Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/12581
Title: Diagnosis and Prediction of CKD Progression by Assessment of Urinary Peptides.
Austin Authors: Schanstra, Joost P;Zürbig, Petra;Alkhalaf, Alaa;Argiles, Angel;Bakker, Stephan J L;Beige, Joachim;Bilo, Henk J G;Chatzikyrkou, Christos;Dakna, Mohammed;Dawson, Jesse;Delles, Christian;Haller, Hermann;Haubitz, Marion;Husi, Holger;Jankowski, Joachim;Jerums, George ;Kleefstra, Nanne;Kuznetsova, Tatiana;Maahs, David M;Menne, Jan;Mullen, William;Ortiz, Alberto;Persson, Frederik;Rossing, Peter;Ruggenenti, Piero;Rychlik, Ivan;Serra, Andreas L;Siwy, Justyna;Snell-Bergeon, Janet;Spasovski, Goce;Staessen, Jan A;Vlahou, Antonia;Mischak, Harald;Vanholder, Raymond
Affiliation: Department of Nephrology and Hypertension, University Hospital of Magdeburg, Magdeburg, Germany
Studies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven, Leuven, Belgium
Division of Biotechnology, Biomedical Research Foundation, Academy of Athens, Athens, Greece
Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
Division of Nephrology, University Hospital, and Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Switzerland
School of Medicine, Jimenez Diaz Foundation Institute for Health Research, Autonomous University of Madrid, Madrid, Spain
Institute for Molecular Cardiovascular Research, RWTH Aachen University Hospital, Aachen, Germany
Department of Nephrology, Klinikum Fulda gAG, Fulda, Germany
Department of Nephrology and Hypertension, Medical School of Hanover, Hanover, Germany
RD Néphrologie, Montpellier, France
Paul Sabatier University (Toulouse III), Toulouse, France
Austin Health, University of Melbourne, Heidelberg, Australia
Institute of Cardiovascular and Metabolic Disease, French Institute of Health and Medical Research U1048, Toulouse, France
Department of Internal Medicine IV, Charity Medical University of Berlin, Berlin, Germany
mosaiques diagnostics GmbH, Hanover, Germany
KfH Renal Unit, Department Nephrology, Leipzig and Martin-Luther-University, Halle/Wittenberg, Germany
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;
BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom;
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;
Mario Negri Institute of Pharmacology Research, Bergamo, Italy;
Second Department of Internal Medicine, Third Faculty of Medicine, Charles University, Prague, Czech Republic;
Barbara Davis Center for Childhood Diabetes, University of Colorado Denver, Aurora, Colorado;
University Department of Nephrology, Medical Faculty, University of Skopje, Skopje, Macedonia;
Nephrology Section, Department of Internal Medicine, Ghent University Hospital, Ghent, Belgium.
Issue Date: 14-Jan-2015
Publication information: Journal of the American Society of Nephrology : Jasn 2015; 26(8): 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.
Gov't Doc #: 25589610
URI: http://ahro.austin.org.au/austinjspui/handle/1/12581
DOI: 10.1681/ASN.2014050423
URL: https://pubmed.ncbi.nlm.nih.gov/25589610
Type: Journal Article
Subjects: CKD
albuminuria
biomarker
extracellular matrix
fibrosis
renal progression
Appears in Collections:Journal articles

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