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Quantitative variability of 342 plasma proteins in a human twin population
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 hi...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BlackWell Publishing Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4358658/ https://www.ncbi.nlm.nih.gov/pubmed/25652787 http://dx.doi.org/10.15252/msb.20145728 |
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author | Liu, Yansheng Buil, Alfonso Collins, Ben C Gillet, Ludovic CJ Blum, Lorenz C Cheng, Lin-Yang Vitek, Olga Mouritsen, Jeppe Lachance, Genevieve Spector, Tim D Dermitzakis, Emmanouil T Aebersold, Ruedi |
author_facet | Liu, Yansheng Buil, Alfonso Collins, Ben C Gillet, Ludovic CJ Blum, Lorenz C Cheng, Lin-Yang Vitek, Olga Mouritsen, Jeppe Lachance, Genevieve Spector, Tim D Dermitzakis, Emmanouil T Aebersold, Ruedi |
author_sort | Liu, Yansheng |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4358658 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BlackWell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-43586582015-03-20 Quantitative variability of 342 plasma proteins in a human twin population Liu, Yansheng Buil, Alfonso Collins, Ben C Gillet, Ludovic CJ Blum, Lorenz C Cheng, Lin-Yang Vitek, Olga Mouritsen, Jeppe Lachance, Genevieve Spector, Tim D Dermitzakis, Emmanouil T Aebersold, Ruedi Mol Syst Biol Articles 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. BlackWell Publishing Ltd 2015-02-04 /pmc/articles/PMC4358658/ /pubmed/25652787 http://dx.doi.org/10.15252/msb.20145728 Text en © 2015 The Authors. Published under the terms of the CC BY 4.0 license http://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Liu, Yansheng Buil, Alfonso Collins, Ben C Gillet, Ludovic CJ Blum, Lorenz C Cheng, Lin-Yang Vitek, Olga Mouritsen, Jeppe Lachance, Genevieve Spector, Tim D Dermitzakis, Emmanouil T Aebersold, Ruedi Quantitative variability of 342 plasma proteins in a human twin population |
title | Quantitative variability of 342 plasma proteins in a human twin population |
title_full | Quantitative variability of 342 plasma proteins in a human twin population |
title_fullStr | Quantitative variability of 342 plasma proteins in a human twin population |
title_full_unstemmed | Quantitative variability of 342 plasma proteins in a human twin population |
title_short | Quantitative variability of 342 plasma proteins in a human twin population |
title_sort | quantitative variability of 342 plasma proteins in a human twin population |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4358658/ https://www.ncbi.nlm.nih.gov/pubmed/25652787 http://dx.doi.org/10.15252/msb.20145728 |
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