Department of Nephrology, South China Hospital, Medical School, Shenzhen University, Shenzhen, Guangdong, China.
Department of Nephrology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Front Immunol. 2023 Jul 24;14:1202298. doi: 10.3389/fimmu.2023.1202298. eCollection 2023.
Diabetic nephropathy (DN) is the most prevalent microvascular consequence of diabetes and has recently risen to the position of the world's second biggest cause of end-stage renal diseases. Growing studies suggest that oxidative stress (OS) responses are connected to the advancement of DN. This study aimed to developed a novel diagnostic model based on OS-related genes. The differentially expressed oxidative stress-related genes (DE-OSRGs) experiments required two human gene expression datasets, which were given by the GEO database (GSE30528 and GSE96804, respectively). The potential diagnostic genes were identified using the SVM-RFE assays and the LASSO regression model. CIBERSORT was used to determine the compositional patterns of the 22 different kinds of immune cell fraction seen in DN. These estimates were based on the combined cohorts. DN serum samples and normal samples were both subjected to RT-PCR in order to investigate the degree to which certain genes were expressed. In this study, we were able to locate 774 DE-OSRGs in DN. The three marker genes (DUSP1, PRDX6 and S100A8) were discovered via machine learning on two different machines. The high diagnostic value was validated by ROC tests, which focused on distinguishing DN samples from normal samples. The results of the CIBERSORT study suggested that DUSP1, PRDX6, and S100A8 may be associated to the alterations that occur in the immunological microenvironment of DN patients. Besides, the results of RT-PCR indicated that the expression of DUSP1, PRDX6, and S100A8 was much lower in DN serum samples compared normal serum samples. The diagnostic value of the proposed model was likewise verified in our cohort, with an area under the curve of 9.946. Overall, DUSP1, PRDX6, and S100A8 were identified to be the three diagnostic characteristic genes of DN. It's possible that combining these genes will be effective in diagnosing DN and determining the extent of immune cell infiltration.
糖尿病肾病（DN）是糖尿病最常见的微血管并发症，最近已上升为世界第二大终末期肾脏疾病的病因。越来越多的研究表明，氧化应激（OS）反应与 DN 的进展有关。本研究旨在基于 OS 相关基因建立一种新的诊断模型。差异表达的氧化应激相关基因（DE-OSRGs）实验需要两个人类基因表达数据集，分别来自 GEO 数据库（GSE30528 和 GSE96804）。使用 SVM-RFE 检测和 LASSO 回归模型来鉴定潜在的诊断基因。CIBERSORT 用于确定 22 种不同免疫细胞亚群在 DN 中的组成模式。这些估计是基于联合队列的。对 DN 血清样本和正常样本进行 RT-PCR 检测，以研究某些基因的表达程度。在本研究中，我们在 DN 中发现了 774 个 DE-OSRGs。通过两台不同机器的机器学习，发现了三个标记基因（DUSP1、PRDX6 和 S100A8）。通过 ROC 测试验证了其高诊断价值，该测试重点是区分 DN 样本和正常样本。CIBERSORT 研究的结果表明，DUSP1、PRDX6 和 S100A8 可能与 DN 患者免疫微环境的改变有关。此外，RT-PCR 结果表明，DN 血清样本中 DUSP1、PRDX6 和 S100A8 的表达明显低于正常血清样本。该模型的诊断价值在我们的队列中也得到了验证，曲线下面积为 9.946。总的来说，DUSP1、PRDX6 和 S100A8 被确定为 DN 的三个诊断特征基因。联合这些基因可能有助于诊断 DN 并确定免疫细胞浸润的程度。
