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

Zihan Wang; Jintao Zhang; Tao Feng; Dong Zhang; Yun Pan; Xiaofei Liu; Jiawei Xu; Xinrui Qiao; Wenjing Cui; Liang Dong

doi:10.3389/fgene.2022.872499

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

Front Genet. 2022 Apr 11:13:872499. doi: 10.3389/fgene.2022.872499. eCollection 2022.

Authors

Zihan Wang¹, Jintao Zhang¹, Tao Feng², Dong Zhang¹, Yun Pan¹, Xiaofei Liu³, Jiawei Xu³, Xinrui Qiao¹, Wenjing Cui¹, Liang Dong^{1

3}

Affiliations

¹ Department of Respiratory, Shandong Qianfoshan Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
² Department of Respiratory Medicine, Shengli Oilfield Central Hospital, Dongying, China.
³ Department of Respiratory, Shandong Provincial Qianfoshan Hospital, Shandong University, The First Affiliated Hospital of Shandong First Medical University, Shandong Institute of Respiratory Diseases, Jinan, China.

Abstract

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.

Keywords: WGCNA; airway biopsy; asthma; competing endogenous RNA; long non-coding RNA; microRNA.