Nanchong Key Laboratory of Basic Science & Clinical Research On Chronic Kidney Disease, Department of Nephrology, The Second Clinical Medical Institution of North Sichuan Medical College (Nanchong Central Hospital), Nanchong, China.
Shanxi Kidney Disease Institute, Department of Nephrology, Shanxi Provincial People's Hospital, The Affiliated People's Hospital of Shanxi Medical University, Taiyuan, China.
Eur J Med Res. 2022 Mar 5;27(1):37. doi: 10.1186/s40001-022-00666-3.
Antineutrophil cytoplasmic antibody-associated vasculitis (AAV) is a group of life-threatening systemic autoimmune diseases. The aim of this study was to determine the relationship between the AAV hub gene and immune cell infiltration, and its value for clinical disease treatment.
We downloaded the microarray information of 37 AAV patients and 27 controls from Gene Expression Omnibus (GEO). Genes were classified into totally different modules exploitation weighted gene co-expression network analysis (WGCNA). AAV diagnostic indicators were screened and then assessed immune cell infiltration by the least absolute shrinkage and selection operator (LASSO) and CIBERSORT. Finally, Connectivity Map analysis was applied to predict possible AAV glomerulus injury improvement therapies.
WGCNA was developed and differentially expressed genes were classified into 6 modules, the black module was most tightly correlated to AAV. Among them, TIMP1 and FCER1G were most closely related to clinical features. Resting mast cells and monocytes emerged as having the foremost distinguished variations in AAV. C3AR1 and FCER1G were involved in AAV development by immune regulation. Connectivity Map analysis indicated the most significant compound was fisetin.
The present study is that the initial to spot immune cell infiltration with microarray data of glomeruli in AAV, which provides novel proof and clues for additional analysis of the molecular mechanisms.
抗中性粒细胞胞质抗体相关性血管炎(AAV)是一组危及生命的系统性自身免疫性疾病。本研究旨在确定 AAV 枢纽基因与免疫细胞浸润的关系及其对临床疾病治疗的价值。
我们从基因表达综合数据库(GEO)中下载了 37 名 AAV 患者和 27 名对照的微阵列信息。利用加权基因共表达网络分析(WGCNA)将基因分类为完全不同的模块。筛选 AAV 诊断指标,然后通过最小绝对值收缩和选择算子(LASSO)和 CIBERSORT 评估免疫细胞浸润。最后,通过连接图谱分析预测可能改善 AAV 肾小球损伤的治疗方法。
构建了 WGCNA,将差异表达基因分类为 6 个模块,黑色模块与 AAV 相关性最强。其中,TIMP1 和 FCER1G 与临床特征最密切相关。静止肥大细胞和单核细胞在 AAV 中表现出最显著的变化。C3AR1 和 FCER1G 通过免疫调节参与 AAV 的发生。连接图谱分析表明,最显著的化合物是漆黄素。
本研究首次利用 AAV 肾小球的微阵列数据检测到免疫细胞浸润,为进一步分析分子机制提供了新的证据和线索。