Evidence map›Paper›PMID 28951502›Full record

ReviewMolecular systems biology2017

Revisiting biomarker discovery by plasma proteomics.

Philipp E Geyer, Lesca M Holdt, Daniel Teupser, Matthias Mann

Abstract readReview
In one paragraph

Review in Molecular systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 469 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
469citing papers in PubMed, 3 pooled it
–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

469 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  16. Epigenetic aging in Alzheimer's disease: Relation to proteome.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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409 more citing papers are in PubMed but not listed here.

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

4 authors.

Philipp E GeyerDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
Lesca M HoldtInstitute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany.
Daniel TeupserInstitute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany.
Matthias MannDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany mmann@biochem.mpg.de.ORCID 0000-0003-1292-4799

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical analysis of blood is the most widespread diagnostic procedure in medicine, and blood biomarkers are used to categorize patients and to support treatment decisions. However, existing biomarkers are far from comprehensive and often lack specificity and new ones are being developed at a very slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker candidates in small cohorts, followed by classical immunoassays in much larger validation cohorts. We propose a "rectangular" plasma proteome profiling strategy, in which the proteome patterns of large cohorts are correlated with their phenotypes in health and disease. Translating such concepts into clinical practice will require restructuring several aspects of diagnostic decision-making, and we discuss some first steps in this direction.

Indexed as

BiomarkersBlood ProteinsHumansMass SpectrometryPhenotypeProteomeProteomicsBiomarkersBlood ProteinsProteomebiomarkersdiagnosticmass spectrometryplasma proteomicssystems medicine

Identifiers

PMID28951502
PMCPMC5615924

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Registered trials

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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 OpenQuestion graph.