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Bioinformatics-based analysis of potential candidates chromatin regulators for immune infiltration in osteoarthritis

BACKGROUND: Through the bioinformatics analysis to screen out the potential chromatin regulators (CRs) under the immune infiltration of osteoarthritis (OA), thus providing some theoretical support for future studies of epigenetic mechanisms under OA immune infiltration. METHODS: By integrating CRs a...

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Autores principales: Wang, Weiwei, Ou, Zhixue, Peng, Jianlan, Wang, Ning, Zhou, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783407/
https://www.ncbi.nlm.nih.gov/pubmed/36550476
http://dx.doi.org/10.1186/s12891-022-06098-8
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author Wang, Weiwei
Ou, Zhixue
Peng, Jianlan
Wang, Ning
Zhou, Yi
author_facet Wang, Weiwei
Ou, Zhixue
Peng, Jianlan
Wang, Ning
Zhou, Yi
author_sort Wang, Weiwei
collection PubMed
description BACKGROUND: Through the bioinformatics analysis to screen out the potential chromatin regulators (CRs) under the immune infiltration of osteoarthritis (OA), thus providing some theoretical support for future studies of epigenetic mechanisms under OA immune infiltration. METHODS: By integrating CRs and the OA gene expression matrix, we performed weighted gene co-expression network analysis (WGCNA), differential analysis, and further screened Hub genes by protein-protein interaction (PPI) analysis. Using the OA gene expression matrix, immune infiltration extraction and quantification were performed to analyze the correlations and differences between immune infiltrating cells and their functions. By virtue of these Hub genes, Hub gene association analysis was completed and their upstream miRNAs were predicted by the FunRich software. Moreover, a risk model was established to analyze the risk probability of associated CRs in OA, and the confidence of the results was validated by the validation dataset. RESULTS: This research acquired a total of 32 overlapping genes, and 10 Hub genes were further identified. The strongest positive correlation between dendritic cells and mast cells and the strongest negative correlation between parainflammation and Type I IFN reponse. In the OA group DCs, iDCs, macrophages, MCs, APC co-inhibition, and CCR were significantly increased, whereas B cells, NK cells, Th2 cells, TIL, and T cell co-stimulation were significantly decreased. The risk model results revealed that BRD1 might be an independent risk factor for OA, and the validation dataset results are consistent with it. 60 upstream miRNAs of OA-related CRs were predicted by the FunRich software. CONCLUSION: This study identified certain potential CRs and miRNAs that could regulate OA immunity, thus providing certain theoretical supports for future epigenetic mechanism studies on the immune infiltration of OA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-022-06098-8.
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spelling pubmed-97834072022-12-24 Bioinformatics-based analysis of potential candidates chromatin regulators for immune infiltration in osteoarthritis Wang, Weiwei Ou, Zhixue Peng, Jianlan Wang, Ning Zhou, Yi BMC Musculoskelet Disord Research BACKGROUND: Through the bioinformatics analysis to screen out the potential chromatin regulators (CRs) under the immune infiltration of osteoarthritis (OA), thus providing some theoretical support for future studies of epigenetic mechanisms under OA immune infiltration. METHODS: By integrating CRs and the OA gene expression matrix, we performed weighted gene co-expression network analysis (WGCNA), differential analysis, and further screened Hub genes by protein-protein interaction (PPI) analysis. Using the OA gene expression matrix, immune infiltration extraction and quantification were performed to analyze the correlations and differences between immune infiltrating cells and their functions. By virtue of these Hub genes, Hub gene association analysis was completed and their upstream miRNAs were predicted by the FunRich software. Moreover, a risk model was established to analyze the risk probability of associated CRs in OA, and the confidence of the results was validated by the validation dataset. RESULTS: This research acquired a total of 32 overlapping genes, and 10 Hub genes were further identified. The strongest positive correlation between dendritic cells and mast cells and the strongest negative correlation between parainflammation and Type I IFN reponse. In the OA group DCs, iDCs, macrophages, MCs, APC co-inhibition, and CCR were significantly increased, whereas B cells, NK cells, Th2 cells, TIL, and T cell co-stimulation were significantly decreased. The risk model results revealed that BRD1 might be an independent risk factor for OA, and the validation dataset results are consistent with it. 60 upstream miRNAs of OA-related CRs were predicted by the FunRich software. CONCLUSION: This study identified certain potential CRs and miRNAs that could regulate OA immunity, thus providing certain theoretical supports for future epigenetic mechanism studies on the immune infiltration of OA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-022-06098-8. BioMed Central 2022-12-23 /pmc/articles/PMC9783407/ /pubmed/36550476 http://dx.doi.org/10.1186/s12891-022-06098-8 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 Research
Wang, Weiwei
Ou, Zhixue
Peng, Jianlan
Wang, Ning
Zhou, Yi
Bioinformatics-based analysis of potential candidates chromatin regulators for immune infiltration in osteoarthritis
title Bioinformatics-based analysis of potential candidates chromatin regulators for immune infiltration in osteoarthritis
title_full Bioinformatics-based analysis of potential candidates chromatin regulators for immune infiltration in osteoarthritis
title_fullStr Bioinformatics-based analysis of potential candidates chromatin regulators for immune infiltration in osteoarthritis
title_full_unstemmed Bioinformatics-based analysis of potential candidates chromatin regulators for immune infiltration in osteoarthritis
title_short Bioinformatics-based analysis of potential candidates chromatin regulators for immune infiltration in osteoarthritis
title_sort bioinformatics-based analysis of potential candidates chromatin regulators for immune infiltration in osteoarthritis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783407/
https://www.ncbi.nlm.nih.gov/pubmed/36550476
http://dx.doi.org/10.1186/s12891-022-06098-8
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