Naturally Occurring Human Urinary Peptides for Use in Diagnosis of Chronic Kidney Disease

Good, D. M. et al. (2010) Naturally Occurring Human Urinary Peptides for Use in Diagnosis of Chronic Kidney Disease. Molecular and Cellular Proteomics, 9(11), pp. 2424-2437. (doi: 10.1074/mcp.M110.001917)

Full text not currently available from Enlighten.

Publisher's URL: http://dx.doi.org/10.1074/mcp.M110.001917

Abstract

Owing to 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 800-17,000 Da - using samples from 3,600 individuals analyzed by capillary electrophoresis coupled to mass spectrometry (CE-MS). All processed data were deposited in a 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 (CKD) allowing diagnosis of these diseases with high accuracy. Application of the CKD-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 CE-MS for clinical applications in the analysis of naturally occurring urinary peptides.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Schiffer, Dr Eric and Dominiczak, Professor Anna and Delles, Professor Christian and Mischak, Professor Harald
Authors: Good, D. M., Zurbig, P., Argiles, A., Bauer, H. W., Behrens, G., Coon, J. J., Dakna, M., Decramer, S., Delles, C., Dominiczak, A. F., Ehrich, J. H. H., Eitner, F., Fliser, D., Frommberger, M., Ganser, A., Girolami, M. A., Golovko, I., Gwinner, W., Haubitz, M., Herget-Rosenthal, S., Jankowski, J., Jahn, H., Jerums, G., Julian, B. A., Kellmann, M., Kliem, V., Kolch, W., Krolewski, A. S., Luppi, M., Massy, Z., Melter, M., Neususs, C., Novak, J., Peter, K., Rossing, K., Rupprecht, H., Schanstra, J. P., Schiffer, E., Stolzenburg, J.-U., Tarnow, L., Theodorescu, D., Thongboonkerd, V., Vanholder, R., Weissinger, E. M., Mischak, H., and Schmitt-Kopplin, P.
College/School:College of Medical Veterinary and Life Sciences
College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
Journal Name:Molecular and Cellular Proteomics
Publisher:American Society for Biochemistry and Molecular Biology, Inc.
ISSN:1535-9476
ISSN (Online):1535-9484
Published Online:08 July 2010
Related URLs:

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
396841Probabilistic Reconstruction of Signalling Pathways & Identification of Novel Transcription Factors Employing Heterogeneous Genome-Wide dataMark GirolamiMedical Research Council (MRC)G0401466Computing Science