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      DunedinPACE, a DNA methylation biomarker of the pace of aging

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          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.

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          Most cited references71

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          Regularization and variable selection via the elastic net

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            DNA methylation age of human tissues and cell types

            Background It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. Results I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance. Conclusions I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.
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              An epigenetic biomarker of aging for lifespan and healthspan

              Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation of epigenetic biomarkers of aging were developed using chronological age as a surrogate for biological age, we hypothesized that incorporation of composite clinical measures of phenotypic age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the development of a more powerful epigenetic biomarker of aging. Using an innovative two-step process, we develop a new epigenetic biomarker of aging, DNAm PhenoAge, that strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease. While this biomarker was developed using data from whole blood, it correlates strongly with age in every tissue and cell tested. Based on an in-depth transcriptional analysis in sorted cells, we find that increased epigenetic, relative to chronological age, is associated with increased activation of pro-inflammatory and interferon pathways, and decreased activation of transcriptional/translational machinery, DNA damage response, and mitochondrial signatures. Overall, this single epigenetic biomarker of aging is able to capture risks for an array of diverse outcomes across multiple tissues and cells, and provide insight into important pathways in aging.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                14 January 2022
                2022
                : 11
                : e73420
                Affiliations
                [1 ] Department of Epidemiology & Butler Columbia Aging Center, Columbia University ( https://ror.org/00hj8s172) New York United States
                [2 ] Center for Genomic and Computational Biology, Duke University ( https://ror.org/00py81415) Durham United States
                [3 ] Department of Psychology and Neuroscience, Duke University ( https://ror.org/00py81415) Durham United States
                [4 ] Department of Psychology, University of Otago ( https://ror.org/01jmxt844) Otago New Zealand
                [5 ] Social, Genetic, and Developmental Psychiatry Centre, King's College London ( https://ror.org/0220mzb33) London United Kingdom
                [6 ] Department of Environmental Health Sciences, Columbia University ( https://ror.org/00hj8s172) New York United States
                [7 ] Department of Occupational and Environmental Health, Peking University ( https://ror.org/02v51f717) Beijing China
                [8 ] Complex Disease Epigenetics Group, University of Exeter ( https://ror.org/03yghzc09) Exeter United Kingdom
                [9 ] Robert N Butler Columbia Aging Center, Columbia University ( https://ror.org/00hj8s172) Brooklyn United States
                [10 ] Robert N Butler Columbia Aging Center, Columbia University ( https://ror.org/00hj8s172) New York United States
                [11 ] Department of Environmental Health Sciences, Harvard TH Chan School of Public Health, Harvard University ( https://ror.org/03vek6s52) Boston United States
                [12 ] Department of Medicine, VA Boston Healthcare System ( https://ror.org/04v00sg98) Boston United States
                Max Planck Institute for Biology of Ageing ( https://ror.org/04xx1tc24) Cologne Germany
                Weill Cornell Medicine, Cornell University ( https://ror.org/05bnh6r87) Ithaca United States
                Max Planck Institute for Biology of Ageing ( https://ror.org/04xx1tc24) Cologne Germany
                Max Planck Institute for Biology of Ageing ( https://ror.org/04xx1tc24) Cologne Germany
                University of Bristol United Kingdom
                Max Planck Institute for Biology of Ageing Germany
                Author information
                https://orcid.org/0000-0001-5463-2212
                https://orcid.org/0000-0001-6840-072X
                https://orcid.org/0000-0003-1115-3224
                Article
                73420
                10.7554/eLife.73420
                8853656
                35029144
                6f196fdb-42b4-477b-a72f-002a5eb4495e

                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 27 August 2021
                : 13 December 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: AG032282
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MR/P005918/1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: AG066887
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: AG061378
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100005622, New Zealand Health Research Council;
                Award ID: 16-604
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003524, New Zealand Ministry of Business, Innovation and Employment (MBIE);
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Advance
                Epidemiology and Global Health
                Genetics and Genomics
                Custom metadata
                DunedinPACE is a novel DNA methylation biomarker of the pace of biological aging for intervention trials and natural experiment studies investigating how the rate of aging may be changed by behavioral or drug therapy, or by environmental modification.

                Life sciences
                aging,geroscience,biological aging,gerontology,dna methylation,epigenetic,methylation,healthspan,biomarker,epigenetics

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