Simple jQuery Dropdowns
Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/28611
Title: Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease
Authors: David M. Good
Petra Zürbig
Àngel Argilés
Hartwig W. Bauer
Georg Behrens
Joshua J. Coon
Mohammed Dakna
Stéphane Decramer
Christian Delles
Anna F. Dominiczak
Jochen H.H. Ehrich
Frank Eitner
Danilo Fliser
Moritz Frommberger
Arnold Ganser
Mark A. Girolami
Igor Golovko
Wilfried Gwinner
Marion Haubitz
Stefan Herget-Rosenthal
Joachim Jankowski
Holger Jahn
George Jerums
Bruce A. Julian
Markus Kellmann
Volker Kliem
Walter Kolch
Andrzej S. Krolewski
Mario Luppi
Ziad Massy
Michael Melter
Christian Neusüss
Jan Novak
Karlheinz Peter
Kasper Rossing
Harald Rupprecht
Joost P. Schanstra
Eric Schiffer
Jens Uwe Stolzenburg
Lise Tarnow
Dan Theodorescu
Visith Thongboonkerd
Raymond Vanholder
Eva M. Weissinger
Harald Mischak
Philippe Schmitt-Kopplinr
University of Wisconsin Madison
Mosaiques Diagnostics and Therapeutics AG
RD Néphrologie
Ludwig-Maximilians-Universitat Munchen
Medizinische Hochschule Hannover (MHH)
Inserm
Hopital des Enfants
University of Glasgow
Medizinische Fakultat und Universitats Klinikum Aachen
Universitatsklinikum des Saarlandes Medizinische Fakultat der Universitat des Saarlandes
Helmholtz Center Munich German Research Center for Environmental Health
Red Cross Hospital
Charité – Universitätsmedizin Berlin
Universitatsklinikum Hamburg-Eppendorf und Medizinische Fakultat
University of Melbourne
University of Alabama
Thermo Fisher Scientific, Germany
Lower Saxony Centre for Nephrology
University College Dublin
Joslin Diabetes Center
Harvard Medical School
Universita degli Studi di Modena e Reggio Emilia
CHU Amiens Picardie
Universitat Regensburg
University of Aalen
Baker Heart and Diabetes Institute
Steno Diabetes Center
Transfusion Centre Bayreuth
Universitat Leipzig
University of Virginia
Mahidol University
University Hospital of Ghent
University Colorado Cancer Center
Keywords: Biochemistry, Genetics and Molecular Biology;Chemistry
Issue Date: 1-Nov-2010
Citation: Molecular and Cellular Proteomics. Vol.9, No.11 (2010), 2424-2437
Abstract: Because of its availability, ease of collection, and correlation with physiology and pathology, urine is an attractive source for clinical proteomics/peptidomics. However, the lack of comparable data sets from large cohorts has greatly hindered the development of clinical proteomics. Here, we report the establishment of a reproducible, high resolution method for peptidome analysis of naturally occurring human urinary peptides and proteins, ranging from 800 to 17,000 Da, using samples from 3,600 individuals analyzed by capillary electrophoresis coupled to MS. All processed data were deposited in an Structured Query Language (SQL) database. This database currently contains 5,010 relevant unique urinary peptides that serve as a pool of potential classifiers for diagnosis and monitoring of various diseases. As an example, by using this source of information, we were able to define urinary peptide biomarkers for chronic kidney diseases, allowing diagnosis of these diseases with high accuracy. Application of the chronic kidney disease-specific biomarker set to an independent test cohort in the subsequent replication phase resulted in 85.5% sensitivity and 100% specificity. These results indicate the potential usefulness of capillary electrophoresis coupled to MS for clinical applications in the analysis of naturally occurring urinary peptides. © 2010 by The American Society for Biochemistry and Molecular Biology, Inc.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78149291420&origin=inward
http://repository.li.mahidol.ac.th/dspace/handle/123456789/28611
ISSN: 15359484
15359476
Appears in Collections:Scopus 2006-2010

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.