ArticleFrontiers in aging2021
Adapting Blood DNA Methylation Aging Clocks for Use in Saliva Samples With Cell-type Deconvolution.
Article in Frontiers in aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Comparison of DNA methylation measured in saliva and peripheral blood as a marker of exposure and outcome: a scoping review.Clinical epigenetics · 2026Article
- A novel framework to build saliva-based DNA methylation biomarkers: Quantifying systemic chronic inflammation as a case study.Aging cell · 2025Article
- Article
- Severe drought exposure in utero associates to children's epigenetic age acceleration in a global climate change hot spot.Nature communications · 2024Article
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Authors and funding
4 authors at 1 institution in 2 countries.
Funding
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Abstract
DeepMAge is a deep-learning DNA methylation aging clock that measures the organismal pace of aging with the information from human epigenetic profiles. In blood samples, DeepMAge can predict chronological age within a 2.8 years error margin, but in saliva samples, its performance is drastically reduced since aging clocks are restricted by the training set domain. However, saliva is an attractive fluid for genomic studies due to its availability, compared to other tissues, including blood. In this article, we display how cell type deconvolution and elastic net can be used to expand the domain of deep aging clocks to other tissues. Using our approach, DeepMAge's error in saliva samples was reduced from 20.9 to 4.7 years with no retraining.
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