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hdl:10101/npre.2007.1219.1
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A database of naturally occurring human urinary peptides and proteins for use in clinical applications

Petra Zürbig1, Joshua Coon2, Hartwig Bauer3, Georg Behrens4, Mohammed Dakna1, Anna Dominiczak5, Stephane Decramer6, Jochen Ehrich7, Danilo Fliser8, Moritz Frommberger9, Arnold Ganser10, Mark Giolami11, Igor Golovko1, David Good12, Wilfried Gwinner8, Marion Haubitz8, Stefan Herget-Rosenthal13, Holger Jahn14, George Jerums15, Bruce Julian16, Markus Kellmann17, Volker Kliem18, Walter Kolch19, Andrzej Krolewski20, Mario Luppi21, Ziad Massy22, Michael Melter23, Christian Neusüss24, Jan Novak25, Karlheinz Peter26, Kasper Rossing27, Harald Rupprecht28, Joost Schanstra6, Eric Schiffer1, Jens-Uwe Stolzenburg29, Lise Tarnow27, Dan Theodorescu30, Visith Thongboonkerd31, Raymond Vanholder32, Eva Weissinger10, Harald Mischak1, & Philippe Schmitt-Kopplin9

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  1. Mosaiques diagnostics & therapeutics AG
  2. University of Wisconsin-Madison, Department of Chemistry and Biomolecular Chemistry
  3. Ludwig-Maximilians-University Munich
  4. Hannover Medical School, Department of Clinical Immunology
  5. University of Glasgow, BHF Glasgow Cardiovascular Research Centre
  6. CHU de Toulouse, Pediatric Nephrology Unit
  7. Hannover Medical School, Children's Hospital
  8. Hannover Medical School, Department of Nephrology
  9. GSF - National Research Centre for Environment and Health, Institute for Ecological Chemistry
  10. Hannover Medical School, Department of Hematology, Hemostasis and Oncology
  11. University of Glasgow, Department of Computing Science
  12. University of Wisconsin-Madison, Department of Chemistry
  13. University Duisburg-Essen, Department of Nephrology
  14. University Hospital Hamburg-Eppendorf, Department of Psychiatry
  15. University of Melbourne, Austin Health & Northern Health, Department of Medicine
  16. University of Alabama at Birmingham
  17. Thermo Fisher Scientific GmbH
  18. Saxony Centre for Nephrology, Transplantation Centre, Department of Nephrology Lower
  19. University of Glasgow, The Beatson Institute for Cancer Research & Sir Henry Wellcome Functional Genomics Facility
  20. Harvard Medical School, Department of Medicine
  21. University of Modena and Reggio Emilia, Department of Oncology and Hematology
  22. UPJV, INSERM, ERI-12, and Amiens University Hospital
  23. University of Regensburg, Children’s Hospital
  24. University of Aalen
  25. University of Alabama at Birmingham, Microbiology
  26. Heart Research Institute, Centre for Thrombosis & Myocardial Infarction
  27. Steno Diabetes Centre
  28. Clinical Centre Bayreuth, Department of Nephrology
  29. University of Leipzig, Department of Diagnostic Radiology
  30. University of Virginia
  31. Mahidol University, Faculty of Medicine at Siriraj Hospital
  32. University Hospital of Ghent, Department of Internal Medicine
Document Type:
Manuscript
Date:
Received 11 October 2007 07:09 UTC; Posted 12 October 2007
Subjects:
Biotechnology
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Abstract:

Owing to its availability, ease of collection and correlation with (patho-) physiology, urine is an attractive source for clinical proteomics. However, the lack of comparable datasets from large cohorts has greatly hindered development in this field. Here we report the establishment of a high resolution proteome database of naturally occurring human urinary peptides and proteins – ranging from 800-17,000 Da – from over 3,600 individual samples using capillary electrophoresis coupled to mass spectrometry, yielding an average of 1,500 peptides per sample. All processed data were deposited in an SQL database, currently containing 5,010 relevant unique urinary peptides that serve as classifiers for diagnosis and monitoring of diseases, including kidney and vascular diseases. Of these, 352 have been sequenced to date. To demonstrate the applicability of this database, two examples of disease diagnosis were provided: For renal damage diagnosis, patients with a specific renal disease were identified with high specificity and sensitivity in a blinded cohort of 131 individuals. We further show definition of biomarkers specific for immunosuppression and complications after transplantation (Kaposi’s sarcoma). Due to its high information content, this database will be a powerful tool for the validation of biomarkers for both renal and non-renal diseases.

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This document is licensed to the public under the Creative Commons Attribution 2.5 License
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Zürbig, Petra, Coon, Joshua, Bauer, Hartwig, Behrens, Georg, Dakna, Mohammed, Dominiczak, Anna, Decramer, Stephane, Ehrich, Jochen, Fliser, Danilo, Frommberger, Moritz, Ganser, Arnold, Giolami, Mark, Golovko, Igor, Good, David, Gwinner, Wilfried, Haubitz, Marion, Herget-Rosenthal, Stefan, Jahn, Holger, Jerums, George, Julian, Bruce, Kellmann, Markus, Kliem, Volker, Kolch, Walter, Krolewski, Andrzej, Luppi, Mario, Massy, Ziad, Melter, Michael, Neusüss, Christian, Novak, Jan, Peter, Karlheinz, Rossing, Kasper, Rupprecht, Harald, Schanstra, Joost, Schiffer, Eric, Stolzenburg, Jens-Uwe, Tarnow, Lise, Theodorescu, Dan, Thongboonkerd, Visith, Vanholder, Raymond, Weissinger, Eva, Mischak, Harald, and Schmitt-Kopplin, Philippe. A database of naturally occurring human urinary peptides and proteins for use in clinical applications. Available from Nature Precedings <http://hdl.handle.net/10101/npre.2007.1219.1> (2007)

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