Immune landscape in the glomerular transcriptome of nephrotic syndrome and anca-associated vasculitis

ANCA-associated vasculitis (AAV), and nephrotic syndrome encompassing diseases including minimal change disease (MCD), focal and segmental glomerulosclerosis (FSG), membranous nephropathy (MN), remain a challenge due to their varied immunological characteristics. Recent therapeutic advancements have highlighted the importance of understanding these diseases’ immunological landscapes. This study analyzed transcriptomics data from renal glomerular tissues of patients with AAV, FSG, MCD, MN, and normal controls. Utilizing an immune-related gene set of 883 genes, methods including Gene Set Variation Analysis (GSVA), LASSO regression, and Weighted Correlation Network Analysis (WGCNA) were used. Predictions of immune cell compositions were made through CIBERSORT, TIMER, MCPcounter, and quanTIseq algorithms. The study revealed distinct immunogenetic pathways enriched in each disease: hematopoietic cell lineage in ANCA, linoleic acid metabolism in FSG, PPAR signaling in MCD, and drug metabolism in MN. Classifiers based on immune gene expression showed high accuracy (AUC: ANCA 0.812, FSG 0.99, MCD 1, MN 0.888). Co-expression modules and PPI networks highlighted unique pathways for each disease. Predictions of immune cell composition showed elevated macrophages in FSG and MN, with Treg levels elevated across all four diseases compared to normal controls and highest in FSG. Correlation analyses demonstrated significant associations between classifier scores and immune cell types. This study offers accurate classifiers for AAV, FSG, MCD, and MN, and reveals distinct immunological pathways. These findings advance personalized treatments and highlight potential therapeutic targets in AAV and nephrotic syndrome. Further research should validate these results for clinical applications.

抗中性粒细胞胞浆抗体相关性血管炎（ANCA-associated vasculitis, AAV）以及涵盖微小病变性肾病（minimal change disease, MCD）、局灶节段性肾小球硬化（focal and segmental glomerulosclerosis, FSG）、膜性肾病（membranous nephropathy, MN）在内的肾病综合征，因其复杂多样的免疫学特征始终是临床诊疗的难点。近年来治疗领域的进展凸显了阐明此类疾病免疫学特征的重要性。本研究针对AAV、FSG、MCD、MN患者的肾小球组织转录组数据及正常对照样本展开分析，采用包含883个基因的免疫相关基因集，运用基因集变异分析（GSVA）、最小绝对收缩和选择算子回归（LASSO回归）、加权基因共表达网络分析（WGCNA）等方法，并通过CIBERSORT、TIMER、MCPcounter及quanTIseq算法预测免疫细胞组成。本研究揭示了各疾病富集的独特免疫遗传通路：AAV中富集造血细胞谱系通路，FSG中富集亚油酸代谢通路，MCD中富集过氧化物酶体增殖物激活受体（PPAR）信号通路，MN中富集药物代谢通路。基于免疫基因表达的分类器展现出较高的诊断准确率（曲线下面积AUC：AAV 0.812，FSG 0.99，MCD 1，MN 0.888）。共表达模块与蛋白质相互作用（PPI）网络进一步凸显了各疾病的独特通路特征。免疫细胞组成预测结果显示，FSG与MN患者的巨噬细胞水平升高，且四种疾病患者的调节性T细胞（Treg）水平均较正常对照升高，其中以FSG患者的Treg水平最高。相关性分析表明，分类器评分与免疫细胞类型之间存在显著关联。本研究构建了针对AAV、FSG、MCD及MN的精准分类器，并揭示了各疾病独特的免疫学通路。上述发现推动了个体化治疗的发展，并为AAV及肾病综合征的潜在治疗靶点提供了新思路。未来仍需开展进一步研究以验证本研究结果，推动其临床转化应用。