Epigenetic measures of ageing predict the prevalence and incidence of leading causes of death and disease burden

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

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

The Impact of Childhood Mental Health and Substance Use on Methylation Aging Into Adulthood

OBJECTIVE

To test whether childhood mental health symptoms, substance use, and early adversity accelerate the rate of DNA methylation (DNAm) aging from adolescence to adulthood.

METHOD

DNAm was assayed from blood samples in 381 participants in both adolescence (mean [SD] age = 13.9 [1.6] years) and adulthood (mean [SD] age = 25.9 [2.7] years). Structured diagnostic interviews were completed with participants and their parents at multiple childhood observations (1,950 total) to assess symptoms of common mental health disorders (attention-deficit/hyperactivity disorder, oppositional defiant disorder, conduct disorder, anxiety, and depression) and common types of substance use (alcohol, cannabis, nicotine) and early adversities.

RESULTS

Neither childhood mental health symptoms nor substance use variables were associated with DNAm aging cross-sectionally. In contrast, the following mental health symptoms and substance variables were associated with accelerated DNAm aging from adolescence to adulthood: depressive symptoms (b = 0.314, SE = 0.127, p = .014), internalizing symptoms (b = 0.108, SE = 0.049, p = .029), weekly cannabis use (b =1.665, SE = 0.591, p = .005), and years of weekly cannabis use (b = 0.718, SE = 0.283, p = .012). In models testing all individual variables simultaneously, the combined effect of the variables was equivalent to a potential difference of 3.17 to 3.76 years in DNAm aging. A final model tested a variable assessing cumulative exposure to mental health symptoms, substance use, and early adversities. This cumulative variable was strongly associated with accelerated aging (b = 0.126, SE = 0.044, p = .005).

CONCLUSION

Mental health symptoms and substance use accelerated DNAm aging into adulthood in a manner consistent with a shared risk mechanism.

PLAIN LANGUAGE SUMMARY

Using data from 381 participants in the Great Smoky Mountains Study, the authors examined whether childhood mental health symptoms, substance use, and early adversity accelerate biological aging, as measured by DNA methylation age, from adolescence to adulthood. Depressive symptoms and cannabis use were found to significantly accelerate biological aging. Models that tested the combined effect of mental health symptoms, substance use, and early adversity demonstrated that there was a shared effect across these types of childhood problems on accelerated aging.

DNA Methylation-derived biological age and long-term mortality risk in subjects with type 2 diabetes

BACKGROUND

Individuals with type 2 diabetes (T2D) face an increased mortality risk, not fully captured by canonical risk factors. Biological age estimation through DNA methylation (DNAm), i.e. the epigenetic clocks, is emerging as a possible tool to improve risk stratification for multiple outcomes. However, whether these tools predict mortality independently of canonical risk factors in subjects with T2D is unknown.

METHODS

Among a cohort of 568 T2D patients followed for 16.8 years, we selected a subgroup of 50 subjects, 27 survived and 23 deceased at present, passing the quality check and balanced for all risk factors after propensity score matching. We analyzed DNAm from peripheral blood leukocytes using the Infinium Human MethylationEPIC BeadChip (Illumina) to evaluate biological aging through previously validated epigenetic clocks and assess the DNAm-estimated levels of selected inflammatory proteins and blood cell counts. We tested the associations of these estimates with mortality using two-stage residual-outcome regression analysis, creating a reference model on data from the group of survived patients.

RESULTS

Deceased subjects had higher median epigenetic age expressed with DNAmPhenoAge algorithm (57.49 [54.72; 60.58] years. vs. 53.40 [49.73; 56.75] years; p = 0.012), and accelerated DunedinPoAm pace of aging (1.05 [1.02; 1.11] vs. 1.02 [0.98; 1.06]; p = 0.012). DNAm PhenoAge (HR 1.16, 95% CI 1.05-1.28; p = 0.004) and DunedinPoAm (HR 3.65, 95% CI 1.43-9.35; p = 0.007) showed an association with mortality independently of canonical risk factors. The epigenetic predictors of 3 chronic inflammation-related proteins, i.e. CXCL10, CXCL11 and enRAGE, C-reactive protein methylation risk score and DNAm-based estimates of exhausted CD8 + T cell counts were higher in deceased subjects when compared to survived.

CONCLUSIONS

These findings suggest that biological aging, as estimated through existing epigenetic tools, is associated with mortality risk in individuals with T2D, independently of common risk factors and that increased DNAm-surrogates of inflammatory protein levels characterize deceased T2D patients. Replication in larger cohorts is needed to assess the potential of this approach to refine mortality risk in T2D.

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

INTRODUCTION

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

OBJECTIVE

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

METHODS

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

RESULTS

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

DISCUSSION/CONCLUSION

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

Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology

Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.

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.

Accelerated biological aging six decades after prenatal famine exposure

To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N = 951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944 to 1945, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.

The AccelerAge framework: a new statistical approach to predict biological age based on time-to-event data

Aging is a multifaceted and intricate physiological process characterized by a gradual decline in functional capacity, leading to increased susceptibility to diseases and mortality. While chronological age serves as a strong risk factor for age-related health conditions, considerable heterogeneity exists in the aging trajectories of individuals, suggesting that biological age may provide a more nuanced understanding of the aging process. However, the concept of biological age lacks a clear operationalization, leading to the development of various biological age predictors without a solid statistical foundation. This paper addresses these limitations by proposing a comprehensive operationalization of biological age, introducing the "AccelerAge" framework for predicting biological age, and introducing previously underutilized evaluation measures for assessing the performance of biological age predictors. The AccelerAge framework, based on Accelerated Failure Time (AFT) models, directly models the effect of candidate predictors of aging on an individual's survival time, aligning with the prevalent metaphor of aging as a clock. We compare predictors based on the AccelerAge framework to a predictor based on the GrimAge predictor, which is considered one of the best-performing biological age predictors, using simulated data as well as data from the UK Biobank and the Leiden Longevity Study. Our approach seeks to establish a robust statistical foundation for biological age clocks, enabling a more accurate and interpretable assessment of an individual's aging status.

Atherosclerotic Plaque Epigenetic Age Acceleration Predicts a Poor Prognosis and Is Associated With Endothelial-to-Mesenchymal Transition in Humans

BACKGROUND

Epigenetic age estimators (clocks) are predictive of human mortality risk. However, it is not yet known whether the epigenetic age of atherosclerotic plaques is predictive for the risk of cardiovascular events.

METHODS

Whole-genome DNA methylation of human carotid atherosclerotic plaques (n=485) and of blood (n=93) from the Athero-Express endarterectomy cohort was used to calculate epigenetic age acceleration (EAA). EAA was linked to clinical characteristics, plaque histology, and future cardiovascular events (n=136). We studied whole-genome DNA methylation and bulk and single-cell transcriptomics to uncover molecular mechanisms of plaque EAA. We experimentally confirmed our in silico findings using in vitro experiments in primary human coronary endothelial cells.

RESULTS

Male and female patients with severe atherosclerosis had a median chronological age of 69 years. The median epigenetic age was 65 years in females (median EAA, -2.2 [interquartile range, -4.3 to 2.2] years) and 68 years in males (median EAA, -0.3 [interquartile range, -2.9 to 3.8] years). Patients with diabetes and a high body mass index had higher plaque EAA. Increased EAA of plaque predicted future events in a 3-year follow-up in a Cox regression model (univariate hazard ratio, 1.7; P=0.0034) and adjusted multivariate model (hazard ratio, 1.56; P=0.02). Plaque EAA predicted outcome independent of blood EAA (hazard ratio, 1.3; P=0.018) and of plaque hemorrhage (hazard ratio, 1.7; P=0.02). Single-cell RNA sequencing in plaque samples from 46 patients in the same cohort revealed smooth muscle and endothelial cells as important cell types in plaque EAA. Endothelial-to-mesenchymal transition was associated with EAA, which was experimentally confirmed by TGFβ-triggered endothelial-to-mesenchymal transition inducing rapid epigenetic aging in coronary endothelial cells.

CONCLUSIONS

Plaque EAA is a strong and independent marker of poor outcome in patients with severe atherosclerosis. Plaque EAA was linked to mesenchymal endothelial and smooth muscle cells. Endothelial-to-mesenchymal transition was associated with EAA, which was experimentally validated. Epigenetic aging mechanisms may provide new targets for treatments that reduce atherosclerosis complications.

The Latent Aging of Cells

As epigenetic clocks have evolved from powerful estimators of chronological aging to predictors of mortality and disease risk, it begs the question of what role DNA methylation plays in the aging process. We hypothesize that while it has the potential to serve as an informative biomarker, DNA methylation could also be a key to understanding the biology entangled between aging, (de)differentiation, and epigenetic reprogramming. Here we use an unsupervised approach to analyze time associated DNA methylation from both in vivo and in vitro samples to measure an underlying signal that ties these phenomena together. We identify a methylation pattern shared across all three, as well as a signal that tracks aging in tissues but appears refractory to reprogramming, suggesting that aging and reprogramming may not be fully mirrored processes.

Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts

Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N = 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations.

Associations of Epigenetic Age Acceleration With CVD Risks Across the Lifespan: The Bogalusa Heart Study

Although epigenetic age acceleration (EAA) might serve as a molecular signature of childhood cardiovascular disease (CVD) risk factors and further promote midlife subclinical CVD, few studies have comprehensively examined these life course associations. This study sought to test whether childhood CVD risk factors predict EAA in adulthood and whether EAA mediates the association between childhood CVD risks and midlife subclinical disease. Among 1,580 Bogalusa Heart Study participants, we estimated extrinsic EAA, intrinsic EAA, PhenoAge acceleration (PhenoAgeAccel), and GrimAge acceleration (GrimAgeAccel) during adulthood. We tested prospective associations of longitudinal childhood body mass index (BMI), blood pressure, lipids, and glucose with EAAs using linear mixed effects models. After confirming EAAs with midlife carotid intima-media thickness and carotid plaque, structural equation models examined mediating effects of EAAs on associations of childhood CVD risk factors with subclinical CVD measures. After stringent multiple testing corrections, each SD increase in childhood BMI was significantly associated with 0.6-, 0.9-, and 0.5-year increases in extrinsic EAA, PhenoAgeAccel, and GrimAgeAccel, respectively (P < 0.001 for all 3 associations). Likewise, each SD increase in childhood log-triglycerides was associated with 0.5- and 0.4-year increases in PhenoAgeAccel and GrimAgeAccel (P < 0.001 for both), respectively, whereas each SD increase in childhood high-density lipoprotein cholesterol was associated with a 0.3-year decrease in GrimAgeAccel (P = 0.002). Our findings indicate that PhenoAgeAccel mediates an estimated 27.4% of the association between childhood log-triglycerides and midlife carotid intima-media thickness (P = 0.022). Our data demonstrate that early life CVD risk factors may accelerate biological aging and promote subclinical atherosclerosis.

Blood-Based Epigenetic Age Acceleration and Incident Colorectal Cancer Risk: Findings from a Population-Based Case-Control Study

This study investigates the association between epigenetic age acceleration (EAA) derived from DNA methylation and the risk of incident colorectal cancer (CRC). We utilized data from a random population sample of 9,360 individuals (men and women, aged 45-69) from the HAPIEE Study who had been followed up for 16 years. A nested case-control design yielded 35 incident CRC cases and 354 matched controls. Six baseline epigenetic age (EA) measures (Horvath, Hannum, PhenoAge, Skin and Blood (SB), BLUP, and Elastic Net (EN)) were calculated along with their respective EAAs. After adjustment, the odds ratios (ORs) for CRC risk per decile increase in EAA ranged from 1.20 (95% CI: 1.04-1.39) to 1.44 (95% CI: 1.21-1.76) for the Horvath, Hannum, PhenoAge, and BLUP measures. Conversely, the SB and EN EAA measures showed borderline inverse associations with ORs of 0.86-0.87 (95% CI: 0.76-0.99). Tertile analysis reinforced a positive association between CRC risk and four EAA measures (Horvath, Hannum, PhenoAge, and BLUP) and a modest inverse relationship with EN EAA. Our findings from a prospective population-based-case-control study indicate a direct association between incident CRC and four markers of accelerated baseline epigenetic age. In contrast, two markers showed a negative association or no association. These results warrant further exploration in larger cohorts and may have implications for CRC risk assessment and prevention.

Clarifying the biological and statistical assumptions of cross-sectional biological age predictors: an elaborate illustration using synthetic and real data

BACKGROUND

There is divergence in the rate at which people age. The concept of biological age is postulated to capture this variability, and hence to better represent an individual's true global physiological state than chronological age. Biological age predictors are often generated based on cross-sectional data, using biochemical or molecular markers as predictor variables. It is assumed that the difference between chronological and predicted biological age is informative of one's chronological age-independent aging divergence ∆.

METHODS

We investigated the statistical assumptions underlying the most popular cross-sectional biological age predictors, based on multiple linear regression, the Klemera-Doubal method or principal component analysis. We used synthetic and real data to illustrate the consequences if this assumption does not hold.

RESULTS

The most popular cross-sectional biological age predictors all use the same strong underlying assumption, namely that a candidate marker of aging's association with chronological age is directly informative of its association with the aging rate ∆. We called this the identical-association assumption and proved that it is untestable in a cross-sectional setting. If this assumption does not hold, weights assigned to candidate markers of aging are uninformative, and no more signal may be captured than if markers would have been assigned weights at random.

CONCLUSIONS

Cross-sectional methods for predicting biological age commonly use the untestable identical-association assumption, which previous literature in the field had never explicitly acknowledged. These methods have inherent limitations and may provide uninformative results, highlighting the importance of researchers exercising caution in the development and interpretation of cross-sectional biological age predictors.

Prenatal and childhood lead exposure is prospectively associated with biological markers of aging in adolescence

Few studies have related early life lead exposure to adolescent biological aging, a period characterized by marked increases in maturational tempo. We examined associations between prenatal and childhood lead exposure and adolescent biological age (mean 14.5 years) utilizing multiple epigenetic clocks including: intrinsic (IEAA), extrinsic (EEAA), Horvath, Hannum, PhenoAge, GrimAge, Skin-Blood, Wu, PedBE, as well as DNA methylation derived telomere length (DNAmTL). Epigenetic clocks and DNAmTL were calculated via adolescent blood DNA methylation measured by Infinium MethylationEPIC BeadChips. We constructed general linear models (GLMs) with individual lead measures predicting biological age. We additionally examined sex-stratified models and lead by sex interactions, adjusting for adolescent age and lead levels, maternal smoking and education, and proportion of cell types. We also estimated effects of lead exposure on biological age using generalized estimating equations (GEE). First trimester blood lead was positively associated with a 0.14 increase in EEAA age in the GLMs though not the GEE models (95%CI 0.03, 0.25). First and 2nd trimester blood lead levels were associated with a 0.02 year increase in PedBE age in GLM and GEE models (1st trimester, 95%CI 0.004, 0.03; 2nd trimester, 95%CI 0.01, 0.03). Third trimester and 24 month blood lead levels were associated with a -0.06 and -0.05 decrease in Skin-Blood age, respectively, in GLM models. Additionally, 3rd trimester blood lead levels were associated with a 0.08 year decrease in Hannum age in GLM and GEE models (95%CI -0.15, -0.01). There were multiple significant results in sex-stratified models and significant lead by sex interactions, where males experienced accelerated biological age, compared to females who saw a decelerated biological age, with respect to IEAA, EEAA, Horvath, Hannum, and PedBE clocks. Further research is needed to understand sex-specific relationships between lead exposure and measures of biological aging in adolescence and the trajectory of biological aging into young adulthood.

Validation of biomarkers of aging

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

Stressful life events, social support, and epigenetic aging in the Women's Health Initiative

BACKGROUND

Elevated psychosocial stress has been linked with accelerated biological aging, including composite DNA methylation (DNAm) markers that predict aging-related outcomes ("epigenetic age"). However, no study has examined whether stressful life events (SLEs) are associated with epigenetic age acceleration in postmenopausal women, an aging population characterized by increased stress burden and disease risk.

METHODS

We leveraged the Women's Health Initiative, a large muti-ancestry cohort of postmenopausal women with available psychosocial stress measures over the past year and epigenomic data. SLEs and social support were ascertained via self-report questionnaires. Whole blood DNAm array (450 K) data were used to calculate five DNAm-based predictors of chronological age, health span and life span, and telomere length (HorvathAge, HannumAge, PhenoAge, GrimAge, DNAmTL).

RESULTS

After controlling for potential confounders, higher SLE burden was significantly associated with accelerated epigenetic aging, as measured by GrimAge (β: 0.34, 95% CI: 0.08, 0.59) and DNAmTL (β: -0.016, 95% CI: -0.028, -0.004). Exploratory analyses showed that SLEs-GrimAge associations were stronger in Black women as compared to other races/ethnicities and in those with lower social support levels. In women with lower social support, SLEs-DNAmTL associations showed opposite association in Hispanic women as compared to other race/ethnicity groups.

CONCLUSIONS

Our findings suggest that elevated stress burden is associated with accelerated epigenetic aging in postmenopausal women. Lower social support and/or self-reported race/ethnicity may modify the association of stress with epigenetic age acceleration. These findings advance understanding of how stress may contribute to aging-related outcomes and have important implications for disease prevention and treatment in aging women.

Associations of combined phenotypic ageing and genetic risk with incidence of chronic respiratory diseases in the UK Biobank: a prospective cohort study

BACKGROUND

Accelerated biological ageing has been associated with an increased risk of several chronic respiratory diseases. However, the associations between phenotypic age, a new biological age indicator based on clinical chemistry biomarkers, and common chronic respiratory diseases have not been evaluated.

METHODS

We analysed data from 308 592 participants at baseline in the UK Biobank. The phenotypic age was calculated from chronological age and nine clinical chemistry biomarkers, including albumin, alkaline phosphatase, creatinine, glucose, C-reactive protein, lymphocyte percent, mean cell volume, red cell distribution width and white blood cell count. Furthermore, phenotypic age acceleration (PhenoAgeAccel) was calculated by regressing phenotypic age on chronological age. The associations of PhenoAgeAccel with incident common chronic respiratory diseases and cross-sectional lung function were investigated. Moreover, we constructed polygenic risk scores and evaluated whether PhenoAgeAccel modified the effect of genetic susceptibility on chronic respiratory diseases and lung function.

RESULTS

The results showed significant associations of PhenoAgeAccel with increased risk of idiopathic pulmonary fibrosis (IPF) (hazard ratio (HR) 1.52, 95% CI 1.45-1.59), COPD (HR 1.54, 95% CI 1.51-1.57) and asthma (HR 1.18, 95% CI 1.15-1.20) per 5-year increase and decreased lung function. There was an additive interaction between PhenoAgeAccel and the genetic risk for IPF and COPD. Participants with high genetic risk and who were biologically older had the highest risk of incident IPF (HR 5.24, 95% CI 3.91-7.02), COPD (HR 2.99, 95% CI 2.66-3.36) and asthma (HR 2.07, 95% CI 1.86-2.31). Mediation analysis indicated that PhenoAgeAccel could mediate 10∼20% of the associations between smoking and chronic respiratory diseases, while ∼10% of the associations between particulate matter with aerodynamic diameter <2.5 µm and the disorders were mediated by PhenoAgeAccel.

CONCLUSION

PhenoAgeAccel was significantly associated with incident risk of common chronic respiratory diseases and decreased lung function and could serve as a novel clinical biomarker.

Geroscience-Centric Perspective for Geriatric Psychiatry: Integrating Aging Biology With Geriatric Mental Health Research

The geroscience hypothesis asserts that physiological aging is caused by a small number of biological pathways. Despite the explosion of geroscience research over the past couple of decades, the research on how serious mental illnesses (SMI) affects the biological aging processes is still in its infancy. In this review, we aim to provide a critical appraisal of the emerging literature focusing on how we measure biological aging systematically, and in the brain and how SMIs affect biological aging measures in older adults. We will also review recent developments in the field of cellular senescence and potential targets for interventions for SMIs in older adults, based on the geroscience hypothesis.

Hidalgo B, Aroke EN. Neighborhood Environment and Epigenetic Age: A Scoping Review

BACKGROUND

Interest in how the neighborhood environment impacts age-related health conditions has been increasing for decades. Epigenetic changes are environmentally derived modifications to the genome that alter the way genes function-thus altering health status. Epigenetic age, a biomarker for biological age, has been shown to be a useful predictor of several age-related health conditions. Consequently, its relation to the neighborhood environment has been the focus of a growing body of literature.

OBJECTIVE

We aimed to describe the scope of the evidence on the relationship between neighborhood environmental characteristics and epigenetic age.

METHODS

Using scoping review following methods established by Arksey and O'Malley, we first defined our research questions and searched the literature in PubMed, PsycINFO, and EMBASE. Next, we selected the literature to be included, and finally, we analyzed and summarized the information.

RESULTS

Nine articles met the inclusion criteria. Most studies examined deprivation as the neighborhood characteristic of interest. While all studies were observational in design, the articles included diverse participants, including men and women, adults and children, and multiple ethnicities. Results demonstrated a relationship between the neighborhood environment and epigenetic age, whether the characteristic of interest is socioeconomic or physical.

CONCLUSIONS

Overall, studies concluded there was a relationship between neighborhood characteristics and epigenetic age, whether the characteristic of interest was socioeconomic or physical. However, findings varied based on how the neighborhood characteristic and/or epigenetic age was measured. Furthermore, a paucity of investigations on physical characteristics was noticeable and warrants increased attention.

Accelerated biological aging six decades after prenatal famine exposure

To test the hypothesis that early-life adversity accelerates the pace of biological aging, we analyzed data from the Dutch Hunger Winter Families Study (DHWFS, N=951). DHWFS is a natural-experiment birth-cohort study of survivors of in-utero exposure to famine conditions caused by the German occupation of the Western Netherlands in Winter 1944-5, matched controls, and their siblings. We conducted DNA methylation analysis of blood samples collected when the survivors were aged 58 to quantify biological aging using the DunedinPACE, GrimAge, and PhenoAge epigenetic clocks. Famine survivors had faster DunedinPACE, as compared with controls. This effect was strongest among women. Results were similar for GrimAge, although effect-sizes were smaller. We observed no differences in PhenoAge between survivors and controls. Famine effects were not accounted for by blood-cell composition and were similar for individuals exposed early and later in gestation. Findings suggest in-utero undernutrition may accelerate biological aging in later life.

Relationship between an ageing measure and chronic obstructive pulmonary disease, lung function: a cross-sectional study of NHANES, 2007-2010

OBJECTIVES

Chronic obstructive pulmonary disease (COPD) is a disease associated with ageing. However, actual age does not accurately reflect the degree of biological ageing. Phenotypic age (PhenoAge) is a new indicator of biological ageing, and phenotypic age minus actual age is known as phenotypic age acceleration (PhenoAgeAccel). This research aimed to analyse the relationship between PhenoAgeAccel and lung function and COPD.

DESIGN

A cross-sectional study.

PARTICIPANTS

Data for the study were obtained from the National Health and Nutrition Examination Survey (NHANES) 2007-2010. We defined people with forced expiratory volume in 1 s/forced vital capacity <0.70 after inhaled bronchodilators as COPD and the rest of the population as non-COPD. Adults aged 40 years or older were enrolled in the study.

PRIMARY AND SECONDARY OUTCOME MEASURES

Linear and logistic regression were used to investigate the relationship between PhenoAgeAccel, lung function and COPD. Subgroup analysis was performed by gender, age, ethnicity and smoking index COPD. In addition, we analysed the relationship between the smoking index, respiratory symptoms and PhenoAgeAccel. Multiple models were used to reduce confounding bias.

RESULTS

5397 participants were included in our study, of which 1042 had COPD. Compared with PhenoAgeAccel Quartile1, Quartile 4 had a 52% higher probability of COPD; elevated PhenoAgeAccel was also significantly associated with reduced lung function. Further subgroup analysis showed that high levels of PhenoAgeAccel had a more significant effect on lung function in COPD, older adults and whites (P for interaction <0.05). Respiratory symptoms and a high smoking index were related to higher indicators of ageing.

CONCLUSIONS

Our study found that accelerated ageing is associated with the development of COPD and impaired lung function. Smoking cessation and anti-ageing therapy have potential significance in COPD.

Climate change and epigenetic biomarkers in allergic and airway diseases

Human epigenetic variation is associated with both environmental exposures and allergic diseases and can potentially serve as a biomarker connecting climate change with allergy and airway diseases. In this narrative review, we summarize recent human epigenetic studies examining exposure to temperature, precipitation, extreme weather events, and malnutrition to discuss findings as they relate to allergic and airway diseases. Temperature has been the most widely studied exposure, with the studies implicating both short-term and long-term exposures with epigenetic alterations and epigenetic aging. Few studies have examined natural disasters or extreme weather events. The studies available have reported differential DNA methylation of multiple genes and pathways, some of which were previously associated with asthma or allergy. Few studies have integrated climate-related events, epigenetic biomarkers, and allergic disease together. Prospective longitudinal studies are needed along with the collection of target tissues beyond blood samples, such as nasal and skin cells. Finally, global collaboration to increase diverse representation of study participants, particularly those most affected by climate injustice, as well as strengthen replication, validation, and harmonization of measurements will be needed to elucidate the impacts of climate change on the human epigenome.

Epigenetic aging and PTSD outcomes in the immediate aftermath of trauma

BACKGROUND

Psychological trauma exposure and posttraumatic stress disorder (PTSD) have been associated with advanced epigenetic age. However, whether epigenetic aging measured at the time of trauma predicts the subsequent development of PTSD outcomes is unknown. Moreover, the neural substrates underlying posttraumatic outcomes associated with epigenetic aging are unclear.

METHODS

We examined a multi-ancestry cohort of women and men (n = 289) who presented to the emergency department (ED) after trauma. Blood DNA was collected at ED presentation, and EPIC DNA methylation arrays were used to assess four widely used metrics of epigenetic aging (HorvathAge, HannumAge, PhenoAge, and GrimAge). PTSD symptoms were evaluated longitudinally at the time of ED presentation and over the ensuing 6 months. Structural and functional neuroimaging was performed 2 weeks after trauma.

RESULTS

After covariate adjustment and correction for multiple comparisons, advanced ED GrimAge predicted increased risk for 6-month probable PTSD diagnosis. Secondary analyses suggested that the prediction of PTSD by GrimAge was driven by worse trajectories for intrusive memories and nightmares. Advanced ED GrimAge was also associated with reduced volume of the whole amygdala and specific amygdala subregions, including the cortico-amygdaloid transition and the cortical and accessory basal nuclei.

CONCLUSIONS

Our findings shed new light on the relation between biological aging and trauma-related phenotypes, suggesting that GrimAge measured at the time of trauma predicts PTSD trajectories and is associated with relevant brain alterations. Furthering these findings has the potential to enhance early prevention and treatment of posttraumatic psychiatric sequelae.

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

BACKGROUND AND OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Contributions of neighborhood social environment and air pollution exposure to Black-White disparities in epigenetic aging

Racial disparities in many aging-related health outcomes are persistent and pervasive among older Americans, reflecting accelerated biological aging for Black Americans compared to White, known as weathering. Environmental determinants that contribute to weathering are poorly understood. Having a higher biological age, measured by DNA methylation (DNAm), than chronological age is robustly associated with worse age-related outcomes and higher social adversity. We hypothesize that individual socioeconomic status (SES), neighborhood social environment, and air pollution exposures contribute to racial disparities in DNAm aging according to GrimAge and Dunedin Pace of Aging methylation (DPoAm). We perform retrospective cross-sectional analyses among 2,960 non-Hispanic participants (82% White, 18% Black) in the Health and Retirement Study whose 2016 DNAm age is linked to survey responses and geographic data. DNAm aging is defined as the residual after regressing DNAm age on chronological age. We observe Black individuals have significantly accelerated DNAm aging on average compared to White individuals according to GrimAge (239%) and DPoAm (238%). We implement multivariable linear regression models and threefold decomposition to identify exposures that contribute to this disparity. Exposure measures include individual-level SES, census-tract-level socioeconomic deprivation and air pollution (fine particulate matter, nitrogen dioxide, and ozone), and perceived neighborhood social and physical disorder. Race and gender are included as covariates. Regression and decomposition results show that individual-level SES is strongly associated with and accounts for a large portion of the disparity in both GrimAge and DPoAm aging. Higher neighborhood deprivation for Black participants significantly contributes to the disparity in GrimAge aging. Black participants are more vulnerable to fine particulate matter exposure for DPoAm, perhaps due to individual- and neighborhood-level SES, which may contribute to the disparity in DPoAm aging. DNAm aging may play a role in the environment "getting under the skin", contributing to age-related health disparities between older Black and White Americans.

Biomarkers selection and mathematical modeling in biological age estimation

Biological age (BA) is important for clinical monitoring and preventing aging-related disorders and disabilities. Clinical and/or cellular biomarkers are measured and integrated in years using mathematical models to display an individual's BA. To date, there is not yet a single or set of biomarker(s) and technique(s) that is validated as providing the BA that reflects the best real aging status of individuals. Herein, a comprehensive overview of aging biomarkers is provided and the potential of genetic variations as proxy indicators of the aging state is highlighted. A comprehensive overview of BA estimation methods is also provided as well as a discussion of their performances, advantages, limitations, and potential approaches to overcome these limitations.

Biological Age Acceleration and Motoric Cognitive Risk Syndrome

OBJECTIVE

Motoric cognitive risk (MCR) syndrome, a predementia syndrome characterized by slow gait and subjective cognitive concerns, is associated with multiple age-related risk factors. We hypothesized that MCR is associated with biological age acceleration. We examined the associations of biological age acceleration with MCR, and mortality risk in MCR cases.

METHODS

Biological age was determined using proteomic and epigenetic clocks in participants aged 65 years and older in the LonGenity study (N = 700, females = 57.9%) and Health and Retirement Study (HRS; N = 1,043, females = 57.1%) cohorts. Age acceleration (AgeAccel) was operationally defined as the residual from regressing predicted biological age (from both clocks separately) on chronological age. Association of AgeAccel with incident MCR in the overall sample as well as with mortality risk in MCR cases was examined using Cox models and reported as hazard ratios (HRs).

RESULTS

AgeAccel scores derived from a proteomic clock were associated with prevalent MCR (odds ratio adjusted for age, gender, education years, and chronic illnesses [aOR] = 1.36, 95% confidence interval [CI] = 1.09-1.71) as well as predicted incident MCR (HR = 1.19, 95% CI = 1.00-1.41) in the LonGenity cohort. In HRS, the association of AgeAccel using an epigenetic clock with prevalent MCR was confirmed (aOR = 1.47, 95% CI = 1.16-1.85). Participants with MCR and accelerated aging (positive AgeAccel score) were at the highest risk for mortality in both LonGenity (HR = 3.38, 95% CI = 2.01-5.69) and HRS (HR = 2.47, 95% CI = 1.20-5.10).

INTERPRETATION

Accelerated aging predicts risk for MCR, and is associated with higher mortality in MCR patients. ANN NEUROL 2023;93:1187-1197.

Direct and Indirect Effects of Socioeconomic Status and Discrimination on Subjective Cognitive Decline: A Longitudinal Study of African American Women

OBJECTIVES

The present study builds on recent findings suggesting that the stress of institutional and interpersonal racism may contribute to African Americans' elevated risk for dementia. We investigated the extent to which 2 consequences of racism-low socioeconomic status (SES) and discrimination-predict self-reported cognitive decline (SCD) 19 years later. Further, we examined potential mediating pathways that might link SES and discrimination to cognitive decline. Potential mediators included depression, accelerated biological aging, and onset of chronic illnesses.

METHODS

Hypotheses were tested using a sample of 293 African American women. SCD was assessed using the Everyday Cognition Scale. Structural equation modeling was used to assess the effects of SES and racial discrimination, both measured in 2002, on SCD reported in 2021. Turning to the mediators, midlife depression was assessed in 2002, accelerated aging in 2019, and chronic illness in 2019. Age and prodrome depression were included as covariates.

RESULTS

There were direct effects of SES and discrimination on SCD. In addition, these 2 stressors showed a significant indirect effect on SCD through depression. Finally, there was evidence for a more complex pathway where SES and discrimination accelerate biological aging, with accelerated aging, in turn leading to chronic illness, which then predicted SCD.

DISCUSSION

Results of the present study add to a growing literature indicating that living in a racialized society is a central factor in explaining the high risk for dementia among Black Americans. Future research should continue to emphasize the various ways that exposure to racism over the life course effects cognition.

Epigenetic ageing accelerates before antiretroviral therapy and decelerates after viral suppression in people with HIV in Switzerland: a longitudinal study over 17 years

BACKGROUND

Accelerated epigenetic ageing can occur in untreated HIV infection and is partially reversible with effective antiretroviral therapy (ART). We aimed to make a long-term comparison of epigenetic ageing dynamics in people with HIV during untreated HIV infection and during suppressive ART.

METHODS

In this longitudinal study, conducted over 17 years in HIV outpatient clinics in Switzerland, we applied 5 established epigenetic age estimators (epigenetic clocks) in peripheral blood mononuclear cells (PBMCs) in Swiss HIV Cohort Study participants before or during suppressive ART. All participants had a longitudinal set of PBMC samples available at four timepoints (T1-T4). T1 and T2 had to be 3 years or longer apart, as did T3 and T4. We assessed epigenetic age acceleration (EAA) and a novel rate of epigenetic ageing.

FINDINGS

Between March 13, 1990, and Jan 18, 2018, we recruited 81 people with HIV from the Swiss HIV Cohort Study. We excluded one participant because a sample did not meet quality checks (transmission error). 52 (65%) of 80 patients were men, 76 (95%) were white, and the median patient age was 43 (IQR 37·5-47) years. Per year of untreated HIV infection (median observation 8·08 years, IQR 4·83-11·09), mean EAA was 0·47 years (95% CI 0·37 to 0·57) for Horvath's clock, 0·43 years (0·3 to 0·57) for Hannum's clock, 0·36 years (0·27 to 0·44) for SkinBlood clock, and 0·69 years (0·51 to 0·86) for PhenoAge. Per year of suppressive ART (median observation 9·8 years, IQR 7·2-11), mean EAA was -0·35 years (95% CI -0·44 to -0·27) for Horvath's clock, -0·39 years (-0·50 to -0·27) for Hannum's clock, -0·26 years (-0·33 to -0·18) for SkinBlood clock, and -0·49 years (-0·64 to -0·35) for PhenoAge. Our findings indicate that people with HIV epigenetically aged by a mean of 1·47 years for Horvath's clock, 1·43 years for Hannum's clock, 1·36 years for SkinBlood clock, and 1·69 years for PhenoAge per year of untreated HIV infection; and 0·65 years for Horvath's clock, 0·61 years for Hannum's clock, 0·74 years for SkinBlood clock, and 0·51 years for PhenoAge, per year of suppressive ART. GrimAge showed some change in the mean EAA during untreated HIV infection (0·10 years, 0·02 to 0·19) and suppressive ART (-0·05 years, -0·12 to 0·02). We obtained very similar results using the rate of epigenetic ageing. Contribution of multiple HIV-related, antiretroviral, and immunological variables, and of a DNA methylation-associated polygenic risk score to EAA was small.

INTERPRETATION

In a longitudinal study over more than 17 years, epigenetic ageing accelerated during untreated HIV infection and decelerated during suppressive ART, highlighting the importance of limiting the duration of untreated HIV infection.

FUNDING

Swiss HIV Cohort Study, Swiss National Science Foundation, and Gilead Sciences.

Clinical biomarker-based biological aging and risk of cancer in the UK Biobank

BACKGROUND

Despite a clear link between aging and cancer, there has been inconclusive evidence on how biological age (BA) may be associated with cancer incidence.

METHODS

We studied 308,156 UK Biobank participants with no history of cancer at enrolment. Using 18 age-associated clinical biomarkers, we computed three BA measures (Klemera-Doubal method [KDM], PhenoAge, homeostatic dysregulation [HD]) and assessed their associations with incidence of any cancer and five common cancers (breast, prostate, lung, colorectal, and melanoma) using Cox proportional-hazards models.

RESULTS

A total of 35,426 incident cancers were documented during a median follow-up of 10.9 years. Adjusting for common cancer risk factors, 1-standard deviation (SD) increment in the age-adjusted KDM (hazard ratio = 1.04, 95% confidence interval = 1.03-1.05), age-adjusted PhenoAge (1.09, 1.07-1.10), and HD (1.02, 1.01-1.03) was significantly associated with a higher risk of any cancer. All BA measures were also associated with increased risks of lung and colorectal cancers, but only PhenoAge was associated with breast cancer risk. Furthermore, we observed an inverse association between BA measures and prostate cancer, although it was attenuated after removing glycated hemoglobin and serum glucose from the BA algorithms.

CONCLUSIONS

Advanced BA quantified by clinical biomarkers is associated with increased risks of any cancer, lung cancer, and colorectal cancer.

ADHD genetic burden associates with older epigenetic age: mediating roles of education, behavioral and sociodemographic factors among older adults

BACKGROUND

Shortened lifespans are associated with having Attention Deficit Hyperactivity Disorder (ADHD), which is likely mediated by related behavioral and sociodemographic factors that are also associated with accelerated physiological aging. Such factors include exhibiting more depressive symptoms, more cigarette smoking, higher body mass index, lower educational attainment, lower income in adulthood, and more challenges with cognitive processes compared to the general population. A higher polygenic score for ADHD (ADHD-PGS) is associated with having more characteristic features of ADHD. The degree to which (1) the ADHD-PGS associates with an epigenetic biomarker developed to predict accelerated aging and earlier mortality is unknown, as are whether (2) an association would be mediated by behavioral and sociodemographic correlates of ADHD, or (3) an association would be mediated first by educational attainment, then by behavioral and sociodemographic correlates. We evaluated these relationships in a population-based sample from the US Health and Retirement Study, among N = 2311 adults age 50 and older, of European-ancestry, with blood-based epigenetic and genetic data. The ADHD-PGS was calculated from a prior genomewide meta-analysis. Epigenome-wide DNA methylation levels that index biological aging and earlier age of mortality were quantified by a blood-based biomarker called GrimAge. We used a structural equation modeling approach to test associations with single and multi-mediation effects of behavioral and contextual indicators on GrimAge, adjusted for covariates.

RESULTS

The ADHD-PGS was significantly and directly associated with GrimAge when adjusting for covariates. In single mediation models, the effect of the ADHD-PGS on GrimAge was partially mediated via smoking, depressive symptoms, and education. In multi-mediation models, the effect of the ADHD-PGS on GrimAge was mediated first through education, then smoking, depressive symptoms, BMI, and income.

CONCLUSIONS

Findings have implications for geroscience research in elucidating lifecourse pathways through which ADHD genetic burden and symptoms can alter risks for accelerated aging and shortened lifespans, when indexed by an epigenetic biomarker. More education appears to play a central role in attenuating negative effects on epigenetic aging from behavioral and sociodemographic risk factors related to ADHD. We discuss implications for the potential behavioral and sociodemographic mediators that may attenuate negative biological system effects.

Depressive symptoms are associated with DNA methylation age acceleration in a cross-sectional analysis of adults over age 50 in the United States

Background

Major depressive disorder affects mental well-being and accelerates DNA methylation age, a marker of biological aging. Subclinical depressive symptoms and DNA methylation aging have not been explored.

Objective

To assess the cross-sectional association between depressive symptoms and accelerated DNA methylation aging among United States adults over age 50.

Methods

We included 3,793 participants from the 2016 wave of the Health and Retirement Study. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression scale and operationalized as high versus low/no. Blood DNA methylation GrimAge was regressed on chronologic age to obtain acceleration. Multiple linear regression assessed the relationship between high depressive symptoms and GrimAge acceleration, controlling for demographic factors, health behaviors, and cell type proportions. We investigated sex and race/ethnicity stratified associations.

Results

Participants were 42% male, 14% had high depressive symptoms, 44% had accelerated GrimAge, and were mean age 70 years. In our fully adjusted model, those with high depressive symptoms had 0.40 (95%CI: 0.06, 0.73) years accelerated GrimAge, compared to those with low/no depressive symptoms. The association between depressive symptoms and GrimAge acceleration was larger in male participants ( P = 0.04).

Conclusion

Higher depressive symptoms were associated with accelerated DNA methylation age among older adults.

Epigenetic Age in Peripheral Blood Among Children, Adolescent, and Adult Survivors of Childhood Cancer

Importance

Certain cancer therapies are risk factors for epigenetic age acceleration (EAA) among survivors of childhood cancer, and EAA is associated with chronic health conditions (CHCs). However, small numbers of younger survivors (aged <20 years) previously evaluated have limited the ability to calculate EAA among this age group.

Objective

To evaluate the change rate of epigenetic age (EA) and EAA in younger compared with older survivors and the possible association of EAA with early-onset obesity (aged <20 years), severity/burden of CHCs, and late mortality (>5 years from cancer diagnosis).

Design, Setting, and Participants

Study participants were from the St Jude Lifetime Cohort, initiated in 2007 with ongoing follow-up. The present study was conducted from April 17, 2022, to March 23, 2023. Survivors in this cohort of European ancestry with DNA methylation data were included. Cross-sectional annual changes in EA and EAA were compared across 5 different chronologic age groups: age 0 to 9 (children), 10 to 19 (adolescents), 20 to 34 (younger adults), 35 to 49 (middle-aged adults), and greater than or equal to 50 (older adults) years. Logistic regression evaluated the association between EAA and early-onset obesity or severity/burden of CHCs. Cox proportional hazards regression assessed the association between EAA and late mortality.

Main Outcomes and Measures

Early-onset obesity, severity/burden of CHCs (graded using the Common Terminology Criteria for Adverse Events (grade 1, mild; 2, moderate; 3, severe/disabling; 4, life-threatening) and were combined into high vs low severity/burden based on frequency and grade), and late mortality were the outcomes based on follow-up until April 2020. Expanded DNA methylation profiling increased the number of survivors younger than 20 years (n = 690). Epigenetic age was calculated primarily using the Levine clock, and EAA was derived from least squares regression of EA against chronologic age and was standardized to a z score (Levine EEA).

Results

Among 2846 participants (median age, 30.3 [IQR, 9.3-41.5] years; 53% males), the cross-sectional annual change in EA_Levine was higher in children (1.63 years) and adolescents (1.14 years), and the adjusted least-squares mean of Levine EEA was lower in children (-0.22 years) and older adults (-1.70 years). Each 1-SD increase in Levine EEA was associated with increased risk of developing early-onset obesity (odds ratio [OR], 1.46; 95% CI, 1.19-1.78), high severity/burden of CHCs (OR, 1.13; 95% CI, 1.03-1.24), and late mortality (hazard ratio, 1.75; 95% CI, 1.35-2.26).

Conclusions and Relevance

The findings of this study suggest that EAA measured in children and adolescent survivors of childhood cancer is associated with early-onset obesity, severity/burden of all CHCs, and late mortality. Evaluating EAA may help identify survivors of childhood cancer at increased risk for early-onset obesity, morbidity in general, and mortality.

DNA methylation patterns at birth predict health outcomes in young adults born very low birthweight

Background

Individuals born very low birthweight (VLBW) are at increased risk of impaired cardiovascular and respiratory function in adulthood. To identify markers to predict future risk for VLBW individuals, we analyzed DNA methylation at birth and at 28 years in the New Zealand (NZ) VLBW cohort (all infants born < 1500 g in NZ in 1986) compared with age-matched, normal birthweight controls. Associations between neonatal methylation and cardiac structure and function (echocardiography), vascular function and respiratory outcomes at age 28 years were documented.

Results

Genomic DNA from archived newborn heel-prick blood (n = 109 VLBW, 51 controls) and from peripheral blood at ~ 28 years (n = 215 VLBW, 96 controls) was analyzed on Illumina Infinium MethylationEPIC 850 K arrays. Following quality assurance and normalization, methylation levels were compared between VLBW cases and controls at both ages by linear regression, with genome-wide significance set to p < 0.05 adjusted for false discovery rate (FDR, Benjamini-Hochberg). In neonates, methylation at over 16,400 CpG methylation sites differed between VLBW cases and controls and the canonical pathway most enriched for these CpGs was Cardiac Hypertrophy Signaling (p = 3.44E⁻¹¹). The top 20 CpGs that differed most between VLBW cases and controls featured clusters in ARID3A, SPATA33, and PLCH1 and these 3 genes, along with MCF2L, TRBJ2-1 and SRC, led the list of 15,000 differentially methylated regions (DMRs) reaching FDR-adj significance. Fifteen of the 20 top CpGs in the neonate EWAS showed associations between methylation at birth and adult cardiovascular traits (particularly LnRHI). In 28-year-old adults, twelve CpGs differed between VLBW cases and controls at FDR-adjusted significance, including hypermethylation in EBF4 (four CpGs), CFI and UNC119B and hypomethylation at three CpGs in HIF3A and one in KCNQ1. DNA methylation GrimAge scores at 28 years were significantly greater in VLBW cases versus controls and weakly associated with cardiovascular traits. Four CpGs were identified where methylation differed between VLBW cases and controls in both neonates and adults, three reversing directions with age (two CpGs in EBF4, one in SNAI1 were hypomethylated in neonates, hypermethylated in adults). Of these, cg16426670 in EBF4 at birth showed associations with several cardiovascular traits in adults.

Conclusions

These findings suggest that methylation patterns in VLBW neonates may be informative about future adult cardiovascular and respiratory outcomes and have value in guiding early preventative care to improve adult health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-023-01463-3.

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.

A comparison of cognitive performances based on differing rates of DNA methylation GrimAge acceleration among older men and women

Cognitive heterogeneity increases with age rendering sex differences difficult to identify. Given established sex differences in biological aging, we examined whether comparisons of men and women on neuropsychological test performances differed as a function of age rate. Data were obtained from 1921 adults enrolled in the 2016 wave of the Health and Retirement Study. The residual from regressing the DNA methylation GrimAge clock on chronological age was used as the measure of aging rate. Slow and fast age rates were predefined as 1 standard deviation below or above the sex-specific mean rates, respectively. ANCOVAs were used to test group differences in test performances. Pairwise comparisons revealed that slow aging men outperformed fast aging women (and vice versa) on measures of executive function/speed, visual memory and semantic fluency; however, when groups were matched by aging rates, no significant differences remained. In contrast, women, regardless of their aging rates, education or depressive symptoms maintained their advantage on verbal learning and memory. Implications for research on sex differences in cognitive aging are discussed.

A human stem cell-derived neuronal model of morphine exposure reflects brain dysregulation in opioid use disorder: Transcriptomic and epigenetic characterization of postmortem-derived iPSC neurons

Introduction

Human-derived induced pluripotent stem cell (iPSC) models of brain promise to advance our understanding of neurotoxic consequences of drug use. However, how well these models recapitulate the actual genomic landscape and cell function, as well as the drug-induced alterations, remains to be established. New in vitro models of drug exposure are needed to advance our understanding of how to protect or reverse molecular changes related to substance use disorders.

Methods

We engineered a novel induced pluripotent stem cell-derived model of neural progenitor cells and neurons from cultured postmortem human skin fibroblasts, and directly compared these to isogenic brain tissue from the donor source. We assessed the maturity of the cell models across differentiation from stem cells to neurons using RNA cell type and maturity deconvolution analyses as well as DNA methylation epigenetic clocks trained on adult and fetal human tissue. As proof-of-concept of this model's utility for substance use disorder studies, we compared morphine- and cocaine-treated neurons to gene expression signatures in postmortem Opioid Use Disorder (OUD) and Cocaine Use Disorder (CUD) brains, respectively.

Results

Within each human subject (N = 2, 2 clones each), brain frontal cortex epigenetic age parallels that of skin fibroblasts and closely approximates the donor's chronological age; stem cell induction from fibroblast cells effectively sets the epigenetic clock to an embryonic age; and differentiation of stem cells to neural progenitor cells and then to neurons progressively matures the cells via DNA methylation and RNA gene expression readouts. In neurons derived from an individual who died of opioid overdose, morphine treatment induced alterations in gene expression similar to those previously observed in OUD ex-vivo brain tissue, including differential expression of the immediate early gene EGR1, which is known to be dysregulated by opioid use.

Discussion

In summary, we introduce an iPSC model generated from human postmortem fibroblasts that can be directly compared to corresponding isogenic brain tissue and can be used to model perturbagen exposure such as that seen in opioid use disorder. Future studies with this and other postmortem-derived brain cellular models, including cerebral organoids, can be an invaluable tool for understanding mechanisms of drug-induced brain alterations.

Epigenetic aging in patients diagnosed with coronary artery disease: results of the LipidCardio study

INTRODUCTION

People age biologically at different rates. Epigenetic clock-derived DNA methylation age acceleration (DNAmAA) is among the most promising markers proposed to assess the interindividual differences in biological age. Further research is needed to evaluate the characteristics of the different epigenetic clock biomarkers available with respect to the health domains they reflect best.

METHODS

In this study, we have analyzed 779 participants of the LipidCardio study (mean chronological age 69.9 ± 11.0 years, 30.6% women) who underwent diagnostic angiography at the Charité University Hospital in Berlin, Germany. DNA methylation age (DNAm age) was measured by methylation-sensitive single nucleotide primer extension (MS-SNuPE) and calculated with the 7-CpG clock. We compared the biological age as assessed as DNAmAA of participants with an angiographically confirmed coronary artery disease (CAD, n = 554) with participants with lumen reduction of 50% or less (n = 90) and patients with a normal angiogram (n = 135).

RESULTS

Participants with a confirmed CAD had on average a 2.5-year higher DNAmAA than patients with a normal angiogram. This association did not persist after adjustment for sex in a logistic regression analysis. High-density lipoprotein, low-density lipoprotein, triglycerides, lipoprotein (a), estimated glomerular filtration rate, physical activity, BMI, alcohol consumption, and smoking were not associated with DNAmAA.

CONCLUSION

The association between higher DNAmAA and angiographically confirmed CAD seems to be mainly driven by sex.

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 trajectories and accelerated epigenetic aging in incident type 2 diabetes

DNA methylation (DNAm) patterns across the genome changes during aging and development of complex diseases including type 2 diabetes (T2D). Our study aimed to estimate DNAm trajectories of CpG sites associated with T2D, epigenetic age (DNAmAge), and age acceleration based on four epigenetic clocks (GrimAge, Hannum, Horvath, phenoAge) in the period 10 years prior to and up to T2D onset. In this nested case-control study within Doetinchem Cohort Study, we included 132 incident T2D cases and 132 age- and sex-matched controls. DNAm was measured in blood using the Illumina Infinium Methylation EPIC array. From 107 CpG sites associated with T2D, 10 CpG sites (9%) showed different slopes of DNAm trajectories over time (p < 0.05) and an additional 8 CpG sites (8%) showed significant differences in DNAm levels (at least 1%, p-value per time point < 0.05) at all three time points with nearly parallel trajectories between incident T2D cases and controls. In controls, age acceleration levels were negative (slower epigenetic aging), while in incident T2D cases, levels were positive, suggesting accelerated aging in the case group. We showed that DNAm levels at specific CpG sites, up to 10 years before T2D onset, are different between incident T2D cases and healthy controls and distinct patterns of clinical traits over time may have an impact on those DNAm profiles. Up to 10 years before T2D diagnosis, cases manifested accelerated epigenetic aging. Markers of biological aging including age acceleration estimates based on Horvath need further investigation to assess their utility for predicting age-related diseases including T2D.

Sex differences in epigenetic age in Mediterranean high longevity regions

Sex differences in aging manifest in disparities in disease prevalence, physical health, and lifespan, where women tend to have greater longevity relative to men. However, in the Mediterranean Blue Zones of Sardinia (Italy) and Ikaria (Greece) are regions of centenarian abundance, male-female centenarian ratios are approximately one, diverging from the typical trend and making these useful regions in which to study sex differences of the oldest old. Additionally, these regions can be investigated as examples of healthy aging relative to other populations. DNA methylation (DNAm)-based predictors have been developed to assess various health biomarkers, including biological age, Pace of Aging, serum interleukin-6 (IL-6), and telomere length. Epigenetic clocks are biological age predictors whose deviation from chronological age has been indicative of relative health differences between individuals, making these useful tools for interrogating these differences in aging. We assessed sex differences between the Horvath, Hannum, GrimAge, PhenoAge, Skin and Blood, and Pace of Aging predictors from individuals in two Mediterranean Blue Zones and found that men displayed positive epigenetic age acceleration (EAA) compared to women according to all clocks, with significantly greater rates according to GrimAge (β = 3.55; p = 1.22 × 10^-12), Horvath (β = 1.07; p = 0.00378) and the Pace of Aging (β = 0.0344; p = 1.77 × 10^-08). Other DNAm-based biomarkers findings indicated that men had lower DNAm-predicted serum IL-6 scores (β = -0.00301, p = 2.84 × 10^-12), while women displayed higher DNAm-predicted proportions of regulatory T cells than men from the Blue Zone (p = 0.0150, 95% Confidence Interval [0.00131, 0.0117], Cohen's d = 0.517). All clocks showed better correlations with chronological age in women from the Blue Zones than men, but all clocks showed large mean absolute errors (MAE >30 years) in both sexes, except for PhenoAge (MAE <5 years). Thus, despite their equal survival to older ages in these Mediterranean Blue Zones, men in these regions remain biologically older by most measured DNAm-derived metrics than women, with the exception of the IL-6 score and proportion of regulatory T cells.

Socioeconomic Status, Biological Aging, and Memory in a Diverse National Sample of Older US Men and Women

BACKGROUND AND OBJECTIVES

Exposure to socioeconomic disadvantage is associated with early-onset cognitive aging. Biological aging, the progressive loss of system integrity that occurs as we age, is proposed as a modifiable process mediating this health inequality. We examined whether socioeconomic disparities in cognitive aging in mid-to late-life adults is explained by accelerated biological aging similarly across race, ethnicity, and sex/gender.

METHODS

Data were from a prospective cohort study of the US Health and Retirement Study DNA methylation substudy. Socioeconomic status (SES) was measured from years of education and household wealth at baseline. The extent and pace of biological aging were quantified using 3 DNA methylation measures: PhenoAge, GrimAge, and DunedinPoAm. Cognitive aging was measured from repeated longitudinal assessments of immediate and delayed word recall. Latent growth curve modeling estimated participants' level of memory performance and rate of decline over 2-11 follow-up assessments spanning 2-20 years. Multiple-group models were estimated to assess whether the relationship between SES and memory trajectories was mediated by biological aging across racial-ethnic by sex/gender subgroups.

RESULTS

Data from a total of 3,997 adults aged 50-100 years were analyzed. Participants with lower SES had a lower memory performance, had a faster decline, and exhibited accelerated biological aging (SES effect size associations [β] ranged from 0.08 to 0.41). Accelerated biological aging was associated with decreased memory performance and faster memory decline (effect size range 0.03-0.23). SES-biological aging associations were the strongest for White men and women and weakest for Latinx women. The relationship between biological aging measures and memory was weaker for Black participants compared with that for White and Latinx people. In mediation analysis, biological aging accounted for 4%-27% of the SES-memory gradient in White participants. There was little evidence of mediation in Black or Latinx participants.

DISCUSSION

Among a national sample of mid-to late-life adults, DNA methylation measures of biological aging were variably associated with memory trajectories and SES across White, Black, and Latinx mid-to late-life adults. These results challenge the assumption that DNA methylation biomarkers of aging that were developed in primarily White people can equivalently quantify aging processes affecting cognition in Black and Latinx mid-to late-life adults.

Socioeconomic Status, Biological Aging, and Memory in a Diverse National Sample of Older US Men and Women

BACKGROUND AND OBJECTIVES

Exposure to socioeconomic disadvantage is associated with early-onset cognitive aging. Biological aging, the progressive loss of system integrity that occurs as we age, is proposed as a modifiable process mediating this health inequality. We examined whether socioeconomic disparities in cognitive aging in mid-to late-life adults is explained by accelerated biological aging similarly across race, ethnicity, and sex/gender.

METHODS

Data were from a prospective cohort study of the US Health and Retirement Study DNA methylation substudy. Socioeconomic status (SES) was measured from years of education and household wealth at baseline. The extent and pace of biological aging were quantified using 3 DNA methylation measures: PhenoAge, GrimAge, and DunedinPoAm. Cognitive aging was measured from repeated longitudinal assessments of immediate and delayed word recall. Latent growth curve modeling estimated participants' level of memory performance and rate of decline over 2-11 follow-up assessments spanning 2-20 years. Multiple-group models were estimated to assess whether the relationship between SES and memory trajectories was mediated by biological aging across racial-ethnic by sex/gender subgroups.

RESULTS

Data from a total of 3,997 adults aged 50-100 years were analyzed. Participants with lower SES had a lower memory performance, had a faster decline, and exhibited accelerated biological aging (SES effect size associations [β] ranged from 0.08 to 0.41). Accelerated biological aging was associated with decreased memory performance and faster memory decline (effect size range 0.03-0.23). SES-biological aging associations were the strongest for White men and women and weakest for Latinx women. The relationship between biological aging measures and memory was weaker for Black participants compared with that for White and Latinx people. In mediation analysis, biological aging accounted for 4%-27% of the SES-memory gradient in White participants. There was little evidence of mediation in Black or Latinx participants.

DISCUSSION

Among a national sample of mid-to late-life adults, DNA methylation measures of biological aging were variably associated with memory trajectories and SES across White, Black, and Latinx mid-to late-life adults. These results challenge the assumption that DNA methylation biomarkers of aging that were developed in primarily White people can equivalently quantify aging processes affecting cognition in Black and Latinx mid-to late-life adults.

Life-Course Persistent Antisocial Behavior and Accelerated Biological Aging in a Longitudinal Birth Cohort

Prior research shows that individuals who have exhibited antisocial behavior are in poorer health than their same-aged peers. A major driver of poor health is aging itself, yet research has not investigated relationships between offending trajectories and biological aging. We tested the hypothesis that individuals following a life-course persistent (LCP) antisocial trajectory show accelerated aging in midlife. Trajectories of antisocial behavior from age 7 to 26 years were studied in the Dunedin Multidisciplinary Health and Development Study, a population-representative birth cohort (N = 1037). Signs of aging were assessed at age 45 years using previously validated measures including biomarkers, clinical tests, and self-reports. First, we tested whether the association between antisocial behavior trajectories and midlife signs of faster aging represented a decline from initial childhood health. We then tested whether decline was attributable to tobacco smoking, antipsychotic medication use, debilitating illnesses in adulthood, adverse exposures in childhood (maltreatment, socioeconomic disadvantage) and adulthood (incarceration), and to childhood self-control difficulties. Study members with a history of antisocial behavior had a significantly faster pace of biological aging by midlife, and this was most evident among individuals following the LCP trajectory (β, 0.22, 95%CI, 0.14, 0.28, p ≤ 0.001). This amounted to 4.3 extra years of biological aging between ages 25-45 years for Study members following the LCP trajectory compared to low-antisocial trajectory individuals. LCP offenders also experienced more midlife difficulties with hearing (β, -0.14, 95%CI, -0.21, -0.08, p ≤ 0.001), balance (β, -0.13, 95%CI, -0.18, -0.06, p ≤ 0.001), gait speed (β, -0.18, 95%CI, -0.24, -0.10, p ≤ 0.001), and cognitive functioning (β, -0.25, 95%CI, -0.31, -0.18, p ≤ 0.001). Associations represented a decline from childhood health. Associations persisted after controlling individually for tobacco smoking, antipsychotic medication use, midlife illnesses, maltreatment, socioeconomic status, incarceration, and childhood self-control difficulties. However, the cumulative effect of these lifestyle characteristics together explained why LCP offenders have a faster Pace of Aging than their peers. While older adults typically age-out of crime, LCP offenders will likely age-into the healthcare system earlier than their chronologically same-aged peers. Preventing young people from offending is likely to have substantial benefits for health, and people engaging in a LCP trajectory of antisocial behaviors might be the most in need of health promotion programs. We offer prevention and intervention strategies to reduce the financial burden of offenders on healthcare systems and improve their wellbeing.

Gestational diabetes mellitus, epigenetic age and offspring metabolism

AIMS

No reports examine the relationship between in-utero exposure to gestational diabetes mellitus (GDM), offspring epigenetic age acceleration (EAA), and offspring insulin sensitivity.

METHODS

Using data from a cohort study, we examined associations between GDM in-utero exposure and offspring EAA at approximately 10 years of age, using separate regression models adjusting for offspring chronological age and sex. We also examined associations between EAA with updated homeostasis model assessment of insulin sensitivity and secretion (HOMA2-S and HOMA2-β) measured at approximately 10 and 16 years of age, using mixed linear regression models accounting for repeated measures after adjustment for offspring chronological age and sex.

RESULTS

Compared to unexposed offspring (n = 91), offspring exposed to GDM (n = 88) had greater EAA or older extrinsic age compared to chronological age (β-coefficient 2.00, 95% confidence interval [0.71, 3.28], p = 0.0025), but not greater intrinsic EAA (β-coefficient -0.07, 95% CI [-0.71, 0.57], p = 0.93). Extrinsic EAA was associated with lower insulin sensitivity (β-coefficient -0.018, 95% CI [-0.035, -0.002], p = 0.03) and greater insulin secretion (β-coefficient 0.018, 95% CI [0.006, 0.03], p = 0.003), and these associations persisted after further adjustment for measures of maternal and child adiposity. No associations were observed between intrinsic EAA and insulin sensitivity and secretion, before or after adjustment for measures of maternal and child adiposity.

CONCLUSIONS

In this study, children exposed to GDM experience greater extrinsic EAA, which is associated with lower insulin sensitivity and greater insulin secretion. Further studies are needed to determine the directionality of these associations.

Do Loneliness and Per Capita Income Combine to Increase the Pace of Biological Aging for Black Adults across Late Middle Age?

In a sample of 685 late middle-aged Black adults (M age at 2019 = 57.17 years), we examined the effects of loneliness and per capita income on accelerated aging using a newly developed DNA-methylation based index: the DunedinPACE. First, using linear, mixed effects regression in a growth curve framework, we found that change in DunedinPACE was dependent on age, with a linear model best fitting the data (b = 0.004, p < 0.001), indicating that average pace of change increased among older participants. A quadratic effect was also tested, but was non-significant. Beyond the effect of age, both change in loneliness (b = 0.009, p < 0.05) and change in per capita income (b = -0.016, p < 0.001) were significantly associated with change in DunedinPACE across an 11-year period, accounting for significant between person variability observed in the unconditional model. Including non-self-report indices of smoking and alcohol use did not reduce the association of loneliness or per capita income with DunedinPACE. However, change in smoking was strongly associated with change in DunedinPACE such that those reducing their smoking aged less rapidly than those continuing to smoke. In addition, both loneliness and per capita income were associated with DunedinPACE after controlling for variation in cell-types.

Incarceration exposure and epigenetic aging in neighborhood context

OBJECTIVE

Research has implicated incarceration exposure as a social determinant of health, with recent work suggesting incarceration may trigger a stress response that accelerates physiological deterioration. The objective of the current study is to assess whether neighborhood stressors intensify the health consequences of incarceration exposure.

METHODS

We test whether two neighborhood context measures - socioeconomic disadvantage and perceived crime - moderate the association between incarceration exposure and a measure of accelerated epigenetic aging based on the GrimAge index. Our sample included 408 African American young adults from the Family and Community Health study.

RESULTS

Results from regression analyses with inverse probability of treatment weights suggest that incarceration exposure and neighborhood disadvantage are independently associated with accelerated biological aging. The results also show that the impact of incarceration exposure on accelerated aging is amplified for individuals in neighborhoods with higher levels of perceived crime.

CONCLUSIONS

These findings indicate that the neighborhood contexts where formerly incarcerated individuals return have a substantial impact on their pace of biological aging. Policies aimed at reducing ambient stressors after release may promote healthy aging among formerly incarcerated African American adults.

BMI is positively associated with accelerated epigenetic aging in twin pairs discordant for body mass index

BACKGROUND

Obesity is a heritable complex phenotype that can increase the risk of age-related outcomes. Biological age can be estimated from DNA methylation (DNAm) using various "epigenetic clocks." Previous work suggests individuals with elevated weight also display accelerated aging, but results vary by epigenetic clock and population. Here, we utilize the new epigenetic clock GrimAge, which closely correlates with mortality.

OBJECTIVES

We aimed to assess the cross-sectional association of body mass index (BMI) with age acceleration in twins to limit confounding by genetics and shared environment.

METHODS AND RESULTS

Participants were from the Finnish Twin Cohort (FTC; n = 1424), including monozygotic (MZ) and dizygotic (DZ) twin pairs, and DNAm was measured using the Illumina 450K array. Multivariate linear mixed effects models including MZ and DZ twins showed an accelerated epigenetic age of 1.02 months (p-value = 6.1 × 10^-12 ) per one-unit BMI increase. Additionally, heavier twins in a BMI-discordant MZ twin pair (ΔBMI >3 kg/m² ) had an epigenetic age 5.2 months older than their lighter cotwin (p-value = 0.0074). We also found a positive association between log (homeostatic model assessment of insulin resistance) and age acceleration, confirmed by a meta-analysis of the FTC and two other Finnish cohorts (overall effect = 0.45 years, p-value = 4.1 × 10^-25 ) from adjusted models.

CONCLUSION

We identified significant associations of BMI and insulin resistance with age acceleration based on GrimAge, which were not due to genetic effects on BMI and aging. Overall, these results support a role of BMI in aging, potentially in part due to the effects of insulin resistance.