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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
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