Zou Mengxiao, Yang Dan, Xu Han, Ge Shuwang
Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Autoimmunity. 2025 Dec;58(1):2519285. doi: 10.1080/08916934.2025.2519285. Epub 2025 Jun 23.
Studies have found that there is tertiary lymphoid structure (TLS) in IgA nephropathy (IgAN), and the existence of TLS has an impact on renal function, creatinine, and proteinuria in patients. We aim to explore the potential molecular mechanisms and therapeutic targets of TLS in IgA nephropathy by bioinformatics methods, hoping to provide treatment methods. The datasets GSE226840, GSE237120, and GSE116626 from the Gene Expression Omnibus (GEO) database were employed to investigate the potential therapeutic targets of TLS in IgAN. The R was used to obtain the differentially expressed genes (DEGs) of three datasets, and the Venny was used to intersect the above three parts of the DEGs to obtain the common DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on obtained genes using Metascape. Protein-Protein interaction (PPI) network was constructed. The intersection of the above common differential genes and IgAN differential genes was obtained by Venny tool. The Nephroseq platform was used to screen core genes and explore their relationship with clinical features. Meanwhile, CIBERSORT was utilized to further delve into the correlation between core genes and immune cells. 92 TLS-related genes and 486 IgAN related genes were obtained, and 6 common genes were obtained after crossing the two genes. The intersection genes were verified by Nephroseq, and CDKN1A, CD83, DUSP6, and CD48 were identified as core genes. At the same time, there were differences in the composition of immune cells between the disease group and the control group when the immune infiltration analysis was performed. And by further analyzing the correlation between core genes and immune cells, the study found that the four genes were positively correlated with T cells, B cells, plasma cells, and other immune cells. By exploring the relationship between core genes and clinical features, CDKN1A and DUSP6 were negatively correlated with Glomerular Filtration Rate (GFR) and positively correlated with proteinuria in IgAN patients. CD48 was negatively correlated with GFR and positively correlated with Blood Urea Nitrogen (BUN). The four genes highly associated with TLS and IgAN were screened using GEO database in study. And CDKN1A, CD83, DUSP6 and CD48 may provide potential therapeutic targets for the treatment of TLS in IgAN. At the same time, studies have found that T cells, B cells, and macrophages may be involved in the formation of TLS in IgAN.
研究发现,IgA肾病(IgAN)中存在三级淋巴结构(TLS),TLS的存在对患者的肾功能、肌酐和蛋白尿有影响。我们旨在通过生物信息学方法探索TLS在IgA肾病中的潜在分子机制和治疗靶点,希望能提供治疗方法。使用来自基因表达综合数据库(GEO)的数据集GSE226840、GSE237120和GSE116626来研究TLS在IgA肾病中的潜在治疗靶点。利用R语言获取三个数据集的差异表达基因(DEG),并使用Venny工具对上述三部分DEG进行交集分析以获得共同的DEG。使用Metascape对获得的基因进行基因本体(GO)和京都基因与基因组百科全书(KEGG)通路分析。构建蛋白质-蛋白质相互作用(PPI)网络。通过Venny工具获得上述共同差异基因与IgA肾病差异基因的交集。利用Nephroseq平台筛选核心基因并探索它们与临床特征的关系。同时,使用CIBERSORT进一步深入研究核心基因与免疫细胞之间的相关性。获得了92个与TLS相关的基因和486个与IgA肾病相关的基因,两者交叉后得到6个共同基因。通过Nephroseq对交集基因进行验证,确定细胞周期蛋白依赖性激酶抑制剂1A(CDKN1A)、CD分子83(CD83)、双特异性磷酸酶6(DUSP6)和CD分子48(CD48)为核心基因。同时,在进行免疫浸润分析时,疾病组和对照组之间的免疫细胞组成存在差异。通过进一步分析核心基因与免疫细胞之间的相关性,研究发现这四个基因与T细胞、B细胞、浆细胞和其他免疫细胞呈正相关。通过探索核心基因与临床特征之间的关系,发现CDKN1A和DUSP6与IgA肾病患者的肾小球滤过率(GFR)呈负相关,与蛋白尿呈正相关。CD48与GFR呈负相关,与血尿素氮(BUN)呈正相关。本研究利用GEO数据库筛选出了与TLS和IgA肾病高度相关的四个基因。CDKN1A、CD83、DUSP6和CD48可能为IgA肾病中TLS的治疗提供潜在的治疗靶点。同时,研究发现T细胞、B细胞和巨噬细胞可能参与了IgA肾病中TLS的形成。