July 12, 2010
Publication in molecular and cellular proteomics (MCP)
Good DM, Zürbig P, Argilés A, Bauer HW, Behrens G, Coon JJ, Dakna M, Decramer S, Delles C, Dominiczak AF, Ehrich JHH, Eitner F, Fliser D, Frommberger M, Ganser A, Girolami MA, Golovko I, Gwinner W, Haubitz M, Herget-Rosenthal S, Jankowski J, Jahn H, Jerums G, Julian BA, Kellmann M, Kliem V, Kolch W, Krolewski AS, Luppi M, Massy Z, Melter M, Neusüss C, Novak J, Peter K, Rossing K, Rupprecht H , Schanstra JP, Schiffer E, Stolzenburg JU, Tarnow L, Theodorescu D, Thongboonkerd V, Vanholder R, Weissinger EM, Mischak H, Schmitt-Kopplin P
Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease.
MCP 2010 Jul
Urine is an attractive source for clinical proteomics/peptidomics. Due to the lack of comparable data sets from large cohorts, the development of clinical proteomics was yet greatly hindered. In this publication the establishment of a reproducible, high-resolution method for peptidome analysis of naturally occurring human urinary peptides and proteins using samples from 3,600 individuals analyzed by capillary electrophoresis coupled to mass spectrometry (CE-MS) is reported. All processed data being stored in a database (currently 5,010 urinary peptides) serve as a pool of potential classifiers for diagnosis and monitoring of various diseases. Using this information, the authors were able to define urinary peptide biomarkers for chronic kidney diseases (CKD) allowing diagnosis of these diseases with high accuracy (85.5% sensitivity and 100% specificity). These results indicate the potential usefulness of CE-MS for clinical applications in the analysis of naturally occurring urinary peptides.