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Background Diabetes ranks as the ninth leading cause of death globally, and DNA-methylation age acceleration (DNAmAA) is closely linked to lifespan. However, the impact of DNAmAA on long-term outcomes in specific populations with diabetes and pre-diabetes has not yet been comprehensively studied. Methods This retrospective cohort study utilized data from the National Health and Nutrition Examination Survey (NHANES) 1999–2002, including participants aged 20 years or older diagnosed with diabetes or pre-diabetes. DNAmAA was defined as the difference between epigenetic age and chronological age. Multiple generations of DNAmAA measures were included. Cox proportional hazards regression models were employed to estimate the associations between DNAmAAs and all-cause, cardiovascular, and non-cardiovascular mortality. Results A total of 1,199 participants were included, with a mean age of 64.20 (0.46) years; 621 (51.8%) were male. Significant correlations were observed between chronological age and all DNA-methylation ages in both diabetes and pre-diabetes groups. Over a mean follow-up of 14.13 (5.90) years, 662 deaths were recorded. AgeAccelGrim2 exhibited the strongest association with mortality. Each 5-unit increase in AgeAccelGrim2 was associated with an elevated risk of all-cause mortality (HR 1.35, 95% CI 1.23–1.49), cardiovascular mortality (HR 1.50, 95% CI 1.25–1.80), and non-cardiovascular mortality (HR 1.30, 95% CI 1.16–1.46). These associations remained significant in participants with diabetes and pre-diabetes. Mediation analysis revealed that AgeAccelGrim2 significantly mediates the association between health-related exposures (including the Oxidative Balance Score, Life’s Simple 7 score, and frailty score) and all-cause mortality in diabetes and pre-diabetes populations. Conclusions AgeAccelGrim2 could serve as a valuable biomarker for mortality risk specific to populations with diabetes and pre-diabetes, offering potential applications in personalized management strategies and risk stratification.

Background The capacity of technologies measuring DNA methylation (DNAm) is rapidly evolving, as are the options for applicable bioinformatics methods. The most commonly used DNAm microarray, the Illumina Infinium HumanMethylation450 (450K array), has recently been replaced by the Illumina Infinium HumanMethylationEPIC (EPIC array), nearly doubling the number of targeted CpG sites. Given that a subset of 450K CpG sites is absent on the EPIC array and that several tools for both data normalization and analyses were developed on the 450K array, it is important to assess their utility when applied to EPIC array data. One of the most commonly used 450K tools is the pan-tissue epigenetic clock, a multivariate predictor of biological age based on DNAm at 353 CpG sites. Of these CpGs, 19 are missing from the EPIC array, thus raising the question of whether EPIC data can be used to accurately estimate DNAm age. We also investigated a 71-CpG epigenetic age predictor, referred to as the Hannum method, which lacks 6 probes on the EPIC array. To evaluate these epigenetic clocks in EPIC data properly, a prior assessment of the effects of data preprocessing methods on DNAm age is also required. Methods DNAm was quantified, on both the 450K and EPIC platforms, from human primary monocytes derived from 172 individuals. We calculated DNAm age from raw, and three different preprocessed data forms to assess the effects of different processing methods on the DNAm age estimate. Using an additional cohort, we also investigated DNAm age of peripheral blood mononuclear cells, bronchoalveolar lavage, and bronchial brushing samples using the EPIC array. Results Using monocyte-derived data from subjects on both the 450K and EPIC, we found that DNAm age was highly correlated across both raw and preprocessing methods ( r  > 0.91). Thus, the correlation between chronological age and the DNAm age estimate is largely unaffected by platform differences and normalization methods. However, we found that the choice of normalization method and measurement platform can lead to a systematic offset in the age estimate which in turn leads to an increase in the median error. Comparing the 450K and EPIC DNAm age estimates, we observed that the median absolute difference was 1.44–3.10 years across preprocessing methods. Conclusions Here, we have provided evidence that the epigenetic clock is resistant to the lack of 19 CpG sites missing from the EPIC array as well as highlighted the importance of considering the technical variance of the epigenetic when interpreting group differences below the reported error. Furthermore, our study highlights the utility of epigenetic age acceleration measure, the residuals from a linear regression of DNAm age on chronological age, as the resulting values are robust with respect to normalization methods and measurement platforms.

The repeat expansion in C9orf72 is the most common cause of amyotrophic lateral sclerosis and frontotemporal dementia. C9orf72 patients present with a wide range in disease duration and age of onset. The strongest risk factor for both syndromes is aging, which was linked to DNA methylation (DNAm) age based on the cumulative assessment of the methylation levels of 353 CpGs included on the genome-wide 450k BeadChip. DNAm age may reflect biological age better than chronological age. We conducted a genome-wide blood DNA methylation study of 46 unrelated C9orf72 patients. After correction for multiple testing, none of the CpGs demonstrated association between its methylation level and disease duration or age of onset. However, we detected a significant reverse correlation of DNAm age-acceleration with disease duration and age of onset, suggesting that for every 5-year increase in DNAm age-acceleration there is a 3.2-year earlier age of onset and 1.5-year shorter disease duration. The significant correlations remain after adjusting for gender, TMEM106B genotypes, disease phenotype and C9orf72 5′CpG island methylation status. A similar trend was observed for the blood DNA of affected members of an extended C9orf72 family; and tissues from the central nervous system of C9orf72 autopsy cases. For instance, regression analysis suggested that a 5-year increase in DNAm age-acceleration is linked to an earlier age of onset by 4.7 or 5.5 years for frontal cortex or spinal cord, respectively. Blood DNAm age may be a useful biomarker for biological age, because blood DNAm age-acceleration was similar to all investigated brain tissues, except for cerebellum that ages more slowly. In conclusion, DNA methylation analysis of C9orf72 patients revealed that increased DNAm age-acceleration is associated with a more severe disease phenotype with a shorter disease duration and earlier age of onset.

Background Aging represents a serious health and socioeconomic concern for our society. However, not all people age in the same way and air pollution has been shown to largely impact this process. We explored whether polycyclic aromatic hydrocarbons (PAHs), excellent fossil and wood burning tracers, accelerate biological aging detected by lymphocytes DNA methylation age (DNAmAge) and telomere length (TL), early nuclear DNA (nDNA) hallmarks of non-mitotic and mitotic cellular aging, and mitochondrial DNA copy number (mtDNAcn). Methods The study population consisted of 49 male noncurrent-smoking coke-oven workers and 44 matched controls. Occupational and environmental sources of PAH exposures were evaluated by structured questionnaire and internal dose (urinary 1-pyrenol). We estimated Occup_PAHs, the product of 1-pyrenol and years of employment as coke-oven workers, and Environ_PAHs, from multiple items (diet, indoor and outdoor). Biological aging was determined by DNAmAge, via pyrosequencing, and by TL and mtDNAcn, via quantitative polymerase chain reaction. Genomic instability markers in lymphocytes as target dose [anti-benzo[a]pyrene diolepoxide (anti-BPDE)–DNA adduct], genetic instability (micronuclei), gene-specific (p53, IL6 and HIC1) and global (Alu and LINE-1 repeats) DNA methylation, and genetic polymorphisms (GSTM1) were also evaluated in the latent variable nDNA_changes. Structural equation modelling (SEM) analysis evaluated these multifaceted relationships. Results In univariate analysis, biological aging was higher in coke-oven workers than controls as detected by higher percentage of subjects with biological age older than chronological age (AgeAcc ≥ 0, p  = 0.007) and TL ( p  = 0.038), mtDNAcn was instead similar. Genomic instability, i.e., genotoxic and epigenetic alterations (LINE-1, p53 and Alu) and latent variable nDNA_changes were higher in workers ( p  < 0.001). In SEM analysis, DNAmAge and TL were positively correlated with Occup_PAHs ( p  < 0.0001). Instead, mtDNAcn is positively correlated with the latent variable nDNA_changes ( p  < 0.0001) which is in turn triggered by Occup_PAHs and Environ_PAHs. Conclusions Occupational PAHs exposure influences DNAmAge and TL, suggesting that PAHs target both non-mitotic and mitotic mechanisms and made coke-oven workers biologically older. Also, differences in mtDNAcn, which is modified through nDNA alterations, triggered by environmental and occupational PAH exposure, suggested a nuclear-mitochondrial core-axis of aging. By decreasing this risky gerontogenic exposure, biological aging and the consequent age-related diseases could be prevented.

Posttraumatic stress disorder (PTSD) and stress/trauma exposure are cross-sectionally associated with advanced DNA methylation age relative to chronological age. However, longitudinal inquiry and examination of associations between advanced DNA methylation age and a broader range of psychiatric disorders is lacking. The aim of this study was to examine if PTSD, depression, generalized anxiety, and alcohol-use disorders predicted acceleration of DNA methylation age over time (i.e. an increasing pace, or rate of advancement, of the epigenetic clock). Genome-wide DNA methylation and a comprehensive set of psychiatric symptoms and diagnoses were assessed in 179 Iraq/Afghanistan war veterans who completed two assessments over the course of approximately 2 years. Two DNA methylation age indices (Horvath and Hannum), each a weighted index of an array of genome-wide DNA methylation probes, were quantified. The pace of the epigenetic clock was operationalized as change in DNA methylation age as a function of time between assessments. Analyses revealed that alcohol-use disorders (p = 0.001) and PTSD avoidance and numbing symptoms (p = 0.02) at Time 1 were associated with an increasing pace of the epigenetic clock over time, per the Horvath (but not the Hannum) index of cellular aging. This is the first study to suggest that posttraumatic psychopathology is longitudinally associated with a quickened pace of the epigenetic clock. Results raise the possibility that accelerated cellular aging is a common biological consequence of stress-related psychopathology, which carries implications for identifying mechanisms of stress-related cellular aging and developing interventions to slow its pace.

Background Previous studies have developed models predicting methylation age from DNA methylation in blood and other tissues (epigenetic clock) and suggested the difference between DNA methylation and chronological ages as a marker of healthy aging. The goal of this study was to confirm and expand such observations by investigating whether different concepts of the epigenetic clocks in a population-based cohort are associated with cancer, cardiovascular, and all-cause mortality. Results DNA methylation age was estimated in a cohort of 1863 older people, and the difference between age predicted by DNA methylation and chronological age (Δ age ) was calculated. A case-cohort design and weighted proportional Cox hazard models were used to estimate associations of Δ age with cancer, cardiovascular, and all-cause mortality. Hazard ratios for Δ age (per 5 years) calculated using the epigenetic clock developed by Horvath were 1.23 (95 % CI 1.10–1.38) for all-cause mortality, 1.22 (95 % CI 1.03–1.45) for cancer mortality, and 1.19 (95 % CI 0.98–1.43) for cardiovascular mortality after adjustment for batch effects, age, sex, educational level, history of chronic diseases, hypertension, smoking status, body mass index, and leucocyte distribution. Associations were similar but weaker for Δ age calculated using the epigenetic clock developed by Hannum. Conclusions These results show that age acceleration in terms of the difference between age predicted by DNA methylation and chronological age is an independent predictor of all-cause and cause-specific mortality and may be useful as a general marker of healthy aging.

DNA methylation (DNAm) is an emerging estimator of biological aging, i.e., the often-defined “epigenetic clock”, with a unique accuracy for chronological age estimation (DNAmAge). In this pilot longitudinal study, we examine the hypothesis that intensive relaxing training of 60 days in patients after myocardial infarction and in healthy subjects may influence leucocyte DNAmAge by turning back the epigenetic clock. Moreover, we compare DNAmAge with another mechanism of biological age, leucocyte telomere length (LTL) and telomerase. DNAmAge is reduced after training in healthy subjects (p = 0.053), but not in patients. LTL is preserved after intervention in healthy subjects, while it continues to decrease in patients (p = 0.051). The conventional negative correlation between LTL and chronological age becomes positive after training in both patients (p < 0.01) and healthy subjects (p < 0.05). In our subjects, DNAmAge is not associated with LTL. Our findings would suggest that intensive relaxing practices influence different aging molecular mechanisms, i.e., DNAmAge and LTL, with a rejuvenating effect. Our study reveals that DNAmAge may represent an accurate tool to measure the effectiveness of lifestyle-based interventions in the prevention of age-related diseases.

Purpose The epigenetic clock has been acknowledged as an indicator for molecular aging, but few studies have examined possible associations of DNA methylation (DNAm) age or age acceleration (AA) with symptom burden in individuals who are treated for cancer. This study explored the association of DNAm age or AA with psychoneurological (PN) symptoms, including cognitive impairment, fatigue, sleep disturbances, pain, and depressive symptoms, in breast cancer survivors over a 2-year period. Methods We measured PN symptoms using reliable instruments and DNAm levels by Infinium HumanMethylation450K BeadChip ( N  = 72). DNAm age was calculated by the Horvath, Grim, and Hannum-based intrinsic and extrinsic age estimations. AA was defined by the residual regressing estimated epigenetic age on chronological age. Mixed regression models were fitted for AA and changes in AA to study the association over time. Separate linear regression models and a mixed-effects model were fitted for AA at each time point. Results Horvath-AA, Grim-AA, and extrinsic epigenetic AA were significantly changed over time, while intrinsic epigenetic AA did not exhibit any temporal changes. Increased AA was associated with greater anxiety and fatigue, as well as worse cognitive memory, adjusting for race, BMI, income, chemotherapy, radiation therapy, and chronological age. Increased DNAm age was associated with greater anxiety over 2 years. Conclusion Our findings suggest DNAm age and AA may be associated with PN symptoms over the course of cancer treatment and survivorship. Some PN symptoms may be amenable to preventive interventions targeted to epigenetic clocks that influence aging-associated processes.

Maternal stress during lifetime and pregnancy may influence offspring epigenetic age, impacting long-term health. We conducted a systematic review and meta-analysis of associations between maternal stress and epigenetic aging markers: telomere length (TL) and DNA methylation (DNAm) age acceleration. The systematic search was performed according to PRISMA guidelines and registered on PROSPERO (ref. CRD42023474640). Fixed and random effect meta-analyses were carried out, stratified by stress type and marker type (TL, DNAm). Sixteen studies met inclusion criteria; 12 were meta-analyzed (10 TL, 2 DNAm). Due to high heterogeneity, restricted maximum likelihood meta-analysis suggested significant inverse associations between maternal stress and offspring TL. Perceived stress was associated with shorter TL (p-value = 7 × 10−4, β = −0.085, 95%CI [−0.135, −0.036]), as was lifetime stress/trauma (p-value = 0.01, β = −0.209, 95%CI [−0.370, −0.049]). In contrast, maternal stress showed no significant associations with DNAm age acceleration (p-value = 0.32). Both perceived maternal stress and maternal stress were associated with shorter offspring TL, suggesting that stress exposure across the maternal lifespan influences offspring biological aging markers. No significant association was observed with DNAm-based aging clocks. Further studies with larger sample sizes and more homogeneous settings are needed to confirm and expand upon our observations.

Chronological age is the most important risk factor for the incidence of age-related diseases. The pace of ageing determines the magnitude of that risk and can be expressed as biological age. Targeting fundamental pathways of human aging with geroprotectors has the potential to lower the biological age and therewith prolong the healthspan, the period of life one spends in good health. Target populations for geroprotective interventions should be chosen based on the ageing mechanisms being addressed and the expected effect of the geroprotector on the primary outcome. Biomarkers of ageing, such as DNA methylation age, can be used to select populations for geroprotective interventions and as a surrogate outcome. Here, the use of DNA methylation clocks for selecting target populations for geroprotective intervention is explored.