Yao Lili, Xu Jie, Zhang Xu, Tang Zhuqi, Chen Yuqing, Liu Xiaoyu, Duan Xuchu
Key Laboratory of Neuroregeneration of Jiangsu and Ministry of Education, Nantong Laboratory of Development and Diseases, Department of Endocrine, Department of Pharmacy, School of Life Science, Co-innovation Center of Neuroregeneration, Medical School, Affiliated Hospital of Nantong University, Nantong University, Nantong, China.
Clinical Medical Research Center, Wuxi No. 2 People's Hospital, Jiangnan University Medical Center, Wuxi, China.
Front Genet. 2024 Nov 1;15:1445033. doi: 10.3389/fgene.2024.1445033. eCollection 2024.
Endoplasmic reticulum stress (ERS) is a prominent etiological factor in the pathogenesis of diabetes. Nevertheless, the mechanisms through which ERS contributes to the development of diabetes remain elusive.
Transcriptional expression profiles from the Gene Expression Omnibus (GEO) datasets were analyzed and compared to obtain the differentially expressed genes (DEGs) in T2DM. Following the intersection with ERS associated genes, the ERS related T2DM DEGs were identified. Receiver operating characteristic (ROC) and Least Absolute Shrinkage and Selection Operator (LASSO) analysis were performed to screen out the ERS related biomarker genes and validate their diagnostic values. Gene expression level was detected by qPCR and Elisa assays in diabetic mice and patient serum samples.
By analyzing the transcriptional expression profiles of the GEO datasets, 49 T2DM-related DEGs were screened out in diabetic islets. RTN1, CLGN, PCSK1, IAPP, ILF2, IMPA1, CCDC47, and PTGES3 were identified as ERS-related DEGs in T2DM, which were revealed to be involved in protein folding, membrane composition, and metabolism regulation. ROC and LASSO analysis further screened out CLGN, ILF2, and IMPA1 as biomarker genes with high value and reliability for diagnostic purposes. These three genes were then demonstrated to be targeted by the transcription factors and miRNAs, including CEBPA, CEBPB, miR-197-5p, miR-6133, and others. Among these miRNAs, the expression of miR-197-5p, miR-320c, miR-1296-3P and miR-6133 was down-regulated, while that of miR-4462, miR-4476-5P and miR-7851-3P was up-regulated in diabetic samples. Small molecular drugs, including D002994, D001564, and others, were predicted to target these genes potentially. qPCR and Elisa analysis both validated the same expression alteration trend of the ERS-related biomarker genes in diabetic mice and T2DM patients.
These findings will offer innovative perspectives for clinical diagnosis and treatment strategies for T2DM.
内质网应激（ERS）是糖尿病发病机制中的一个重要病因。然而，ERS促成糖尿病发生发展的机制仍不清楚。
对来自基因表达综合数据库（GEO）数据集的转录表达谱进行分析和比较，以获得2型糖尿病（T2DM）中差异表达基因（DEG）。与ERS相关基因进行交集分析后，确定与ERS相关的T2DM DEG。进行受试者工作特征（ROC）和最小绝对收缩和选择算子（LASSO）分析，以筛选出与ERS相关的生物标志物基因并验证其诊断价值。通过qPCR和酶联免疫吸附测定（ELISA）检测糖尿病小鼠和患者血清样本中的基因表达水平。
通过分析GEO数据集的转录表达谱，在糖尿病胰岛中筛选出49个与T2DM相关的DEG。RTN1、CLGN、PCSK1、IAPP、ILF2、IMPA1、CCDC47和PTGES3被确定为T2DM中与ERS相关的DEG，它们被发现参与蛋白质折叠、膜组成和代谢调节。ROC和LASSO分析进一步筛选出CLGN、ILF2和IMPA1作为具有高价值和可靠性的诊断生物标志物基因。然后证明这三个基因是包括CEBPA、CEBPB、miR-197-5p、miR-6133等转录因子和微小RNA（miRNA）的靶标。在这些miRNA中，miR-197-5p、miR-320c、miR-1296-3P和miR-6133的表达在糖尿病样本中下调，而miR-4462、miR-4476-5P和miR-7851-3P的表达上调。预测包括D002994、D001564等在内的小分子药物可能靶向这些基因。qPCR和ELISA分析均验证了糖尿病小鼠和T2DM患者中与ERS相关的生物标志物基因具有相同的表达变化趋势。
这些发现将为T2DM的临床诊断和治疗策略提供创新视角。
