ORIGINAL RESEARCH article
Front. Physiol.
Sec. Respiratory Physiology and Pathophysiology
Sequencing and bioinformatics analysis of exosome-derived miRNAs in mouse models of pancreatic injury induced by OSA
Provisionally accepted
- 1The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
- 2The Second Clinical Medical College of Fujian Medical University, Quanzhou, China
- 3Gutian County Hospital, Ningde, China
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Introduction: The role of exosomal miRNAs involved in the pathogenesis and development of pancreatic injury caused by obstructive sleep apnea (OSA) remains unclear. Here, miRNA sequencing (miRNA-seq) was used to investigate the expression profile of exosomal miRNAs in pancreatic tissue in a mouse model of chronic intermittent hypoxia (CIH) -induced pancreatic injury. Methods: Firstly, exosomes were isolated from pancreatic tissues of mice subjected to chronic intermittent hypoxia (CIH) or control conditions. Then, miRNA sequencing was performed, and differential expression analysis identified DE miRNAs. The potential functions of target genes were predicted by GO and KEGG analyses. Finally, a ceRNA interaction network was constructed to illustrate the relationships between miRNAs and targeted mRNAs. Results: A total of 55 newly predicted miRNAs and 277 existing miRNAs were identified in pancreatic tissue exosomes from the mouse model of chronic intermittent hypoxic-induced pancreatic injury. 3 up-regulated and 33 down-regulated miRNAs with differential expression were identified. 8 exosome-derived miRNAs were selected to construct CNC networks to predict target genes. Some targets and pathways were elucidated by GO analysis and KEGG analysis. Conclusion: Our work first comprehensively studied the expression profile of exosome-derived miRNA in pancreatic tissue of mouse models of OSA-induced pancreatic injury, bringing fresh perspectives on managing diabetes mellitus brought on by OSA.
Keywords: Exosome-derived miRNAs, obstructive sleep apnea, Pancreatic injury, chronic intermittent hypoxia, Bioinformatics analysis
Received: 24 Sep 2025; Accepted: 31 Oct 2025.
Copyright: © 2025 Chen, Lan, Lin, Guo, Ji and Lin. 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) or licensor 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.
* Correspondence: Qingshi Chen, chenqingshi1986@126.com
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