DNA methylation-based measures of biological age: meta-analysis predicting time to death

Chemotherapy-induced acceleration of DNA methylation-based biological age in breast cancer

Breast cancer is the most common cancer diagnosed in women and is often treated with chemotherapy. Although previous studies have demonstrated increasing biological age in patients who receive chemotherapy, evaluation of this association with DNA methylation-based markers of biological ageing may provide novel insight into the role of chemotherapy on the ageing process. We therefore sought to investigate the association between chemotherapy and markers of biological ageing as estimated from DNA methylation in women with breast cancer. DNA methylation profiling was performed on peripheral blood collected from 18 patients before and after the first cycle of chemotherapy using the Infinium HumanMethylation450 BeadChip. Six markers of biological age acceleration were estimated from DNA methylation levels. Multiple linear regression analyses were performed to evaluate the association between each metric of biological age acceleration and chemotherapy. After adjusting for chronological age and race, intrinsic epigenetic age acceleration (p = 0.041), extrinsic epigenetic age acceleration (p = 0.050), PhenoAge acceleration (p = 0.001), GrimAge acceleration (p < 0.001), and DunedinPACE (p = 0.006) were significantly higher and telomere length (p = 0.027) was significantly lower following the first cycle of chemotherapy compared to before treatment initiation. These results demonstrate greater biological ageing as estimated from DNA methylation following chemotherapy in women with breast cancer. Our findings illustrate that cytotoxic therapies may modulate the ageing process among breast cancer patients and may also have implications for age-related health conditions in cancer survivors.

Association of accelerated biological aging with brain volumes: A cross-sectional study

BACKGROUND

Multiple epidemiological studies have observed the connection between aging and brain volumes. The concept of accelerated biological aging (BA) is more powerful for observing the degree of aging of an individual than chronologic age (CA). The objective of this study is to explore the relationship between BA and brain volumes.

METHODS

BA was measured from clinical traits using two blood-chemistry algorithms, the Klemera-Doubal method (KDM) and the PhenoAge. The two age acceleration biomarkers were calculated by the residuals from regressing CA, termed "KDM-acceleration" and "PhenoAge-acceleration". Brain volumes were from brain magnetic resonance imaging (MRI) data. After adjustment for confounding factors, general linear regression models were used to examine associations between KDM-acceleration and PhenoAge-acceleration and brain volumes, respectively. Additionally, we stratified participants by sex, age, and the four quartiles of the Townsend Deprivation Index (TDI) for extra subgroup analysis.

RESULTS

14,725 participants with available information were enrolled. After full adjustment, we observed negative associations between KDM-acceleration and brain volumes, such as gray matter (β = -0.029), white matter (β = -0.021), gray and white matter (β = -0.026), and hippocampus (β = -0.011 for left and β = -0.014 for right). There were also negative associations between PhenoAge-acceleration and brain volumes, such as white matter (β = -0.008), gray and white matter (β = -0.010), thalamus (β = -0.012 for left and β = -0.012 for right). In the subgroup analysis stratified by sex, age, and the four quartiles of TDI, the association between KDM-acceleration and PhenoAge-acceleration and brain volumes still existed. In subgroup analyses, the variation in associations suggests that socioeconomic and biological factors may differentially influence brain aging.

CONCLUSIONS

Our research indicated that more advanced BA was associated with less brain tissue.

Non-pharmaceutical interventions and epigenetic aging in adults: Protocol for a scoping review

INTRODUCTION

Aging is the strongest risk factor for most chronic diseases. The rising burden of an aging population and non-communicable diseases (NCDs), contributes to escalating costs for society. Several non-pharmaceutical interventions can lower the risk of NCDs, including common mental disorders (CMDs), and may slow down biological aging, as evidenced by outcome markers such as epigenetic clocks. However, a comprehensive overview of whether and which non-pharmaceutical interventions may impact human epigenetic aging is missing. Synthesizing evidence of interventions on epigenetic aging that can be adopted by a wider population is key to guide healthy aging initiatives and to reduce the burden of NCDs and CMDs. This scoping review will identify and assess non-pharmaceutical interventions aimed to slow down epigenetic aging, including their intervention components, and the mode used for intervention delivery.

METHODS AND ANALYSIS

This protocol will include single- and multicomponent intervention studies that target individuals ≥ 18 years of age and use epigenetic clocks as primary or secondary outcomes. Five electronic databases will be searched for studies between July 2011 until December 2023. The final search will include the search terms adults, non-pharmaceutical interventions, epigenetic aging and their respective synonyms. We will include randomized controlled trials, non-randomized controlled studies, cohort studies, and case-control studies. Additionally, the reference list of other reviews will be screened for relevant articles. Study selection is carried out based on the defined eligibility criteria by two authors. Quality and risk of bias for the included studies will be assessed using the Critical Appraisal Skills Programme (CASP) checklist. Data extraction will include generic key information such as the research question and results, the intervention components, and specific epigenetic outcome measures used. Further data regarding the delivery mode of the treatment protocol will be collected.

ETHICS AND DISSEMINATION

This scoping review will summarize the characteristics of non-pharmaceutical intervention studies on epigenetic aging. This review will be the first step to formally identify key intervention components and delivery modes to guide future research on healthy aging interventions. The results will be disseminated through a peer-reviewed publication and presented at relevant conferences. This review will synthesize information from available publications and does not require further ethical approval.

REGISTRATION DETAILS

Open Science Framework https://doi.org/10.17605/OSF.IO/FEHNB.

Dissecting the impact of differentiation stage, replicative history, and cell type composition on epigenetic clocks

Epigenetic clocks, built on DNA methylation patterns of bulk tissues, are powerful age predictors, but their biological basis remains incompletely understood. Here, we conducted a comparative analysis of epigenetic age in murine muscle, epithelial, and blood cell types across lifespan. Strikingly, our results show that cellular subpopulations within these tissues, including adult stem and progenitor cells as well as their differentiated progeny, exhibit different epigenetic ages. Accordingly, we experimentally demonstrate that clocks can be skewed by age-associated changes in tissue composition. Mechanistically, we provide evidence that the observed variation in epigenetic age among adult stem cells correlates with their proliferative state, and, fittingly, forced proliferation of stem cells leads to increases in epigenetic age. Collectively, our analyses elucidate the impact of cell type composition, differentiation state, and replicative potential on epigenetic age, which has implications for the interpretation of existing clocks and should inform the development of more sensitive clocks.

Epigenetics, Microbiome and Personalized Medicine: Focus on Kidney Disease

Personalized medicine, which involves modifying treatment strategies/drug dosages based on massive laboratory/imaging data, faces large statistical and study design problems. The authors believe that the use of continuous multidimensional data, such as those regarding gut microbiota, or binary multidimensional systems properly transformed into a continuous variable, such as the epigenetic clock, offer an advantageous scenario for the design of trials of personalized medicine. We will discuss examples focusing on kidney diseases, specifically on IgA nephropathy. While gut dysbiosis can provide a treatment strategy to restore the standard gut microbiota using probiotics, transforming epigenetic omics data into epigenetic clocks offers a promising tool for personalized acute and chronic kidney disease care. Epigenetic clocks involve a complex transformation of DNA methylome data into estimated biological age. These clocks can identify people at high risk of developing kidney problems even before symptoms appear. Some of the effects of both the epigenetic clock and microbiota on kidney diseases seem to be mediated by endothelial dysfunction. These "big data" (epigenetic clocks and microbiota) can help tailor treatment plans by pinpointing patients likely to experience rapid declines or those who might not need overly aggressive therapies.

Development of an epigenetic clock resistant to changes in immune cell composition

Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG methylation values to predict chronological or biological age. Increases in predicted epigenetic age relative to chronological age (epigenetic age acceleration) are connected to aging-associated pathologies, and changes in epigenetic age are linked to canonical aging hallmarks. However, epigenetic clocks rely on training data from bulk tissues whose cellular composition changes with age. Here, we found that human naive CD8+ T cells, which decrease in frequency during aging, exhibit an epigenetic age 15-20 years younger than effector memory CD8+ T cells from the same individual. Importantly, homogenous naive T cells isolated from individuals of different ages show a progressive increase in epigenetic age, indicating that current epigenetic clocks measure two independent variables, aging and immune cell composition. To isolate the age-associated cell intrinsic changes, we created an epigenetic clock, the IntrinClock, that did not change among 10 immune cell types tested. IntrinClock shows a robust predicted epigenetic age increase in a model of replicative senescence in vitro and age reversal during OSKM-mediated reprogramming.

GWAS of biological aging to find longevity genes in schizophrenia

Schizophrenia (SCZ) is a severe psychotic disorder associated with premature mortality and aging. Moreover, the symptoms and progression of psychiatric disorders in general are associated with decreased lifespan, biological aging, and poorer medical outcomes. In this study, we investigated the relationship between several epigenetic clocks and scanned the entire genome for association in a cohort of SCZ individuals (n = 107). Biological age was computed from blood DNA methylation (DNAm) and tested for association against  common  variants across the genome using general linear models. Genes affecting epigenetic age acceleration in our cohort were found mainly when using the telomeric length clock rather than the other biological clocks. These findings pair with existing evidence that there are some genes associated with longevity and suggest further investigations of  putative biological mechanisms for morbidity and premature mortality, not only in patients with SCZ but also in the general population.

DNA methyltransferase 1 (DNMT1) promotes cyst growth and epigenetic age acceleration in autosomal dominant polycystic kidney disease

Alteration of DNA methylation leads to diverse diseases, and the dynamic changes of DNA methylation (DNAm) on sets of CpG dinucleotides in mammalian genomes are termed "DNAm age" and "epigenetic clocks" that can predict chronological age. However, whether and how dysregulation of DNA methylation promotes cyst progression and epigenetic age acceleration in autosomal dominant polycystic kidney disease (ADPKD) remains elusive. Here, we show that DNA methyltransferase 1 (DNMT1) is upregulated in cystic kidney epithelial cells and tissues and that knockout of Dnmt1 and targeting DNMT1 with hydralazine, a safe demethylating agent, delays cyst growth in Pkd1 mutant kidneys and extends life span of Pkd1 conditional knockout mice. With methyl-CpG binding domain (MBD) protein-enriched genome sequencing (MBD-seq), DNMT1 chromatin immunoprecipitation (ChIP)-sequencing and RNA-sequencing analysis, we identified two novel DNMT1 targets, PTPRM and PTPN22 (members of the protein tyrosine phosphatase family). PTPRM and PTPN22 function as mediators of DNMT1 and the phosphorylation and activation of PKD-associated signaling pathways, including ERK, mTOR and STAT3. With whole-genome bisulfide sequencing in kidneys of patients with ADPKD versus normal individuals, we found that the methylation of epigenetic clock-associated genes was dysregulated, supporting that epigenetic age is accelerated in the kidneys of patients with ADPKD. Furthermore, five epigenetic clock-associated genes, including Hsd17b14, Itpkb, Mbnl1, Rassf5 and Plk2, were identified. Thus, the diverse biological roles of these five genes suggest that their methylation status may not only predict epigenetic age acceleration but also contribute to disease progression in ADPKD.

Maternal smoking during pregnancy could accelerate aging in the adulthood: evidence from a perspective study in UK Biobank

BACKGROUND

Maternal smoking during pregnancy (MSDP) is significantly linked to the short- or long-term health of offspring. However, little research has examined whether MSDP affect the aging rate of offspring.

METHODS

This study used questionnaires to determine out whether the participants' mothers smoked when they were pregnant. For evaluating aging rate, we used the following several outcome measures: telomere length, frailty index, cognitive function, homeostatic dysregulation score, KDM-age, age-related hospitalization rate, premature death, and life expectancy.

RESULT

After adjusting for covariates, we found that the offspring of the MSDP group had significantly shorter telomere length in adulthood by 0.8 % (β = -0.008,95%CI:-0.009 to -0.006) compared with non-MSDP group. Compared to the non-MSDP group, participants in MSDP group showed higher levels of homeostatic dysregulation (β = 0.015,95%CI: 0.007-0.024) and were frailer (β = 0.008,95%CI:0.007-0.009). The KDM age increased by 0.100 due to MSDP (β = 0.100,95 % CI:0.018-0.181), and the age acceleration of KDM algorithm also increases significantly (β = 0.101, 95%CI:0.020-0.183). Additionally, we found that the risk of aging-related hospitalizations was significantly higher than the non-MSDP group by 10.4 %(HR = 1.104,95%CI:1.066-1.144). Moreover, MSDP group had a 12.2 % increased risk of all-cause premature mortality (HR = 1.122,95%CI:1.064-1.182) and a significant risk of lung cancer-specific premature mortality increased by 55.4 %(HR = 1.554,95%CI:1.346-1.793). In addition, participants in the MSDP group had significantly decreased cognitive function and shorter life expectancies than those in non-MSDP group.

CONCLUSION

Our findings indicated a significant association between MSPD and accelerated aging, elevated hospitalization rates, increased premature mortality rates, and reduced life expectancies in offspring.

Biological aging of different blood cell types

Biological age (BA) captures detrimental age-related changes. The best-known and most-used BA indicators include DNA methylation-based epigenetic clocks and telomere length (TL). The most common biological sample material for epidemiological aging studies, whole blood, is composed of different cell types. We aimed to compare differences in BAs between blood cell types and assessed the BA indicators' cell type-specific associations with chronological age (CA). An analysis of DNA methylation-based BA indicators, including TL, methylation level at cg16867657 in ELOVL2, as well as the Hannum, Horvath, DNAmPhenoAge, and DunedinPACE epigenetic clocks, was performed on 428 biological samples of 12 blood cell types. BA values were different in the majority of the pairwise comparisons between cell types, as well as in comparison to whole blood (p < 0.05). DNAmPhenoAge showed the largest cell type differences, up to 44.5 years and DNA methylation-based TL showed the lowest differences. T cells generally had the "youngest" BA values, with differences across subsets, whereas monocytes had the "oldest" values. All BA indicators, except DunedinPACE, strongly correlated with CA within a cell type. Some differences such as DNAmPhenoAge-difference between naïve CD4 + T cells and monocytes were constant regardless of the blood donor's CA (range 20-80 years), while for DunedinPACE they were not. In conclusion, DNA methylation-based indicators of BA exhibit cell type-specific characteristics. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and underscore the importance of considering cell composition when utilizing them as indicators for the success of aging interventions.

Decoding Clonal Hematopoiesis: Emerging Themes and Novel Mechanistic Insights

Clonal hematopoiesis (CH), the relative expansion of mutant clones, is derived from hematopoietic stem cells (HSCs) with acquired somatic or cytogenetic alterations that improve cellular fitness. Individuals with CH have a higher risk for hematological and non-hematological diseases, such as cardiovascular disease, and have an overall higher mortality rate. Originally thought to be restricted to a small fraction of elderly people, recent advances in single-cell sequencing and bioinformatics have revealed that CH with multiple expanded mutant clones is universal in the elderly population. Just a few years ago, phylogenetic reconstruction across the human lifespan and novel sensitive sequencing techniques showed that CH can start earlier in life, decades before it was thought possible. These studies also suggest that environmental factors acting through aberrant inflammation might be a common theme promoting clonal expansion and disease progression. However, numerous aspects of this phenomenon remain to be elucidated and the precise mechanisms, context-specific drivers, and pathways of clonal expansion remain to be established. Here, we review our current understanding of the cellular mechanisms driving CH and specifically focus on how pro-inflammatory factors affect normal and mutant HSC fates to promote clonal selection.

DNA methylation clocks for estimating biological age in Chinese cohorts

Epigenetic clocks are accurate predictors of human chronological age based on the analysis of DNA methylation (DNAm) at specific CpG sites. However, a systematic comparison between DNA methylation data and other omics datasets has not yet been performed. Moreover, available DNAm age predictors are based on datasets with limited ethnic representation. To address these knowledge gaps, we generated and analyzed DNA methylation datasets from two independent Chinese cohorts, revealing age-related DNAm changes. Additionally, a DNA methylation aging clock (iCAS-DNAmAge) and a group of DNAm-based multi-modal clocks for Chinese individuals were developed, with most of them demonstrating strong predictive capabilities for chronological age. The clocks were further employed to predict factors influencing aging rates. The DNAm aging clock, derived from multi-modal aging features (compositeAge-DNAmAge), exhibited a close association with multi-omics changes, lifestyles, and disease status, underscoring its robust potential for precise biological age assessment. Our findings offer novel insights into the regulatory mechanism of age-related DNAm changes and extend the application of the DNAm clock for measuring biological age and aging pace, providing the basis for evaluating aging intervention strategies.

MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease

Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledgebase containing manually curated summary statistics from 98 published tables in 38 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels-at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD. Database URL: https://miami-ad.org/.

Poverty Status at Birth Predicts Epigenetic Changes at Age 15

Epigenetic studies have provided new opportunities to better understand the biological effects of poverty and racial/ethnic minority status. However, little is known about sex differences in these processes.

Methods

We used 15 years of follow up of 854 racially and ethnically diverse birth cohort who were followed from birth to age 15. Structural equation modeling (SEM) was used to examine the effects of race/ethnicity, maternal education, and family structure on poverty at birth, as well as the effects of poverty at birth on epigenetic changes at age 15. We also explored variations by sex.

Results

Our findings indicate that Black and Latino families had lower maternal education and married family structure which in turn predicted poverty at birth. Poverty at birth then was predictive of epigenetic changes 15 years later when the index child was 15. This suggested that poverty at birth partially mediates the effects of race/ethnicity, maternal education, and family structure on epigenetic changes of youth at age 15. There was an effect of poverty status at birth on DNA methylation of male but not female youth at age 15. Thus, poverty at birth may have a more salient effect on long term epigenetic changes of male than female youth.

Conclusions

Further studies are needed to understand the mechanisms underlying the observed sex differences in the effects of poverty as a mechanism that connects race/ethnicity, maternal education, and family structure to epigenetic changes later in life.

Map of epigenetic age acceleration: A worldwide analysis

We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.

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.

Race, Poverty Status at Birth, and DNA Methylation of Youth at Age 15

Epigenetic studies, which can reflect biological aging, have shown that measuring DNA methylation (DNAm) levels provides new insights into the biological effects of social environment and socioeconomic position (SEP). This study explores how race, family structure, and SEP (income to poverty ratio) at birth influence youth epigenetic aging at age 15. Data were obtained from the Future of Families and Child Wellbeing Study (FFCWS) cohort, with GrimAge used as a measure of DNAm levels and epigenetic aging. Our analysis included 854 racially and ethnically diverse participants followed from birth to age 15. Structural equation modeling (SEM) examined the relationships among race, SEP at birth, and epigenetic aging at age 15, controlling for sex, ethnicity, and family structure at birth. Findings indicate that race was associated with lower SEP at birth and faster epigenetic aging. Specifically, income to poverty ratio at birth partially mediated the effects of race on accelerated aging by age 15. The effect of income to poverty ratio at birth on DNAm was observed in male but not female youth at age 15. Thus, SEP partially mediated the effect of race on epigenetic aging in male but not female youth. These results suggest that income to poverty ratio at birth partially mediates the effects of race on biological aging into adolescence. These findings highlight the long-term biological impact of early-life poverty in explaining racial disparities in epigenetic aging and underscore the importance of addressing economic inequalities to mitigate these disparities. Policymakers should focus on poverty prevention in Black communities to prevent accelerated biological aging and associated health risks later in life. Interventions aimed at eliminating poverty and addressing racial inequities could have significant long-term benefits for public health. Future research should explore additional factors contributing to epigenetic aging and investigate potential interventions to slow down the aging process. Further studies are needed to understand the mechanisms underlying these associations and to identify effective strategies for mitigating the impact of SEP and racial disparities on biological aging.

Associations of Epigenetic Age Estimators With Cognitive Function Trajectories in the Women's Health Initiative Memory Study

BACKGROUND AND OBJECTIVES

Epigenetic age estimators indicating faster/slower biological aging vs chronological age independently associate with several age-related outcomes; however, longitudinal associations with cognitive function are understudied. We examined associations of epigenetic age estimators with cognitive function measured annually.

METHODS

This longitudinal study consisted of older women enrolled in the Women's Health Initiative Memory Study with DNA methylation (DNAm) collected at baseline (1995-1998) from 3 ancillary studies and were followed up to 13 years. Global cognitive function was measured annually by Modified Mini-Mental State Examination (3MS; baseline-2007) and by modified Telephone Interview for Cognitive Status (TICS-m, 2008-2021). We calculated 5 epigenetic age estimators: extrinsic AgeAccel, intrinsic AgeAccel, AgeAccelPheno, AgeAccelGrim2, Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE), and AgeAccelGrim2 components (DNA-based plasma protein surrogates). We estimated longitudinal epigenetic age estimator-cognitive function associations using linear mixed-effects models containing age, education, race or ethnicity, and subsequently alcohol, smoking, body mass index, and comorbidities. We examined effect modification by APOE ε4 carriage.

RESULTS

A total of 795 participants were enrolled. The mean baseline age was 70.8 ± 4 years (10.7% Black, 3.9% Hispanic or Latina, 85.4% White), A 1-SD (0.12) increment in DunedinPACE associated with faster annual declines in TICS-m scores in minimally adjusted (β = -0.118, 95% CI -0.202 to -0.034; p = 0.0006) and fully adjusted (β = -0.123, 95% CI -0.211 to -0.036; p = 0.006) models. AgeAccelPheno associated with faster annual declines in TICS-m with minimal adjustment (β = -0.091, 95% CI -0.176 to -0.006; p = 0.035) but not with full adjustment. No other epigenetic age estimators associated with changes in 3MS or TICS-m. Higher values of DNAm-based surrogates of growth differentiation factor 15, beta-2 microglobulin, Cystatin C, tissue inhibitor metalloproteinase 1, and adrenomedullin associated with faster annual declines in 3MS and TICS-m. Higher DNAm log A1c associated with faster annual declines in TICS-m only. DunedinPACE associated with faster annual declines in 3MS among APOE ε4 carriers but not among noncarriers (p-interaction = 0.020).

DISCUSSION

Higher DunedinPACE associated with faster declines in TICS-m and 3MS scores among APOE ε4 carriers. DunedinPACE may help identify older women at risk of future cognitive decline. Limitations include the ancillary studies that collected epigenetic data not designed to study epigenetics and cognitive function. We examined epigenetic age estimators with global cognitive function and not specific cognitive domains. Findings may not generalize to men and more diverse populations.

Chemokine CXCL9, a marker of inflammaging, is associated with changes of muscle strength and mortality in older men

Our study examined associations of the CXC motif chemokine ligand 9 (CXCL9), a pro-inflammatory protein implicated in age-related inflammation, with musculoskeletal function in elderly men. We found in certain outcomes both cross-sectional and longitudinal significant associations of CXCL9 with poorer musculoskeletal function and increased mortality in older men. This requires further investigation.

PURPOSE

We aim to determine the relationship of (CXCL9), a pro-inflammatory protein implicated in age-related inflammation, with both cross-sectional and longitudinal musculoskeletal outcomes and mortality in older men.

METHODS

A random sample from the Osteoporotic Fractures in Men (MrOS) Study cohort (N = 300) was chosen for study subjects that had attended the third and fourth clinic visits, and data was available for major musculoskeletal outcomes (6 m walking speed, chair stands), hip bone mineral density (BMD), major osteoporotic fracture, mortality, and serum inflammatory markers. Serum levels of CXCL9 were measured by ELISA, and the associations with musculoskeletal outcomes were assessed by linear regression and fractures and mortality with Cox proportional hazards models.

RESULTS

The mean CXCL9 level of study participants (79.1 ± 5.3 years) was 196.9 ± 135.2 pg/ml. There were significant differences for 6 m walking speed, chair stands, physical activity scores, and history of falls in the past year across the quartiles of CXCL9. However, higher CXCL9 was only significantly associated with changes in chair stands (β =  - 1.098, p < 0.001) even after adjustment for multiple covariates. No significant associations were observed between CXCL9 and major osteoporotic fracture or hip BMD changes. The risk of mortality increased with increasing CXCL9 (hazard ratio quartile (Q)4 vs Q1 1.98, 95% confidence interval 1.25-3.14; p for trend < 0.001).

CONCLUSIONS

Greater serum levels of CXCL9 were significantly associated with a decline in chair stands and increased mortality. Additional studies with a larger sample size are needed to confirm our findings.

DNA methylation-based telomere length is associated with HIV infection, physical frailty, cancer, and all-cause mortality

Telomere length (TL) is an important indicator of cellular aging. Shorter TL is associated with several age-related diseases including coronary heart disease, heart failure, diabetes, osteoporosis, and cancer. Recently, a DNA methylation-based TL (DNAmTL) estimator has been developed as an alternative method for directly measuring TL. In this study, we examined the association of DNAmTL with cancer prevalence and mortality risk among people with and without HIV in the Veterans Aging Cohort Study Biomarker Cohort (VACS, N = 1917) and Women's Interagency HIV Study Cohort (WIHS, N = 481). We profiled DNAm in whole blood (VACS) or in peripheral blood mononuclear cells (WIHS) using an array-based method. Cancer prevalence was estimated from electronic medical records and cancer registry data. The VACS Index was used as a measure of physiologic frailty. Models were adjusted for self-reported race and ethnicity, batch, smoking status, alcohol consumption, and five cell types (CD4, CD8, NK, B cell, and monocyte). We found that people with HIV had shorter average DNAmTL than those without HIV infection [beta = -0.25, 95% confidence interval (-0.32, -0.18), p = 1.48E-12]. Greater value of VACS Index [beta = -0.002 (-0.003, -0.001), p = 2.82E-05] and higher cancer prevalence [beta = -0.07 (-0.10, -0.03), p = 1.37E-04 without adjusting age] were associated with shortened DNAmTL. In addition, one kilobase decrease in DNAmTL was associated with a 40% increase in mortality risk [hazard ratio: 0.60 (0.44, 0.82), p = 1.42E-03]. In summary, HIV infection, physiologic frailty, and cancer are associated with shortening DNAmTL, contributing to an increased risk of all-cause mortality.

Cerebrospinal fluid proteomic profile of frailty: Results from the PROLIPHYC cohort

Frailty is a clinical state reflecting a decrease in physiological reserve capacities, known to affect numerous biological pathways and is associated with health issues, including neurodegenerative diseases. However, how global protein expression is affected in the central nervous system in frail subject remains underexplored. In this post hoc cross-sectional biomarker analysis, we included 90 adults (52-85 years) suspected of normal pressure hydrocephalus (NPH) and presenting with markers of neurodegenerative diseases. We investigated the human proteomic profile of cerebrospinal fluid associated with frailty defined by an established cumulated frailty index (FI, average = 0.32), not enriched for neurology clinical features. Using a label-free quantitative proteomic approach, we identified and quantified 999 proteins of which 13 were positively associated with frailty. Pathway analysis with the top positively frailty-associated proteins revealed enrichment for proteins related to inflammation and immune response. Among the 60 proteins negatively associated with frailty, functional pathways enriched included neurogenesis, synaptogenesis and neuronal guidance. We constructed a frailty prediction model using ridge regression with 932 standardized proteins. Our results showed that the "proteomic model" could become an equivalent predictor of FI in order to study chronological age. This study represents the first comprehensive exploration of the proteomic profile of frailty within cerebrospinal fluid. It sheds light on the physiopathology of frailty, particularly highlighting processes of neuroinflammation and inhibition of neurogenesis. Our findings unveil a range of biological mechanisms that are dysregulated in frailty, in NPH subjects at risk of neurodegenerative impairment, offering new perspectives on frailty phenotyping and prediction.

Epigenetic age oscillates during the day

Since their introduction, epigenetic clocks have been extensively used in aging, human disease, and rejuvenation studies. In this article, we report an intriguing pattern: epigenetic age predictions display a 24-h periodicity. We tested a circadian blood sample collection using 17 epigenetic clocks addressing different aspects of aging. Thirteen clocks exhibited significant oscillations with the youngest and oldest age estimates around midnight and noon, respectively. In addition, daily oscillations were consistent with the changes of epigenetic age across different times of day observed in an independant populational dataset. While these oscillations can in part be attributed to variations in white blood cell type composition, cell count correction methods might not fully resolve the issue. Furthermore, some epigenetic clocks exhibited 24-h periodicity even in the purified fraction of neutrophils pointing at plausible contributions of intracellular epigenomic oscillations. Evidence for circadian variation in epigenetic clocks emphasizes the importance of the time-of-day for obtaining accurate estimates of epigenetic age.

Biomarkers of Cellular Senescence and Aging: Current State-of-the-Art, Challenges and Future Perspectives

Population aging has increased the global prevalence of aging-related diseases, including cancer, sarcopenia, neurological disease, arthritis, and heart disease. Understanding aging, a fundamental biological process, has led to breakthroughs in several fields. Cellular senescence, evinced by flattened cell bodies, vacuole formation, and cytoplasmic granules, ubiquitously plays crucial roles in tissue remodeling, embryogenesis, and wound repair as well as in cancer therapy and aging. The lack of universal biomarkers for detecting and quantifying senescent cells, in vitro and in vivo, constitutes a major limitation. The applications and limitations of major senescence biomarkers, including senescence-associated β-galactosidase staining, telomere shortening, cell-cycle arrest, DNA methylation, and senescence-associated secreted phenotypes are discussed. Furthermore, explore senotherapeutic approaches for aging-associated diseases and cancer. In addition to the conventional biomarkers, this review highlighted the in vitro, in vivo, and disease models used for aging studies. Further, technologies from the current decade including multi-omics and computational methods used in the fields of senescence and aging are also discussed in this review. Understanding aging-associated biological processes by using cellular senescence biomarkers can enable therapeutic innovation and interventions to improve the quality of life of older adults.

Bidirectional relationship between epigenetic age and brain health events

Chronological age offers an imperfect estimate of the molecular changes that occur with aging. Epigenetic age, which is derived from DNA methylation data, provides a more nuanced representation of aging-related biological processes. This study examines the bidirectional relationship between epigenetic age and the occurrence of brain health events (stroke, dementia, and late-life depression). Using data from the Health and Retirement Study, we analyzed blood samples from over 4,000 participants to determine how epigenetic age relates to past and future brain health events. Study participants with a prior brain health event prior to blood collection were 4% epigenetically older (beta 0.04, SE 0.01), suggesting that these conditions are associated with faster aging than that captured by chronological age. Furthermore, a one standard deviation increase in epigenetic age was associated with 70% higher odds of experiencing a brain health event in the next four years after blood collection (OR 1.70, 95%CI 1.16-2.50), indicating that epigenetic age is not just a consequence but also a predictor of poor brain health. Both results were replicated through Mendelian Randomization analyses, supporting their causal nature. Our findings support the utilization of epigenetic age as a useful biomarker to evaluate the role of interventions aimed at preventing and promoting recovery after a brain health event.

Maximizing Insights from Longitudinal Epigenetic Age Data: Simulations, Applications, and Practical Guidance

Background

Epigenetic Age (EA) is an age estimate, developed using DNA methylation (DNAm) states of selected CpG sites across the genome. Although EA and chronological age are highly correlated, EA may not increase uniformly with time. Departures, known as epigenetic age acceleration (EAA), are common and have been linked to various traits and future disease risk. Limited by available data, most studies investigating these relationships have been cross-sectional - using a single EA measurement. However, the recent growth in longitudinal DNAm studies has led to analyses of associations with EA over time. These studies differ in (i) their choice of model; (ii) the primary outcome (EA vs. EAA); and (iii) in their use of chronological age or age-independent time variables to account for the temporal dynamic. We evaluated the robustness of each approach using simulations and tested our results in two real-world examples, using biological sex and birthweight as predictors of longitudinal EA.

Results

Our simulations showed most accurate effect sizes in a linear mixed model or generalized estimating equation, using chronological age as the time variable. The use of EA versus EAA as an outcome did not strongly impact estimates. Applying the optimal model in real-world data uncovered an accelerated EA rate in males and an advanced EA that decelerates over time in children with higher birthweight.

Conclusion

Our results can serve as a guide for forthcoming longitudinal EA studies, aiding in methodological decisions that may determine whether an association is accurately estimated, overestimated, or potentially overlooked.

DNA methylation in peripheral blood is associated with renal aging and renal function decline: a national community study

BACKGROUND

Older patients are at risk for acute kidney injury and chronic kidney disease. Age-related increases in DNA methylation at CpG islands have been linked to aging-related diseases like cancer and cardiovascular disease, but the exact causal relationship between methylation in renal aging and other kidney diseases remains unclear. This study aimed to elucidate the methylation status of peripheral blood mononuclear cells (PBMCs) in the Asian population. Using human whole blood DNA methylation analysis from the Taiwan Biobank, we included participants with both whole blood genome-wide methylation data and follow-up data on serum creatinine. We investigated hyper- and hypomethylated genes in comparison of participants with higher and lower estimated glomerular filtration (eGFR) decline rate in overall cohort as well as in comparison of old and young participants in subgroup of participants with higher eGFR decline rate. Common genes and signaling pathways in both comparative analyses were identified.

RESULTS

Among 1587 participants in the analysis, 187 participants had higher eGFR decline rate. According to the comparison of methylation in participants with different eGFR declines and at different ages, respectively, we identified common hypermethylated genes, including DNMT3A and GGACT, as well as hypomethylated genes such as ARL6IP5, CYB5D1, BCL6, RPRD2, ZNF451, and MIAT in both participants with higher eGFR decline and those of older age. We observed associations between the methylation status of signaling pathways and aging as well as renal function decline. These pathways notably included autophagy, p38 mitogen-activated protein kinases, and sirtuins, which were associated with autophagy process and cytokine production.

CONCLUSIONS

Through methylation analysis of PBMCs, we identified genes and signaling pathways which could play crucial roles in the interplay of renal aging and renal function decline. These findings contribute to the development of novel biomarkers for identifying at-risk groups and even for therapeutic agent discovery.

Epigenetic Aging and Musculoskeletal Outcomes in a Cohort of Women Living With HIV

BACKGROUND

The relationship between accelerated epigenetic aging and musculoskeletal outcomes in women with HIV (WWH) has not been studied.

METHODS

We measured DNA methylation age using the Infinium MethylationEPIC BeadChip in a cohort from the Women's Interagency HIV Study (n = 190) with measures of bone mineral density (BMD) and physical function. We estimated 6 biomarkers of epigenetic aging-epigenetic age acceleration (EAA), extrinsic EAA, intrinsic EAA, GrimAge, PhenoAge, and DNA methylation-estimated telomere length-and evaluated associations of epigenetic aging measures with BMD and physical function. We also performed epigenome-wide association studies to examine associations of DNA methylation signatures with BMD and physical function.

RESULTS

This study included 118 WWH (mean age, 49.7 years; 69% Black) and 72 without HIV (mean age, 48.9 years; 69% Black). WWH had higher EAA (mean ± SD, 1.44 ± 5.36 vs -1.88 ± 5.07; P < .001) and lower DNA methylation-estimated telomere length (7.13 ± 0.31 vs 7.34 ± 0.23, P < .001) than women without HIV. There were no significant associations between accelerated epigenetic aging and BMD. Rather, measures of accelerated epigenetic aging were associated with lower physical function.

CONCLUSIONS

Accelerated epigenetic aging was observed in WWH as compared with women without HIV and was associated with lower physical function in both groups.

Associations of childhood, adolescence, and midlife cognitive function with DNA methylation age acceleration in midlife

Prior studies showed increased age acceleration (AgeAccel) is associated with worse cognitive function among old adults. We examine the associations of childhood, adolescence and midlife cognition with AgeAccel based on DNA methylation (DNAm) in midlife. Data are from 359 participants who had cognition measured in childhood and adolescence in the Child Health and Development study, and had cognition, blood based DNAm measured during midlife in the Disparities study. Childhood cognition was measured by Raven's Progressive Matrices and Peabody Picture Vocabulary Test (PPVT). Adolescent cognition was measured only by PPVT. Midlife cognition included Wechsler Test of Adult Reading (WTAR), Verbal Fluency (VF), Digit Symbol (DS). AgeAccel measures including Horvath, Hannum, PhenoAge, GrimAge and DunedinPACE were calculated from DNAm. Linear regressions adjusted for potential confounders were utilized to examine the association between each cognitive measure in relation to each AgeAccel. There are no significant associations between childhood cognition and midlife AgeAccel. A 1-unit increase in adolescent PPVT, which measures crystalized intelligence, is associated with 0.048-year decrease of aging measured by GrimAge and this association is attenuated after adjustment for adult socioeconomic status. Midlife crystalized intelligence measure WTAR is negatively associated with PhenoAge and DunedinPACE, and midlife fluid intelligence measure (DS) is negatively associated with GrimAge, PhenoAge and DunedinPACE. AgeAccel is not associated with VF in midlife. In conclusion, our study showed the potential role of cognitive functions at younger ages in the process of biological aging. We also showed a potential relationship of both crystalized and fluid intelligence with aging acceleration.

Loneliness, epigenetic age acceleration, and chronic health conditions

Having associations with a range of adverse physical health outcomes including mortality, loneliness is increasingly recognized as a pressing public health concern, but the mechanisms studied to date do not yet explain all loneliness-related health risk. We sought to evaluate whether epigenetic influences on DNA methylation could help explain the relationship between loneliness and health. To do so, we first estimated associations between loneliness and epigenetic age acceleration (EAA) in a subsample of participants in the study of midlife in the United States (n = 1,310), before testing whether EAA mediated and/or moderated the association between loneliness and the onset of chronic health conditions in older adulthood (n = 445 completing longitudinal follow-ups). Greater loneliness was weakly associated with greater EAA in the Horvath, DunedinPACE, and GrimAge measures after accounting for demographic (0.08 ≤ β ≤ 0.11) and behavioral (0.06 ≤ β ≤ 0.08) covariates. Loneliness also predicted increases in chronic condition counts and these effects were more pronounced for individuals with higher DunedinPACE EAA values (interaction term β = 0.09, p = .009), suggesting possible synergistic impacts. EAA measures appear to be promising in helping to understand individual variations in the health impacts of loneliness, but the specific mechanisms involved require further research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Eight Weeks of Physical Training Decreases 2 Years of DNA Methylation Age of Sedentary Women

Purpose: The acceleration of epigenetic age is a predictor of mortality and contributes to the increase in chronic diseases. Adherence to a healthy lifestyle is a strategy to reduce epigenetic age. The present study aimed to determine whether eight weeks of combined (aerobic and strength) training (CT) can influence the epigenetic age of women between 50 and 70 years old and the differences in sites and methylated regions. Methods: Eighteen women (AARLow: lower age acceleration residual, n = 10; AARHigh: higher age acceleration residual, n = 8) participated in a combined exercise training program (60 minutes, 3× a week) for eight weeks. DNA was extracted from whole blood using the salting out technique. DNA methylation was performed using the array technique (Illumina's Infinium Methylation BeadChip 850k). We used the DNA Methylation Age Calculator platform to calculate the biological epigenetic age. Two-way ANOVA followed by FISHER LSD posthoc was Applied, adopting p < .05. Results: After eight weeks of CT, there were no changes to the epigenetic age acceleration for the AARLow group (PRE: -2.3 ± 3.2 to POST: -2.3 ± 3.6). However, the AARHigh group significantly decreased the age acceleration (PRE: 3.6 ± 2.6 to POST: 2.2 ± 2.7) (group effect, p = .01; time effect, p = .31; group vs. time effect, p = .005). Conclusion: CT for eight weeks benefits the epigenetic clock of women with the most accelerated age.

Aging as a loss of morphostatic information: A developmental bioelectricity perspective

Maintaining order at the tissue level is crucial throughout the lifespan, as failure can lead to cancer and an accumulation of molecular and cellular disorders. Perhaps, the most consistent and pervasive result of these failures is aging, which is characterized by the progressive loss of function and decline in the ability to maintain anatomical homeostasis and reproduce. This leads to organ malfunction, diseases, and ultimately death. The traditional understanding of aging is that it is caused by the accumulation of molecular and cellular damage. In this article, we propose a complementary view of aging from the perspective of endogenous bioelectricity which has not yet been integrated into aging research. We propose a view of aging as a morphostasis defect, a loss of biophysical prepattern information, encoding anatomical setpoints used for dynamic tissue and organ homeostasis. We hypothesize that this is specifically driven by abrogation of the endogenous bioelectric signaling that normally harnesses individual cell behaviors toward the creation and upkeep of complex multicellular structures in vivo. Herein, we first describe bioelectricity as the physiological software of life, and then identify and discuss the links between bioelectricity and life extension strategies and age-related diseases. We develop a bridge between aging and regeneration via bioelectric signaling that suggests a research program for healthful longevity via morphoceuticals. Finally, we discuss the broader implications of the homologies between development, aging, cancer and regeneration and how morphoceuticals can be developed for aging.

Retirement Makes You Old? Causal Effect of Retirement on Biological Age

Retirement is a critical life event for older people. Health scholars have scrutinized the health effects of retirement, but its consequences on age-related diseases and mortality are unclear. We extend this body of research by integrating measurements of biological age, representing the physiological decline preceding disease onset. Using data from the UK Biobank and a fuzzy regression discontinuity design, we estimated the effects of retirement on two biomarker-based biological age measures. Results showed that retirement significantly increases biological age for those induced to retire by the State Pension eligibility by 0.871-2.503 years, depending on sex and specific biological age measurement. Given the emerging scientific discussion about direct interventions to biological age to achieve additional improvements in population health, the positive effect of retirement on biological age has important implications for an increase in the State Pension eligibility age and its potential consequences on population health, public health care policy, and older people's labor force participation. Overall, this study provides novel empirical evidence contributing to the question of what social factors make people old.

Relationships of depression and antidepressant use with epigenetic age acceleration and all-cause mortality among postmenopausal women

We investigated relations of depressive symptoms, antidepressant use, and epigenetic age acceleration with all-cause mortality risk among postmenopausal women. Data were analyzed from ≤1,900 participants in the Women's Health Initiative study testing four-way decomposition models. After a median 20.4y follow-up, 1,161 deaths occurred. Approximately 11% had elevated depressive symptoms (EDS+), 7% were taking antidepressant medication at baseline (ANTIDEP+), while 16.5% fell into either category (EDS_ANTIDEP+). Baseline ANTIDEP+, longitudinal transition into ANTIDEP+ and accelerated epigenetic aging directly predicted increased mortality risk. GrimAge DNA methylation age acceleration (AgeAccelGrim) partially mediated total effects of baseline ANTIDEP+ and EDS_ANTIDEP+ on all-cause mortality risk in socio-demographic factors-adjusted models (Pure Indirect Effect >0, P < 0.05; Total Effect >0, P < 0.05). Thus, higher AgeAccelGrim partially explained the relationship between antidepressant use and increased all-cause mortality risk, though only prior to controlling for lifestyle and health-related factors. Antidepressant use and epigenetic age acceleration independently predicted increased all-cause mortality risk. Further studies are needed in varying populations.

Healthy Japanese dietary pattern is associated with slower biological aging in older men: WASEDA'S health study

Aging is the greatest risk factor for numerous diseases and mortality, and establishing geroprotective interventions targeting aging is required. Previous studies have suggested that healthy dietary patterns, such as the Mediterranean diet, are associated with delayed biological aging; however, these associations depend on nationality and sex. Therefore, this study aimed to investigate the relationship between dietary patterns identified through principal component analysis and biological aging in older men of Japan, one of the countries with the longest life expectancies. Principal component analysis identified two dietary patterns: a healthy Japanese dietary pattern and a Western-style dietary pattern. Eight epigenetic clocks, some of the most accurate aging biomarkers, were identified using DNA methylation data from whole-blood samples. Correlation analyses revealed that healthy Japanese dietary patterns were significantly negatively or positively correlated with multiple epigenetic age accelerations (AgeAccel), including AgeAccelGrim, FitAgeAccel, and age-adjusted DNAm-based telomere length (DNAmTLAdjAge). Conversely, the Western-style dietary pattern was observed not to correlate significantly with any of the examined AgeAccels or age-adjusted values. After adjusting for covariates, the healthy Japanese dietary pattern remained significantly positively correlated with DNAmTLAdjAge. Regression analysis showed that healthy Japanese dietary pattern contributed less to epigenetic age acceleration than smoking status. These findings suggest that a Western-style dietary pattern may not be associated with biological aging, whereas a healthy Japanese dietary pattern is associated with delayed biological aging in older Japanese men. Our findings provide evidence that healthy dietary patterns may have mild beneficial effects on delayed biological aging in older Japanese men.

Decreased but persistent epigenetic age acceleration is associated with changes in T-cell subsets after initiation of highly active antiretroviral therapy in persons living with HIV

Introduction

Persons living with HIV (PLWH) experience the early onset of age-related illnesses, even in the setting of successful human immunodeficiency virus (HIV) suppression with highly active antiretroviral therapy (HAART). HIV infection is associated with accelerated epigenetic aging as measured using DNA methylation (DNAm)-based estimates of biological age and of telomere length (TL).

Methods

DNAm levels (Infinium MethylationEPIC BeadChip) from peripheral blood mononuclear cells from 200 PLWH and 199 HIV-seronegative (SN) participants matched on chronologic age, hepatitis C virus, and time intervals were used to calculate epigenetic age acceleration, expressed as age-adjusted acceleration residuals from 4 epigenetic clocks [Horvath's pan-tissue age acceleration residual (AAR), extrinsic epigenetic age acceleration (EEAA), phenotypic epigenetic age acceleration (PEAA), and grim epigenetic age acceleration (GEAA)] plus age-adjusted DNAm-based TL (aaDNAmTL). Epigenetic age acceleration was compared for PLWH and SN participants at two visits: up to 1.5 years prior and 2-3 years after HAART (or equivalent visits). Flow cytometry was performed in PLWH and SN participants at both visits to evaluate T-cell subsets.

Results

Epigenetic age acceleration in PLWH decreased after the initiation of HAART but remained greater post-HAART than that in age-matched SN participants, with differences in medians of 6.6, 9.1, and 7.7 years for AAR, EEAA, and PEAA, respectively, and 0.39 units of aaDNAmTL shortening (all p < 0.001). Cumulative HIV viral load after HAART initiation was associated with some epigenetic acceleration (EEAA, PEAA, and aaDNAmTL), but even PLWH with undetectable HIV post-HAART showed persistent epigenetic age acceleration compared to SN participants (p < 0.001). AAR, EEAA, and aaDNAmTL showed significant associations with total, naïve, and senescent CD8 T-cell counts; the total CD4 T-cell counts were associated with AAR, EEAA, and PEAA (p = 0.04 to <0.001). In an epigenome-wide analysis using weighted gene co-methylation network analyses, 11 modules demonstrated significant DNAm differences pre- to post-HAART initiation. Of these, nine were previously identified as significantly different from pre- to post-HIV infection but in the opposite direction.

Discussion

In this large longitudinal study, we demonstrated that, although the magnitude of the difference decreases with HAART is associated with the cumulative viral load, PLWH are persistently epigenetically older than age-matched SN participants even after the successful initiation of HAART, and these changes are associated with changes in T-cell subsets.

Predicting exacerbation of renal function by DNA methylation clock and DNA damage of urinary shedding cells: a pilot study

Recent reports have shown the feasibility of measuring biological age from DNA methylation levels in blood cells from specific regions identified by machine learning, collectively known as the epigenetic clock or DNA methylation clock. While extensive research has explored the association of the DNA methylation clock with cardiovascular diseases, cancer, and Alzheimer's disease, its relationship with kidney diseases remains largely unexplored. In particular, it is unclear whether the DNA methylation clock could serve as a predictor of worsening kidney function. In this pilot study involving 20 subjects, we investigated the association between the DNA methylation clock and subsequent deterioration of renal function. Additionally, we noninvasively evaluated DNA damage in urinary shedding cells using a previously reported method to examine the correlation with the DNA methylation clock and worsening kidney function. Our findings revealed that patients with an accelerated DNA methylation clock exhibited increased DNA damage in urinary shedding cells, along with a higher rate of eGFR decline. Moreover, in cases of advanced CKD (G4-5), the DNA damage in urinary shedding cells was significantly increased, highlighting the interplay between elevated DNA damage and eGFR decline. This study suggests the potential role of the DNA methylation clock and urinary DNA damage as predictive markers for the progression of chronic kidney disease.

Reliable detection of stochastic epigenetic mutations and associations with cardiovascular aging

Stochastic epigenetic mutations (SEMs) have been proposed as novel aging biomarkers to capture heterogeneity in age-related DNA methylation changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. Because SEMs are defined by their outlier status, it is critical to differentiate extreme values due to technical noise or data artifacts from those due to real biology. Using technical replicate data, we found SEM detection is not reliable: across 3 datasets, 24 to 39% of hypoSEM and 46 to 67% of hyperSEM are not shared between replicates. We identified factors influencing SEM reliability-including blood cell type composition, probe beta-value statistics, genomic location, and presence of SNPs. We used these factors in a training dataset to build a machine learning-based filter that removes unreliable SEMs, and found this filter enhances reliability in two independent validation datasets. We assessed associations between SEM loads and aging phenotypes in the Framingham Heart Study and discovered that associations with aging outcomes were in large part driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations were preserved after filtering out unreliable SEMs and were enhanced after adjusting for blood cell composition. Finally, we utilized these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which uses parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.

The effect of epigenetic aging on neurodegenerative diseases: a Mendelian randomization study

Background

Aging has always been considered as a risk factor for neurodegenerative diseases, but there are individual differences and its mechanism is not yet clear. Epigenetics may unveil the relationship between aging and neurodegenerative diseases.

Methods

Our study employed a bidirectional two-sample Mendelian randomization (MR) design to assess the potential causal association between epigenetic aging and neurodegenerative diseases. We utilized publicly available summary datasets from several genome-wide association studies (GWAS). Our investigation focused on multiple measures of epigenetic age as potential exposures and outcomes, while the occurrence of neurodegenerative diseases served as potential exposures and outcomes. Sensitivity analyses confirmed the accuracy of the results.

Results

The results show a significant decrease in risk of Parkinson's disease with GrimAge (OR = 0.8862, 95% CI 0.7914-0.9924, p = 0.03638). Additionally, we identified that HannumAge was linked to an increased risk of Multiple Sclerosis (OR = 1.0707, 95% CI 1.0056-1.1401, p = 0.03295). Furthermore, we also found that estimated plasminogen activator inhibitor-1(PAI-1) levels demonstrated an increased risk for Alzheimer's disease (OR = 1.0001, 95% CI 1.0000-1.0002, p = 0.04425). Beyond that, we did not observe any causal associations between epigenetic age and neurodegenerative diseases risk.

Conclusion

The findings firstly provide evidence for causal association of epigenetic aging and neurodegenerative diseases. Exploring neurodegenerative diseases from an epigenetic perspective may contribute to diagnosis, prognosis, and treatment of neurodegenerative diseases.

Assessing the association of epigenetic age acceleration with osteoarthritis in the Multicenter Osteoarthritis Study (MOST)

PURPOSE

Advancing age is one of the strongest risk factors for osteoarthritis (OA). DNA methylation-based measures of epigenetic age acceleration may provide insights into mechanisms underlying OA.

METHODS

We analyzed data from the Multicenter Osteoarthritis Study in a subset of 671 participants ages 45-69 years with no or mild radiographic knee OA. DNA methylation was assessed with the Illumina Infinium MethylationEPIC 850K array. We calculated predicted epigenetic age according to Hannum, Horvath, PhenoAge, and GrimAge epigenetic clocks, then regressed epigenetic age on chronological age to obtain the residuals. Associations between the residuals and knee, hand, and multi-joint OA were assessed using logistic regression, adjusted for chronological age, sex, clinical site, smoking status, and race.

RESULTS

Twenty-three percent met criteria for radiographic hand OA, 25% met criteria for radiographic knee OA, and 8% met criteria for multi-joint OA. Mean chronological age (SD) was 58.4 (6.7) years. Mean predicted epigenetic age (SD) according to Horvath, Hannum, PhenoAge, and GrimAge epigenetic clocks was 64.9 (6.4), 68.6 (5.9), 50.5 (7.7), and 67.0 (6.2), respectively. Horvath epigenetic age acceleration was not associated with an increased odds of hand OA, odds ratio (95% confidence intervals) = 1.03 (0.99-1.08), with similar findings for knee and multi-joint OA. We found similar magnitudes of associations for Hannum epigenetic age, PhenoAge, and GrimAge acceleration compared to Horvath epigenetic age acceleration.

CONCLUSIONS

Epigenetic age acceleration as measured by various well-validated epigenetic clocks based on DNA methylation was not associated with increased risk of knee, hand, or multi-joint OA independent of chronological age.

Heterogeneity of aging and mortality risk among individuals with hypertension: Insights from phenotypic age and phenotypic age acceleration

OBJECTIVES

Hypertension, a key contributor to mortality, is impacted by biological aging. We investigated the relationship between novel biological aging metrics - Phenotypic Age (PA) and Phenotypic Age Acceleration (PAA) - and mortality in individuals with hypertension, exploring the mediating effects of arterial stiffness (estimated Pulse Wave Velocity, ePWV), and Heart/Vascular Age (HVA).

METHODS

Using data from 62,160 National Health and Nutrition Examination Survey (NHANES) participants (1999-2010), we selected 4,228 individuals with hypertension and computed PA, PAA, HVA, and ePWV. Weighted, multivariable Cox regression analysis yielded Hazard Ratios (HRs) relating PA, PAA to mortality, and mediation roles of ePWV, PAA, HVA were evaluated. Mendelian randomization (MR) analysis was employed to investigate causality between genetically inferred PAA and hypertension.

RESULTS

Over a 12-year median follow-up, PA and PAA were tied to increased mortality risks in individuals with hypertension. All-cause mortality hazard ratios per 10-year PA and PAA increments were 1.96 (95% CI, 1.81-2.11) and 1.67 (95% CI, 1.52-1.85), respectively. Cardiovascular mortality HRs were 2.32 (95% CI, 1.97-2.73) and 1.93 (95% CI, 1.65-2.26) for PA and PAA, respectively. ePWV, PAA, and HVA mediated 42%, 30.3%, and 6.9% of PA's impact on mortality, respectively. Mendelian randomization highlighted a causal link between PAA genetics and hypertension (OR = 1.002; 95% CI, 1.000-1.003).

CONCLUSION

PA and PAA, enhancing cardiovascular risk scores by integrating diverse biomarkers, offer vital insights for aging and mortality evaluation in individuals with hypertension, suggesting avenues for intensified aging mitigation and cardiovascular issue prevention. Validations in varied populations and explorations of underlying mechanisms are warranted.

Uncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation

Age estimation is a critical aspect of reconstructing a biological profile in forensic sciences. Diverse biochemical processes have been studied in their correlation with age, and the results have driven DNA methylation to the forefront as a promising biomarker. DNA methylation, an epigenetic modification, has been extensively studied in recent years for developing age estimation models in criminalistics and forensic anthropology. Epigenetic clocks, which analyze DNA sites undergoing hypermethylation or hypomethylation as individuals age, have paved the way for improved prediction models. A wide range of biomarkers and methods for DNA methylation analysis have been proposed, achieving different accuracies across samples and cell types. This review extensively explores literature from the past 5 years, showing scientific efforts toward the ultimate goal: applying age prediction models to assist in human identification.

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.

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

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

Association of Cadherin-Related Family Member 1 with Traumatic Brain Injury

The cadherin family plays a pivotal role in orchestrating synapse formation in the central nervous system. Cadherin-related family member 1 (CDHR1) is a photoreceptor-specific calmodulin belonging to the expansive cadherin superfamily. However, its role in traumatic brain injury (TBI) remains largely unknown. CDHR1 expression across various brain tissue sites was analyzed using the GSE104687 dataset. Employing a summary-data-based Mendelian Randomization (SMR) approach, integrated analyses were performed by amalgamating genome-wide association study abstracts from TBI with public data on expressed quantitative trait loci and DNA methylation QTL from both blood and diverse brain tissues. CDHR1 expression and localization in different brain tissues were meticulously delineated using western blotting, immunohistochemistry, and enzyme-linked immunosorbent assay. CDHR1 expression was consistently elevated in the TBI group compared to that in the sham group across multiple tissues. The inflammatory response emerged as a crucial biological mechanism, and pro-inflammatory and anti-inflammatory factors were not expressed in either group. Integrated SMR analyses encompassing both blood and brain tissues substantiated the heightened CDHR1 expression profiles, with methylation modifications emerging as potential contributing factors for increased TBI risk. This was corroborated by western blotting and immunohistochemistry, confirming augmented CDHR1 expression following TBI. This multi-omics-based genetic association study highlights the elevated TBI risk associated with CDHR1 expression coupled with putative methylation modifications. These findings provide compelling evidence for future targeted investigations and offer promising avenues for developing interventional therapies for TBI.

Pregnancy is linked to faster epigenetic aging in young women

A central prediction of evolutionary theory is that energy invested into reproduction comes at the expense of somatic maintenance and repair, accelerating biological aging. Supporting this prediction are findings that high fertility among women predicts shorter lifespan and poorer health later in life. However, biological aging is thought to begin before age-related health declines, limiting the applicability of morbidity and mortality for studying the aging process earlier in life. Here, we examine the relationship between reproductive history and biological aging in a sample of young (20 to 22yo) men and women from the Cebu Longitudinal Health and Nutrition Survey, located in the Philippines (n = 1,735). We quantify biological aging using six measures, collectively known as epigenetic clocks, reflecting various facets of cellular aging, health, and mortality risk. In a subset of women, we test whether longitudinal changes in gravidity between young and early-middle adulthood (25 to 31yo) are associated with changes in epigenetic aging during that time. Cross-sectionally, gravidity was associated with all six measures of accelerated epigenetic aging in women (n = 825). Furthermore, longitudinal increases in gravidity were linked to accelerated epigenetic aging in two epigenetic clocks (n = 331). In contrast, the number of pregnancies a man reported fathering was not associated with epigenetic aging among same-aged cohort men (n = 910). These effects were robust to socioecological, environmental, and immunological factors, consistent with the hypothesis that pregnancy accelerates biological aging and that these effects can be detected in young women in a high-fertility context.

Meta-analysis of epigenetic aging in schizophrenia reveals multifaceted relationships with age, sex, illness duration, and polygenic risk

BACKGROUND

The study of biological age acceleration may help identify at-risk individuals and reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a whole blood DNAm sample of 1090 SCZ cases and 1206 controls across four European cohorts, we performed a meta-analysis of differential aging using three DNAm clocks (i.e., Hannum, Horvath, and Levine). To dissect how DNAm aging contributes to SCZ, we integrated information on duration of illness and SCZ polygenic risk, as well as stratified our analyses by chronological age and biological sex.

RESULTS

We found that blood-based DNAm aging is significantly altered in SCZ independent from duration of the illness since onset. We observed sex-specific and nonlinear age effects that differed between clocks and point to possible distinct age windows of altered aging in SCZ. Most notably, intrinsic cellular age (Horvath clock) is decelerated in SCZ cases in young adulthood, while phenotypic age (Levine clock) is accelerated in later adulthood compared to controls. Accelerated phenotypic aging was most pronounced in women with SCZ carrying a high polygenic burden with an age acceleration of + 3.82 years (CI 2.02-5.61, P = 1.1E-03). Phenotypic aging and SCZ polygenic risk contributed additively to the illness and together explained up to 14.38% of the variance in disease status.

CONCLUSIONS

Our study contributes to the growing body of evidence of altered DNAm aging in SCZ and points to intrinsic age deceleration in younger adulthood and phenotypic age acceleration in later adulthood in SCZ. Since increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. Our study did not find that DNAm aging could be explained by the duration of illness of patients, but we did observe age- and sex-specific effects that warrant further investigation. Finally, our results show that combining genetic and epigenetic predictors can improve predictions of disease outcomes and may help with disease management in schizophrenia.

Organ-specific biological clocks: Ageotyping for personalized anti-aging medicine

Aging is a complex multidimensional, progressive remodeling process affecting multiple organ systems. While many studies have focused on studying aging across multiple organs, assessment of the contribution of individual organs to overall aging processes is a cutting-edge issue. An organ's biological age might influence the aging of other organs, revealing a multiorgan aging network. Recent data demonstrated a similar yet asynchronous inter-organs and inter-individuals progression of aging, thereby providing a foundation to track sources of declining health in old age. The integration of multiple omics with common clinical parameters through artificial intelligence has allowed the building of organ-specific aging clocks, which can predict the development of specific age-related diseases at high resolution. The peculiar individual aging-trajectory, referred to as ageotype, might provide a novel tool for a personalized anti-aging, preventive medicine. Here, we review data relative to biological aging clocks and omics-based data, suggesting different organ-specific aging rates. Additional research on longitudinal data, including young subjects and analyzing sex-related differences, should be encouraged to apply ageotyping analysis for preventive purposes in clinical practice.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

High ambient temperature and HI may accelerate biological aging.

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

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

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

Importance

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

Objective

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

Design

Nationally representative prospective cohort study.

Setting

United States (U.S.).

Participants

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

Exposure

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

Main Outcome

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

Results

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

Conclusions and Relevance

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

Key Points

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