Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021 Dec 3;20(12):5241-5263.
doi: 10.1021/acs.jproteome.1c00657. Epub 2021 Oct 21.

Advances and Utility of the Human Plasma Proteome

Eric W Deutsch  1 , Gilbert S Omenn  1   2 , Zhi Sun  1 , Michal Maes  1 , Maria Pernemalm  3 , Krishnan K Palaniappan  4 , Natasha Letunica  5 , Yves Vandenbrouck  6 , Virginie Brun  6 , Sheng-Ce Tao  7 , Xiaobo Yu  8 , Philipp E Geyer  9 , Vera Ignjatovic  5   10 , Robert L Moritz  1 , Jochen M Schwenk  11
Affiliations
Review

Advances and Utility of the Human Plasma Proteome

Eric W Deutsch et al. J Proteome Res. .

Abstract

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

Keywords: DNA aptamers (Somascan); Human Plasma Proteome Project; Human Proteome Project; PeptideAtlas; blood; mass spectrometry; plasma; proteomics; proximity extension assays (PEA by Olink).

PubMed Disclaimer

Conflict of interest statement

Conflict of interest

The authors declare the following competing financial interest(s): Krishnan K. Palaniappan is an employee of Freenome. Philipp E. Geyer is an employee of OmicEra Diagnostics GmbH. All other authors declare no competing financial interest.

Figures

Figure 1.
Figure 1.. Canonical proteins detected as a function of MS/MS spectra added to the Human Plasma PeptideAtlas build.
Each rectangle represents one experiment; the width of the rectangle is the number of identified PSMs in the experiment. The upper blue extent indicates the total number of canonical proteins assembled in the build. The lower red rectangles represent the total number of canonical proteins in each experiment. Most experiments contain only ~450 canonical proteins, but some experiments reach as high as ~2000 canonical proteins. An approximate timescale for when datasets were added to the build is overlaid in two-year extents since 2004. An interactive version of the figure, where individual experiments can be identified, is available at the PeptideAtlas build summary web page.
Figure 2.
Figure 2.. Number of canonical proteins as a function of MS/MS spectra added to the Human Blood Extracellular Vesicle PeptideAtlas build.
Each rectangle represents one experiment; the width of the rectangle is the number of identified PSMs in the experiment. The upper blue extent indicates the total number of canonical proteins assembled in the build. The lower red rectangles represent the total number of canonical proteins in each experiment.
Figure 3.
Figure 3.. Comparison of the Plasma and EV build protein abundances.
A) Comparison of log10 EV protein abundances vs log10 Plasma protein abundances for the 2047 proteins in common between the two builds. The abundance estimates are based on overall PSM counts and are arbitrarily scaled. A diagonal line of equivalent abundance is overlaid. B) A Venn-like diagram depicting the overlap (central 40%) of proteins in the Plasma (left) and EV (right) builds, stratified by log10 protein abundance estimates based on PSM counts on the y-axis. The plasma build has 10 times as many PSMs and therefore more proteins detectable at lower abundance.
Figure 4:
Figure 4:. Literature search of manuscripts investigating serum or plasma alterations in COVID-19.
(A) Studies ranked according to the analyzed number of samples. (B) Portion of manuscripts applying different technologies to investigate the proteome of COVID-19 patients. Of note, in some studies more than one technology has been applied.
Figure 5:
Figure 5:. Genome wide associations of circulating protein levels.
Simplified illustration to depict how genetic variation can influence protein levels. Projecting the results of regression analyses onto the genome can identify regions of genetic variation, so called protein Quantitative Trait Loci (pQTLs), that associate with protein levels. These regions can either localize with the proteins of interest (cis-pQTLs, red) or relate to other regions in the genome (trans-pQTLs, blue).
See this image and copyright information in PMC

References

    1. Ignjatovic V; Geyer PE; Palaniappan KK; Chaaban JE; Omenn GS; Baker MS; Deutsch EW; Schwenk JM Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data. J. Proteome Res 2019, 18 (12), 4085–4097. 10.1021/acs.jproteome.9b00503. - DOI - PMC - PubMed
    1. Loo JA; Yan W; Ramachandran P; Wong DT Comparative Human Salivary and Plasma Proteomes. J. Dent. Res 2010, 89 (10), 1016–1023. 10.1177/0022034510380414. - DOI - PMC - PubMed
    1. Hanash S; Celis JE The Human Proteome Organization: A Mission to Advance Proteome Knowledge. Mol. Cell. Proteomics MCP 2002, 1 (6), 413–414. - PubMed
    1. Omenn GS; States DJ; Adamski M; Blackwell TW; Menon R; Hermjakob H; Apweiler R; Haab BB; Simpson RJ; Eddes JS; Kapp EA; Moritz RL; Chan DW; Rai AJ; Admon A; Aebersold R; Eng J; Hancock WS; Hefta SA; Meyer H; Paik Y-K; Yoo J-S; Ping P; Pounds J; Adkins J; Qian X; Wang R; Wasinger V; Wu CY; Zhao X; Zeng R; Archakov A; Tsugita A; Beer I; Pandey A; Pisano M; Andrews P; Tammen H; Speicher DW; Hanash SM Overview of the HUPO Plasma Proteome Project: Results from the Pilot Phase with 35 Collaborating Laboratories and Multiple Analytical Groups, Generating a Core Dataset of 3020 Proteins and a Publicly-Available Database. Proteomics 2005, 5 (13), 3226–3245. 10.1002/pmic.200500358. - DOI - PubMed
    1. Legrain P; Aebersold R; Archakov A; Bairoch A; Bala K; Beretta L; Bergeron J; Borchers CH; Corthals GL; Costello CE; Deutsch EW; Domon B; Hancock W; He F; Hochstrasser D; Marko-Varga G; Salekdeh GH; Sechi S; Snyder M; Srivastava S; Uhlén M; Wu CH; Yamamoto T; Paik Y-K; Omenn GS The Human Proteome Project: Current State and Future Direction. Mol. Cell. Proteomics 2011, 10 (7), M111.009993. 10.1074/mcp.M111.009993. - DOI - PMC - PubMed

Publication types