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Journal of Proteome Research
Article . 2019 . Peer-reviewed
License: STM Policy #29
Data sources: Crossref
https://doi.org/10.1101/716563...
Article . 2019 . Peer-reviewed
Data sources: Crossref
MPG.PuRe
Article . 2019
Data sources: MPG.PuRe
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Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

Authors: Ignjatovic, Vera; Geyer, Philipp Emanuel; Palaniappan, Krishnan; Chaaban, Jessican E; Omenn, Gilbert S; Baker, Mark; Deutsch, Eric; +1 Authors

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

Abstract

Abstract The proteomic analyses of human blood and blood-derived products (e.g. plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g. inter-individual variability), analysis of biospecimen (e.g. sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest whilst enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice. Abstract Figure

Country
Denmark
Keywords

Proteomics, Quality Control, Blood Specimen Collection, data acquisition, Computational Biology, Blood Proteins, sample collection, plasma processing workflows, bioinformatic analysis, Mass Spectrometry, Workflow, Human Plasma Proteome Project (HPPP), quality metrics, study design, Human Proteome Project (HPP), blood, Humans, mass spectrometry (MS), serum, plasma, data processing

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    196
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
196
Top 1%
Top 10%
Top 1%
Green
bronze