Li Chenshuai, Wang Yalei, Wang Xinying, Li Yali
Tianjin Beichen Traditional Chinese Medicine Hospital, Tianjin, China.
Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, Tianjin, China.
Pediatr Res. 2025 Aug 9. doi: 10.1038/s41390-025-04319-z.
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.
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.
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.
Key molecular players and pathways involved in BPD were elucidated, providing insights for future targeted therapies addressing immunity and mitophagy in BPD.
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.
支气管肺发育不良（BPD）是早产儿中一种常见的呼吸系统疾病，伴有肺功能受损、感染风险增加及其他长期并发症。本研究旨在阐明BPD的分子机制，尤其是线粒体自噬。
进行生物信息学分析以鉴定BPD中差异表达基因（DEG）。采用加权基因共表达网络分析（WGCNA）探索与线粒体自噬相关的基因模块，进行功能富集分析以确定关键生物学过程，并进行免疫浸润分析以评估免疫细胞差异。
在鉴定出的720个DEG中，419个上调，301个下调：这些可能作为潜在的BPD生物标志物。WGCNA显示绿松石模块与线粒体自噬密切相关（r = -0.6061，p < 0.05），表明其在BPD发病机制中的重要性。富集分析突出了白细胞迁移和中性粒细胞胞外陷阱形成，提示免疫介导的炎症反应。鉴定出8个枢纽基因（S100P、CDC42EP3、CEACAM3、CKLF、RGL4、DOK3、B4GALT5和MCEMP1）作为潜在治疗靶点。免疫浸润分析显示中性粒细胞和活化的CD8 + T细胞存在显著差异，强调了免疫系统在BPD中的作用。
阐明了BPD中涉及的关键分子参与者和途径，为未来针对BPD免疫和线粒体自噬的靶向治疗提供了见解。
本研究确定CEACAM3和CDC42EP3是支气管肺发育不良（BPD）中线粒体自噬和免疫失调的关键基因。它为肿瘤坏死因子-α/核因子-κB信号通路及其在BPD发病机制中的作用提供了新见解。本研究通过将CEACAM3与中性粒细胞浸润以及CDC42EP3与CD8 + T细胞活性相关联，推进了生物标志物的发现。所选择的机器学习和生物信息学方法提高了BPD的诊断准确性和治疗靶向性。这些发现为未来指导高危新生儿个性化干预的转化研究奠定了基础。
