Progressive CKD is generally detected at a late stage by a sustained decline in eGFR and/or the presence of significant albuminuria. With the aim of early and improved risk stratification of patients with CKD, we studied urinary peptides in a large cross-sectional multicenter cohort of 1990 individuals, including 522 with follow-up data, using proteome analysis. We validated that a previously established multipeptide urinary biomarker classifier performed significantly better in detecting and predicting progression of CKD than the current clinical standard, urinary albumin. The classifier was also more sensitive for identifying patients with rapidly progressing CKD. Compared with the combination of baseline eGFR and albuminuria (area under the curve [AUC]=0.758), the addition of the multipeptide biomarker classifier significantly improved CKD risk prediction (AUC=0.831) as assessed by the net reclassification index (0.303620.065; P,0.001) and integrated discrimination improvement (0.05860.014; P,0.001). Correlation of individual urinary peptides with CKD stage and progression showed that the peptides that associated with CKD, irrespective of CKD stage or CKD progression, were either fragments of the major circulating proteins, suggesting failure of the glomerular filtration barrier sieving properties, or different collagen fragments, suggesting accumulation of intrarenal extracellular matrix. Furthermore, protein fragments associated with progression of CKD originated mostly from proteins related to inflammation and tissue repair. Results of this study suggest that urinary proteome analysis might significantly improve the current state of the art of CKD detection and outcome prediction and that identification of the urinary peptides allows insight into various ongoing pathophysiologic processes in CKD.

A limitation of proteomic methods with respect to their clinical applicability is the lack of possibilities to directly deduce the amount of a protein or peptide from a particular mass spectrometry (MS) spectrum. For quantification of chronic kidney disease (CKD)-specific urinary polypeptides in capillary electrophoresis coupled with mass spectrometry (CE-MS), we compared signal intensity calibration methods based on either urinary creatinine or stable isotope labeled synthetic marker analogues (absolute quantification) with those based on ion counting using highly abundant collagen fragments as nonmarker references (relative quantification). Our results indicate that relative quantification of biomarker excretion based on ion counts in reference to endogenous "housekeeping" peptides is sufficient for the determination of urinary polypeptide levels. The calculation of absolute concentrations via exogenous stable isotope-labeled peptide standards is of no additional benefit.

Background: Microalbuminuria is an early sign of kidney disease in diabetes and indicates cardiovascular risk. We tested if a prespecified urinary proteomic risk classifier (CKD273) was associated with development of microalbuminuria and if progression to microalbuminuria could be prevented with the mineralocorticoid receptor antagonist spironolactone. Methods: Prospective multicentre study in people with type 2 diabetes, normal urinary albumin excretion and preserved renal function in 15 European specialist centres. High-risk individuals determined by CKD273 were randomised 1:1 (interactive web response system) in a double-blind randomised controlled trial comparing spironolactone 25 mg o.d. to placebo. Primary endpoint was development of confirmed microalbuminuria in all individuals with available data. Secondary endpoints included reduction in incidence of microalbuminuria with spironolactone and association between CKD273 and impaired renal function defined as a glomerular filtration rate < 60 ml/min per 1•73 m 2. This study is registered with ClinicalTrials.gov: NCT02040441 and is completed. Findings: From March 25, 2014 to September 30, 2018 we followed 1775 participants, 12% (n=216) had high-risk urinary proteomic pattern of which 209 were included in the trial and assigned spironolactone (n=102) or placebo (n=107). Median follow-up time was 2•51 years (IQR 2•0-3•0). Progression to microalbuminuria was seen in 28•2% of high-risk and 8•9% of low-risk people (P< 0•001) (hazard ratio (HR), 2•48; 95% confidence interval [CI], 1•80 to 3•42 P<0•001, independent of baseline clinical characteristics). A 30% decline in eGFR from baseline was seen in 42 (19•4 %) high-risk participants compared to 62 (3•9 %) low-risk participants, HR 5•15; 95 % CI (3•41 to 7•76; p<0.0001). Development of microalbuminuria was seen in 35 (33%) randomised to placebo and 26 (25%) randomised to spironolactone treatment (HR 0•81, 95% CI, 0•49 to 1•34, P=0•41). Harms: hyperkalaemia was seen in 13 versus 4, and gynaecomastia in 3 versus 0 subjects on spironolactone and placebo, respectively. Interpretation: In people with type 2 diabetes and normoalbuminuria, the urinary proteomic classifier CKD273 was associated with a 2•5 times increased risk for progression to microalbuminuria over a median of 2•5 years, independent of clinical characteristics. Spironolactone did not prevent progression to microalbuminuria in high-risk subjects.

Capillary electrophoresis combined with mass spectrometry (CE‐MS) has been used for several years for the investigation of proteins and peptides as biomarkers for diagnosis and prognosis of diseases. In addition, the technology has recently been introduced to support the stratification of patients in clinical trials and in large clinical studies. In this review, we aim at presenting the development of CE‐MS over the last 20 years, by focusing on the clinical potential of proteome and peptidome analysis and highlighting some of the key technical issues and advancements that have been made in this context towards implementation. Based on the reviewed literature, it has become evident that CE‐MS is now an accepted tool in clinical application in several disease areas. Apart from a critical overview on the current state‐of‐the‐art in CE‐MS, we also indicate the expected developments for potential future use.

Purpose: Urine proteomics is emerging as a powerful tool for biomarker discovery. The purpose of this study is the development of a well-characterized ''real life'' sample that can be used as reference standard in urine clinical proteomics studies. Experimental design: We report on the generation of male and female urine samples that are extensively characterized by different platforms and methods (CE-MS, LC-MS, LC-MS/MS, 1-D gel analysis in combination with nano-LC MS/MS (using LTQ-FT ultra), and 2-DE-MS) for their proteome and peptidome. In several cases analysis involved a definition of the actual biochemical entities, i.e. proteins/peptides associated with molecular mass and detected PTMs and the relative abundance of these compounds. Results: The combination of different technologies allowed coverage of a wide mass range revealing the advantages and complementarities of the different technologies. Application of these samples in ''inter-laboratory'' and ''inter-platform'' data comparison is also demonstrated. Conclusions and clinical relevance: These well-characterized urine samples are freely available upon request to enable data comparison especially in the context of biomarker discovery and validation studies. It is also expected that they will provide the basis for the comprehensive characterization of the urinary proteome.