Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Curr Pharm Des. 2024;30(25):1966-1984. doi: 10.2174/0113816128297623240521070426.
Chronic Bronchitis (CB) is a recurrent and persistent pulmonary inflammation disease. Growing evidence suggests an association between CB and Anti-neutrophil Cytoplasmic Antibody-associated Glomerulonephritis (ANCA-GN). However, the precise mechanisms underlying their association remain unclear.
The purpose of this study was to further explore the molecular mechanism of the occurrence of chronic bronchitis (CB) associated with anti-neutrophil cytoplasmic antibody-associated glomerulonephritis (ANCA- GN).
Our study aimed to investigate the potential shared pathogenesis of CB-associated ANCA-GN.
Datasets of ANCA (GSE108113 and GSE104948) and CB (GSE151052 and GSE162635) were obtained from the Gene Expression Omnibus (GEO) datasets. Firstly, GSE108113 and GSE151052 were analyzed to identify common differentially expressed genes (DEGs) by Limma package. Based on common DEGs, protein-protein interaction (PPI) network and functional enrichment analyses, including GO, KEGG, and GSEA, were performed. Then, hub genes were identified by degree algorithm and validated in GSE104948 and GSE162635. Further PPI network and functional enrichment analyses were performed on hub genes. Additionally, a competitive ceRNA network was constructed through miRanda and spongeScan. Transcription factors (TFs) were predicted and verified using the TRRUST database. Furthermore, the CIBERSORT algorithm was employed to explore immune cell infiltration. The Drug Gene Interaction Database (DGIDB) was utilized to predict small-molecular compounds of CB and ANCA-GN.
A total of 963 DEGs were identified in the integrated CB dataset, and 610 DEGs were identified in the integrated ANCA-GN dataset. Totally, we identified 22 common DEGs, of which 10 hub genes (LYZ, IRF1, PIK3CG, IL2RG, NT5E, ARG2, HBEGF, NFATC2, ALPL, and FKBP5) were primarily involved in inflammation and immune responses. Focusing on hub genes, we constructed a ceRNA network composed of 323 miRNAs and 348 lncRNAs. Additionally, five TFs (SP1, RELA, NFKB1, HIF1A, and SP3) were identified to regulate the hub genes. Furthermore, immune cell infiltration results revealed immunoregulation in CB and ANCA-GN. Finally, some small-molecular compounds (Daclizumab, Aldesleukin, and NT5E) were predicted to predominantly regulate inflammation and immunity, especially IL-2.
Our study explores the inflammatory-immune pathways underlying CB-associated ANCA-GN and emphasizes the importance of NETs and lymphocyte differentiation, providing novel insights into the shared pathogenesis and therapeutic targets.
慢性支气管炎(CB)是一种反复发作和持续存在的肺部炎症性疾病。越来越多的证据表明,CB 与抗中性粒细胞胞质抗体相关性血管炎(ANCA-GN)之间存在关联。然而,它们之间关联的确切机制仍不清楚。
本研究旨在进一步探讨慢性支气管炎(CB)合并抗中性粒细胞胞质抗体相关性血管炎(ANCA-GN)的发生的分子机制。
我们的研究旨在探讨 CB 相关的 ANCA-GN 的潜在共同发病机制。
从基因表达综合数据库(GEO)数据集获得 ANCA(GSE108113 和 GSE104948)和 CB(GSE151052 和 GSE162635)数据集。首先,使用 Limma 包分析 GSE108113 和 GSE151052 以鉴定共同差异表达基因(DEGs)。基于共同 DEGs,进行蛋白质-蛋白质相互作用(PPI)网络和功能富集分析,包括 GO、KEGG 和 GSEA。然后,通过度算法识别枢纽基因,并在 GSE104948 和 GSE162635 中进行验证。进一步对枢纽基因进行 PPI 网络和功能富集分析。此外,通过 miRanda 和 spongeScan 构建竞争性 ceRNA 网络。使用 TRRUST 数据库预测和验证转录因子(TFs)。进一步使用 CIBERSORT 算法探索免疫细胞浸润。利用 Drug Gene Interaction Database(DGIDB)预测 CB 和 ANCA-GN 的小分子化合物。
在整合的 CB 数据集中共鉴定出 963 个 DEGs,在整合的 ANCA-GN 数据集中共鉴定出 610 个 DEGs。总共鉴定出 22 个共同 DEGs,其中 10 个枢纽基因(LYZ、IRF1、PIK3CG、IL2RG、NT5E、ARG2、HBEGF、NFATC2、ALPL 和 FKBP5)主要参与炎症和免疫反应。针对枢纽基因,我们构建了一个由 323 个 miRNA 和 348 个 lncRNA 组成的 ceRNA 网络。此外,鉴定出 5 个 TFs(SP1、RELA、NFKB1、HIF1A 和 SP3)来调节枢纽基因。此外,免疫细胞浸润结果表明 CB 和 ANCA-GN 存在免疫调节。最后,预测到一些小分子化合物(Daclizumab、Aldesleukin 和 NT5E)主要调节炎症和免疫,特别是 IL-2。
本研究探讨了 CB 相关的 ANCA-GN 的炎症免疫途径,并强调了 NETs 和淋巴细胞分化的重要性,为共同发病机制和治疗靶点提供了新的见解。