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      Temporal Dynamics of Epigenetic Aging and Frailty From Midlife to Old Age

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          Abstract

          Background

          DNA methylation-derived epigenetic clocks and frailty are well-established biological age measures capturing different aging processes. However, whether they are dynamically linked to each other across chronological age remains poorly understood.

          Methods

          This analysis included 1 309 repeated measurements in 524 individuals aged 50–90 years from the Swedish Adoption/Twin Study of Aging. Frailty was measured using a validated 42-item frailty index (FI). Five epigenetic clocks were calculated, including 4 principal component (PC)-based clocks trained on chronological age (PCHorvathAge and PCHannumAge) and aging-related physiological conditions (PCPhenoAge and PCGrimAge), and a pace of aging clock (DunedinPACE). Using dual change score models, we examined the dynamic, bidirectional associations between each of the epigenetic clocks and the FI over age to test for potential causal associations.

          Results

          The FI exhibited a nonlinear, accelerated increase across the older adulthood, whereas the epigenetic clocks mostly increased linearly with age. For PCHorvathAge, PCHannumAge, PCPhenoAge, and PCGrimAge, their associations with the FI were primarily due to correlated levels at age 50 but with no evidence of a dynamic longitudinal association. In contrast, we observed a unidirectional association between DunedinPACE and the FI, where a higher DunedinPACE predicted a subsequent increase in the FI, but not vice versa.

          Conclusions

          Our results highlight a temporal order between epigenetic aging and frailty such that changes in DunedinPACE precede changes in the FI. This potentially suggests that the pace of aging clock can be used as an early marker of the overall physiological decline at system level.

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          Most cited references30

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          Frailty in elderly people

          Frailty is the most problematic expression of population ageing. It is a state of vulnerability to poor resolution of homoeostasis after a stressor event and is a consequence of cumulative decline in many physiological systems during a lifetime. This cumulative decline depletes homoeostatic reserves until minor stressor events trigger disproportionate changes in health status. In landmark studies, investigators have developed valid models of frailty and these models have allowed epidemiological investigations that show the association between frailty and adverse health outcomes. We need to develop more efficient methods to detect frailty and measure its severity in routine clinical practice, especially methods that are useful for primary care. Such progress would greatly inform the appropriate selection of elderly people for invasive procedures or drug treatments and would be the basis for a shift in the care of frail elderly people towards more appropriate goal-directed care. Copyright © 2013 Elsevier Ltd. All rights reserved.
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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: Decision Editor
                Journal
                J Gerontol A Biol Sci Med Sci
                J Gerontol A Biol Sci Med Sci
                gerona
                The Journals of Gerontology Series A: Biological Sciences and Medical Sciences
                Oxford University Press (US )
                1079-5006
                1758-535X
                October 2024
                27 October 2023
                27 October 2023
                : 79
                : 10
                : glad251
                Affiliations
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet , Stockholm, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Stockholm, Sweden
                Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere , Tampere, Finland
                Department of Psychology, University of California , Riverside, California, USA
                Institute for Behavioral Genetics, University of Colorado Boulder , Boulder, Colorado, USA
                (Medical Sciences Section)
                Author notes
                Address correspondence to: Jonathan K.L. Mak, MSc. E-mail: jonathan.mak@ 123456ki.se
                Author information
                https://orcid.org/0000-0003-4454-8580
                https://orcid.org/0000-0003-3605-7829
                https://orcid.org/0000-0002-2452-1500
                https://orcid.org/0000-0003-0250-4491
                https://orcid.org/0000-0001-6502-7173
                Article
                glad251
                10.1093/gerona/glad251
                11421301
                37889476
                0c6b9056-44db-45d0-bc16-ac2da842724e
                © The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 24 August 2023
                : 23 October 2023
                : 14 November 2023
                Page count
                Pages: 8
                Funding
                Funded by: MacArthur Foundation Research Network on Successful Aging;
                Funded by: Swedish Council for Working Life and Social Research, DOI 10.13039/501100001861;
                Award ID: 97:0147:1B
                Award ID: 2009-0795
                Funded by: Swedish Research Council, DOI 10.13039/501100004359;
                Award ID: 825-2007-7460
                Award ID: 825-2009-6141
                Award ID: 521-2013-8689
                Funded by: Swedish Research Council, DOI 10.13039/501100004359;
                Award ID: 2018-02077
                Award ID: 2019-01272
                Award ID: 2020-06101
                Award ID: 2022-01608
                Funded by: Loo & Hans Osterman Foundation;
                Funded by: Karolinska Institutet Foundation;
                Funded by: Strategic Research Program in Epidemiology at Karolinska Institutet;
                Funded by: King Gustaf V and Queen Victoria’s Foundation of Freemasons;
                Funded by: Yrjö Jahnsson Foundation, DOI 10.13039/100010114;
                Funded by: Sigrid Jusélius Foundation, DOI 10.13039/501100006306;
                Funded by: Swedish Research Council, DOI 10.13039/501100004359;
                Award ID: 2017-00641
                Categories
                THE JOURNAL OF GERONTOLOGY: Medical Sciences
                Special Issue: Complex Systems Dynamics and the Aging Process
                Special Article
                AcademicSubjects/MED00280
                AcademicSubjects/SCI00960

                Geriatric medicine
                dna methylation,dual change score models,epigenetic clock,frailty,longitudinal
                Geriatric medicine
                dna methylation, dual change score models, epigenetic clock, frailty, longitudinal

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