Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies

Abstract 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 quant...

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Main Authors: Philipp E Geyer, Eugenia Voytik, Peter V Treit, Sophia Doll, Alisa Kleinhempel, Lili Niu, Johannes B Müller, Marie‐Luise Buchholtz, Jakob M Bader, Daniel Teupser, Lesca M Holdt, Matthias Mann
Format: Article
Language:English
Published: Wiley 2019-11-01
Series:EMBO Molecular Medicine
Subjects:
Online Access:https://doi.org/10.15252/emmm.201910427
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spelling doaj-7408b776a53943d6a2e3eb353fa0f1c52021-08-02T19:07:44ZengWileyEMBO Molecular Medicine1757-46761757-46842019-11-011111n/an/a10.15252/emmm.201910427Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studiesPhilipp E Geyer0Eugenia Voytik1Peter V Treit2Sophia Doll3Alisa Kleinhempel4Lili Niu5Johannes B Müller6Marie‐Luise Buchholtz7Jakob M Bader8Daniel Teupser9Lesca M Holdt10Matthias Mann11Department of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried GermanyDepartment of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried GermanyDepartment of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried GermanyDepartment of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried GermanyInstitute of Laboratory Medicine University Hospital LMU Munich Munich GermanyNNF Center for Protein Research Faculty of Health Sciences University of Copenhagen Copenhagen DenmarkDepartment of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried GermanyInstitute of Laboratory Medicine University Hospital LMU Munich Munich GermanyDepartment of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried GermanyInstitute of Laboratory Medicine University Hospital LMU Munich Munich GermanyInstitute of Laboratory Medicine University Hospital LMU Munich Munich GermanyDepartment of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried GermanyAbstract 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.https://doi.org/10.15252/emmm.201910427biomarker discoverymass spectrometryplasma proteomicssample qualitystudy design
collection DOAJ
language English
format Article
sources DOAJ
author Philipp E Geyer
Eugenia Voytik
Peter V Treit
Sophia Doll
Alisa Kleinhempel
Lili Niu
Johannes B Müller
Marie‐Luise Buchholtz
Jakob M Bader
Daniel Teupser
Lesca M Holdt
Matthias Mann
spellingShingle Philipp E Geyer
Eugenia Voytik
Peter V Treit
Sophia Doll
Alisa Kleinhempel
Lili Niu
Johannes B Müller
Marie‐Luise Buchholtz
Jakob M Bader
Daniel Teupser
Lesca M Holdt
Matthias Mann
Plasma Proteome Profiling to detect and avoid sample‐related biases in biomarker studies
EMBO Molecular Medicine
biomarker discovery
mass spectrometry
plasma proteomics
sample quality
study design
author_facet Philipp E Geyer
Eugenia Voytik
Peter V Treit
Sophia Doll
Alisa Kleinhempel
Lili Niu
Johannes B Müller
Marie‐Luise Buchholtz
Jakob M Bader
Daniel Teupser
Lesca M Holdt
Matthias Mann
author_sort Philipp E Geyer
title 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_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_sort plasma proteome profiling to detect and avoid sample‐related biases in biomarker studies
publisher Wiley
series EMBO Molecular Medicine
issn 1757-4676
1757-4684
publishDate 2019-11-01
description Abstract 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.
topic biomarker discovery
mass spectrometry
plasma proteomics
sample quality
study design
url https://doi.org/10.15252/emmm.201910427
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