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Geroscience. 2019 Nov 9. doi: 10.1007/s11357-019-00123-w. [Epub ahead of print]

The plasma metabolome as a predictor of biological aging in humans.

Author information

1
Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, 80309, USA.
2
Department of Mathematics, University of Colorado Boulder, Boulder, CO, 80309, USA.
3
Department of Biochemistry and Molecular Genetics, Anschutz Medical Campus, University of Colorado Denver, Aurora, CO, 80045, USA.
4
Department of Food Science and Human Nutrition, College of Health and Human Sciences, Colorado State University, Fort Collins, CO, 80523, USA.
5
Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, 80309, USA. cmartens@udel.edu.
6
Department of Kinesiology and Applied Physiology, University of Delaware, 540 South College Ave, Newark, DE, 19716, USA. cmartens@udel.edu.

Abstract

Chronological age is an important predictor of morbidity and mortality; however, it is unable to account for heterogeneity in the decline of physiological function and health with advancing age. Several attempts have been made to instead define a "biological age" using multiple physiological parameters in order to account for variation in the trajectory of human aging; however, these methods require technical expertise and are likely too time-intensive and costly to be implemented into clinical practice. Accordingly, we sought to develop a metabolomic signature of biological aging that could predict changes in physiological function with the convenience of a blood sample. A weighted model of biological age was generated based on multiple clinical and physiological measures in a cohort of healthy adults and was then applied to a group of healthy older adults who were tracked longitudinally over a 5-10-year timeframe. Plasma metabolomic signatures were identified that were associated with biological age, including some that could predict whether individuals would age at a faster or slower rate. Metabolites most associated with the rate of biological aging included amino acid, fatty acid, acylcarnitine, sphingolipid, and nucleotide metabolites. These results not only have clinical implications by providing a simple blood-based assay of biological aging, but also provide insight into the molecular mechanisms underlying human healthspan.

KEYWORDS:

Biological aging, Metabolomics, Healthspan, Precision medicine

PMID:
31707594
DOI:
10.1007/s11357-019-00123-w

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