Cargando…
Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies
Plasma and serum are rich sources of information regarding an individual's health state, and protein tests inform medical decision making. Despite major investments, few new biomarkers have reached the clinic. Mass spectrometry (MS)‐based proteomics now allows highly specific and quantitative r...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6835559/ https://www.ncbi.nlm.nih.gov/pubmed/31566909 http://dx.doi.org/10.15252/emmm.201910427 |
_version_ | 1783466700947062784 |
---|---|
author | Geyer, Philipp E Voytik, Eugenia Treit, Peter V Doll, Sophia Kleinhempel, Alisa Niu, Lili Müller, Johannes B Buchholtz, Marie‐Luise Bader, Jakob M Teupser, Daniel Holdt, Lesca M Mann, Matthias |
author_facet | Geyer, Philipp E Voytik, Eugenia Treit, Peter V Doll, Sophia Kleinhempel, Alisa Niu, Lili Müller, Johannes B Buchholtz, Marie‐Luise Bader, Jakob M Teupser, Daniel Holdt, Lesca M Mann, Matthias |
author_sort | Geyer, Philipp E |
collection | PubMed |
description | Plasma and serum are rich sources of information regarding an individual's health state, and protein tests inform medical decision making. Despite major investments, few new biomarkers have reached the clinic. Mass spectrometry (MS)‐based proteomics now allows highly specific and quantitative readout of the plasma proteome. Here, we employ Plasma Proteome Profiling to define quality marker panels to assess plasma samples and the likelihood that suggested biomarkers are instead artifacts related to sample handling and processing. We acquire deep reference proteomes of erythrocytes, platelets, plasma, and whole blood of 20 individuals (> 6,000 proteins), and compare serum and plasma proteomes. Based on spike‐in experiments, we determine sample quality‐associated proteins, many of which have been reported as biomarker candidates as revealed by a comprehensive literature survey. We provide sample preparation guidelines and an online resource ( www.plasmaproteomeprofiling.org) to assess overall sample‐related bias in clinical studies and to prevent costly miss‐assignment of biomarker candidates. |
format | Online Article Text |
id | pubmed-6835559 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68355592019-11-08 Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies Geyer, Philipp E Voytik, Eugenia Treit, Peter V Doll, Sophia Kleinhempel, Alisa Niu, Lili Müller, Johannes B Buchholtz, Marie‐Luise Bader, Jakob M Teupser, Daniel Holdt, Lesca M Mann, Matthias EMBO Mol Med Report Plasma and serum are rich sources of information regarding an individual's health state, and protein tests inform medical decision making. Despite major investments, few new biomarkers have reached the clinic. Mass spectrometry (MS)‐based proteomics now allows highly specific and quantitative readout of the plasma proteome. Here, we employ Plasma Proteome Profiling to define quality marker panels to assess plasma samples and the likelihood that suggested biomarkers are instead artifacts related to sample handling and processing. We acquire deep reference proteomes of erythrocytes, platelets, plasma, and whole blood of 20 individuals (> 6,000 proteins), and compare serum and plasma proteomes. Based on spike‐in experiments, we determine sample quality‐associated proteins, many of which have been reported as biomarker candidates as revealed by a comprehensive literature survey. We provide sample preparation guidelines and an online resource ( www.plasmaproteomeprofiling.org) to assess overall sample‐related bias in clinical studies and to prevent costly miss‐assignment of biomarker candidates. John Wiley and Sons Inc. 2019-09-30 2019-11-07 /pmc/articles/PMC6835559/ /pubmed/31566909 http://dx.doi.org/10.15252/emmm.201910427 Text en © 2019 The Authors. Published under the terms of the CC BY 4.0 license This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Report Geyer, Philipp E Voytik, Eugenia Treit, Peter V Doll, Sophia Kleinhempel, Alisa Niu, Lili Müller, Johannes B Buchholtz, Marie‐Luise Bader, Jakob M Teupser, Daniel Holdt, Lesca M Mann, Matthias Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies |
title | Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies |
title_full | Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies |
title_fullStr | Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies |
title_full_unstemmed | Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies |
title_short | Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies |
title_sort | plasma proteome profiling to detect and avoid sample‐related biases in biomarker studies |
topic | Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6835559/ https://www.ncbi.nlm.nih.gov/pubmed/31566909 http://dx.doi.org/10.15252/emmm.201910427 |
work_keys_str_mv | AT geyerphilippe plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT voytikeugenia plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT treitpeterv plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT dollsophia plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT kleinhempelalisa plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT niulili plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT mullerjohannesb plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT buchholtzmarieluise plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT baderjakobm plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT teupserdaniel plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT holdtlescam plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies AT mannmatthias plasmaproteomeprofilingtodetectandavoidsamplerelatedbiasesinbiomarkerstudies |