■ANCA相关性血管炎(AAV),和肾病综合征,包括微小病变疾病(MCD),局灶性和节段性肾小球硬化(FSG),膜性肾病(MN),由于其不同的免疫学特征,仍然是一个挑战。最近的治疗进展突出了理解这些疾病的免疫学景观的重要性。
■这项研究分析了AAV患者肾小球组织的转录组学数据,FSG,MCD,MN,正常控制。利用883个基因的免疫相关基因集,方法包括基因集变异分析(GSVA),LASSO回归,采用加权相关网络分析(WGCNA)。通过CIBERSORT对免疫细胞组成进行了预测,TIMER,MCPcounter,和quanTiseq算法。
■该研究揭示了在每种疾病中富集的不同的免疫遗传途径:ANCA中的造血细胞谱系,FSG中的亚油酸代谢,MCD中的PPAR信号,和MN中的药物代谢。基于免疫基因表达的分类器显示出高准确性(AUC:ANCA0.812,FSG0.99,MCD1,MN0.888)。共表达模块和PPI网络突出了每种疾病的独特途径。免疫细胞组成的预测显示FSG和MN中巨噬细胞升高,与正常对照相比,所有四种疾病的Treg水平均升高,并且在FSG中最高。相关分析表明分类器评分和免疫细胞类型之间的显著关联。
■这项研究为AAV提供了准确的分类器,FSG,MCD,MN,并揭示了不同的免疫途径。这些发现推进了个性化治疗,突出了AAV和肾病综合征的潜在治疗靶点。进一步的研究应该验证这些结果的临床应用。
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.