Dataset Information

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

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.

SUBMITTER: Schanstra JP

PROVIDER: S-EPMC4520165 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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

Schanstra Joost P JP Zürbig Petra P Alkhalaf Alaa A Argiles Angel A Bakker Stephan J L SJ Beige Joachim J Bilo Henk J G HJ Chatzikyrkou Christos C Dakna Mohammed M Dawson Jesse J Delles Christian C Haller Hermann H Haubitz Marion M Husi Holger H Jankowski Joachim J Jerums George G Kleefstra Nanne N Kuznetsova Tatiana T Maahs David M DM Menne Jan J Mullen William W Ortiz Alberto A Persson Frederik F Rossing Peter P Ruggenenti Piero P Rychlik Ivan I Serra Andreas L AL Siwy Justyna J Snell-Bergeon Janet J Spasovski Goce G Staessen Jan A JA Vlahou Antonia A Mischak Harald H Vanholder Raymond R

Journal of the American Society of Nephrology : JASN 20150114 8

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 pr ...[more]

PMID: 25589610

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Project description:Introduction:Chronic kidney disease of uncertain etiology (CKDu), an emerging chronic kidney disease (CKD) subtype, contributes to significant morbidity and mortality in certain tropical countries. Although several indicators of CKDu have been previously suggested, sensitive and specific tests to detect early disease or predict disease progression are currently unavailable. This study focused on evaluating 8 renal urinary markers, namely neutrophil gelatinase-associated lipocalin (NGAL), Kidney Injury Molecule-1 (KIM1), cystatin C (CST3), beta 2 microglobulin (B2M), osteopontin (OPN), alpha 1 microglobulin (A1M), tissue inhibitor of metalloproteinase 1 (TIMP1), and retinol binding protein 4 (RBP4), with the hypothesis that these have distinct expression patterns in patients with CKDu. Methods:A cross-sectional study was conducted with 5 study groups comprising subjects from CKDu, endemic CKD, nonendemic CKD, and endemic healthy and nonendemic healthy controls. The urinary levels of the 8 selected renal biomarkers were quantified using multiplex biomarker assay, and the data were subjected to systematic analysis using logistic regression algorithm aiming to extract the best marker combination that could distinctly identify the disease groups noninvasively from the healthy controls. Results:A 3-marker signature panel comprising A1M, KIM1, and RBP4 was identified to represent the best minimum marker combination for differentiating all CKD categories, including CKDu, from healthy controls with an overall sensitivity of ?0.867 and specificity ?0.765. The marker combination comprising OPN, KIM1, and RBP4 showed high predictive performance for distinguishing patients with CKDu from patients with CKD with both sensitivity and specificity ?0.93, which was superior to any existing noninvasive indicator. Conclusion:In all, our systematic evaluation of urinary markers previously linked to CKD, in general, allowed identification of exclusive marker panel combination for early diagnosis and confirmation of CKDu.

Dataset Information

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

Publications

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

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