» Articles » PMID: 25652787

Quantitative Variability of 342 Plasma Proteins in a Human Twin Population

Overview
Journal Mol Syst Biol
Specialty Molecular Biology
Date 2015 Feb 6
PMID 25652787
Citations 154
Authors
Affiliations
Soon will be listed here.
Abstract

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2-7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis-SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood-based biomarker studies.

Citing Articles

Changes in rat plasma proteomes during the first week after birth.

Wei L, Guo Z, Wei J, Zhou Y, Sun W, Han C Front Vet Sci. 2025; 12:1440716.

PMID: 40070918 PMC: 11894578. DOI: 10.3389/fvets.2025.1440716.


Plasma proteome variation and its genetic determinants in children and adolescents.

Niu L, Stinson S, Holm L, Lund M, Fonvig C, Cobuccio L Nat Genet. 2025; 57(3):635-646.

PMID: 39972214 PMC: 11906355. DOI: 10.1038/s41588-025-02089-2.


Mass spectrometry-based mapping of plasma protein QTLs in children and adolescents.

Liu Y Nat Genet. 2025; 57(3):487-488.

PMID: 39972213 DOI: 10.1038/s41588-025-02088-3.


Immunoaffinity Depletion of High-Abundance Proteins from Serum/Plasma for Proteomic Analysis.

Lee P, Osman J, Low T Methods Mol Biol. 2024; 2884:1-12.

PMID: 39715993 DOI: 10.1007/978-1-0716-4298-6_1.


Absolute Quantitative Targeted Monitoring of Potential Plasma Protein Biomarkers: A Pilot Study on Healthy Individuals.

Kononikhin A, Starodubtseva N, Brzhozovskiy A, Tokareva A, Kashirina D, Zakharova N Biomedicines. 2024; 12(10).

PMID: 39457715 PMC: 11504031. DOI: 10.3390/biomedicines12102403.


References
1.
Aebersold R, Anderson L, Caprioli R, Druker B, Hartwell L, Smith R . Perspective: a program to improve protein biomarker discovery for cancer. J Proteome Res. 2005; 4(4):1104-9. DOI: 10.1021/pr050027n. View

2.
Andrew T, Hart D, Snieder H, de Lange M, Spector T, MacGregor A . Are twins and singletons comparable? A study of disease-related and lifestyle characteristics in adult women. Twin Res. 2002; 4(6):464-77. DOI: 10.1375/1369052012803. View

3.
Rosenberger G, Koh C, Guo T, Rost H, Kouvonen P, Collins B . A repository of assays to quantify 10,000 human proteins by SWATH-MS. Sci Data. 2015; 1:140031. PMC: 4322573. DOI: 10.1038/sdata.2014.31. View

4.
Rost H, Rosenberger G, Navarro P, Gillet L, Miladinovic S, Schubert O . OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data. Nat Biotechnol. 2014; 32(3):219-23. DOI: 10.1038/nbt.2841. View

5.
Keller A, Nesvizhskii A, Kolker E, Aebersold R . Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem. 2002; 74(20):5383-92. DOI: 10.1021/ac025747h. View