Literature DB >> 24589724

Multicentre prospective validation of a urinary peptidome-based classifier for the diagnosis of type 2 diabetic nephropathy.

Justyna Siwy1, Joost P Schanstra2, Angel Argiles3, Stephan J L Bakker4, Joachim Beige5, Petr Boucek6, Korbinian Brand7, Christian Delles8, Flore Duranton9, Beatriz Fernandez-Fernandez10, Marie-Luise Jankowski11, Mohammad Al Khatib12, Thomas Kunt12, Maria Lajer13, Ralf Lichtinghagen7, Morten Lindhardt13, David M Maahs14, Harald Mischak15, William Mullen8, Gerjan Navis16, Marina Noutsou17, Alberto Ortiz10, Frederik Persson13, John R Petrie8, Johannes M Roob18, Peter Rossing19, Piero Ruggenenti20, Ivan Rychlik21, Andreas L Serra22, Janet Snell-Bergeon14, Goce Spasovski23, Olivera Stojceva-Taneva23, Matias Trillini24, Heiko von der Leyen25, Brigitte M Winklhofer-Roob26, Petra Zürbig27, Joachim Jankowski11.   

Abstract

BACKGROUND: Diabetic nephropathy (DN) is one of the major late complications of diabetes. Treatment aimed at slowing down the progression of DN is available but methods for early and definitive detection of DN progression are currently lacking. The 'Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria trial' (PRIORITY) aims to evaluate the early detection of DN in patients with type 2 diabetes (T2D) using a urinary proteome-based classifier (CKD273).
METHODS: In this ancillary study of the recently initiated PRIORITY trial we aimed to validate for the first time the CKD273 classifier in a multicentre (9 different institutions providing samples from 165 T2D patients) prospective setting. In addition we also investigated the influence of sample containers, age and gender on the CKD273 classifier.
RESULTS: We observed a high consistency of the CKD273 classification scores across the different centres with areas under the curves ranging from 0.95 to 1.00. The classifier was independent of age (range tested 16-89 years) and gender. Furthermore, the use of different urine storage containers did not affect the classification scores. Analysis of the distribution of the individual peptides of the classifier over the nine different centres showed that fragments of blood-derived and extracellular matrix proteins were the most consistently found.
CONCLUSION: We provide for the first time validation of this urinary proteome-based classifier in a multicentre prospective setting and show the suitability of the CKD273 classifier to be used in the PRIORITY trial.
© The Author 2014. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Entities:  

Keywords:  biomarkers; chronic kidney disease; diabetic nephropathy; diagnosis; urine proteomics

Mesh:

Substances:

Year:  2014        PMID: 24589724      PMCID: PMC4118140          DOI: 10.1093/ndt/gfu039

Source DB:  PubMed          Journal:  Nephrol Dial Transplant        ISSN: 0931-0509            Impact factor:   5.992


  35 in total

1.  Debate: CON position. Should microalbuminuria ever be considered as a renal endpoint in any clinical trial?

Authors:  Richard J Glassock
Journal:  Am J Nephrol       Date:  2010-04-22       Impact factor: 3.754

2.  Two-dimensional gel electrophoresis of urinary proteins in kidney diseases.

Authors:  A Argiles; G Mourad; C Mion; R C Atkins; J Haiech
Journal:  Contrib Nephrol       Date:  1990       Impact factor: 1.580

3.  Identification and validation of urinary biomarkers for differential diagnosis and evaluation of therapeutic intervention in anti-neutrophil cytoplasmic antibody-associated vasculitis.

Authors:  Marion Haubitz; David M Good; Alexander Woywodt; Hermann Haller; Harald Rupprecht; Dan Theodorescu; Mohammed Dakna; Joshua J Coon; Harald Mischak
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4.  How to get proteomics to the clinic? Issues in clinical proteomics, exemplified by CE-MS.

Authors:  Harald Mischak
Journal:  Proteomics Clin Appl       Date:  2012-09-24       Impact factor: 3.494

5.  Urine biomarkers predict the cause of glomerular disease.

Authors:  Sanju A Varghese; T Brian Powell; Milos N Budisavljevic; Jim C Oates; John R Raymond; Jonas S Almeida; John M Arthur
Journal:  J Am Soc Nephrol       Date:  2007-02-14       Impact factor: 10.121

Review 6.  Chronic kidney disease: a new look at pathogenetic mechanisms and treatment options.

Authors:  Damien Noone; Christoph Licht
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7.  In patients with type 1 diabetes and new-onset microalbuminuria the development of advanced chronic kidney disease may not require progression to proteinuria.

Authors:  Bruce A Perkins; Linda H Ficociello; Bijan Roshan; James H Warram; Andrzej S Krolewski
Journal:  Kidney Int       Date:  2010-01       Impact factor: 10.612

Review 8.  Mechanisms and treatment of CKD.

Authors:  Piero Ruggenenti; Paolo Cravedi; Giuseppe Remuzzi
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9.  A comparison between MALDI-MS and CE-MS data for biomarker assessment in chronic kidney diseases.

Authors:  L Molin; R Seraglia; A Lapolla; E Ragazzi; J Gonzalez; A Vlahou; J P Schanstra; A Albalat; M Dakna; J Siwy; J Jankowski; V Bitsika; H Mischak; P Zürbig; P Traldi
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10.  Addressing the challenge of defining valid proteomic biomarkers and classifiers.

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  37 in total

Review 1.  Proteomic biomarkers in kidney disease: issues in development and implementation.

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Review 3.  Proteomic urinary biomarker approach in renal disease: from discovery to implementation.

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Review 4.  Current state of the art for enhancing urine biomarker discovery.

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Review 5.  Urinary proteomics using capillary electrophoresis coupled to mass spectrometry for diagnosis and prognosis in kidney diseases.

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Review 8.  Urinary Proteomics for Diagnosis and Monitoring of Diabetic Nephropathy.

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Journal:  Curr Diab Rep       Date:  2016-11       Impact factor: 4.810

Review 9.  Combination use of medicines from two classes of renin-angiotensin system blocking agents: risk of hyperkalemia, hypotension, and impaired renal function.

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Review 10.  Diabetic Kidney Disease in Adolescents With Type 2 Diabetes: New Insights and Potential Therapies.

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