Affiliated Hospital of Shaoxing University of Edocrine and Metabolism Department, Zhejiang, China.
Affiliated Hospital of Shaoxing University of Clinical Laboratory, Zhejiang, China.
Medicine (Baltimore). 2023 Oct 27;102(43):e35618. doi: 10.1097/MD.0000000000035618.
The present study was designed to identify potential diagnostic markers for diabetic kidney disease (DKD). Two publicly available gene expression profiles (GSE142153 and GSE30528 datasets) from human DKD and control samples were downloaded from the GEO database. Differentially expressed genes (DEGs) were screened between 23 DKD and 10 control samples using the gene data from GSE142153. Weighted gene co expression network analysis was used to find the modules related to DKD. The overlapping genes of DEGs and Turquoise modules were narrowed down and using the least absolute shrinkage and selection operator regression model and support vector machine-recursive feature elimination analysis to identify candidate biomarkers. The area under the receiver operating characteristic curve value was obtained and used to evaluate discriminatory ability using the gene data from GSE30528. A total of 110 DEGs were obtained: 64 genes were significantly upregulated and 46 genes were significantly downregulated. Weighted gene co expression network analysis found that the turquoise module had the strongest correlation with DKD (R = -0.58, P = 4 × 10-4). Thirty-eight overlapping genes of DEGs and turquoise modules were extracted. The identified DEGs were mainly involved in p53 signaling pathway, HIF-1 signaling pathway, JAK - STAT signaling pathway and FoxO signaling pathway between and the control. C-X-C motif chemokine ligand 3 was identified as diagnostic markers of DKD with an area under the receiver operating characteristic curve of 0.735 (95% CI 0.487-0.932). C-X-C motif chemokine ligand 3 was identified as diagnostic biomarkers of DKD and can provide new insights for future studies on the occurrence and the molecular mechanisms of DKD.
本研究旨在鉴定糖尿病肾病（DKD）的潜在诊断标志物。从 GEO 数据库中下载了两个公开的人类 DKD 和对照样本的基因表达谱（GSE142153 和 GSE30528 数据集）。使用 GSE142153 中的基因数据筛选 23 个 DKD 和 10 个对照样本之间的差异表达基因（DEGs）。使用加权基因共表达网络分析寻找与 DKD 相关的模块。缩小 DEGs 和绿松石模块的重叠基因，并使用最小绝对收缩和选择算子回归模型和支持向量机递归特征消除分析来鉴定候选生物标志物。使用 GSE30528 中的基因数据获得接收者操作特征曲线下的面积，并使用该面积评估鉴别能力。共获得 110 个 DEGs：64 个基因显著上调，46 个基因显著下调。加权基因共表达网络分析发现绿松石模块与 DKD 的相关性最强（R = -0.58，P = 4×10-4）。提取了 DEGs 和绿松石模块的 38 个重叠基因。鉴定的 DEGs 主要参与了 p53 信号通路、HIF-1 信号通路、JAK-STAT 信号通路和 FoxO 信号通路之间的调控，而与对照相比。C-X-C 基序趋化因子配体 3 被鉴定为 DKD 的诊断标志物，其接受者操作特征曲线下的面积为 0.735（95%CI 0.487-0.932）。C-X-C 基序趋化因子配体 3 被鉴定为 DKD 的诊断生物标志物，可为未来研究 DKD 的发生和分子机制提供新的见解。
