Department of Pediatrics, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
PeerJ. 2024 Sep 16;12:e18070. doi: 10.7717/peerj.18070. eCollection 2024.
Lupus nephritis (LN) is an autoimmune-related kidney disease with a poor prognosis, however the potential pathogenic mechanism remains unclear and there is a lack of precise biomarkers. Therefore, a thorough screening and identification of renal markers in LN are immensely beneficial to the research on its pathogenic mechanisms and treatment strategies.
We utilized bioinformatics to analyze the differentially expressed genes (DEGs) at the transcriptome level of three clusters: total renal, glomeruli, and renal tubulointerstitium in the GEO database to discover potential renal biomarkers of LN. We utilized NephroSeq datasets and measured mRNA and protein levels in the kidneys of MRL/lpr mice to confirm the expression of key DEGs.
Seven significantly differential genes () were revealed from the transcriptome database of GSE200306, which were mostly enriched in the pathway of the hematopoietic cell lineage and T cell differentiation respectively by KEGG and GO analysis. The seven hot differential genes were verified to have consistent change trends using three datasets from NephroSeq database. The receiver operating characteristic (ROC) curve indicated that five DEGs ( and exhibited a higher diagnostic ROC value in both the glomerulus and tubulointerstitium group. Validation of core genes using MRL/lpr mice showed that and exhibit significantly differential mRNA and protein expression patterns in mouse kidneys like the datasets.
This study identified seven key renal biomarkers through bioinformatics analysis using the GEO and NephroSeq databases. It was identified that and may have a high predictive value as renal biomarkers in the pathogenesis of LN, as confirmed by animal validation.
狼疮肾炎（LN）是一种自身免疫相关性肾病，预后不良，但潜在的发病机制仍不清楚，也缺乏精确的生物标志物。因此，全面筛选和鉴定 LN 的肾脏标志物，对于研究其发病机制和治疗策略具有重要意义。
我们利用生物信息学分析了 GEO 数据库中三个聚类（总肾、肾小球和肾小管间质）的转录组水平的差异表达基因（DEGs），以发现 LN 的潜在肾脏生物标志物。我们利用 NephroSeq 数据集并测量了 MRL/lpr 小鼠肾脏中的 mRNA 和蛋白水平，以验证关键 DEGs 的表达。
从 GSE200306 转录组数据库中发现了 7 个显著差异表达基因（），KEGG 和 GO 分析表明，这些基因主要富集在造血细胞谱系和 T 细胞分化途径中。使用 NephroSeq 数据库中的三个数据集验证了这 7 个热点差异基因具有一致的变化趋势。受试者工作特征（ROC）曲线表明，在肾小球和小管间质组中，5 个 DEGs（、、、和）的诊断 ROC 值更高。使用 MRL/lpr 小鼠验证核心基因显示，和在小鼠肾脏中的 mRNA 和蛋白表达模式与数据集相似，表现出明显的差异。
本研究通过 GEO 和 NephroSeq 数据库的生物信息学分析，鉴定了 7 个关键的肾脏生物标志物。通过动物验证，确定和可能作为 LN 发病机制中的肾脏生物标志物具有较高的预测价值。
