Plasma proteomic biomarker signature of age predicts health and life span

  1. Toshiko Tanaka  Is a corresponding author
  2. Nathan Basisty
  3. Giovanna Fantoni
  4. Julian Candia
  5. Ann Z Moore
  6. Angelique Bioancotto
  7. Birgit Schilling
  8. Stefania Bandinelli
  9. Luigi Ferrucci
  1. National Institute on Aging, NIH, United States
  2. Buck Institute for Research on Aging, United States
  3. National Cancer Institute, NIH, United States
  4. Sanofi, United States
  5. Azienda Sanitaria di Firenze, Italy

Abstract

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) was identified. 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 premise of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk for disease to be targeted for in depth diagnostic procedures and early interventions.

Data availability

Phenotypic data and source codes used for this manuscript is provided. Due to the contents of the InCHIANTI study consent forms, proteomic and DNA methylation data cannot be made publicly available. Researchers can seek access to these data through the submission of proposals and subsequent approval through the InCHIANTI study website (inchiantistudy.net).

Article and author information

Author details

  1. Toshiko Tanaka

    Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, United States
    For correspondence
    tanakato@mail.nih.gov
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4161-3829
  2. Nathan Basisty

    Buck Institute for Research on Aging, Novato, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Giovanna Fantoni

    Clinical Research Core, National Institute on Aging, NIH, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Julian Candia

    Laboratory of Human Carcinogenesis, National Cancer Institute, NIH, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5793-8989
  5. Ann Z Moore

    Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Angelique Bioancotto

    Immunology & Inflammation Research Therapeutic Area, Sanofi, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Birgit Schilling

    Buck Institute for Research on Aging, Novato, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9907-2749
  8. Stefania Bandinelli

    Geriatric Unit, Azienda Sanitaria di Firenze, Florence, Italy
    Competing interests
    The authors declare that no competing interests exist.
  9. Luigi Ferrucci

    Intramural Research Program, National Institute on Aging, NIH, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6273-1613

Funding

National Institutes of Health (U01 AG060906)

  • Birgit Schilling

National Institutes of Health (K99 AG065484)

  • Nathan Basisty

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: The study protocol (exemption #11976) was approved by the Italian National Institute of Research and Care of Aging Institutional Review and Medstar Research Institute (Baltimore, MD) and approved by the Internal Review Board of the National Institute for Environmental Health Sciences (NIEHS).

Copyright

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.

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  1. Toshiko Tanaka
  2. Nathan Basisty
  3. Giovanna Fantoni
  4. Julian Candia
  5. Ann Z Moore
  6. Angelique Bioancotto
  7. Birgit Schilling
  8. Stefania Bandinelli
  9. Luigi Ferrucci
(2020)
Plasma proteomic biomarker signature of age predicts health and life span
eLife 9:e61073.
https://doi.org/10.7554/eLife.61073

Share this article

https://doi.org/10.7554/eLife.61073

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