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IL36G is associated with cutaneous antiviral competence in psoriasis

BACKGROUND: Psoriasis is a common inflammatory skin disease that has a great impact on patients’ physical and mental health. However, the causes and underlying molecular mechanisms of psoriasis are still largely unknown. METHODS: The expression profiles of genes from psoriatic lesion samples and ski...

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Autores principales: Lu, You-Wang, Chen, Yong-Jun, Shi, Nian, Yang, Lu-Hui, Wang, Hong-Mei, Dong, Rong-Jing, Kuang, Yi-Qun, Li, Yu-Ye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510771/
https://www.ncbi.nlm.nih.gov/pubmed/36172384
http://dx.doi.org/10.3389/fimmu.2022.971071
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author Lu, You-Wang
Chen, Yong-Jun
Shi, Nian
Yang, Lu-Hui
Wang, Hong-Mei
Dong, Rong-Jing
Kuang, Yi-Qun
Li, Yu-Ye
author_facet Lu, You-Wang
Chen, Yong-Jun
Shi, Nian
Yang, Lu-Hui
Wang, Hong-Mei
Dong, Rong-Jing
Kuang, Yi-Qun
Li, Yu-Ye
author_sort Lu, You-Wang
collection PubMed
description BACKGROUND: Psoriasis is a common inflammatory skin disease that has a great impact on patients’ physical and mental health. However, the causes and underlying molecular mechanisms of psoriasis are still largely unknown. METHODS: The expression profiles of genes from psoriatic lesion samples and skin samples from healthy controls were integrated via the sva software package, and differentially expressed genes (DEGs) between psoriasis and healthy skin were screened by the limma package. Furthermore, GO and KEGG pathway enrichments for the DEGs were performed using the Clusterprofiler package. Protein–protein interaction (PPI) networks for the DEGs were then constructed to identify hub genes. scGESA analysis was performed on a single-cell RNA sequencing dataset via irGSEA. In order to find the cytokines correlated with the hub genes expression, single cell weighted gene co-expression network analyses (scWGCNA) were utilized to build a gene co-expression network. Furthermore, the featured genes of psoriasis found in suprabasal keratinocytes were intersected with hub genes. We then analyzed the expression of the intersection genes and cytokines in the integrated dataset. After that, we used other datasets to reveal the changes in the intersection genes’ expression levels during biological therapy. The relationship between intersection genes and PASI scores was also explored. RESULTS: We identified 148 DEGs between psoriatic and healthy samples. GO and KEGG pathway enrichment analysis suggested that DEGs are mainly involved in the defense response to other organisms. The PPI network showed that 11 antiviral proteins (AVPs) were hub genes. scGSEA analysis in the single-cell transcriptome dataset showed that those hub genes are highly expressed in keratinocytes, especially in suprabasal keratinocytes. ISG15, MX1, IFI44L, and IFI27 were the characteristic genes of psoriasis in suprabasal keratinocytes. scWGCNA showed that three cytokines—IL36G, MIF, and IL17RA—were co-expressed in the turquoise module. Only interleukin-36 gamma (IL36G) was positively correlated with AVPs in the integrated dataset. IL36G and AVPs were found co-expressed in a substantial number of suprabasal keratinocytes. Furthermore, we found that the expression levels of IL36G and the 4 AVPs showed positive correlation with PASI score in patients with psoriasis, and that these levels decreased significantly during treatment with biological therapies, but not with methotrexate. CONCLUSION: IL36G and antiviral proteins may be closely related with the pathogenesis of psoriasis, and they may represent new candidate molecular markers for the occurrence and severity of psoriasis.
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spelling pubmed-95107712022-09-27 IL36G is associated with cutaneous antiviral competence in psoriasis Lu, You-Wang Chen, Yong-Jun Shi, Nian Yang, Lu-Hui Wang, Hong-Mei Dong, Rong-Jing Kuang, Yi-Qun Li, Yu-Ye Front Immunol Immunology BACKGROUND: Psoriasis is a common inflammatory skin disease that has a great impact on patients’ physical and mental health. However, the causes and underlying molecular mechanisms of psoriasis are still largely unknown. METHODS: The expression profiles of genes from psoriatic lesion samples and skin samples from healthy controls were integrated via the sva software package, and differentially expressed genes (DEGs) between psoriasis and healthy skin were screened by the limma package. Furthermore, GO and KEGG pathway enrichments for the DEGs were performed using the Clusterprofiler package. Protein–protein interaction (PPI) networks for the DEGs were then constructed to identify hub genes. scGESA analysis was performed on a single-cell RNA sequencing dataset via irGSEA. In order to find the cytokines correlated with the hub genes expression, single cell weighted gene co-expression network analyses (scWGCNA) were utilized to build a gene co-expression network. Furthermore, the featured genes of psoriasis found in suprabasal keratinocytes were intersected with hub genes. We then analyzed the expression of the intersection genes and cytokines in the integrated dataset. After that, we used other datasets to reveal the changes in the intersection genes’ expression levels during biological therapy. The relationship between intersection genes and PASI scores was also explored. RESULTS: We identified 148 DEGs between psoriatic and healthy samples. GO and KEGG pathway enrichment analysis suggested that DEGs are mainly involved in the defense response to other organisms. The PPI network showed that 11 antiviral proteins (AVPs) were hub genes. scGSEA analysis in the single-cell transcriptome dataset showed that those hub genes are highly expressed in keratinocytes, especially in suprabasal keratinocytes. ISG15, MX1, IFI44L, and IFI27 were the characteristic genes of psoriasis in suprabasal keratinocytes. scWGCNA showed that three cytokines—IL36G, MIF, and IL17RA—were co-expressed in the turquoise module. Only interleukin-36 gamma (IL36G) was positively correlated with AVPs in the integrated dataset. IL36G and AVPs were found co-expressed in a substantial number of suprabasal keratinocytes. Furthermore, we found that the expression levels of IL36G and the 4 AVPs showed positive correlation with PASI score in patients with psoriasis, and that these levels decreased significantly during treatment with biological therapies, but not with methotrexate. CONCLUSION: IL36G and antiviral proteins may be closely related with the pathogenesis of psoriasis, and they may represent new candidate molecular markers for the occurrence and severity of psoriasis. Frontiers Media S.A. 2022-09-12 /pmc/articles/PMC9510771/ /pubmed/36172384 http://dx.doi.org/10.3389/fimmu.2022.971071 Text en Copyright © 2022 Lu, Chen, Shi, Yang, Wang, Dong, Kuang and Li https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Lu, You-Wang
Chen, Yong-Jun
Shi, Nian
Yang, Lu-Hui
Wang, Hong-Mei
Dong, Rong-Jing
Kuang, Yi-Qun
Li, Yu-Ye
IL36G is associated with cutaneous antiviral competence in psoriasis
title IL36G is associated with cutaneous antiviral competence in psoriasis
title_full IL36G is associated with cutaneous antiviral competence in psoriasis
title_fullStr IL36G is associated with cutaneous antiviral competence in psoriasis
title_full_unstemmed IL36G is associated with cutaneous antiviral competence in psoriasis
title_short IL36G is associated with cutaneous antiviral competence in psoriasis
title_sort il36g is associated with cutaneous antiviral competence in psoriasis
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510771/
https://www.ncbi.nlm.nih.gov/pubmed/36172384
http://dx.doi.org/10.3389/fimmu.2022.971071
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