Revealing VCAN as a Potential Common Diagnostic Biomarker of Renal Tubules and Glomerulus in Diabetic Kidney Disease Based on Machine Learning, Single-Cell Transcriptome Analysis and Mendelian Randomization
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Updated: Oct 26, 2026
Assessment of Kidney Function in Mouse Models of Glomerular Disease
Published on: June 30, 2018
Li Jiang1, Jie Jian2, Xulin Sai3
1Diabetes Department of Integrated Chinese and Western Medicine, China National Center for Integrated Traditional Chinese and Western Medicine, China- Japan Friendship Hospital, Beijing, China.
Backgruound:
Diabetic kidney disease (DKD) is recognized as a significant complication of diabetes mellitus and categorized into glomerular DKDs and tubular DKDs, each governed by distinct pathological mechanisms and biomarkers.
Methods:
Through the identification of common features observed in glomerular and tubular lesions in DKD, numerous differentially expressed gene were identified by the machine learning, single-cell transcriptome and mendelian randomization.
Results:
The diagnostic markers versican (VCAN) was identified, offering supplementary options for clinical diagnosis. VCAN significantly highly expressed in glomerular parietal epithelial cell and proximal convoluted tubular cell. It was mainly involved in the up-regulation of immune genes and infiltration of immune cells like mast cell. Mendelian randomization analysis confirmed that serum VCAN protein levels were a risky factor for DKD, while there was no reverse association. It exhibited the good diagnostic potential for estimated glomerular filtration rate and proteinuria in DKD.
Conclusion:
VCAN showed the prospects into DKD pathology and clinical indicator.
Insights
Diabetic kidney disease (DKD) involves distinct glomerular and tubular damage. Researchers identified versican (VCAN) as a key biomarker, showing potential for diagnosing DKD and its complications.
Area of Science:
- Nephrology
- Endocrinology
- Biomarker Discovery
Background:
- Diabetic kidney disease (DKD) is a major complication of diabetes mellitus.
- DKD is classified into glomerular and tubular forms, each with unique pathological pathways.
- Identifying shared features and biomarkers is crucial for understanding and managing DKD.
Purpose of the Study:
- To identify novel biomarkers for diabetic kidney disease.
- To explore the role of identified biomarkers in DKD pathogenesis.
- To evaluate the diagnostic potential of biomarkers for DKD.
Main Methods:
- Utilized machine learning and single-cell transcriptome analysis to identify differentially expressed genes in DKD.
- Employed Mendelian randomization to investigate causal relationships between gene expression and DKD.
- Analyzed the expression patterns and cellular localization of candidate biomarkers.
Main Results:
- Versican (VCAN) was identified as a diagnostic marker for DKD.
- VCAN is highly expressed in glomerular parietal epithelial and proximal convoluted tubular cells.
- VCAN is associated with immune gene upregulation and immune cell infiltration, and serum VCAN is a risk factor for DKD.
Conclusions:
- VCAN demonstrates significant potential as a biomarker for diabetic kidney disease.
- VCAN offers insights into the pathological mechanisms of DKD.
- VCAN may serve as a valuable clinical indicator for DKD diagnosis and management.
