Format

Send to

Choose Destination
J Am Soc Nephrol. 2015 Aug;26(8):1999-2010. doi: 10.1681/ASN.2014050423. Epub 2015 Jan 14.

Diagnosis and Prediction of CKD Progression by Assessment of Urinary Peptides.

Author information

1
Institute of Cardiovascular and Metabolic Disease, French Institute of Health and Medical Research U1048, Toulouse, France; Paul Sabatier University (Toulouse III), Toulouse, France;
2
mosaiques diagnostics GmbH, Hanover, Germany; zuerbig@mosaiques-diagnostics.com.
3
University Medical Center Groningen and University of Groningen, Groningen, The Netherlands;
4
RD Néphrologie, Montpellier, France;
5
KfH Renal Unit, Department Nephrology, Leipzig and Martin-Luther-University, Halle/Wittenberg, Germany;
6
University Medical Center Groningen and University of Groningen, Groningen, The Netherlands; Diabetes Centre, Isala Clinics, Zwolle, The Netherlands;
7
Department of Nephrology and Hypertension, University Hospital of Magdeburg, Magdeburg, Germany;
8
mosaiques diagnostics GmbH, Hanover, Germany;
9
BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom;
10
Department of Nephrology and Hypertension, Medical School of Hanover, Hanover, Germany;
11
Department of Nephrology, Klinikum Fulda gAG, Fulda, Germany;
12
Institute for Molecular Cardiovascular Research, RWTH Aachen University Hospital, Aachen, Germany; Department of Internal Medicine IV, Charity Medical University of Berlin, Berlin, Germany;
13
Austin Health, University of Melbourne, Heidelberg, Australia;
14
Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium; Faculty of Health, University of Copenhagen, Copenhagen, Denmark;
15
Barbara Davis Center for Childhood Diabetes, University of Colorado Denver, Aurora, Colorado;
16
School of Medicine, Jimenez Diaz Foundation Institute for Health Research, Autonomous University of Madrid, Madrid, Spain;
17
Steno Diabetes Center, Gentofte, Denmark;
18
Steno Diabetes Center, Gentofte, Denmark; Faculty of Health, University of Aarhus, Aarhus, Denmark; Faculty of Health, University of Copenhagen, Copenhagen, Denmark;
19
Mario Negri Institute of Pharmacology Research, Bergamo, Italy;
20
Second Department of Internal Medicine, Third Faculty of Medicine, Charles University, Prague, Czech Republic;
21
Division of Nephrology, University Hospital, and Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Switzerland;
22
mosaiques diagnostics GmbH, Hanover, Germany; Department of Internal Medicine IV, Charity Medical University of Berlin, Berlin, Germany;
23
University Department of Nephrology, Medical Faculty, University of Skopje, Skopje, Macedonia;
24
Faculty of Health, University of Copenhagen, Copenhagen, Denmark;
25
Division of Biotechnology, Biomedical Research Foundation, Academy of Athens, Athens, Greece; School of Biomedical and Healthcare Sciences, Plymouth University, Plymouth, United Kingdom; and.
26
Nephrology Section, Department of Internal Medicine, Ghent University Hospital, Ghent, Belgium.

Abstract

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.

KEYWORDS:

CKD; albuminuria; biomarker; extracellular matrix; fibrosis; renal progression

PMID:
25589610
PMCID:
PMC4520165
DOI:
10.1681/ASN.2014050423
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for HighWire Icon for PubMed Central
Loading ...
Support Center