Associations of socioeconomic disparities with buccal DNA-methylation measures of biological aging

Social determinants of health and epigenetic clocks: Meta-analysis of 140 studies

Social determinants of health are social factors that affect health and survival. Two of the most powerful social determinants are socioeconomic status (SES) and race/ethnicity; people with lower SES or marginalized race/ethnicity tend to experience earlier onset of aging-related diseases and have shorter lifespans. DNA methylation (DNAm) measures of biological aging, often referred to as "epigenetic clocks", are increasingly used to study the social determination of health. However, there are several generations of epigenetic clocks and it remains unclear which are most sensitive to social factors affecting health. Moreover, there is uncertainty about how technical factors, such as the tissue from which DNA is derived or the technology used to measure DNA methylation may affect associations of social determinants with epigenetic clocks. We conducted a pre-registered multi-level meta-analysis of 140 studies, including N = 65,919 participants, encompassing 1,065 effect sizes for associations of SES and racial/ethnic identity with three generations of epigenetic clocks. We found that associations were weakest for the first generation of epigenetic clocks developed to predict age differences between people. Associations were stronger for the second generation of epigenetic clocks developed to predict mortality and health risks. The strongest associations were observed for a third generation of epigenetic clocks, sometimes referred to as "epigenetic speedometers", developed to predict the pace of aging. In studies of children, only the speedometers showed significant associations with SES. Effects of sex and technical factors were minimal and there was no evidence of publication bias.

Genetic and environmental contributions to epigenetic aging across adolescence and young adulthood

BACKGROUND

Epigenetic aging estimators commonly track chronological and biological aging, quantifying its accumulation (i.e., epigenetic age acceleration) or speed (i.e., epigenetic aging pace). Their scores reflect a combination of inherent biological programming and the impact of environmental factors, which are suggested to vary at different life stages. The transition from adolescence to adulthood is an important period in this regard, marked by an increasing and, then, stabilizing epigenetic aging variance. Whether this pattern arises from environmental influences or genetic factors is still uncertain. This study delves into understanding the genetic and environmental contributions to variance in epigenetic aging across these developmental stages. Using twin modeling, we analyzed four estimators of epigenetic aging, namely Horvath Acceleration, PedBE Acceleration, GrimAge Acceleration, and DunedinPACE, based on saliva samples collected at two timepoints approximately 2.5 years apart from 976 twins of four birth cohorts (aged about 9.5, 15.5, 21.5, and 27.5 years at first and 12, 18, 24, and 30 years at second measurement occasion).

RESULTS

Half to two-thirds (50-68%) of the differences in epigenetic aging were due to unique environmental factors, indicating the role of life experiences and epigenetic drift, besides measurement error. The remaining variance was explained by genetic (Horvath Acceleration: 24%; GrimAge Acceleration: 32%; DunedinPACE: 47%) and shared environmental factors (Horvath Acceleration: 26%; PedBE Acceleration: 47%). The genetic and shared environmental factors represented the primary sources of stable differences in corresponding epigenetic aging estimators over 2.5 years. Age moderation analyses revealed that the variance due to individually unique environmental sources was smaller in younger than in older cohorts in epigenetic aging estimators trained on chronological age (Horvath Acceleration: 47-49%; PedBE Acceleration: 33-68%). The variance due to genetic contributions, in turn, potentially increased across age groups for epigenetic aging estimators trained in adult samples (Horvath Acceleration: 18-39%; GrimAge Acceleration: 24-43%; DunedinPACE: 42-57%).

CONCLUSIONS

Transition to adulthood is a period of the increasing variance in epigenetic aging. Both environmental and genetic factors contribute to this trend. The degree of environmental and genetic contributions can be partially explained by the design of epigenetic aging estimators.

Pubertal timing as a predictor of epigenetic aging and mortality risk in young adulthood

Early pubertal timing is associated with adverse health in adulthood. These effects may be mediated by DNA methylation changes associated with accelerated cellular aging and mortality risk, but few studies tested associations between pubertal timing and epigenetic markers in adulthood. Additionally, pubertal timing effects often vary by sex and are understudied in diverse youth. Thus, this longitudinal study examined links between pubertal timing and later epigenetic aging and mortality risk together with sex differences in predominantly Black youth. Participants included 350 individuals (58% female, 42% male; 80% Black, 19% non-Hispanic White). Perceived pubertal timing relative to peers and self-reported phenotypic pubertal timing based on age-adjusted Tanner scores were assessed during early adolescence (Mage = 13) whereas epigenetic aging (GrimAge, DunedinPace of Aging Calculated from the Epigenome, and PhenoAge) and mortality risk were measured during young adulthood (Mage = 27). After adjusting for covariates (smoking, body mass index, family income, early-life stress, race/ethnicity, sex, parenthood), early pubertal timing (both perceived and phenotypic) predicted higher epigenetic mortality risk, and early phenotypic pubertal timing predicted accelerated DunedinPace of Aging Calculated from the Epigenome. Both perceived and phenotypic early pubertal timing were correlated with accelerated GrimAge. Off-time phenotypic pubertal timing (i.e., early and late) was associated with accelerated PhenoAge in males only whereas perceived off-time pubertal timing was unexpectedly linked with lower PhenoAge acceleration. These findings extend prior research by linking two dimensions of early pubertal timing with epigenetic mortality risk and accelerated aging in racially diverse young adults and showing nonlinear effects on PhenoAge acceleration that differ across pubertal timing measures and show some sex differences. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Is virtue its own reward? Moral identity, empathy, and volunteering during adolescence as predictors of subsequent epigenetic aging

Higher levels of moral identity, empathy, and volunteering (virtues) are associated with increased self-esteem and psychological well-being, which, in turn, are predictive of fewer health problems. Epigenetic aging, a marker of health, reflects the rate at which individuals age biologically relative to their chronological age. Epigenetic aging is shaped by behavioral factors and environmental stressors, but the effects of moral identity, empathy, and volunteering on epigenetic aging are underexplored. Thus, this study examined if these three dimensions of virtue predict epigenetic aging during adolescence and if these relationships are mediated by self-esteem and psychological well-being. The sample included 1,213 adolescents (51% female; 62% Black, 34% Non-Hispanic White, 4% Other race/ethnicity) that participated at three time points between 2004 and 2017 (Mage 13, 16, 19 years). Results revealed that higher moral identity and empathy were associated with higher self-esteem and psychological well-being during early adolescence. Moreover, higher empathy during early adolescence was associated with slower epigenetic aging on the GrimAge clock during late adolescence. Path analyses adjusting for covariates showed that higher self-esteem during middle adolescence predicted slower epigenetic aging in late adolescence, but none of the three virtues in early adolescence predicted self-esteem, psychological well-being, or epigenetic aging over time.

Applying blood-derived epigenetic algorithms to saliva: cross-tissue similarity of DNA-methylation indices of aging, physiology, and cognition

BACKGROUND

Epigenetic algorithms of aging, health, and cognition, based on DNA-methylation (DNAm) patterns, are prominent tools for measuring biological age and have been linked to age-related diseases, cognitive decline, and mortality. While most of these methylation profile scores (MPSs) are developed in blood tissue, there is growing interest in using less invasive tissues like saliva. The aim of the current study is to probe the cross-tissue intraclass correlation coefficients (ICCs) of MPSs developed in blood applied to saliva DNAm from the same people. While our primary focus is on MPSs that were previously found to be robustly correlated with social determinants of health, including second- and third-generation clocks and MPSs of physiology and cognition, we also report ICC values for first-generation clocks to enable comparison across metrics. We pooled three publicly available datasets that had both saliva and blood DNAm from the same individuals (total n = 107, aged 5-74 years), corrected MPSs for cell composition within each tissue, and computed the cross-tissue ICCs.

RESULTS

We found that after correcting for cell composition, saliva-blood cross-tissue ICCs were moderate for second- and third-generation indices of aging and MPSs of physiology and cognition. Specifically, PCGrimAge had the highest ICC (0.76), followed by PCPhenoAge (0.72), a measure of cognitive performance (Epigenetic-g, 0.69), DunedinPACE (0.68), PCGrimAge Acceleration (0.67), PCPhenoAge Acceleration (0.66), an MPS of hs-CRP (0.58), and BMI (0.54). These ICCs appear lower than previous reports on within-tissue ICCs (saliva ICCs range from 0.67 to 0.85, blood ICCs range from 0.73 to 0.93). Cross-tissue ICCs values for first-generation biological age acceleration measures were poor, ranging from 0.19 to 0.25.

CONCLUSIONS

Our findings suggest that applying second- and third-generation MPSs of biological age acceleration and related phenotypes developed in blood to saliva DNAm results in moderate cross-tissue similarity and the precise cross-tissue correspondence differs by measure. While the degree of cross-tissue similarity of several MPSs may suffice for some research settings, it may not be suitable in clinical or commercial applications. Collection of both blood and saliva DNAm samples is necessary to validate existing algorithms and to customize MPSs in saliva DNAm.

Epigenetic entropy, social disparity, and health and lifespan in the Women's Health Initiative

The pace of aging varies between individuals and is marked by changes in DNA methylation (DNAm) including an increase in randomness or entropy. Here, we computed epigenetic scores of aging and entropy using DNAm datasets from the Women's Health Initiative (WHI). We investigated how different epigenetic aging metrics relate to demographic and health variables, and mortality risk. Income and education, two proxies of socioeconomics (SE), had consistent associations with epigenetic aging and entropy. Notably, stochastic increases in DNAm at sites targeted by the polycomb proteins were significantly related to both aging and SE. While higher income was associated with reduced age-related DNAm changes in White women, the protective effect of income was diminished in Black and Hispanic women, and on average, Black and Hispanic women had relatively more aged epigenomes. Faster pace of aging, as estimated by the DunedinPACE, predicted higher mortality risk, while the maintenance of methylation at enhancer regions was associated with improved survival. Our findings demonstrate close ties between social and economic factors and aspects of epigenetic aging, suggesting potential biological mechanisms through which societal disparities may contribute to differences in health outcomes and lifespan across demographic groups.

Life-Course Socioeconomic Trajectories and Biological Aging: The Importance of Lifestyles and Physical Wellbeing

BACKGROUND/OBJECTIVES

Studies investigating the associations between life-course socioeconomic status (SES) and biological aging (the difference between biological and chronological age, Δage) have mostly been focused on epigenetic clocks and on a limited number of mediators. The aim of this study was to investigate this relationship using a blood-based aging clock, as well as the potential mediation of different factors including lifestyles or their proxies and physical and mental wellbeing.

METHODS

A deep-learning aging clock based on 36 blood markers was deployed, in a large Italian population cohort: the Moli-sani study (N = 4772; ≥35 years; 48% men). SES was defined as an eight-level trajectory over the life course, which was tested with Δage in linear models incrementally adjusted for age, sex, and prevalent health conditions. Moreover, the proportion of associations explained by diverse potential mediators, including diet, smoking, physical activity, alcohol, body mass index (BMI), and physical and mental quality of life (QoL) was estimated.

RESULTS

Compared to participants with a stably high SES, those showing an educational and financial downward trajectory were older than their CA (β (95%CI) = 1.28 (0.73-1.83) years), as were those with a stably low SES (0.75 (0.25-01.25) years). These associations were largely explained by the tested mediators (overall proportion: 36.2% and 66.3%, respectively), prominently by physical QoL (20.7% and 41.0%), BMI (16.8% and 34.3%), lifestyle (10.6% and 24.6%), and dietary inflammatory score (5.3% and 9.2%).

CONCLUSIONS

These findings indicate that life-course socioeconomic inequalities are associated with accelerated biological aging, suggesting physical wellbeing and pro-inflammatory lifestyles as potential public health targets to slow down this process in susceptible socioeconomic strata of the population.

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.

Cross-Tissue Comparison of Epigenetic Aging Clocks in Humans

Epigenetic clocks are a common group of tools used to measure biological aging - the progressive deterioration of cells, tissues and organs. Epigenetic clocks have been trained almost exclusively using blood-based tissues but there is growing interest in estimating epigenetic age using less-invasive oral-based tissues (i.e., buccal or saliva) in both research and commercial settings. However, differentiated cell types across body tissues exhibit unique DNA methylation landscapes and age-related alterations to the DNA methylome. Applying epigenetic clocks derived from blood-based tissues to estimate epigenetic age of oral-based tissues may introduce biases. We tested the within-person comparability of common epigenetic clocks across five tissue types: buccal epithelial, saliva, dry blood spots, buffy coat (i.e., leukocytes), and peripheral blood mononuclear cells. We tested 284 distinct tissue samples from 83 individuals aged 9-70 years. Overall, there were significant within-person differences in epigenetic clock estimates from oral-based versus blood-based tissues, with average differences of almost 30 years observed in some age clocks. In addition, most epigenetic clock estimates of blood-based tissues exhibited low correlation with estimates from oral-based tissues despite controlling for cellular proportions and other technical factors. Our findings indicate that application of blood-derived epigenetic clocks in oral-based tissues may not yield comparable estimates of epigenetic age, highlighting the need for careful consideration of tissue type when estimating epigenetic age.

Structural racism in primary schools and changes in epigenetic age acceleration among Black and White youth

Structural racism generates racial inequities in U.S. primary education, including segregated schools, inequitable funding and resources, racial disparities in discipline and achievement, and hostile racial climates, which are risk factors for adverse youth health and development. Black youth are disproportionately exposed to adverse school contexts that may become biologically embedded via stress-mediated epigenetic pathways. This study examined whether childhood exposure to adverse school contexts is associated with changes in epigenetic aging during adolescent development. DNA methylation-based epigenetic clocks were calculated from saliva samples at ages 9 and 15 among Black (n = 774) and White (n = 287) youth in the Future of Families and Child Wellbeing Study (2009-2015). We performed latent class analyses to identify race-specific primary school contexts using administrative data on segregation, discipline, achievement, resources, economic disadvantage, and racial harassment. We then estimated change in epigenetic age acceleration from childhood to adolescence across school typologies using GrimAge, PhenoAge, and DunedinPACE epigenetic clocks. Three distinct school contexts were identified for Black youth: segregated and highly-disadvantaged (17.0%), segregated and moderately-disadvantaged (52.1%), and integrated and moderately-disadvantaged (30.8%). Two school contexts emerged for White youth: integrated and unequal (46.5%) and predominantly White & advantaged (53.5%). At age 15, Black youth who attended segregated and highly-disadvantaged primary schools experienced increases in their speed of epigenetic aging with GrimAge and DunedinPACE. Slowed epigenetic aging with GrimAge was observed for Black youth who attended integrated and moderately-disadvantaged schools. School contexts were not associated with changes in epigenetic age acceleration for White youth. Our findings suggest that manifestations of structural racism in primary school contexts are associated with early-life epigenetic age acceleration and may forecast future health inequities.

Utilizing epigenetics to study the shared nature of development and biological aging across the lifespan

Recently, biological aging has been quantified in DNA-methylation samples of older adults and applied as so-called "methylation profile scores" (MPSs) in separate target samples, including samples of children. This nascent research indicates that (1) biological aging can be quantified early in the life course, decades before the onset of aging-related disease, (2) is affected by common environmental predictors of childhood development, and (3) shows overlap with "developmental processes" (e.g., puberty). Because the MPSs were computed using algorithms developed in adults, these studies indicate a molecular link between childhood environments, development, and adult biological aging. Yet, if MPSs can be used to connect development and aging, previous research has only traveled one way, deriving MPSs developed in adults and applying them to samples of children. Researchers have not yet quantified epigenetic measures that reflect the pace of child development, and tested whether resulting MPSs are associated with physical and psychological aging. In this perspective I posit that combining measures of biological aging with new quantifications of child development has the power to address fundamental questions about life span: How are development and experience in childhood related to biological aging in adulthood? And what is 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.

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.

Cumulative stress, PTSD, and emotion dysregulation during pregnancy and epigenetic age acceleration in Hispanic mothers and their newborn infants

Pregnancy can exacerbate or prompt the onset of stress-related disorders, such as post-traumatic stress disorder (PTSD). PTSD is associated with heightened stress responsivity and emotional dysregulation, as well as increased risk of chronic disorders and mortality. Further, maternal PTSD is associated with gestational epigenetic age acceleration in newborns, implicating the prenatal period as a developmental time period for the transmission of effects across generations. Here, we evaluated the associations between PTSD symptoms, maternal epigenetic age acceleration, and infant gestational epigenetic age acceleration in 89 maternal-neonatal dyads. Trauma-related experiences and PTSD symptoms in mothers were assessed during the third trimester of pregnancy. The MethylationEPIC array was used to generate DNA methylation data from maternal and neonatal saliva samples collected within 24 h of infant birth. Maternal epigenetic age acceleration was calculated using Horvath's multi-tissue clock, PhenoAge and GrimAge. Gestational epigenetic age was estimated using the Haftorn clock. Maternal cumulative past-year stress (GrimAge: p = 3.23e-04, PhenoAge: p = 9.92e-03), PTSD symptoms (GrimAge: p = 0.019), and difficulties in emotion regulation (GrimAge: p = 0.028) were associated with accelerated epigenetic age in mothers. Maternal PTSD symptoms were associated with lower gestational epigenetic age acceleration in neonates (p = 0.032). Overall, our results suggest that maternal cumulative past-year stress exposure and trauma-related symptoms may increase the risk for age-related problems in mothers and developmental problems in their newborns.

Stability of DNA-Methylation Profiles of Biological Aging in Children and Adolescents

Background and Objectives

Methylation profile scores (MPSs) index biological aging and aging-related disease in adults and are cross-sectionally associated with social determinants of health in childhood. MPSs thus provide an opportunity to trace how aging-related biology responds to environmental changes in early life. Information regarding the stability of MPSs in early life is currently lacking.

Method

We use longitudinal data from children and adolescents ages 8-18 (N = 428, M age = 12.15 years) from the Texas Twin Project. Participants contributed two waves of salivary DNA-methylation data (mean lag = 3.94 years), which were used to construct four MPSs reflecting multi-system physiological decline and mortality risk (PhenoAgeAccel and GrimAgeAccel), pace of biological aging (DunedinPACE), and cognitive function (Epigenetic-g). Furthermore, we exploit variation among participants in whether they were exposed to the COVID-19 pandemic during the course of study participation, in order to test how a historical period characterized by environmental disruption might affect children's aging-related MPSs.

Results

All MPSs showed moderate longitudinal stability (test-retest rs = 0.42, 0.44, 0.46, 0.51 for PhenoAgeAccel, GrimAgeAccel, and Epigenetic-g, and DunedinPACE, respectively). No differences in the stability of MPSs were apparent between those whose second assessment took place after the onset of the COVID-19 pandemic vs. those for whom both assessments took place prior to the pandemic.

Conclusions

Aging-related DNA-methylation patterns are less stable in childhood than has been previously observed in adulthood. Further developmental research on the methylome is necessary to understand which environmental perturbations in childhood impact trajectories of biological aging and when children are most sensitive to those impacts.

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 (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 (β =-.34), but not young adults, adolescents or children. This association was not accounted for by statistical correction for 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 worse self-reported health (β =.13 to β = .19). But, effect sizes were weaker than observations in blood, thus 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.