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Abstract

Epigenetic clocks have transformed the study of biological aging in epidemiology and clinical trials. However, the utility of these measures in clinical settings is limited by a lack of population-based norms that clinicians, patients, and researchers can use to understand and communicate how fast an individual is aging relative to same-aged peers. Here, we developed age norms for DunedinPACE, an epigenetic Pace of Aging measure derived from DNA methylation. To do so, we meta-analyzed data from 11 cohorts (N = 37,855 individuals, ages 17-99 years) to characterize the association between chronological age and DunedinPACE. We investigated sex differences and nonlinearity, confirmed results using longitudinal data, verified that age-normed DunedinPACE scores predict clinical outcomes, and illustrated how norms support the needs of clinical aging research. The age norms reported here will help integrate biomarkers of aging, such as DunedinPACE, into precision public health and medicine.

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