Quantitative variability of 342 plasma proteins in a human twin population.

Mol Syst Biol

Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland Faculty of Science, University of Zurich, Zurich, Switzerland

Published: February 2015

AI Article Synopsis

  • - The study investigates the unknown factors influencing the variability of human plasma proteins by analyzing data from twin studies, which helps separate genetic and environmental contributions to protein levels.
  • - Using SWATH mass spectrometry, researchers quantified a large number of peptides from plasma samples taken from twins over several years, revealing that different proteins vary greatly in their abundance and genetic influence.
  • - The findings highlight the importance of considering genetic and temporal factors when calibrating clinical biomarkers, and identify specific genetic variants (cis-SNPs) that affect the levels of certain proteins, which could improve future blood-based biomarker research.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4358658PMC
http://dx.doi.org/10.15252/msb.20145728DOI Listing

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