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Construction of lncRNA-Mediated Competing Endogenous RNA Networks Correlated With T2 Asthma

Background: Precise classification has been reported as a central challenge in the clinical research on diagnosis and prediction of treatment efficacy in asthma. In this study, the aim was to investigate the underlying competing endogenous RNA network mechanism of asthma, especially T2 asthma, as we...

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Autores principales: Wang, Zihan, Zhang, Jintao, Feng, Tao, Zhang, Dong, Pan, Yun, Liu, Xiaofei, Xu, Jiawei, Qiao, Xinrui, Cui, Wenjing, Dong, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035528/
https://www.ncbi.nlm.nih.gov/pubmed/35480331
http://dx.doi.org/10.3389/fgene.2022.872499
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author Wang, Zihan
Zhang, Jintao
Feng, Tao
Zhang, Dong
Pan, Yun
Liu, Xiaofei
Xu, Jiawei
Qiao, Xinrui
Cui, Wenjing
Dong, Liang
author_facet Wang, Zihan
Zhang, Jintao
Feng, Tao
Zhang, Dong
Pan, Yun
Liu, Xiaofei
Xu, Jiawei
Qiao, Xinrui
Cui, Wenjing
Dong, Liang
author_sort Wang, Zihan
collection PubMed
description Background: Precise classification has been reported as a central challenge in the clinical research on diagnosis and prediction of treatment efficacy in asthma. In this study, the aim was to investigate the underlying competing endogenous RNA network mechanism of asthma, especially T2 asthma, as well as to find more diagnostic biomarkers and effective therapeutic targets. Methods: Multiple sets of T2 asthma airway biopsy transcription profiles were collected, which involved long non-coding RNA (lncRNA), mRNA, and microRNA (miRNA). DIANA-LncBase, targetscan, mirwalk, and miRDB databases were employed to predict interactions between lncRNAs, miRNAs and target mRNAs. To identify mRNAs correlated with T2 asthma, differential expression and network analyses were conducted through weighted gene co-expression network analysis (WGCNA). Subsequently, the expressions of potential biomarkers were examined through qRT-PCR analysis in the T2 asthma coreinteracting cellular factor (IL-13/IL-33) induced experimental model. Lastly, the ceRNA network was confirmed by plasmid transfection and RNAi experiments in a 16HBE cell line. Results: 30 lncRNAs, 22 miRNAs and 202 mRNAs were differentially expressed in airway biopsies from T2 asthma patients. As indicated by the ROC analysis, the lncRNA, PCAT19, had high diagnostic accuracy (AUC >0.9) in distinguishing T2 asthma patients from non-T2 asthma patients and healthy controls. Furthermore, a competing ceRNA network was established, consisting of 13 lncRNAs, 12 miRNAs, as well as eight mRNAs. The reliability of this network was verified by testing several representative interactions in the network. Conclusion: To the best of our knowledge, this study has been the first to establish an lncRNA-mediated ceRNA regulatory network for studying T2 asthma. The findings of this study may elucidate the pathogenesis and help find potential therapeutic targets for T2 asthma. In T2 asthma, PCAT19-dominated ceRNA regulation networks may play a critical role, and PCAT19 may serve as a potential immune-related biomarker for asthma and other respiratory diseases correlated with eosinophilic inflammation.
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spelling pubmed-90355282022-04-26 Construction of lncRNA-Mediated Competing Endogenous RNA Networks Correlated With T2 Asthma Wang, Zihan Zhang, Jintao Feng, Tao Zhang, Dong Pan, Yun Liu, Xiaofei Xu, Jiawei Qiao, Xinrui Cui, Wenjing Dong, Liang Front Genet Genetics Background: Precise classification has been reported as a central challenge in the clinical research on diagnosis and prediction of treatment efficacy in asthma. In this study, the aim was to investigate the underlying competing endogenous RNA network mechanism of asthma, especially T2 asthma, as well as to find more diagnostic biomarkers and effective therapeutic targets. Methods: Multiple sets of T2 asthma airway biopsy transcription profiles were collected, which involved long non-coding RNA (lncRNA), mRNA, and microRNA (miRNA). DIANA-LncBase, targetscan, mirwalk, and miRDB databases were employed to predict interactions between lncRNAs, miRNAs and target mRNAs. To identify mRNAs correlated with T2 asthma, differential expression and network analyses were conducted through weighted gene co-expression network analysis (WGCNA). Subsequently, the expressions of potential biomarkers were examined through qRT-PCR analysis in the T2 asthma coreinteracting cellular factor (IL-13/IL-33) induced experimental model. Lastly, the ceRNA network was confirmed by plasmid transfection and RNAi experiments in a 16HBE cell line. Results: 30 lncRNAs, 22 miRNAs and 202 mRNAs were differentially expressed in airway biopsies from T2 asthma patients. As indicated by the ROC analysis, the lncRNA, PCAT19, had high diagnostic accuracy (AUC >0.9) in distinguishing T2 asthma patients from non-T2 asthma patients and healthy controls. Furthermore, a competing ceRNA network was established, consisting of 13 lncRNAs, 12 miRNAs, as well as eight mRNAs. The reliability of this network was verified by testing several representative interactions in the network. Conclusion: To the best of our knowledge, this study has been the first to establish an lncRNA-mediated ceRNA regulatory network for studying T2 asthma. The findings of this study may elucidate the pathogenesis and help find potential therapeutic targets for T2 asthma. In T2 asthma, PCAT19-dominated ceRNA regulation networks may play a critical role, and PCAT19 may serve as a potential immune-related biomarker for asthma and other respiratory diseases correlated with eosinophilic inflammation. Frontiers Media S.A. 2022-04-11 /pmc/articles/PMC9035528/ /pubmed/35480331 http://dx.doi.org/10.3389/fgene.2022.872499 Text en Copyright © 2022 Wang, Zhang, Feng, Zhang, Pan, Liu, Xu, Qiao, Cui and Dong. 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 Genetics
Wang, Zihan
Zhang, Jintao
Feng, Tao
Zhang, Dong
Pan, Yun
Liu, Xiaofei
Xu, Jiawei
Qiao, Xinrui
Cui, Wenjing
Dong, Liang
Construction of lncRNA-Mediated Competing Endogenous RNA Networks Correlated With T2 Asthma
title Construction of lncRNA-Mediated Competing Endogenous RNA Networks Correlated With T2 Asthma
title_full Construction of lncRNA-Mediated Competing Endogenous RNA Networks Correlated With T2 Asthma
title_fullStr Construction of lncRNA-Mediated Competing Endogenous RNA Networks Correlated With T2 Asthma
title_full_unstemmed Construction of lncRNA-Mediated Competing Endogenous RNA Networks Correlated With T2 Asthma
title_short Construction of lncRNA-Mediated Competing Endogenous RNA Networks Correlated With T2 Asthma
title_sort construction of lncrna-mediated competing endogenous rna networks correlated with t2 asthma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035528/
https://www.ncbi.nlm.nih.gov/pubmed/35480331
http://dx.doi.org/10.3389/fgene.2022.872499
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