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Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways
BACKGROUND: Allergic rhinitis (AR) is an important risk factor for the development of asthma. The “unified airway” theory considers the upper and lower airways as a morphological and functional whole. However, studies exploring biomarkers linking the upper and lower airways in allergic disease are l...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9888248/ https://www.ncbi.nlm.nih.gov/pubmed/36733482 http://dx.doi.org/10.3389/fimmu.2023.1048195 |
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author | Wang, Mingming Gong, Li Luo, Yang He, Shaojuan Zhang, Xianxing Xie, Xinyu Li, Xuezhong Feng, Xin |
author_facet | Wang, Mingming Gong, Li Luo, Yang He, Shaojuan Zhang, Xianxing Xie, Xinyu Li, Xuezhong Feng, Xin |
author_sort | Wang, Mingming |
collection | PubMed |
description | BACKGROUND: Allergic rhinitis (AR) is an important risk factor for the development of asthma. The “unified airway” theory considers the upper and lower airways as a morphological and functional whole. However, studies exploring biomarkers linking the upper and lower airways in allergic disease are lacking, which may provide insight into the mechanisms underlying AR comorbid asthma. PURPOSE: To integrate bioinformatics techniques to explore biomarkers in airway allergic diseases, and to provide a molecular etiology profile for preventing the development of asthma in AR patients. METHODS: Biomarkers were screened by identifying key genes common between AR and asthma through WGCNA and differential gene analysis. GO and KEGG analyses were performed using DAVID. Immuno-infiltration analysis was performed by CIBERSORTx. The predictive value of CST1 to distinguish Th2-high asthma was determined by ROC curves. GSEA was used to analyze the signaling pathways involved in CST1. TargetScan and miRNet were combined with GSE142237 to construct ceRNA network. CMap was used to explore potential therapeutic drugs. RESULTS: Validation of datasets showed that CST1 was the only gene that was up-regulated in both upper and lower airways in patients with AR and asthma, and correlation heatmaps showed that CST1 was the gene with the highest sum of correlation coefficients. GO and KEGG analysis demonstrated that the lower airways of AR patients were mainly involved in inflammatory and immune responses, similar to asthma. Immune infiltration showed that CST1 was mainly positively correlated with activated CD4 memory T cells. According to the ROC curve, CST1 showed excellent diagnostic efficiency for Th2-high asthma. GSEA indicated that CST1 was involved in the FcϵRI signaling pathway and O-glycan biosynthesis. A ceRNA network including the lncRNAs KCNQ1OT1 and NEAT1 was constructed. Four drugs, including verrucarin-A, had the potential to prevent the development of asthma in AR patients. In addition, corticosteroids were found to downregulate CST1 expression. CONCLUSION: CST1 plays a key role in the development of AR comorbid asthma and may be a biomarker for airway allergic diseases. Targeted treatment of CST1 has the potential to prevent the development of asthma in AR patients and deserves further study. |
format | Online Article Text |
id | pubmed-9888248 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98882482023-02-01 Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways Wang, Mingming Gong, Li Luo, Yang He, Shaojuan Zhang, Xianxing Xie, Xinyu Li, Xuezhong Feng, Xin Front Immunol Immunology BACKGROUND: Allergic rhinitis (AR) is an important risk factor for the development of asthma. The “unified airway” theory considers the upper and lower airways as a morphological and functional whole. However, studies exploring biomarkers linking the upper and lower airways in allergic disease are lacking, which may provide insight into the mechanisms underlying AR comorbid asthma. PURPOSE: To integrate bioinformatics techniques to explore biomarkers in airway allergic diseases, and to provide a molecular etiology profile for preventing the development of asthma in AR patients. METHODS: Biomarkers were screened by identifying key genes common between AR and asthma through WGCNA and differential gene analysis. GO and KEGG analyses were performed using DAVID. Immuno-infiltration analysis was performed by CIBERSORTx. The predictive value of CST1 to distinguish Th2-high asthma was determined by ROC curves. GSEA was used to analyze the signaling pathways involved in CST1. TargetScan and miRNet were combined with GSE142237 to construct ceRNA network. CMap was used to explore potential therapeutic drugs. RESULTS: Validation of datasets showed that CST1 was the only gene that was up-regulated in both upper and lower airways in patients with AR and asthma, and correlation heatmaps showed that CST1 was the gene with the highest sum of correlation coefficients. GO and KEGG analysis demonstrated that the lower airways of AR patients were mainly involved in inflammatory and immune responses, similar to asthma. Immune infiltration showed that CST1 was mainly positively correlated with activated CD4 memory T cells. According to the ROC curve, CST1 showed excellent diagnostic efficiency for Th2-high asthma. GSEA indicated that CST1 was involved in the FcϵRI signaling pathway and O-glycan biosynthesis. A ceRNA network including the lncRNAs KCNQ1OT1 and NEAT1 was constructed. Four drugs, including verrucarin-A, had the potential to prevent the development of asthma in AR patients. In addition, corticosteroids were found to downregulate CST1 expression. CONCLUSION: CST1 plays a key role in the development of AR comorbid asthma and may be a biomarker for airway allergic diseases. Targeted treatment of CST1 has the potential to prevent the development of asthma in AR patients and deserves further study. Frontiers Media S.A. 2023-01-17 /pmc/articles/PMC9888248/ /pubmed/36733482 http://dx.doi.org/10.3389/fimmu.2023.1048195 Text en Copyright © 2023 Wang, Gong, Luo, He, Zhang, Xie, Li and Feng 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 Wang, Mingming Gong, Li Luo, Yang He, Shaojuan Zhang, Xianxing Xie, Xinyu Li, Xuezhong Feng, Xin Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways |
title | Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways |
title_full | Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways |
title_fullStr | Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways |
title_full_unstemmed | Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways |
title_short | Transcriptomic analysis of asthma and allergic rhinitis reveals CST1 as a biomarker of unified airways |
title_sort | transcriptomic analysis of asthma and allergic rhinitis reveals cst1 as a biomarker of unified airways |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9888248/ https://www.ncbi.nlm.nih.gov/pubmed/36733482 http://dx.doi.org/10.3389/fimmu.2023.1048195 |
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