A systematic review of biological, social and environmental factors associated with epigenetic clock acceleration

Reliable detection of stochastic epigenetic mutations and associations with cardiovascular aging

Stochastic epigenetic mutations (SEMs) have been proposed as novel aging biomarkers to capture heterogeneity in age-related DNA methylation changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. Because SEMs are defined by their outlier status, it is critical to differentiate extreme values due to technical noise or data artifacts from those due to real biology. Using technical replicate data, we found SEM detection is not reliable: across 3 datasets, 24 to 39% of hypoSEM and 46 to 67% of hyperSEM are not shared between replicates. We identified factors influencing SEM reliability-including blood cell type composition, probe beta-value statistics, genomic location, and presence of SNPs. We used these factors in a training dataset to build a machine learning-based filter that removes unreliable SEMs, and found this filter enhances reliability in two independent validation datasets. We assessed associations between SEM loads and aging phenotypes in the Framingham Heart Study and discovered that associations with aging outcomes were in large part driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations were preserved after filtering out unreliable SEMs and were enhanced after adjusting for blood cell composition. Finally, we utilized these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which uses parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.

Self-rated health, epigenetic ageing, and long-term mortality in older Australians

Self-rated health (SRH) is a subjective indicator of overall health based on a single questionnaire item. Previous evidence found that it is a strong predictor of mortality, although the underlying mechanism is poorly understood. Epigenetic age is an objective, emerging biomarker of health, estimated using DNA methylation data at hundreds of sites across the genome. This study aimed to assess the overlap and interaction between SRH and epigenetic ageing in predicting mortality risk. We used DNA methylation data from 1059 participants in the Melbourne Collaborative Cohort Study (mean age: 69 years) to calculate three age-adjusted measures of epigenetic ageing: GrimAge, PhenoAge, and DunedinPACE. SRH was assessed using a five-category questionnaire item ("excellent, very good, good, fair, poor"). Cox models were used to assess the associations of SRH, epigenetic ageing, and their interaction, with all-cause mortality over up to 17 years of follow-up (Ndeaths = 345). The association of SRH with mortality per category increase was HR = 1.29; 95%CI: 1.14-1.46. The association was slightly attenuated after adjusting for all three epigenetic ageing measures (HR = 1.25, 95%CI: 1.10-1.41). A strong gradient was observed in the association of GrimAge (Pinteraction = 0.006) and DunedinPACE (Pinteraction = 0.002) with mortality across worsening SRH strata. For example, the association between DunedinPACE and mortality in participants with "excellent" SRH was HR = 1.02, 95%CI: 0.73-1.43 and for "fair/poor" HR = 1.72, 95%CI: 1.35-2.20. SRH and epigenetic ageing were synergistic risk factors of mortality in our study. These findings suggest that consideration of subjective and objective factors may improve general health assessment, which has implications for the ongoing development of molecular markers of ageing.

Epigenetic Study of Cohort of Monozygotic Twins With Hypertrophic Cardiomyopathy Due to MYBPC3 (Cardiac Myosin-Binding Protein C)

BACKGROUND

Hypertrophic cardiomyopathy is an autosomal dominant cardiac disease. The mechanisms that determine its variable expressivity are poorly understood. Epigenetics could play a crucial role in bridging the gap between genotype and phenotype by orchestrating the interplay between the environment and the genome regulation. In this study we aimed to establish a possible correlation between the peripheral blood DNA methylation patterns and left ventricular hypertrophy severity in patients with hypertrophic cardiomyopathy, evaluating the potential impact of lifestyle variables and providing a biological context to the observed changes.

METHODS AND RESULTS

Methylation data were obtained from peripheral blood samples (Infinium MethylationEPIC BeadChip arrays). We employed multiple pair-matched models to extract genomic positions whose methylation correlates with the degree of left ventricular hypertrophy in 3 monozygotic twin pairs carrying the same founder pathogenic variant (MYBPC3 p.Gly263Ter). This model enables the isolation of the environmental influence, beyond age, on DNA methylation changes by removing the genetic background. Our results revealed a more anxious personality among more severely affected individuals. We identified 56 differentially methylated positions that exhibited moderate, proportional changes in methylation associated with left ventricular hypertrophy. These differentially methylated positions were enriched in regions regulated by repressor histone marks and tended to cluster at genes involved in left ventricular hypertrophy development, such as HOXA5, TRPC3, UCN3, or PLSCR2, suggesting that changes in peripheral blood may reflect myocardial alterations.

CONCLUSIONS

We present a unique pair-matched model, based on 3 monozygotic twin pairs carrying the same founder pathogenic variant and different phenotypes. This study provides further evidence of the pivotal role of epigenetics in hypertrophic cardiomyopathy variable expressivity.

Exploring the potential of epigenetic clocks in aging research

The process of aging is a notable risk factor for numerous age-related illnesses. Hence, a reliable technique for evaluating biological age or the pace of aging is crucial for understanding the aging process and its influence on the progression of disease. Epigenetic alterations are recognized as a prominent biomarker of aging, and epigenetic clocks formulated on this basis have been shown to provide precise estimations of chronological age. Extensive research has validated the effectiveness of epigenetic clocks in determining aging rates, identifying risk factors for aging, evaluating the impact of anti-aging interventions, and predicting the emergence of age-related diseases. This review provides a detailed overview of the theoretical principles underlying the development of epigenetic clocks and their utility in aging research. Furthermore, it explores the existing obstacles and possibilities linked to epigenetic clocks and proposes potential avenues for future studies in this field.

Now and then in eukaryotic DNA methylation

Since the mid-1970s, increasingly innovative methods to detect DNA methylation provided detailed information about its distribution, functions, and dynamics. As a result, new concepts were formulated and older ones were revised, transforming our understanding of the associated biology and catalyzing unprecedented advances in biomedical research, drug development, anthropology, and evolutionary biology. In this review, we discuss a few of the most notable advances, which are intimately intertwined with the study of DNA methylation, with a particular emphasis on the past three decades. Examples of these strides include elucidating the intricacies of 5-methylcytosine (5-mC) oxidation, which are at the core of the reversibility of this epigenetic modification; the three-dimensional structural characterization of eukaryotic DNA methyltransferases, which offered insights into the mechanisms that explain several disease-associated mutations; a more in-depth understanding of DNA methylation in development and disease; the possibility to learn about the biology of extinct species; the development of epigenetic clocks and their use to interrogate aging and disease; and the emergence of epigenetic biomarkers and therapies.

Is age more than a number? Accounting for adult development and aging in the study of psychoneuroimmunology, stress, and health

Traditional stress-and-health models link stressors to their health consequences through a well-characterized cascade. Most of the research assumes that the stress-health sequence unfolds in the same way across adulthood, whether a person is 25 years old or 80. Taking a "developmental" or "lifespan" approach has been synonymous with studying the lasting health impacts of early life experiences. However, theories and evidence from adult development and geroscience suggest that stress-health dynamics evolve in important ways over the adult lifespan-from the stressors that we encounter, to the emotion regulation strategies that we use to confront challenges, to the psychosocial resources at our disposal, to the cellular milieu, and thus to the magnitude of stressors' biological and functional consequences. This critical review synthesizes theoretical perspectives and selected empirical literature on the social-emotional and biological dimensions of aging to promote an Integrative Model of Aging, Stress, and Health. Through this integration, the model illustrates how an interdisciplinary, developmental perspective can enrich our understanding of stress's consequences for health across adulthood. It also seeks to guide a new generation of research questions that confront aging with a multidimensional approach. The piece concludes with personal reflections on the foundational legacy of the author's mentor, Dr. Janice Kiecolt-Glaser.

Characterising developmental dynamics of adult epigenetic clock sites

BACKGROUND

DNA methylation (DNAm), an epigenetic mechanism that regulates gene activity in response to genetic and environmental influences, changes as we age. DNAm at specific sites on the genome can be used to calculate 'epigenetic clocks', which are powerful biomarkers of age, as well as of ageing. However, little is known about how these clock sites 'behave' during development and what factors influence their variability in early life. This knowledge could be used to optimise healthy ageing well before the onset of age-related conditions.

METHODS

We leveraged results from two longitudinal population-based cohorts (N = 5019 samples from 2348 individuals) to characterise trajectories of adult clock sites from birth to early adulthood. To explore what factors may drive early individual differences at these clock sites, we also tested for enrichment of genetic factors and prenatal exposures based on existing epigenome-wide association meta-analyses.

FINDINGS

We find that clock sites (i) diverge widely in their developmental trajectories, often showing non-linear change over time; (ii) are substantially more likely than non-clock sites to vary between individuals already from birth, differences that are predictive of DNAm variation at later ages; and (iii) show enrichment for genetic influences and prenatal environmental exposures, including prenatal smoking, diet and maternal physical health conditions.

INTERPRETATION

These results suggests that age(ing)-related epigenetic processes might originate-and differ between individuals-already very early in development. Understanding what drives these differences may in future help us to devise better strategies to promote healthy ageing.

FUNDING

This research was conducted while C.A.M.C. was a Hevolution/AFAR New Investigator Awardee in Aging Biology and Geroscience Research. Full personal funding details, as well as cohort funding details, can be found in the Acknowledgements.

Modeling the impact of socioeconomic disparity, biological markers and environmental exposures on phenotypic age using mediation analysis and structural equation models

INTRODUCTION

Average age is increasing worldwide, raising the public health burden of age-related diseases, as more resources will be required to manage treatments. Phenotypic Age is a score that can be useful to provide an estimate of the probability of developing aging-related conditions, and prevention of such conditions could be performed efficiently studying the mechanisms leading to an increased phenotypic age. The objective of this study is to characterize the mechanisms that lead to aging acceleration from the interactions among socio-demographic factors, health predispositions and biological phenotypes.

METHODS

We present an approach based on the combination of mediation analysis and structural equation models (SEM) to better characterize these mechanisms, quantifying the interactions between biological and external factors and the effects of preexisting health conditions and socioeconomic disparities. We use two independent cohorts of the NHANES dataset: we use the largest (n = 13,186) to select the variables that enlarge the gap between phenotypic and chronological ages, we then create a SEM based on nested linear regressions to quantify the influence of all sociodemographic variables expressed in three latent variables indicating ethnicity, socioeconomic status and preexisting health status. We then replicate the model and apply it to the second cohort (n = 4,425) to compare the results.

RESULTS

Results show that phenotypic age increases with poor glucose control or obesity-related biomarkers, especially if combined with a low socioeconomic status or the presence of chronic or vascular diseases, and provide a framework to quantify these relationships. Black ethnicity, low income/education and a history of chronic diseases are also associated with a higher phenotypic age. Although these findings are already known in literature, the proposed SEM-based framework provides an useful tool to assess the combinations of these heterogeneous factors from a quantitative point of view.

CONCLUSION

In an aging society, phenotypic age is an important metric that can be used to estimate the individual health risk, however its value is influenced by a myriad of external factors, both biological and sociodemographic. The framework proposed in this paper can help quantifying the combined effects of these factors and be a starting point to the creation of personalized prevention and intervention strategies.

Early resilience and epigenetic ageing: Results from the prospective Young Finns Study with a 31-year follow-up

Evidence is accumulating on the connection of early adversities and harsh family environment with epigenetic ageing. We investigated whether early psychosocial resilience is associated with epigenetic ageing in adulthood. We used the population-based Young Finns data (n = 1593). Early psychosocial resilience was assessed in 1980-1989 across five broad domains: (1) index of psychological strength (self-esteem at home/in general/at school, perceived possibilities to influence at home, internal life control), (2) index of social satisfaction (perceived support from family/friends and life satisfaction), (3) index of leisure time activities (hobbies and physical fitness), (4) index of responsible health behaviors (infrequent smoking or alcohol consumption), and (5) index of school career (school grades and adaptation). Epigenetic ages were calculated for blood samples from 2011, and the analyses were performed with variables describing age deviation (AgeDevHannum, AgeDevHorvath, AgeDevPheno, AgeDevGrim) and DunedinPACE. Covariates included early family environment, polygenic risk scores for schizophrenia and major depression, adulthood education, and adulthood health behaviors. All of the early resilience indexes were associated with lower levels of epigenetic ageing in adulthood, most consistently with AgeDevGrim and DunedinPACE. The associations of psychological strength and social satisfaction, in particular, seemed to be non-linear. In a smaller subsample (n = 289), high early resilience was related to lower AgeDevGrim over a 25-year follow-up in those who had high "baseline" levels of AgeDevGrim. In conclusion, early resilience seems to associate with lower level of epigenetic ageing in adulthood. Our results tentatively suggest that early resilience may increase "equality in epigenetic ageing" in a general population.

DNAm aging biomarkers are responsive: Insights from 51 longevity interventional studies in humans

Aging biomarkers can potentially allow researchers to rapidly monitor the impact of an aging intervention, without the need for decade-spanning trials, by acting as surrogate endpoints. Prior to testing whether aging biomarkers may be useful as surrogate endpoints, it is first necessary to determine whether they are responsive to interventions that target aging. Epigenetic clocks are aging biomarkers based on DNA methylation with prognostic value for many aging outcomes. Many individual studies are beginning to explore whether epigenetic clocks are responsive to interventions. However, the diversity of both interventions and epigenetic clocks in different studies make them difficult to compare systematically. Here, we curate TranslAGE-Response, a harmonized database of 51 public and private longitudinal interventional studies and calculate a consistent set of 16 prominent epigenetic clocks for each study, along with 95 other DNAm biomarkers that help explain changes in each clock. With this database, we discover patterns of responsiveness across a variety of interventions and DNAm biomarkers. For example, clocks trained to predict mortality or pace of aging have the strongest response across all interventions and show consistent agreement with each other, pharmacological and lifestyle interventions drive the strongest response from DNAm biomarkers, and study population and study duration are key factors in driving responsiveness of DNAm biomarkers in an intervention. Some classes of interventions such as TNF-alpha inhibitors have strong, consistent effects across multiple studies, while others such as senolytic drugs have inconsistent effects. Clocks with multiple sub-scores (i.e. "explainable clocks") provide specificity and greater mechanistic insight into responsiveness of interventions than single-score clocks. Our work can help the geroscience field design future clinical trials, by guiding the choice of interventions, specific subsets of epigenetic clocks to minimize multiple testing, study duration, study population, and sample size, with the eventual aim of determining whether epigenetic clocks can be used as surrogate endpoints.

Breaking new ground on human health and well-being with epigenetic clocks: A systematic review and meta-analysis of epigenetic age acceleration associations

Epigenetic clocks provide an accurate molecular readout of epigenetic age and epigenetic age acceleration (EAA) derived from DNA methylation data have shown promise as biomarkers of ageing. This systematic review synthesised research on associations between EAA measures and various physiological, cognitive, social, and environmental factors. A comprehensive search strategy identified 299 publications reporting 1050 unique EAA-factor associations based on 53 methylation clocks. Random-effects meta-analyses pooled results across studies for selected EAA-factor pairs. Significant pooled associations emerged, providing insights into relationships between specific factors and accelerated epigenetic ageing. We developed a novel four-level classification system to categorise this diverse range of factors and enable a structured synthesis. To aid further research planning in this rapidly evolving field, TEAPEE (Tracker of EAA Associations with Phenotype & Environmental Exposure) - an interactive, searchable web table detailing all EAA-factor associations - was developed, cataloguing the epigenetic clocks, associated factors, classification categories, and direct links to the original studies. This resource will empower future investigations into the multifaceted determinants of epigenetic ageing, contributing to a deeper understanding of the epigenome's sensitivity to various life experiences and exposures.

A novel DNA methylation-based surrogate biomarker for chronic systemic inflammation (InfLaMeS): results from the Health and Retirement Study

Chronic low-grade systemic inflammation is a risk factor for chronic diseases and mortality and is an important biomarker in health research. DNA methylation (DNAm) surrogate biomarkers are valuable exposure, risk factor and health outcome predictors in studies where the measures cannot be measured directly and often perform as well or better than direct measure. We generated a DNAm surrogate biomarker for chronic, systemic inflammation from a systemic inflammation latent variable of seven inflammatory markers and evaluated its performance relative to measured inflammatory biomarkers in predicting several age-associated outcomes of interest, including mortality, activities of daily living and multimorbidity in the Health and Retirement Study (HRS). The DNAm surrogate, Inflammation Latent Variable Methylation Surrogate (InfLaMeS), correlated with seven individual inflammation markers (r= -0.2-0.6) and performed as well or better to the systemic inflammation latent variable measure when predicting multimorbidity, disability, and 4-year mortality in HRS. Findings were validated in an external cohort, The Irish Longitudinal Study of Ageing. These results suggest that InfLaMeS provides a robust alternative to measured blood-chemistry measures of inflammation with broad applicability in instances where values of inflammatory markers are not measured but DNAm data is available.

Influence of physical activity on the epigenetic clock: evidence from a Japanese cross-sectional study

BACKGROUND

Biological age, especially epigenetic age derived from the epigenetic clock, is a significant measure of aging, considering the differences in aging rates among individuals. The epigenetic clock, a machine learning-based algorithm, uses DNA methylation states to estimate biological age. Previous studies have reported inconsistent associations between physical activity (PA) and the epigenetic clock, especially second-generation clocks such as PhenoAge and GrimAge. This study aimed to clarify this relationship using cross-sectional data from Japanese participants aged 40-69.

METHODS

We used two datasets from the Saga J-MICC study, of which 867 samples were available for analysis. DNA methylation data from peripheral blood samples were used to calculate the epigenetic age using the epigenetic clocks PhenoAge and GrimAge. PA and sedentary time were measured using a single-axis accelerometer, while self-reported PA, sedentary time, and covariates were assessed using a self-administered questionnaire. The association between PA or sedentary time and epigenetic age acceleration was assessed using multiple linear regression.

RESULTS

Pearson's correlation coefficients between accelerometer-based and self-reported PA variables ranged from 0.09 to 0.20. Multivariable regression analysis showed that accelerometer-based PA and sedentary time were associated with epigenetic age decelerations and accelerations, respectively. However, self-reported PA was not associated with the epigenetic age accelerations.

CONCLUSIONS

These results indicate that reducing sedentary time and increasing PA were associated with slowing both PhenoAge and GrimAge, even in East Asian populations with different exercise habits, body shapes, and lifestyles. This study highlights the potential of objective second-generation epigenetic age acceleration as an outcome index for healthcare interventions and clinical applications.

Psychiatry and sensation: the epigenetic links

A complex interaction among sensory, social and epigenetic determinants in psychiatric conditions was described across all age strata. The high prevalence of mental disorders in individuals with sensory deficits might be attributed to the interaction among social isolation, cognitive functioning and sensory processing. The epigenetic implications of such interactions were examined: environmental and social factors can affect gene expression and impact the pathogenesis of psychiatric disorders also through sensory processing. This article discussed the role of social determinants, in other words, social isolation, loneliness and chronic stress, in promoting psychiatric disorders and, in a vicious circle, sensory deficits (vision, hearing, olfaction and somatosensation). We emphasized the importance of integrating social, sensory and epigenetic factors to target different treatments for psychiatric conditions.

Applicability of epigenetic age models to next-generation methylation arrays

BACKGROUND

Epigenetic clocks are mathematical models used to estimate epigenetic age based on DNA methylation at specific CpG sites. As new methylation microarrays are developed and older models discontinued, existing epigenetic clocks might become obsolete. Here, we explored the effects of the changes introduced in the new EPICv2 DNA methylation array on existing epigenetic clocks.

METHODS

We tested the performance of four epigenetic clocks on the probeset of the EPICv2 array using a dataset of 10,835 samples. We developed a new epigenetic age prediction model compatible across the 450 k, EPICv1, and EPICv2 microarrays and validated it on 2095 samples. We estimated technical noise and intra-subject variation using two datasets with repeated sampling. We used data from (i) cancer survivors who had undergone different therapies, (ii) breast cancer patients and controls, and (iii) an exercise-based interventional study, to test the ability of our model to detect alterations in epigenetic age acceleration in response to theoretically antiaging interventions.

RESULTS

The results of the four epiclocks tested are significantly distorted by the EPICv2 probeset, causing an average difference of up to 25 years. Our new model produced highly accurate chronological age predictions, comparable to a state-of-the-art epiclock. The model reported the lowest epigenetic age acceleration in normal populations, as well as the lowest variation across technical replicates and repeated samples from the same subjects. Finally, our model reproduced previous results of increased epigenetic age acceleration in cancer patients and in survivors treated with radiation therapy, and no changes from exercise-based interventions.

CONCLUSION

Existing epigenetic clocks require updates for full EPICv2 compatibility. Our new model translates the capabilities of state-of-the-art epigenetic clocks to the EPICv2 platform and is cross-compatible with older microarrays. The characterization of epigenetic age prediction variation provides useful metrics to contextualize the relevance of epigenetic age alterations. The analysis of data from subjects influenced by radiation, cancer, and exercise-based interventions shows that despite being good predictors of chronological age, neither a pathological state like breast cancer, a hazardous environmental factor (radiation), nor exercise (a beneficial intervention) caused significant changes in the values of the "epigenetic age" determined by these first-generation models.

Epigenetic age acceleration is associated with occupational exposures, sex, and survival in amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is linked to ageing and genetic and environmental risk factors, yet underlying mechanisms are incompletely understood. We aimed to evaluate epigenetic age acceleration (EAA), i.e., DNA methylation (DNAm) age acceleration, and its association with ALS case status and survival.

METHODS

In this study, we included 428 ALS and 288 control samples collected between 2011 and 2021. We calculated EAA using the GrimAge residual method from ALS and control blood samples and grouped participants with ALS into three ageing groups (fast, normal, slow). We associated EAA with ALS case status and survival, stratified by sex, and correlated it with environmental and biological factors through occupational exposure assessments, immune cell proportions, and transcriptome changes.

FINDINGS

Participants with ALS had higher average EAA by 1.80 ± 0.30 years (p < 0.0001) versus controls. Participants with ALS in the fast ageing group had a hazard ratio of 1.52 (95% confidence interval 1.16-2.00, p = 0.0028) referenced to the normal ageing group. In males, this hazard ratio was 1.55 (95% confidence interval 1.11-2.17, p = 0.010), and EAA was positively correlated with high-risk occupational exposures including particulate matter (adj.p < 0.0001) and metals (adj.p = 0.0087). Also, in male participants with ALS, EAA was positively correlated with neutrophil proportions and was negatively correlated with CD4+ T cell proportions. Pathways dysregulated in participants with ALS with fast ageing included spliceosome, nucleocytoplasmic transport, axon guidance, and interferons.

INTERPRETATION

EAA was associated with ALS case status and, at least in males, with shorter survival after diagnosis. The effect of EAA on ALS was partially explained by occupational exposures and immune cell proportions in a sex-dependent manner. These findings highlight the complex interactions of ageing and exposures in ALS.

FUNDING

NIH, CDC/National ALS Registry, ALS Association, Dr. Randall Whitcomb Fund for ALS Genetics, Peter Clark Fund for ALS Research, Sinai Medical Staff Foundation, Scott L. Pranger ALS Clinic Fund, NeuroNetwork Therapeutic Discovery Fund, NeuroNetwork for Emerging Therapies.

The association between weekly exercise patterns and acceleration of aging: Evidence from a population-based study

BACKGROUND

Acceleration of aging is a major challenge in public health. Previous studies have focused on the associations between specific types of exercise or overall levels of physical activity with accelerated aging, with less attention given to the weekly exercise patterns.

OBJECTIVE

To explore the relationship between weekly exercise patterns and acceleration of aging among American adults.

METHODS

We extracted data from the 2015-2018 National Health and Nutrition Examination Survey (NHANES), involving 9850 participants aged ≥20 with comprehensive records on exercise and phenotypic age. Hierarchical clustering categorized participants into three groups based on weekly exercise time and days: cluster 1 (Rare or No Exercise), cluster 2 (Moderate Frequency, Moderate Duration) and cluster 3 (Moderate Frequency, Long Duration). Acceleration of aging was defined as the phenotypic age advance >0.

RESULTS

After full adjustment, weekly exercise time and days showed the significant non-linear negative correlation with accelerated aging. The risk of accelerated aging was lowest when weekly exercise days reached five and the weekly exercise time reached three hours. Both cluster 2 and cluster 3 were significantly negatively correlated with acceleration of aging. No significant differences were observed in the association with accelerated aging between cluster 2 and cluster 3.

CONCLUSIONS

These findings highlight the importance of targeted exercise programs for healthy aging. They also emphasize the need for public health initiatives to integrate regular physical activity into daily routines to improve the longevity and well-being of American adults.

Retro-age: A unique epigenetic biomarker of aging captured by DNA methylation states of retroelements

Reactivation of retroelements in the human genome has been linked to aging. However, whether the epigenetic state of specific retroelements can predict chronological age remains unknown. We provide evidence that locus-specific retroelement DNA methylation can be used to create retroelement-based epigenetic clocks that accurately measure chronological age in the immune system, across human tissues, and pan-mammalian species. We also developed a highly accurate retroelement epigenetic clock compatible with EPICv.2.0 data that was constructed from CpGs that did not overlap with existing first- and second-generation epigenetic clocks, suggesting a unique signal for epigenetic clocks not previously captured. We found retroelement-based epigenetic clocks were reversed during transient epigenetic reprogramming, accelerated in people living with HIV-1, and responsive to antiretroviral therapy. Our findings highlight the utility of retroelement-based biomarkers of aging and support a renewed emphasis on the role of retroelements in geroscience.

Probabilistic inference of epigenetic age acceleration from cellular dynamics

The emergence of epigenetic predictors was a pivotal moment in geroscience, propelling the measurement and concept of biological aging into a quantitative era; however, while current epigenetic clocks show strong predictive power, they are data-driven in nature and are not based on the underlying biological mechanisms driving methylation dynamics. We show that predictions of these clocks are susceptible to several confounding non-age-related phenomena that make interpretation of these estimates and associations difficult. To address these limitations, we developed a probabilistic model describing methylation transitions at the cellular level. Our approach reveals two measurable components, acceleration and bias, which directly reflect perturbations of the underlying cellular dynamics. Acceleration is the proportional increase in the speed of methylation transitions across CpG sites, whereas bias corresponds to global changes in methylation levels. Using data from 15,900 participants from the Generation Scotland study, we develop a robust inference framework and show that these are two distinct processes confounding current epigenetic predictors. Our results show improved associations of acceleration and bias with physiological traits known to impact healthy aging, such as smoking and alcohol consumption, respectively. Furthermore, a genome-wide association study of epigenetic age acceleration identified seven genomic loci.

Childhood adversity, accelerated GrimAge, and associated health consequences

Childhood adversity is linked to psychological, behavioral, and physical health problems, including obesity and cardiometabolic disease. Epigenetic alterations are one pathway through which the effects of early life stress and adversity might persist into adulthood. Epigenetic mechanisms have also been proposed to explain why cardiometabolic health can vary greatly between individuals with similar Body Mass Index (BMIs). We evaluated two independent cross-sectional cohorts of adults without known medical illness, one of which explicitly recruited individuals with early life stress (ELS) and control participants (n = 195), and the other a general community sample (n = 477). In these cohorts, we examine associations between childhood adversity, epigenetic aging, and metabolic health. Childhood adversity was associated with increased GrimAge Acceleration (GAA) in both cohorts, both utilizing a dichotomous yes/no classification (both p < 0.01) as well as a continuous measure using the Childhood Trauma Questionnaire (CTQ) (both p < 0.05). Further investigation demonstrated that CTQ subscales for physical and sexual abuse (both p < 0.05) were associated with increased GAA in both cohorts, whereas physical and emotional neglect were not. In both cohorts, higher CTQ was also associated with higher BMI and increased insulin resistance (both p < 0.05). Finally, we demonstrate a moderating effect of BMI on the relationship between GAA and insulin resistance where GAA correlated with insulin resistance specifically at higher BMIs. These results, which were largely replicated between two independent cohorts, suggest that interactions between epigenetics, obesity, and metabolic health may be important mechanisms through which childhood adversity contributes to long-term physical and metabolic health effects.

A perspective on epigenomic aging processes in the human brain and their plasticity in patients with mental disorders - a systematic review

The debate surrounding nature versus nurture remains a central question in neuroscience, psychology, and in psychiatry, holding implications for both aging processes and the etiology of mental illness. Epigenetics can serve as a bridge between genetic predisposition and environmental influences, thus offering a potential avenue for addressing these questions. Epigenetic clocks, in particular, offer a theoretical framework for measuring biological age based on DNA methylation signatures, enabling the identification of disparities between biological and chronological age. This structured review seeks to consolidate current knowledge regarding the relationship between mental disorders and epigenetic age within the brain. Through a comprehensive literature search encompassing databases such as EBSCO, PubMed, and ClinicalTrials.gov, relevant studies were identified and analyzed. Studies that met inclusion criteria were scrutinized, focusing on those with large sample sizes, analyses of both brain tissue and blood samples, investigation of frontal cortex markers, and a specific emphasis on schizophrenia and depressive disorders. Our review revealed a paucity of significant findings, yet notable insights emerged from studies meeting specific criteria. Studies characterized by extensive sample sizes, analysis of brain tissue and blood samples, assessment of frontal cortex markers, and a focus on schizophrenia and depressive disorders yielded particularly noteworthy results. Despite the limited number of significant findings, these studies shed light on the complex interplay between epigenetic aging and mental illness. While the current body of literature on epigenetic aging in mental disorders presents limited significant findings, it underscores the importance of further research in this area. Future studies should prioritize large sample sizes, comprehensive analyses of brain tissue and blood samples, exploration of specific brain regions such as the frontal cortex, and a focus on key mental disorders. Such endeavors will contribute to a deeper understanding of the relationship between epigenetic aging and mental illness, potentially informing novel diagnostic and therapeutic approaches.

A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors

Existing metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non-modifiable factors in metabolomic aging have not been systematically studied. Here, a new aging measure-MetaboAgeMort-is developed using metabolomic profiles from 239,291 UK Biobank participants for 10-year all-cause mortality prediction. The MetaboAgeMort showed significant associations with all-cause mortality, cause-specific mortality, and diverse incident diseases. Adding MetaboAgeMort to a conventional risk factors model improved the predictive ability of 10-year mortality. A total of 99 modifiable factors across seven categories are identified for MetaboAgeMort. Among these, 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. The tissue-enrichment analysis showed significant enrichment in liver. While the external validation of the MetaboAgeMort is required, this study illuminates heterogeneous metabolomic aging across the same age, providing avenues for identifying high-risk individuals, developing anti-aging therapies, and personalizing interventions, thus promoting healthy aging and longevity.

Identifying biological markers and sociodemographic factors that influence the gap between phenotypic and chronological ages

INTRODUCTION

The world's population is aging rapidly, leading to increased public health and economic burdens due to age-related cardiovascular and neurodegenerative diseases. Early risk detection is essential for prevention and to improve the quality of life in elderly individuals. Plus, health risks associated with aging are not directly tied to chronological age, but are also influenced by a combination of environmental exposures. Past research has introduced the concept of "Phenotypic Age," which combines age with biomarkers to estimate an individual's health risk.

METHODS

This study explores which factors contribute most to the gap between chronological and phenotypic ages. We combined ten machine learning regression techniques applied to the NHANES dataset, containing demographic, laboratory and socioeconomic data from 41,474 patients, to identify the most important features. We then used clustering analysis and a mixed-effects model to stratify by sex, ethnicity, and education.

RESULTS

We identified 28 demographic, biological and environmental factors related to a significant gap between phenotypic and chronological ages. Stratifying for sex, education and ethnicity, we found statistically significant differences in the outcome distributions.

CONCLUSION

By showing that health risk prevention should consider both biological and sociodemographic factors, we offer a new approach to predict aging rates and potentially improve targeted prevention strategies for age-related conditions.

Quantifiable blood TCR repertoire components associate with immune aging

T cell senescence alters the homeostasis of distinct T cell populations and results in decayed adaptive immune protection in older individuals, but a link between aging and dynamic T cell clone changes has not been made. Here, using a newly developed computational framework, Repertoire Functional Units (RFU), we investigate over 6500 publicly available TCR repertoire sequencing samples from multiple human cohorts and identify age-associated RFUs consistently across different cohorts. Quantification of RFU reduction with aging reveals accelerated loss under immunosuppressive conditions. Systematic analysis of age-associated RFUs in clinical samples manifests a potential link between these RFUs and improved clinical outcomes, such as lower ICU admission and reduced risk of complications, during acute viral infections. Finally, patients receiving bone marrow transplantation show a secondary expansion of the age-associated clones upon stem cell transfer from younger donors. Together, our results suggest the existence of a 'TCR clock' that could reflect the immune functions in aging populations.

Pharmacogenomics and pediatric drug development: science and political power. A narrative review

INTRODUCTION

Pharmacogenomics (PGx) investigates how genomes control enzyme expression. Developmental pharmacology (DP) describes the temporal sequence of enzymes impacting absorption, distribution, metabolism, and excretion (ADME) of food and drugs.

AREAS COVERED

US and European Union (EU) legislation facilitate and/or enforce pediatric studies for all new drugs, called overall 'pediatric drug development' (PDD). DP and PDD look at patients' chronological age, but oscillate between legal and physiological meanings of the term 'child.' Children's bodies become mature with puberty.

EXPERT OPINION

Decades after first DP observations in babies, PGx offers a better understanding of the variability of safety and efficacy of drugs, of the process of aging, and of shifting enzyme patterns across aging. We should rethink and revise outdated interpretations of ADME changes in minors. The Declaration of Helsinki forbids pointless studies that some pediatric researchers and regulatory agencies, more so the EMA than the FDA, demand pointless pediatric studies is regrettable. Medicine needs to differentiate between legal and physiological meanings of the term 'child' and should use objective measures of maturity.

Epigenetic aging in major depressive disorder: Clocks, mechanisms and therapeutic perspectives

Depression, a chronic mental disorder characterized by persistent sadness, loss of interest, and difficulty in daily tasks, impacts millions globally with varying treatment options. Antidepressants, despite their long half-life and minimal effectiveness, leave half of patients undertreated, highlighting the need for new therapies to enhance well-being. Epigenetics, which studies genetic changes in gene expression or cellular phenotype without altering the underlying Deoxyribonucleic Acid (DNA) sequence, is explored in this article. This article delves into the intricate relationship between epigenetic mechanisms and depression, shedding light on how environmental stressors, early-life adversity, and genetic predispositions shape gene expression patterns associated with depression. We have also discussed Histone Deacetylase (HDAC) inhibitors, which enhance cognitive function and mood regulation in depression. Non-coding RNAs, (ncRNAs) such as Long Non-Coding RNAs (lncRNAs) and micro RNA (miRNAs), are highlighted as potential biomarkers for detecting and monitoring major depressive disorder (MDD). This article also emphasizes the reversible nature of epigenetic modifications and their influence on neuronal growth processes, underscoring the dynamic interplay between genetics, environment, and epigenetics in depression development. It explores the therapeutic potential of targeting epigenetic pathways in treating clinical depression. Additionally, it examines clinical findings related to epigenetic clocks and their role in studying depression and biological aging.

Childhood Adversity and Adolescent Epigenetic Age Acceleration: The Role of Adolescent Sleep Health

Study Objectives

We investigated how a dimension of early life adversity (ELA) capturing threat in the home relates to later epigenetic age acceleration in adolescence through sleep (duration, efficiency, and timing), to empirically test theoretical models suggesting the importance of sleep as a key mechanism linking ELA with poor health outcomes, and to expand the limited literature on sleep and epigenetic aging among youth.

Methods

We utilized data from 861 participants from the Future of Families and Child Wellbeing Study (FFCWS) who participated in the actigraphy sub study at age 15. Sleep variables used were average total sleep time (TST), sleep efficiency (SE), and sleep onset timing. Home threat was determined at ages 3, 5, and 9 from parent reports on the Child Conflict Tactics Scale (CTS-PC), and epigenetic aging was measured through DNA methylation analyses of saliva samples collected at age 15.

Results

Higher levels of childhood home threat exposure were associated with less adolescent TST, lower SE, and later sleep onset timing. Adolescent SE and timing were associated with a faster pace of aging and epigenetic age acceleration. Sleep efficiency and timing mediated the link between childhood home threat exposure and adolescent epigenetic aging.

Conclusions

Epigenetic embedding of childhood threat exposure in the home may occur through adversity-related sleep disturbances in adolescence. Findings warrant greater attention to pediatric sleep health in theoretical models of biological embedding of adversity and point to the examination of improving sleep health as a potential way to prevent adversity-related epigenetic age acceleration.

Gestational epigenetic age and ADHD symptoms in childhood: a prospective, multi-cohort study

Epigenetic age acceleration (EAA), defined as the difference between chronological age and epigenetically predicted age, was calculated from multiple gestational epigenetic clocks (Bohlin, EPIC overlap, and Knight) using DNA methylation levels from cord blood in three large population-based birth cohorts: the Generation R Study (The Netherlands), the Avon Longitudinal Study of Parents and Children (United Kingdom), and the Norwegian Mother, Father and Child Cohort Study (Norway). We hypothesized that a lower EAA associates prospectively with increased ADHD symptoms. We tested our hypotheses in these three cohorts and meta-analyzed the results (n = 3383). We replicated previous research on the association between gestational age (GA) and ADHD. Both clinically measured gestational age as well as epigenetic age measures at birth were negatively associated with ADHD symptoms at ages 5-7 years (clinical GA: β = -0.04, p < 0.001, Bohlin: β = -0.05, p = 0.01; EPIC overlap: β = -0.05, p = 0.01; Knight: β = -0.01, p = 0.26). Raw EAA (difference between clinical and epigenetically estimated gestational age) was positively associated with ADHD in our main model, whereas residual EAA (raw EAA corrected for clinical gestational age) was not associated with ADHD symptoms across cohorts. Overall, findings support a link between lower gestational age (either measured clinically or using epigenetic-derived estimates) and ADHD symptoms. Epigenetic age acceleration does not, however, add unique information about ADHD risk independent of clinically estimated gestational age at birth.

Map of epigenetic age acceleration: A worldwide analysis

We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.

A systematic review of phenotypic and epigenetic clocks used for aging and mortality quantification in humans

Aging is the leading driver of disease in humans and has profound impacts on mortality. Biological clocks are used to measure the aging process in the hopes of identifying possible interventions. Biological clocks may be categorized as phenotypic or epigenetic, where phenotypic clocks use easily measurable clinical biomarkers and epigenetic clocks use cellular methylation data. In recent years, methylation clocks have attained phenomenal performance when predicting chronological age and have been linked to various age-related diseases. Additionally, phenotypic clocks have been proven to be able to predict mortality better than chronological age, providing intracellular insights into the aging process. This review aimed to systematically survey all proposed epigenetic and phenotypic clocks to date, excluding mitotic clocks (i.e., cancer risk clocks) and those that were modeled using non-human samples. We reported the predictive performance of 33 clocks and outlined the statistical or machine learning techniques used. We also reported the most influential clinical measurements used in the included phenotypic clocks. Our findings provide a systematic reporting of the last decade of biological clock research and indicate possible avenues for future research.

Common DNA sequence variation influences epigenetic aging in African populations

Aging is associated with genome-wide changes in DNA methylation in humans, facilitating the development of epigenetic age prediction models. However, most of these models have been trained primarily on European-ancestry individuals, and none account for the impact of methylation quantitative trait loci (meQTL). To address these gaps, we analyzed the relationships between age, genotype, and CpG methylation in 3 understudied populations: central African Baka (n = 35), southern African ‡Khomani San (n = 52), and southern African Himba (n = 51). We find that published prediction methods yield higher mean errors in these cohorts compared to European-ancestry individuals, and find that unaccounted-for DNA sequence variation may be a significant factor underlying this loss of accuracy. We leverage information about the associations between DNA genotype and CpG methylation to develop an age predictor that is minimally influenced by meQTL, and show that this model remains accurate across a broad range of genetic backgrounds. Intriguingly, we also find that the older individuals and those exhibiting relatively lower epigenetic age acceleration in our cohorts tend to carry more epigenetic age-reducing genetic variants, suggesting a novel mechanism by which heritable factors can influence longevity.

Influence of Single Nucleotide Polymorphisms on CRS Outcomes: A Preliminary Observational Study

OBJECTIVE(S)

To conduct a preliminary investigation into the relationship between specific SNP variants, type II inflammation, and the effectiveness of dupilumab therapy and surgery in patients with CRS.

METHODS

In this prospective study, 48 subjects were enrolled, comprising 32 CRS patients and 16 healthy controls. The CRS patients were subjected to either dupilumab therapy or endoscopic surgery according to EPOS guidelines. SNP variants were identified using the TaqMan SNP genotyping technique. The identified SNP profiles were compared between the control group and CRS patients, and their potential influence on treatment outcomes was evaluated. Treatment responses were assessed based on symptom scores, such as SS-I, SNOT-22, disease progression using the NPS findings, and SNP profiles at a 6-month follow-up. The primary measures included the Nasal Polyp Score, Smell Identification Test (SIT) score, and SNOT-22 outcomes.

RESULTS

Dupilumab therapy and surgery significantly decreased NPS, with the last showing superior results. However, dupilumab therapy resulted in a significantly improved SIT score. Significant differences were observed in SNP profiles, particularly with rs1800629 (TNFA), rs2856838 (IL1a), rs17561 (IL1a), and rs1805011 (IL4R). In particular, the expression of rs2856838 and rs1805011 variants in the dupilumab group was associated with significantly better SIT and SNOT-22 outcomes than non-expressors. Also, the surgery group patients expressing the rs2856838 variant reported significant improvements in SNOT-22 scores.

CONCLUSION

These preliminary findings suggest that SNP genotypes may guide personalized treatment strategies for CRS. Further larger prospective studies are required to confirm these initial observations.

LEVEL OF EVIDENCE

2 Laryngoscope, 2024.

Development of an epigenetic clock resistant to changes in immune cell composition

Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG methylation values to predict chronological or biological age. Increases in predicted epigenetic age relative to chronological age (epigenetic age acceleration) are connected to aging-associated pathologies, and changes in epigenetic age are linked to canonical aging hallmarks. However, epigenetic clocks rely on training data from bulk tissues whose cellular composition changes with age. Here, we found that human naive CD8+ T cells, which decrease in frequency during aging, exhibit an epigenetic age 15-20 years younger than effector memory CD8+ T cells from the same individual. Importantly, homogenous naive T cells isolated from individuals of different ages show a progressive increase in epigenetic age, indicating that current epigenetic clocks measure two independent variables, aging and immune cell composition. To isolate the age-associated cell intrinsic changes, we created an epigenetic clock, the IntrinClock, that did not change among 10 immune cell types tested. IntrinClock shows a robust predicted epigenetic age increase in a model of replicative senescence in vitro and age reversal during OSKM-mediated reprogramming.

GrimAge is elevated in older adults with mild COVID-19 an exploratory analysis

COVID-19 has been contained; however, the side effects associated with its infection continue to be a challenge for public health, particularly for older adults. On the other hand, epigenetic status contributes to the inter-individual health status and is associated with COVID-19 severity. Nevertheless, current studies focus only on severe COVID-19. Considering that most of the worldwide population developed mild COVID-19 infection. In the present exploratory study, we aim to analyze the association of mild COVID-19 with epigenetic ages (HorvathAge, HannumAge, GrimAge, PhenoAge, SkinAge, and DNAmTL) and clinical variables obtained from a Mexican cohort of older adults. We found that all epigenetic ages significantly differ from the chronological age, but only GrimAge is elevated. Additionally, both the intrinsic epigenetic age acceleration (IEAA) and the extrinsic epigenetic age acceleration (EEAA) are accelerated in all patients. Moreover, we found that immunological estimators and DNA damage were associated with PhenoAge, SkinBloodHorvathAge, and HorvathAge, suggesting that the effects of mild COVID-19 on the epigenetic clocks are mainly associated with inflammation and immunology changes. In conclusion, our results show that the effects of mild COVID-19 on the epigenetic clock are mainly associated with the immune system and an increase in GrimAge, IEAA, and EEAA.

Is exposure to pesticides associated with biological aging? A systematic review and meta-analysis

OBJECTIVE

Exposure to pesticides is a risk factor for various diseases, yet its association with biological aging remains unclear. We aimed to systematically investigate the relationship between pesticide exposure and biological aging.

METHODS

PubMed, Embase and Web of Science were searched from inception to August 2023. Observational studies investigating the association between pesticide exposure and biomarkers of biological aging were included. Three-level random-effect meta-analysis was used to synthesize the data. Risk of bias was assessed by the Newcastle-Ottawa Scale.

RESULTS

Twenty studies evaluating the associations between pesticide exposure and biomarkers of biological aging in 10,368 individuals were included. Sixteen reported telomere length and four reported epigenetic clocks. Meta-analysis showed no statistically significant associations between pesticide exposure and the Hannum clock (pooled β = 0.27; 95 %CI: -0.25, 0.79), or telomere length (pooled Hedges'g = -0.46; 95 %CI: -1.10, 0.19). However, the opposite direction of effects for the two outcomes showed an indication of possible accelerated biological aging. After removal of influential effect sizes or low-quality studies, shorter telomere length was found in higher-exposed populations.

CONCLUSION

The existing evidence for associations between pesticide exposure and biological aging is limited due to the scarcity of studies on epigenetic clocks and the substantial heterogeneity across studies on telomere length. High-quality studies incorporating more biomarkers of biological aging, focusing more on active chemical ingredients of pesticides and accounting for potential confounders are needed to enhance our understanding of the impact of pesticides on biological aging.

Lifestyle factors and metabolomic aging biomarkers: Meta-analysis of cross-sectional and longitudinal associations in three prospective cohorts

Biological age uses biophysiological information to capture a person's age-related risk of adverse outcomes. MetaboAge and MetaboHealth are metabolomics-based biomarkers of biological age trained on chronological age and mortality risk, respectively. Lifestyle factors contribute to the extent chronological and biological age differ. The association of lifestyle factors with MetaboAge and MetaboHealth, potential sex differences in these associations, and MetaboAge's and MetaboHealth's sensitivity to lifestyle changes have not been studied yet. Linear regression analyses and mixed-effect models were used to examine the cross-sectional and longitudinal associations of scaled lifestyle factors with scaled MetaboAge and MetaboHealth in 24,332 middle-aged participants from the Doetinchem Cohort Study, Rotterdam Study, and UK Biobank. Random-effect meta-analyses were performed across cohorts. Repeated metabolomics measurements had a ten-year interval in the Doetinchem Cohort Study and a five-year interval in the UK Biobank. In the first study incorporating longitudinal information on MetaboAge and MetaboHealth, we demonstrate associations between current smoking, sleeping ≥8 hours/day, higher BMI, and larger waist circumference were associated with higher MetaboHealth, the latter two also with higher MetaboAge. Furthermore, adhering to the dietary and physical activity guidelines were inversely associated with MetaboHealth. Lastly, we observed sex differences in the associations between alcohol use and MetaboHealth.

Epigenetic Aging Helps Explain Differential Resilience in Older Adults

Past research suggests that resilience to health hazards increases with age, potentially because less resilient individuals die at earlier ages, leaving behind their more resilient peers. Using lifetime cigarette smoking as a model health hazard, we examined whether accelerated epigenetic aging (indicating differences in the speed of individuals' underlying aging process) helps explain age-related resilience in a nationally representative sample of 3,783 older U.S. adults from the Health and Retirement Study. Results of mediation moderation analyses indicated that participants aged 86 or older showed a weaker association between lifetime cigarette smoking and mortality relative to participants aged 76-85 and a weaker association between smoking and multimorbidity relative to all younger cohorts. This moderation effect was mediated by a reduced association between smoking pack-years and epigenetic aging. This research helps identify subpopulations of particularly resilient individuals and identifies epigenetic aging as a potential mechanism explaining this process. Interventions in younger adults could utilize epigenetic aging estimates to identify the most vulnerable individuals and intervene before adverse health outcomes, such as chronic disease morbidity or mortality, manifest.

The effects of acute exercise on stress reactivity assessed via a multidimensional approach: a systematic review

Psychological stress is associated with numerous deleterious health effects. Accumulating evidence suggests acute exercise reduces stress reactivity. As stressors activate a wide array of psychological and physiological systems it is imperative stress responses are examined through a multidimensional lens. Moreover, it seems prudent to consider whether stress responses are influenced by exercise intervention characteristics such as modality, duration, intensity, timing, as well as participant fitness/physical activity levels. The current review therefore examined the role of acute exercise on stress reactivity through a multidimensional approach, as well as whether exercise intervention characteristics and participant fitness/physical activity levels may moderate these effects. Stress reactivity was assessed via heart rate, blood pressure, cortisol, catecholamines, and self-report. A systematic search following PRISMA guidelines of five databases was updated in November 2022. Reviewed studies met the following criteria: English language, participants aged ≥ 18, use of acute exercise, use of a validated stress-inducing task, and assessment(s) of stress reactivity. Thirty-one studies (1386 participants) were included. Acute exercise resulted in reliable reductions to blood pressure and cortisol. Acute exercise yielded mostly negligible effects on heart rate reactivity and negligible effects on self-report measures. As for exercise intervention characteristics, intensity-dependent effects were present, such that higher intensities yielded larger reductions to reactivity measures, while limited evidence was present for duration, modality, and timing-dependent effects. Regarding participant fitness/physical activity levels, the effects on stress reactivity were mixed. Future work should standardize the definitions and assessment time points of stress reactivity, as well as investigate the interaction between physiological and psychological stress responses in real-world contexts.

Editorial: Can Improving Youth Mental Health Reduce Mortality?

It is well established that mental health conditions, including substance use disorders, are associated with premature mortality. A meta-analysis1 has demonstrated that this association holds across a range of diagnoses. Although the effect is stronger for schizophrenia, depression and anxiety contribute to more deaths overall because of their high prevalence rates. Moreover, more than two-thirds of associated deaths were explained by natural causes.1 The next logical questions, then, are as follows: which mechanisms underlie this association, and can they can be mitigated? In the current issue of JAACAP, Clark et al.2 aim to tie mental health symptoms and substance use to the acceleration of biological aging.

Discovering the direct relations between nutrients and epigenetic ageing

BACKGROUND

Along with the ageing of society, the absolute prevalence of age-related diseases is expected to rise, leading to a substantial burden on healthcare systems and society. Thus, there is an urgent need to promote healthy ageing. As opposed to chronological age, biological age was introduced to accurately represent the ageing process, as it considers physiological deterioration that is linked to morbidity and mortality risk. Furthermore, biological age responds to various factors, including nutritional factors, which have the potential to mitigate the risk of age-related diseases. As a result, a promising biomarker of biological age known as the epigenetic clock has emerged as a suitable measure to investigate the direct relations between nutritional factors and ageing, thereby identifying potential intervention targets to improve healthy ageing.

METHODS

In this study, we analysed data from 3,969 postmenopausal women from the Women's Health Initiative to identify nutrients that are associated with the rate of ageing by using an accurate measure of biological age called the PhenoAge epigenetic clock. We used Copula Graphical Models, a data-driven exploratory analysis tool, to identify direct relationships between nutrient intake and age-acceleration, while correcting for every variable in the dataset.

RESULTS

We revealed that increased dietary intakes of coumestrol, beta-carotene and arachidic acid were associated with decelerated epigenetic ageing. In contrast, increased intakes of added sugar, gondoic acid, behenic acid, arachidonic acid, vitamin A and ash were associated with accelerated epigenetic ageing in postmenopausal women.

CONCLUSION

Our study discovered direct relations between nutrients and epigenetic ageing, revealing promising areas for follow-up studies to determine the magnitude and causality of our estimated diet-epigenetic relationships.

Childhood trauma is linked to epigenetic age deceleration in young adults with previous youth residential care placements

Background: Early adversity increases the risk for mental and physical disorders as well as premature death. Epigenetic processes, and altered epigenetic aging in particular, might mediate these effects. While the literature that examined links between early adversity and epigenetic aging is growing, results have been heterogeneous.Objective: In the current work, we explored the link between early adversity and epigenetic aging in a sample of formerly out-of-home placed young adults.Method: A total of N = 117 young adults (32% women, age mean = 26.3 years, SD = 3.6 years) with previous youth residential care placements completed the Childhood Trauma Questionnaire (CTQ) and the Life Events Checklist (LEC-R) and provided blood samples for the analysis of DNA methylation using the Illumina Infinium MethylationEPIC BeadChip Microarray. Epigenetic age was estimated using Hovarth's and Hannum's epigenetic clocks. Furthermore, Hovarth's and Hannum's epigenetic age residuals were calculated as a proxy of epigenetic aging by regressing epigenetic age on chronological age. The statistical analysis plan was preregistered (https://osf.io/b9ev8).Results: Childhood trauma (CTQ) was negatively associated with Hannum's epigenetic age residuals, β = -.23, p = .004 when controlling for sex, BMI, smoking status and proportional white blood cell type estimates. This association was driven by experiences of physical neglect, β = -.25, p = .001. Lifetime trauma exposure (LEC-R) was not a significant predictor of epigenetic age residuals.Conclusion: Childhood trauma, and physical neglect in particular, was associated with decelerated epigenetic aging in our sample. More studies focusing on formerly institutionalized at-risk populations are needed to better understand which factors affect stress-related adaptations following traumatic experiences.

Revealing the Hidden Impacts: Insights into Biological Aging and Long-Term Effects in Pauci- and Asymptomatic COVID-19 Healthcare Workers

This study explores the role of inflammation and oxidative stress, hallmarks of COVID-19, in accelerating cellular biological aging. We investigated early molecular markers-DNA methylation age (DNAmAge) and telomere length (TL)-in blood leukocytes, nasal cells (NCs), and induced sputum (IS) one year post-infection in pauci- and asymptomatic healthcare workers (HCWs) infected during the first pandemic wave (February-May 2020), compared to COPD patients, model for "aged lung". Data from questionnaires, Work Ability Index (WAI), blood analyses, autonomic cardiac balance assessments, heart rate variability (HRV), and pulmonary function tests were collected. Elevated leukocyte DNAmAge significantly correlated with advancing age, male sex, daytime work, and an aged phenotype characterized by chronic diseases, elevated LDL and glycemia levels, medications affecting HRV, and declines in lung function, WAI, lymphocyte count, hemoglobin levels, and HRV (p < 0.05). Increasing age, LDL levels, job positions involving intensive patient contact, and higher leukocyte counts collectively contributed to shortened leukocyte TL (p < 0.05). Notably, HCWs exhibited accelerated biological aging in IS cells compared to both blood leukocytes (p ≤ 0.05) and NCs (p < 0.001) and were biologically older than COPD patients (p < 0.05). These findings suggest the need to monitor aging in pauci- and asymptomatic COVID-19 survivors, who represent the majority of the general population.

Effects of walking on epigenetic age acceleration: a Mendelian randomization study

INTRODUCTION

Walking stands as the most prevalent physical activity in the daily lives of individuals and is closely associated with physical functioning and the aging process. Nonetheless, the precise cause-and-effect connection between walking and aging remains unexplored. The epigenetic clock emerges as the most promising biological indicator of aging, capable of mirroring the biological age of the human body and facilitating an investigation into the association between walking and aging. Our primary objective is to investigate the causal impact of walking with epigenetic age acceleration (EAA).

METHODS

We conducted a two-sample two-way Mendelian randomization (MR) study to investigate the causal relationship between walking and EAA. Walking and Leisure sedentary behavior data were sourced from UK Biobank, while EAA data were gathered from a total of 28 cohorts. The MR analysis was carried out using several methods, including the inverse variance weighted (IVW), weighted median, MR-Egger, and robust adjusted profile score (RAPS). To ensure the robustness of our findings, we conducted sensitivity analyses, which involved the MR-Egger intercept test, Cochran's Q test, and MR-PRESSO, to account for and mitigate potential pleiotropy.

RESULTS

The IVW MR results indicate a significant impact of usual walking pace on GrimAge (BETA = - 1.84, 95% CI (- 2.94, - 0.75)), PhenoAge (BETA = - 1.57, 95% CI (- 3.05, - 0.08)), Horvath (BETA = - 1.09 (- 2.14, - 0.04)), and Hannum (BETA = - 1.63, 95% CI (- 2.70, - 0.56)). Usual walking pace is significantly associated with a delay in epigenetic aging acceleration (EAA) (P < 0.05). Moreover, the direction of effect predicted by the gene remained consistent across RAPS outcomes and sensitivity MR analyses. There is a lack of robust causal relationships between other walking conditions, such as walking duration and walking frequency, on EAA (P > 0.05).

CONCLUSION

Our evidence demonstrates that a higher usual walking pace is associated with a deceleration of the acceleration of all four classical epigenetic clocks acceleration.

Generations of epigenetic clocks and their links to socioeconomic status in the Health and Retirement Study

Aim: This is a brief description of links between nine epigenetic clocks related to human aging and socioeconomic and behavioral characteristics as well as health outcomes.Materials & methods: We estimate frequently used and novel clocks from one data source, the Health and Retirement Study.Results: While all of these clocks are thought to reflect "aging," they use different CpG sites and do not strongly relate to each other. First and fourth generation clocks are not as linked to socioeconomic status or health outcomes as second and third generation clocks.Conclusion: Epigenetic clocks reflect exciting new tools and their continued evolution is likely to improve our understanding of how exposures get under the skin to accelerate aging.

Examining nutrition strategies to influence DNA methylation and epigenetic clocks: a systematic review of clinical trials

Nutrition has powerful impacts on our health and longevity. One of the mechanisms by which nutrition might influence our health is by inducing epigenetic modifications, modulating the molecular mechanisms that regulate aging. Observational studies have provided evidence of a relationship between nutrition and differences in DNA methylation. However, these studies are limited in that they might not provide an accurate control of the interactions between different nutrients, or between nutrition and other lifestyle behaviors. Here we systematically reviewed clinical studies examining the impact of nutrition strategies on DNA methylation. We examined clinical studies in community-dwelling adults testing the effects of nutrition interventions on i) global DNA methylation and its proxies, and ii) epigenetic clocks. We included 21 intervention studies that focused on the effects of healthy nutrition patterns, specific foods or nutrients, as well as the effect of multivitamin or multimineral supplements. In four studies on the methylation effects of healthy dietary patterns, as defined by being rich in vegetables, fruits, whole-grains, and nuts and reduced in the intake of added sugars, saturated fat, and alcohol, two of them suggested that a healthy diet, is associated with lower epigenetic age acceleration, one of them reported increases in global DNA methylation, while another one found no diet effects. Studies examining epigenetic effects of specific foods, nutrients, or mixtures of nutrients were scarce. For both folic acid and polyunsaturated fatty acids, the available independent studies produced conflicting findings. Although more evidence is still needed to draw firm conclusions, results begin to suggest that healthy dietary patterns have positive effects on DNA methylation. Additional evidence from large randomized-controlled clinical trials is needed to support the effects of healthy nutrition on the DNA methylome.

Trauma, adversity, and biological aging: behavioral mechanisms relevant to treatment and theory

Although stress and adversity are largely universal experiences, people exposed to greater hardship are at increased risk for negative health consequences. Recent studies identify accelerated biological aging as a mechanism that could explain how trauma and adversity gives rise to poor health, and advances in this area of study coincide with technological innovations in the measurement of biological aging, particularly epigenetic profiles consistent with accelerated aging derived from DNA methylation. In this review, we provide an overview of the current literature examining how adversity might accelerate biological aging, with a specific focus on social and health behaviors. The most extensive evidence in this area suggests that health-compromising behaviors, particularly smoking, may partially explain the association between adversity and accelerated aging. Although there is relatively less published support for the role of social behaviors, emerging evidence points to the importance of social connection as a mechanism for future study. Our review highlights the need to determine the extent to which the associations from adversity to accelerated aging are consistent with causal processes. As we consider these questions, the review emphasizes methodological approaches from the causal inference literature that can help deepen our understanding of how stress and trauma might result in poor health. The use of these methodologies will help provide evidence as to which behavioral interventions might slow aging and improve health, particularly among populations that more often experience adversity and trauma.

Five years of change in adult twins: longitudinal changes of genetic and environmental influence on epigenetic clocks

BACKGROUND

Epigenetic clocks were known as promising biomarkers of aging, including original clocks trained by individual CpG sites and principal component (PC) clocks trained by PCs of CpG sites. The effects of genetic and environmental factors on epigenetic clocks are still unclear, especially for PC clocks.

METHODS

We constructed univariate twin models in 477 same-sex twin pairs from the Chinese National Twin Registry (CNTR) to estimate the heritability of five epigenetic clocks (GrimAge, PhenoAge, DunedinPACE, PCGrimAge, and PCPhenoAge). Besides, we investigated the longitudinal changes of genetic and environmental influences on epigenetic clocks across 5 years in 134 same-sex twin pairs.

RESULTS

Heritability of epigenetic clocks ranged from 0.45 to 0.70, and those for PC clocks were higher than those for original clocks. For five epigenetic clocks, the longitudinal stability was moderate to high and was largely due to genetic effects. The genetic correlations between baseline and follow-up epigenetic clocks were moderate to high. Special unique environmental factors emerged both at baseline and at follow-up. PC clocks showed higher longitudinal stability and unique environmental correlations than original clocks.

CONCLUSIONS

For five epigenetic clocks, they have the potential to identify aging interventions. High longitudinal stability is mainly due to genetic factors, and changes of epigenetic clocks over time are primarily due to changes in unique environmental factors. Given the disparities in genetic and environmental factors as well as longitudinal stability between PC and original clocks, the results of studies with original clocks need to be further verified with PC clocks.

Work at high altitude and non-fatal cardiovascular disease associated with unfitness to work: Prospective cohort observation

INTRODUCTION

Mining at high altitude exposes workers to hypoxic environment and cold climate in addition to conventional hazards in mining, but very little is known on how to define fitness to work in prospective candidates with pre-existing conditions. The aim of the current study was to define the incidence of cardiovascular diseases leading to unfitness to work as well as their predictors in a prospective observation.

METHODS

A total of 569 prospective employees (median age 34 (interquartile range (IQR) 28;40) years, 95% men 85% mid-altitude residents) for a high-altitude gold mine in Kyrgyzstan operating at 3800-4500 meters above sea level were screened at pre-employment in 2009-2012 and followed by January 2022. Cox regression was used to quantify the association of baseline demographics and physiological variables with newly diagnosed cardiovascular diseases (CVD) leading to unfitness to work, expressed as hazard ratios (HRs) with 95% confidence intervals (CI).

RESULTS

With 5190 person-years of observation, 155 (27%) workers have left work, of whom 23 had a newly identified CVD leading to unfitness to work (cumulative incidence 4%) with no difference between drivers and other occupations, despite greater blood pressure and body mass index (BMI) in the former at baseline. Age (HR 1.13 (95% CI 1.06;1.22) and BMI (HR 1.18 (95% CI 1.04;1.34)) were associated with a greater chance of having CVD, adjusted for lung function, baseline diagnoses, year of employment and baseline blood pressure. Narrowing the analysis to only men, drivers, smokers and even middle-altitude residents did not change the effect.

CONCLUSION

These findings confirmed high efficacy of pre-employment screening limiting access of workers with advanced conditions to work which later yielded low CVD incidence. In addition to conventional contraindications to work at high altitude, age and high BMI should be considered when a decision is made.

Objective Assessments of Smoking and Drinking Outperform Clinical Phenotypes in Predicting Variance in Epigenetic Aging

The reliability of the associations of the acceleration of epigenetic aging (EA) indices with clinical phenotypes other than for smoking and drinking is poorly understood. Furthermore, the majority of clinical phenotyping studies have been conducted using data from subjects of European ancestry. In order to address these limitations, we conducted clinical, physiologic, and epigenetic assessments of a cohort of 278 middle-aged African American adults and analyzed the associations with the recently described principal-components-trained version of GrimAge (i.e., PC-GrimAge) and with the DunedinPACE (PACE) index using regression analyses. We found that 74% of PC-GrimAge accelerated aging could be predicted by a simple baseline model consisting of age, sex, and methylation-sensitive digital PCR (MSdPCR) assessments of smoking and drinking. The addition of other serological, demographic, and medical history variables or PACE values did not meaningfully improve the prediction, although some variables did significantly improve the model fit. In contrast, clinical variables mapping to cardiometabolic syndrome did independently contribute to the prediction of PACE values beyond the baseline model. The PACE values were poorly correlated with the GrimAge values (r = 0.2), with little overlap in variance explained other than that conveyed by smoking and drinking. The results suggest that EA indices may differ in the clinical information that they provide and may have significant limitations as screening tools to guide patient care.