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

Geyer, P. E., Voytik, E., Treit, P. V., Doll, S., Kleinhempel, A., Niu, L., et al. (2019). Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies. EMBO MOLECULAR MEDICINE, 11(11): e10427. doi:10.15252/emmm.201910427.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-51DA-A Version Permalink: http://hdl.handle.net/21.11116/0000-0005-51DB-9
Genre: Journal Article

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 Creators:
Geyer, Philipp E.1, Author              
Voytik, Eugenia1, Author              
Treit, Peter V.1, Author              
Doll, Sophia1, Author              
Kleinhempel, Alisa2, Author
Niu, Lili2, Author
Müller, Johannes B.1, Author              
Buchholtz, Marie-Luise2, Author
Bader, Jakob M.1, Author              
Teupser, Daniel2, Author
Holdt, Lesca M.2, Author
Mann, Matthias1, Author              
Affiliations:
1Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565159              
2external, ou_persistent22              

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Free keywords: MASS-SPECTROMETRY; QUANTIFICATION; DISCOVERY; PROTEINS; PROJECT; SERUMbiomarker discovery; mass spectrometry; plasma proteomics; sample quality; study design;
 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 ( ) to assess overall sample-related bias in clinical studies and to prevent costly miss-assignment of biomarker candidates.

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Language(s): eng - English
 Dates: 2019
 Publication Status: Published online
 Pages: 12
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: ISI: 000496486100010
DOI: 10.15252/emmm.201910427
 Degree: -

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Title: EMBO MOLECULAR MEDICINE
Source Genre: Journal
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Publ. Info: 111 RIVER ST, HOBOKEN 07030-5774, NJ USA : WILEY
Pages: - Volume / Issue: 11 (11) Sequence Number: e10427 Start / End Page: - Identifier: ISSN: 1757-4676