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      Epigenetic clocks and their association with trajectories in perceived discrimination and depressive symptoms among US middle-aged and older adults

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          Abstract

          Background: Perceived discrimination may be associated with accelerated aging later in life, with depressive symptoms acting as potential mediator.

          Methods: A nationally representative sample of older adults was used [Health and Retirement Study 2010–2016, Age: 50–100 y in 2016, N = 2,806, 55.6% female, 82.3% Non-Hispanic White (NHW)] to evaluate associations of perceived discrimination measures [Experience of discrimination or EOD; and Reasons for Perceived discrimination or RPD) and depressive symptoms (DEP)] with 13 DNAm-based measures of epigenetic aging. Group-based trajectory and four-way mediation analyses were used.

          Results: Overall, and mostly among female and NHW participants, greater RPD in 2010–2012 had a significant adverse total effect on epigenetic aging [2016: DNAm GrimAge, DunedinPoAm38 (MPOA), Levine (PhenoAge) and Horvath 2], with 20–50% of this effect being explained by a pure indirect effect through DEP in 2014–2016. Among females, sustained elevated DEP (2010–2016) was associated with greater LIN DNAm age (β ± SE: +1.506 ± 0.559, p = 0.009, reduced model), patterns observed for elevated DEP (high vs. low) for GrimAge and MPOA DNAm markers. Overall and in White adults, the relationship of the Levine clock with perceived discrimination in general (both EOD and RPD) was mediated through elevated DEP.

          Conclusions: Sustained elevations in DEP and RPD were associated with select biological aging measures, consistently among women and White adults, with DEP acting as mediator in several RPD-EPICLOCK associations.

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          Most cited references60

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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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              Genome-wide methylation profiles reveal quantitative views of human aging rates.

              The ability to measure human aging from molecular profiles has practical implications in many fields, including disease prevention and treatment, forensics, and extension of life. Although chronological age has been linked to changes in DNA methylation, the methylome has not yet been used to measure and compare human aging rates. Here, we build a quantitative model of aging using measurements at more than 450,000 CpG markers from the whole blood of 656 human individuals, aged 19 to 101. This model measures the rate at which an individual's methylome ages, which we show is impacted by gender and genetic variants. We also show that differences in aging rates help explain epigenetic drift and are reflected in the transcriptome. Moreover, we show how our aging model is upheld in other human tissues and reveals an advanced aging rate in tumor tissue. Our model highlights specific components of the aging process and provides a quantitative readout for studying the role of methylation in age-related disease. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Aging (Albany NY)
                Aging
                Aging (Albany NY)
                Impact Journals
                1945-4589
                15 July 2022
                01 July 2022
                : 14
                : 13
                : 5311-5344
                Affiliations
                [1 ]Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
                [2 ]Department of Research Programs, Fort Belvoir Community Hospital, Fort Belvoir, VA 22060, USA
                [3 ]Department of Psychology, University of Maryland, Baltimore County, Catonsville, MD 21250, USA
                [4 ]Department of Demography, University of California Berkeley, Berkeley, CA 94720, USA
                Author notes
                [*]

                Co-first authors

                Correspondence to: May A. Beydoun; email: baydounm@mail.nih.gov
                Article
                204150 204150
                10.18632/aging.204150
                9320538
                35776531
                0b8ebc83-b928-46b9-aca6-be1397a3dc2a
                Copyright: © 2022 Beydoun et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 March 2022
                : 01 June 2022
                Categories
                Research Paper

                Cell biology
                dna methylation,epigenetic clocks,biological age,perceived discrimination,depressive symptoms

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