Li Xiaolong, Zhu Qingmiao, Huang Jinge, Zhao Kai, Zhao Ting
Zhejiang Chinese Medical University School of Basic Medical Sciences, Hangzhou, 310053, China.
The First Affiliated Hospital of Zhejiang, Chinese Medical University, Hangzhou, 310053, China.
Clin Rheumatol. 2025 Sep 19. doi: 10.1007/s10067-025-07703-6.
Ferroptosis has garnered attention as a mechanism of cell death contributing to lupus and lupus nephritis pathogenesis. However, the precise locations of occurrence, mechanisms triggering disease progression, and critical targets remain unclear.
Differentially expressed genes were identified using the "limma" package in R. Weighted gene co-expression network analysis was applied to explore gene modules associated with LN. Ferroptosis-related genes were obtained from FerrDb V2 and intersected with DEGs and WGCNA modules to identify candidate genes. Hub genes were selected using LASSO and Random Forest algorithms, followed by ROC curve validation. Immune cell infiltration was analyzed using the CIBERSORT algorithm, and correlations with hub gene expression were assessed. A protein-protein interaction network was constructed via STRING. Finally, RT-qPCR was performed to validate the expression of selected genes in kidney tissues from MRL/lpr and C57BL/6 mice.
Differential expression gene analysis and weighted gene co-expression network analysis identified 688 LN-related genes in PBMC, 625 in the renal tubulointerstitium, and 1428 in renal glomeruli. The LASSO and Random Forest algorithms selected hub genes associated with ferroptosis and were validated through ROC analysis. Immunocyte infiltration analysis revealed differential patterns in different tissues, with most hub genes highly correlated with immune cell infiltrations. PPI analysis and RT-qPCR validation identified a PPARG-centered regulatory network (including PPARG, CDKN1A, NR4A1, ATF3, DUSP1 and PDK4) that may be crucial for the regulation of ferroptosis in lupus nephritis.
This study reveals, for the first time, the mechanisms and regulatory hub genes of ferroptosis in different LN tissues. The regulatory network centered around PPARG may play a crucial role in ferroptosis in LN, providing a new perspective for in-depth investigation into LN pathogenesis and targeted therapy development. Key Points • Identified tissue-specific ferroptosis biomarkers in lupus nephritis using multiple machine learning methods. • The diagnostic efficacy of the PPARG regulatory network was validated through both internal and external validation. • Discovered the regulatory network of ferroptosis in lupus nephritis by constructing the PPARG regulatory network.
铁死亡作为一种导致狼疮和狼疮性肾炎发病机制的细胞死亡方式，已受到关注。然而，其发生的确切位置、触发疾病进展的机制以及关键靶点仍不清楚。
使用R语言中的“limma”软件包鉴定差异表达基因。应用加权基因共表达网络分析来探索与狼疮性肾炎相关的基因模块。从FerrDb V2数据库中获取铁死亡相关基因，并与差异表达基因和加权基因共表达网络分析模块进行交集分析，以确定候选基因。使用LASSO和随机森林算法选择枢纽基因，随后进行ROC曲线验证。使用CIBERSORT算法分析免疫细胞浸润情况，并评估其与枢纽基因表达的相关性。通过STRING构建蛋白质-蛋白质相互作用网络。最后，进行RT-qPCR以验证MRL/lpr和C57BL/6小鼠肾组织中所选基因的表达。
差异表达基因分析和加权基因共表达网络分析在PBMC中鉴定出688个与狼疮性肾炎相关的基因，在肾小管间质中鉴定出625个，在肾小球中鉴定出1428个。LASSO和随机森林算法选择了与铁死亡相关的枢纽基因，并通过ROC分析进行了验证。免疫细胞浸润分析揭示了不同组织中的差异模式，大多数枢纽基因与免疫细胞浸润高度相关。蛋白质-蛋白质相互作用分析和RT-qPCR验证确定了一个以PPARG为中心的调控网络（包括PPARG、CDKN1A、NR4A1、ATF3、DUSP1和PDK4），该网络可能对狼疮性肾炎中铁死亡的调控至关重要。
本研究首次揭示了不同狼疮性肾炎组织中铁死亡的机制和调控枢纽基因。以PPARG为中心的调控网络可能在狼疮性肾炎的铁死亡中起关键作用，为深入研究狼疮性肾炎发病机制和开发靶向治疗提供了新的视角。要点 • 使用多种机器学习方法鉴定狼疮性肾炎中组织特异性铁死亡生物标志物。 • 通过内部和外部验证验证了PPARG调控网络的诊断效能。 • 通过构建PPARG调控网络发现了狼疮性肾炎中铁死亡的调控网络。
