Accurately measuring biological age is crucial for improving healthcare for the elderly
population. However, the complexity of aging biology poses challenges in how to robustly …

Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG
methylation values to predict chronological or biological age. Increases in predicted …

Individuals with psychiatric disorders are at increased risk of age-related diseases and early
mortality. Recent studies demonstrate that this link between mental health and aging is …

Biologic aging reflects the genetic, molecular, and cellular changes underlying the
development of morbidity and mortality with advancing chronological age. As several …

Dietary restriction (DR) is the most powerful intervention to enhance health and lifespan
across species. However, recent findings indicate that DR started in late life has limited …

Age-related changes in DNA methylation (DNAm) form the basis of the most robust
predictors of age—epigenetic clocks—but a clear mechanistic understanding of exactly …

Aging is a major risk factor for many diseases. Accurate methods for predicting age in
specific cell types are essential to understand the heterogeneity of aging and to assess …

Chronological age prediction from DNA methylation sheds light on human aging, health,
and lifespan. Current clocks are mostly based on linear models and rely upon hundreds of …

Background Epigenetic clocks are promising tools for the study of aging in humans. The
clocks quantify biological aging above and beyond chronological age, demonstrate …

This review summarizes the current understanding of the interaction between circadian
rhythms of gene expression and epigenetic clocks characterized by the specific profile of …