Mining biomarkers for type 2 diabetic nephropathy based on urinary proteomics and metabolomics
Поиск биомаркеров диабетической нефропатии 2 типа на основе протеомики и метаболомики мочи
2026-06-22
SCID: 54.1/9vntvsbg
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albumin-to-creatinine ratio (ACR)urinary SERPINA1urinary amino acid panelurinary metabolomicsurinary proteomics
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Abstract (AI)
Background: To evaluate and identify urinary biomarkers for the early diagnosis and staging of diabetic kidney disease (DKD). Methods: This study enrolled 200 participants, including healthy controls (NDM, n=50) and patients with type 2 diabetes. The diabetic patients were stratified by urinary albumin-to-creatinine ratio (ACR) into the following groups: normoalbuminuria (SDM, n=50), microalbuminuria (MADKD, n=50), and macroalbuminuria (ADKD, n=50). Utilizing an integrated multi-dimensional screening strategy, we systematically evaluated traditional urinary protein markers (urinary retinol-binding protein [URBP], urinary immunoglobulin G [UIgG], urinary transferrin [UTRF], urinary alpha-1-microglobulin [Uα1-MG], and urinary beta-2-microglobulin [Uβ2-MG]), 20 urinary amino acids, and urinary proteins identified via high-throughput mass spectrometry. Candidate proteins were validated by ELISA, and their diagnostic performance was assessed using ROC curve analysis, with ACR serving as the practical clinical reference. Results: Among the traditional urinary protein markers, UTRF and UIgG demonstrated excellent diagnostic value, with areas under the curve (AUC) of 0.926 and 0.916, respectively. Among the amino acids, PRO showed the best diagnostic performance (AUC = 0.746). However, when all 20 urinary amino acids were combined into a diagnostic model, it exhibited outstanding diagnostic value (AUC = 0.928), outperforming individual amino acids and even traditional protein markers. From the top 50 proteins identified in the proteomic screening, serpin family A member 1 (SERPINA1) was determined to be a key protein. Subsequent ELISA validation and ROC analysis further confirmed that SERPINA1 possesses outstanding diagnostic capability (AUC = 0.964, 95% CI: 0.936-0.990), significantly outperforming other candidate proteins, namely osteoclast-associated Ig-like receptor (OSCAR), contactin 1 (CNTN1), and CD58 molecule (CD58). Conclusions: Traditional proteins, especially UTRF/UIgG, hold diagnostic value. The 20-amino-acid combination (AUC = 0.928) outperformed them. This study first systematically identifies urinary SERPINA1 as a highly promising DKD biomarker, offering a novel target for early diagnosis and precise management.
Key Findings
1
A combined diagnostic model using all 20 urinary amino acids achieved outstanding diagnostic performance (AUC = 0.928), outperforming individual amino acids and traditional protein markers.
2
Among traditional urinary protein markers, urinary transferrin (UTRF) and urinary immunoglobulin G (UIgG) showed excellent diagnostic value for DKD (AUC 0.926 and 0.916).
3
Proline (PRO) was the best-performing single urinary amino acid for DKD diagnosis (AUC = 0.746).
4
Proteomic screening identified SERPINA1 as a key urinary protein biomarker; ELISA validation showed SERPINA1 had superior diagnostic capability (AUC = 0.964, 95% CI: 0.936-0.990).
5
SERPINA1 significantly outperformed other candidate proteins (OSCAR, CNTN1, CD58) as a urinary biomarker for DKD, suggesting it as a novel target for early diagnosis and precise management.
Research Object
Urinary biomarkers (proteins and amino acids) from patients with type 2 diabetic nephropathy / diabetic kidney disease
Research Subject
Diagnostic performance for early diagnosis and staging of diabetic kidney disease, including identification and validation of specific urinary biomarkers (e.g., SERPINA1, UTRF, UIgG, combined 20-amino-acid panel) assessed by ROC/AUC against ACR-based clinical staging
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2026-06-22
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