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 (0.303±-0.065; P<0.001) and integrated discrimination improvement (0.058±0.014; 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.

2nd Department of Internal Medicine 3rd Faculty of Medicine Charles University Prague Czech Republic;

Austin Health University of Melbourne Heidelberg Australia;

Barbara Davis Center for Childhood Diabetes University of Colorado Denver Aurora Colorado;

BHF Glasgow Cardiovascular Research Centre Institute of Cardiovascular and Medical Sciences University of Glasgow Glasgow United Kingdom;

Department of Cardiovascular Sciences University of Leuven Leuven Belgium; Faculty of Health University of Copenhagen Copenhagen Denmark;

Department of Nephrology and Hypertension Medical School of Hanover Hanover Germany;

Department of Nephrology and Hypertension University Hospital of Magdeburg Magdeburg Germany;

Department of Nephrology Klinikum Fulda gAG Fulda Germany;

Division of Biotechnology Biomedical Research Foundation Academy of Athens Athens Greece; School of Biomedical and Healthcare Sciences Plymouth University Plymouth United Kingdom; and

Division of Nephrology University Hospital and Epidemiology Biostatistics and Prevention Institute University of Zurich Switzerland;

Faculty of Health University of Copenhagen Copenhagen Denmark;

Institute for Molecular Cardiovascular Research RWTH Aachen University Hospital Aachen Germany; Department of Internal Medicine 4 Charity Medical University of Berlin Berlin Germany;

Institute of Cardiovascular and Metabolic Disease French Institute of Health and Medical Research U1048 Toulouse France; Paul Sabatier University Toulouse France;

KfH Renal Unit Department Nephrology Leipzig and Martin Luther University Halle Wittenberg Germany;

Mario Negri Institute of Pharmacology Research Bergamo Italy;

mosaiques diagnostics GmbH Hanover Germany;

mosaiques diagnostics GmbH Hanover Germany; Department of Internal Medicine 4 Charity Medical University of Berlin Berlin Germany;

Nephrology Section Department of Internal Medicine Ghent University Hospital Ghent Belgium

RD Néphrologie Montpellier France;

School of Medicine Jimenez Diaz Foundation Institute for Health Research Autonomous University of Madrid Madrid Spain;

Steno Diabetes Center Gentofte Denmark;

Steno Diabetes Center Gentofte Denmark; Faculty of Health University of Aarhus Aarhus Denmark; Faculty of Health University of Copenhagen Copenhagen Denmark;

University Department of Nephrology Medical Faculty University of Skopje Skopje Macedonia;

University Medical Center Groningen and University of Groningen Groningen The Netherlands;

University Medical Center Groningen and University of Groningen Groningen The Netherlands; Diabetes Centre Isala Clinics Zwolle The Netherlands;

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J Am Soc Nephrol. 2015 Aug;26(8):1760-1. doi: 10.1681/ASN.2014121243. PubMed

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Urine proteomics for prediction of disease progression in patients with IgA nephropathy

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