Finding diabetic nephropathy biomarkers in the plasma peptidome by high-throughput magnetic bead processing and MALDI-TOF-MS analysis

TY - JOUR

T1 - Finding diabetic nephropathy biomarkers in the plasma peptidome by high-throughput magnetic bead processing and MALDI-TOF-MS analysis

AU - Hansen, Henning G

AU - Overgaard, Julie

AU - Lajer, Maria

AU - Hubalek, Frantisek

AU - Højrup, Peter

AU - Pedersen, Lykke

AU - Tarnow, Lise

AU - Rossing, Peter

AU - Pociot, Flemming

AU - McGuire, James N

N1 - Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PY - 2010/9/1

Y1 - 2010/9/1

N2 - 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.

AB - 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.

U2 - 10.1002/prca.200900169

DO - 10.1002/prca.200900169

M3 - Journal article

C2 - 21137087

SN - 1862-8346

VL - 4

SP - 697

EP - 705

JO - Proteomics - Clinical Applications

JF - Proteomics - Clinical Applications

IS - 8-9

ER -