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Peer-reviewedCC BYScientific Reports

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

  • Ying Xie1
  • Jing Ding1
  • Zhengwei Liang1
  • Rongrui Zhang1
  • Sha Lv2
  • Qian Zhang1
  • Jingjing Da3
  • Deqin Lu1
  1. 1Department of Pathophysiology, School of Basic Medical Sciences, Guizhou Medical University, Gui’an New District
  2. 2Guizhou Provincial Key Laboratory of Pathogenesis and Prevention of Common Chronic Diseases, Gui’an New District
  3. 3Department of Nephrology, NHC Key Laboratory of Pulmonary Immunological Disease, Guizhou Provincial Key Laboratory of Pathogenesis and Prevention of Common Chronic Diseases Research, Guizhou Provincial People’s Hospital
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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.

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Cite

BibTeXRIS
BibTeX
@article{xie2026moesin,
  title = {{Moesin emerges as a potential exploratory biomarker associated with renal fibrosis in diabetic kidney disease}},
  author = {Ying Xie and Jing Ding and Zhengwei Liang and Rongrui Zhang and Sha Lv and Qian Zhang and Jingjing Da and Deqin Lu},
  journal = {Scientific Reports},
  year = {2026},
  month = sep,
  doi = {10.1038/s41598-026-69932-2},
  url = {https://doi.org/10.1038/s41598-026-69932-2},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Moesin emerges as a potential exploratory biomarker associated with renal fibrosis in diabetic kidney disease
AU  - Ying Xie
AU  - Jing Ding
AU  - Zhengwei Liang
AU  - Rongrui Zhang
AU  - Sha Lv
AU  - Qian Zhang
AU  - Jingjing Da
AU  - Deqin Lu
PY  - 2026
DA  - 2026/09/01
JO  - Scientific Reports
DO  - 10.1038/s41598-026-69932-2
UR  - https://doi.org/10.1038/s41598-026-69932-2
AB  - 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.
SN  - 2045-2322
ER  -