Moesin emerges as a potential exploratory biomarker associated with renal fibrosis in diabetic kidney disease

Abstract Diabetic kidney disease (DKD) has complex and incompletely understood pathogenesis. This study aimed to identify potential DKD biomarkers through multi‑microarray bioinformatic analysis and experimental validation. GEO datasets GSE30528 and GSE30529 were normalized and integrated to screen differentially expressed genes (DEGs). Multiple bioinformatic approaches and ROC analysis were applied, and Moesin (MSN) expression was further validated using IHC, Western blot, qRT‒PCR, together with in vivo and in vitro knockdown assays. Renal histopathology and profibrotic proteins including Collagen I/III and Fibronectin (FN) were evaluated. We obtained 2152 DEGs from renal transcriptomic datasets. MSN was markedly up-regulated in kidney tissues from DKD patients, diabetic mice, and high-glucose-stimulated glomerular endothelial cells (GEnCs). MSN showed moderate diagnostic ability (AUC = 0.808, 95% CI 0.666–0.950) for DKD. Functional Msn knockdown alleviated renal fibrotic phenotypes and decreased profibrotic protein accumulation. Collectively, our combined bioinformatic and experimental data suggest that MSN may serve as an exploratory biomarker for pathological assessment of DKD.