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Am J Perinatol 2022; 39(15): 1702-1710
DOI: 10.1055/s-0041-1726124
Original Article

Integrated MicroRNA–mRNA Analyses of Distinct Expression Profiles in Hyperoxia-Induced Bronchopulmonary Dysplasia in Neonatal Mice

Chengqiang Wang
1   Public Health, Guilin Medical University, Lingui, Guilin, People's Republic of China
,
Sheng Zhang
2   Affiliated BaYi Children's Hospital, Seventh Medical Center of People's Liberation Army General Hospital, Dongcheng, Beijing, People's Republic of China
3   Beijing Key Laboratory of Pediatric Organ Failure, Dongcheng, Beijing, People's Republic of China
,
Lina Zhu
2   Affiliated BaYi Children's Hospital, Seventh Medical Center of People's Liberation Army General Hospital, Dongcheng, Beijing, People's Republic of China
,
Jun Duan
4   Department of Pediatrics, the First Affiliated Hospital of Anhui Medical University, Shushan, Hefei, People's Republic of China
,
Bo Huang
1   Public Health, Guilin Medical University, Lingui, Guilin, People's Republic of China
,
Xiaoying Zhang 
1   Public Health, Guilin Medical University, Lingui, Guilin, People's Republic of China
2   Affiliated BaYi Children's Hospital, Seventh Medical Center of People's Liberation Army General Hospital, Dongcheng, Beijing, People's Republic of China
› Author Affiliations Funding This work was supported by the project supported by the National Natural Science Foundation of China (81270059); the Science and Technology Base and Talent Project of Guangxi Province (AD19245006).
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Abstract

Objective Bronchopulmonary dysplasia (BPD) is a common chronic lung disease of preterm neonates; the underlying pathogenesis is not fully understood. Recent studies suggested microRNAs (miRNAs) may be involved in BPD.

Study Design miRNA and mRNA microarrays were performed to analyze the expression profiles of miRNA and mRNA in BPD and control lung tissues after oxygen and air exposure on day 21. Bioinformatics methods, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), were performed to predict the potential functions of differentially expressed genes. Then, miRNA–mRNA regulatory network was constructed by protein–protein interaction (PPI) data and TarBase data.

Results Our results showed that a total of 192 differentially expressed miRNAs (74 downregulated and 118 upregulated) and 1,225 differentially expressed mRNAs (479 downregulated and 746 upregulated) were identified between BPD mice and normoxia-control mice. GO and KEGG analysis showed that for downregulated genes, the top significant enriched GO terms and KEGG pathways were both mainly related to immune and inflammation processes; for upregulated genes, the top significant enriched GO terms and KEGG pathways were both mainly related to extracellular matrix (ECM) remodeling. PPI network and miRNA–mRNA regulatory network construction revealed that the key genes and pathways associated with inflammation and immune regulation.

Conclusion Our findings revealed the integrated miRNA–mRNA data of distinct expression profiles in hyperoxia-induced BPD mice, and may provide some clues of the potential biomarkers for BPD, and provide novel insights into the development of new promising biomarkers for the treatment of BPD.

Key Points

  • Integrated advanced bioinformatics methods may offer a better way to understand the molecular expression profiles involved in BPD.

  • ECM remodeling, inflammation, and immune regulation may be essential to BPD.

  • The miRNA–mRNA regulatory network construction may contribute to develop new biomarkers for the treatment of BPD.

Keywords

bronchopulmonary dysplasia - preterm infant - hyperoxia - microRNA - bioinformatics - immune regulation

Authors' Contributions

X.Z. designed and supervised the study; C.W., S.Z., L.Z., J.D., and B.H. performed the experiments and analysis work; and X.Z. prepared the manuscript. All authors reviewed the final paper.


Supplementary Material



Publication History

Received: 10 September 2020

Accepted: 02 January 2021

Article published online:
23 March 2021

© 2021. Thieme. All rights reserved.

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