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  • Basic Science Article
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Investigating mitophagy mechanisms in bronchopulmonary dysplasia through bioinformatics

Pediatric Research (2025)Cite this article

Abstract

Background

Bronchopulmonary dysplasia (BPD) is a prevalent respiratory disease in premature infants and is accompanied by impaired lung function, increased infection risk, and other long-term complications. This study aimed to elucidate the molecular mechanisms of BPD, especially mitophagy.

Methods

Bioinformatics analyses were performed to identify differentially expressed genes (DEGs) in BPD. Weighted gene co-expression network analysis (WGCNA) was used to explore gene modules associated with mitophagy, functional enrichment analyses to identify key biological processes, and immune infiltration to assess immune cell differences.

Results

Among the 720 DEGs identified, 419 were upregulated and 301 were downregulated: these may serve as potential BPD biomarkers. WGCNA revealed that the turquoise module was strongly related to mitophagy (r = −0.6061, p < 0.05), indicating its significance in BPD pathogenesis. Enrichment analyses highlighted leukocyte migration and neutrophil extracellular trap formation, suggesting immune-mediated inflammatory response. Eight hub genes (S100P, CDC42EP3, CEACAM3, CKLF, RGL4, DOK3, B4GALT5, and MCEMP1) were identified as potential therapeutic targets. Immune infiltration analysis revealed significant differences in neutrophils and activated CD8+T cells, underscoring the immune system’s role in BPD.

Conclusion

Key molecular players and pathways involved in BPD were elucidated, providing insights for future targeted therapies addressing immunity and mitophagy in BPD.

Impact

  • This study identifies CEACAM3 and CDC42EP3 as key genes involved in mitophagy and immune dysregulation in bronchopulmonary dysplasia (BPD).

  • It provides novel insights into the TNF-α/NF-κB signaling pathway and its role in the pathogenesis of BPD.

  • This study advances biomarker discovery by associating CEACAM3 with neutrophil infiltration and CDC42EP3 with CD8+ T cell activity.

  • The selected machine learning and bioinformatics approaches enhance the diagnostic accuracy and therapeutic targeting of BPD.

  • These findings lay the foundation for future translational research in guiding personalized interventions for high-risk neonates.

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Fig. 1
Fig. 2: Enrichment analysis based on mitophagy-related differentially expressed genes (DEGs).
Fig. 3: Hub genes obtained by machine learning algorithms.
Fig. 4: Interaction analysis of hub genes.
Fig. 5: Differences in immune infiltration between the BPD group and control group.

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Data availability

The datasets utilized here can be obtained in online repositories. The article/supplementary material lists the names of the repository/repositories as well as respective accession numbers.

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Acknowledgements

We thank all contributors to the GEO database and all the participants who made this research possible.

Funding

Tianjin Health Research Project(TJWJ2022QN089) and The Science & Technolgy Development Fund of Tianjin Education Commission for Higher Education (2024KJ052) supported this work.

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Authors and Affiliations

  1. Tianjin Beichen Traditional Chinese Medicine Hospital, Tianjin, China

    Chenshuai Li, Yalei Wang & Xinying Wang

  2. Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, Tianjin, China

    Yali Li

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Contributions

C.L. overall design and writing of the paper; Y.W. participated in the design of the study and performed the statistical analysis; X.W. contributed analysis tools; Y.L. participated in the revision of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yalei Wang.

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Li, C., Wang, Y., Wang, X. et al. Investigating mitophagy mechanisms in bronchopulmonary dysplasia through bioinformatics. Pediatr Res (2025). https://doi.org/10.1038/s41390-025-04319-z

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