Preprint · CC-BY
via OpenAlex
Age related disorder in DNA methylation patterns underlies epigenetic clock signals, but displays distinct responses to epigenetic rejuvenation events
Emily M. Bertucci, Ethan P. Shealy, Benjamin B. Parrott
bioRxiv (Cold Spring Harbor Laboratory) · 2022 · ▲ 1 citations
Abstract
Abstract Changes in DNA methylation with age are observed across the tree of life. The stereotypical nature of these changes can be modeled to produce epigenetic clocks capable of predicting biological age with unprecedented accuracy. Despite the predictive ability of epigenetic clocks, the underlying processes that produce clock signals are not resolved but are hypothesized to be rooted in stochastic processes leading to an erosion in the epigenetic landscape. Here, we test this hypothesis using a novel computational approach for measuring disorder in DNA methylation patterns across the epigenome. We find that loci comprising conventional epigenetic clocks are enriched in regions that both accumulate and lose disorder with age, suggesting a direct link between DNA methylation disorder and epigenetic clock(definition) signals. Across the murine lifespan, disorder accumulates in Polycomb Repressive Complex 2 target genes and decreases in CTCF and transcription factor binding sites, resulting in genomic hotspots of age-related epigenetic disorder. We further investigate the connections between age-related changes in disorder and epigenetic clock signals by comparing the influences of development, lifespan interventions, and cellular dedifferentiation using a series of newly developed epigenetic clocks based on regional disorder, average methylation states, and commonly used measures of entropy. We identify both common responses as well as critical differences between canonical epigenetic clocks and those based on regional disorder, demonstrating a fundamental decoupling of epigenetic aging processes. Collectively, this work identifies key linkages between epigenetic disorder and epigenetic clock signals, and simultaneously demonstrates the multifaceted nature of epigenetic aging in which stochastic processes occurring at non-random loci produce predictable outcomes.
◌ CITATION ONLY
Full text is not openly licensed for redistribution here. Read it at the source:
Provenance
- Source
- OpenAlex
- DOI
- 10.1101/2022.12.01.518745
- Canonical
- link ↗
- Fetched
- 2026-10-14 MST
Cite this
APA
Bertucci, E.M., Shealy, E.P., & Parrott, B.B. (2022). Age related disorder in DNA methylation patterns underlies epigenetic clock signals, but displays distinct responses to epigenetic rejuvenation events. <em>bioRxiv (Cold Spring Harbor Laboratory)</em>. https://doi.org/10.1101/2022.12.01.518745
Vancouver
Bertucci EM, Shealy EP, Parrott BB. Age related disorder in DNA methylation patterns underlies epigenetic clock signals, but displays distinct responses to epigenetic rejuvenation events. bioRxiv (Cold Spring Harbor Laboratory). 2022. doi:10.1101/2022.12.01.518745.
BibTeX
@unpublished{emily2022Agerel,
title = {Age related disorder in DNA methylation patterns underlies epigenetic clock signals, but displays distinct responses to epigenetic rejuvenation events},
author = {Emily M. Bertucci and Ethan P. Shealy and Benjamin B. Parrott},
journal = {bioRxiv (Cold Spring Harbor Laboratory)},
year = {2022},
doi = {10.1101/2022.12.01.518745},
}
Research neighborhood
References, citing works, and semantically nearest findings. Click a node to open it.
Related findings
Science Advances 2025
Open access · CC-BY
DNA methylation–based age prediction and sex-specific epigenetic aging in a lizard with female-biased longevity
bioRxiv (Cold Spring Harbor Laboratory) 2022
Preprint · OA
Development of a novel aging clock based on chromatin accessibility
Aging 2024
Open access · CC-BY
Cell-type specific epigenetic clocks to quantify biological age at cell-type resolution
Journal of Internal Medicine 2022
Citation only
Epigenetic aging: Biological age prediction and informing a mechanistic theory of aging
Cell Reports Methods 2023
Open access · CC-BY
Accurate age prediction from blood using a small set of DNA methylation sites and a cohort-based machine learning algorithm
Innovation in Aging 2019
Open access · CC-BY