Diabetes is a chronic metabolic disorder with rising global prevalence, particularly in developed and high-income regions. Central to its pathogenesis is the dysfunction of pancreatic β-cells, alongside impaired glucose and lipid metabolism in peripheral insulin-responsive tissues. Exosomes are nano-sized extracellular vesicles essential for intercellular communication and have emerged as pivotal regulators of metabolic homeostasis. Secreted by virtually all cell types, exosomes encapsulate bioactive cargo that reflects their cellular origin and physiological state, thereby exerting diverse functional effects. Recent evidence highlights the role of exosomes derived from the liver, gut, adipose tissue, skeletal muscle, and mesenchymal stem cells in modulating β-cell proliferation, insulin secretion, and survival. In peripheral tissues exosomes also influence insulin sensitivity by regulating glucose and lipid metabolism, ultimately shaping β-cell responses under hyperglycemic conditions. A more comprehensive understanding of exosome-mediated crosstalk between metabolic organs and pancreatic β-cells could pave the way for the development of exosome-based diagnostic tools and therapeutic strategies aimed at improving early detection, prevention, and treatment of the diabetes.

Early identification of pre-diabetes provides an opportunity for intervention and treatment to delay its progression to type 2 diabetes mellitus (T2DM). We aimed to identify the biomarkers of impaired glucose tolerance (IGT) through bioinformatics analysis. The GSE76896 dataset, including non-diabetic (ND), IGT, and T2DM clinical samples, was deeply analyzed to identify 309 Co-DEGs for IGT and T2DM. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that inflammatory responses and the PI3K-AKT signaling pathway are important patho-physiological features of IGT and T2DM. Protein–protein interaction (PPI) network analysis and cytoHubba technolgy identified seven hub genes: namely, CCL2, CXCL1, CXCL8, EDN1, FGF13, MMP1, and NGF. The expression and ROC curves of these hub genes were validated using the GSE38642 dataset. Through an immunofluorescence assay, we found that the expression of FGF13 in islets of mice in the HFD and T2DM groups was significantly lower than in the control group. Similarly, the level of FGF13 in the sera of IGT and T2DM patients was lower than that in the healthy group. Together, these results suggest that FGF13 can be treated as a novel biomarker of IGT, which may provide new targets for the diagnosis and treatment of pre-diabetes and T2DM.