A URINARY PROTEOME-BASED CLASSIFIER FOR THE EARLY DETECTION OF DECLINE IN GLOMERULAR FILTRATION

Background. Chronic kidney disease (CKD) progression is currently assessed by a decline in estimated glomerular filtration rate (eGFR) and/or an increase in urinary albumin excretion (UAE). However, these markers are considered either to be latestage markers or to have low sensitivity or specificity. In this study, we investigated the performance of the urinary proteome-based classifier CKD273, compared with UAE, in a number of different narrow ranges of CKD severity, with each range separated by an eGFR of 10 mL/min/1.73 m(2). Methods. A total of 2672 patients with different CKD stages were included in the study. Of these, 394 individuals displayed a decline in eGFR of > 5 mL/min/1.73 m(2)/year (progressors) and the remaining individuals were considered non-progressors. For all samples, UAE values and CKD273 classification scores were obtained. To assess UAE values and CKD273 scores at different disease stages, the cohort was divided according to baseline eGFRs of >= 80, 70-79, 60-69, 50-59, 40-49, 30-39 and < 29 mL/min/1.73 m(2). In addition, areas under the curve for CKD273 and UAE were calculated. Results. In early stage CKD, the urinary proteome-based classifier performed significantly better than UAE in detecting progressors. In contrast, UAE performed better in patients with late-stage CKD. No significant difference in performance was found between CKD273 and UAE in patients with moderately reduced renal function. Conclusions. These results suggest that urinary peptides, as combined in the CKD273 classifier, allow the detection of progressive CKD at early stages, a point where therapeutic intervention is more likely to be effective. However, late-stage disease, where irreversible damage of the kidney is already present, is better detected by UAE.