Epigenetic-based age acceleration in a representative sample of older Americans: Associations with aging-related morbidity and mortality

Moderate BMI accumulation modified associations between blood benzene, toluene, ethylbenzene and xylene (BTEX) and phenotypic aging: mediating roles of inflammation and oxidative stress

The associations between blood benzene, toluene, ethylbenzene, and xylenes (BTEX) and biological aging among general adults remain elusive. The present study comprised 5780 participants from the National Health and Nutrition Examination Survey 1999-2010. A novel measure of biological aging, phenotypic age acceleration (PhenoAge.Accel), derived from biochemical markers was calculated. Weighted generalized linear regression and weighted quantile sum regression (WQS) were utilized to assess the associations between BTEX components and mixed exposure, and PhenoAge.Accel. The mediating roles of systemic immune-inflammation index (SII) and oxidative stress indicators (serum bilirubin and gamma-glutamyl transferase), along with the modifying effects of body mass index (BMI) were also examined. In the single-exposure model, the highest quantile of blood benzene (b = 0.89, 95%CI: 0.58 to 1.20), toluene (b = 0.87, 95%CI: 0.52 to 1.20), and ethylbenzene (b = 0.80, 95%CI: 0.46 to 1.10) was positively associated with PhenoAge.Accel compared to quantile 1. Mixed-exposure analyses revealed a consistent positive association between BTEX mixed exposure and PhenoAge.Accel (b = 0.88, 95%CI: 0.56 to 1.20), primarily driven by benzene (92.78%). The association between BTEX and PhenoAge.Accel was found to be partially mediated by inflammation and oxidative stress indicators (ranging from 3.2% to 13.7%). Additionally, BMI negatively modified the association between BTEX mixed exposure and PhenoAge.Accel, with a threshold identified at 36.2 kg/m^2. Furthermore, BMI negatively moderated the direct effect of BTEX mixed exposure on PhenoAge.Accel in moderated mediation models, while positively modified the link between SII and PhenoAge.Accel in the indirect path (binteraction = 0.04, 95%CI: 0.01 to 0.06). Overall, BTEX mixed exposure was associated with PhenoAge.Accel among US adults, with benzene may have reported most contribution, and inflammation and oxidative damage processes may partially explain this underlying mechanism. The study also highlighted the potential benefits of appropriate BMI increased. Additional large-scale cohort studies and experiments were necessary to substantiate these findings.

Longitudinal Changes in Epigenetic Age Acceleration Across Childhood and Adolescence

Importance

Individuals exposed to discrimination may exhibit greater epigenetic age acceleration (ie, cellular indicators of premature aging) over time, but few studies have examined longitudinal changes in epigenetic age acceleration, the heterogeneity in these changes for diverse groups of youths, and contextual explanations (ie, discrimination) for differences by ethnicity or race.

Objective

To provide a descriptive illustration of changes in epigenetic age acceleration across childhood and adolescence among an ethnically and racially diverse sample of youths.

Design, Setting, and Participants

This cohort study leveraged longitudinal data on a large sample of youths from low-income households in 20 large urban US cities who provided repeated assessments of saliva tissue samples at ages 9 and 15 years for DNA methylation analysis. Of 4898 youths from the Future of Families and Child Well-Being study, an ongoing study that oversampled children born to unmarried parents from 1998 to 2000, 2039 were included in the present analysis, as these youths had salivary DNA methylation data assayed and publicly available. Analyses were conducted from March 2023 to June 2024.

Exposures

Racialized intrusive encounters with police (eg, stop and frisk and racial slurs).

Main Outcomes and Measures

Analyses were conducted to examine longitudinal changes in salivary epigenetic age acceleration over time, whether such changes varied across ethnically and racially diverse groups of youths, and whether police intrusion was associated with variation across ethnic and racial groups.

Results

Among 2039 youths (mean [SD] age at baseline, 9.27 [0.38] years; 1023 [50%] male and 1016 [50%] female; 917 [45%] Black, 430 [21%] Hispanic or Latino, 351 [17%] White, and 341 [17%] other, including multiple races and self-identified other) with salivary epigenetic clocks at 9 and 15 years of age, longitudinal results showed that White youths exhibited less accelerated epigenetic aging over time than did Black and Hispanic or Latino youths and those reporting other or multiple races or ethnicities from ages 9 to 15 years, particularly in the Hannum (B, 1.54; 95% CI, 0.36-2.18), GrimAge (B, 1.31; 95% CI, 0.68-1.97), and DunedinPACE epigenetic clocks (B, 0.27; 95% CI, 0.11-0.44). Across these clocks and the PhenoAge clock, police intrusion was associated with Black youths' more accelerated epigenetic aging (Hannum: B, 0.11; 95% CI, 0.03-0.23; GrimAge: B, 0.09; 95% CI, 0.03-0.18; PhenoAge: B, 0.08; 95% CI, 0.02-0.18; DunedinPACE: B, 0.01; 95% CI, 0.01-0.03).

Conclusions and Relevance

The transition from childhood to adolescence may represent a sensitive developmental period when racism can have long-term deleterious impacts on healthy human development across the life span. Future research should build on the present study and interrogate which social regularities and policies may be perpetuating discrimination against ethnically and racially minoritized adolescents.

Epigenetic Aging Associations With Psychoneurological Symptoms and Social Functioning in Adults With Sickle Cell Disease

Objective: Sickle cell disease (SCD), the most common inherited blood disorder in the United States, is associated with severe psychoneurological symptoms. While epigenetic age acceleration has been linked to psychoneurological symptom burden in other diseases, this connection is unexplored in SCD. This study aimed to assess the association between epigenetic age acceleration and psychoneurological symptom burden in SCD. Methods: In this cross-sectional study, emotional impact, pain impact, sleep impact, social functioning, and cognitive function were assessed in 87 adults living with SCD. DNA methylation data were generated from blood specimens and used to calculate epigenetic age using five clocks (Horvath, Hannum, PhenoAge, GrimAge, & DunedinPACE). Associations between epigenetic age acceleration and symptoms were assessed. Results: The sample (N = 87) had a mean (SD) chronologic age was 30.6 (8.1) years. Epigenetic age acceleration was associated with several symptom outcomes. GrimAge age acceleration (β = -0.49, p = .03) and increased DunedinPACE (β = -2.23, p = .004) were associated with worse emotional impact scores. PhenoAge (β = -0.32, p = .04) and the GrimAge (β = -0.48, p = .05) age acceleration were associated with worse pain impact scores. Increased DunedinPACE (β = -2.07 p = .04) were associated with worse sleep impact scores. Increased DunedinPACE (β = -2.87, p = .005) was associated with worse social functioning scores. We did not find associations between epigenetic age acceleration and cognitive function in this sample. Conclusion: Epigenetic age acceleration was associated with worse symptom experiences, suggesting the potential for epigenetic age acceleration as a biomarker to aid in risk stratification or targets for intervention to mitigate symptom burden in SCD.

Cohort profile: DNA methylation in the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA) - recruitment and participant characteristics

PURPOSE

Epigenetic modifications including DNA methylation (DNAm) are proposed mechanisms by which social or environmental exposures may influence health and behaviours as we age. The Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA) DNAm cohort, established in 2013, is one of several worldwide, nationally representative prospective studies of ageing with biological samples from participants who consented to multiomic analysis.

PARTICIPANTS

NICOLA recruited 8478 participants (8283 aged 50 years or older and 195 spouses or partners at the same address aged under 50 years). Computer-Assisted Personal Interviews, Self-Completion Questionnaires and detailed Health Assessments (HA) were completed. Of the 3471 (44.1%) participants who attended the HA in wave 1, which included venous blood sampling, 2000 were identified for the DNAm cohort. Following technical and data quality control checks, DNAm data are currently available for n=1870.

FINDINGS TO DATE

There was no significant difference based on age, self-reported gender, education, employment, smoking or alcohol status and subjective health reports between the DNAm cohort and other HA attendees. Participants were more likely to be in the DNAm group if they lived with one other person (OR 1.26, 95% CI 1.07 to 1.49). The DNAm group had a lower proportion of depressed participants and those meeting criteria for post-traumatic stress disorder (11.7% and 4.4% vs 13.5% and 4.5%, respectively) categorised by objective assessment tools but this was not significant (OR 0.84, 95% CI 0.69 to 1.02 and OR 0.87, 95% CI 0.64 to 1.19).

FUTURE PLANS

The deeply phenotyped DNAm cohort in NICOLA with planned prospective follow-up and additional multiomic data releases will increase the cohort's utility for research into ageing. The genomic and epigenetic data for the DNAm cohort has been deposited on the European Genome-Phenome Archive, increasing the profile of this cohort and data availability to researchers.

Uncertainty quantification in epigenetic clocks via conformalized quantile regression

DNA methylation (DNAm) is a chemical modification of DNA that can be influenced by various factors, including age, environment, and lifestyle. An epigenetic clock is a predictive tool that measures biological age based on DNAm levels. It can provide insights into an individual's biological age, which may differ from their chronological age. This difference, known as the epigenetic age acceleration, may indicate the state of one's health and risk for age-related diseases. Moreover, epigenetic clocks are used in studies of aging to assess the effectiveness of anti-aging interventions and to understand the underlying mechanisms of aging and disease. Various epigenetic clocks have been developed using samples from different populations, tissues, and cell types, typically by training high-dimensional linear regression models with an elastic net penalty. While these models can predict mean biological age with high precision, there is a lack of uncertainty quantification which is important for interpreting the precision of age estimations and for clinical decision-making. To understand the distribution of a biological age clock beyond its mean, we propose a general pipeline for training epigenetic clocks, based on an integration of high-dimensional quantile regression and conformal prediction, to effectively reveal population heterogeneity and construct prediction intervals. Our approach produces adaptive prediction intervals not only achieving nominal coverage but also accounting for the inherent variability across individuals. By using the data collected from 728 blood samples in 11 DNAm datasets from children, we find that our quantile regression-based prediction intervals are narrower than those derived from conventional mean regression-based epigenetic clocks. This observation demonstrates an improved statistical efficiency over the existing pipeline for training epigenetic clocks. In addition, the resulting intervals have a synchronized varying pattern to age acceleration, effectively revealing cellular evolutionary heterogeneity in age patterns in different developmental stages during individual childhoods and adolescent cohort. Our findings suggest that conformalized high-dimensional quantile regression can produce valid prediction intervals and uncover underlying population heterogeneity. Although our methodology focuses on the distribution of aging in children, it is applicable to a broader range of populations to improve understanding of epigenetic age beyond the mean. This inference-based toolbox could provide valuable insights for future applications of epigenetic interventions for age-related diseases.

Animal Models Relevant for Geroscience: Current Trends and Future Perspectives in Biomarkers, and Measures of Biological Aging

For centuries, aging was considered inevitable and immutable. Geroscience provides the conceptual framework to shift this focus toward a new view that regards aging as an active biological process, and the biological age of an individual as a modifiable entity. Significant steps forward have been made toward the identification of biomarkers for and measures of biological age, yet knowledge gaps in geroscience are still numerous. Animal models of aging are the focus of this perspective, which discusses how experimental design can be optimized to inform and refine the development of translationally relevant measures and biomarkers of biological age. We provide recommendations to the field, including: the design of longitudinal studies in which subjects are deeply phenotyped via repeated multilevel behavioral/social/molecular assays; the need to consider sociobehavioral variables relevant for the species studied; and finally, the importance of assessing age of onset, severity of pathologies, and age-at-death. We highlight approaches to integrate biomarkers and measures of functional impairment using machine learning approaches designed to estimate biological age as well as to predict future health declines and mortality. We expect that advances in animal models of aging will be crucial for the future of translational geroscience but also for the next chapter of medicine.

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.

Epigenetic age acceleration and mortality risk prediction in U.S. adults

Background

Epigenetic clocks have emerged as novel measures of biological age and potential predictors of mortality. We aimed to test whether epigenetic age acceleration (EAA) estimated using different epigenetic clocks predict long-term overall, cardiovascular or cancer mortality.

Methods

We analyzed data from 2,105 participants to the 1999-2002 National Health and Nutrition Examination Survey aged ≥50 years old who were followed for mortality through 2019. EAAs was calculated from the residuals of Horvath, Hannum, SkinBlood, Pheno, Zhang, Lin, Weidner, Vidal-Bralo and Grim epigenetic clocks regressed on chronological age. Using cox proportional hazards regression, we estimated the hazard ratio (HR) and 95% confidence interval (CI) for the association of EAA (per 5-year) and the DunedinPoAm pace of aging (per 10% increase) with overall, cardiovascular and cancer mortality, adjusting for covariates and white blood cell composition.

Results

During a median follow-up of 17.5 years, 998 deaths occurred, including 272 from cardiovascular disease and 209 from cancer. Overall mortality was most significantly predicted by Grim EAA (P < 0.0001; HR: 1.50, 95% CI: 1.32-1.71) followed by Hannum (P = 0.001; HR: 1.16, 95% CI: 1.07-1.27), Pheno (P = 0.001; HR: 1.13, 95% CI: 1.05-1.21), Horvath (P = 0.007; HR: 1.13, 95% CI: 1.04-1.22) and Vidal-Bralo (P = 0.008; HR: 1.13, 95% CI: 1.03-1.23) EAAs. Grim EAA predicted cardiovascular mortality (P < 0.0001; HR: 1.55, 95% CI: 1.29-1.86), whereas Hannum (P = 0.006; HR: 1.24, 95% CI: 1.07-1.44), Horvath (P = 0.02; HR: 1.18, 95% CI: 1.02-1.35) and Grim (P = 0.049; HR: 1.37, 95% CI: 1.00-1.87) EAAs predicted cancer mortality. DunedinPoAm pace of aging was associated with overall (P = 0.003; HR: 1.23, 95% CI: 1.08-1.38) and cardiovascular (P = 0.04; HR: 1.25, 95% CI: 1.01-1.55) mortality.

Conclusions

In a U.S. representative sample, Horvath, Hannum, Pheno, Vidal-Bralo and Grim EAA all predicted overall mortality but only Grim EAA predicted cardiovascular mortality and Horvath, Hannum or Grim EAA predicted cancer mortality. Pace of aging predicted overall and cardiovascular mortality.

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.

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.

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.

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.

Current evidence supporting associations of DNA methylation measurements with survivorship burdens in cancer survivors: A scoping review

INTRODUCTION

Identifying reliable biomarkers that reflect cancer survivorship symptoms remains a challenge for researchers. DNA methylation (DNAm) measurements reflecting epigenetic changes caused by anti-cancer therapy may provide needed insights. Given lack of consensus describing utilization of DNAm data to predict survivorship issues, a review evaluating the current landscape is warranted.

OBJECTIVE

Provide an overview of current studies examining associations of DNAm with survivorship burdens in cancer survivors.

METHODS

A literature review was conducted including studies if they focused on cohorts of cancer survivors, utilized peripheral blood cell DNAm data, and evaluated the associations of DNAm and survivorship issues.

RESULTS

A total of 22 studies were identified, with majority focused on breast (n = 7) or childhood cancer (n = 9) survivors, and half studies included less than 100 patients (n = 11). Survivorship issues evaluated included those related to neurocognition (n = 5), psychiatric health (n = 3), general wellness (n = 9), chronic conditions (n = 5), and treatment specific toxicities (n = 4). Studies evaluated epigenetic age metrics (n = 10) and DNAm levels at individual CpG sites or regions (n = 12) for their associations with survivorship issues in cancer survivors along with relevant confounding factors. Significant associations of measured DNAm in the peripheral blood samples of cancer survivors and survivorship issues were identified.

DISCUSSION/CONCLUSION

Studies utilizing epigenetic age metrics and differential methylation analysis demonstrated significant associations of DNAm measurements with survivorship burdens. Associations were observed encompassing diverse survivorship outcomes and timeframes relative to anti-cancer therapy initiation. These findings underscore the potential of these measurements as useful biomarkers in survivorship care and research.

Psychoneuroimmunology in multiple myeloma and autologous hematopoietic stem cell transplant: Opportunities for research among patients and caregivers

Multiple myeloma (MM) is an incurable cancer and is the leading indication for autologous hematopoietic stem cell transplantation (HSCT). To be eligible for HSCT, a patient must have a caregiver, as caregivers play a central role in HSCT preparation and recovery. MM patients remain on treatment indefinitely, and thus patients and their caregivers face long-term challenges including the intensity of HSCT and perpetual therapy after transplant. Importantly, both patients and their caregivers show heightened depressive and anxiety symptoms, with dyadic correspondence evidenced and caregivers' distress often exceeding that of patients. An extensive psychoneuroimmunology (PNI) literature links distress with health via immune and neuroendocrine dysregulation as well as biological aging. However, data on PNI in the context of multiple myeloma - in patients or caregivers - are remarkably limited. Distress in MM patients has been associated with poorer outcomes including higher inflammation, greater one year post-HSCT hospital readmissions, and worse overall survival. Further, anxiety and depression are linked to biological aging and may contribute to the poor long-term health of both patients and caregivers. Because MM generally affects older adults, individual differences in biological aging may represent an important modifier of MM biology and HSCT treatment outcomes. There are a number of clinical scenarios in which biologically younger people could be prescribed more intensive therapies, with potential for greater benefit, by using a personalized cancer therapy approach based on the quantification of physiologic reserve. Further, despite considerable psychological demands, the effects of distress on health among MM caregivers is largely unexamined. Within this context, the current critical review highlights gaps in knowledge at the intersection of HSCT, inflammation, and biological aging in the context of MM. Research in this area hold promise for opportunities for novel and impactful psychoneuroimmunology (PNI) research to enhance health outcomes, quality of life, and longevity among both MM patients and their caregivers.

Health-related quality of life and DNA methylation-based aging biomarkers among survivors of childhood cancer

BACKGROUND

Childhood cancer survivors are at high risk for morbidity and mortality and poor patient-reported outcomes, typically health-related quality of life (HRQOL). However, associations between DNA methylation-based aging biomarkers and HRQOL have not been evaluated.

METHODS

DNA methylation was generated with Infinium EPIC BeadChip on blood-derived DNA (median for age at blood draw = 34.5 years, range = 18.5-66.6 years), and HRQOL was assessed with age at survey (mean = 32.3 years, range = 18.4-64.5 years) from 2206 survivors in the St Jude Lifetime Cohort. DNA methylation-based aging biomarkers, including epigenetic age using multiple clocks (eg, GrimAge) and others (eg, DNAmB2M: beta-2-microglobulin; DNAmADM: adrenomedullin), were derived from the DNAm Age Calculator (https://dnamage.genetics.ucla.edu). HRQOL was assessed using the Medical Outcomes Study 36-Item Short-Form Health Survey to capture 8 domains and physical and mental component summaries. General linear models evaluated associations between HRQOL and epigenetic age acceleration (EAA; eg, EAA_GrimAge) or other age-adjusted DNA methylation-based biomarkers (eg, ageadj_DNAmB2M) after adjusting for age at blood draw, sex, cancer treatments, and DNA methylation-based surrogate for smoking pack-years. All P values were 2-sided.

RESULTS

Worse HRQOL was associated with greater EAA_GrimAge (physical component summaries: β = -0.18 years, 95% confidence interval [CI] = -0.251 to -0.11 years; P = 1.85 × 10-5; and 4 individual HRQOL domains), followed by ageadj_DNAmB2M (physical component summaries: β = -0.08 years, 95% CI = -0.124 to -0.037 years; P = .003; and 3 individual HRQOL domains) and ageadj_DNAmADM (physical component summaries: β = -0.082 years, 95% CI = -0.125 to -0.039 years; P = .002; and 2 HRQOL domains). EAA_Hannum (Hannum clock) was not associated with any HRQOL.

CONCLUSIONS

Overall and domain-specific measures of HRQOL are associated with DNA methylation measures of biological aging. Future longitudinal studies should test biological aging as a potential mechanism underlying the association between poor HRQOL and increased risk of clinically assessed adverse health outcomes.

Associations between epigenetic age acceleration and longitudinal measures of psychosocioeconomic stress and status

Relationships between epigenetic aging markers and psychosocial variables such as socioeconomic status and stress have been well-documented, but are often examined cross-sectionally or retrospectively, and have tended to focus on objective markers of SES or major life events. Here, we examined associations between psychosocial variables, including measures of socioeconomic status and social stress, and epigenetic aging markers in adulthood, using longitudinal data spanning three decades from the Midlife in the United States (MIDUS) study. The largest effects were observed for epigenetic markers of change in health, such as DunedinPACE and GrimAge, and for associations involving education, income, net assets, general social stress, inequality-related stress, and financial stress. Analyses of polygenic indices suggests that at least in the case of education, the link to epigenetic aging cannot be accounted for by common genetic variants.

Epigenetic Aging and Racialized, Economic, and Environmental Injustice: NIMHD Social Epigenomics Program

Importance

Epigenetic age acceleration is associated with exposure to social and economic adversity and may increase the risk of premature morbidity and mortality. However, no studies have included measures of structural racism, and few have compared estimates within or across the first and second generation of epigenetic clocks.

Objective

To determine whether epigenetic age acceleration is positively associated with exposures to diverse measures of racialized, economic, and environmental injustice measured at different levels and time periods.

Design, Setting, and Participants

This cross-sectional study used data from the My Body My Story (MBMS) study between August 8, 2008, and December 31, 2010, and examination 5 of the Multi-Ethnic Atherosclerosis Study (MESA) from April 1, 2010, to February 29, 2012. In the MBMS, DNA extraction was performed in 2021; linkage of structural measures to the MBMS and MESA, in 2022. US-born individuals were randomly selected from 4 community health centers in Boston, Massachusetts (MBMS), and 4 field sites in Baltimore, Maryland; Forsyth County, North Carolina; New York City, New York; and St Paul, Minnesota (MESA). Data were analyzed from November 13, 2021, to August 31, 2023.

Main Outcomes and Measures

Ten epigenetic clocks (6 first-generation and 4 second-generation), computed using DNA methylation data (DNAm) from blood spots (MBMS) and purified monocytes (MESA).

Results

The US-born study population included 293 MBMS participants (109 men [37.2%], 184 women [62.8%]; mean [SD] age, 49.0 [8.0] years) with 224 Black non-Hispanic and 69 White non-Hispanic participants and 975 MESA participants (492 men [50.5%], 483 women [49.5%]; mean [SD] age, 70.0 [9.3] years) with 229 Black non-Hispanic, 191 Hispanic, and 555 White non-Hispanic participants. Of these, 140 (11.0%) exhibited accelerated aging for all 5 clocks whose estimates are interpretable on the age (years) scale. Among Black non-Hispanic MBMS participants, epigenetic age acceleration was associated with being born in a Jim Crow state by 0.14 (95% CI, 0.003-0.27) SDs and with birth state conservatism by 0.06 (95% CI, 0.01-0.12) SDs, pooling across all clocks. Low parental educational level was associated with epigenetic age acceleration, pooling across all clocks, for both Black non-Hispanic (0.24 [95% CI, 0.08-0.39] SDs) and White non-Hispanic (0.27 [95% CI, 0.03-0.51] SDs) MBMS participants. Adult impoverishment was positively associated with the pooled second-generation clocks among the MESA participants (Black non-Hispanic, 0.06 [95% CI, 0.01-0.12] SDs; Hispanic, 0.07 [95% CI, 0.01-0.14] SDs; White non-Hispanic, 0.05 [95% CI, 0.01-0.08] SDs).

Conclusions and Relevance

The findings of this cross-sectional study of MBMS and MESA participants suggest that epigenetic age acceleration was associated with racialized and economic injustice, potentially contributing to well-documented inequities in premature mortality. Future research should test the hypothesis that epigenetic accelerated aging may be one of the biological mechanisms underlying the well-documented elevated risk of premature morbidity and mortality among social groups subjected to racialized and economic injustice.

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.

Food insecurity and epigenetic aging in middle-aged and older adults

BACKGROUND

Food insecurity is recognized as a key social determinant of health for older adults. While food insecurity has been associated with morbidity and mortality, few studies have examined how it may contribute to accelerated biological aging. A potential mechanism by which food insecurity may contribute to aging is via epigenetic alterations. We examined the relationship between food insecurity and epigenetic aging, a novel measure of biological aging, in a nationally representative sample of middle-aged and older adults in the United States.

METHODS

Cross-sectional analysis of adults 50 years of age and older from the 2016 Health and Retirement Study (HRS). Financial food insecurity was self-reported via two questions that ascertained having enough money for food or eating less than they felt they should. Epigenetic aging was measured via epigenetic clocks based on DNA methylation patterns that predict aging correlates of morbidity and mortality. Linear regressions were performed to test for differences in the epigenetic clocks, adjusting for biological, socioeconomic, and behavioral factors.

RESULTS

The analysis consisted of 3875 adults with mean age of 68.5 years. A total of 8.1% reported food insecurity. Food insecurity was associated with several characteristics, including younger age, race/ethnic minority, lower income, total wealth, and educational attainment, higher BMI, and less physical activity. Food insecurity was associated with accelerated epigenetic aging compared to food security, as measured via second (Zhang, PhenoAge, GrimAge) and third (DunedinPoAm) generation epigenetic clocks. In particular, food insecurity remained significantly associated with accelerated Zhang (B = 0.09, SE = 0.03, p = 0.011) and GrimAge (B = 0.57, SE = 0.24, p = 0.022) in the fully adjusted models.

CONCLUSIONS

Food insecurity is associated with accelerated epigenetic aging among middle-aged and older adults in the United States. Food insecurity may contribute to DNA methylation alterations across the genome and biological age acceleration. These findings add to a growing understanding of the influence of socioeconomic status on the epigenome and health in aging.

New Directions in Geroscience: Integrating Social and Behavioral Drivers of Biological Aging

ABSTRACT

The "geroscience hypothesis" posits that slowing the physiological processes of aging would lead to delayed disease onset and longer healthspan and lifespan. This shift from a focus on solely treating existing disease to slowing the aging process is a shift toward prevention, including a focus on risk factors found in the social environment. Although geroscience traditionally has focused on the molecular and cellular drivers of biological aging, more fundamental causes of aging may be found in the social exposome-the complex array of human social environmental exposures that shape health and disease. The social exposome may interact with physiological processes to accelerate aging biology. In this commentary, we review the potential of these insights to shape the emerging field of translational geroscience. The articles in this special issue highlight how social stress and social determinants of health are associated with biomarkers of aging such as inflammation, epigenetic clocks, and telomeres, and spotlight promising interventions to mitigate stress-related inflammation. For geroscience to incorporate the social exposome into its translational agenda, studies are needed that elucidate and quantify the effects of social exposures on aging and that consider social exposures as intervention targets. The life course perspective allows us to measure both exposures and aging biology over time including sensitive periods of development and major social transitions. In addition, given rapid changes in the measurement of aging biology, which include machine learning techniques, multisystem phenotypes of aging are being developed to better reflect whole body aging, replacing reliance on single system biomarkers. In this expanded and more integrated field of translational geroscience, strategies targeting factors in the social exposome hold promise for achieving aging health equity and extending healthy longevity.

The embodiment of parental death in early life through accelerated epigenetic aging: Implications for understanding how parental death before 18 shapes age-related health risk among older adults

Parental death in early life has been linked to various adverse health outcomes in older adulthood. This study extends prior research to evaluate how parental death in early life is tied to accelerated epigenetic aging, a potentially important biological mechanism from which social and environmental exposures impact age-related health. We used data from the 2016 Venous Blood Study (VBS), a component of the Health and Retirement Study (HRS), to examine the association between parental death in early life and accelerated epigenetic aging as measured by three widely used epigenetic clocks (PCPhenoAge, PCGrimAge, and DunedinPACE). We also assessed whether some of the association is explained by differences in educational attainment, depressive symptoms, and smoking behavior. Methods included a series of linear regression models and formal mediation analysis. Findings indicated that parental death in early life is associated with accelerated epigenetic aging for PCPhenoAge and DunedinPACE. The inclusion of educational attainment, depressive symptoms, and smoking behavior attenuated this association, with formal mediation analysis providing additional support for these observations. Parental death in early life may be one of the most difficult experiences an individual may face. The elevated biological risk associated with parental death in early life may operate through immediate changes but also through more downstream risk factors. This study highlights how early life adversity can set in motion biological changes that have lifelong consequences.

Epigenetic age acceleration and the risk of frailty, and persistent activities of daily living (ADL) disability

BACKGROUND

Epigenetic ageing is among the most promising ageing biomarkers and may be a useful marker of physical function decline, beyond chronological age. This study investigated whether epigenetic age acceleration (AA) is associated with the change in frailty scores over 7 years and the 7-year risk of incident frailty and persistent Activities of Daily Living (ADL) disability among 560 Australians (50.7% females) aged ≥70 years.

METHODS

Seven AA indices, including GrimAge, GrimAge2, FitAge and DunedinPACE, were estimated from baseline peripheral-blood DNA-methylation. Frailty was assessed using both the 67-item deficit-accumulation frailty index (FI) and Fried phenotype (Fried). Persistent ADL disability was defined as loss of ability to perform one or more basic ADLs for at least 6 months. Linear mixed models and Cox proportional-hazard regression models were used as appropriate.

RESULTS

Accelerated GrimAge, GrimAge2, FitAge and DunedinPACE at baseline were associated with increasing FI scores per year (adjusted-Beta ranged from 0.0015 to 0.0021, P < 0.05), and accelerated GrimAge and GrimAge2 were associated with an increased risk of incident FI-defined frailty (adjusted-HRs 1.43 and 1.39, respectively, P < 0.05). The association between DunedinPACE and the change in FI scores was stronger in females (adjusted-Beta 0.0029, P 0.001 than in males (adjusted-Beta 0.0002, P 0.81). DunedinPACE, but not the other AA measures, was also associated with worsening Fried scores (adjusted-Beta 0.0175, P 0.04). No associations were observed with persistent ADL disability.

CONCLUSION

Epigenetic AA in later life is associated with increasing frailty scores per year and the risk of incident FI-defined frailty.

Demographic characteristics and epigenetic biological aging among post-9/11 veterans: Associations of DunedinPACE with sex, race, and age

Measures of epigenetic aging derived from DNA methylation (DNAm) have enabled the assessment of biological aging in new populations and cohorts. In the present study, we used an epigenetic measure of aging, DunedinPACE, to examine rates of aging across demographic groups in a sample of 2,309 United States military veterans from the VISN 6 MIRECC's Post-Deployment Mental Health Study. As assessed by DunedinPACE, female veterans were aging faster than male veterans (β = 0.39, 95 % CI [0.29, 0.48], p < .001), non-Hispanic Black veterans were aging faster than non-Hispanic White veterans (β = 0.58, 95 % CI [0.50, 0.66], p < .001), and older veterans were biologically aging faster than younger veterans (β = 0.21, 95 % CI [0.18, 0.25], p < .001). In secondary analyses, these differences in rates of aging were not explained by a variety of biopsychosocial covariates. In addition, the percentage of European genetic admixture in non-Hispanic Black veterans was not associated with DunedinPACE. Our findings suggest that female and non-Hispanic Black veterans are at greater risk of accelerated aging among post-9/11 veterans. Interventions that slow aging might provide relatively greater benefit among veterans comprising these at-risk groups.

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.

Associations between body mass index, biological age and frailty in the critically ill

BACKGROUND

The relationship between body mass index (BMI) and outcomes in the acute care setting is controversial, with evidence suggesting that obesity is either protective - which is also called obesity paradox - or associated with worse outcomes. The purpose of this study was to assess whether BMI was related to frailty and biological age, and whether BMI remained predictive of mortality after adjusting for frailty and biological age.

SUBJECTS

Of the 2950 patients who had a biological age estimated on admission to the intensive care unit, 877 (30 %) also had BMI and frailty data available for further analysis in this retrospective cohort study.

METHODS

Biological age of each patient was estimated using the Levine PhenoAge model based on results of nine blood tests that were reflective of DNA methylation. Biological age in excess of chronological age was then indexed to the local study context by a linear regression to generate the residuals. The associations between BMI, clinical frailty scale, and the residuals were first analyzed using univariable analyses. Their associations with mortality were then assessed by multivariable analysis, including the use of a 3-knot restricted cubic spline function to allow non-linearity.

RESULTS

Both frailty (p = 0.003) and the residuals of the biological age (p = 0.001) were related to BMI in a U-shaped fashion. BMI was not related to hospital mortality, but both frailty (p = 0.015) and the residuals of biological age (OR per decade older than chronological age 1.50, 95 % confidence interval [CI] 1.04-2.18; p = 0.031) were predictive of mortality after adjusting for chronological age, diabetes mellitus and severity of acute illness.

CONCLUSIONS

BMI was significantly associated with both frailty and biological age in a U-shaped fashion but only the latter two were related to mortality. These results may, in part, explain why obesity paradox could be observed in some studies.

Early-life risk factors, accelerated biological aging and the late-life risk of mortality and morbidity

BACKGROUND

Early-life exposure increases health risks throughout an individual's lifetime. Biological aging is influenced by early-life risks as a key process of disease development, but whether early-life risks could accelerate biological aging and elevate late-life mortality and morbidity risks remains unknown. Knowledge is also limited on the potential moderating role of healthy lifestyle.

METHODS

We investigate associations of three early-life risks around birth, breastfeeding, maternal smoking and birth weight, with biological aging of 202 580 UK Biobank participants (54.9 ± 8.1 years old). Biological aging was quantified as KDM-BA, PhenoAge and frailty. Moderate alcohol intake, no current smoking, healthy diet, BMI <30 kg/m2 and regular physical activity were considered as healthy lifestyles. Mortality and morbidity data were retrieved from health records.

RESULTS

Individual early-life risk factors were robustly associated with accelerated biological aging. A one-unit increase in the 'early-life risk score' integrating the three factors was associated with 0.060 (SE=0.0019) and 0.036-unit (SE = 0.0027) increase in z-scored KDM-BA acceleration and PhenoAge acceleration, respectively, and with 22.3% higher odds (95% CI: 1.185-1.262) of frailty. Increased chronological age and healthy lifestyles could mitigate the accelerations of KDM-BA and PhenoAge, respectively. Associations of early-life risk score with late-life mortality and morbidity were mediated by biological aging (proportions: 5.66-43.12%). KDM-BA and PhenoAge accelerations could significantly mediate the impact on most outcomes except anxiety, and frailty could not mediate the impact on T2D.

CONCLUSION

Biological aging could capture and mediate the late-life health risks stemming from the early-life risks, and could be potentially targeted for healthy longevity promotion.

A blood biomarker of the pace of aging is associated with brain structure: replication across three cohorts

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3380; total N individuals=2322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, greater burden of white matter microlesions, and thinner cortex. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

Exposure to ambient temperature and heat index in relation to DNA methylation age: A population-based study in Taiwan

BACKGROUND

Climate change caused an increase in ambient temperature in the past decades. Exposure to high ambient temperature could result in biological aging, but relevant studies in a warm environment were lacking. We aimed to study the exposure effects of ambient temperature and heat index (HI) in relation to age acceleration in Taiwan, a subtropical island in Asia.

METHODS

The study included 2,084 participants from Taiwan Biobank. Daily temperature and relative humidity data were collected from weather monitoring stations. Individual residential exposure was estimated by ordinary kriging. Moving averages of ambient temperature and HI from 1 to 180 days prior to enrollment were calculated to estimate the exposure effects in multiple time periods. Age acceleration was defined as the difference between DNA methylation age and chronological age. DNA methylation age was calculated by the Horvath's, Hannum's, Weidner's, ELOVL2, FHL2, phenotypic (Pheno), Skin & blood, and GrimAge2 (Grim2) DNA methylation age algorithms. Multivariable linear regression models, generalized additive models (GAMs), and distributed lag non-linear models (DLNMs) were conducted to estimate the effects of ambient temperature and HI exposures in relation to age acceleration.

RESULTS

Exposure to high ambient temperature and HI were associated with increased age acceleration, and the associations were stronger in prolonged exposure. The heat stress days with maximum HI in caution (80-90°F), extreme caution (90-103°F), danger (103-124°F), and extreme danger (>124°F) were also associated with increased age acceleration, especially in the extreme danger days. Each extreme danger day was associated with 571.38 (95 % CI: 42.63-1100.13), 528.02 (95 % CI: 36.16-1019.87), 43.9 (95 % CI: 0.28-87.52), 16.82 (95 % CI: 2.36-31.28) and 15.52 (95 % CI: 2.17-28.88) days increase in the Horvath's, Hannum's, Weidner's, Pheno, and Skin & blood age acceleration, respectively.

CONCLUSION

High ambient temperature and HI may accelerate biological aging.

Body Size, Diet Quality, and Epigenetic Aging: Cross-Sectional and Longitudinal Analyses

Epigenetic age is an emerging marker of health that is highly predictive of disease and mortality risk. There is a lack of evidence on whether lifestyle changes are associated with changes in epigenetic aging. We used data from 1 041 participants in the Melbourne Collaborative Cohort Study with blood DNA methylation measures at baseline (1990-1994, mean age: 57.4 years) and follow-up (2003-2007, mean age: 68.8 years). The Alternative Healthy Eating Index-2010 (AHEI-2010), the Mediterranean Dietary Score, and the Dietary Inflammatory Index were used as measures of diet quality, and weight, waist circumference, and waist-to-hip ratio as measures of body size. Five age-adjusted epigenetic aging measures were considered: GrimAge, PhenoAge, PCGrimAge, PCPhenoAge, and DunedinPACE. Multivariable linear regression models including restricted cubic splines were used to assess the cross-sectional and longitudinal associations of body size and diet quality with epigenetic aging. Associations between weight and epigenetic aging cross-sectionally at both time points were positive and appeared greater for DunedinPACE (per SD: β ~0.24) than for GrimAge and PhenoAge (β ~0.10). The longitudinal associations with weight change were markedly nonlinear (U-shaped) with stable weight being associated with the lowest epigenetic aging at follow-up, except for DunedinPACE, for which only weight gain showed a positive association. We found negative, linear associations for AHEI-2010 both cross-sectionally and longitudinally. Other adiposity measures and dietary scores showed similar results. In middle-aged to older adults, declining diet quality and weight gain may increase epigenetic age, while the association for weight loss may require further investigation. Our study sheds light on the potential of weight management and dietary improvement in slowing aging processes.

Better Life's Essential 8 contributes to slowing the biological aging process: a cross-sectional study based on NHANES 2007-2010 data

Objective

To investigate the relationship between Life's Essential 8 (LE8) and Phenotypic Age Acceleration (PhenoAgeAccel) in United States adults and to explore the impact of LE8 on phenotypic biological aging, thereby providing references for public health policies and health education.

Methods

Utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2010, this cross-sectional study analyzed 7,339 adults aged 20 and above. Comprehensive assessments of LE8, PhenoAgeAccel, and research covariates were achieved through the integration of Demographics Data, Dietary Data, Laboratory Data, and Questionnaire Data derived from NHANES. Weighted generalized linear regression models and restricted cubic spline plots were employed to analyze the linear and non-linear associations between LE8 and PhenoAgeAccel, along with gender subgroup analysis and interaction effect testing.

Results

(1) Dividing the 2007-2010 NHANES cohort into quartiles based on LE8 unveiled significant disparities in age, gender, race, body mass index, education level, marital status, poverty-income ratio, smoking and drinking statuses, diabetes, hypertension, hyperlipidemia, phenotypic age, PhenoAgeAccel, and various biological markers (p < 0.05). Mean cell volume demonstrated no intergroup differences (p > 0.05). (2) The generalized linear regression weighted models revealed a more pronounced negative correlation between higher quartiles of LE8 (Q2, Q3, and Q4) and PhenoAgeAccel compared to the lowest LE8 quartile in both crude and fully adjusted models (p < 0.05). This trend was statistically significant (p < 0.001) in the full adjustment model. Gender subgroup analysis within the fully adjusted models exhibited a significant negative relationship between LE8 and PhenoAgeAccel in both male and female participants, with trend tests demonstrating significant results (p < 0.001 for males and p = 0.001 for females). (3) Restricted cubic spline (RCS) plots elucidated no significant non-linear trends between LE8 and PhenoAgeAccel overall and in gender subgroups (p for non-linear > 0.05). (4) Interaction effect tests denoted no interaction effects between the studied stratified variables such as age, gender, race, education level, and marital status on the relationship between LE8 and PhenoAgeAccel (p for interaction > 0.05). However, body mass index and diabetes manifested interaction effects (p for interaction < 0.05), suggesting that the influence of LE8 on PhenoAgeAccel might vary depending on an individual's BMI and diabetes status.

Conclusion

This study, based on NHANES data from 2007-2010, has revealed a significant negative correlation between LE8 and PhenoAgeAccel, emphasizing the importance of maintaining a healthy lifestyle in slowing down the biological aging process. Despite the limitations posed by the study's design and geographical constraints, these findings provide a scientific basis for the development of public health policies focused on healthy lifestyle practices. Future research should further investigate the causal mechanisms underlying the relationship between LE8 and PhenoAgeAccel and consider cross-cultural comparisons to enhance our understanding of healthy aging.

Educational Mobility, Pace of Aging, and Lifespan Among Participants in the Framingham Heart Study

Importance

People who complete more education live longer lives with better health. New evidence suggests that these benefits operate through a slowed pace of biological aging. If so, measurements of the pace of biological aging could offer intermediate end points for studies of how interventions to promote education will affect healthy longevity.

Objective

To test the hypothesis that upward educational mobility is associated with a slower pace of biological aging and increased longevity.

Design, Setting, and Participants

This prospective cohort study analyzed data from 3 generations of participants in the Framingham Heart Study: (1) the original cohort, enrolled beginning in 1948; (2) the Offspring cohort, enrolled beginning in 1971; and (3) the Gen3 cohort, enrolled beginning in 2002. A 3-generation database was constructed to quantify intergenerational educational mobility. Mobility data were linked with blood DNA-methylation data collected from the Offspring cohort in 2005 to 2008 (n = 1652) and the Gen3 cohort in 2009 to 2011 (n = 1449). Follow-up is ongoing. Data analysis was conducted from June 2022 to November 2023 using data obtained from the National Institutes of Health database of Genotypes and Phenotypes (dbGaP).

Exposure

Educational mobility was measured by comparing participants' educational outcomes with those of their parents.

Main Outcomes and Measures

The pace of biological aging was measured from whole-blood DNA-methylation data using the DunedinPACE epigenetic clock. For comparison purposes, the analysis was repeated using 4 other epigenetic clocks. Survival follow-up was conducted through 2019.

Results

This study analyzed data from 3101 participants from the Framingham Heart Study; 1652 were in the Offspring cohort (mean [SD] age, 65.57 [9.22] years; 764 [46.2%] male) and 1449 were in the Gen3 cohort (mean [SD] age, 45.38 [7.83] years; 691 [47.7%] male). Participants who were upwardly mobile in educational terms tended to have slower pace of aging in later life (r = -0.18 [95% CI, -0.23 to -0.13]; P < .001). This pattern of association was similar across generations and held in within-family sibling comparisons. There were 402 Offspring cohort participants who died over the follow-up period. Upward educational mobility was associated with lower mortality risk (hazard ratio, 0.89 [95% CI, 0.81 to 0.98]; P = .01). Slower pace of aging accounted for approximately half of this association.

Conclusions and Relevance

This cohort study's findings support the hypothesis that interventions to promote educational attainment may slow the pace of biological aging and promote longevity. Epigenetic clocks have potential as near-term outcome measures of intervention effects on healthy aging. Experimental evidence is needed to confirm findings.

Polygenic risk for schizophrenia, social dispositions, and pace of epigenetic aging: Results from the Young Finns Study

Schizophrenia is often regarded as a disorder of premature aging. We investigated (a) whether polygenic risk for schizophrenia (PRSsch ) relates to pace of epigenetic aging and (b) whether personal dispositions toward active and emotionally close relationships protect against accelerated epigenetic aging in individuals with high PRSsch . The sample came from the population-based Young Finns Study (n = 1348). Epigenetic aging was measured with DNA methylation aging algorithms such as AgeAccelHannum , EEAAHannum , IEAAHannum , IEAAHorvath , AgeAccelHorvath , AgeAccelPheno , AgeAccelGrim , and DunedinPACE. A PRSsch was calculated using summary statistics from the most comprehensive genome-wide association study of schizophrenia to date. Social dispositions were assessed in terms of extraversion, sociability, reward dependence, cooperativeness, and attachment security. We found that PRSsch did not have a statistically significant effect on any studied indicator of epigenetic aging. Instead, PRSsch had a significant interaction with reward dependence (p = 0.001-0.004), cooperation (p = 0.009-0.020), extraversion (p = 0.019-0.041), sociability (p = 0.003-0.016), and attachment security (p = 0.007-0.014) in predicting AgeAccelHannum , EEAAHannum , or IEAAHannum . Specifically, participants with high PRSsch appeared to display accelerated epigenetic aging at higher (vs. lower) levels of extraversion, sociability, attachment security, reward dependence, and cooperativeness. A rather opposite pattern was evident for those with low PRSsch . No such interactions were evident when predicting the other indicators of epigenetic aging. In conclusion, against our hypothesis, frequent social interactions may relate to accelerated epigenetic aging in individuals at risk for psychosis. We speculate that this may be explained by social-cognitive impairments (perceiving social situations as overwhelming or excessively arousing) or ending up in less supportive or deviant social groups.

Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell-type deconvolution applied to human blood epigenetic clocks

Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.

Association of Epigenetic Age and Everyday Discrimination With Longitudinal Trajectories of Chronic Health Conditions in Older Adults

We investigated the strength of the association between baseline epigenetic age, everyday discrimination, and trajectories of chronic health conditions (CHCs) across 3 study waves, among adults 50 years of age and older. We used 2016-2020 data from the Health and Retirement Study (HRS). Data for the PhenoAge and DNAm GrimAge second-generation epigenetic clocks were from the 2016 HRS Venous Blood Study. CHC trajectories were constructed using latent class growth curve models. Multinomial logistic regression models assessed the strength of the association between accelerated epigenetic age, everyday discrimination, and the newly constructed CHC trajectories for participants with complete data (n = 2 893). In the fully adjusted model, accelerated PhenoAge (relative risk ratios [RRR] = 2.53, 95% confidence interval [95% CI] = 1.81, 3.55) and DNAm GrimAge (RRR = 2.79, 95% CI = 1.95, 4.00) were associated with classification into the high CHC trajectory class. Racial disparities were evident, with increased risk of classification into the high trajectory class for Black (PhenoAge: RRR = 1.69, 95% CI = 1.07, 2.68) and reduced risk for Hispanic (PhenoAge: RRR = 0.32, 95% CI = 0.16, 0.64; DNAm GrimAge: RRR = 0.34, 95% CI = 0.17, 0.68), relative to White participants. Everyday discrimination was associated with classification into the medium-high (RRR = 1.28, 95% CI = 1.00, 1.64) and high (RRR = 1.52, 95% CI = 1.07, 2.16) trajectory classes in models assessing DNAm GrimAge. More research is needed to better understand the longitudinal health outcomes of accelerated aging and adverse social exposures. Such research may provide insights into vulnerable adults who may need varied welfare supports earlier than the mandated chronological age for access to federal and state resources.

Epigenetic aging in older people living with HIV in Eswatini: a pilot study of HIV and lifestyle factors and epigenetic aging

BACKGROUND

People living with HIV (PLHIV) on effective antiretroviral therapy are living near-normal lives. Although they are less susceptible to AIDS-related complications, they remain highly vulnerable to non-communicable diseases. In this exploratory study of older PLHIV (OPLHIV) in Eswatini, we investigated whether epigenetic aging (i.e., the residual between regressing epigenetic age on chronological age) was associated with HIV-related parameters, and whether lifestyle factors modified these relationships. We calculated epigenetic aging focusing on the Horvath, Hannum, PhenoAge and GrimAge epigenetic clocks, and a pace of biological aging biomarker (DunedinPACE) among 44 OPLHIV in Eswatini.

RESULTS

Age at HIV diagnosis was associated with Hannum epigenetic age acceleration (EAA) (β-coefficient [95% Confidence Interval]; 0.53 [0.05, 1.00], p = 0.03) and longer duration since HIV diagnosis was associated with slower Hannum EAA (- 0.53 [- 1.00, - 0.05], p = 0.03). The average daily dietary intake of fruits and vegetables was associated with DunedinPACE (0.12 [0.03, 0.22], p = 0.01). The associations of Hannum EAA with the age at HIV diagnosis and duration of time since HIV diagnosis were attenuated when the average daily intake of fruits and vegetables or physical activity were included in our models. Diet and self-perceived quality of life measures modified the relationship between CD4+ T cell counts at participant enrollment and Hannum EAA.

CONCLUSIONS

Epigenetic age is more advanced in OPLHIV in Eswatini in those diagnosed with HIV at an older age and slowed in those who have lived for a longer time with diagnosed HIV. Lifestyle and quality of life factors may differentially affect epigenetic aging in OPLHIV. To our knowledge, this is the first study to assess epigenetic aging in OPLHIV in Eswatini and one of the few in sub-Saharan Africa.

Self-control is associated with health-relevant disparities in buccal DNA-methylation measures of biological aging in older adults

Self-control is a personality dimension that is associated with better physical health and a longer lifespan. Here, we examined (1) whether self-control is associated with buccal and saliva DNA-methylation (DNAm) measures of biological aging quantified in children, adolescents, and adults, and (2) whether biological aging measured in buccal DNAm is associated with self-reported health. Following preregistered analyses, we computed two DNAm measures of advanced biological age (principal-component PhenoAge and GrimAge Acceleration) and a DNAm measure of pace of aging (DunedinPACE) in buccal samples from the German Socioeconomic Panel Study (SOEP-G[ene], n = 1058, age range 0-72, Mage = 42.65) and saliva samples from the Texas Twin Project (TTP, n = 1327, age range 8-20, Mage = 13.50). We found that lower self-control was associated with advanced biological age in older adults (PhenoAge Acceleration β = - .34, [- .51, - .17], p < .001; GrimAge Acceleration β = - .34, [- .49, - .19], p < .001), but not young adults, adolescents or children. These associations remained statistically robust even after correcting for possible confounders such as socioeconomic contexts, BMI, or genetic correlates of low self-control. Moreover, a faster pace of aging and advanced biological age measured in buccal DNAm were associated with self-reported disease (PhenoAge Acceleration: β = .13 [.06, .19], p < .001; GrimAge Acceleration: β = .19 [.12, .26], p < .001; DunedinPACE: β = .09 [.02, .17], p = .01). However, effect sizes were weaker than observations in blood, suggesting that customization of DNAm aging measures to buccal and saliva tissues may be necessary. Our findings are consistent with the hypothesis that self-control is associated with health via pathways that accelerate biological aging in older adults.

Epigenetic age acceleration is associated with speed of pubertal growth but not age of pubertal onset

Using data from a longitudinal cohort of children, we examined whether epigenetic age acceleration (EAA) was associated with pubertal growth and whether these associations were mediated by adiposity. We examined associations between EAA at approximately 10 years of age with pubertal growth metrics, including age at peak height velocity (PHV), PHV, and sex steroid levels and whether these associations were mediated by measures of adiposity including body mass index (BMI) and MRI-assessed visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Children (n = 135) with accelerated EAA had higher PHV (β 0.018, p = 0.0008) although the effect size was small. The association between EAA and age at PHV was not significant (β  - 0.0022, p = 0.067). Although EAA was associated with higher BMI (β 0.16, p = 0.0041), VAT (β 0.50, p = 0.037), and SAT (β 3.47, p = 0.0076), BMI and VAT did not mediate associations between EAA and PHV, while SAT explained 8.4% of the association. Boys with higher EAA had lower total testosterone (β  - 12.03, p = 0.0014), but associations between EAA and other sex steroids were not significant, and EAA was not associated with sex steroid levels in girls. We conclude that EAA did not have strong associations with either age at onset of puberty or pubertal growth speed, although associations with growth speed were statistically significant. Studies with larger sample sizes are needed to confirm this pattern of associations.

Validation of biomarkers of aging

The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.

Sex-Specific Associations between Prenatal Exposure to Di(2-ethylhexyl) Phthalate, Epigenetic Age Acceleration, and Susceptibility to Early Childhood Upper Respiratory Infections

Di(2-ethylhexyl) phthalate (DEHP) is a common plasticizer that can affect immune system development and susceptibility to infection. Aging processes (measured as epigenetic age acceleration (EAA)) may mediate the immune-related effects of prenatal exposure to DEHP. This study's objective was to examine associations between prenatal DEHP exposure, EAA at three months of age, and the number of upper respiratory infections (URIs) from 12 to 18 months of age using a sample of 69 maternal-child pairs from a Canadian pregnancy cohort. Blood DNA methylation data were generated using the Infinium HumanMethylation450 BeadChip; EAA was estimated using Horvath's pan-tissue clock. Robust regressions examined overall and sex-specific associations. Higher prenatal DEHP exposure (B = 6.52, 95% CI = 1.22, 11.81) and increased EAA (B = 2.98, 95% CI = 1.64, 4.32) independently predicted more URIs. In sex-specific analyses, some similar effects were noted for boys, and EAA mediated the association between prenatal DEHP exposure and URIs. In girls, higher prenatal DEHP exposure was associated with decreased EAA, and no mediation was noted. Higher prenatal DEHP exposure may be associated with increased susceptibility to early childhood URIs, particularly in boys, and aging biomarkers such as EAA may be a biological mechanism. Larger cohort studies examining the potential developmental immunotoxicity of phthalates are needed.

Quantitative relationships of FAM50B and PTCHD3 methylation with reduced intelligence quotients in school aged children exposed to lead: Evidence from epidemiological and in vitro studies

At present, the application of DNA methylation (DNAm) biomarkers in environmental health risk assessment (EHRA) is more challenging due to the unclearly quantitative relationship between them. We aimed to explore the role of FAM50B and PTCHD3 at the level of signaling pathways, and establish the quantitative relationship between them and children's intelligence quotients (IQs). DNAm of target regions was measured in multiple cell models and was compared with the human population data. Then the dose-response relationships of lead exposure with neurotoxicity and DNAm were established by benchmark dose (BMD) model, followed by potential signaling pathway screening. Results showed that there was a quantitative linear relationship between children's IQs and FAM50B/PTCHD3 DNAm (DNAm between 51.40 % - 78.78 % and 31.41 % - 74.19 % for FAM50B and PTCHD3, respectively), and this relationship was more significant when children's IQs > 90. The receiver operating characteristic (ROC) and calibration curves showed that FAM50B/PTCHD3 DNAm had a satisfying accuracy and consistency in predicting children's IQs, which was confirmed by sensitivity analysis of gender and CpG site grouping data. In cell experiments, there was also a quantitative linear relationship between FAM50B DNAm and reactive oxygen species (ROS) production, which was mediated by PI3K-AKT signaling pathway. In addition, the lead BMD of ROS was close to that of FAM50B DNAm, suggesting that FAM50B DNAm was a suitable biomarker for the risk assessments of adverse outcomes induced by lead. Taken collectively, these results suggest that FAM50B/PTCHD3 can be applied to EHRA and the prevention/intervention of adverse effects of lead on children's IQs.

Epigenetic aging & embodying injustice: US My Body My Story and Multi-Ethnic Atherosclerosis Study

Importance

Epigenetic accelerated aging is associated with exposure to social and economic adversity and may increase risk of premature morbidity and mortality. However, no studies have included measures of structural racism and few have compared estimates within or across the 1st and 2nd generation of epigenetic clocks (the latter additionally trained on phenotypic data).

Objective

To determine if accelerated epigenetic aging is associated with exposures to diverse measures of racialized, economic, and environmental injustice measured at different levels and time periods.

Design

Cross-sectional My Body My Story Study (MBMS; US, 2008-2010) and Exam 5 Multi-Ethnic Atherosclerosis Study (MESA; US, 2010-2012). MBMS DNA extraction: 2021; linkage of structural measures to MBMS and MESA: 2022.

Setting

MBMS recruited a random sample of US-born Black non-Hispanic (BNH) and white non-Hispanic (WNH) participants from 4 community health centers in Boston, MA. The MESA Exam 5 epigenetic component included 975 randomly selected US-born BNH, WNH, and Hispanic participants from four field sites: Baltimore, MD; Forsyth County, NC; New York City, NY; St. Paul, MN.

Participants

US-born persons (MBMS: 224 BNH, 69 WNH; MESA: 229 BNH, 555 WNH, 191 Hispanic).

Main outcome and measures

10 epigenetic clocks (six 1st generation; four 2nd generation), computed using DNA methylation data (DNAm) from blood spots (MBMS; N = 293) and purified monocytes (MESA; N = 975).

Results

Among Black non-Hispanic MBMS participants, epigenetic age acceleration was associated with being born in a Jim Crow state by 0.14 standard deviations (95% confidence interval [CI] 0.00, 0.27) and with birth state conservatism (0.06, 95% CI 0.00, 0.05), pooling across all clocks, as was low parental education for both Black non-Hispanic and white non-Hispanic MBMS participants (respectively: 0.24, 95% CI 0.08, 0.39, and 0.27, 95% CI 0.03, 0.51. Adult impoverishment was positively associated with the pooled 2nd generation clocks among the MESA participants (Black non-Hispanic: 0.06, 95% CI 0.01, 0.12; white non-Hispanic: 0.05, 95% CI 0.01, 0.08; Hispanic: 0.07, 95% CI 0.01, 0.14).

Conclusions and Relevance

Epigenetic accelerated aging may be one of the biological mechanisms linking exposure to racialized and economic injustice to well-documented inequities in premature morbidity and mortality.

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.

Air pollution, dementia, and lifespan in the socio-economic gradient of aging: perspective on human aging for planning future experimental studies

Air pollution (AirPoll) accelerates human aging, as assessed by increased adult mortality and earlier onset of cardiovascular diseases, and dementia. Socio-economic strata (SES) of wealth and education have parallel differences of mortality and these diseases. Children from impoverished homes differ in brain development at birth and in risk of early fat excess and hypertension. To further enhance the healthspan, biogerontologists may consider a wider range of environmental exposures from gestation through later life morbidity that comprise the Gero-Exposome. Experimental studies with rodents and nematodes document shared transcriptional responses to AirPoll. In rodents, AirPoll exposure activates gene systems for body-wide detoxification through Nrf2 and NFkB transcription factors that mediate multiple aging processes. Gestational environmental factors include maternal diet and exposure to AirPoll and cigarette smoke. Correspondingly, gestational exposure of mice to AirPoll increased adult body fat, impaired glucose clearance, and decreased adult neurogenesis in the hippocampus, a brain region damaged in dementia. Nematode larvae also respond to AirPoll with Alzheimer relevant responses. These experimental approaches could identify to interventions for expanded human health and longevity across SES gradients.

Associations of essential trace elements with epigenetic aging indicators and the potential mediating role of inflammation

BACKGROUND

Essential trace elements (ETEs) play essential roles in vital functions, but their effects on epigenetic aging remain poorly understood.

OBJECTIVES

This study aimed to investigate the associations of ETEs with four epigenetic aging indicators and assess the potential mediating role of inflammation.

METHODS

We recruited 93 individuals from hospitals between October 2018 and August 2019. Plasma levels of cobalt, copper, iron, manganese, molybdenum, selenium, and zinc were measured by ICP-MS, and leukocyte DNA methylation levels were measured using Illumina MethylationEPIC beadchip. Linear regression was used to estimate the association between seven plasma ETEs and epigenetic aging indicators. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) models were used to evaluate the effect of ETEs mixtures. Inflammatory status was assessed using four systemic inflammation indices (neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and systemic immune-inflammation index (SII)) and three cytokines (IL-4, IL-6, and IL-13). Mediation analysis was performed to explore the role of inflammation in the above associations.

RESULTS

Plasma Se levels were significantly negatively associated with DunedinPACE, whereas Cu levels were significantly positively associated with it. Both WQS regression and BKMR models suggested that Se and Cu dominate the effect of the ETEs mixture. MLR and interleukin 6 were significantly and positively associated with DunedinPACE. Further mediation analysis indicated that inflammation partially mediated the association between ETEs and DunedinPACE.

DISCUSSION

Plasma Se and Cu levels are closely associated to epigenetic aging, and inflammation might be a potential mechanism underlying this relationship. These findings contribute to the prevention of health hazards associated with population aging.

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.

Epigenetic aging in older people living with HIV in Eswatini: a pilot study of HIV and lifestyle factors and epigenetic aging

Background

People living with HIV (PLHIV) on effective antiretroviral therapy (ART) are living near-normal lives. Although they are less susceptible to AIDS-related complications, they remain highly vulnerable to non-communicable diseases (NCD). In this exploratory study of older PLHIV (OPLHIV) in Eswatini, we investigated whether biological aging (i.e., the difference between epigenetic age and chronological age, termed 'epigenetic age acceleration [EAA]') was associated with HIV-related parameters, and whether lifestyle factors modified these relationships. We calculated EAA focusing on the second-generation epigenetic clocks, PhenoAge and GrimAge, and a pace of aging biomarker (DunedinPACE) among 44 OPLHIV in Eswatini.

Results

Among participants, the PhenoAge clock showed older epigenetic age (68 years old [63, 77]) but a younger GrimAge epigenetic age (median=56 years old [interquartile range=50, 61]) compared to the chronological age (59 years old [54, 66]). Participants diagnosed with HIV at an older age showed slower DunedinPACE (β-coefficient [95% Confidence Interval]; -0.02 [-0.04, -0.01], p=0.002) and longer duration since HIV diagnosis was associated with faster DunedinPACE (0.02 [0.01, 0.04], p=0.002). The average daily dietary intake of fruits and vegetables was associated with faster DunedinPACE (0.12 [0.03, 0.22], p=0.01) and modified the relationship between HIV status variables (number of years living with HIV since diagnosis, age at HIV diagnosis, CD4+ T cell counts) and PhenoAge EAA, and DunedinPACE.

Conclusions

Biological age is accelerated in OPLHIV in Eswatini, with those living with HIV for a longer duration at risk for faster biological aging. Lifestyle factors, especially healthier diets, may attenuate biological aging in OPLHIV. To our knowledge, this is the first study to assess biological aging in Eswatini and one of the few in sub-Saharan Africa.

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

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

Biological age is superior to chronological age in predicting hospital mortality of the critically ill

Biological age is increasingly recognized as being more accurate than chronological age in determining chronic health outcomes. This study assessed whether biological age, assessed on intensive care unit (ICU) admission, can predict hospital mortality. This retrospective cohort study, conducted in a tertiary multidisciplinary ICU in Western Australia, used the Levine PhenoAge model to estimate each patient's biological age (also called PhenoAge). Each patient's PhenoAge was calibrated to generate a regression residual which was equivalent to biological age unexplained by chronological age in the local context. PhenoAgeAccel was a dichotomized measure of the residuals, and its presence suggested that one was biologically older than the corresponding chronological age. Of the 2950 critically ill adult patients analyzed, 291 died (9.9%) before hospital discharge. Both PhenoAge and its residuals (after regressing on chronological age) had a significantly better ability to differentiate between hospital survivors and non-survivors than chronological age (area under the receiver-operating-characteristic curve 0.648 and 0.654 vs. 0.547 respectively). Being phenotypically older than one's chronological age was associated with an increased risk of mortality (PhenoAgeAccel hazard ratio [HR] 1.997, 95% confidence interval [CI] 1.568-2.542; p = 0.001) in a dose-related fashion and did not reach a plateau until at least a 20-year gap. This adverse association remained significant (adjusted HR 1.386, 95% CI 1.077-1.784; p = 0.011) after adjusted for severity of acute illness and comorbidities. PhenoAgeAccel was more prevalent among those with pre-existing chronic cardiovascular disease, end-stage renal failure, cirrhosis, immune disease, diabetes mellitus, or those treated with immunosuppressive therapy. Being phenotypically older than one's chronological age was more common among those with comorbidities, and this was associated with an increased risk of mortality in a dose-related fashion in the critically ill that was not fully explained by comorbidities and severity of acute illness.

Effect of women's fertility and sexual development on epigenetic clock: Mendelian randomization study

BACKGROUND AND OBJECTIVES

In observational studies, women's fertility and sexual development traits may have implications for DNA methylation patterns, and pregnancy-related risk factors can also affect maternal DNA methylation patterns. The aim of our study is to disentangle any potential causal associations between women's fertility and sexual development traits and epigenetic clocks, as well as to search for probable mediators by using the Mendelian randomization (MR) method.

METHODS

Instrumental variables for exposures, mediators, and outcomes were adopted from genome-wide association studies data of European ancestry individuals. The potential causal relationship between women's fertility and sexual development traits and four epigenetic clocks were evaluated by inverse variance weighted method and verified by other two methods. Furthermore, we employed multivariable MR (MVMR) adjusting for hypertension, hyperglycemia, BMI changes, and insomnia. Then, combining the MVMR results and previous research, we performed two-step MR to explore the mediating effects of BMI, AFS, and AFB. Multiple sensitivity analyses were further performed to verify the robustness of our findings.

RESULTS

Leveraging two-sample MR analysis, we observed statistically significant associations between earlier age at first birth (AFB) with a higher HannumAge, PhenoAge and GrimAge acceleration(β = - 0.429, 95% CI [- 0.781 to - 0.077], p = 0.017 for HannumAge; β = - 0.571, 95% CI [- 1.006 to - 0.136], p = 0.010 for PhenoAge, and β = - 1.136, 95% CI [- 1.508 to - 0.765], p = 2.03E-09 for GrimAge respectively) and age at first sexual intercourse (AFS) with a higher HannumAge and GrimAge acceleration(β = - 0.175, 95% CI [- 0.336 to - 0.014], p = 0.033 for HannumAge; β = - 0.210, 95% CI [- 0.350 to - 0.070], p = 0.003 for GrimAge, respectively). Further analyses indicated that BMI, AFB and AFS played mediator roles in the path from women's fertility and sexual development traits to epigenetic aging.

CONCLUSIONS

Our study suggested that AFS and AFB are associated with epigenetic aging. These findings may prove valuable in informing the development of prevention strategies and interventions targeted towards women's fertility and sexual development experiences and their relationship with epigenetic aging-related diseases.

A blood biomarker of accelerated aging in the body associates with worse structural integrity in the brain: replication across three cohorts

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3,380; total N individuals=2,322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, and thinner cortex. In two datasets, faster DunedinPACE was associated with greater burden of white matter hyperintensities. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.