Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China.
Department of Hematology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Front Immunol. 2023 Mar 29;14:1126348. doi: 10.3389/fimmu.2023.1126348. eCollection 2023.
Drug-induced acute kidney damage (DI-AKI) is a clinical phenomenon of rapid loss of kidney function over a brief period of time as a consequence of the using of medicines. The lack of a specialized treatment and the instability of traditional kidney injury markers to detect DI-AKI frequently result in the development of chronic kidney disease. Thus, it is crucial to continue screening for DI-AKI hub genes and specific biomarkers.
Differentially expressed genes (DEGs) of group iohexol, cisplatin, and vancomycin's were analyzed using Limma package, and the intersection was calculated. DEGs were then put into String database to create a network of protein-protein interactions (PPI). Ten algorithms are used in the Cytohubba plugin to find the common hub genes. Three DI-AKI models' hub gene expression was verified and using PCR and western blot. To investigate the hub gene's potential as a biomarker, protein levels of mouse serum and urine were measured by ELISA kits. The UUO, IRI and aristolochic acid I-induced nephrotoxicity (AAN) datasets in the GEO database were utilized for external data verification by WGCNA and Limma package. Finally, the Elisa kit was used to identify DI-AKI patient samples.
95 up-regulated common DEGs and 32 down-regulated common DEGs were obtained using Limma package. A PPI network with 84 nodes and 24 edges was built with confidence >0.4. Four hub genes were obtained by Algorithms of Cytohubba plugin, including TLR4, AOC3, IRF4 and TNFAIP6. Then, we discovered that the protein and mRNA levels of four hub genes were significantly changed in the DI-AKI model and . External data validation revealed that only the AAN model, which also belonged to DI-AKI model, had significant difference in these hub genes, whereas IRI and UUO did not. Finally, we found that plasma TLR4 levels were higher in patients with DI-AKI, especially in vancomycin-induced AKI.
The immune system and inflammation are key factors in DI-AKI. We discovered the immunological and inflammatory-related genes TLR4, AOC3, IRF4, and TNFAIP6, which may be promising specific biomarkers and essential hub genes for the prevention and identification of DI-AKI.
药物引起的急性肾损伤（DI-AKI）是一种临床现象，即由于使用药物，肾功能在短时间内迅速丧失。由于缺乏专门的治疗方法和传统的肾损伤标志物不稳定，DI-AKI 常导致慢性肾脏病的发生。因此，继续筛选 DI-AKI 枢纽基因和特定生物标志物至关重要。
使用 Limma 包分析碘海醇、顺铂和万古霉素组的差异表达基因（DEGs），并计算交集。将 DEGs 放入 String 数据库中以创建蛋白质-蛋白质相互作用（PPI）网络。使用 Cytohubba 插件中的十种算法寻找共同的枢纽基因。验证三个 DI-AKI 模型的枢纽基因表达，并通过 PCR 和 Western blot 进行验证。为了研究枢纽基因作为生物标志物的潜力，通过 ELISA 试剂盒测量小鼠血清和尿液中的蛋白水平。利用 GEO 数据库中的 UUO、IRI 和马兜铃酸 I 诱导的肾毒性（AAN）数据集，通过 WGCNA 和 Limma 包进行外部数据验证。最后，使用 Elisa 试剂盒鉴定 DI-AKI 患者样本。
使用 Limma 包获得 95 个上调的常见 DEGs 和 32 个下调的常见 DEGs。构建了一个具有 84 个节点和 24 个边的 PPI 网络，置信度 >0.4。通过 Cytohubba 插件的算法获得了 4 个枢纽基因，包括 TLR4、AOC3、IRF4 和 TNFAIP6。然后，我们发现这四个枢纽基因在 DI-AKI 模型中的蛋白和 mRNA 水平均发生显著变化。外部数据验证表明，只有属于 DI-AKI 模型的 AAN 模型在这些枢纽基因中存在显著差异，而 IRI 和 UUO 则没有。最后，我们发现 DI-AKI 患者的血浆 TLR4 水平较高，尤其是万古霉素诱导的 AKI。
免疫系统和炎症是 DI-AKI 的关键因素。我们发现了与免疫和炎症相关的基因 TLR4、AOC3、IRF4 和 TNFAIP6，它们可能是有前途的特定生物标志物和 DI-AKI 预防和识别的重要枢纽基因。
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