Evidence map›Paper›PMID 42068309›Full record

ArticleJournal of proteome research2026

Benchmarking Plasma Proteomics Workflows and Their Correlation to Clinical Routine Protein Assays.

Anders Handrup Kverneland, Ole Østergaard, Luisa Schmidt, Mia Østergaard Johansen, Steffen Ullitz Thorsen, Ruth Frikke Schmidt, Christina Christoffersen, Jesper Velgaard Olsen

Abstract read
In one paragraph

Article in Journal of proteome research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Anders Handrup KvernelandNovo Nordisk Foundation Center for Protein Research, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.ORCID 0000-0002-9883-936X
Ole ØstergaardNovo Nordisk Foundation Center for Protein Research, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.ORCID 0000-0003-3160-8548
Luisa SchmidtNovo Nordisk Foundation Center for Protein Research, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.
Mia Østergaard JohansenDepartment of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, 2100 Copenhagen, Denmark.
Steffen Ullitz ThorsenDepartment of Clinical Immunology, Copenhagen University Hospital-Rigshospitalet, 2100 Copenhagen, Denmark.
Ruth Frikke SchmidtDepartment of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, 2100 Copenhagen, Denmark.
Christina ChristoffersenDepartment of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, 2100 Copenhagen, Denmark.
Jesper Velgaard OlsenNovo Nordisk Foundation Center for Protein Research, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.ORCID 0000-0002-4747-4938

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plasma proteomics based on mass spectrometry has great potential for biomarker discovery. Plasma is challenging for mass spectrometry due to the high dynamic range in protein abundance. Several workflows have been developed to overcome this, and in this study, we compare prominent enrichment and depletion workflows using platelet-poor plasma (PPP), platelet-rich plasma (PRP), and serum (SER). Our results show that depletion workflows including Top14 depletion and acid precipitation allow quantification of very different proteomes than methods based on enrichments of extracellular vesicles such as bead-based enrichment or ultracentrifugation. Enrichment methods are superior in terms of proteome depth and quantitative performance but may be less robust in large cohorts. There is a very high correlation between PPP and PRP samples for all methods and less to SER samples, especially with enrichment workflows. The correlation of 10 protein measurements, performed by clinical routine processes on a Cobas system, showed heterogeneous results. Low-abundant proteins with biological dynamics within a healthy cohort, including C-reactive protein and lipoprotein(a), correlated very well to proteomics-based workflows, while others, including albumin and transferrin, correlated poorly. In conclusion, the workflow for plasma proteomics should be aligned with the aim of the analysis and setup of the sample collection.

Indexed as

Blood ProteinsProteomeProteomicsBenchmarkingBiomarkersHumansMass SpectrometryPlatelet-Rich PlasmaWorkflowBiomarkersBlood ProteinsProteomebiomarker discoveryclinical proteomicsCobasextracellular vesiclesOrbitrap Astralplasma proteomicsplatelet-poor plasmaplatelet-rich plasmaworkflow assessment

Identifiers

PMID42068309
PMCPMC13248009

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.