DNA Methylation “GrimAge” Acceleration Mediates Sex/Gender Differences in Verbal Memory and Processing Speed: Findings From the Health and Retirement Study

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Abstract

Whether sex/gender differences in rates of biological aging mediate sex/gender differences in cognition in older adults has not been fully examined. The aim of the current study was to investigate this association. Data from up to 1 928 participants (mean age = 75, standard deviation = 7.04, female = 57%) who took part in the 2016 Harmonized Cognitive Assessment Protocol and Venous Blood Study; substudies of the Health and Retirement Study were included in the current study. The residuals from 4 age-adjusted epigenetic clocks (Horvath, Hannum, PhenoAge, and GrimAge) were used to measure biological age acceleration. Sex/gender differences in cognition were tested using a series of analyses of covariance. Mediation analyses tested whether the measures of age acceleration accounted for these sex/gender differences, controlling for age, education, smoking status, and white blood cell count. Women outperformed men on measures of verbal learning, verbal memory, visual scanning, and processing speed. No other significant sex/gender differences were identified. Results from mediation analyses revealed that women’s slower rates of GrimAge fully accounted for their faster processing speeds and partially accounted for their better performances on verbal learning, verbal memory, and visual scanning measures. None of the other measures of age acceleration were significant mediators. Accounting for sex/gender differences in biological aging may differentiate between cognitive sex/gender differences that are driven by universal (ie, age-related) versus sex-specific mechanisms. More broadly, these findings support the growing evidence that the GrimAge clock outperforms other clocks in predicting cognitive outcomes.

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Diagnostic and Statistical Manual of Mental Disorders

American Psychiatric Association (2013)

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DNA methylation age of human tissues and cell types

Steve Horvath, Ilias Lagkouvardos (2014)

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

Morgan E Levine, Ake T. Lu, Austin Quach … (2018)

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.