ArticleGeroScience2024
Application of a mathematical model to clarify the statistical characteristics of a pan-tissue DNA methylation clock.
Article in GeroScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Automatic extraction of mesenchymal stromal cells from single-cell RNA-sequencing data of human dental pulp.BioData mining · 2026Article
- estiMAge: development of a DNA methylation clock to estimate the methylation age of single cells.Bioinformatics advances · 2025Article
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1 author.
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Abstract
DNA methylation clocks estimate biological age based on DNA methylation profiles. This study developed a mathematical model to describe DNA methylation aging and the establishment of a pan-tissue DNA methylation clock. The model simulates the aging dynamics of DNA methylation profiles based on passive demethylation as well as the process of cross-sectional bulk data acquisition. As a result, this study identified two conditions under which the pan-tissue DNA methylation clock can successfully predict biological age: one condition is that the target tissues are sufficiently well represented in the training dataset, and the other condition is that the target sample contains cell subsets that are common among different tissues. When either of these conditions is met, the clock performs well. It is also suggested that the epigenetic age of all samples in the target tissue tends to be either over or underestimated when biological age prediction fails. The model can reveal the statistical characteristics of DNA methylation clocks.
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