title: Noninvasive diagnosis of chronic kidney diseases using urinary proteome analysis.
abstract: BACKGROUND
  In spite of its invasive nature and risks, kidney biopsy is currently required for precise diagnosis of many chronic kidney diseases (CKDs). Here, we explored the hypothesis that analysis of the urinary proteome can discriminate different types of CKD irrespective of the underlying mechanism of disease.
  
  
  METHODS
  We used data from the proteome analyses of 1180 urine samples from patients with different types of CKD, generated by capillary electrophoresis coupled to mass spectrometry. A set of 706 samples served as the discovery cohort, and 474 samples were used for independent validation. For each CKD type, peptide biomarkers were defined using statistical analysis adjusted for multiple testing. Potential biomarkers of statistical significance were combined in support vector machine (SVM)-based classifiers.
  
  
  RESULTS
  For seven different types of CKD, several potential urinary biomarker peptides (ranging from 116 to 619 peptides) were defined and combined into SVM-based classifiers specific for each CKD. These classifiers were validated in an independent cohort and showed good to excellent accuracy for discrimination of one CKD type from the others (area under the receiver operating characteristic curve ranged from 0.77 to 0.95). Sequence analysis of the biomarkers provided further information that may clarify the underlying pathophysiology.
  
  
  CONCLUSIONS
  Our data indicate that urinary proteome analysis has the potential to identify various types of CKD defined by pathological assessment of renal biopsies and current clinical practice in general. Moreover, these approaches may provide information to model molecular changes per CKD.
authors.affiliation: Mosaiques Diagnostics GmbH, Hanover, Germany.
authors.forename: Justyna
authors.initials: J
authors.lastname: Siwy
authors.affiliation: Mosaiques Diagnostics GmbH, Hanover, Germany.
authors.forename: Petra
authors.initials: P
authors.lastname: Zürbig
authors.affiliation: RD Néphrologie, Montpellier, France.
authors.forename: Angel
authors.initials: A
authors.lastname: Argiles
authors.affiliation: KfH Renal Unit, Department Nephrology, Leipzig and Martin Luther University, Halle/Wittenberg, Germany.
authors.forename: Joachim
authors.initials: J
authors.lastname: Beige
authors.affiliation: Department of Nephrology, Klinikum Fulda gAG, Fulda, Germany.
authors.forename: Marion
authors.initials: M
authors.lastname: Haubitz
authors.affiliation: Institute for Molecular Cardiovascular Research, RWTH Aachen University Hospital, Aachen, Germany.|School for Cardiovascular Diseases (CARIM), University of Maastricht, Maastricht, The Netherlands.
authors.forename: Joachim
authors.initials: J
authors.lastname: Jankowski
authors.affiliation: University of Alabama at Birmingham, Birmingham, AL, USA.
authors.forename: Bruce A
authors.initials: BA
authors.lastname: Julian
authors.affiliation: Abbvie, North Chicago, IL, USA.
authors.forename: Peter G
authors.initials: PG
authors.lastname: Linde
authors.affiliation: Department of Nephrology and Kidney Transplantation, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.
authors.forename: David
authors.initials: D
authors.lastname: Marx
authors.affiliation: Mosaiques Diagnostics GmbH, Hanover, Germany.|BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
authors.forename: Harald
authors.initials: H
authors.lastname: Mischak
authors.affiliation: BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
authors.forename: William
authors.initials: W
authors.lastname: Mullen
authors.affiliation: University of Alabama at Birmingham, Birmingham, AL, USA.
authors.forename: Jan
authors.initials: J
authors.lastname: Novak
authors.affiliation: School of Medicine, Jimenez Diaz Foundation Institute for Health Research, Autonomous University of Madrid, Madrid, Spain.
authors.forename: Alberto
authors.initials: A
authors.lastname: Ortiz
authors.affiliation: Steno Diabetes Center, Gentofte, Denmark.
authors.forename: Frederik
authors.initials: F
authors.lastname: Persson
authors.affiliation: Mosaiques Diagnostics GmbH, Hanover, Germany.|Charite-Universitätsmedizin, Berlin, Germany.
authors.forename: Claudia
authors.initials: C
authors.lastname: Pontillo
authors.affiliation: Steno Diabetes Center, Gentofte, Denmark.|Faculty of Health, University of Aarhus, Aarhus, Denmark.|Faculty of Health, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Peter
authors.initials: P
authors.lastname: Rossing
authors.affiliation: Department of Nephrology, Klinikum Bayreuth, Bayreuth, Germany.
authors.forename: Harald
authors.initials: H
authors.lastname: Rupprecht
authors.affiliation: Institute of Cardiovascular and Metabolic Disease, French Institute of Health and Medical Research U1048, Toulouse, France.|Université Toulouse III Paul-Sabatier, Toulouse, France.
authors.forename: Joost P
authors.initials: JP
authors.lastname: Schanstra
authors.affiliation: Division of Biotechnology, Biomedical Research Foundation, Academy of Athens, Athens, Greece.
authors.forename: Antonia
authors.initials: A
authors.lastname: Vlahou
authors.affiliation: Nephrology Section, Department of Internal Medicine, Ghent University Hospital, Ghent, Belgium.
authors.forename: Raymond
authors.initials: R
authors.lastname: Vanholder
mesh_terms: D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000652:urine*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D020543:Proteome / Q000032:analysis*; D040901:Proteomics / Q000379:methods*; D012372:ROC Curve; D051436:Renal Insufficiency, Chronic / Q000175:diagnosis* / Q000652:urine; D016482:Urinalysis / Q000379:methods*
chemical_list: D015415:Biomarkers; D020543:Proteome
keywords: biomarkers; chronic kidney disease; peptides; proteome analysis; urine