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.
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