Maximizing insights from longitudinal epigenetic age data: simulations, applications, and practical guidance
Abstract Background Epigenetic age (EA) is an age estimate, developed using DNA methylation (DNAm) states of selected CpG sites across the genome. Although EA and chronological age are highly correlated, EA may not increase uniformly with time. Departures, known as epigenetic age acceleration (EAA),...
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| Main Authors: | Anna Großbach, Matthew J. Suderman, Anke Hüls, Alexandre A. Lussier, Andrew D. A. C. Smith, Esther Walton, Erin C. Dunn, Andrew J. Simpkin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-12-01
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| Series: | Clinical Epigenetics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13148-024-01784-x |
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