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综合生物信息学分析筛选出特发性肺纤维化的关键基因和通路。

Integrated bioinformatics analysis screened the key genes and pathways of idiopathic pulmonary fibrosis.

作者信息

Wu Juan, Wei Yangyang, Kang Hong, Yu Xiao, Wei Shuting, Xue Ting, Kong Xiaomei

机构信息

NHC Key Laboratory of Pneumoconiosis, Shanxi Key Laboratory of Respiratory Diseases, Department of Pulmonary and Critical Care Medicine, The First Hospital of Shanxi Medical University, Taiyuan, China.

出版信息

Sci Rep. 2025 Apr 25;15(1):14448. doi: 10.1038/s41598-025-97037-9.

Abstract

To investigate the molecular mechanisms underlying idiopathic pulmonary fibrosis (IPF), we analyzed the GSE173355 and GSE173356 datasets obtained from the NCBI-GEO database. We identified differentially expressed genes (DEGs) and differentially methylated sites. Functional enrichment analysis was conducted for both DEGs and differentially methylated sites. Functional enrichment analysis was performed for both DEGs and differentially methylated sites, alongside an examination of immune-related scores, proportions, and GSVA enrichment scores of immune cells in IPF versus control samples. An integrated gene-methylation association analysis revealed 8 genes with expression levels negatively influenced by methylation. The Rap1 pathway, Focal adhesion, and Axon guidance were significantly enriched among both DEGs and differentially methylated sites. Immune-related scores were notably lower in the IPF group compared to the control group, with marked differences in immune cell proportions and GSVA enrichment scores. Screening of DEGs identified 361 differentially expressed immune-related genes (IRGs). Protein-protein interaction (PPI) network analysis using the STRING database and Cytoscape software unveiled 10 key genes and 3 core subnetworks. RT-qPCR validation in bleomycin-induced IPF mouse model and A549 EMT model confirmed the reliability of most findings. These results provide new insights into IPF pathogenesis and potential therapeutic strategies, necessitating further functional validation.

摘要

为了研究特发性肺纤维化(IPF)潜在的分子机制,我们分析了从NCBI - GEO数据库获得的GSE173355和GSE173356数据集。我们鉴定了差异表达基因(DEGs)和差异甲基化位点。对DEGs和差异甲基化位点都进行了功能富集分析。对DEGs和差异甲基化位点进行了功能富集分析,同时检查了IPF与对照样本中免疫相关评分、免疫细胞比例和GSVA富集评分。综合基因 - 甲基化关联分析揭示了8个表达水平受甲基化负面影响的基因。Rap1通路、粘着斑和轴突导向在DEGs和差异甲基化位点中均显著富集。与对照组相比,IPF组的免疫相关评分显著较低,免疫细胞比例和GSVA富集评分存在明显差异。对DEGs的筛选鉴定出361个差异表达的免疫相关基因(IRGs)。使用STRING数据库和Cytoscape软件进行的蛋白质 - 蛋白质相互作用(PPI)网络分析揭示了关键基因和3个核心子网。在博来霉素诱导的IPF小鼠模型和A549上皮 - 间质转化(EMT)模型中进行的RT - qPCR验证证实了大多数研究结果的可靠性。这些结果为IPF发病机制和潜在治疗策略提供了新见解,需要进一步的功能验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/00ff/12032202/f10fe58c9c25/41598_2025_97037_Fig1_HTML.jpg

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