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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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 Urheber:
Geyer, Philipp E.1, Autor           
Voytik, Eugenia1, Autor           
Treit, Peter V.1, Autor           
Doll, Sophia1, Autor           
Kleinhempel, Alisa, Autor
Niu, Lili, Autor
Müller, Johannes B.1, Autor           
Buchholtz, Marie-Luise, Autor
Bader, Jakob Maximilian1, Autor           
Teupser, Daniel, Autor
Holdt, Lesca M., Autor
Mann, Matthias1, Autor           
Affiliations:
1Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565159              

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Schlagwörter: MASS-SPECTROMETRY; QUANTIFICATION; DISCOVERY; PROTEINS; PROJECT; SERUMbiomarker discovery; mass spectrometry; plasma proteomics; sample quality; study design;
 Zusammenfassung: 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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Sprache(n): eng - English
 Datum: 2019
 Publikationsstatus: Online veröffentlicht
 Seiten: 12
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: ISI: 000496486100010
DOI: 10.15252/emmm.201910427
 Art des Abschluß: -

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Titel: Embo Molecular Medicine
  Kurztitel : Embo Mol. Med.
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Chichester : Wiley-Blackwell
Seiten: - Band / Heft: 11 (11) Artikelnummer: e10427 Start- / Endseite: - Identifikator: ISSN: 1757-4676
CoNE: https://pure.mpg.de/cone/journals/resource/1757-4676