Socioeconomic Position and DNA Methylation Age Acceleration Across the Life Course

Lifetime employment trajectories and cancer

Working life is associated with lifestyle, screening uptake, and occupational health risks that may explain differences in cancer onset. To better understand the association between working life and cancer risk, we need to account for the entire employment history. We investigated whether lifetime employment trajectories are associated with cancer risk. We used data from 6809 women and 5716 men, average age 70 years, from the Survey of Health, Ageing, and Retirement in Europe. Employment history from age 16 to 65 was collected retrospectively using a life calendar and trajectories were constructed using sequence analysis. Associations between employment trajectories and self-reported cancer were assessed using logistic regression. We identified eight employment trajectories for women and two for men. Among women, the risk of cancer was higher in the trajectories "Mainly full-time to home/family", "Full-time or home/family to part-time", "Mainly full-time", and "Other" compared with the "Mainly home/family" trajectory. Among men, the risk of cancer was lower in the "Mainly self-employment" trajectory compared with "Mainly full-time". We could show how employment trajectories were associated with cancer risk, underlining the potential of sequence analysis for life course epidemiology. More research is needed to understand these associations and determine if causal relationships exist.

The Impact of Early Life Adversity on Peripubertal Accelerated Epigenetic Aging and Psychopathology

OBJECTIVE

To examine longitudinal associations between early life threat and deprivation on epigenetic age acceleration at ages 9 and 15 years, and to examine associations of age acceleration on later internalizing and externalizing symptoms.

METHOD

The study examines a large (n = 2,039) and racially diverse (Black/African American = 44%, Latino = 18%, White = 5%) sample from a national dataset. Epigenetic age acceleration was estimated using the pediatric buccal epigenetic clock. Early life threat and deprivation were measured using composites from the Parent-Child Conflict Tactics Scale and county-level violent and property crime rate data. Internalizing and externalizing symptoms came from parent-reported Child Behavior Checklist. Path analysis models examined associations of threat and deprivation at age 3 years on epigenetic age acceleration at ages 9 and 15. Experiences of threat were further broken down into threat experienced in the home and in the community.

RESULTS

Home threat experienced at age 3 years predicted age acceleration at 9 and 15, and community threat experienced at 3 predicted age acceleration at 15, but not at 9. Deprivation was not a significant predictor of accelerated aging. Age acceleration at age 9 predicted externalizing, but not internalizing, symptoms at age 15. Community threat had a direct effect on externalizing. No association emerged with internalizing.

CONCLUSION

Findings revealed that threat, not deprivation, was predictive of age acceleration, demonstrating support for this pattern longitudinally, using an epigenetic clock that is accurate in children. The findings provide critical nuance to the examination of threat, and highlight associated risks and possible intervention points for externalizing symptoms.

Parental Divorce in Childhood and the Accelerated Epigenetic Aging for Earlier and Later Cohorts: Role of Mediators of Chronic Depressive Symptoms, Education, Smoking, Obesity, and Own Marital Disruption

We examine effects of parental divorce on epigenetic aging in later adulthood for two birth cohorts: one born in the early 20th century and the other born in the later 20th century. Using data from the Health and Retirement Study (n = 1,545), we examine the relationship between parental divorce in childhood and accelerated epigenetic aging in older adulthood as indicated by the Dunedin methylation Pace of Aging score. We assess how this relationship is mediated by chronic depressive symptoms, education, lifetime smoking, body mass index (BMI), and an older adult's own divorce. The mean age of the earlier cohort is 85.8 (SD = 3.9) and that of the later cohort is 60.2 (SD = 2.8). We find that parental divorce was related to faster aging in the later-born cohort, and that 56% of this relationship (b = 0.060) was mediated by chronic depressive symptoms (b = 0.013), lower education levels (b = 0.005), and smoking (b = 0.019). For the earlier cohort, there was no effect of parental divorce on epigenetic aging. Parental divorce in childhood may have lasting effects on later-life health, as reflected in the rate of epigenetic aging. However, the effects and mechanisms of this relationship differ across cohorts living in different social environments.

Cumulative Stress Across the Life Course and Biological Aging in Adulthood

OBJECTIVE

Psychosocial stressors have been linked with accelerated biological aging in adults; however, few studies have examined stressors across the life course in relation to biological aging.

METHODS

In 359 individuals (57% White, 34% Black) from the Child Health and Development Studies Disparities study, economic (income, education, financial strain), social (parent-child relations, caretaker responsibilities) and traumatic (death of a sibling or child, violence exposure) stressors were assessed at multiple time points (birth and ages 9, 15, and 50 years). Experiences of major discrimination were assessed at age 50. Life period stress scores were then assessed as childhood (birth-age 15 years) and adulthood (age 50 years). At age 50 years, participants provided blood samples, and DNA methylation was assessed with the EPIC BeadChip. Epigenetic age was estimated using six epigenetic clocks (Horvath, Hannum, Skin and Blood age, PhenoAge, GrimAge, Dunedin Pace of Aging). Age acceleration was determined using residuals from regressing chronologic age on each of the epigenetic age metrics. Telomere length was assessed using the quantitative polymerase chain reaction-based methods.

RESULTS

In linear regression models adjusted for race and gender, total life stress, and childhood and adult stress independently predicted accelerated aging based on GrimAge and faster pace of aging based on the DunedinPace. Associations were attenuated after adjusting for smoking status. In sex-stratified analyses, greater childhood stress was associated with accelerated epigenetic aging among women but not men. No associations were noted with telomere length.

CONCLUSIONS

We found that cumulative stressors across the life course were associated with accelerated epigenetic age, with differences by sex (e.g., accelerated among women). Further research of this association in large and diverse samples is needed.

Sex differences in biological aging and the association with clinical measures in older adults

Females live longer than males, and there are sex disparities in physical health and disease incidence. However, sex differences in biological aging have not been consistently reported and may differ depending on the measure used. This study aimed to determine the correlations between epigenetic age acceleration (AA), and other markers of biological aging, separately in males and females. We additionally explored the extent to which these AA measures differed according to socioeconomic characteristics, clinical markers, and diseases. Epigenetic clocks (HorvathAge, HannumAge, PhenoAge, GrimAge, GrimAge2, and DunedinPACE) were estimated in blood from 560 relatively healthy Australians aged ≥ 70 years (females, 50.7%) enrolled in the ASPREE study. A system-wide deficit accumulation frailty index (FI) composed of 67 health-related measures was generated. Brain age and subsequently brain-predicted age difference (brain-PAD) were estimated from neuroimaging. Females had significantly reduced AA than males, but higher FI, and there was no difference in brain-PAD. FI had the strongest correlation with DunedinPACE (range r: 0.21 to 0.24 in both sexes). Brain-PAD was not correlated with any biological aging measures. Significant correlations between AA and sociodemographic characteristics and health markers were more commonly found in females (e.g., for DunedinPACE and systolic blood pressure r = 0.2, p < 0.001) than in males. GrimAA and Grim2AA were significantly associated with obesity and depression in females, while in males, hypertension, diabetes, and chronic kidney disease were associated with these clocks, as well as DunedinPACE. Our findings highlight the importance of considering sex differences when investigating the link between biological age and clinical measures.

The Effect of the Earned Income Tax Credit on Physical and Mental health-Results from the Atlanta Paycheck Plus Experiment

Policy Points The Paycheck Plus randomized controlled trial tested a fourfold increase in the Earned Income Tax Credit (EITC) for single adults without dependent children over 3 years in New York and Atlanta. In New York, the intervention improved economic, mental, and physical health outcomes. In Atlanta, it had no economic benefit or impact on physical health and may have worsened mental health. In Atlanta, tax filing and bonus receipt were lower than in the New York arm of the trial, which may explain the lack of economic benefits. Lower mental health scores in the treatment group were driven by disadvantaged men, and the study sample was in good mental health.

CONTEXT

The Paycheck Plus experiment examined the effects of an enhanced Earned Income Tax Credit (EITC) for single adults on economic and health outcomes in Atlanta, GA and New York City (NYC). The NYC study was completed two years prior to the Atlanta study and found mental and physical benefits for the subgroups that responded best to the economic incentives provided. In this article, we present the findings from the Atlanta study, in which the uptake of the treatment (tax filings and EITC bonus) were lower and economic and health benefits were not observed.

METHODS

Paycheck Plus Atlanta was an unblinded randomized controlled trial that assigned n = 3,971 participants to either the standard federal EITC (control group) or an EITC supplement of up to $2,000 (treatment group) for three tax years (2017-2019). Administrative data on employment and earnings were obtained from the Georgia Department of Labor and survey data were used to examine validated measures of health and well-being.

FINDINGS

In Atlanta, the treatment group had significantly higher earnings in the first project year but did not have significantly higher cumulative earnings than the control group overall (mean difference = $1,812, 95% CI = -150, 3,774, p = 0.07). The treatment group also had significantly lower scores on two measures of mental health after the intervention was complete: the Patient Health Questionnaire 8 (mean difference = 0.19, 95% CI = 0.06, 0.32, p = 0.005) and the Kessler 6 (mean difference = 0.15, 95% CI = 0.03, 0.27, p = 0.012). Secondary analyses suggested these results were driven by disadvantaged men, but the study sample was in good mental health.

CONCLUSIONS

The EITC experiment in Atlanta was not associated with gains in earnings or improvements in physical or mental health.

Association of Neighborhood Deprivation and Depressive Symptoms With Epigenetic Age Acceleration: Evidence From the Canadian Longitudinal Study on Aging

BACKGROUND

Neighborhood deprivation and depression have been linked to epigenetic age acceleration. The next-generation epigenetic clocks including the DNA methylation (DNAm) GrimAge, and PhenoAge have incorporated clinical biomarkers of physiological dysregulation by selecting cytosine-phosphate-guanine sites that are associated with risk factors for disease, and have shown improved accuracy in predicting morbidity and time-to-mortality compared to the first-generation clocks. The aim of this study is to examine the association between neighborhood deprivation and DNAm GrimAge and PhenoAge acceleration in adults, and assess interaction with depressive symptoms.

METHODS

The Canadian Longitudinal Study on Aging recruited 51 338 participants aged 45-85 years across provinces in Canada. This cross-sectional analysis is based on a subsample of 1 445 participants at baseline (2011-2015) for whom epigenetic data were available. Epigenetic age acceleration (years) was assessed using the DNAm GrimAge and PhenoAge, and measured as residuals from regression of the biological age on chronological age.

RESULTS

A greater neighborhood material and/or social deprivation compared to lower deprivation (b = 0.66; 95% confidence interval [CI] = 0.21, 1.12) and depressive symptoms scores (b = 0.07; 95% CI = 0.01, 0.13) were associated with higher DNAm GrimAge acceleration. The regression estimates for these associations were higher but not statistically significant when epigenetic age acceleration was estimated using DNAm PhenoAge. There was no evidence of a statistical interaction between neighborhood deprivation and depressive symptoms.

CONCLUSIONS

Depressive symptoms and neighborhood deprivation are independently associated with premature biological aging. Policies that improve neighborhood environments and address depression in older age may contribute to healthy aging among older adults living in predominantly urban areas.

Are housing circumstances associated with faster epigenetic ageing?

BACKGROUND

Numerous aspects of housing are associated with health. However, the pathways between housing and health, particularly the psychosocial elements of housing, are less well understood. Epigenetic information alongside social survey data offers an opportunity to explore biological ageing, measured using DNA methylation, as a potential pathway through which housing affects health.

METHODS

We use data on housing and DNA methylation from the UK Household Longitudinal Study, linked with prior survey responses from the British Household Panel Survey, covering adults in Great Britain. We explore the association between epigenetic ageing and housing circumstances, both contemporary and historical, using hierarchical regression.

RESULTS

We find that living in a privately rented home is related to faster biological ageing. Importantly, the impact of private renting (coefficient (SE) 0.046 years (0.011) vs owned outright, p<0.001) is greater than the impact of experiencing unemployment (coefficient 0.027 years (0.012) vs employed, p<0.05) or being a former smoker (coefficient 0.021 years (0.005) vs never smoker, p<0.001). When we include historical housing circumstances in the analysis, we find that repeated housing arrears and exposure to pollution/environmental problems are also associated with faster biological ageing.

CONCLUSION

Our results suggest that challenging housing circumstances negatively affect health through faster biological ageing. However, biological ageing is reversible, highlighting the significant potential for housing policy changes to improve health.

Occupational characteristics and epigenetic aging among older adults in the United States

Occupational characteristics have been studied as risk factors for several age-related diseases and are thought to impact the ageing process, although there has been limited empirical work demonstrating an association between adverse occupational characteristics and accelerated ageing and this prior work has yielded mixed results. We used the 2010 and 2016 waves of the Health and Retirement Study (n = 1,251) to examine the association between occupation categories and self-reported working conditions of American adults at midlife and their subsequent epigenetic ageing as measured through five epigenetic clocks: PCHorvath, PCHannum, PCPhenoAge, PCGrimAge, and DunedinPACE. We found that individuals working in sales/clerical, service, and manual work show evidence of epigenetic age acceleration compared to those working in managerial/professional jobs and that the associations were stronger with second- and third-generation clocks. Individuals reporting high stress and high physical effort at work showed evidence of epigenetic age acceleration only on PCGrimAge and DunedinPACE. Most of these associations were attenuated after adjustment for race/ethnicity, educational attainment, and lifestyle-related risk factors. Sales/clerical work remained significantly associated with PCHorvath and PCHannum, while service work remained significantly associated with PCGrimAge. The results suggest that manual work and occupational physical activity may appear to be risk factors for epigenetic age acceleration through their associations with socioeconomic status, while stress at work may be a risk factor for epigenetic age acceleration through its associations with health behaviours outside of work. Additional work is needed to understand when in the life course and the specific mechanisms through which these associations occur.

Partnership status and positive DNA methylation age acceleration across the adult lifespan in the UK

Although a significant body of research has shown that married people are healthier and live longer, empirical research on sex differences in the link between marital status and health suggests results are mixed. Moreover, the sex disparities in marital status and health relationships vary across adulthood. The literature on partnership status and measures of ageing is largely focused on older age groups and is limited in its view of early adulthood. Data from waves 2 and 3 (2010-2012) of Understanding Society: UKHLS were used to examine the association of current partnership status with epigenetic age acceleration (AA) assessed with DNA methylation (DNAm) algorithms 'Phenoage' and ' DunedinPACE ' in 3492 participants (aged 16-97). Regression models were estimated separately for men and women, and further stratified by age groups. Divorced/separated and widowed people showed positive age acceleration compared to the married/cohabiting people (reference group). Some sex differences were apparent, especially, among the single and divorced/separated groups. Age differences were also apparent, for example in men, being single was negatively associated with DNAmAA in the youngest group, but positively in the oldest group compared to partnered counterparts. These findings illustrate the importance of partnerships on the ageing process, in particular marital change through divorce and widowhood for positive age acceleration in adults. For single groups, observations were heterogenous by age and sex.

Next Generation, Modifiable Cardiometabolic Biomarkers: Mitochondrial Adaptation and Metabolic Resilience: A Scientific Statement From the American Heart Association

Cardiometabolic risk is increasing in prevalence across the life span with disproportionate ramifications for youth at socioeconomic disadvantage. Established risk factors and associated disease progression are harder to reverse as they become entrenched over time; if current trends are unchecked, the consequences for individual and societal wellness will become untenable. Interrelated root causes of ectopic adiposity and insulin resistance are understood but identified late in the trajectory of systemic metabolic dysregulation when traditional cardiometabolic risk factors cross current diagnostic thresholds of disease. Thus, children at cardiometabolic risk are often exposed to suboptimal metabolism over years before they present with clinical symptoms, at which point life-long reliance on pharmacotherapy may only mitigate but not reverse the risk. Leading-edge indicators are needed to detect the earliest departure from healthy metabolism, so that targeted, primordial, and primary prevention of cardiometabolic risk is possible. Better understanding of biomarkers that reflect the earliest transitions to dysmetabolism, beginning in utero, ideally biomarkers that are also mechanistic/causal and modifiable, is critically needed. This scientific statement explores emerging biomarkers of cardiometabolic risk across rapidly evolving and interrelated "omic" fields of research (the epigenome, microbiome, metabolome, lipidome, and inflammasome). Connections in each domain to mitochondrial function are identified that may mediate the favorable responses of each of the omic biomarkers featured to a heart-healthy lifestyle, notably to nutritional interventions. Fuller implementation of evidence-based nutrition must address environmental and socioeconomic disparities that can either facilitate or impede response to therapy.

Associations of Early-Life Adversity With Later-Life Epigenetic Aging Profiles in the Multi-Ethnic Study of Atherosclerosis

Epigenetic biomarkers of accelerated aging have been widely used to predict disease risk and may enhance our understanding of biological mechanisms between early-life adversity and disparities in aging. With respect to childhood adversity, most studies have used parental education or childhood disadvantage and/or have not examined the role played by socioemotional or physical abuse and trauma in epigenetic profiles at older ages. This study leveraged data from the Multi-Ethnic Study of Atherosclerosis (MESA) on experiences of threat and deprivation in participants' early lives (i.e., before the age of 18 years) to examine whether exposure to specific dimensions of early-life adversity is associated with epigenetic profiles at older ages that are indicative of accelerated biological aging. The sample included 842 MESA respondents with DNA methylation data collected between 2010 and 2012 who answered questions on early-life adversities in a 2018-2019 telephone follow-up. We found that experiences of deprivation, but not threat, were associated with later-life GrimAge epigenetic aging signatures that were developed to predict mortality risk. Results indicated that smoking behavior partially mediates this association, which suggests that lifestyle behaviors may act as downstream mechanisms between parental deprivation in early life and accelerated epigenetic aging in later life.

Using Epigenetic Clocks to Characterize Biological Aging in Studies of Children and Childhood Exposures: a Systematic Review

Biological age, measured via epigenetic clocks, offers a unique and useful tool for prevention scientists to explore the short- and long-term implications of age deviations for health, development, and behavior. The use of epigenetic clocks in pediatric research is rapidly increasing, and there is a need to review the landscape of this work to understand the utility of these clocks for prevention scientists. We summarize the current state of the literature on the use of specific epigenetic clocks in childhood. Using systematic review methods, we identified studies published through February 2023 that used one of three epigenetic clocks as a measure of biological aging. These epigenetic clocks could either be used as a predictor of health outcomes or as a health outcome of interest. The database search identified 982 records, 908 of which were included in a title and abstract review. After full-text screening, 68 studies were eligible for inclusion. While findings were somewhat mixed, a majority of included studies found significant associations between the epigenetic clock used and the health outcome of interest or between an exposure and the epigenetic clock used. From these results, we propose the use of epigenetic clocks as a tool to understand how exposures impact biologic aging pathways and development in early life, as well as to monitor the effectiveness of preventive interventions that aim to reduce exposure and associated adverse health outcomes.

Parental education and epigenetic aging in middle-aged and older adults in the United States: A life course perspective

Epigenetic aging is one plausible mechanism by which socioeconomic status (SES) contributes to disparities in morbidity and mortality. Although the association between SES and epigenetic aging is well documented, the role of parental education into adulthood remains understudied. We examined (1) if parental education was independently associated with epigenetic aging, (2) whether upward educational mobility buffered this association, and (3) if the benefit of parental education was differentiated by race/ethnicity. Secondary data analysis of a subsample (n = 3875) of Non-Hispanic [NH] Black, Hispanic, NH White, and NH other race participants from the Venous Blood Study within Health and Retirement Study were examined. Thirteen clocks based on DNA methylation of cytosine-phosphate-guanine sites were used to calculate epigenetic aging. Participants' education (personal) and their report of their respective parent's education (parental; mother's and/or father's) were included as independent variables; several potential confounders were also included. Direct associations and interactions between parental and personal education were estimated via survey-weighted generalized linear models; marginal means for epigenetic aging were estimated and contrasts were made between the education subcategories. Analyses were also stratified by race/ethnicity. Our results showed that higher parental education was independently associated with slower epigenetic aging among four clocks, whereas higher personal education magnified this association among four different epigenetic clocks. Participants with the lowest parental and personal education had higher marginal means (i.e., accelerated aging) compared to participants with the highest parental and personal education, and there was little evidence of upward mobility. These associations were more frequently observed among NH White participants, whereas fewer were observed for Hispanic and NH Black participants. Overall, our findings support that early-life circumstances may be biologically embedded through epigenetic aging, which may also limit the biological benefits associated with one's own education.

Epigenetic age acceleration mediates the relationship between neighborhood deprivation and pain severity in adults with or at risk for knee osteoarthritis pain

An estimated 250 million people worldwide suffer from knee osteoarthritis (KOA), with older adults having greater risk. Like other age-related diseases, residents of high-deprivation neighborhoods experience worse KOA pain outcomes compared to their more affluent neighbors. The purpose of this study was to examine the relationship between neighborhood deprivation and pain severity in KOA and the influence of epigenetic age acceleration (EpAA) on that relationship. The sample of 128 participants was mostly female (60.9%), approximately half non-Hispanic Black (49.2%), and had a mean age of 58 years. Spearman bivariate correlations revealed that pain severity positively correlated with EpAA (ρ = 0.47, p ≤ 0.001) and neighborhood deprivation (ρ = 0.25, p = 0.004). We found a positive significant relationship between neighborhood deprivation and EpAA (ρ = 0.47, p ≤ 0.001). Results indicate a mediating relationship between neighborhood deprivation (predictor), EpAA (mediator), and pain severity (outcome variable). There was a significant indirect effect of neighborhood deprivation on pain severity through EpAA, as the mediator accounted for a moderate portion of the total effect, PM = 0.44. Epigenetic age acceleration may act as a mechanism through which neighborhood deprivation leads to worse KOA pain outcomes and may play a role in the well-documented relationship between the neighborhood of residence and age-related diseases.

Epigenetic clocks and research implications of the lack of data on whom they have been developed: a review of reported and missing sociodemographic characteristics

Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population.

Psychological Stress and Epigenetic Aging in Older Men: The VA Normative Aging Study

Psychological stress remains an important risk factor for morbidity and mortality throughout the life course. However, there have been counterintuitive findings reported in previous studies of older persons that examine the relationships of perceived psychological stress with DNA methylation-based markers of aging, which also serve as predictors of morbidity and mortality (epigenetic age/clocks). We aimed to replicate and expand findings from existing work by examining relationships of self-reported stress with nine epigenetic clocks: Hannum, Horvath, Intrinsic, Extrinsic, SkinBloodClock, PhenoAge, GrimAge, DNAm Telomere Length, and Pace of Aging. We analyzed data from 607 male participants (mean age 73.2 years) of the VA Normative Aging Study with one to two study visits from 1999 to 2007 (observations = 956). Stress was assessed via the 14-item Perceived Stress Scale (PSS). Epigenetic age was calculated from DNA methylation measured in leukocytes with the HumanMethylation450 BeadChip. In linear mixed effects models adjusted for demographic/lifestyle/health factors, a standard deviation (sd) increase in PSS was associated with Horvath (β = -0.35-years, 95%CI: -0.61, -0.09, P=0.008) and Intrinsic (β = -0.40-years, 95%CI: -0.67, -0.13, P=0.004) epigenetic age deceleration. However, in models limited to participants with the highest levels of stress (≥ 75th-percentile), Horvath (β = 2.29-years, 95%CI: 0.16, 4.41, P=0.04) and Intrinsic (β = 2.06-years, 95%CI: -0.17, 4.28, P=0.07) age acceleration associations were observed. Our results reinforce the complexity of psychological stress and epigenetic aging relationships and lay a foundation for future studies that explore longitudinal relationships with other adult stress metrics and factors that can influence stress such as resilience measures.

DNA methylation age at birth and childhood: performance of epigenetic clocks and characteristics associated with epigenetic age acceleration in the Project Viva cohort

BACKGROUND

Epigenetic age acceleration (EAA) and epigenetic gestational age acceleration (EGAA) are biomarkers of physiological development and may be affected by the perinatal environment. The aim of this study was to evaluate performance of epigenetic clocks and to identify biological and sociodemographic correlates of EGAA and EAA at birth and in childhood. In the Project Viva pre-birth cohort, DNA methylation was measured in nucleated cells in cord blood (leukocytes and nucleated red blood cells, N = 485) and leukocytes in early (N = 120, median age = 3.2 years) and mid-childhood (N = 460, median age = 7.7 years). We calculated epigenetic gestational age (EGA; Bohlin and Knight clocks) and epigenetic age (EA; Horvath and skin & blood clocks), and respective measures of EGAA and EAA. We evaluated the performance of clocks relative to chronological age using correlations and median absolute error. We tested for associations of maternal-child characteristics with EGAA and EAA using mutually adjusted linear models controlling for estimated cell type proportions. We also tested associations of Horvath EA at birth with childhood EAA.

RESULTS

Bohlin EGA was strongly correlated with chronological gestational age (Bohlin EGA r = 0.82, p < 0.001). Horvath and skin & blood EA were weakly correlated with gestational age, but moderately correlated with chronological age in childhood (r = 0.45-0.65). Maternal smoking during pregnancy was associated with higher skin & blood EAA at birth [B (95% CI) = 1.17 weeks (- 0.09, 2.42)] and in early childhood [0.34 years (0.03, 0.64)]. Female newborns and children had lower Bohlin EGAA [- 0.17 weeks (- 0.30, - 0.04)] and Horvath EAA at birth [B (95% CI) = - 2.88 weeks (- 4.41, - 1.35)] and in childhood [early childhood: - 0.3 years (- 0.60, 0.01); mid-childhood: - 0.48 years (- 0.77, - 0.18)] than males. When comparing self-reported Asian, Black, Hispanic, and more than one race or other racial/ethnic groups to White, we identified significant differences in EGAA and EAA at birth and in mid-childhood, but associations varied across clocks. Horvath EA at birth was positively associated with childhood Horvath and skin & blood EAA.

CONCLUSIONS

Maternal smoking during pregnancy and child sex were associated with EGAA and EAA at multiple timepoints. Further research may provide insight into the relationship between perinatal factors, pediatric epigenetic aging, and health and development across the lifespan.

Integrative Approaches of DNA Methylation Patterns According to Age, Sex and Longitudinal Changes

Background

In humans, age-related DNA methylation has been studied in blood, tissues, buccal swabs, and fibroblasts, and changes in DNA methylation patterns according to age and sex have been detected. To date, approximately 137,000 samples have been analyzed from 14,000 studies, and the information has been uploaded to the NCBI GEO database.

Methods

A correlation between age and methylation level and longitudinal changes in methylation levels was revealed in both sexes. Here, 20 public datasets derived from whole blood were analyzed using the Illumina BeadChip. Batch effects with respect to the time differences were correlated. The overall change in the pattern was provided as the inverse of the coefficient of variation (COV).

Results

Of the 20 datasets, nine were from a longitudinal study. All data had age and sex as common variables. Comprehensive details of age-, sex-, and longitudinal change-based DNA methylation levels in the whole blood sample were elucidated in this study. ELOVL2 and FHL2 showed the maximum correlation between age and DNA methylation. The methylation patterns of genes related to mental health differed according to age. Age-correlated genes have been associated with malformations (anteverted nostril, craniofacial abnormalities, and depressed nasal bridge) and drug addiction (drug habituation and smoking).

Conclusion

Based on 20 public DNA methylation datasets, methylation levels according to age and longitudinal changes by sex were identified and visualized using an integrated approach. The results highlight the molecular mechanisms underlying the association of sex and biological age with changes in DNA methylation, and the importance of optimal genomic information management.

Social mobility across the lifecourse and DNA methylation age acceleration in adults in the UK

Disadvantaged socio-economic position (SEP) is associated with greater biological age, relative to chronological age, measured by DNA methylation (positive 'age acceleration', AA). Social mobility has been proposed to ameliorate health inequalities. This study aimed to understand the association of social mobility with positive AA. Diagonal reference modelling and ordinary least square regression techniques were applied to explore social mobility and four measures of age acceleration (first-generation: 'Horvath', 'Hannum' and second-generation: 'Phenoage', DunedinPoAm) in n = 3140 participants of the UK Household Longitudinal Study. Disadvantaged SEP in early life is associated with positive AA for three (Hannum, Phenoage and DunedinPoAm) of the four measures examined while the second generation biomarkers are associated with SEP in adulthood (p < 0.01). Social mobility was associated with AA measured with Hannum only such that compared to no mobility, upward mobility was associated with greater age independently of origin and destination SEP. Compared to continuously advantaged groups, downward mobility was associated with positive Phenoage (1.06y [- 0.03, 2.14]) and DunedinPoAm assessed AA (0.96y [0.24, 1.68]). For these two measures, upward mobility was associated with negative AA (Phenoage, - 0.65y [- 1.30, - 0.002]; DunedinPoAm, - 0.96y [- 1.47, - 0.46]) compared to continually disadvantaged groups. While we find some support for three models of lifecourse epidemiology with early life as a sensitive period, SEP across the lifecourse and social mobility for age acceleration measured with DNA methylation, our findings suggest that disadvantaged SEP across the lifecourse is most consistently associated with positive AA.

Exploring the relationship between DNA methylation age measures and psychoneurological symptoms in women with early-stage breast cancer

PURPOSE

The epigenetic clock has been acknowledged as an indicator for molecular aging, but few studies have examined possible associations of DNA methylation (DNAm) age or age acceleration (AA) with symptom burden in individuals who are treated for cancer. This study explored the association of DNAm age or AA with psychoneurological (PN) symptoms, including cognitive impairment, fatigue, sleep disturbances, pain, and depressive symptoms, in breast cancer survivors over a 2-year period.

METHODS

We measured PN symptoms using reliable instruments and DNAm levels by Infinium HumanMethylation450K BeadChip (N = 72). DNAm age was calculated by the Horvath, Grim, and Hannum-based intrinsic and extrinsic age estimations. AA was defined by the residual regressing estimated epigenetic age on chronological age. Mixed regression models were fitted for AA and changes in AA to study the association over time. Separate linear regression models and a mixed-effects model were fitted for AA at each time point.

RESULTS

Horvath-AA, Grim-AA, and extrinsic epigenetic AA were significantly changed over time, while intrinsic epigenetic AA did not exhibit any temporal changes. Increased AA was associated with greater anxiety and fatigue, as well as worse cognitive memory, adjusting for race, BMI, income, chemotherapy, radiation therapy, and chronological age. Increased DNAm age was associated with greater anxiety over 2 years.

CONCLUSION

Our findings suggest DNAm age and AA may be associated with PN symptoms over the course of cancer treatment and survivorship. Some PN symptoms may be amenable to preventive interventions targeted to epigenetic clocks that influence aging-associated processes.

Pace of aging, family environment and cognitive skills in children and adolescents

Pace of aging is an epigenetic clock which captures the speed at which someone is biologically aging compared to the chronological-age peers. We here use data from the Avon Longitudinal Study of Parents and Children (ALSPAC) to investigate the interrelation between the study children's parental social class at birth, and their pace of aging and cognitive skills measures in childhood and adolescence. We show that children from lower parental social classes display faster pace of aging and that the social class gradient in pace of aging is strongest in adolescence. About one third of this association can be explained by other socio-economic and demographic covariates, as well as life events. Similarly, study children's pace of aging manifests a negative association with their measures of cognitive skills in late adolescence only. This association becomes stronger as the contemporary pace of aging of the mother becomes faster. Our results seem to identify adolescence as the period of life when pace of aging, family environment and cognitive skills measures begin to interact.

Association between work characteristics and epigenetic age acceleration: cross-sectional results from UK - Understanding Society study

Occupation-related stress and work characteristics are possible determinants of social inequalities in epigenetic aging but have been little investigated. Here, we investigate the association of several work characteristics with epigenetic age acceleration (AA) biomarkers. The study population included employed and unemployed men and women (n = 631) from the UK Understanding Society study. We evaluated the association of employment and work characteristics related to job type, job stability; job schedule; autonomy and influence at work; occupational physical activity; and feelings regarding the job with four epigenetic age acceleration biomarkers (Hannum, Horvath, PhenoAge, GrimAge) and pace of aging (DunedinPoAm, DunedinPACE). We fitted linear regression models, unadjusted and adjusted for established risk factors, and found the following associations for unemployment (years of acceleration): HorvathAA (1.51, 95% CI 0.08, 2.95), GrimAgeAA (1.53, 95% CI 0.16, 2.90) and 3.21 years for PhenoAA (95% CI 0.89, 5.33). Job insecurity increased PhenoAA (1.83, 95% CI 0.003, 3.67), while working at night was associated with an increase of 2.12 years in GrimAgeAA (95% CI 0.69, 3.55). We found effects of unemployment to be stronger in men and effects of night shift work to be stronger in women. These results provide evidence of associations between unemployment with accelerated ageing and suggest that insecure employment and night work may also increase age acceleration. Our findings have implications for policies relating to current changes in working conditions and highlight the utility of biological age biomarkers in studies in younger populations without long-term health information.

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.

Sex-specific and generational effects of alcohol and tobacco use on epigenetic age acceleration in the Michigan longitudinal study

Background:

Methods:

Results:

Conclusions:

Association of subjective social status with epigenetic aging among Black and White women

OBJECTIVE

Subjective social status (SSS), an individual's assessment of their own social status in relation to others, is associated with health and mortality independently of objective SES; however, no studies have tested whether SSS influences epigenetic aging. The current study examines if SSS is associated with epigenetic age acceleration in both Black and White women, independently of objective SES measured during both childhood and adulthood.

METHOD

For 9- and 10-year-old Black and White girls, parental education and annual household income was obtained. At ages 39-42, 361 participants (175 Black, 186 White) reported their current education, household income, and SSS, and provided saliva to assess age acceleration using the GrimAge epigenetic clock. Linear regression estimated the association of SSS with epigenetic age acceleration, controlling for objective SES (current education, current income, parents' education, income during childhood), smoking, and counts of cell types.

RESULTS

When all objective SES variables were included in the model, SSS remained significantly associated with epigenetic age acceleration, b = - 0.31, p = .003, ß = - 0.15. Black women had significantly greater age acceleration than White women, (t(359) = 5.20, p > .001, d = 0.55) but race did not moderate the association between SSS and epigenetic age acceleration.

CONCLUSIONS

Women who rated themselves lower in SSS had greater epigenetic age acceleration, regardless of income and education. There was no difference by race for this association.

Counteracting aged DNA methylation states to combat ageing and age-related diseases

DNA methylation (DNAm) overwrites information about multiple extrinsic factors on the genome. Age is one of these factors. Age causes characteristic DNAm changes that are thought to be not only major drivers of normal ageing but also precursors to diseases, cancer being one of these. Although there is still much to learn about the relationship between ageing, age-related diseases and DNAm, we now know how to interpret some of the effects caused by age in the form of changes in methylation marks at specific loci. In fact, these changes form the basis of the so called "epigenetic clocks", which translate the genomic methylation profile into an "epigenetic age". Epigenetic age does not only estimate chronological age but can also predict the risk of chronic diseases and mortality. Epigenetic age is believed to be one of the most accurate metrics of biological age. Initial evidence has recently been gathered pointing to the possibility that the rate of epigenetic ageing can be slowed down or even reversed. In this review, we discuss some of the most relevant advances in this field. Expected outcome is that this approach can provide insights into how to preserve health and reduce the impact of ageing diseases in humans.

The Socioeconomic Gradient in Epigenetic Ageing Clocks: Evidence from the Multi-Ethnic Study of Atherosclerosis and the Health and Retirement Study

Epigenetic clocks have been widely used to predict disease risk in multiple tissues or cells. Their success as a measure of biological ageing has prompted research on the connection between epigenetic pathways of ageing and the socioeconomic gradient in health and mortality. However, studies examining social correlates of epigenetic ageing have yielded inconsistent results. We conducted a comprehensive, comparative analysis of associations between various dimensions of socioeconomic status (SES) (education, income, wealth, occupation, neighbourhood environment, and childhood SES) and eight epigenetic clocks in two well-powered US ageing studies: The Multi-Ethnic Study of Atherosclerosis (MESA) (n = 1,211) and the Health and Retirement Study (HRS) (n = 4,018). In both studies, we found robust associations between SES measures in adulthood and the GrimAge and DunedinPoAm clocks (Bonferroni-corrected p-value < 0.01). In the HRS, significant associations with the Levine and Yang clocks were also evident. These associations were only partially mediated by smoking, alcohol consumption, and obesity, which suggests that differences in health behaviours alone cannot explain the SES gradient in epigenetic ageing in older adults. Further analyses revealed concurrent associations between polygenic risk for accelerated intrinsic epigenetic ageing, SES, and the Levine clock, indicating that genetic risk and social disadvantage may contribute additively to faster biological aging.

Characterising sex differences of autosomal DNA methylation in whole blood using the Illumina EPIC array

BACKGROUND

Sex differences are known to play a role in disease aetiology, progression and outcome. Previous studies have revealed autosomal epigenetic differences between males and females in some tissues, including differences in DNA methylation patterns. Here, we report for the first time an analysis of autosomal sex differences in DNAme using the Illumina EPIC array in human whole blood by performing a discovery (n = 1171) and validation (n = 2471) analysis.

RESULTS

We identified and validated 396 sex-associated differentially methylated CpG sites (saDMPs) with the majority found to be female-biased CpGs (74%). These saDMP's are enriched in CpG islands and CpG shores and located preferentially at 5'UTRs, 3'UTRs and enhancers. Additionally, we identified 266 significant sex-associated differentially methylated regions overlapping genes, which have previously been shown to exhibit epigenetic sex differences, and novel genes. Transcription factor binding site enrichment revealed enrichment of transcription factors related to critical developmental processes and sex determination such as SRY and ESR1.

CONCLUSION

Our study reports a reliable catalogue of sex-associated CpG sites and elucidates several characteristics of these sites using large-scale discovery and validation data sets. This resource will benefit future studies aiming to investigate sex specific epigenetic signatures and further our understanding of the role of DNA methylation in sex differences in human whole blood.

Social mobility and biological aging among older adults in the United States

Lower socioeconomic status is associated with faster biological aging, the gradual and progressive decline in system integrity that accumulates with advancing age. Efforts to promote upward social mobility may, therefore, extend healthy lifespan. However, recent studies suggest that upward mobility may also have biological costs related to the stresses of crossing social boundaries. We tested associations of life-course social mobility with biological aging using data from participants in the 2016 Health and Retirement Study (HRS) Venous Blood Study who provided blood-chemistry (n = 9,255) and/or DNA methylation (DNAm) data (n = 3,976). We quantified social mobility from childhood to later-life using data on childhood family characteristics, educational attainment, and wealth accumulation. We quantified biological aging using 3 DNAm "clocks" and 3 blood-chemistry algorithms. We observed substantial social mobility among study participants. Those who achieved upward mobility exhibited less-advanced and slower biological aging. Associations of upward mobility with less-advanced and slower aging were consistent for blood-chemistry and DNAm measures of biological aging, and were similar for men and women and for Black and White Americans (Pearson-r effect-sizes ∼0.2 for blood-chemistry measures and the DNAm GrimAge clock and DunedinPoAm pace-of-aging measures; effect-sizes were smaller for the DNAm PhenoAge clock). Analysis restricted to educational mobility suggested differential effects by racial identity; mediating links between educational mobility and healthy aging may be disrupted by structural racism. In contrast, mobility producing accumulation of wealth appeared to benefit White and Black Americans equally, suggesting economic intervention to reduce wealth inequality may have potential to heal disparities in healthy aging.

Understanding Health Inequalities Through the Lens of Social Epigenetics

Longstanding racial/ethnic inequalities in morbidity and mortality persist in the United States. Although the determinants of health inequalities are complex, social and structural factors produced by inequitable and racialized systems are recognized as contributing sources. Social epigenetics is an emerging area of research that aims to uncover biological pathways through which social experiences affect health outcomes. A growing body of literature links adverse social exposures to epigenetic mechanisms, namely DNA methylation, offering a plausible pathway through which health inequalities may arise. This review provides an overview of social epigenetics and highlights existing literature linking social exposures-i.e., psychosocial stressors, racism, discrimination, socioeconomic position, and neighborhood social environment-to DNA methylation in humans. We conclude with a discussion of social epigenetics as a mechanistic link to health inequalities and provide suggestions for future social epigenetics research on health inequalities.

Work-related stress and well-being in association with epigenetic age acceleration: A Northern Finland Birth Cohort 1966 Study

Recent evidence indicates consistent association of low socioeconomic status with epigenetic age acceleration, measured from DNA methylation. As work characteristics and job stressors are crucial components of socioeconomic status, we investigated their association with various measures of epigenetic age acceleration. The study population included employed and unemployed men and women (n=604) from the Northern Finland Birth Cohort 1966. We investigated the association of job strain, effort-reward imbalance and work characteristics with five biomarkers of epigenetic aging (Hannum, Horvath, PhenoAge, GrimAge, and DunedinPoAm). Our results indicate few significant associations between work stress indicators and epigenetic age acceleration, limited to a range of ±2 years, and smoking recording the highest effect on GrimAge age acceleration biomarker between current and no smokers (median difference 4.73 years (IQR 1.18, 8.41). PhenoAgeAA was associated with job strain active work (β=-1.301 95%CI -2.391, -0.212), slowing aging of less than 1.5 years, and working as white-collar slowed aging six months (GrimAgeAA β=-0.683, 95%CI -1.264, -0.102) when compared to blue collars. Association was found for working for more than 40 hours per week that increased the aging over 1.5 years, (HorvathAA β =2.058 95%CI 0.517,3.599, HannumAA β=1.567, 95%CI 0.415,2.719). The pattern of associations was different between women and men and some of the estimated effects are inconsistent with current literature. Our results provide the first evidence of association of work conditions with epigenetic aging biomarkers. However, further epidemiological research is needed to fully understand how work-related stress affects epigenetic age acceleration in men and women in different societies.

Neighborhood structural disadvantage and biological aging in a sample of Black middle age and young adults

OBJECTIVES

Research on the social determinants of health has suggested that neighborhood disadvantage may undermine healthy aging and is particularly relevant for understanding health disparities. Recently, this work has examined deoxyribonucleic acid methylation (DNAm)-based measures of biological aging to understand the risk factors for morbidity and mortality. However, it is unknown whether neighborhood disadvantage is related to different indices of DNAm-based aging among Black Americans and whether such neighborhood effects vary as a function of age or gender.

METHODS

Our analyses of a Black American sample included 448 young adults and 493 middle-aged adults. We measured neighborhood disadvantage using the Area Deprivation Index at the census block group level. DNAm-based accelerated aging indices were measured using established procedures. Regressions with clustered standard errors were used for the analysis.

RESULTS

Neighborhood disadvantage was independently associated with acceleration in PhenoAge, GrimAge, and DunedinPoAm, among young and middle-aged adults. Further, there was no evidence that gender conditioned the effects of neighborhood disadvantage on the aging indices.

CONCLUSIONS

Regardless of age groups or gender, accelerated biological aging among Black Americans is partly rooted in differences in neighborhood disadvantage. From a policy standpoint, our findings suggest that programs that decrease neighborhood disadvantage are likely to increase healthy aging, especially among Black Americans.

Combining current knowledge on DNA methylation-based age estimation towards the development of a superior forensic DNA intelligence tool

The estimation of chronological age from biological fluids has been an important quest for forensic scientists worldwide, with recent approaches exploiting the variability of DNA methylation patterns with age in order to develop the next generation of forensic 'DNA intelligence' tools for this application. Drawing from the conclusions of previous work utilising massively parallel sequencing (MPS) for this analysis, this work introduces a DNA methylation-based age estimation method for blood that exhibits the best combination of prediction accuracy and sensitivity reported to date. Statistical evaluation of markers from 51 studies using microarray data from over 4000 individuals, followed by validation using in-house generated MPS data, revealed a final set of 11 markers with the greatest potential for accurate age estimation from minimal DNA material. Utilising an algorithm based on support vector machines, the proposed model achieved an average error (MAE) of 3.3 years, with this level of accuracy retained down to 5 ng of starting DNA input (~ 1 ng PCR input). The accuracy of the model was retained (MAE = 3.8 years) in a separate test set of 88 samples of Spanish origin, while predictions for donors of greater forensic interest (< 55 years of age) displayed even higher accuracy (MAE = 2.6 years). Finally, no sex-related bias was observed for this model, while there were also no signs of variation observed between control and disease-associated populations for schizophrenia, rheumatoid arthritis, frontal temporal dementia and progressive supranuclear palsy in microarray data relating to the 11 markers.

Reduction in Epigenetic Age Acceleration Is Related to Empathy in Mothers with Neglectful Caregiving

DNA methylation clocks are used as molecular estimators of epigenetic age, but with little evidence in mothers and none in neglectful mothering. We investigated differences in epigenetic age acceleration (EAA) and the role of empathy using the PhenoAge clock. We collected saliva samples from mothers with extreme disregard for their child's needs (50 in the neglect group, NG) and mothers with non-neglectful caregiving (87 in the control group, CG). Mothers completed an empathy scale, along with questionnaires of their own childhood maltreatment, adverse life events and psychiatric disorders. Sociodemographic variables potentially affecting EAA were also measured. The ANCOVA solution showed a significant increase in EAA in the NG compared to the CG, after adjustment for maternal age, number of pregnancies, financial assistance, adverse events, childhood maltreatment and psychiatric disorder. The group interaction effects showed a reduction in EAA for greater empathic concern and for a higher education level both as positive factors, and an increment in EAA for mothers living in a two-parent family as a risk factor, all in the NG. Our findings open the search for protective factors of EAA associated with caregiver behavior to reduce health vulnerabilities and poor social functioning, especially for mothers at risk of maladaptive caregiving.

Impact of paternal education on epigenetic ageing in adolescence and mid-adulthood: a multi-cohort study in the USA and Mexico

BACKGROUND

Both parental and neighbourhood socio-economic status (SES) are linked to poorer health independently of personal SES measures, but the biological mechanisms are unclear. Our objective was to examine these influences via epigenetic age acceleration (EAA)-the discrepancy between chronological and epigenetic ages.

METHODS

We examined three USA-based [Coronary Artery Risk Disease in Adults (CARDIA) study, Fragile Families and Child Wellbeing Study (FFCWS) and Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS)] and one Mexico-based (Project Viva) cohort. DNA methylation was measured using Illumina arrays, personal/parental SES by questionnaire and neighbourhood disadvantage from geocoded address. In CARDIA, we examined the most strongly associated personal, parental and neighbourhood SES measures with EAA (Hannum's method) at study years 15 and 20 separately and combined using a generalized estimating equation (GEE) and compared with other EAA measures (Horvath's EAA, PhenoAge and GrimAge calculators, and DunedinPoAm).

RESULTS

EAA was associated with paternal education in CARDIA [GEEs: βsome college = -1.01 years (-1.91, -0.11) and β<high school = 1.05 (0.09, 2.01) vs college graduates] and FFCWS [GEEs: β<high school = 0.62 (0.00, 1.24)]. We found stronger associations for some paternal education categories among White adults (for GEE, βsome college = -1.39 (-2.41, -0.38)], men (βsome college = -1.76 (-3.16, -0.35)] and women [β<high school = 1.77 (0.42, 3.11)].

CONCLUSIONS

These findings suggest that EAA captures epigenetic impacts of paternal education independently of personal SES later in life. Longitudinal studies should explore these associations at different life stages and link them to health outcomes. EAA could be a useful biomarker of SES-associated health and provide important insight into the pathogenesis and prevention of chronic disease.

Exploring domains, clinical implications and environmental associations of a deep learning marker of biological ageing

Deep Neural Networks (DNN) have been recently developed for the estimation of Biological Age (BA), the hypothetical underlying age of an organism, which can differ from its chronological age (CA). Although promising, these population-specific algorithms warrant further characterization and validation, since their biological, clinical and environmental correlates remain largely unexplored. Here, an accurate DNN was trained to compute BA based on 36 circulating biomarkers in an Italian population (N = 23,858; age ≥ 35 years; 51.7% women). This estimate was heavily influenced by markers of metabolic, heart, kidney and liver function. The resulting Δage (BA-CA) significantly predicted mortality and hospitalization risk for all and specific causes. Slowed biological aging (Δage < 0) was associated with higher physical and mental wellbeing, healthy lifestyles (e.g. adherence to Mediterranean diet) and higher socioeconomic status (educational attainment, household income and occupational status), while accelerated aging (Δage > 0) was associated with smoking and obesity. Together, lifestyles and socioeconomic variables explained ~48% of the total variance in Δage, potentially suggesting the existence of a genetic basis. These findings validate blood-based biological aging as a marker of public health in adult Italians and provide a robust body of knowledge on its biological architecture, clinical implications and potential environmental influences.

DNA methylation of decedent blood samples to estimate the chronological age of human remains

Chronological age estimation may offer valuable investigative leads in human identification cases. Bisulfite pyrosequencing analysis of single CpG sites on five genes (KLF14, ELOVL2, C1orf132, TRIM59, and FHL2) was performed on 264 postmortem blood samples from individuals aged 3 months to 93 years. The goals were to develop age prediction models based on the correlation between the methylation profile and chronological age and to assess the accuracy of the prediction. Linear regression between methylation levels and age at each CpG site revealed that the five markers show a statistically significant correlation with age. The methylation data from a training set of 160 postmortem blood samples were used to develop an age prediction model with a correlation coefficient of 0.65, explaining 73.1% of age variation, with a mean absolute deviation from the chronological age of 7.60 years. The accuracy of the model was evaluated with a test set of 72 samples producing a mean absolute deviation of 7.42 years. The training and test sets were also categorized by specific age groups to assess accuracy and deviation from chronological age. The data for both sets revealed a lower prediction potential as an individual increases in age, particularly for the age categories above 50 years.

A Structured Approach to Evaluating Life-Course Hypotheses: Moving Beyond Analyses of Exposed Versus Unexposed in the -Omics Context

The structured life-course modeling approach (SLCMA) is a theory-driven analytical method that empirically compares multiple prespecified life-course hypotheses characterizing time-dependent exposure-outcome relationships to determine which theory best fits the observed data. In this study, we performed simulations and empirical analyses to evaluate the performance of the SLCMA when applied to genomewide DNA methylation (DNAm). Using simulations (n = 700), we compared 5 statistical inference tests used with SLCMA, assessing the familywise error rate, statistical power, and confidence interval coverage to determine whether inference based on these tests was valid in the presence of substantial multiple testing and small effects-2 hallmark challenges of inference from -omics data. In the empirical analyses (n = 703), we evaluated the time-dependent relationship between childhood abuse and genomewide DNAm. In simulations, selective inference and the max-|t|-test performed best: Both controlled the familywise error rate and yielded moderate statistical power. Empirical analyses using SLCMA revealed time-dependent effects of childhood abuse on DNAm. Our findings show that SLCMA, applied and interpreted appropriately, can be used in high-throughput settings to examine time-dependent effects underlying exposure-outcome relationships over the life course. We provide recommendations for applying the SLCMA in -omics settings and encourage researchers to move beyond analyses of exposed versus unexposed individuals.

Life course socioeconomic position and DNA methylation age acceleration in mid-life

Background

Ageing biomarkers can help us better understand how well-established socioeconomic position (SEP) disparities in ageing occur. A promising new set of DNAm methylation (DNAm)-based ageing biomarkers indicate through their age acceleration (AA) measures if biological ageing is slower or faster than chronological ageing. Few studies have investigated the association between SEP and DNAm AA.

Methods

We used linear regression to examine the sex-adjusted relationships between childhood social class, adult social class, intergenerational social class change, education and adult household earnings with first (Horvath AA and Hannum AA) and second generation (PhenoAge AA and GrimAge AA) DNAm AA markers using data from the MRC National Survey of Health and Development.

Results

In the first-generation biomarkers, there was little evidence of any associations with Horvath AA but associations of childhood social class and income with Hannum AA were observed. Strong associations were seen between greater disadvantage in childhood and adult SEP and greater AA in the second generation biomarkers. For example, those with fathers in an unskilled occupational social class in childhood had 3.6 years greater PhenoAge AA (95% CI 1.8 to 5.4) than those with fathers from a professional social class. Individuals without qualifications had higher AA compared with those with higher education (4.1 years greater GrimAge AA (95% CI 3.1 to 5.0)).

Conclusion

Our findings highlight the importance of exposure to social disadvantage in childhood to the biological ageing process. The second generation clocks appear to be more sensitive to the accumulation of social disadvantage across the life course.

An Exploratory Study of Epigenetic Age in Preeclamptic and Normotensive Pregnancy Reveals Differences by Self-Reported Race but Not Pregnancy Outcome

Preeclampsia is a leading cause of maternal and neonatal morbidity and mortality. Chronological age and race are associated with preeclampsia, but the role of these factors is not entirely understood. We hypothesized that DNA methylation age, a measure of biological age, would be higher in individuals with preeclampsia than in individuals with normotensive pregnancy and that DNA methylation age would differ by race across pregnancy. This was a longitudinal, exploratory study of 56 pregnant individuals (n = 28 preeclampsia cases and n = 28 normotensive controls). Genome-wide DNA methylation data were generated from trimester-specific peripheral blood samples. DNA methylation age was estimated using the "Improved Precision" clock, and ∆age, the difference between DNA methylation age and chronological age, was computed. DNA methylation age was compared with chronological age using Pearson correlations. The relationships between ∆age and preeclampsia status, self-reported race, and covariates were tested using multiple linear regression and performed both with and without consideration of cell-type heterogeneity. We observed strong correlation between chronological age and DNA methylation age across pregnancy, with significantly stronger correlation observed in White participants than in Black participants. We observed no association between ∆age and preeclampsia status. However, ∆age was higher in participants with higher pre-pregnancy body mass index in trimester 1 and lower in Black participants than in White participants in trimesters 2 and 3. Observations were largely consistent when controlling for cell-type heterogeneity. Our findings in a small sample support the need for additional studies to investigate the relationship between race and biological age, which could provide further insight into racial disparities across pregnancy. However, this study does not support an association between ∆age and preeclampsia status.

Determination of saliva epigenetic age in infancy, and its association with parental socio-economic characteristics and pregnancy outcomes

Epigenetic age acceleration (AA) has been associated with adverse environmental exposures and many chronic conditions. We estimated, in the NINFEA birth cohort, infant saliva epigenetic age, and investigated whether parental socio-economic position (SEP) and pregnancy outcomes are associated with infant epigenetic AA. A total of 139 saliva samples collected at on average 10.8 (range 7-17) months were used to estimate Horvath's DNA methylation age. Epigenetic AA was defined as the residual from a linear regression of epigenetic age on chronological age. Linear regression models were used to test the associations of parental SEP and pregnancy outcomes with saliva epigenetic AA. A moderate positive association was found between DNA methylation age and chronological age, with the median absolute difference of 6.8 months (standard deviation [SD] 3.9). The evidence of the association between the indicators of low SEP and epigenetic AA was weak; infants born to unemployed mothers or with low education had on average 1 month higher epigenetic age than infants of mothers with high education and employment (coefficient 0.78 months, 95% confidence intervals [CIs]: -0.79 to 2.34 for low/medium education; 0.96, 95% CI: -1.81 to 3.73 for unemployment). There was no evidence for association of gestational age, birthweight or caesarean section with infant epigenetic AA. Using the Horvath's method, DNA methylation age can be fairly accurately predicted from saliva samples already in the first months of life. This study did not reveal clear associations between either pregnancy outcomes or parental socio-economic characteristics and infant saliva epigenetic AA.

How are social determinants of health integrated into epigenetic research? A systematic review

OBJECTIVE

We systematically review the literature on social epigenetics, examining how empirical research to date has conceptualized and operationalized social determinants of health (SDOH).

METHODS

Using comprehensive search procedures, we identified studies that consider the impact of SDOH on DNA methylation (DNAm), the most common measure of epigenetic change in research on human adult populations. We analyzed the studies to determine: 1) which populations and environments have been investigated in the literature; 2) how SDOH are defined and operationalized; 3) which SDOH have been linked to DNAm; and 4) what lessons from the SDOH literature can be better integrated into future studies exploring the social determinants of health and epigenetic outcomes.

RESULTS

We identified 67 studies, with 39 to 8397 participants. The SDOH most commonly considered were early life socioeconomic exposures and early life trauma or mental health. Our review highlights four broad challenges: a) high dependence on convenience sampling, b) limited racial/ethnic, and geographic diversity in sampling frames, c) overreliance on individual sociodemographic characteristics as proxies for broader stratification processes, and d) a focus on downstream social determinants of health and individualized experiences with social stressors.

CONCLUSIONS

Future social epigenetics research should prioritize larger, more diverse and representative population-based samples and employ the SDOH framework to better inform the conceptualization of research questions and interpretation of findings. In particular, the simplified depiction of race/ethnicity, gender, and socioeconomic status as individual-level characteristics should be updated with an explicit acknowledgement that these characteristics are more accurately interpreted as cues used by society to differentiate subpopulations. Social epigenetics research can then more clearly elucidate the biological consequences of these social exposures for patterns of gene expression, subsequent disease etiology, and health inequities.

Anti-aging technoscience & the biologization of cumulative inequality: Affinities in the biopolitics of successful aging

This paper charts the emergence of under-remarked affinities between contemporary anti-aging technoscience and some social scientific work on biological aging. Both have recently sought to develop increasingly sophisticated operationalizations of age, aging and agedness as biological phenomena, in response to traditional notions of normal and chronological aging. Rather than being an interesting coincidence, these affinities indicate the influence of a biopolitics of successful aging on government, industry and social science. This biopolitics construes aging as a personal project that is mastered through specific forms of entrepreneurial individual action, especially consumption practices. Social scientists must remain alert to this biopolitics and its influence on their own work, because the individualization of cumulative inequalities provides intellectual and moral justifications for anti-aging interventions that exploit those inequalities.

Association of Neighborhood Deprivation With Epigenetic Aging Using 4 Clock Metrics

IMPORTANCE

Neighborhood deprivation is associated with age-related disease, mortality, and reduced life expectancy. However, biological pathways underlying these associations are not well understood.

OBJECTIVE

To evaluate the association between neighborhood deprivation and epigenetic measures of age acceleration and genome-wide methylation.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from the Sister Study, a prospective cohort study comprising 50 884 women living in the US and Puerto Rico aged 35 to 74 years at enrollment who had a sister with breast cancer but had not had breast cancer themselves. Cohort enrollment occurred between July 2003 and March 2009. Participants completed a computer-assisted telephone interview on demographic, socioeconomic, lifestyle, and residential factors and provided anthropometric measures and peripheral blood samples at a home examination. DNA methylation data obtained for 2630 non-Hispanic White women selected for a case-cohort study in 2014 were used in this cross-sectional analysis. DNA methylation was measured using the HumanMethylation450 BeadChips in whole blood samples collected at baseline. Data analysis for this study was performed from October 17, 2019, to August 27, 2020.

EXPOSURES

Each participants' primary address was linked to an established index of neighborhood deprivation.

MAIN OUTCOMES AND MEASURES

Epigenetic age was estimated using 4 epigenetic clocks (Horvath, Hannum, PhenoAge, and GrimAge). Age acceleration was determined using residuals from regressing chronologic age on each of the 4 epigenetic age metrics. Linear regression was used to estimate associations between neighborhood deprivation and epigenetic age acceleration as well as DNA methylation at individual cytosine-guanine sites across the genome.

RESULTS

Mean (SD) age of the 2630 participants was 56.9 (8.7) years. Those with the greatest (>75th percentile) vs least (≤25th percentile) neighborhood deprivation had higher epigenetic age acceleration estimated by Hannum (β = 0.23; 95% CI, 0.01-0.45), PhenoAge (β = 0.28; 95% CI, 0.06-.50), and GrimAge (β = 0.37; 95% CI, 0.12-0.62). Increasing US quartiles of neighborhood deprivation exhibited a trend with Hannum, PhenoAge, and GrimAge. For example, GrimAge showed a significant dose-response (P test for trend <.001) as follows: level 2 vs level 1 (β = 0.30; 95% CI, 0.17-0.42), level 3 vs level 1 (β = 0.35; 95% CI, 0.19-0.50), and level 4 vs level 1 (β = 0.37; 95% CI, 0.12-0.62). Neighborhood deprivation was found to be associated with 3 cytosine-phosphate-guanine sites, with 1 of these annotated to a known gene MAOB (P = 9.71 × 10-08).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that residing in a neighborhood with a higher deprivation index appears to be reflected by methylation-based markers of aging.

Epigenetic clock as a correlate of anxiety

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In young adult women, slower epigenetic clock predicted less symptoms of anxiety.

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In young adult women, slower epigenetic clock predicted greater cortical GM volume.

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This effect of epigenetic clock in young adult women was largest in frontal lobe.

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The link of epigenetic clock and anxiety was mediated by GM volume in frontal lobe.

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No similar relationships were found in young adult men or adolescents.

DNA methylation changes consistently throughout life and age-dependent alterations in DNA methylation can be used to estimate one’s epigenetic age. Post-mortem studies revealed higher epigenetic age in brains of patients with major depressive disorder, as compared with controls. Since MDD is highly correlated with anxiety, we hypothesized that symptoms of anxiety, as well as lower volume of grey matter (GM) in depression-related cortical regions, will be associated with faster epigenetic clock in a community-based sample of young adults. Participants included 88 young adults (53% men; 23–24 years of age) from the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) who participated in its neuroimaging follow-up and provided saliva samples for epigenetic analysis. Epigenetic age was calculated according to Horvath (Horvath, 2013). Women had slower epigenetic clock than men (Cohen’s d = 0.48). In women (but not men), slower epigenetic clock was associated with less symptoms of anxiety. In the brain, women (but not men) with slower epigenetic clock had greater GM volume in the cerebral cortex (brain size-corrected; R² = 0.07). Lobe-specific analyses showed that in women (but not men), slower epigenetic clock was associated with greater GM volume in frontal lobe (R² = 0.16), and that GM volume in frontal lobe mediated the relationship between the speed of epigenetic clock and anxiety trait (ab = 0.15, SE = 0.15, 95% CI [0.007; 0.369]). These findings were not replicated, however, in a community-based sample of adolescents (n = 129; 49% men; 12–19 years of age), possibly due to the different method of tissue collection (blood vs. saliva) or additional sources of variability in the cohort of adolescents (puberty stages, socioeconomic status, prenatal exposure to maternal smoking during pregnancy).

Scars of childhood socioeconomic stress: A systematic review

Childhood socioeconomic position (SEP) is associated with the development of adult psychological outcomes, with DNA methylation (DNAm) as a mechanism to potentially explain these changes. We present the first systematic review synthesising the literature investigating childhood SEP and DNAm. Thirty-two publications were included. Seventeen studies focused on candidate genes, typically focusing on genes implicated with the stress response and/or development of psychiatric conditions. These studies typically investigated different regions of the genes, which revealed inconsistent results. Six studies calculated epigenetic age, with a small number revealing an elevated significant association with childhood SEP. Epigenome-wide studies revealed altered patterns of DNAm which varied between the nine studies. This research area is emerging and demonstrated great variance in findings with no clear patterns identified across studies. Multiple methodological shortcomings are identified, including at the phenotypic level where construct validity of childhood SEP is highly inconsistent, with studies using a wide range of measures. Larger cohorts will be required with international collaborations to strengthen this research area.

Accelerating the Search for Interventions Aimed at Expanding the Health Span in Humans: The Role of Epidemiology

BACKGROUND

Extensive work in basic and clinical science suggests that biological mechanisms of aging are causally related to the development of disease and disability in late life. Modulation of the biological mechanisms of aging can extend both life span and health span in animal models, but translation to humans has been slow.

METHODS

Summary of workshop proceedings from the 2018-2019 Epidemiology of Aging Workshop hosted by the Intramural Research Program at the National Institute on Aging.

RESULTS

Epidemiologic studies play a vital role to progress in this field, particularly in evaluating new risk factors and measures of biologic aging that may influence health span, as well as developing relevant outcome measures that are robust and relevant for older individuals.

CONCLUSIONS

Appropriately designed epidemiological studies are needed to identify targets for intervention and to inform study design and sample size estimates for future clinical trials designed to promote health span.

Association between GDF15, poverty and mortality in urban middle-aged African American and white adults

Mortality disparities are influenced by race and poverty. There is limited information about whether poverty influences biologic markers of mortality risk. Emerging data suggests that growth differentiation factor 15 (GDF15) is associated with mortality; however, the interplay between GDF15, sociodemographic factors and mortality is not known. We sought to evaluate the interactions between GDF15 and sex, race and poverty status on mortality. Serum GDF15 was measured in 1036 African American and white middle-aged men and women above and below 125% of the Federal poverty status from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study. Multivariable adjusted Cox regression models were used to assess the association between log-transformed GDF15 (logGDF15) and 12-year mortality outcomes (all-cause, cardiovascular- and cancer-specific outcomes) and interactions with sex, race and poverty status. Likelihood ratio tests were used to assess significance of the interaction terms. Median GDF15 was 655.2 pg/mL (IQR = 575.1). During 12.2 years of follow-up, 331 died of which 94 cardiovascular- and 87 were cancer-specific deaths. One unit of increase in logGDF15 was associated with a hazard ratio for all-cause mortality, cardiovascular- and cancer-specific mortality of 2.26 (95% confidence interval [CI], 1.94–2.64), 2.74 (95%CI, 2.06–3.63) and 1.41 (95%CI, 1.00–2.00), respectively. There was an interaction between logGDF15 and poverty status on all-cause mortality (p<0.05). The GDF15×poverty status interaction term improved model calibration for all-cause mortality. Our study provides the first evidence that the effect of elevated GDF15 on all-cause mortality is modified by poverty status.

Epigenetic clocks may come out of rhythm-implications for the estimation of chronological age in forensic casework

There is a growing perception that DNA methylation may be influenced by exogenous and endogenous parameters. Knowledge of these factors is of great relevance for the interpretation of DNA-methylation data for the estimation of chronological age in forensic casework. We performed a literature review to identify parameters, which might be of relevance for the prediction of chronological age based on DNA methylation. The quality of age predictions might particularly be influenced by lifetime adversities (chronic stress, trauma/post-traumatic stress disorder (PTSD), violence, low socioeconomic status/education), cancer, obesity and related diseases, infectious diseases (especially HIV and Cytomegalovirus (CMV) infections), sex, ethnicity and exposure to toxins (alcohol, smoking, air pollution, pesticides). Such factors may alter the DNA methylation pattern and may explain the partly high deviations between epigenetic age and chronological age in single cases (despite of low mean absolute deviations) that can also be observed with “epigenetic clocks” comprising a high number of CpG sites. So far, only few publications dealing with forensic age estimation address these confounding factors. Future research should focus on the identification of further relevant confounding factors and the development of models that are “robust” against the influence of such biological factors by systematic investigations under targeted inclusion of diverse and defined cohorts.