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Diagnosis and prediction of CKD progression by assessment of urinary peptides

Joost P Schanstra, Petra Zürbig, Alaa Alkhalaf, Angel Argiles, Stephan JL Bakker, Joachim Beige, Henk JG Bilo, Christos Chatzikyrkou, Mohammed Dakna, Jesse Dawson, et al. (2015) JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY. 26(8). p.1999-2010
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.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
DIABETIC-NEPHROPATHY, POSITION STATEMENT, IMPROVING GLOBAL OUTCOMES, CHRONIC KIDNEY-DISEASE, PROTEOMIC ANALYSIS, ALBUMIN EXCRETION, RISK, BIOMARKERS, INJURY, NEED
journal title
JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY
J. Am. Soc. Nephrol.
volume
26
issue
8
pages
1999 - 2010
Web of Science type
Article
Web of Science id
000358895100024
JCR category
UROLOGY & NEPHROLOGY
JCR impact factor
8.491 (2015)
JCR rank
3/77 (2015)
JCR quartile
1 (2015)
ISSN
1046-6673
DOI
10.1681/ASN.2014050423
language
English
UGent publication?
yes
classification
A1
additional info
the first two authors contributed equally to this work
copyright statement
I have transferred the copyright for this publication to the publisher
id
7095199
handle
http://hdl.handle.net/1854/LU-7095199
date created
2016-02-22 15:07:11
date last changed
2016-12-19 15:45:21
@article{7095199,
  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{\textlangle}0.001) and integrated discrimination improvement (0.058 +/- 0.014; P{\textlangle}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.},
  author       = {Schanstra, Joost P and Z{\"u}rbig, Petra and Alkhalaf, Alaa and Argiles, Angel and Bakker, Stephan JL and Beige, Joachim and Bilo, Henk JG and Chatzikyrkou, Christos and Dakna, Mohammed and Dawson, Jesse and Delles, Christian and Haller, Hermann and Haubitz, Marion and Husi, Holger and Jankowski, Joachim and Jerums, George and Kleefstra, Nanne and Kuznetsova, Tatiana and Maahs, David M and Menne, Jan and Mullen, William and Ortiz, Alberto and Persson, Frederik and Rossing, Peter and Ruggenenti, Piero and Rychlik, Ivan and Serra, Andreas L and Siwy, Justyna and Snell-Bergeon, Janet and Spasovski, Goce and Staessen, Jan A and Vlahou, Antonia and Mischak, Harald and Vanholder, Raymond},
  issn         = {1046-6673},
  journal      = {JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY},
  keyword      = {DIABETIC-NEPHROPATHY,POSITION STATEMENT,IMPROVING GLOBAL OUTCOMES,CHRONIC KIDNEY-DISEASE,PROTEOMIC ANALYSIS,ALBUMIN EXCRETION,RISK,BIOMARKERS,INJURY,NEED},
  language     = {eng},
  number       = {8},
  pages        = {1999--2010},
  title        = {Diagnosis and prediction of CKD progression by assessment of urinary peptides},
  url          = {http://dx.doi.org/10.1681/ASN.2014050423},
  volume       = {26},
  year         = {2015},
}

Chicago
Schanstra, Joost P, Petra Zürbig, Alaa Alkhalaf, Angel Argiles, Stephan JL Bakker, Joachim Beige, Henk JG Bilo, et al. 2015. “Diagnosis and Prediction of CKD Progression by Assessment of Urinary Peptides.” Journal of the American Society of Nephrology 26 (8): 1999–2010.
APA
Schanstra, J. P., Zürbig, P., Alkhalaf, A., Argiles, A., Bakker, S. J., Beige, J., Bilo, H. J., et al. (2015). Diagnosis and prediction of CKD progression by assessment of urinary peptides. JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY, 26(8), 1999–2010.
Vancouver
1.
Schanstra JP, Zürbig P, Alkhalaf A, Argiles A, Bakker SJ, Beige J, et al. Diagnosis and prediction of CKD progression by assessment of urinary peptides. JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY. 2015;26(8):1999–2010.
MLA
Schanstra, Joost P, Petra Zürbig, Alaa Alkhalaf, et al. “Diagnosis and Prediction of CKD Progression by Assessment of Urinary Peptides.” JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY 26.8 (2015): 1999–2010. Print.