Abstract
PURPOSE AND EXPERIMENTAL DESIGN: Diabetic nephropathy (DN) is the most common cause of end-stage renal disease and improved biomarkers would help identify high-risk individuals. The aim of this study was to discover candidate biomarkers for DN in the plasma peptidome in an in-house cross-sectional cohort (n=122) of type 1 diabetic patients diagnosed with normo-, micro-, and macroalbuminuria.
RESULTS: Automated, high-throughput, and reproducible (interassay median CV: 13-14%) plasma peptide profiling protocols involving RPC18 and weak cation exchange magnetic beads on a liquid handling workstation with a MALDI-TOF-MS readout were successfully established. Using these protocols and a combined univariate (Kruskal-Wallis) and multivariate (independent component analysis) statistical analysis approach, ten single peptides and three multi-peptide candidate biomarkers were found. Employment of RPC18 and weak cation exchange magnetic beads proved to be complementary.
CONCLUSIONS AND CLINICAL RELEVANCE: The proteins found in this study, including C3f and apolipoprotein C-I, represent new candidate biomarkers for DN from the plasma peptidome. The automated procedures and implementation of independent components analysis provide a fast and informative system for analyzing individual patient samples in protein biomarker discovery.
Originalsprog | Engelsk |
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Tidsskrift | Proteomics - Clinical Applications |
Vol/bind | 4 |
Udgave nummer | 8-9 |
Sider (fra-til) | 697-705 |
Antal sider | 9 |
ISSN | 1862-8346 |
DOI | |
Status | Udgivet - sep. 2010 |
Udgivet eksternt | Ja |