Summary
This study examined the utility of urinary proteomics analysis using capillary electrophoresis coupled to mass spectrometry (CE-MS) for diagnosing chronic kidney disease (CKD) and predicting rapid kidney function decline. The authors analyzed urine samples from 18 CKD patients (including those with hypertensive nephropathy) and 17 healthy controls. They found that a urinary proteomic classifier based on 273 peptides had superior diagnostic accuracy for CKD compared to urine albumin dipstick testing. Additionally, the proteomic classifier improved the identification of patients with rapid kidney function decline when combined with albuminuria data. Reduced urinary levels of collagens I-III, uromodulin, and other proteins implicated in fibrosis and tubular dysfunction were associated with CKD diagnosis and rapid progression.
Strengths of the study
- Clinically relevant study comparing a novel biomarker approach to existing methods for CKD diagnosis and prognosis prediction
- Inclusion of hypertensive nephropathy patients, an understudied but prevalent CKD population
- Rigorous statistical analyses, including ROC curves and reclassification analyses
- Use of the well-established CE-MS platform for urinary proteomics
- Thorough biochemical interpretation of identified proteomic differences
Weaknesses of the study
- Small sample size, especially for subgroup analyses by CKD etiology
- Single-center study, limiting generalizability
- Cross-sectional design for diagnostic analyses
- Lack of adjustment for potential confounding variables in some analyses
- Heavy reliance on retrospective eGFR data for defining disease progression
The findings suggest urinary proteomics could complement current clinical biomarkers like albuminuria for improved CKD diagnosis and prognosis. However, larger prospective multicenter studies are needed to validate the clinical utility of this approach across diverse CKD populations and care settings before potential implementation. The reduced levels of specific urinary proteins provide insights into shared pathways of fibrosis and tubular injury in CKD progression, regardless of underlying cause.
Concluding remarks
In summary, this study highlights the potential of urinary proteomics for enhanced CKD diagnosis and risk prediction but also demonstrates the need for larger prospective clinical validation studies before potential implementation of this approach. The proteomic findings provide insights into common pathways of CKD progression across different etiologies.
Read this article at https://link.springer.com/article/10.1186/s12014-015-9092-7
