scEpiAge: an age predictor highlighting single-cell ageing heterogeneity in mouse blood

Ageing is the accumulation of changes and decline of function of organisms over time. The concept and biomarkers of biological age have been established, notably DNA methylation-based clocks. The emergence of single-cell DNA methylation profiling methods opens the possibility of studying the biological age of individual cells. Here, we generate a large single-cell DNA methylation and transcriptome dataset from mouse peripheral blood samples, spanning a broad range of ages. The number of genes expressed increases with age, but gene-specific changes are small. We next develop scEpiAge, a single-cell DNA methylation age predictor, which can accurately predict age in (very sparse) publicly available datasets, and also in single cells. DNA methylation age distribution is wider than technically expected, indicating epigenetic age heterogeneity and functional differences. Our work provides a foundation for single-cell and sparse data epigenetic age predictors, validates their functionality and highlights epigenetic heterogeneity during ageing.

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Publication Details

Journal
Nature Communications
Published
2024-08-31
DOI
https://doi.org/10.1038/s41467-024-51833-5
Citations
14
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
3.27

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article

scEpiAge: an age predictor highlighting single-cell ageing heterogeneity in mouse blood

Ferdinand von Meyenn, Marc Jan Bonder, Thomas M. Stubbs, Wolf Reik et al.
14 citations
Nature Communications
Epigenetics and DNA Methylation
3.27
article

scEpiAge: an age predictor highlighting single-cell ageing heterogeneity in mouse blood

Ferdinand von Meyenn, Marc Jan Bonder, Thomas M. Stubbs, Wolf Reik, Anne‐Katrien Stark, Felix Krueger, Aida M. Hashtroud, Siyuan Luo, Steffen Rulands, João Agostinho de Sousa, Oliver Stegle, Stephen J. Clark
article en
14 citations

Abstract

Ageing is the accumulation of changes and decline of function of organisms over time. The concept and biomarkers of biological age have been established, notably DNA methylation-based clocks. The emergence of single-cell DNA methylation profiling methods opens the possibility of studying the biological age of individual cells. Here, we generate a large single-cell DNA methylation and transcriptome dataset from mouse peripheral blood samples, spanning a broad range of ages. The number of genes expressed increases with age, but gene-specific changes are small. We next develop scEpiAge, a single-cell DNA methylation age predictor, which can accurately predict age in (very sparse) publicly available datasets, and also in single cells. DNA methylation age distribution is wider than technically expected, indicating epigenetic age heterogeneity and functional differences. Our work provides a foundation for single-cell and sparse data epigenetic age predictors, validates their functionality and highlights epigenetic heterogeneity during ageing.

Nature CommunicationsVol. 15(1)
New England Biolabs (United States) (US), Babraham Institute (GB), University Medical Center Groningen (NL), Omron (Japan) (JP), German Cancer Research Center (DE), King's College London (GB), Heidelberg University (DE), Center for NanoScience (DE), Wellcome Sanger Institute (GB), ETH Zurich (CH), Oncode Institute (NL), Max Planck Institute for the Physics of Complex Systems (DE), European Molecular Biology Laboratory (DE), Ludwig-Maximilians-Universität München (DE)
Wellcome Trust, European Commission, King's Health Partners, Eidgenössische Technische Hochschule Zürich, Biotechnology and Biological Sciences Research Council
Openalex Percentile: Top 7%
Epigenetics and DNA Methylation
3.27
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