A rat epigenetic clock recapitulates phenotypic aging and co-localizes with heterochromatin

Author:

Levine Morgan12ORCID,McDevitt Ross A3ORCID,Meer Margarita1ORCID,Perdue Kathy3,Di Francesco Andrea45ORCID,Meade Theresa3,Farrell Colin6ORCID,Thrush Kyra2,Wang Meng2,Dunn Christopher7ORCID,Pellegrini Matteo8ORCID,de Cabo Rafael4ORCID,Ferrucci Luigi4ORCID

Affiliation:

1. Department of Pathology, Yale University School of Medicine, New Haven, United States

2. Program in Computational Biology and Bioinformatics, Yale University, New Haven, United States

3. Comparative Medicine Section, Biomedical Research Center, National Institute on Aging, National Institutes of Health, Baltimore, United States

4. Translational Gerontology Branch, Biomedical Research Center, National Institute on Aging, National Institutes of Health, Baltimore, United States

5. Calico Life Sciences, South San Francisco, United States

6. Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States

7. Laboratory of Molecular Biology and Immunology, Flow Core Unit, Biomedical Research Center, National Institute on Aging, National Institutes of Health, Baltimore, United States

8. Molecular Biology Institute and Departments of Energy Laboratory of Structural Biology and Molecular Medicine, and Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, United States

Abstract

Robust biomarkers of aging have been developed from DNA methylation in humans and more recently, in mice. This study aimed to generate a novel epigenetic clock in rats—a model with unique physical, physiological, and biochemical advantages—by incorporating behavioral data, unsupervised machine learning, and network analysis to identify epigenetic signals that not only track with age, but also relates to phenotypic aging. Reduced representation bisulfite sequencing (RRBS) data was used to train an epigenetic age (DNAmAge) measure in Fischer 344 CDF (F344) rats. This measure correlated with age at (r = 0.93) in an independent sample, and related to physical functioning (p=5.9e-3), after adjusting for age and cell counts. DNAmAge was also found to correlate with age in male C57BL/6 mice (r = 0.79), and was decreased in response to caloric restriction. Our signatures driven by CpGs in intergenic regions that showed substantial overlap with H3K9me3, H3K27me3, and E2F1 transcriptional factor binding.

Funder

National Institute on Aging

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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