Justyna Siwy1, Petra Zürbig1, Angel Argiles2, Joachim Beige3, Marion Haubitz4, Joachim Jankowski5,6, Bruce A Julian7, Peter G Linde8, David Marx9, Harald Mischak1,10, William Mullen10, Jan Novak7, Alberto Ortiz11, Frederik Persson12, Claudia Pontillo1,13, Peter Rossing12,14,15, Harald Rupprecht16, Joost P Schanstra17,18, Antonia Vlahou19, Raymond Vanholder20. 1. Mosaiques Diagnostics GmbH, Hanover, Germany. 2. RD Néphrologie, Montpellier, France. 3. KfH Renal Unit, Department Nephrology, Leipzig and Martin Luther University, Halle/Wittenberg, Germany. 4. Department of Nephrology, Klinikum Fulda gAG, Fulda, Germany. 5. Institute for Molecular Cardiovascular Research, RWTH Aachen University Hospital, Aachen, Germany. 6. School for Cardiovascular Diseases (CARIM), University of Maastricht, Maastricht, The Netherlands. 7. University of Alabama at Birmingham, Birmingham, AL, USA. 8. Abbvie, North Chicago, IL, USA. 9. Department of Nephrology and Kidney Transplantation, Hôpitaux Universitaires de Strasbourg, Strasbourg, France. 10. BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK. 11. School of Medicine, Jimenez Diaz Foundation Institute for Health Research, Autonomous University of Madrid, Madrid, Spain. 12. Steno Diabetes Center, Gentofte, Denmark. 13. Charite-Universitätsmedizin, Berlin, Germany. 14. Faculty of Health, University of Aarhus, Aarhus, Denmark. 15. Faculty of Health, University of Copenhagen, Copenhagen, Denmark. 16. Department of Nephrology, Klinikum Bayreuth, Bayreuth, Germany. 17. Institute of Cardiovascular and Metabolic Disease, French Institute of Health and Medical Research U1048, Toulouse, France. 18. Université Toulouse III Paul-Sabatier, Toulouse, France. 19. Division of Biotechnology, Biomedical Research Foundation, Academy of Athens, Athens, Greece. 20. Nephrology Section, Department of Internal Medicine, Ghent University Hospital, Ghent, Belgium.
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.
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.
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Authors: Laurence Beck; Andrew S Bomback; Michael J Choi; Larry B Holzman; Carol Langford; Laura H Mariani; Michael J Somers; Howard Trachtman; Meryl Waldman Journal: Am J Kidney Dis Date: 2013-07-18 Impact factor: 8.860
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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 Journal: J Proteomics Date: 2012-07-26 Impact factor: 4.044
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Authors: Bruce A Julian; Stefan Wittke; Marion Haubitz; Petra Zürbig; Eric Schiffer; Brendan M McGuire; Robert J Wyatt; Jan Novak Journal: World J Urol Date: 2007-07-10 Impact factor: 3.661
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Authors: Lorenzo Catanese; Justyna Siwy; Emmanouil Mavrogeorgis; Kerstin Amann; Harald Mischak; Joachim Beige; Harald Rupprecht Journal: Proteomes Date: 2021-07-13
Authors: Ahmed Alaini; Deepak Malhotra; Helbert Rondon-Berrios; Christos P Argyropoulos; Zeid J Khitan; Dominic S C Raj; Mark Rohrscheib; Joseph I Shapiro; Antonios H Tzamaloukas Journal: World J Methodol Date: 2017-09-26