Identification and validation of diagnostic markers and drugs for pediatric bronchopulmonary dysplasia based on integrating bioinformatics and molecular docking analysis.

Abstract

BPD is a prevalent chronic lung disease in infancy with lifelong impacts. Its early diagnosis and treatment are hindered by complex pathophysiology and limited mechanistic understanding. This study seeks to establish a foundation for early diagnosis and targeted therapy by identifying diagnostic markers and exploring drug-gene associations. Gene expression data were retrieved from the GEO database. Functional enrichment analyses were conducted on the differentially expressed genes (DEGs). DEGs were used to construct a PPI network. Three algorithms were applied to identify diagnostic markers. Immune cell infiltration was analyzed using the CIBERSORT tool, assessing relationships between immune cells and diagnostic markers. Molecular docking was performed to evaluate interactions between predict candidate drugs and diagnostic markers. Six hub genes were identified as diagnostic markers. Diagnostic markers showed significant correlations with specific immune cells. Resveratrol and progesterone were found to stably bind to all six diagnostic markers in molecular docking analyses, suggesting therapeutic potential. In conclusion, our results show that IL7R, CXCL10, DEFA4, PRTN3, NCAPG and CCNB1 are BPD diagnostic indicators, and revealing immunological features associated with BPD. The molecular interactions of resveratrol and progesterone with the aforementioned key targets suggest their potential as therapeutic drugs for treating BPD.