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Plasma proteomic biomarker signature of age predicts health and life span

Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (5...

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Autores principales: Tanaka, Toshiko, Basisty, Nathan, Fantoni, Giovanna, Candia, Julián, Moore, Ann Z, Biancotto, Angelique, Schilling, Birgit, Bandinelli, Stefania, Ferrucci, Luigi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7723412/
https://www.ncbi.nlm.nih.gov/pubmed/33210602
http://dx.doi.org/10.7554/eLife.61073
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author Tanaka, Toshiko
Basisty, Nathan
Fantoni, Giovanna
Candia, Julián
Moore, Ann Z
Biancotto, Angelique
Schilling, Birgit
Bandinelli, Stefania
Ferrucci, Luigi
author_facet Tanaka, Toshiko
Basisty, Nathan
Fantoni, Giovanna
Candia, Julián
Moore, Ann Z
Biancotto, Angelique
Schilling, Birgit
Bandinelli, Stefania
Ferrucci, Luigi
author_sort Tanaka, Toshiko
collection PubMed
description Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis-epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions.
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spelling pubmed-77234122020-12-09 Plasma proteomic biomarker signature of age predicts health and life span Tanaka, Toshiko Basisty, Nathan Fantoni, Giovanna Candia, Julián Moore, Ann Z Biancotto, Angelique Schilling, Birgit Bandinelli, Stefania Ferrucci, Luigi eLife Computational and Systems Biology Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis-epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions. eLife Sciences Publications, Ltd 2020-11-19 /pmc/articles/PMC7723412/ /pubmed/33210602 http://dx.doi.org/10.7554/eLife.61073 Text en http://creativecommons.org/publicdomain/zero/1.0/ http://creativecommons.org/publicdomain/zero/1.0/This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication (http://creativecommons.org/publicdomain/zero/1.0/) .
spellingShingle Computational and Systems Biology
Tanaka, Toshiko
Basisty, Nathan
Fantoni, Giovanna
Candia, Julián
Moore, Ann Z
Biancotto, Angelique
Schilling, Birgit
Bandinelli, Stefania
Ferrucci, Luigi
Plasma proteomic biomarker signature of age predicts health and life span
title Plasma proteomic biomarker signature of age predicts health and life span
title_full Plasma proteomic biomarker signature of age predicts health and life span
title_fullStr Plasma proteomic biomarker signature of age predicts health and life span
title_full_unstemmed Plasma proteomic biomarker signature of age predicts health and life span
title_short Plasma proteomic biomarker signature of age predicts health and life span
title_sort plasma proteomic biomarker signature of age predicts health and life span
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7723412/
https://www.ncbi.nlm.nih.gov/pubmed/33210602
http://dx.doi.org/10.7554/eLife.61073
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