Multi-Omic Biological Age Estimation and Its Correlation With Wellness and Disease Phenotypes: A Longitudinal Study of 3,558 Individuals.


Journal

The journals of gerontology. Series A, Biological sciences and medical sciences
ISSN: 1758-535X
Titre abrégé: J Gerontol A Biol Sci Med Sci
Pays: United States
ID NLM: 9502837

Informations de publication

Date de publication:
13 11 2019
Historique:
received: 15 02 2019
entrez: 15 11 2019
pubmed: 15 11 2019
medline: 10 7 2020
Statut: ppublish

Résumé

Biological age (BA), derived from molecular and physiological measurements, has been proposed to better predict mortality and disease than chronological age (CA). In the present study, a computed estimate of BA was investigated longitudinally in 3,558 individuals using deep phenotyping, which encompassed a broad range of biological processes. The Klemera-Doubal algorithm was applied to longitudinal data consisting of genetic, clinical laboratory, metabolomic, and proteomic assays from individuals undergoing a wellness program. BA was elevated relative to CA in the presence of chronic diseases. We observed a significantly lower rate of change than the expected ~1 year/year (to which the estimation algorithm was constrained) in BA for individuals participating in a wellness program. This observation suggests that BA is modifiable and suggests that a lower BA relative to CA may be a sign of healthy aging. Measures of metabolic health, inflammation, and toxin bioaccumulation were strong predictors of BA. BA estimation from deep phenotyping was seen to change in the direction expected for both positive and negative health conditions. We believe BA represents a general and interpretable "metric for wellness" that may aid in monitoring aging over time.

Identifiants

pubmed: 31724055
pii: 5625183
doi: 10.1093/gerona/glz220
pmc: PMC6853785
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

S52-S60

Subventions

Organisme : NIA NIH HHS
ID : U01 AG022303
Pays : United States
Organisme : NIA NIH HHS
ID : U19 AG023122
Pays : United States
Organisme : NIA NIH HHS
ID : UH2 AG064706
Pays : United States

Informations de copyright

© The Author(s) 2019. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Auteurs

John C Earls (JC)

Institute for Systems Biology, Seattle, Washington.
Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, Washington.

Noa Rappaport (N)

Institute for Systems Biology, Seattle, Washington.

Laura Heath (L)

Institute for Systems Biology, Seattle, Washington.

Tomasz Wilmanski (T)

Institute for Systems Biology, Seattle, Washington.

Andrew T Magis (AT)

Institute for Systems Biology, Seattle, Washington.

Nicholas J Schork (NJ)

Human Biology Program, J. Craig Venter Institute, Translational Genomics Research Institute, La Jolla, California, Ann Arbor.

Gilbert S Omenn (GS)

University of Michigan, Ann Arbor.

Jennifer Lovejoy (J)

Institute for Systems Biology, Seattle, Washington.

Leroy Hood (L)

Institute for Systems Biology, Seattle, Washington.
Providence St. Joseph Health, Seattle, Washington.

Nathan D Price (ND)

Institute for Systems Biology, Seattle, Washington.
Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, Washington.

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