Daniel W Belsky1, Avshalom Caspi2, David L Corcoran2, Karen Sugden3, Richie Poulton4, Louise Arseneault5, Andrea Baccarelli6, Kartik Chamarti3, Xu Gao7, Eilis Hannon8, Hona Lee Harrington3, Renate Houts3, Meeraj Kothari9, Dayoon Kwon10, Jonathan Mill8, Joel Schwartz11, Pantel Vokonas12, Cuicui Wang11, Benjamin S Williams3, Terrie E Moffitt3. 1. Department of Epidemiology & Butler Columbia Aging Center, Columbia University, New York, United States. 2. Center for Genomic and Computational Biology, Duke University, Durham, United States. 3. Department of Psychology and Neuroscience, Duke University, Durham, United States. 4. Department of Psychology, University of Otago, Otago, New Zealand. 5. Social, Genetic, and Developmental Psychiatry Centre, King's College London, London, United Kingdom. 6. Department of Environmental Health Sciences, Columbia University, New York, United States. 7. Department of Occupational and Environmental Health, Peking University, Beijing, China. 8. Complex Disease Epigenetics Group, University of Exeter, Exeter, United Kingdom. 9. Robert N Butler Columbia Aging Center, Columbia University, Brooklyn, United States. 10. Robert N Butler Columbia Aging Center, Columbia University, New York, United States. 11. Department of Environmental Health Sciences, Harvard TH Chan School of Public Health, Harvard University, Boston, United States. 12. Department of Medicine, VA Boston Healthcare System, Boston, United States.
Abstract
Background: Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously, we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al., 2020). Here, we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome). Methods: We used data from the Dunedin Study 1972-1973 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named DunedinPACE, in five additional datasets. Results: DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge. Conclusions: DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience. Funding: This research was supported by US-National Institute on Aging grants AG032282, AG061378, AG066887, and UK Medical Research Council grant MR/P005918/1.
Background: Measures to quantify changes in the pace of biological aging in response to intervention are needed to evaluate geroprotective interventions for humans. Previously, we showed that quantification of the pace of biological aging from a DNA-methylation blood test was possible (Belsky et al., 2020). Here, we report a next-generation DNA-methylation biomarker of Pace of Aging, DunedinPACE (for Pace of Aging Calculated from the Epigenome). Methods: We used data from the Dunedin Study 1972-1973 birth cohort tracking within-individual decline in 19 indicators of organ-system integrity across four time points spanning two decades to model Pace of Aging. We distilled this two-decade Pace of Aging into a single-time-point DNA-methylation blood-test using elastic-net regression and a DNA-methylation dataset restricted to exclude probes with low test-retest reliability. We evaluated the resulting measure, named DunedinPACE, in five additional datasets. Results: DunedinPACE showed high test-retest reliability, was associated with morbidity, disability, and mortality, and indicated faster aging in young adults with childhood adversity. DunedinPACE effect-sizes were similar to GrimAge Clock effect-sizes. In analysis of incident morbidity, disability, and mortality, DunedinPACE and added incremental prediction beyond GrimAge. Conclusions: DunedinPACE is a novel blood biomarker of the pace of aging for gerontology and geroscience. Funding: This research was supported by US-National Institute on Aging grants AG032282, AG061378, AG066887, and UK Medical Research Council grant MR/P005918/1.
Entities:
Keywords:
DNA methylation; aging; biological aging; biomarker; epidemiology; epigenetic; epigenetics; genetics; genomics; gerontology; geroscience; global health; healthspan; methylation
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