Dynamic DNA methylation during aging: A "prophet" of age-related outcomes
Open accessAbstract
The biological markers of aging used to predict physical health status in older people are of great interest. Telomere shortening, which occurs during the process of cell replication, was initially considered a promising biomarker for the prediction of age and age-related outcomes (e.g., diseases, longevity). However, the high instability in detection and low correlation with age-related outcomes limit the extension of telomere length to the field of prediction. Currently, a growing number of studies have shown that dynamic DNA methylation throughout human lifetime exhibits strong correlation with age and age-related outcomes. Indeed, many researchers have built age prediction models with high accuracy based on age-dependent methylation changes in certain CpG loci. For now, DNA methylation based on epigenetic clocks, namely epigenetic or DNA methylation age, serves as a new standard to track chronological age and predict biological age. Measures of age acceleration (Δage, DNA methylation age - chronological age) have been developed to assess the health status of a person. In addition, there is evidence that an accelerated epigenetic age exists in patients with certain age-related diseases (e.g., Alzheimer's disease, cardiovascular disease). In this review, we provide an overview of the dynamic signatures of DNA methylation during aging and emphasize its practical utility in the prediction of various age-related outcomes.
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Biological confounders known to affect epigenetic patterns such as age, sex, ethnicity, body mass index, smoking behavior or nutritional aspects may introduce critical biases limiting the interpretation of epigenetic data.
“Biological confounders known to affect epigenetic patterns such as age (Xiao, Wang, & Kong, 2019), sex (Yousefi et al., 2015), ethnicity (Fraser, Lam, Neumann, & Kobor, 2012), body mass index (Sayols-Baixeras et al., 2017), smoking behavior (Li et al., 2018) or nutritional aspects (Gadecka & Bielak-Zmijewska, 2019) may introduce critical biases limiting the interpretation of epigenetic data.”
From The applied implications of epigenetics in anxiety, affective and stress-related disorders - A review and synthesis on psychosocial stress, psychotherapy and prevention (2020) · cites this paper as Xiao, Wang, & Kong, 2019
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- Authors
- Xiao, F.-H., Wang, H.-T., & Kong, Q.-P.
- Affiliations
- Chinese University of Hong Kong (HK)
- Corresponding author
- Kong, Qing-Peng
- Venue
- Frontiers in Genetics
- Publisher
- Frontiers Media SA
- Published
- 2019-02-18
- Volume
- 10
- Pages
- 107-107
- ISSN
- 1664-8021 (ISSN-L)
- PMC
- PMC6387955
- OpenAlex
- W2917732063
- Cited by
- 140
- References
- 112
- Citations by year
- 2026: 9 · 2025: 11 · 2024: 24 · 2023: 23 · 2022: 27 · 2021: 28 · 2020: 11 · 2019: 6 · 2013: 1
- FWCI
- 1.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Genetics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Keywords
- DNA methylation, aging, epigenetic clocks, DNA methylation age, biological age, accelerated aging, telomere shortening, age-related diseases, Alzheimer's disease, cardiovascular disease, age prediction model, CpG sites, aging biomarkers
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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