Open AccessTowards reproducible MRM based biomarker discovery using dried blood spots
Author(s) -
Süreyya Özcan,
Jason D. Cooper,
Santiago G. Lago,
Diarmuid T. Kenny,
Nitin Rustogi,
Paweł Stocki,
Sabine Bahn
Publication year - 2017
Publication title -
scientific reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 213
ISSN - 2045-2322
DOI - 10.1038/srep45178
Subject(s) - biomarker discovery , dried blood , proteomics , dried blood spot , reproducibility , biomarker , computational biology , quantitative proteomics , false discovery rate , sample size determination , computer science , bioinformatics , chromatography , chemistry , biology , statistics , mathematics , biochemistry , gene
There is an increasing interest in the use of dried blood spot (DBS) sampling and multiple reaction monitoring in proteomics. Although several groups have explored the utility of DBS by focusing on protein detection, the reproducibility of the approach and whether it can be used for biomarker discovery in high throughput studies is yet to be determined. We assessed the reproducibility of multiplexed targeted protein measurements in DBS compared to serum. Eighty-two medium to high abundance proteins were monitored in a number of technical and biological replicates. Importantly, as part of the data analysis, several statistical quality control approaches were evaluated to detect inaccurate transitions. After implementing statistical quality control measures, the median CV on the original scale for all detected peptides in DBS was 13.2% and in Serum 8.8%. We also found a strong correlation ( r = 0.72) between relative peptide abundance measured in DBS and serum. The combination of minimally invasive sample collection with a highly specific and sensitive mass spectrometry (MS) technique allows for targeted quantification of multiple proteins in a single MS run. This approach has the potential to fundamentally change clinical proteomics and personalized medicine by facilitating large-scale studies.