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

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Standard

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.

In: EMBO Molecular Medicine, Vol. 11, No. 11, e10427, 2019.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Geyer, PE, Voytik, E, Treit, PV, Doll, S, Kleinhempel, A, Niu, L, Müller, JB, Buchholtz, M-L, Bader, JM, Teupser, D, Holdt, LM & Mann, M 2019, 'Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies', EMBO Molecular Medicine, vol. 11, no. 11, e10427. https://doi.org/10.15252/emmm.201910427

APA

Geyer, P. E., Voytik, E., Treit, P. V., Doll, S., Kleinhempel, A., Niu, L., Müller, J. B., Buchholtz, M-L., Bader, J. M., Teupser, D., Holdt, L. M., & Mann, M. (2019). Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies. EMBO Molecular Medicine, 11(11), [e10427]. https://doi.org/10.15252/emmm.201910427

Vancouver

Geyer PE, Voytik E, Treit PV, Doll S, Kleinhempel A, Niu L et al. Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies. EMBO Molecular Medicine. 2019;11(11). e10427. https://doi.org/10.15252/emmm.201910427

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. / Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies. In: EMBO Molecular Medicine. 2019 ; Vol. 11, No. 11.

Bibtex

@article{60b2bc8ba38842febb33ae9817188e92,
title = "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 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.",
author = "Geyer, {Philipp E.} and Eugenia Voytik and Treit, {Peter V.} and Sophia Doll and Alisa Kleinhempel and Lili Niu and M{\"u}ller, {Johannes B} and Marie-Luise Buchholtz and Bader, {Jakob M} and Daniel Teupser and Holdt, {Lesca M} and Matthias Mann",
year = "2019",
doi = "10.15252/emmm.201910427",
language = "English",
volume = "11",
journal = "EMBO Molecular Medicine",
issn = "1757-4676",
publisher = "Wiley-Blackwell",
number = "11",

}

RIS

TY - JOUR

T1 - Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies

AU - Geyer, Philipp E.

AU - Voytik, Eugenia

AU - Treit, Peter V.

AU - Doll, Sophia

AU - Kleinhempel, Alisa

AU - Niu, Lili

AU - Müller, Johannes B

AU - Buchholtz, Marie-Luise

AU - Bader, Jakob M

AU - Teupser, Daniel

AU - Holdt, Lesca M

AU - Mann, Matthias

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

U2 - 10.15252/emmm.201910427

DO - 10.15252/emmm.201910427

M3 - Journal article

C2 - 31566909

VL - 11

JO - EMBO Molecular Medicine

JF - EMBO Molecular Medicine

SN - 1757-4676

IS - 11

M1 - e10427

ER -

ID: 228085072