Because of 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 to 17,000 Da, using samples from 3,600 individuals analyzed by 
capillary electrophoresis coupled to MS. All processed data were deposited in an 
Structured Query Language (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, allowing diagnosis of these diseases with high 
accuracy. Application of the chronic kidney disease-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 capillary electrophoresis coupled to MS for clinical applications 
in the analysis of naturally occurring urinary peptides.