Tian Ming, Tang Min, Chen Caiming, Lin Yufang, Chen Hong, Xu Yanfang
Department of Nephrology, Blood Purification Research Center, the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China.
Fujian Clinical Research Center for Metabolic Chronic Kidney Disease, the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China.
J Inflamm Res. 2024 Dec 24;17:11469-11483. doi: 10.2147/JIR.S489087. eCollection 2024.
A comprehensive bioinformatics analysis was conducted to investigate potential new diagnostic biomarkers and immune infiltration characteristics associated with tubulointerstitial injury in lupus nephritis (LN), and to examine possible correlations between key genes and infiltrating immune cells.
The GSE32591, GSE113342, and GSE200306 datasets were downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) were identified in the pooled dataset. Support vector machine-recursive feature elimination analysis and the least absolute shrinkage and selection operator regression model were used to screen for possible markers, and the compositional patterns of the 22 types of immune cell fractions in LN were determined using CIBERSORT. Finally, Western blotting, quantitative real-time polymerase chain reaction, and multiple immunofluorescence methods were used to confirm the significance of these feature genes in MRL/lpr mice and patients with LN.
Seventeen DEGs were identified, of which 11 were considerably upregulated and six were markedly downregulated. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed significant enrichment in pertussis, complement and coagulation cascades, systemic lupus erythematosus, and other pathways. Based on the machine learning results, we identified and were key diagnostic genes for tubulointerstitial injury associated with LN. Immune cell infiltration analysis revealed that and were associated with M1 macrophages. Finally, the association between and macrophages in MRL/lpr mice and patients with LN were verified.
This study suggests that and which are highly expressed in renal tubular epithelial cells in LN and are associated with macrophage infiltration, may be a novel diagnostic and therapeutic target.
进行全面的生物信息学分析，以研究与狼疮性肾炎（LN）肾小管间质损伤相关的潜在新诊断生物标志物和免疫浸润特征，并检查关键基因与浸润免疫细胞之间的可能相关性。
从基因表达综合数据库下载GSE32591、GSE113342和GSE200306数据集，并在合并数据集中鉴定差异表达基因（DEG）。使用支持向量机递归特征消除分析和最小绝对收缩和选择算子回归模型筛选可能的标志物，并使用CIBERSORT确定LN中22种免疫细胞分数的组成模式。最后，使用蛋白质免疫印迹、定量实时聚合酶链反应和多重免疫荧光方法来证实这些特征基因在MRL/lpr小鼠和LN患者中的意义。
鉴定出17个DEG，其中11个显著上调，6个显著下调。京都基因与基因组百科全书通路分析显示在百日咳、补体和凝血级联、系统性红斑狼疮和其他通路中显著富集。基于机器学习结果，我们确定 和 是与LN相关的肾小管间质损伤的关键诊断基因。免疫细胞浸润分析显示 和 与M1巨噬细胞相关。最后，验证了MRL/lpr小鼠和LN患者中 和 巨噬细胞之间的关联。
本研究表明， 在LN肾小管上皮细胞中高表达且与巨噬细胞浸润相关，可能是一种新的诊断和治疗靶点。
