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Bronchopulmonary dysplasia: analysis and validation of ferroptosis-related diagnostic biomarkers and immune cell infiltration features

Pediatric Research (2024)Cite this article

Abstract

Background

Early and precise diagnosis of bronchopulmonary dysplasia (BPD) is essential to improve the prognosis of preterm infants with BPD. Studying ferroptosis-related genes for diagnostic markers of BPD was the objective of this study.

Methods

Using the GEO database and the FerrDb database, we obtained the GSE32472 dataset and screened the ferroptosis-related differentially expressed mRNAs (FRDE-mRNAs). By using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), possible biological functions and pathways were identified for FRDE-mRNAs. Three machine learning algorithms (LASSO, SVM-RFE, Random Forest) were used to recognize hub genes, as well as CIBERSORT for exploring the immune landscape of BPD and controls. Functional predictions for hub genes were made using single-gene gene set enrichment analysis (GSEA).

Results

Twenty three FRDE-mRNAs were obtained and were mainly involved in autophagy, fatty acid metabolism and ferroptosis. The four hub genes (LPIN1, ACADSB, WIPI1 and SLC7A11) screened were utilized to construct a diagnostic nomogram. The receiver operating characteristic (ROC) curves and calibration curves demonstrateld that the nomogram exhibited good predictive performance. Eight types of immune cell markers differed significantly between BPD and controls.

Conclusion

We developed a diagnostic model for BPD, which could facilitate the early diagnosis and timely intervention of BPD.

Impact

  • The role of ferroptosis in bronchopulmonary dysplasia is rarely reported.

  • The ferroptosis-related genes (LPIN1, ACADSB, WIPI1 and SLC7A11) we identified could serve as early diagnostic biomarkers for BPD.

  • Immune cell infiltration features in BPD and signaling pathways associated with marker genes give new insight into the disease process and provide a basis for further research.

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Fig. 1: Identification of ferroptosis-related differentially expressed mRNAs.
Fig. 2: Enrichment analysis of ferroptosis-related DE-mRNAs.
Fig. 3: Identification of 4 biomarkers using machine learning algorithms.
Fig. 4: Establishment and validation of the model.
Fig. 5: Differential expression analysis of 4 biomarkers.
Fig. 6: Analysis of the immune landscape.

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Data availability

Publicly available dataset was analyzed in this study. The dataset can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32472.

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Authors and Affiliations

  1. School of Medicine, Yangzhou University, Yangzhou, China

    Changjiang Fang, Haixia Tu, Dengqin Bi & Guihua Shu

  2. Dalian Medical University, Dalian, China

    Rong Li

  3. Department of Neonatology, Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou, China

    Guihua Shu

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  1. Changjiang Fang
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Contributions

Changjiang Fang designed the research, analyzed the data, and wrote the manuscript; Haixia Tu, Rong Li and Dengqin Bi analyzed and interpreted the data; Guihua Shu designed the research, analyzed the data, and corrected the manuscript.

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Correspondence to Guihua Shu.

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Fang, C., Tu, H., Li, R. et al. Bronchopulmonary dysplasia: analysis and validation of ferroptosis-related diagnostic biomarkers and immune cell infiltration features. Pediatr Res (2024). https://doi.org/10.1038/s41390-024-03249-6

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