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Discovery of CLEC2B as a diagnostic biomarker and screening of celastrol as a candidate drug for psoriatic arthritis through bioinformatics analysis

BACKGROUND: Psoriatic arthritis (PSA) is a chronic, immune-mediated inflammatory joint disease that is liked to mortality due to cardiovascular disease. Diagnostic markers and effective therapeutic options for PSA remain limited due to the lack of understanding of the pathogenesis. We aimed to ident...

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Autores principales: Niu, Min, Yuan, Jingman, Yan, Meixi, Yang, Ge, Yan, Ziyi, Yang, Xichao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10226212/
https://www.ncbi.nlm.nih.gov/pubmed/37246213
http://dx.doi.org/10.1186/s13018-023-03843-0
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author Niu, Min
Yuan, Jingman
Yan, Meixi
Yang, Ge
Yan, Ziyi
Yang, Xichao
author_facet Niu, Min
Yuan, Jingman
Yan, Meixi
Yang, Ge
Yan, Ziyi
Yang, Xichao
author_sort Niu, Min
collection PubMed
description BACKGROUND: Psoriatic arthritis (PSA) is a chronic, immune-mediated inflammatory joint disease that is liked to mortality due to cardiovascular disease. Diagnostic markers and effective therapeutic options for PSA remain limited due to the lack of understanding of the pathogenesis. We aimed to identify potential diagnostic markers and screen the therapeutic compounds for PSA based on bioinformatics analysis. METHODS: Differentially expressed genes (DEGs) of PSA were identified from the GSE61281 dataset. WGCNA was used to identify PSA-related modules and prognostic biomarkers. Clinical samples were collected to validate the expression of the diagnostic gene. These DEGs were subjected to the CMap database for the identification of therapeutic candidates for PSA. Potential pathways and targets for drug candidates to treat PSA were predicted using Network Pharmacology. Molecular docking techniques were used to validate key targets. RESULTS: CLEC2B was identified as a diagnostic marker for PSA patients (AUC > 0.8) and was significantly upregulated in blood samples. In addition, celastrol was identified as a candidate drug for PSA. Subsequently, the network pharmacology approach identified four core targets (IL6, TNF, GAPDH, and AKT1) of celastrol and revealed that celastrol could treat PSA by modulating inflammatory-related pathways. Finally, molecular docking demonstrated stable binding of celastrol to four core targets in the treatment of PSA. Animal experiments indicated celastrol alleviated inflammatory response in the mannan-induced PSA. CONCLUSION: CLEC2B was a diagnostic marker for PSA patients. Celastrol was identified as a potential therapeutic drug for PSA via regulating immunity and inflammation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-023-03843-0.
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spelling pubmed-102262122023-05-30 Discovery of CLEC2B as a diagnostic biomarker and screening of celastrol as a candidate drug for psoriatic arthritis through bioinformatics analysis Niu, Min Yuan, Jingman Yan, Meixi Yang, Ge Yan, Ziyi Yang, Xichao J Orthop Surg Res Research Article BACKGROUND: Psoriatic arthritis (PSA) is a chronic, immune-mediated inflammatory joint disease that is liked to mortality due to cardiovascular disease. Diagnostic markers and effective therapeutic options for PSA remain limited due to the lack of understanding of the pathogenesis. We aimed to identify potential diagnostic markers and screen the therapeutic compounds for PSA based on bioinformatics analysis. METHODS: Differentially expressed genes (DEGs) of PSA were identified from the GSE61281 dataset. WGCNA was used to identify PSA-related modules and prognostic biomarkers. Clinical samples were collected to validate the expression of the diagnostic gene. These DEGs were subjected to the CMap database for the identification of therapeutic candidates for PSA. Potential pathways and targets for drug candidates to treat PSA were predicted using Network Pharmacology. Molecular docking techniques were used to validate key targets. RESULTS: CLEC2B was identified as a diagnostic marker for PSA patients (AUC > 0.8) and was significantly upregulated in blood samples. In addition, celastrol was identified as a candidate drug for PSA. Subsequently, the network pharmacology approach identified four core targets (IL6, TNF, GAPDH, and AKT1) of celastrol and revealed that celastrol could treat PSA by modulating inflammatory-related pathways. Finally, molecular docking demonstrated stable binding of celastrol to four core targets in the treatment of PSA. Animal experiments indicated celastrol alleviated inflammatory response in the mannan-induced PSA. CONCLUSION: CLEC2B was a diagnostic marker for PSA patients. Celastrol was identified as a potential therapeutic drug for PSA via regulating immunity and inflammation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-023-03843-0. BioMed Central 2023-05-29 /pmc/articles/PMC10226212/ /pubmed/37246213 http://dx.doi.org/10.1186/s13018-023-03843-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Niu, Min
Yuan, Jingman
Yan, Meixi
Yang, Ge
Yan, Ziyi
Yang, Xichao
Discovery of CLEC2B as a diagnostic biomarker and screening of celastrol as a candidate drug for psoriatic arthritis through bioinformatics analysis
title Discovery of CLEC2B as a diagnostic biomarker and screening of celastrol as a candidate drug for psoriatic arthritis through bioinformatics analysis
title_full Discovery of CLEC2B as a diagnostic biomarker and screening of celastrol as a candidate drug for psoriatic arthritis through bioinformatics analysis
title_fullStr Discovery of CLEC2B as a diagnostic biomarker and screening of celastrol as a candidate drug for psoriatic arthritis through bioinformatics analysis
title_full_unstemmed Discovery of CLEC2B as a diagnostic biomarker and screening of celastrol as a candidate drug for psoriatic arthritis through bioinformatics analysis
title_short Discovery of CLEC2B as a diagnostic biomarker and screening of celastrol as a candidate drug for psoriatic arthritis through bioinformatics analysis
title_sort discovery of clec2b as a diagnostic biomarker and screening of celastrol as a candidate drug for psoriatic arthritis through bioinformatics analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10226212/
https://www.ncbi.nlm.nih.gov/pubmed/37246213
http://dx.doi.org/10.1186/s13018-023-03843-0
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