Evidence map›Paper›PMID 28938075›Full record

ArticleJournal of proteome research2017

The Human Plasma Proteome Draft of 2017: Building on the Human Plasma PeptideAtlas from Mass Spectrometry and Complementary Assays.

Jochen M Schwenk, Gilbert S Omenn, Zhi Sun, David S Campbell, Mark S Baker, Christopher M Overall, Ruedi Aebersold, Robert L Moritz, Eric W Deutsch

Open access · greenAbstract readHistorical Article
In one paragraph

Article in Journal of proteome research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 128 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
128citing papers in PubMed, 2 pooled it
12.9field-weighted citation impact, top 1% of its field
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

128 citing papers in PubMed, 2 syntheses or guidelines pooled it, 238 citations in OpenAlex.

  1. Pooled it
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  18. The plasma proteome and breast cancer risk.Breast cancer research : BCR · 2025
    Article
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68 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

9 authors at 6 institutions in 5 countries.

Jochen M SchwenkAffinity Proteomics, SciLifeLab, School of Biotechnology, KTH Royal Institute of Technology , Tomtebodavägen 23, SE-171 65 Solna, Sweden.
Gilbert S OmennDepartments of Computational Medicine & Bioinformatics, Internal Medicine, and Human Genetics and School of Public Health, University of Michigan , Ann Arbor, Michigan 48109-2218, United States.ORCID 0000-0002-8976-6074
Zhi SunInstitute for Systems Biology , Seattle, Washington 98109, United States.
David S CampbellInstitute for Systems Biology , Seattle, Washington 98109, United States.
Mark S BakerDepartment of Biomedical Sciences, Faculty of Medicine and Health Science, Macquarie University , Sydney, New South Wales 2109, Australia.ORCID 0000-0001-5858-4035
Christopher M OverallCentre for Blood Research, Departments of Oral Biological & Medical Sciences, and Biochemistry & Molecular Biology, Faculty of Dentistry, University of British Columbia , Vancouver, Canada.
Ruedi AebersoldDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich , Zurich, Switzerland.
Robert L MoritzInstitute for Systems Biology , Seattle, Washington 98109, United States.ORCID 0000-0002-3216-9447
Eric W DeutschInstitute for Systems Biology , Seattle, Washington 98109, United States.ORCID 0000-0001-8732-0928
Institute for Systems Biology · USMacquarie University · AUScience for Life Laboratory · SEUniversity of British Columbia · CAUniversity of Michigan · USUniversity of Zurich · CH

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DUDLEY, AIMEE M · 2006 to 2016
$30.6M
Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
TrainingU54EB020406 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOGA, ARTHUR W · 2014 to 2018
$12.5M
Shortening the development cycle time of Trans Proteomic Pipeline tools with high performance computingR01GM087221 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC, MORITZ, ROBERT L · 2010 to 2021
$6.0M
University of Michigan Proteogenomics Data Analysis CenterU24CA210967 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHINNAIYAN, ARUL M, DHANASEKARAN, SARAVANA M · 2016 to 2020
$4.1M
Advancing data and metadata standards for proteomics mass spectraR24GM127667 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DEUTSCH, ERIC · 2017 to 2019
$1.2M
NCI NIH HHS U24 CA210967NIBIB NIH HHS U54 EB020406NIEHS NIH HHS P30 ES017885NIGMS NIH HHS P50 GM076547NIGMS NIH HHS R01 GM087221NIGMS NIH HHS R24 GM127667
6 · The paper itself

Abstract

Human blood plasma provides a highly accessible window to the proteome of any individual in health and disease. Since its inception in 2002, the Human Proteome Organization's Human Plasma Proteome Project (HPPP) has been promoting advances in the study and understanding of the full protein complement of human plasma and on determining the abundance and modifications of its components. In 2017, we review the history of the HPPP and the advances of human plasma proteomics in general, including several recent achievements. We then present the latest 2017-04 build of Human Plasma PeptideAtlas, which yields ∼43 million peptide-spectrum matches and 122,730 distinct peptide sequences from 178 individual experiments at a 1% protein-level FDR globally across all experiments. Applying the latest Human Proteome Project Data Interpretation Guidelines, we catalog 3509 proteins that have at least two non-nested uniquely mapping peptides of nine amino acids or more and >1300 additional proteins with ambiguous evidence. We apply the same two-peptide guideline to historical PeptideAtlas builds going back to 2006 and examine the progress made in the past ten years in plasma proteome coverage. We also compare the distribution of proteins in historical PeptideAtlas builds in various RNA abundance and cellular localization categories. We then discuss advances in plasma proteomics based on targeted mass spectrometry as well as affinity assays, which during early 2017 target ∼2000 proteins. Finally, we describe considerations about sample handling and study design, concluding with an outlook for future advances in deciphering the human plasma proteome.

Indexed as

Blood ProteinsDatabases, ProteinHistory, 21st CenturyHumansMass SpectrometryPlasmaProteomeProteomicsBlood ProteinsProteomeHuman Proteome Projectmass spectrometryplasmaproteomics

Identifiers

PMID28938075
PMCPMC5864247
OpenAlexW2759592955

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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 OpenQuestion graph.