Relationship between five Epigenetic Clocks, Telomere Length and Functional Capacity assessed in Older Adults: Cross-sectional and Longitudinal Analyses

Association between frailty index and epigenetic aging acceleration in older adults: Evidence from the health and retirement study

BACKGOUND

This study aimed to examine the associations between the frailty index and four epigenetic aging acceleration (EAA) estimators in cross-sectional and longitudinal settings.

METHODS

The frailty index in the older adults was measured according to a cumulative health-deficit model. Four different epigenetic age measures (Hannum, PhenoAge, GrimAge, and DunedinPoAm38) were regressed against chronological age, and the resulting standardized residuals were indicative of EAA. The longitudinal relationship between EAA at baseline and changes in the frailty index during the 4-year follow-up were examined using a mixed linear model.

RESULTS

A single standard deviation (SD) increment in the frailty index was associated with a faster EAA, as indicated by the four clocks in Hannum (b = 0.057; P = 0.015), PhenoAge (b = 0.096; P < 0.001), GrimAge (b = 0.120; P < 0.001), and DunedinPoAm38 (b = 0.062; P = 0.002) in the fully adjusted model. A 1-SD increment in the GrimAge EAA was associated with a 0.003 frailty index increase (b = 0.003; P = 0.002). A 1-SD increment in DunedinPoAm38 EAA was associated with a 0.002 frailty index increase (b = 0.002; P = 0.009).

CONCLUSIONS

The frailty index was cross-sectionally associated with EAA, while only GrimAge and DunedinPoAm38 EAA predicted changes in the frailty index. More research is needed to understand the interplay between pathways.

There Are Multiple Clocks That Time Us: Cross-Sectional and Longitudinal Associations Among 14 Alternative Indicators of Age and Aging

Aging is a complex process influenced by mechanisms operating at numerous levels of functioning. Multiple biomarkers of age have been identified, yet we know little about how the different alternative age indicators are intertwined. In the Berlin Aging Study II (nmin = 328; nmax = 1 517, women = 51%; 14.27 years of education), we examined how levels and 7-year changes in indicators derived from blood assays, magnetic resonance imaging brain scans, other-ratings, and self-reports converge among older adults. We included 8 epigenetic biomarkers (incl. 5 epigenetic "clocks"), a BioAge composite from clinical laboratory parameters, brain age, skin age, subjective age, subjective life expectancy, and subjective health horizon. We found moderate associations within aging domains, both cross-sectionally and longitudinally over 7 years. However, associations across different domains were infrequent and modest. Notably, participants with older BioAge had correspondingly older epigenetic ages. Our results suggest that different aging clocks are only loosely interconnected and that more specific measures are needed to differentiate healthy from unhealthy aging.

From geroscience to precision geromedicine: Understanding and managing aging

Major progress has been made in elucidating the molecular, cellular, and supracellular mechanisms underlying aging. This has spurred the birth of geroscience, which aims to identify actionable hallmarks of aging. Aging can be viewed as a process that is promoted by overactivation of gerogenes, i.e., genes and molecular pathways that favor biological aging, and alternatively slowed down by gerosuppressors, much as cancers are caused by the activation of oncogenes and prevented by tumor suppressors. Such gerogenes and gerosuppressors are often associated with age-related diseases in human population studies but also offer targets for modeling age-related diseases in animal models and treating or preventing such diseases in humans. Gerogenes and gerosuppressors interact with environmental, behavioral, and psychological risk factors to determine the heterogeneous trajectory of biological aging and disease manifestation. New molecular profiling technologies enable the characterization of gerogenic and gerosuppressive pathways, which serve as biomarkers of aging, hence inaugurating the era of precision geromedicine. It is anticipated that, pending results from randomized clinical trials and regulatory approval, gerotherapeutics will be tailored to each person based on their genetic profile, high-dimensional omics-based biomarkers of aging, clinical and digital biomarkers of aging, psychosocial profile, and past or present exposures.

Symposia Report of The Annual Biological Sciences Section Meeting of the Gerontological Society of America 2023, Tampa, Florida

The aging process is universal, and it is characterized by a progressive deterioration and decrease in physiological function leading to decline on the organismal level. Nevertheless, a number of genetic and nongenetic interventions have been described, which successfully extend healthspan and lifespan in different species. Furthermore, a number of clinical trials have been evaluating the feasibility of different interventions to promote human health. The goal of the annual Biological Sciences Section of the Gerontological Society of America meeting was to share current knowledge of different topics in aging research and provide a vision of the future of aging research. The meeting gathered international experts in diverse areas of aging research including basic biology, demography, and clinical and translational studies. Specific topics included metabolism, inflammaging, epigenetic clocks, frailty, senescence, neuroscience, stem cells, reproductive aging, inter-organelle crosstalk, comparative transcriptomics of longevity, circadian clock, metabolomics, and biodemography.

The Epigenetic Landscape: From Molecular Mechanisms to Biological Aging

Epigenetics, the study of heritable changes in gene expression that do not involve alterations to the deoxyribonucleic acid (DNA) sequence, plays a pivotal role in cellular function, development, and aging. This review explores key epigenetic mechanisms, including DNA methylation (DNAm), histone modifications, chromatin remodeling, RNA-based regulation, and long-distance chromosomal interactions. These modifications contribute to cellular differentiation and function, mediating the dynamic interplay between the genome and environmental factors. Epigenetic clocks, biomarkers based on DNAm patterns, have emerged as powerful tools to measure biological age and predict health span. This article highlights the evolution of epigenetic clocks, from first-generation models such as Horvath's multi-tissue clock to advanced second- and third-generation clocks such as DNAGrimAge and DunedinPACE, which incorporate biological parameters and clinical biomarkers for precise age estimation. Moreover, the role of epigenetics in aging and age-related diseases is discussed, emphasizing its impact on genomic stability, transcriptional regulation, and cellular senescence. Epigenetic dysregulation is implicated in cancer, genetic disorders, and neurodegenerative diseases, making it a promising target for therapeutic interventions. The reversibility of epigenetic modifications offers hope for mitigating age acceleration and enhancing health span through lifestyle changes and pharmacological approaches.

A review of artificial intelligence-based brain age estimation and its applications for related diseases

The study of brain age has emerged over the past decade, aiming to estimate a person's age based on brain imaging scans. Ideally, predicted brain age should match chronological age in healthy individuals. However, brain structure and function change in the presence of brain-related diseases. Consequently, brain age also changes in affected individuals, making the brain age gap (BAG)-the difference between brain age and chronological age-a potential biomarker for brain health, early screening, and identifying age-related cognitive decline and disorders. With the recent successes of artificial intelligence in healthcare, it is essential to track the latest advancements and highlight promising directions. This review paper presents recent machine learning techniques used in brain age estimation (BAE) studies. Typically, BAE models involve developing a machine learning regression model to capture age-related variations in brain structure from imaging scans of healthy individuals and automatically predict brain age for new subjects. The process also involves estimating BAG as a measure of brain health. While we discuss recent clinical applications of BAE methods, we also review studies of biological age that can be integrated into BAE research. Finally, we point out the current limitations of BAE's studies.

Epigenetic Aging and Musculoskeletal Outcomes in a Cohort of Women Living With HIV

BACKGROUND

The relationship between accelerated epigenetic aging and musculoskeletal outcomes in women with HIV (WWH) has not been studied.

METHODS

We measured DNA methylation age using the Infinium MethylationEPIC BeadChip in a cohort from the Women's Interagency HIV Study (n = 190) with measures of bone mineral density (BMD) and physical function. We estimated 6 biomarkers of epigenetic aging-epigenetic age acceleration (EAA), extrinsic EAA, intrinsic EAA, GrimAge, PhenoAge, and DNA methylation-estimated telomere length-and evaluated associations of epigenetic aging measures with BMD and physical function. We also performed epigenome-wide association studies to examine associations of DNA methylation signatures with BMD and physical function.

RESULTS

This study included 118 WWH (mean age, 49.7 years; 69% Black) and 72 without HIV (mean age, 48.9 years; 69% Black). WWH had higher EAA (mean ± SD, 1.44 ± 5.36 vs -1.88 ± 5.07; P < .001) and lower DNA methylation-estimated telomere length (7.13 ± 0.31 vs 7.34 ± 0.23, P < .001) than women without HIV. There were no significant associations between accelerated epigenetic aging and BMD. Rather, measures of accelerated epigenetic aging were associated with lower physical function.

CONCLUSIONS

Accelerated epigenetic aging was observed in WWH as compared with women without HIV and was associated with lower physical function in both groups.

Change in body weight of older adults before and during the COVID-19 pandemic: longitudinal results from the Berlin Aging Study II

OBJECTIVES

Change in body weight during the COVID-19 pandemic as an unintended side effect of lockdown measures has been predominantly reported for younger and middle-aged adults. However, information on older adults for which weight loss is known to result in adverse outcomes, is scarce. In this study we describe the body weight change in older adults before, during, and after the COVID-19 lockdown measures and explore putative associated factors with a focus on the period that includes the first six months of the COVID-19 containment measures.

DESIGN

Prospective cohort study with three follow-up examinations over the course of 10 years.

SETTING AND PARTICIPANTS

In this study, we analyzed the longitudinal weight change of 472 participants of the Berlin Aging Study II (mean age of 67.5 years at baseline).

MEASUREMENTS

Body weight was assessed at four time points. Additionally, differences between subgroups characterized by socio-economic, cognitive, and psychosocial variables as well as morbidity burden, biological age markers (epigenetic clocks, telomere length), and frailty were compared.

RESULTS

On average, women and men lost 0.87% (n = 227) and 0.5% (n = 245) of their body weight per year in the study period covering the first six months of the COVID-19 pandemic. Weight loss among men was particularly pronounced among groups characterized by change in physical activity due to COVID-19 lockdown, low positive affect, premature epigenetic age (7-CpG clock), diagnosed metabolic syndrome, and a more masculine gender score (all variables: p < 0.05, n = 245).

CONCLUSION

During the COVID-19 pandemic, older participants lost weight with a 2.5-times (women) and 2-times (men) higher rate than what is expected in this age.

Geroscience and pathology: a new frontier in understanding age-related diseases

Geroscience, a burgeoning discipline at the intersection of aging and disease, aims to unravel the intricate relationship between the aging process and pathogenesis of age-related diseases. This paper explores the pivotal role played by geroscience in reshaping our understanding of pathology, with a particular focus on age-related diseases. These diseases, spanning cardiovascular and cerebrovascular disorders, malignancies, and neurodegenerative conditions, significantly contribute to the morbidity and mortality of older individuals. We delve into the fundamental cellular and molecular mechanisms underpinning aging, including mitochondrial dysfunction and cellular senescence, and elucidate their profound implications for the pathogenesis of various age-related diseases. Emphasis is placed on the importance of assessing key biomarkers of aging and biological age within the realm of pathology. We also scrutinize the interplay between cellular senescence and cancer biology as a central area of focus, underscoring its paramount significance in contemporary pathological research. Moreover, we shed light on the integration of anti-aging interventions that target fundamental aging processes, such as senolytics, mitochondria-targeted treatments, and interventions that influence epigenetic regulation within the domain of pathology research. In conclusion, the integration of geroscience concepts into pathological research heralds a transformative paradigm shift in our understanding of disease pathogenesis and promises breakthroughs in disease prevention and treatment.

Measuring healthy ageing: current and future tools

Human ageing is a complex, multifactorial process characterised by physiological damage, increased risk of age-related diseases and inevitable functional deterioration. As the population of the world grows older, placing significant strain on social and healthcare resources, there is a growing need to identify reliable and easy-to-employ markers of healthy ageing for early detection of ageing trajectories and disease risk. Such markers would allow for the targeted implementation of strategies or treatments that can lessen suffering, disability, and dependence in old age. In this review, we summarise the healthy ageing scores reported in the literature, with a focus on the past 5 years, and compare and contrast the variables employed. The use of approaches to determine biological age, molecular biomarkers, ageing trajectories, and multi-omics ageing scores are reviewed. We conclude that the ideal healthy ageing score is multisystemic and able to encompass all of the potential alterations associated with ageing. It should also be longitudinal and able to accurately predict ageing complications at an early stage in order to maximize the chances of successful early intervention.

Measuring healthy ageing: current and future tools

Human ageing is a complex, multifactorial process characterised by physiological damage, increased risk of age-related diseases and inevitable functional deterioration. As the population of the world grows older, placing significant strain on social and healthcare resources, there is a growing need to identify reliable and easy-to-employ markers of healthy ageing for early detection of ageing trajectories and disease risk. Such markers would allow for the targeted implementation of strategies or treatments that can lessen suffering, disability, and dependence in old age. In this review, we summarise the healthy ageing scores reported in the literature, with a focus on the past 5 years, and compare and contrast the variables employed. The use of approaches to determine biological age, molecular biomarkers, ageing trajectories, and multi-omics ageing scores are reviewed. We conclude that the ideal healthy ageing score is multisystemic and able to encompass all of the potential alterations associated with ageing. It should also be longitudinal and able to accurately predict ageing complications at an early stage in order to maximize the chances of successful early intervention.

Epigenetic age and socioeconomic status contribute to racial disparities in cognitive and functional aging between Black and White older Americans

Epigenetic age, a biological aging marker measured by DNA methylation, is a potential mechanism by which social factors drive disparities in age-related health. Epigenetic age gap is the residual between epigenetic age measures and chronological age. Previous studies showed associations between epigenetic age gap and age-related outcomes including cognitive capacity and performance on some functional measures, but whether epigenetic age gap contributes to disparities in these outcomes is unknown. We use data from the Health and Retirement Study to examine the role of epigenetic age gap in racial disparities in cognitive and functional outcomes and consider the role of socioeconomic status (SES). Epigenetic age measures are GrimAge or Dunedin Pace of Aging methylation (DPoAm). Cognitive outcomes are cross-sectional score and two-year change in Telephone Interview for Cognitive Status (TICS). Functional outcomes are prevalence and incidence of limitations performing Instrumental Activities of Daily Living (IADLs). We find, relative to White participants, Black participants have lower scores and greater decline in TICS, higher prevalence and incidence rates of IADL limitations, and higher epigenetic age gap. Age- and gender-adjusted analyses reveal that higher GrimAge and DPoAm gap are both associated with worse cognitive and functional outcomes and mediate 6-11% of racial disparities in cognitive outcomes and 19-39% of disparities in functional outcomes. Adjusting for SES attenuates most DPoAm associations and most mediation effects. These results support that epigenetic age gap contributes to racial disparities in cognition and functioning and may be an important mechanism linking social factors to disparities in health outcomes.

Self-reported and accelerometer-based assessment of physical activity in older adults: results from the Berlin Aging Study II

Physical activity (PA) has a substantial impact on health and mortality. Besides questionnaires that rely on subjective assessment of activity levels, accelerometers can help to objectify an individual's PA. In this study, variables estimating PA and sleep time obtained through the wGT3X-BT activity monitor (ActiGraph LLC, USA) in 797 participants of the Berlin Aging Study II (BASE-II) were analyzed. Self-reports of PA and sleep time were recorded with Rapid Assessment of Physical Activity (RAPA) and the Pittsburgh Sleep Quality Index sleep questionnaire (PSQI). Total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), triglycerides (TG), fasting glucose, and hemoglobin A1c (HbA1c) were determined in an accredited standard laboratory. Of all participants, 760 fulfilled the PA wear-time criteria. In this sample mean age was 75.6 years (SD: 3.8 years, range 66.0-94.1 years) and 53% of the included participants were women. Average wear time was 23.2 h/day (SD 1.3 h/day). Statistically significant differences between RAPA groups were found for all accelerometric variables except energy expenditure. Post-hoc analysis, however, suggested low agreement between subjective and device-based assessment of physical activity. TC, HDL-C, LDL-C, TG, fasting glucose and HbA1c were weakly correlated with accelerometric variables (Pearson's r ≤ 0.25). Device-based average sleep time per night (mean sleep time = 6.91 h, SD = 1.3, n = 720) and self-reported average sleep time per night (mean sleep time = 7.1 h, SD = 1.15 h, n = 410) were in a comparable range and moderately correlated (Pearson's r = 0.31, p < 0.001, n = 410). Results from this study suggest that self-reported PA obtained through the RAPA and device-based measures assessed by accelerometers are partially inconsistent in terms of the physical activity level of the participants. Self-reported and device-based measures of average sleep time per night, however, were comparable.

Associations of stress and stress-related psychiatric disorders with GrimAge acceleration: review and suggestions for future work

The notion of "biological aging" as distinct from chronological aging has been of increasing interest in psychiatry, and many studies have explored associations of stress and psychiatric illness with accelerated biological aging. The "epigenetic clocks" are one avenue of this research, wherein "biological age" is estimated using DNA methylation data from specific CpG dinucleotide sites within the human genome. Many iterations of the epigenetic clocks have been developed, but the GrimAge clock continues to stand out for its ability to predict morbidity and mortality. Several studies have now explored associations of stress, PTSD, and MDD with GrimAge acceleration (GrimAA). While stress, PTSD, and MDD are distinct psychiatric entities, they may share common mechanisms underlying accelerated biological aging. Yet, no one has offered a review of the evidence on associations of stress and stress-related psychopathology with GrimAA. In this review, we identify nine publications on associations of stress, PTSD, and MDD with GrimAA. We find that results are mixed both within and across each of these exposures. However, we also find that analytic methods - and specifically, the choice of covariates - vary widely between studies. To address this, we draw upon popular methods from the field of clinical epidemiology to offer (1) a systematic framework for covariate selection, and (2) an approach to results reporting that facilitates analytic consensus. Although covariate selection will differ by the research question, we encourage researchers to consider adjustment for tobacco, alcohol use, physical activity, race, sex, adult socioeconomic status, medical comorbidity, and blood cell composition.

DNA methylation age acceleration is associated with risk of diabetes complications

BACKGROUND

Patients with Type 2 diabetes mellitus (T2D) are at risk for micro- and macrovascular complications. Implementable risk scores are needed to improve targeted prevention for patients that are particularly susceptible to complications. The epigenetic clock estimates an individual's biological age using DNA methylation profiles.

METHODS

In this study, we examined older adults of the Berlin Aging Study II that were reexamined on average 7.4 years after baseline assessment as part of the GendAge study. DNA methylation age (DNAmA) and its deviation from chronological age DNAmA acceleration (DNAmAA) were calculated with the 7-CpG clock (available at both timepoints, n = 1,071), Horvath's clock, Hannum's clock, PhenoAge and GrimAge (available at follow-up only, n = 1,067). T2D associated complications were assessed with the Diabetes Complications Severity Index (DCSI).

RESULTS

We report on a statistically significant association between oral glucose tolerance test results and Hannum and PhenoAge DNAmAA. PhenoAge was also associated with fasting glucose. In contrast, we found no cross-sectional association after covariate adjustment between DNAmAA and a diagnosis of T2D. However, longitudinal analyses showed that every additional year of 7-CpG DNAmAA at baseline increased the odds for developing one or more additional complications or worsening of an already existing complication during the follow-up period by 11% in male participants with T2D. This association persisted after covariate adjustment (OR = 1.11, p = 0.045, n = 56).

CONCLUSION

Although our results remain to be independently validated, this study shows promising evidence of utility of the 7-CpG clock in identifying patients with diabetes who are at high risk for developing complications.

Epigenetic aging in patients diagnosed with coronary artery disease: results of the LipidCardio study

INTRODUCTION

People age biologically at different rates. Epigenetic clock-derived DNA methylation age acceleration (DNAmAA) is among the most promising markers proposed to assess the interindividual differences in biological age. Further research is needed to evaluate the characteristics of the different epigenetic clock biomarkers available with respect to the health domains they reflect best.

METHODS

In this study, we have analyzed 779 participants of the LipidCardio study (mean chronological age 69.9 ± 11.0 years, 30.6% women) who underwent diagnostic angiography at the Charité University Hospital in Berlin, Germany. DNA methylation age (DNAm age) was measured by methylation-sensitive single nucleotide primer extension (MS-SNuPE) and calculated with the 7-CpG clock. We compared the biological age as assessed as DNAmAA of participants with an angiographically confirmed coronary artery disease (CAD, n = 554) with participants with lumen reduction of 50% or less (n = 90) and patients with a normal angiogram (n = 135).

RESULTS

Participants with a confirmed CAD had on average a 2.5-year higher DNAmAA than patients with a normal angiogram. This association did not persist after adjustment for sex in a logistic regression analysis. High-density lipoprotein, low-density lipoprotein, triglycerides, lipoprotein (a), estimated glomerular filtration rate, physical activity, BMI, alcohol consumption, and smoking were not associated with DNAmAA.

CONCLUSION

The association between higher DNAmAA and angiographically confirmed CAD seems to be mainly driven by sex.

Association between Immunosenescence, Mitochondrial Dysfunction and Frailty Syndrome in Older Adults

Aging is associated with changes in the immune system, increased inflammation and mitochondrial dysfunction. The relationship between these phenomena and the clinical phenotype of frailty is unclear. Here, we evaluated the immune phenotypes, T cell functions and mitochondrial functions of immune cells in frail and robust older subjects. We enrolled 20 frail subjects age- and gender-matched with 20 robust controls, and T cell phenotype, response to immune stimulation, cytokine production and immune cell mitochondrial function were assessed. Our results showed that numbers of CD4+ and CD8+ T cells were decreased in frail subjects, without impairment to their ratios. Memory and naïve T cells were not significantly affected by frailty, whereas the expression of CD28 but not that of ICOS was decreased in T cells from frail subjects. T cells from robust subjects produced more IL-17 after CD28 stimulation. Levels of serum cytokines were similar in frail subjects and controls. Mitochondrial bioenergetics and ATP levels were significantly lower in immune cells from frail subjects. In conclusion, we suggest that changes in T cell profiles are associated with aging rather than with frailty syndrome; however, changes in T cell response to immune stimuli and reduced mitochondrial activity in immune cells may be considered hallmarks of frailty.

Epigenome-Wide Association Study in Peripheral Tissues Highlights DNA Methylation Profiles Associated with Episodic Memory Performance in Humans

The decline in episodic memory (EM) performance is a hallmark of cognitive aging and an early clinical sign in Alzheimer’s disease (AD). In this study, we conducted an epigenome-wide association study (EWAS) using DNA methylation (DNAm) profiles from buccal and blood samples for cross-sectional (n = 1019) and longitudinal changes in EM performance (n = 626; average follow-up time 5.4 years) collected under the auspices of the Lifebrain consortium project. The mean age of participants with cross-sectional data was 69 ± 11 years (30−90 years), with 50% being females. We identified 21 loci showing suggestive evidence of association (p < 1 × 10−5) with either or both EM phenotypes. Among these were SNCA, SEPW1 (both cross-sectional EM), ITPK1 (longitudinal EM), and APBA2 (both EM traits), which have been linked to AD or Parkinson’s disease (PD) in previous work. While the EM phenotypes were nominally significantly (p < 0.05) associated with poly-epigenetic scores (PESs) using EWASs on general cognitive function, none remained significant after correction for multiple testing. Likewise, estimating the degree of “epigenetic age acceleration” did not reveal significant associations with either of the two tested EM phenotypes. In summary, our study highlights several interesting candidate loci in which differential DNAm patterns in peripheral tissue are associated with EM performance in humans.

Epigenetic aging and perceived psychological stress in old age

Adverse effects of psychological stress on physical and mental health, especially in older age, are well documented. How perceived stress relates to the epigenetic clock measure, DNA methylation age acceleration (DNAmAA), is less well understood and existing studies reported inconsistent results. DNAmAA was estimated from five epigenetic clocks (7-CpG, Horvath's, Hannum's, PhenoAge and GrimAge DNAmAA). Cohen's Perceived Stress Scale (PSS) was used as marker of psychological stress. We analyzed data from 1,100 Berlin Aging Study II (BASE-II) participants assessed as part of the GendAge study (mean age = 75.6 years, SD = 3.8 years, 52.1% women). In a first step, we replicated well-established associations of perceived stress with morbidity, frailty, and symptoms of depression in the BASE-II cohort studied here. In a second step, we did not find any statistically significant association of perceived stress with any of the five epigenetic clocks in multiple linear regression analyses that adjusted for covariates. Although the body of literature suggests an association between higher DNAmAA and stress or trauma during early childhood, the current study found no evidence for an association of perception of stress with DNAmAA in older people. We discuss possible reasons for the lack of associations and highlight directions for future research.

Vitamin D supplementation is associated with slower epigenetic aging

Adverse effects of low vitamin D level on mortality and morbidity are controversially discussed. Especially older people are at risk for vitamin D deficiency and therefore exposed to its potentially harmful consequences. A way of measuring differences in the biological age is through DNA methylation age (DNAm age) and its deviation from chronological age, DNAm age acceleration (DNAmAA). We previously reported on an association between vitamin D deficiency and higher 7-CpG DNAmAA in participants of the Berlin Aging Study II (BASE-II). In this study, we employ a quasi-interventional study design to assess the relationship between DNAmAA of five epigenetic clocks and vitamin D supplementation. Longitudinal data were available for 1,036 participants of BASE-II that were reexamined on average 7.4 years later in the GendAge study (mean age at follow-up: 75.6 years, SD = 3.8 years, age range: 64.9-94.1 years, 51.9% female). DNAmAA was estimated with the 7-CpG clock, Horvath's clock, Hannum's clock, PhenoAge, and GrimAge. Methylation data were obtained through methylation-sensitive single nucleotide primer extension (MS-SNuPE) or Illumina's Infinium "MethylationEPIC" array. Vitamin D-deficient participants who chose to start vitamin D supplementation after baseline examination showed a 2.6-year lower 7-CpG DNAmAA (p = 0.011) and 1.3-year lower Horvath DNAmAA (p = 0.042) compared to untreated and vitamin D-deficient participants. DNAmAA did not statistically differ between participants with successfully treated vitamin D deficiency and healthy controls (p > 0.16). Therefore, we conclude that intake of vitamin D supplement is associated with lower DNAmAA in participants with vitamin D deficiency.