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Aging (Albany NY). 2018 Apr 18;10(4):573-591. doi: 10.18632/aging.101414.

An epigenetic biomarker of aging for lifespan and healthspan.

Author information

1
Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA.
2
Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, USA, Baltimore, MD 21224, USA.
3
Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
4
Geriatric Unit, Azienda Toscana Centro, Florence, Italy.
5
Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
6
Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY 10032, USA.
7
Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA.
8
Department of Genetics, Department of Biostatistics, Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA.
9
Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA.
10
Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA.
11
Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
12
Center of Human Development and Aging, New Jersey Medical School, Rutgers State University of New Jersey, Newark, NJ 07103, USA.
13
Department of Epidemiology & Prevention, Division of Public Health Sciences, Wake Forrest School of Medicine, Winston-Salem, NC 27157, USA.
14
Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA.

Abstract

Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation of epigenetic biomarkers of aging were developed using chronological age as a surrogate for biological age, we hypothesized that incorporation of composite clinical measures of phenotypic age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the development of a more powerful epigenetic biomarker of aging. Using an innovative two-step process, we develop a new epigenetic biomarker of aging, DNAm PhenoAge, that strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease. While this biomarker was developed using data from whole blood, it correlates strongly with age in every tissue and cell tested. Based on an in-depth transcriptional analysis in sorted cells, we find that increased epigenetic, relative to chronological age, is associated with increased activation of pro-inflammatory and interferon pathways, and decreased activation of transcriptional/translational machinery, DNA damage response, and mitochondrial signatures. Overall, this single epigenetic biomarker of aging is able to capture risks for an array of diverse outcomes across multiple tissues and cells, and provide insight into important pathways in aging.

KEYWORDS:

epigenetic clock; DNA methylation; biomarker; healthspan

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