Abstract

Introduction: Pre-diabetes, a high-risk metabolic state, is situated between normal glucose homeostasis and diabetes. Early identification of pre-diabetes offers opportunities for intervention and diabetes reversal, highlighting the crucial need to investigate reliable biomarkers for this condition. Methods: We conducted an in-depth bioinformatics analysis of clinical samples from non-diabetic (ND), impaired glucose tolerance (IGT), and type 2 diabetes mellitus (T2DM) categories within the GSE164416 dataset. Thereafter the HFD and STZ treated mice were used for validation. Results: This analysis identified several codifferentially expressed genes (Co-DEGs) for IGT and T2DM, including CFB, TSHR, VNN2, APOC1, CLDN2, SLPI, LCN2, CXCL17, FAIM2, and REG3A. Validation of these genes and the determination of ROC curves were performed using the GSE76895 dataset. Thereafter, CLDN2 was selected for further verification. Gene expression analysis and immunofluorescence analysis revealed a significant upregulation of CLDN2 expression in the pancreas islets of mice in the high-fat diet and T2DM groups compared to the control group. Similarly, serum level of CLDN2 in patients with IGT and T2DM were significantly higher than those in the healthy group. Discussion: These results suggest that CLDN2 can serve as a novel biomarker for pre-diabetes, providing a new direction for future research in the prevention of type 2 diabetes.

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