Assessment of Epigenetic Clocks as Biomarkers of Aging in Basic and Population Research

A hematology-based clock derived from the Study of Longitudinal Aging in Mice to estimate biological age

Biological clocks and other molecular biomarkers of aging are difficult to implement widely in a clinical setting. In this study, we used routinely collected hematological markers to develop an aging clock to predict blood age and determine whether the difference between predicted age and chronologic age (aging gap) is associated with advanced aging in mice. Data from 2,562 mice of both sexes and three strains were drawn from two longitudinal studies of aging. Eight hematological variables and two metabolic indices were collected longitudinally (12,010 observations). Blood age was predicted using a deep neural network. Blood age was significantly correlated with chronological age, and aging gap was positively associated with mortality risk and frailty. Platelets were identified as the strongest age predictor by the deep neural network. An aging clock based on routinely collected blood measures has the potential to provide a practical clinical tool to better understand individual variability in the aging process.

Contextualizing aging clocks and properly describing biological age

Usage of the phrase "biological age" has picked up considerably since the advent of aging clocks and it has become commonplace to describe an aging clock's output as biological age. In contrast to this labeling, biological age is also often depicted as a more abstract concept that helps explain how individuals are aging internally, externally, and functionally. Given that the bulk of molecular aging is tissue-specific and aging itself is a remarkably complex, multifarious process, it is unsurprising that most surveyed scientists agree that aging cannot be quantified via a single metric. We share this sentiment and argue that, just like it would not be reasonable to assume that an individual with an ideal grip strength, VO2 max, or any other aging biomarker is biologically young, we should be careful not to conflate an aging clock with whole-body biological aging. To address this, we recommend that researchers describe the output of an aging clock based on the type of input data used or the name of the clock itself. Epigenetic aging clocks produce epigenetic age, transcriptomic aging clocks produce transcriptomic age, and so forth. If a clock has a unique name, such as our recently developed epigenetic aging clock CheekAge, the name of the clock can double as the output. As a compromise solution, aging biomarkers can be described as indicators of biological age. We feel that these recommendations will help scientists and the public differentiate between aging biomarkers and the much more elusive concept of biological age.

Lagged effects of childhood depressive symptoms on adult epigenetic aging

BACKGROUND

Cross-sectional studies have identified health risks associated with epigenetic aging. However, it is unclear whether these risks make epigenetic clocks 'tick faster' (i.e. accelerate biological aging). The current study examines concurrent and lagged within-person changes of a variety of health risks associated with epigenetic aging.

METHODS

Individuals from the Great Smoky Mountains Study were followed from age 9 to 35 years. DNA methylation profiles were assessed from blood, at multiple timepoints (i.e. waves) for each individual. Health risks were psychiatric, lifestyle, and adversity factors. Concurrent (N = 539 individuals; 1029 assessments) and lagged (N = 380 individuals; 760 assessments) analyses were used to determine the link between health risks and epigenetic aging.

RESULTS

Concurrent models showed that BMI (r = 0.15, PFDR < 0.01) was significantly correlated to epigenetic aging at the subject-level but not wave-level. Lagged models demonstrated that depressive symptoms (b = 1.67 months per symptom, PFDR = 0.02) in adolescence accelerated epigenetic aging in adulthood, also when models were fully adjusted for BMI, smoking, and cannabis and alcohol use.

CONCLUSIONS

Within-persons, changes in health risks were unaccompanied by concurrent changes in epigenetic aging, suggesting that it is unlikely for risks to immediately 'accelerate' epigenetic aging. However, time lagged analyses indicated that depressive symptoms in childhood/adolescence predicted epigenetic aging in adulthood. Together, findings suggest that age-related biological embedding of depressive symptoms is not instant but provides prognostic opportunities. Repeated measurements and longer follow-up times are needed to examine stable and dynamic contributions of childhood experiences to epigenetic aging across the lifespan.

High-Impact Pain Is Associated With Epigenetic Aging Among Middle-Aged and Older Adults: Findings From the Health and Retirement Study

BACKGROUND

Chronic pain has been associated with accelerated biological aging, which may be related to epigenetic alterations. We evaluated the association of high-impact pain (ie, pain that limits activities and function) with epigenetic aging, a 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. Epigenetic aging was derived from 13 epigenetic clocks based on DNA methylation patterns that predict aging correlates of morbidity and mortality. Ordinary least squares regressions were performed to test for differences in the epigenetic clocks, adjusting for the complex survey design, as well as biological, social, and behavioral factors.

RESULTS

The analysis consisted of 3 855 adults with mean age of 68.5 years, including 59.8% with no pain and 25.8% with high-impact pain. Consistent with its operational definition, high-impact pain was associated with greater functional and activity limitations. High-impact pain was associated with accelerated epigenetic aging compared to no pain, as measured via second (Zhang, PhenoAge, GrimAge) and third (DunedinPoAm) generation epigenetic clocks. Additionally, GrimAge was accelerated in high-impact pain as compared to low-impact pain.

CONCLUSIONS

High-impact pain is associated with accelerated epigenetic aging among middle-aged and older adults in the United States. These findings highlight aging-associated epigenetic alterations in high-impact chronic pain and suggest a potential for epigenetic therapeutic approaches for pain management and the preservation of physical function in older adults.

Investigating the Relationship between Epigenetic Age and Cardiovascular Risk in a Population with Overweight/Obesity

Introduction: Cardiovascular diseases stand as the leading global cause of mortality. Major modifiable risk factors encompass overweight/obese conditions, high blood pressure, elevated LDL cholesterol, diabetes, smoking, secondhand smoke exposure, unhealthy diet, and physical inactivity. In the present study, we explored the relationship between cardiovascular risk factors and epigenetic age (DNAm age), an estimate reflecting an individual's actual physiological functionality and overall health. Additionally, we assessed the association between DNAm age acceleration and cardiovascular risk, as evaluated through the Framingham risk score (FRS). Methods: The study includes 190 subjects with overweight/obese conditions. We calculated their DNAm age using Zbieć-Piekarska et al.'s DNAm age estimator on five sets of CpGs analyzed in the peripheral leucocytes. Linear regression models were employed to test the associations. Results: Various parameters contributing to increased cardiovascular risk were associated with DNAm age acceleration, such as systolic blood pressure (β = 0.045; SE = 0.019; p = 0.019), heart rate (β = 0.096; SE = 0.032; p = 0.003), blood glucose (β = 0.025; SE = 0.012; p = 0.030), glycated hemoglobin (β = 0.105; SE = 0.042; p = 0.013), diabetes (β = 2.247; SE = 0.841; p = 0.008), and menopausal conditions (β = 2.942; SE = 1.207; p = 0.016), as well as neutrophil (β = 0.100; SE = 0.042; p = 0.018) and granulocyte (β = 0.095; SE = 0.044; p = 0.033) counts. Moreover, DNAm age acceleration raised the FRS (∆% 5.3%, 95% CI 0.8; 9.9, p = 0.019). Conclusion: For the first time, we report that cardiovascular risk factors accelerated DNAm age in a selected population of hypersusceptible individuals with overweight or obesity. Our results highlight the potential of DNAm age acceleration as a biomarker of cumulative effects in cardiovascular risk assessment.

Multinational evaluation of anthropometric age (AnthropoAge) as a measure of biological age in the USA, England, Mexico, Costa Rica, and China: a population-based longitudinal study

OBJECTIVE

To validate AnthropoAge, a new metric of biological age (BA), for prediction of all-cause mortality and age-related outcomes and characterize population-specific aging patterns using multinational longitudinal cohorts.

METHODS

We analyzed harmonized multinational data from the Gateway to Global Aging, including studies from the US, England, Mexico, Costa Rica, and China. We used body mass index and waist-to-height ratio to estimate AnthropoAge and AnthropoAgeAccel in participants aged 50-90 years old as proxies of BA and age acceleration, respectively. We compared the predictive capacity for all-cause mortality of AnthropoAge and chronological age (CA) using Cox models, described aging trends in all countries and explored the utility of longitudinal assessments of AnthropoAgeAccel to predict new-onset functional decline and age-related diseases using generalized estimating equations (GEE).

FINDINGS

Using data from 55,628 participants, we found AnthropoAge (c-statistic 0.772) outperformed CA (0.76) for prediction of mortality independently of comorbidities, sex, race/ethnicity, education, and lifestyle; this result was replicated in most countries individually except for Mexico. Individuals with accelerated aging had a ~39% higher risk of death, and AnthropoAge also identified trends of faster biological aging per year. In longitudinal analyses, higher AnthropoAgeAccel values were independently predictive of self-reported health deterioration and new-onset deficits in basic/instrumental activities of daily living (ADL/IADL), diabetes, hypertension, cancer, chronic lung disease, myocardial infarction, and stroke.

CONCLUSIONS

AnthropoAge is a robust and reproducible BA metric associated with age-related outcomes. Its implementation could facilitate modeling trends of biological aging acceleration in different populations, although recalibration may enhance its utility in underrepresented populations such as individuals from Latin America.

Sociodemographic and Lifestyle Factors and Epigenetic Aging in US Young Adults: NIMHD Social Epigenomics Program

Importance

Epigenetic clocks represent molecular evidence of disease risk and aging processes and have been used to identify how social and lifestyle characteristics are associated with accelerated biological aging. However, most research is based on samples of older adults who already have measurable chronic disease.

Objective

To investigate whether and how sociodemographic and lifestyle characteristics are associated with biological aging in a younger adult sample across a wide array of epigenetic clock measures.

Design, Setting, and Participants

This cohort study was conducted using data from the National Longitudinal Study of Adolescent to Adult Health, a US representative cohort of adolescents in grades 7 to 12 in 1994 followed up for 25 years to 2018 over 5 interview waves. Participants who provided blood samples at wave V (2016-2018) were analyzed, with samples tested for DNA methylation (DNAm) in 2021 to 2024. Data were analyzed from February 2023 to May 2024.

Exposure

Sociodemographic (sex, race and ethnicity, immigrant status, socioeconomic status, and geographic location) and lifestyle (obesity status by body mass index [BMI] in categories of reference range or underweight [<25], overweight [25 to <30], obesity [30 to <40], and severe obesity [≥40]; exercise level; tobacco use; and alcohol use) characteristics were assessed.

Main Outcome and Measure

Biological aging assessed from banked blood DNAm using 16 epigenetic clocks.

Results

Data were analyzed from 4237 participants (mean [SD] age, 38.4 [2.0] years; percentage [SE], 51.3% [0.01] female and 48.7% [0.01] male; percentage [SE], 2.7% [<0.01] Asian or Pacific Islander, 16.7% [0.02] Black, 8.7% [0.01] Hispanic, and 71.0% [0.03] White). Sociodemographic and lifestyle factors were more often associated with biological aging in clocks trained to estimate morbidity and mortality (eg, PhenoAge, GrimAge, and DunedinPACE) than clocks trained to estimate chronological age (eg, Horvath). For example, the β for an annual income less than $25 000 vs $100 000 or more was 1.99 years (95% CI, 0.45 to 3.52 years) for PhenoAgeAA, 1.70 years (95% CI, 0.68 to 2.72 years) for GrimAgeAA, 0.33 SD (95% CI, 0.17 to 0.48 SD) for DunedinPACE, and -0.17 years (95% CI, -1.08 to 0.74 years) for Horvath1AA. Lower education, lower income, higher obesity levels, no exercise, and tobacco use were associated with faster biological aging across several clocks; associations with GrimAge were particularly robust (no college vs college or higher: β = 2.63 years; 95% CI, 1.67-3.58 years; lower vs higher annual income: <$25 000 vs ≥$100 000: β = 1.70 years; 95% CI, 0.68-2.72 years; severe obesity vs no obesity: β = 1.57 years; 95% CI, 0.51-2.63 years; no weekly exercise vs ≥5 bouts/week: β = 1.33 years; 95% CI, 0.67-1.99 years; current vs no smoking: β = 7.16 years; 95% CI, 6.25-8.07 years).

Conclusions and Relevance

This study found that important social and lifestyle factors were associated with biological aging in a nationally representative cohort of younger adults. These findings suggest that molecular processes underlying disease risk may be identified in adults entering midlife before disease is manifest and inform interventions aimed at reducing social inequalities in heathy aging and longevity.

The Sociodemographic and Lifestyle Correlates of Epigenetic Aging in a Nationally Representative U.S. Study of Younger Adults

Importance

Epigenetic clocks represent molecular evidence of disease risk and aging processes and have been used to identify how social and lifestyle characteristics are associated with accelerated biological aging. However, most of this research is based on older adult samples who already have measurable chronic disease.

Objective

To investigate whether and how sociodemographic and lifestyle characteristics are related to biological aging in a younger adult sample across a wide array of epigenetic clock measures.

Design

Nationally representative prospective cohort study.

Setting

United States (U.S.).

Participants

Data come from the National Longitudinal Study of Adolescent to Adult Health, a national cohort of adolescents in grades 7-12 in U.S. in 1994 followed for 25 years over five interview waves. Our analytic sample includes participants followed-up through Wave V in 2016-18 who provided blood samples for DNA methylation (DNAm) testing (n=4237) at Wave V.

Exposure

Sociodemographic (sex, race/ethnicity, immigrant status, socioeconomic status, geographic location) and lifestyle (obesity status, exercise, tobacco, and alcohol use) characteristics.

Main Outcome

Biological aging assessed from blood DNAm using 16 epigenetic clocks when the cohort was aged 33-44 in Wave V.

Results

While there is considerable variation in the mean and distribution of epigenetic clock estimates and in the correlations among the clocks, we found sociodemographic and lifestyle factors are more often associated with biological aging in clocks trained to predict current or dynamic phenotypes (e.g., PhenoAge, GrimAge and DunedinPACE) as opposed to clocks trained to predict chronological age alone (e.g., Horvath). Consistent and strong associations of faster biological aging were found for those with lower levels of education and income, and those with severe obesity, no weekly exercise, and tobacco use.

Conclusions and Relevance

Our study found important social and lifestyle factors associated with biological aging in a nationally representative cohort of younger-aged adults. These findings indicate that molecular processes underlying disease risk can be identified in adults entering midlife before disease is manifest and represent useful targets for interventions to reduce social inequalities in heathy aging and longevity.

Key Points

Question: Are epigenetic clocks, measures of biological aging developed mainly on older-adult samples, meaningful for younger adults and associated with sociodemographic and lifestyle characteristics in expected patterns found in prior aging research?Findings: Sociodemographic and lifestyle factors were associated with biological aging in clocks trained to predict morbidity and mortality showing accelerated aging among those with lower levels of education and income, and those with severe obesity, no weekly exercise, and tobacco use.Meaning: Age-related molecular processes can be identified in younger-aged adults before disease manifests and represent potential interventions to reduce social inequalities in heathy aging and longevity.

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.

Development of an epigenetic clock to predict visual age progression of human skin

Aging is a complex process characterized by the gradual decline of physiological functions, leading to increased vulnerability to age-related diseases and reduced quality of life. Alterations in DNA methylation (DNAm) patterns have emerged as a fundamental characteristic of aged human skin, closely linked to the development of the well-known skin aging phenotype. These changes have been correlated with dysregulated gene expression and impaired tissue functionality. In particular, the skin, with its visible manifestations of aging, provides a unique model to study the aging process. Despite the importance of epigenetic age clocks in estimating biological age based on the correlation between methylation patterns and chronological age, a second-generation epigenetic age clock, which correlates DNAm patterns with a particular phenotype, specifically tailored to skin tissue is still lacking. In light of this gap, we aimed to develop a novel second-generation epigenetic age clock explicitly designed for skin tissue to facilitate a deeper understanding of the factors contributing to individual variations in age progression. To achieve this, we used methylation patterns from more than 370 female volunteers and developed the first skin-specific second-generation epigenetic age clock that accurately predicts the skin aging phenotype represented by wrinkle grade, visual facial age, and visual age progression, respectively. We then validated the performance of our clocks on independent datasets and demonstrated their broad applicability. In addition, we integrated gene expression and methylation data from independent studies to identify potential pathways contributing to skin age progression. Our results demonstrate that our epigenetic age clock, VisAgeX, specifically predicting visual age progression, not only captures known biological pathways associated with skin aging, but also adds novel pathways associated with skin aging.

Characterizing epigenetic aging in an adult sickle cell disease cohort

ABSTRACT

Sickle cell disease (SCD) affects ∼100 000 predominantly African American individuals in the United States, causing significant cellular damage, increased disease complications, and premature death. However, the contribution of epigenetic factors to SCD pathophysiology remains relatively unexplored. DNA methylation (DNAm), a primary epigenetic mechanism for regulating gene expression in response to the environment, is an important driver of normal cellular aging. Several DNAm epigenetic clocks have been developed to serve as a proxy for cellular aging. We calculated the epigenetic ages of 89 adults with SCD (mean age, 30.64 years; 60.64% female) using 5 published epigenetic clocks: Horvath, Hannum, PhenoAge, GrimAge, and DunedinPACE. We hypothesized that in chronic disease, such as SCD, individuals would demonstrate epigenetic age acceleration, but the results differed depending on the clock used. Recently developed clocks more consistently demonstrated acceleration (GrimAge, DunedinPACE). Additional demographic and clinical phenotypes were analyzed to explore their association with epigenetic age estimates. Chronological age was significantly correlated with epigenetic age in all clocks (Horvath, r = 0.88; Hannum, r = 0.89; PhenoAge, r = 0.85; GrimAge, r = 0.88; DunedinPACE, r = 0.34). The SCD genotype was associated with 2 clocks (PhenoAge, P = .02; DunedinPACE, P < .001). Genetic ancestry, biological sex, β-globin haplotypes, BCL11A rs11886868, and SCD severity were not associated. These findings, among the first to interrogate epigenetic aging in adults with SCD, demonstrate epigenetic age acceleration with recently developed epigenetic clocks but not older-generation clocks. Further development of epigenetic clocks may improve their predictive ability and utility for chronic diseases such as SCD.

The Relationship of Neighborhood Disadvantage, Biological Aging, and Psychosocial Risk and Resilience Factors in Heart Failure Incidence Among Black Persons: A Moderated Mediation Analysis

OBJECTIVES

Deprived living environments contribute to greater heart failure (HF) risk among non-Hispanic Black persons, who disproportionately occupy disadvantaged neighborhoods. The mechanisms for these effects are not fully explicated, partially attributable to an insufficient understanding of the individual factors that contribute additional risk or resilience to the impact of neighborhood disadvantage on health. The objective of this study was, therefore, to clarify the complex pathways over which such exposures act to facilitate more targeted, effective interventions. Given the evidence for a mediating role of biological age and a moderating role of individual psychosocial characteristics in the neighborhood disadvantage-HF link, we tested a moderated mediation mechanism.

METHODS

Using multilevel causal moderated mediation models, we prospectively examined whether the association of neighborhood disadvantage with incident HF mediated through accelerated biological aging, captured by the GrimAge epigenetic clock, is moderated by hypothesized psychosocial risk (negative affect) and resilience (optimism) factors.

RESULTS

Among a sample of 1,448 Black participants in the shared Jackson Heart Study-Atherosclerosis Risk in Communities cohort (mean age 64.3 years), 334 adjudicated incident hospitalized HF events occurred over a median follow-up of 18 years. In models adjusted for age and sex, the indirect (GrimAge-mediated) effect of neighborhood disadvantage was moderated by psychosocial risk such that for every standard deviation increase in negative affect the hazards of HF was 1.18 (95% confidence interval = 1.05, 1.36). No moderated mediation effect was detected for optimism.

DISCUSSION

Findings support the necessity for multilevel interventions simultaneously addressing neighborhood and individual psychosocial risk in the reduction of HF among Black persons.

Epigenetics of the far northern Yakutian population

BACKGROUND

Yakuts are one of the indigenous populations of the subarctic and arctic territories of Siberia characterized by a continental subarctic climate with severe winters, with the regular January average temperature in the regional capital city of Yakutsk dipping below - 40 °C. The epigenetic mechanisms of adaptation to such ecologies and environments and, in particular, epigenetic age acceleration in the local population have not been studied before.

RESULTS

This work reports the first epigenetic study of the Yakutian population using whole-blood DNA methylation data, supplemented with the comparison to the residents of Central Russia. Gene set enrichment analysis revealed, among others, geographic region-specific differentially methylated regions associated with adaptation to climatic conditions (water consumption, digestive system regulation), aging processes (actin filament activity, cell fate), and both of them (channel activity, regulation of steroid and corticosteroid hormone secretion). Further, it is demonstrated that the epigenetic age acceleration of the Yakutian representatives is significantly higher than that of Central Russia counterparts. For both geographic regions, we showed that epigenetically males age faster than females, whereas no significant sex differences were found between the regions.

CONCLUSIONS

We performed the first study of the epigenetic data of the Yakutia cohort, paying special attention to region-specific features, aging processes, age acceleration, and sex specificity.

Measures of Aging Biology in Saliva and Blood as Novel Biomarkers for Stroke and Heart Disease in Older Adults

BACKGROUND AND OBJECTIVES

The role of aging biology as a novel risk factor and biomarker for vascular outcomes in different accessible body tissues such as saliva and blood remain unclear. We aimed to (1) assess the role of aging biology as a risk factor of stroke and heart disease among individuals of same chronologic age and sex and (2) compare aging biology biomarkers measured in different accessible body tissues as novel biomarkers for stroke and heart disease in older adults.

METHODS

This study included individuals who consented for blood and saliva draw in the Venous Blood Substudy and Telomere Length Study of the Health and Retirement Study (HRS). The HRS is a population-based, nationally representative longitudinal survey of individuals aged 50 years and older in the United States. Saliva-based measures included telomere length. Blood-based measures included DNA methylation and physiology biomarkers. Propensity scores-matched analyses and Cox regression models were conducted.

RESULTS

This study included individuals aged 50 years and older, who consented for blood (N = 9,934) and saliva (N = 5,808) draw in the HRS. Blood-based biomarkers of aging biology showed strong associations with incident stroke as follows: compared with the lowest tertile of blood-based biomarkers of aging, biologically older individuals had significantly higher risk of stroke based on DNA methylation Grim Age clock (adjusted hazard ratio [aHR] = 2.64, 95% CI 1.90-3.66, p < 0.001) and Physiology-based Phenotypic Age clock (aHR = 1.75, 95% CI 1.27-2.42, p < 0.001). In secondary analysis, biologically older individuals had increased risk of heart disease as follows: DNA methylation Grim Age clock (aHR = 1.77, 95% CI 1.49-2.11, p < 0.001) and Physiology-based Phenotypic Age clock (aHR = 1.61, 95% CI 1.36-1.90, p < 0.001).

DISCUSSION

Compared with saliva-based telomere length, blood-based aging physiology and some DNA methylation biomarkers are strongly associated with vascular disorders including stroke and are more precise and sensitive biomarkers of aging. Saliva-based telomere length and blood-based DNA methylation and physiology biomarkers likely represent different aspects of biological aging and accordingly vary in their precision as novel biomarkers for optimal vascular health.

Biological Age Mediates the Effects of Perceived Neighborhood Problems on Heart Failure Risk Among Black Persons

OBJECTIVE

We assessed whether biological age, measured by the epigenetic clock GrimAge, mediates the association of objective and subjective neighborhood disadvantage with incident HF among Black persons.

METHODS

Participants were 1448 self-reported Black adults (mean age (standard deviation, SD) = 64.3 (5.5)) dually enrolled in two community-based cohorts in Jackson, Mississippi, the ARIC and JHS cohorts, who were free of HF as of January 1, 2000. Incident HF events leading to hospitalization through December 31, 2017, were classified using ICD-9 discharge codes of HF. Multilevel age- and sex-adjusted Cox causal mediation models were used to examine whether biological age (at the person and neighborhood level) mediated the effects of objective (the National Area Deprivation Index, ADI) and subjective (perceived neighborhood problems) neighborhood disadvantage on incident HF.

RESULTS

A total of 334 incident hospitalized HF events occurred over a median follow-up of 18.0 years. The total effect of the ADI and perceived neighborhood problems (SD units) on HF was hazard ration (HR) = 1.26 and 95% confidence interval (CI) 0.98-1.56 and HR = 1.26 and 95% CI 1.10-1.41, respectively. GrimAge mediated a majority of the effect of perceived neighborhood problems on HF (person-level indirect effect HR = 1.07; 95% CI 1.02-1.12 and neighborhood-level indirect effect HR = 1.18; 95% CI 1.03-1.34), with the combined indirect effect explaining 94.8% of the relationship. The combined indirect effect of ADI on incident HF was comparable but not statistically significant.

CONCLUSIONS

Subjective neighborhood disadvantage may confer an increased risk of HF among Black populations.

The Association of Epigenetic Age Acceleration and Multimorbidity at Age 90 in the Women's Health Initiative

BACKGROUND

Epigenetic age acceleration (EAA), a measure of accelerated biological aging, has been associated with an increased risk of several age-related chronic conditions. This is the first study to prospectively examine the relationship between EAA and both multimorbidity count and a weighted multimorbidity score among long-lived postmenopausal women.

METHODS

We included 1 951 women from the Women's Health Initiative who could have survived to age 90. EAA was estimated using the Horvath pan-tissue, Hannum, PhenoAge, and GrimAge "clocks." Twelve chronic conditions were included in the multimorbidity count. The multimorbidity score was weighted for each morbidity's relationship with mortality in the study population. Using mixed-effects Poisson and linear regression models that included baseline covariates associated with both EAA and multimorbidity, we estimated relative risks (RRs) and 95% confidence intervals (CIs) for the relationships between each EAA measure at the study baseline with both multimorbidity count and weighted multimorbidity score at age 90, respectively.

RESULTS

For every one standard deviation increase in AgeAccelPheno, the rate of multimorbidity accumulation increased 6% (RR = 1.06; 95% CI = 1.01-1.12; p = .025) and the multimorbidity score by 7% (RR = 1.07; 95% CI = 1.01-1.13; p = .014) for women who survived to age 90. The results for a one standard deviation increase in AgeAccelHorvath, AgeAccelHannum, and AgeAccelGrim with multimorbidity accumulation and score were weaker compared to AgeAccelPheno, and the latter 2 did not reach statistical significance.

CONCLUSION

AgeAccelPheno and AgeAccelHannum may predict multimorbidity count and score at age 90 in older women and, thus, may be useful as a biomarker predictor of multimorbidity burden in the last decades of life.

Arsenic Exposure and Epigenetic Aging: The Association with Cardiovascular Disease and All-Cause Mortality in the Strong Heart Study

BACKGROUND

Inorganic arsenic (As) may increase the risk of cardiovascular disease (CVD) and all-cause mortality through accelerated aging, which can be estimated using epigenetic-based measures.

OBJECTIVES

We evaluated three DNA methylation-based aging measures (PhenoAge, GrimAge, DunedinPACE) (epigenetic aging measures) as potential mediators of the previously reported association of As exposure with CVD incidence, CVD mortality, and all-cause mortality in the Strong Heart Study (SHS), an epidemiological cohort of American Indian adults.

METHODS

Blood DNA methylation and urinary As levels were measured in 2,323 SHS participants (41.5% men, mean age of 55 years old). PhenoAge and GrimAge values were calculated using a residual-based method. We tested the association of urinary As with epigenetic aging measures using linear regression, the association of epigenetic aging measures with the three health outcomes using additive hazards models, and the mediation of As-related CVD incidence, CVD mortality, and all-cause mortality by epigenetic aging measures using the product of coefficients method.

RESULTS

SHS participants with higher vs. lower urinary As levels had similar PhenoAge age, older GrimAge age, and faster DunedinPACE. An interquartile range increase in urinary As was associated with higher of PhenoAge age acceleration [mean difference  ( 95 %  confidence interval ) = 0.48 (0.17, 0.80) years], GrimAge age acceleration [0.80 (0.60, 1.00) years], and DunedinPACE [0.011 (0.005, 0.018)], after adjusting for age, sex, center location, genetic components, smoking status, and body mass index. Of the 347 incident CVD events per 100,000 person-years associated with a doubling in As exposure, 21.3% (9.1, 57.1) and 22.6% (9.5, 56.9), were attributable to differences in GrimAge and DunedinPACE, respectively.

DISCUSSION

Arsenic exposure was associated with older GrimAge and faster DunedinPACE measures of biological age. Furthermore, accelerated biological aging measured from DNA methylation accounted for a relevant fraction of As-associated risk for CVD, CVD mortality, and all-cause mortality in the SHS, supporting the role of As in accelerated aging. Research of the biological underpinnings can contribute to a better understanding of the role of aging in arsenic-related disease. https://doi.org/10.1289/EHP11981.

Measuring healthy ageing: current and future tools

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

Accelerated Aging and the Life Course of Individuals Born Preterm

Individuals born preterm have shorter lifespans and elevated rates of chronic illness that contribute to mortality risk when compared to individuals born at term. Emerging evidence suggests that individuals born preterm or of low birthweight also exhibit physiologic and cellular biomarkers of accelerated aging. It is unclear whether, and to what extent, accelerated aging contributes to a higher risk of chronic illness and mortality among individuals born preterm. Here, we review accelerated aging phenotypes in adults born preterm and biological pathways that appear to contribute to accelerated aging. We highlight biomarkers of accelerated aging and various resiliency factors, including both pharmacologic and non-pharmacologic factors, that might buffer the propensity for accelerated aging among individuals born preterm.

Greater stress and trauma mediate race-related differences in epigenetic age between Black and White young adults in a community sample

Black Americans suffer lower life expectancy and show signs of accelerated aging compared to other Americans. While previous studies observe these differences in children and populations with chronic illness, whether these pathologic processes exist or how these pathologic processes progress has yet to be explored prior to the onset of significant chronic illness, within a young adult population. Therefore, we investigated race-related differences in epigenetic age in a cross-sectional sample of young putatively healthy adults and assessed whether lifetime stress and/or trauma mediate those differences. Biological and psychological data were collected from self-reported healthy adult volunteers within the local New Haven area (399 volunteers, 19.8% Black, mean age: 29.28). Stress and trauma data was collected using the Cumulative Adversity Inventory (CAI) interview, which assessed specific types of stressors, including major life events, traumatic events, work, financial, relationship and chronic stressors cumulatively over time. GrimAge Acceleration (GAA), determined from whole blood collected from participants, measured epigenetic age. In order to understand the impact of stress and trauma on GAA, exploratory mediation analyses were then used. We found cumulative stressors across all types of events (mean difference of 6.9 p = 2.14e-4) and GAA (β = 2.29 years [1.57-3.01, p = 9.70e-10] for race, partial η2 = 0.091, model adjusted R2 = 0.242) were significantly greater in Black compared to White participants. Critically, CAI total score (proportion mediated: 0.185 [0.073-0.34, p = 6e-4]) significantly mediated the relationship between race and GAA. Further analysis attributed this difference to more traumatic events, particularly assaultive traumas and death of loved ones. Our results suggest that, prior to development of significant chronic disease, Black individuals have increased epigenetic age compared to White participants and that increased cumulative stress and traumatic events may contribute significantly to this epigenetic aging difference.

Biomarkers of aging for the identification and evaluation of longevity interventions

With the rapid expansion of aging biology research, the identification and evaluation of longevity interventions in humans have become key goals of this field. Biomarkers of aging are critically important tools in achieving these objectives over realistic time frames. However, the current lack of standards and consensus on the properties of a reliable aging biomarker hinders their further development and validation for clinical applications. Here, we advance a framework for the terminology and characterization of biomarkers of aging, including classification and potential clinical use cases. We discuss validation steps and highlight ongoing challenges as potential areas in need of future research. This framework sets the stage for the development of valid biomarkers of aging and their ultimate utilization in clinical trials and practice.

Cross-National and Cross-Generational Evidence That Educational Attainment May Slow the Pace of Aging in European-Descent Individuals

OBJECTIVES

Individuals with more education are at lower risk of developing multiple, different age-related diseases than their less-educated peers. A reason for this might be that individuals with more education age slower. There are 2 complications in testing this hypothesis. First, there exists no definitive measure of biological aging. Second, shared genetic factors contribute toward both lower educational attainment and the development of age-related diseases. Here, we tested whether the protective effect of educational attainment was associated with the pace of aging after accounting for genetic factors.

METHODS

We examined data from 5 studies together totaling almost 17,000 individuals with European ancestry born in different countries during different historical periods, ranging in age from 16 to 98 years old. To assess the pace of aging, we used DunedinPACE, a DNA methylation algorithm that reflects an individual's rate of aging and predicts age-related decline and Alzheimer's disease and related disorders. To assess genetic factors related to education, we created a polygenic score based on the results of a genome-wide association study of educational attainment.

RESULTS

Across the 5 studies, and across the life span, higher educational attainment was associated with a slower pace of aging even after accounting for genetic factors (meta-analysis effect size = -0.20; 95% confidence interval [CI]: -0.30 to -0.10; p = .006). Further, this effect persisted after taking into account tobacco smoking (meta-analysis effect size = -0.13; 95% CI: -0.21 to -0.05; p = .01).

DISCUSSION

These results indicate that higher levels of education have positive effects on the pace of aging, and that the benefits can be realized irrespective of individuals' genetics.

Measuring healthy ageing: current and future tools

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

Subclinical atherosclerosis and accelerated epigenetic age mediated by inflammation: a multi-omics study

AIMS

Epigenetic age is emerging as a personalized and accurate predictor of biological age. The aim of this article is to assess the association of subclinical atherosclerosis with accelerated epigenetic age and to investigate the underlying mechanisms mediating this association.

METHODS AND RESULTS

Whole blood methylomics, transcriptomics, and plasma proteomics were obtained for 391 participants of the Progression of Early Subclinical Atherosclerosis study. Epigenetic age was calculated from methylomics data for each participant. Its divergence from chronological age is termed epigenetic age acceleration. Subclinical atherosclerosis burden was estimated by multi-territory 2D/3D vascular ultrasound and by coronary artery calcification. In healthy individuals, the presence, extension, and progression of subclinical atherosclerosis were associated with a significant acceleration of the Grim epigenetic age, a predictor of health and lifespan, regardless of traditional cardiovascular risk factors. Individuals with an accelerated Grim epigenetic age were characterized by an increased systemic inflammation and associated with a score of low-grade, chronic inflammation. Mediation analysis using transcriptomics and proteomics data revealed key pro-inflammatory pathways (IL6, Inflammasome, and IL10) and genes (IL1B, OSM, TLR5, and CD14) mediating the association between subclinical atherosclerosis and epigenetic age acceleration.

CONCLUSION

The presence, extension, and progression of subclinical atherosclerosis in middle-aged asymptomatic individuals are associated with an acceleration in the Grim epigenetic age. Mediation analysis using transcriptomics and proteomics data suggests a key role of systemic inflammation in this association, reinforcing the relevance of interventions on inflammation to prevent cardiovascular disease.

Utility of DNA Methylation as a Biomarker in Aging and Alzheimer's Disease

Epigenetic mechanisms such as DNA methylation have been implicated in a number of diseases including cancer, heart disease, autoimmune disorders, and neurodegenerative diseases. While it is recognized that DNA methylation is tissue-specific, a limitation for many studies is the ability to sample the tissue of interest, which is why there is a need for a proxy tissue such as blood, that is reflective of the methylation state of the target tissue. In the last decade, DNA methylation has been utilized in the design of epigenetic clocks, which aim to predict an individual's biological age based on an algorithmically defined set of CpGs. A number of studies have found associations between disease and/or disease risk with increased biological age, adding weight to the theory of increased biological age being linked with disease processes. Hence, this review takes a closer look at the utility of DNA methylation as a biomarker in aging and disease, with a particular focus on Alzheimer's disease.

Exercise and epigenetic ages in older adults with myeloid malignancies

BACKGROUND

Older adults with myeloid malignancies are susceptible to treatment-related toxicities. Accelerated DNAm age, or the difference between DNA methylation (DNAm) age and chronological age, may be used as a biomarker of biological age to predict individuals at risk. In addition, cancer treatment can also lead to accelerated DNAm age. Exercise is a promising intervention to reduce or prevent functional, psychological, and cognitive impairments in older patients with myeloid malignancies, yet there is little evidence of the effects of exercise on DNAm age. We explored (1) the associations of accelerated DNAm age with physical, psychological, and cognitive functions at baseline; (2) changes in DNAm age from baseline to post-intervention; and (3) the associations of changes in accelerated DNAm age with changes in functions from baseline to post-intervention.

METHODS

We enrolled older patients with myeloid malignancies to a single-arm pilot study testing a mobile health (mHealth) exercise intervention that combines an exercise program (EXCAP©®) with a mobile application over 2 cycles of chemotherapy (8-12 weeks). Patients completed measures of physical, psychological, and cognitive functions and provided blood samples for analyses of DNAm age at baseline and post-intervention. Paired t-tests or Wilcoxon signed rank tests assessed changes in DNAm ages, and Spearman's correlation assessed the relationships between accelerated ages and functions.

RESULTS

We included 20 patients (mean age: 72 years, range 62-80). Accelerated GrimAge, accelerated PhenoAge, and DunedinPACE were stable from baseline to post-intervention. At baseline, DunedinPACE was correlated with worse grip strength (r = -0.41, p = 0.08). From baseline to post-intervention, decreases in accelerated GrimAge (r = -0.50, p = 0.02), accelerated PhenoAge (r = - 0.39, p = 0.09), and DunedinPace (r = - 0.43, p = 0.06) were correlated with increases in distance walked on 6-min walk test. Decreases in accelerated GrimAge (r = - 0.49, p = 0.03), accelerated PhenoAge (r = - 0.40, p = 0.08), and DunedinPace (r = - 0.41, p = 0.07) were correlated with increases in in grip strength.

CONCLUSIONS

Among older adults with myeloid malignancies receiving chemotherapy, GrimAge and PhenoAge on average are stable after a mHealth exercise intervention. Decreases in accelerated GrimAge, accelerated PhenoAge, and DunedinPACE over 8-12 weeks of exercise were correlated with increased physical performance. Future trials assessing the effects of exercise on treatment-related toxicities should evaluate DNAm age. Trial registration Clinicaltrials.gov identifier: NCT04981821.

Multi-omic underpinnings of epigenetic aging and human longevity

Biological aging is accompanied by increasing morbidity, mortality, and healthcare costs; however, its molecular mechanisms are poorly understood. Here, we use multi-omic methods to integrate genomic, transcriptomic, and metabolomic data and identify biological associations with four measures of epigenetic age acceleration and a human longevity phenotype comprising healthspan, lifespan, and exceptional longevity (multivariate longevity). Using transcriptomic imputation, fine-mapping, and conditional analysis, we identify 22 high confidence associations with epigenetic age acceleration and seven with multivariate longevity. FLOT1, KPNA4, and TMX2 are novel, high confidence genes associated with epigenetic age acceleration. In parallel, cis-instrument Mendelian randomization of the druggable genome associates TPMT and NHLRC1 with epigenetic aging, supporting transcriptomic imputation findings. Metabolomics Mendelian randomization identifies a negative effect of non-high-density lipoprotein cholesterol and associated lipoproteins on multivariate longevity, but not epigenetic age acceleration. Finally, cell-type enrichment analysis implicates immune cells and precursors in epigenetic age acceleration and, more modestly, multivariate longevity. Follow-up Mendelian randomization of immune cell traits suggests lymphocyte subpopulations and lymphocytic surface molecules affect multivariate longevity and epigenetic age acceleration. Our results highlight druggable targets and biological pathways involved in aging and facilitate multi-omic comparisons of epigenetic clocks and human longevity.

Effect of long-term caloric restriction on DNA methylation measures of biological aging in healthy adults from the CALERIE trial

The geroscience hypothesis proposes that therapy to slow or reverse molecular changes that occur with aging can delay or prevent multiple chronic diseases and extend healthy lifespan1-3. Caloric restriction (CR), defined as lessening caloric intake without depriving essential nutrients4, results in changes in molecular processes that have been associated with aging, including DNA methylation (DNAm)5-7, and is established to increase healthy lifespan in multiple species8,9. Here we report the results of a post hoc analysis of the influence of CR on DNAm measures of aging in blood samples from the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE) trial, a randomized controlled trial in which n = 220 adults without obesity were randomized to 25% CR or ad libitum control diet for 2 yr (ref. 10). We found that CALERIE intervention slowed the pace of aging, as measured by the DunedinPACE DNAm algorithm, but did not lead to significant changes in biological age estimates measured by various DNAm clocks including PhenoAge and GrimAge. Treatment effect sizes were small. Nevertheless, modest slowing of the pace of aging can have profound effects on population health11-13. The finding that CR modified DunedinPACE in a randomized controlled trial supports the geroscience hypothesis, building on evidence from small and uncontrolled studies14-16 and contrasting with reports that biological aging may not be modifiable17. Ultimately, a conclusive test of the geroscience hypothesis will require trials with long-term follow-up to establish effects of intervention on primary healthy-aging endpoints, including incidence of chronic disease and mortality18-20.

Current Marital Status and Epigenetic Clocks Among Older Adults in the United States: Evidence From the Health and Retirement Study

Objectives: This study examines how current marital status is associated with epigenetic aging. Methods: Data from the 2016 Health and Retirement Study were used to examine marital status differences in the four epigenetic clocks, that is, GrimAge, DunedinPoAm, PhenoAge, and Zhang (N = 3765). Weighted ordinary least square regression models were estimated separately for men and women. Results: Remarried, cohabiting, divorced/separated and widowed older adults showed greater epigenetic aging than the continuously married similarly among men and women. Distinct sex difference was observed among the never married. While never-married women exhibited greater epigenetic aging than their continuously married counterparts, older men in lifelong singlehood showed comparable epigenetic aging to their continuously married peers. Discussion: The findings speak to the importance of marital context for epigenetic aging in later life and the biological risk associated with lifelong singlehood for older women in the US.

Within subject cross-tissue analyzes of epigenetic clocks in substance use disorder postmortem brain and blood

There is a possible accelerated biological aging in patients with substance use disorders (SUD). The evaluation of epigenetic clocks, which are accurate estimators of biological aging based on DNA methylation changes, has been limited to blood tissue in patients with SUD. Consequently, the impact of biological aging in the brain of individuals with SUD remains unknown. In this study, we evaluated multiple epigenetic clocks (DNAmAge, DNAmAgeHannum, DNAmAgeSkinBlood, DNAmPhenoAge, DNAmGrimAge, and DNAmTL) in individuals with SUD (n = 42), including alcohol (n = 10), opioid (n = 19), and stimulant use disorder (n = 13), and controls (n = 10) in postmortem brain (prefrontal cortex) and blood tissue obtained from the same individuals. We found a higher DNAmPhenoAge (β = 0.191, p-value = 0.0104) and a nominally lower DNAmTL (β = -0.149, p-value = 0.0603) in blood from individuals with SUD compared to controls. SUD subgroup analysis showed a nominally lower brain DNAmTL in subjects with alcohol use disorder, compared to stimulant use disorder and controls (β = 0.0150, p-value = 0.087). Cross-tissue analyzes indicated a lower blood DNAmTL and a higher blood DNAmAge compared to their respective brain values in the SUD group. This study highlights the relevance of tissue specificity in biological aging studies and suggests that peripheral measures of epigenetic clocks in SUD may depend on the specific type of drug used.

DNA methylation-based measures of biological aging and cognitive decline over 16-years: preliminary longitudinal findings in midlife

DNA methylation-based (DNAm) measures of biological aging associate with increased risk of morbidity and mortality, but their links with cognitive decline are less established. This study examined changes over a 16-year interval in epigenetic clocks (the traditional and principal components [PC]-based Horvath, Hannum, PhenoAge, GrimAge) and pace of aging measures (Dunedin PoAm, Dunedin PACE) in 48 midlife adults enrolled in the longitudinal arm of the Adult Health and Behavior project (56% Female, baseline AgeM = 44.7 years), selected for discrepant cognitive trajectories. Cognitive Decliners (N = 24) were selected based on declines in a composite score derived from neuropsychological tests and matched with participants who did not show any decline, Maintainers (N = 24). Multilevel models with repeated DNAm measures within person tested the main effects of time, group, and group by time interactions. DNAm measures significantly increased over time generally consistent with elapsed time between study visits. There were also group differences: overall, Cognitive Decliners had an older PC-GrimAge and faster pace of aging (Dunedin PoAm, Dunedin PACE) than Cognitive Maintainers. There were no significant group by time interactions, suggesting accelerated epigenetic aging in Decliners remained constant over time. Older PC-GrimAge and faster pace of aging may be particularly sensitive to cognitive decline in midlife.

Association of Pace of Aging Measured by Blood-Based DNA Methylation With Age-Related Cognitive Impairment and Dementia

BACKGROUND AND OBJECTIVES

DNA methylation algorithms are increasingly used to estimate biological aging; however, how these proposed measures of whole-organism biological aging relate to aging in the brain is not known. We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Framingham Heart Study (FHS) Offspring Cohort to test the association between blood-based DNA methylation measures of biological aging and cognitive impairment and dementia in older adults.

METHODS

We tested 3 "generations" of DNA methylation age algorithms (first generation: Horvath and Hannum clocks; second generation: PhenoAge and GrimAge; and third generation: DunedinPACE, Dunedin Pace of Aging Calculated from the Epigenome) against the following measures of cognitive impairment in ADNI: clinical diagnosis of dementia and mild cognitive impairment, scores on Alzheimer disease (AD) / Alzheimer disease and related dementias (ADRD) screening tests (Alzheimer's Disease Assessment Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment), and scores on cognitive tests (Rey Auditory Verbal Learning Test, Logical Memory test, and Trail Making Test). In an independent replication in the FHS Offspring Cohort, we further tested the longitudinal association between the DNA methylation algorithms and the risk of developing dementia.

RESULTS

In ADNI (N = 649 individuals), the first-generation (Horvath and Hannum DNA methylation age clocks) and the second-generation (PhenoAge and GrimAge) DNA methylation measures of aging were not consistently associated with measures of cognitive impairment in older adults. By contrast, a third-generation measure of biological aging, DunedinPACE, was associated with clinical diagnosis of Alzheimer disease (beta [95% CI] = 0.28 [0.08-0.47]), poorer scores on Alzheimer disease/ADRD screening tests (beta [Robust SE] = -0.10 [0.04] to 0.08[0.04]), and cognitive tests (beta [Robust SE] = -0.12 [0.04] to 0.10 [0.03]). The association between faster pace of aging, as measured by DunedinPACE, and risk of developing dementia was confirmed in a longitudinal analysis of the FHS Offspring Cohort (N = 2,264 individuals, hazard ratio [95% CI] = 1.27 [1.07-1.49]).

DISCUSSION

Third-generation blood-based DNA methylation measures of aging could prove valuable for measuring differences between individuals in the rate at which they age and in their risk for cognitive decline, and for evaluating interventions to slow aging.

DNA Methylation - and Telomere - Based Biological Age Estimation as Markers of Biological Aging in Donors Kidneys

The biological age of an organ may represent a valuable tool for assessing its quality, especially in the elder. We examined the biological age of the kidneys [right (RK) and left kidney (LK)] and blood leukocytes in the same subject and compared these to assess whether blood mirrors kidney biological aging. Biological age was studied in n = 36 donors (median age: 72 years, range: 19-92; male: 42%) by exploring mitotic and non-mitotic pathways, using telomere length (TL) and age-methylation changes (DNAmAge) and its acceleration (AgeAcc). RK and LK DNAmAge are older than blood DNAmAge (RK vs. Blood, p = 0.0271 and LK vs. Blood, p = 0.0245) and RK and LK AgeAcc present higher score (this mean the AgeAcc is faster) than that of blood leukocytes (p = 0.0271 and p = 0.0245) in the same donor. TL of RK and LK are instead longer than that of blood (p = 0.0011 and p = 0.0098) and the increase in Remuzzi-Karpinski score is strongly correlated with kidney TL attrition (p = 0.0046). Finally, blood and kidney TL (p < 0.01) and DNAmAge (p < 0.001) were correlated. These markers can be evaluated in further studies as indicators of biological age of donor organ quality and increase the usage of organs from donors of advanced age therefore offering a potential translational research inkidney transplantation.

Understanding Health Inequalities Through the Lens of Social Epigenetics

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

Testing Black-White Disparities in Biological Aging Among Older Adults in the United States: Analysis of DNA-Methylation and Blood-Chemistry Methods

Biological aging is a proposed mechanism through which social determinants drive health disparities. We conducted proof-of-concept testing of 8 DNA-methylation (DNAm) and blood-chemistry quantifications of biological aging as mediators of disparities in healthspan between Black and White participants in the 2016 wave of the Health and Retirement Study (n = 9,005). We quantified biological aging from 4 DNAm "clocks" (Horvath, Hannum, PhenoAge, and GrimAge clock), a DNAm pace-of-aging measure (DunedinPoAm), and 3 blood-chemistry measures (PhenoAge, Klemera-Doubal method biological age, and homeostatic dysregulation). We quantified Black-White disparities in healthspan from cross-sectional and longitudinal data on physical performance tests, self-reported limitations in activities of daily living, and physician-diagnosed chronic diseases, self-rated health, and survival. DNAm and blood-chemistry quantifications of biological aging were moderately correlated (Pearson's r = 0.1-0.4). The GrimAge clock, DunedinPoAm, and all 3 blood-chemistry measures were associated with healthspan characteristics (e.g., mortality effect-size hazard ratios were 1.71-2.32 per standard deviation of biological aging) and showed evidence of more advanced/faster biological aging in Black participants than in White participants (Cohen's d = 0.4-0.5). These measures accounted for 13%-95% of Black-White differences in healthspan-related characteristics. Findings suggest that reducing disparities in biological aging can contribute to building health equity.

Epigenetics of single-site and multi-site atherosclerosis in African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA)

BACKGROUND

DNA methylation, an epigenetic mechanism modulated by lifestyle and environmental factors, may be an important biomarker of complex diseases including cardiovascular diseases (CVD) and subclinical atherosclerosis.

METHODS

DNA methylation in peripheral blood samples from 391 African-Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) was assessed at baseline, and atherosclerosis was assessed 5 and 12 years later. Using linear mixed models, we examined the association between previously identified CpGs for coronary artery calcification (CAC) and carotid plaque, both individually and aggregated into methylation risk scores (MRSCAC and MRScarotid), and four measures of atherosclerosis (CAC, abdominal aorta calcification (AAC), ankle-brachial index (ABI), and multi-site atherosclerosis based on gender-specific quartiles of the single-site measures). We also examined the association between four epigenetic age acceleration measures (IEAA, EEAA, PhenoAge acceleration, and GrimAge acceleration) and the four atherosclerosis measures. Finally, we characterized the temporal stability of the epigenetic measures using repeated DNA methylation measured 5 years after baseline (N = 193).

RESULTS

After adjusting for CVD risk factors, four CpGs (cg05575921(AHRR), cg09935388 (GFI1), cg21161138 (AHRR), and cg18168448 (LRRC52)) were associated with multi-site atherosclerosis (FDR < 0.1). cg05575921 was also associated with AAC and cg09935388 with ABI. MRSCAC was associated with ABI (Beta = 0.016, P = 0.006), and MRScarotid was associated with both AAC (Beta = 0.605, equivalent to approximately 1.8-fold increase in the Agatston score of AAC, P = 0.004) and multi-site atherosclerosis (Beta = 0.691, P = 0.002). A 5-year increase in GrimAge acceleration (~ 1 SD) was associated with a 1.6-fold (P = 0.012) increase in the Agatston score of AAC and 0.7 units (P = 0.0003) increase in multi-site atherosclerosis, all after adjusting for CVD risk factors. All epigenetic measures were relatively stable over 5 years, with the highest intraclass correlation coefficients observed for MRScarotid and GrimAge acceleration (0.87 and 0.89, respectively).

CONCLUSIONS

We found evidence of an association between DNA methylation and atherosclerosis at multiple vascular sites in a sample of African-Americans. Further evaluation of these potential biomarkers is warranted to deepen our understanding of the relationship between epigenetics and atherosclerosis.

Epigenetic aging biomarkers and occupational exposure to benzene, trichloroethylene and formaldehyde

Epigenetic aging biomarkers are associated with increased morbidity and mortality. We evaluated if occupational exposure to three established chemical carcinogens is associated with acceleration of epigenetic aging. We studied workers in China occupationally exposed to benzene, trichloroethylene (TCE) or formaldehyde by measuring personal air exposures prior to blood collection. Unexposed controls matched by age and sex were selected from nearby factories. We measured leukocyte DNA methylation (DNAm) in peripheral white blood cells using the Infinium HumanMethylation450 BeadChip to calculate five epigenetic aging clocks and DNAmTL, a biomarker associated with leukocyte telomere length and cell replication. We tested associations between exposure intensity and epigenetic age acceleration (EAA), defined as the residuals of regressing the DNAm aging biomarker on chronological age, matching factors and potential confounders. Median differences in EAA between exposure groups were tested using a permutation test with exact p-values. Epigenetic clocks were strongly correlated with age (Spearman r > 0.8) in all three occupational studies. There was a positive exposure-response relationship between benzene and the Skin-Blood Clock EAA biomarker: median EAA was -0.91 years in controls (n = 44), 0.78 years in workers exposed to <10 ppm (n = 41; mean benzene = 1.35 ppm; p = 0.034 vs. controls), and 2.10 years in workers exposed to ≥10 ppm (n = 9; mean benzene = 27.3 ppm; p = 0.019 vs. controls; p_trend = 0.0021). In the TCE study, control workers had a median Skin-Blood Clock EAA of -0.54 years (n = 71) compared to 1.63 years among workers exposed to <10 ppm of TCE (n = 27; mean TCE = 4.22 ppm; p = 0.035). We observed no evidence of EAA associations with formaldehyde exposure (39 controls, 31 exposed). Occupational benzene and TCE exposure were associated with increased epigenetic age acceleration measured by the Skin-Blood Clock. For TCE, there was some evidence of epigenetic age acceleration for lower exposures compared to controls. Our results suggest that some chemical carcinogens may accelerate epigenetic aging.

Fundamental Clock of Biological Aging: Convergence of Molecular, Neurodegenerative, Cognitive and Psychiatric Pathways: Non-Equilibrium Thermodynamics Meet Psychology

In humans, age-associated degrading changes, widely observed in molecular and cellular processes underly the time-dependent decline in spatial navigation, time perception, cognitive and psychological abilities, and memory. Cross-talk of biological, cognitive, and psychological clocks provides an integrative contribution to healthy and advanced aging. At the molecular level, genome, proteome, and lipidome instability are widely recognized as the primary causal factors in aging. We narrow attention to the roles of protein aging linked to prevalent amino acids chirality, enzymatic and spontaneous (non-enzymatic) post-translational modifications (PTMs ^SP), and non-equilibrium phase transitions. The homochirality of protein synthesis, resulting in the steady-state non-equilibrium condition of protein structure, makes them prone to multiple types of enzymatic and spontaneous PTMs, including racemization and isomerization. Spontaneous racemization leads to the loss of the balanced prevalent chirality. Advanced biological aging related to irreversible PTMs ^SP has been associated with the nontrivial interplay between somatic (molecular aging) and mental (psychological aging) health conditions. Through stress response systems (SRS), the environmental and psychological stressors contribute to the age-associated “collapse” of protein homochirality. The role of prevalent protein chirality and entropy of protein folding in biological aging is mainly overlooked. In a more generalized context, the time-dependent shift from enzymatic to the non-enzymatic transformation of biochirality might represent an important and yet underappreciated hallmark of aging. We provide the experimental arguments in support of the racemization theory of aging.

Do epigenetic clocks provide explanations for sex differences in lifespan? A cross-sectional twin study

Background

The sex gap in life expectancy has been narrowing in Finland over the past 4–5 decades; however, on average, women still live longer than men. Epigenetic clocks are markers for biological aging which predict life span. In this study, we examined the mediating role of lifestyle factors on the association between sex and biological aging in younger and older adults.

Methods

Our sample consists of younger and older twins (21‒42 years, n = 1 477; 50‒76 years, n = 763) including 151 complete younger opposite-sex twin pairs (21‒30 years). Blood-based DNA methylation was used to compute epigenetic age acceleration by 4 epigenetic clocks as a measure of biological aging. Path modeling was used to study whether the association between sex and biological aging is mediated through lifestyle-related factors, that is, education, body mass index, smoking, alcohol use, and physical activity.

Results

In comparison to women, men were biologically older and, in general, they had unhealthier life habits. The effect of sex on biological aging was partly mediated by body mass index and, in older twins, by smoking. Sex was directly associated with biological aging and the association was stronger in older twins.

Conclusions

Previously reported sex differences in life span are also evident in biological aging. Declining smoking prevalence among men is a plausible explanation for the narrowing of the difference in life expectancy between the sexes. Data generated by the epigenetic clocks may help in estimating the effects of lifestyle and environmental factors on aging and in predicting aging in future generations.

A quantile frailty index without dichotomization

measures of health quantify the aging process of individuals. They should be interpretable, associated with future adverse outcomes, and straightforward to assemble. We use the rank-ordering of risk within a population to construct a quantile frailty index (QFI) that avoids dichotomization, is convenient and interpretable, and is associated with adverse outcomes. We show that the QFI outperforms previous frailty index (FI) measures on cross-sectional laboratory data (NHANES, CSHA, and ELSA). We construct the QFI by ranking the risk of individuals with respect to a reference population. Sex-specific reference populations narrow male-female FI differences as a function of age, and improve predictive performance. With a fixed reference population of 80-85 year olds, our QFI appears similar to earlier FI measures. With an age-matched reference population for each individual, we obtain a QFI that contains very little age information and that has similar predictive performance as other age-controlled FI measures. Adding age as an auxiliary variable leads to significantly better performance. We conclude that age should be controlled for when evaluating the predictive performance of summary measures of health. This is straight-forward to do with the QFI.

Years of Schooling Could Reduce Epigenetic Aging: A Study of a Mexican Cohort

Adverse conditions in early life, including environmental, biological and social influences, are risk factors for ill-health during aging and the onset of age-related disorders. In this context, the recent field of social epigenetics offers a valuable method for establishing the relationships among them However, current clinical studies on environmental changes and lifespan disorders are limited. In this sense, the Tlaltizapan (Mexico) cohort, who 52 years ago was exposed to infant malnutrition, low income and poor hygiene conditions, represents a vital source for exploring such factors. Therefore, in the present study, 52 years later, we aimed to explore differences in clinical/biochemical/anthropometric and epigenetic (DNA methylation) variables between individuals from such a cohort, in comparison with an urban-raised sample. Interestingly, only cholesterol levels showed significant differences between the cohorts. On the other hand, individuals from the Tlaltizapan cohort with more years of schooling had a lower epigenetic age in the Horvath (p-value = 0.0225) and PhenoAge (p-value = 0.0353) clocks, compared to those with lower-level schooling. Our analysis indicates 12 differentially methylated sites associated with the PI3-Akt signaling pathway and galactose metabolism in individuals with different durations of schooling. In conclusion, our results suggest that longer durations of schooling could promote DNA methylation changes that may reduce epigenetic age; nevertheless, further studies are needed.

GrimAge Outperforms Other Epigenetic Clocks in the Prediction of Age-Related Clinical Phenotypes and All-Cause Mortality

The aging process is characterized by the presence of high interindividual variation between individuals of the same chronical age prompting a search for biomarkers that capture this heterogeneity. Epigenetic clocks measure changes in DNA methylation levels at specific CpG sites that are highly correlated with calendar age. The discrepancy resulting from the regression of DNA methylation age on calendar age is hypothesized to represent a measure of biological aging with a positive/negative residual signifying age acceleration (AA)/deceleration, respectively. The present study examines the associations of 4 epigenetic clocks-Horvath, Hannum, PhenoAge, GrimAge-with a wide range of clinical phenotypes (walking speed, grip strength, Fried frailty, polypharmacy, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MOCA), Sustained Attention Reaction Time, 2-choice reaction time), and with all-cause mortality at up to 10-year follow-up, in a sample of 490 participants in the Irish Longitudinal Study on Ageing (TILDA). HorvathAA and HannumAA were not predictive of health; PhenoAgeAA was associated with 4/9 outcomes (walking speed, frailty MOCA, MMSE) in minimally adjusted models, but not when adjusted for other social and lifestyle factors. GrimAgeAA by contrast was associated with 8/9 outcomes (all except grip strength) in minimally adjusted models, and remained a significant predictor of walking speed, .polypharmacy, frailty, and mortality in fully adjusted models. Results indicate that the GrimAge clock represents a step-improvement in the predictive utility of the epigenetic clocks for identifying age-related decline in an array of clinical phenotypes promising to advance precision medicine.

Childhood growth and development and DNA methylation age in mid-life

BACKGROUND

In the first study of its kind, we examine the association between growth and development in early life and DNAm age biomarkers in mid-life.

METHODS

Participants were from the Medical Research Council National Survey of Health and Development (n = 1376). Four DNAm age acceleration (AgeAccel) biomarkers were measured when participants were aged 53 years: AgeAccelHannum; AgeAccelHorvath; AgeAccelLevine; and AgeAccelGrim. Exposure variables included: relative weight gain (standardised residuals from models of current weight z-score on current height, and previous weight and height z-scores); and linear growth (standardised residuals from models of current height z-score on previous height and weight z-scores) during infancy (0-2 years, weight gain only), early childhood (2-4 years), middle childhood (4-7 years) and late childhood to adolescence (7-15 years); age at menarche; and pubertal stage for men at 14-15 years. The relationship between relative weight gain and linear growth and AgeAccel was investigated using conditional growth models. We replicated analyses from the late childhood to adolescence period and pubertal timing among 240 participants from The National Child and Development Study (NCDS).

RESULTS

A 1SD increase in relative weight gain in late childhood to adolescence was associated with 0.50 years (95% CI 0.20, 0.79) higher AgeAccelGrim. Although the CI includes the null, the estimate was similar in NCDS [0.57 years (95% CI - 0.01, 1.16)] There was no strong evidence that relative weight gain and linear growth in childhood was associated with any other AgeAccel biomarker. There was no relationship between pubertal timing in men and AgeAccel biomarkers. Women who reached menarche ≥ 12 years had 1.20 years (95% CI 0.15, 2.24) higher AgeAccelGrim on average than women who reached menarche < 12 years; however, this was not replicated in NCDS and was not statistically significant after Bonferroni correction.

CONCLUSIONS

Our findings generally do not support an association between growth and AgeAccel biomarkers in mid-life. However, we found rapid weight gain during pubertal development, previously related to higher cardiovascular disease risk, to be associated with older AgeAccelGrim. Given this is an exploratory study, this finding requires replication.

The degree of frailty as a translational measure of health in aging

Frailty is a multiply determined, age-related state of increased risk for adverse health outcomes. We review how the degree of frailty conditions the development of late-life diseases and modifies their expression. The risks for frailty range from subcellular damage to social determinants. These risks are often synergistic-circumstances that favor damage also make repair less likely. We explore how age-related damage and decline in repair result in cellular and molecular deficits that scale up to tissue, organ and system levels, where they are jointly expressed as frailty. The degree of frailty can help to explain the distinction between carrying damage and expressing its usual clinical manifestations. Studying people-and animals-who live with frailty, including them in clinical trials and measuring the impact of the degree of frailty are ways to better understand the diseases of old age and to establish best practices for the care of older adults.

Associations of Age, Sex, Race/Ethnicity, and Education With 13 Epigenetic Clocks in a Nationally Representative U.S. Sample: The Health and Retirement Study

BACKGROUND

Many DNA methylation-based indicators have been developed as summary measures of epigenetic aging. We examine the associations between 13 epigenetic clocks, including 4 second generation clocks, as well as the links of the clocks to social, demographic, and behavioral factors known to be related to health outcomes: sex, race/ethnicity, socioeconomic status, obesity, and lifetime smoking pack-years.

METHODS

The Health and Retirement Study is the data source which is a nationally representative sample of Americans over age 50. Assessment of DNA methylation was based on the EPIC chip and epigenetic clocks were developed based on existing literature.

RESULTS

The clocks vary in the strength of their relationships with age, with each other and with independent variables. Second generation clocks trained on health-related characteristics tend to relate more strongly to the sociodemographic and health behaviors known to be associated with health outcomes in this age group.

CONCLUSIONS

Users of this publicly available data set should be aware that epigenetic clocks vary in their relationships to age and to variables known to be related to the process of health change with age.

Epigenetic age acceleration is associated with cardiometabolic risk factors and clinical cardiovascular disease risk scores in African Americans

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of mortality among US adults. African Americans have higher burden of CVD morbidity and mortality compared to any other racial group. Identifying biomarkers for clinical risk prediction of CVD offers an opportunity for precision prevention and earlier intervention.

RESULTS

Using linear mixed models, we investigated the cross-sectional association between four measures of epigenetic age acceleration (intrinsic (IEAA), extrinsic (EEAA), PhenoAge (PhenoAA), and GrimAge (GrimAA)) and ten cardiometabolic markers of hypertension, insulin resistance, and dyslipidemia in 1,100 primarily hypertensive African Americans from sibships in the Genetic Epidemiology Network of Arteriopathy (GENOA). We then assessed the association between epigenetic age acceleration and time to self-reported incident CVD using frailty hazard models and investigated CVD risk prediction improvement compared to models with clinical risk scores (Framingham risk score (FRS) and the atherosclerotic cardiovascular disease (ASCVD) risk equation). After adjusting for sex and chronological age, increased epigenetic age acceleration was associated with higher systolic blood pressure (IEAA), higher pulse pressure (EEAA and GrimAA), higher fasting glucose (PhenoAA and GrimAA), higher fasting insulin (EEAA), lower low density cholesterol (GrimAA), and higher triglycerides (GrimAA). A five-year increase in GrimAA was associated with CVD incidence with a hazard ratio of 1.54 (95% CI 1.22-2.01) and remained significant after adjusting for CVD risk factors. The addition of GrimAA to risk score models improved model fit using likelihood ratio tests (P = 0.013 for FRS and P = 0.008 for ASCVD), but did not improve C statistics (P > 0.05). Net reclassification index (NRI) showed small but significant improvement in reassignment of risk categories with the addition of GrimAA to FRS (NRI: 0.055, 95% CI 0.040-0.071) and the ASCVD equation (NRI: 0.029, 95% CI 0.006-0.064).

CONCLUSIONS

Epigenetic age acceleration measures are associated with traditional CVD risk factors in an African-American cohort with a high prevalence of hypertension. GrimAA was associated with CVD incidence and slightly improved prediction of CVD events over clinical risk scores.

Telomere Length as a Marker of Biological Age: State-of-the-Art, Open Issues, and Future Perspectives

Telomere shortening is a well-known hallmark of both cellular senescence and organismal aging. An accelerated rate of telomere attrition is also a common feature of age-related diseases. Therefore, telomere length (TL) has been recognized for a long time as one of the best biomarkers of aging. Recent research findings, however, indicate that TL per se can only allow a rough estimate of aging rate and can hardly be regarded as a clinically important risk marker for age-related pathologies and mortality. Evidence is obtained that other indicators such as certain immune parameters, indices of epigenetic age, etc., could be stronger predictors of the health status and the risk of chronic disease. However, despite these issues and limitations, TL remains to be very informative marker in accessing the biological age when used along with other markers such as indices of homeostatic dysregulation, frailty index, epigenetic clock, etc. This review article is aimed at describing the current state of the art in the field and at discussing recent research findings and divergent viewpoints regarding the usefulness of leukocyte TL for estimating the human biological age.

The potential for complex computational models of aging

The gradual accumulation of damage and dysregulation during the aging of living organisms can be quantified. Even so, the aging process is complex and has multiple interacting physiological scales - from the molecular to cellular to whole tissues. In the face of this complexity, we can significantly advance our understanding of aging with the use of computational models that simulate realistic individual trajectories of health as well as mortality. To do so, they must be systems-level models that incorporate interactions between measurable aspects of age-associated changes. To incorporate individual variability in the aging process, models must be stochastic. To be useful they should also be predictive, and so must be fit or parameterized by data from large populations of aging individuals. In this perspective, we outline where we have been, where we are, and where we hope to go with such computational models of aging. Our focus is on data-driven systems-level models, and on their great potential in aging research.