related to osteoarthritis immune infiltration. These genes were involved in TNF signaling pathway, IL-17 signaling pathway, response to steroid hormone, glucocorticoid and corticosteroid. Ten hub genes including MYC, JUN, DUSP1, NFKBIA, VEGFA, ATF3, IL-6, PTGS2, IL1B and SOCS3 were selected by using PPI network. Among them, four genes (MYC, JUN, DUSP1 and NFKBIA) specifically expressed in immune system were identified and clinical samples revealed consistent change of these four genes in synovial tissue retrieved from patients with osteoarthritis. CONCLUSION: A 4-gene-based diagnostic model was developed, which had well predictive performance in osteoarthritis. MYC, JUN, DUSP1 and NFKBIA might be biomarkers and potential therapeutic targets in osteoarthritis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-023-03541-x.
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spelling pubmed-98628112023-01-22 Mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study Zhang, Qingyu Sun, Chao Liu, Xuchang Zhu, Chao Ma, Chuncheng Feng, Rongjie J Orthop Surg Res Research Article BACKGROUND: Osteoarthritis is a chronic degenerative joint disease, and increasing evidences suggest that the pathogenic mechanism involves immune system and inflammation. AIMS: The aim of current study was to uncover hub genes linked to immune infiltration in osteoarthritis synovial tissue using comprehensive bioinformatics analysis and experimental confirmation. METHODS: Multiple microarray datasets (GSE55457, GSE55235, GSE12021 and GSE1919) for osteoarthritis in Gene Expression Omnibus database were downloaded for analysis. Differentially expressed genes (DEGs) were identified using Limma package in R software, and immune infiltration was evaluated by CIBERSORT algorithm. Then weighted gene co-expression network analysis (WGCNA) was performed to uncover immune infiltration-associated gene modules. Protein–protein interaction (PPI) network was constructed to select the hub genes, and the tissue distribution of these genes was analyzed using BioGPS database. Finally, the expression pattern of these genes was confirmed by RT-qPCR using clinical samples. RESULTS: Totally 181 DEGs between osteoarthritis and normal control were screened. Macrophages, mast cells, memory CD4 T cells and B cells accounted for the majority of immune cell composition in synovial tissue. Osteoarthritis synovial showed high abundance of infiltrating resting mast cells, B cells memory and plasma cells. WGCNA screened 93 DEGs related to osteoarthritis immune infiltration. These genes were involved in TNF signaling pathway, IL-17 signaling pathway, response to steroid hormone, glucocorticoid and corticosteroid. Ten hub genes including MYC, JUN, DUSP1, NFKBIA, VEGFA, ATF3, IL-6, PTGS2, IL1B and SOCS3 were selected by using PPI network. Among them, four genes (MYC, JUN, DUSP1 and NFKBIA) specifically expressed in immune system were identified and clinical samples revealed consistent change of these four genes in synovial tissue retrieved from patients with osteoarthritis. CONCLUSION: A 4-gene-based diagnostic model was developed, which had well predictive performance in osteoarthritis. MYC, JUN, DUSP1 and NFKBIA might be biomarkers and potential therapeutic targets in osteoarthritis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-023-03541-x. BioMed Central 2023-01-21 /pmc/articles/PMC9862811/ /pubmed/36681837 http://dx.doi.org/10.1186/s13018-023-03541-x Text en © The Author(s) 2023 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 Research Article
Zhang, Qingyu
Sun, Chao
Liu, Xuchang
Zhu, Chao
Ma, Chuncheng
Feng, Rongjie
Mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study
title Mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study
title_full Mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study
title_fullStr Mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study
title_full_unstemmed Mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study
title_short Mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study
title_sort mechanism of immune infiltration in synovial tissue of osteoarthritis: a gene expression-based study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9862811/
https://www.ncbi.nlm.nih.gov/pubmed/36681837
http://dx.doi.org/10.1186/s13018-023-03541-x
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