Nonlinear DNA methylation trajectories in aging male mice

Maja Olecka, Alena Bömmel, Lena Best, Madlen Haase, Silke Foerste, Konstantin Riege, Thomas Dost, Stefano Flor, Otto W. Witte, Sören Franzenburg, Marco Groth, Björn Eyss, Christoph Kaleta, Christiane Frahm and Steve Hoffmann ()
Additional contact information
Maja Olecka: Leibniz Institute on Aging - Fritz Lipmann Institute (FLI)
Alena Bömmel: Leibniz Institute on Aging - Fritz Lipmann Institute (FLI)
Lena Best: University of Kiel and University Medical Center Schleswig-Holstein
Madlen Haase: Jena University Hospital
Silke Foerste: Leibniz Institute on Aging - Fritz Lipmann Institute (FLI)
Konstantin Riege: Leibniz Institute on Aging - Fritz Lipmann Institute (FLI)
Thomas Dost: University of Kiel and University Medical Center Schleswig-Holstein
Stefano Flor: University of Kiel and University Medical Center Schleswig-Holstein
Otto W. Witte: Jena University Hospital
Sören Franzenburg: Kiel University and University Medical Center Schleswig-Holstein
Marco Groth: Leibniz Institute on Aging - Fritz Lipmann Institute (FLI)
Björn Eyss: Leibniz Institute on Aging - Fritz Lipmann Institute (FLI)
Christoph Kaleta: University of Kiel and University Medical Center Schleswig-Holstein
Christiane Frahm: Jena University Hospital
Steve Hoffmann: Leibniz Institute on Aging - Fritz Lipmann Institute (FLI)

Nature Communications, 2024, vol. 15, issue 1, 1-15

Abstract: Abstract Although DNA methylation data yields highly accurate age predictors, little is known about the dynamics of this quintessential epigenomic biomarker during lifespan. To narrow the gap, we investigate the methylation trajectories of male mouse colon at five different time points of aging. Our study indicates the existence of sudden hypermethylation events at specific stages of life. Precisely, we identify two epigenomic switches during early-to-midlife (3-9 months) and mid-to-late-life (15-24 months) transitions, separating the rodents’ life into three stages. These nonlinear methylation dynamics predominantly affect genes associated with the nervous system and enrich in bivalently marked chromatin regions. Based on groups of nonlinearly modified loci, we construct a clock-like classifier STageR (STage of aging estimatoR) that accurately predicts murine epigenetic stage. We demonstrate the universality of our clock in an independent mouse cohort and with publicly available datasets.

Date: 2024
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DOI: 10.1038/s41467-024-47316-2

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