Bioinformatical analysis and experimental validation of endoplasmic reticulum stress-related biomarker genes in type 2 diabetes mellitus

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.