目的:探索糖尿病肾病（DKD）肾小球病变的生物标记物和免疫细胞浸润特征。方法:利用生物信息学方法，从基因表达数据库的数据集GSE96804和GSE30528中鉴定出肾小球病变的共同差异表达基因（DEG），并进行功能富集分析；构建蛋白质-蛋白质相互作用网络（PPI），使用结点分析提取Hub基因作为DKD的生物学标记；应用受试者工作特征（ROC）曲线和主成分分析（PCA）评估Hub基因对DKD的诊断效能；采用CIBERSORT方法分析数据集中DKD组（n n=7）和对照组（n n=4）中免疫细胞的浸润差异。组间基因差异表达分析比较采用n t检验，免疫浸润分析比较采用Wilcoxon检验。n 结果:从数据集获得62个共同DEG，主要富集在 52条基因本体论和4条京都基因和基因组百科全书通路。从PPI网络中鉴定了10个Hub基因，这些基因主要与细胞外基质（ECM）成分构成、胶原蛋白结合、免疫细胞趋化性、ECM-受体相互作用和磷脂酰肌醇激酶3-丝氨酸/苏氨酸激酶信号通路有关。PCA和ROC曲线分析显示，Hub基因在GSE96804、GSE30528和Merge数据集对DKD都具有预测价值，ROC曲线下面积值分别为0.945、0.982和0.776。免疫浸润结果提示，与正常组相比，DKD组的肾小球中的M2巨噬细胞和静息肥大细胞比例较高［分别为（2.77±2.42）%和（8.68±3.10）%，0和（8.96±7.14）%，均n P<0.05］。n 结论:Hub基因可作为DKD肾小球病变的生物学标记，对DKD具有一定的预测价值，巨噬细胞浸润是DKD的重要特征。“,”Objective:To characterize the biomarkers and immune cell infiltration for glomeruli of diabetic kidney disease (DKD).Methods:Differentially expressed genes (DEG) of glomeruli from in datasets GSE96804 and GSE30528 were identified, and functional enrichment analyses for DEG were performed by using the bioinformatics. Hub genes were extracted as the biomarkers of DKD by module analysis from the protein-protein interaction network (PPI). Receiver operating characteristic (ROC) curve analysis and principal component analysis (PCA) were applied to assess the diagnostic efficiency of Hub genes for DKD. The CIBERSORT algorithm was used to analyze the immune infiltration of glomeruli between DKD group (n n=7) and the control group (n n=4). The n t test was used to compare the difference of gene expression and Wilcoxon test was used to compare the difference of immune infiltration between two groups.n Results:A total of 62 DEG, including 41 downregulated genes and 21 upregulated genes, were detected from the integrated dataset. They were enriched in 52 Gene Ontology terms and 4 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Furthermore, we identified ten Hub genes from the PPI network using module analysis, mainly related to extracellular matrix structural constituent, collagen binding, immune cell chemotaxis, extracellular matrix (ECM)-receptor interaction and phosphatidylinositol 3-kinase-serine/threonine-protein kinase (PI3K-Akt) signaling pathway. Consistently, Hub genes showed a predictive effect for DKD by PCA and ROC curve analysis, and the value of area under curve was 0.945, 0.982 and 0.776 in GSE96804, GSE30528 and Merge datasets, respectively. Immune infiltration profiles revealed that compared with normal glomeruli, the glomeruli from DKD contained a higher proportion of M2 macrophages and resting mast cells [(2.77±2.42) % vs (8.68±3.10) %, 0 vs (8.96±7.14) %, both n P<0.05].n Conclusions:Hub gene can be used as a biological marker of DKD glomerulopathy, and it has a certain predictive value for DKD. Macrophage infiltration is an important characteristic of DKD.