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Frailty is classically associated with advanced age but is also an important predictor of clinical outcomes in comparatively young adults with cirrhosis. We examined the association of biological aging with frailty and post-transplant outcomes in a pilot of adults with cirrhosis undergoing liver transplantation (LT). Frailty was measured via the Liver Frailty Index (LFI). The primary epigenetic clock DNA methylation (DNAm) PhenoAge was calculated from banked peripheral blood mononuclear cells; we secondarily explored two first-generation clocks (Hannum; Horvath) and two additional second-generation clocks (GrimAge; GrimAge2). Twelve adults were included: seven frail (LFI ≥ 4.4, mean age 55 years) and five robust (LFI

Young blood plasma is known to confer beneficial effects on various organs in mice and rats. However, it was not known whether plasma from young adult pigs rejuvenates old rat tissues at the epigenetic level; whether it alters the epigenetic clock, which is a highly accurate molecular biomarker of aging. To address this question, we developed and validated six different epigenetic clocks for rat tissues that are based on DNA methylation values derived from n = 613 tissue samples. As indicated by their respective names, the rat pan-tissue clock can be applied to DNA methylation profiles from all rat tissues, while the rat brain, liver, and blood clocks apply to the corresponding tissue types. We also developed two epigenetic clocks that apply to both human and rat tissues by adding n = 1366 human tissue samples to the training data. We employed these six rat clocks to investigate the rejuvenation effects of a porcine plasma fraction treatment in different rat tissues. The treatment more than halved the epigenetic ages of blood, heart, and liver tissue. A less pronounced, but statistically significant, rejuvenation effect could be observed in the hypothalamus. The treatment was accompanied by progressive improvement in the function of these organs as ascertained through numerous biochemical/physiological biomarkers, behavioral responses encompassing cognitive functions. An immunoglobulin G (IgG) N-glycosylation pattern shift from pro- to anti-inflammatory also indicated reversal of glycan aging. Overall, this study demonstrates that a young porcine plasma-derived treatment markedly reverses aging in rats according to epigenetic clocks, IgG glycans, and other biomarkers of aging.

• Epigenetic clocks leverage artificial intelligence to predict biological age by analyzing specific age-related CpG sites • An overview of classic epigenetic clocks is provided • Epigenetic clocks help identify aging risk factors and evaluate anti-aging interventions • The potential of epigenetic clocks to predict the onset of aging-related diseases is explored • The current limitations of epigenetic clocks are discussed, along with prospects for future development The process of aging is a notable risk factor for numerous age-related illnesses. Hence, a reliable technique for evaluating biological age or the pace of aging is crucial for understanding the aging process and its influence on the progression of disease. Epigenetic alterations are recognized as a prominent biomarker of aging, and epigenetic clocks formulated on this basis have been shown to provide precise estimations of chronological age. Extensive research has validated the effectiveness of epigenetic clocks in determining aging rates, identifying risk factors for aging, evaluating the impact of anti-aging interventions, and predicting the emergence of age-related diseases. This review provides a detailed overview of the theoretical principles underlying the development of epigenetic clocks and their utility in aging research. Furthermore, it explores the existing obstacles and possibilities linked to epigenetic clocks and proposes potential avenues for future studies in this field. [ABSTRACT FROM AUTHOR]

Evidence is accumulating on the connection of early adversities and harsh family environment with epigenetic ageing. We investigated whether early psychosocial resilience is associated with epigenetic ageing in adulthood. We used the population‐based Young Finns data (n = 1593). Early psychosocial resilience was assessed in 1980–1989 across five broad domains: (1) index of psychological strength (self‐esteem at home/in general/at school, perceived possibilities to influence at home, internal life control), (2) index of social satisfaction (perceived support from family/friends and life satisfaction), (3) index of leisure time activities (hobbies and physical fitness), (4) index of responsible health behaviors (infrequent smoking or alcohol consumption), and (5) index of school career (school grades and adaptation). Epigenetic ages were calculated for blood samples from 2011, and the analyses were performed with variables describing age deviation (AgeDevHannum, AgeDevHorvath, AgeDevPheno, AgeDevGrim) and DunedinPACE. Covariates included early family environment, polygenic risk scores for schizophrenia and major depression, adulthood education, and adulthood health behaviors. All of the early resilience indexes were associated with lower levels of epigenetic ageing in adulthood, most consistently with AgeDevGrim and DunedinPACE. The associations of psychological strength and social satisfaction, in particular, seemed to be non‐linear. In a smaller subsample (n = 289), high early resilience was related to lower AgeDevGrim over a 25‐year follow‐up in those who had high “baseline” levels of AgeDevGrim. In conclusion, early resilience seems to associate with lower level of epigenetic ageing in adulthood. Our results tentatively suggest that early resilience may increase “equality in epigenetic ageing” in a general population. [ABSTRACT FROM AUTHOR]

Mathematical algorithms known as "epigenetic clocks" use methylation values at a set of CpG sites to estimate the biological age of an individual in a tissue-specific manner. These clocks have demonstrated both acceleration and delays in epigenetic aging in multiple neuropsychiatric conditions, including schizophrenia and neurodevelopmental disorders such as autism spectrum disorder. However, no study to date has examined epigenetic aging in ADHD despite its status as one of the most prevalent neurodevelopmental conditions, with 1 in 9 children having ever received an ADHD diagnosis in the US. Only a handful of studies have examined epigenetic age in brain tissue from neurodevelopmental conditions, with none focused on ADHD, despite the obvious relevance to pathogenesis. Thus, here we asked if post-mortem brain tissue in those with lifetime histories of ADHD would show accelerated or delayed epigenetic age, as has been found for other neurodevelopmental conditions. We applied four different epigenetic clocks to estimate epigenetic age in individuals with ADHD and unaffected controls from cortical (anterior cingulate cortex, N = 55) and striatal (caudate, N = 56) post-mortem brain tissue, as well as peripheral blood (N = 84) and saliva (N = 112). After determining which epigenetic clock performed best in each tissue, we asked if ADHD was associated with altered biological aging in corticostriatal brain and peripheral tissues. We found that a range of epigenetic clocks accurately predicted chronological age in all tissues. We also found that a diagnosis of ADHD was not significantly associated with differential epigenetic aging, neither for the postmortem ACC or caudate, nor for peripheral tissues. These findings held when accounting for comorbid psychiatric diagnoses, substance use, and stimulant medication. Thus, in this study of epigenetic clocks in ADHD, we find no evidence of altered epigenetic aging in corticostriatal brain regions nor in peripheral tissue. We consider reasons for this unexpected finding, including the limited sampling of brain regions, the age range of individuals studied, and the possibility that processes that accelerate epigenetic age may be counteracted by the developmental delay posited in some models of ADHD. [ABSTRACT FROM AUTHOR]

Background: Biological age, especially epigenetic age derived from the epigenetic clock, is a significant measure of aging, considering the differences in aging rates among individuals. The epigenetic clock, a machine learning-based algorithm, uses DNA methylation states to estimate biological age. Previous studies have reported inconsistent associations between physical activity (PA) and the epigenetic clock, especially second-generation clocks such as PhenoAge and GrimAge. This study aimed to clarify this relationship using cross-sectional data from Japanese participants aged 40–69. Methods: We used two datasets from the Saga J-MICC study, of which 867 samples were available for analysis. DNA methylation data from peripheral blood samples were used to calculate the epigenetic age using the epigenetic clocks PhenoAge and GrimAge. PA and sedentary time were measured using a single-axis accelerometer, while self-reported PA, sedentary time, and covariates were assessed using a self-administered questionnaire. The association between PA or sedentary time and epigenetic age acceleration was assessed using multiple linear regression. Results: Pearson's correlation coefficients between accelerometer-based and self-reported PA variables ranged from 0.09 to 0.20. Multivariable regression analysis showed that accelerometer-based PA and sedentary time were associated with epigenetic age decelerations and accelerations, respectively. However, self-reported PA was not associated with the epigenetic age accelerations. Conclusions: These results indicate that reducing sedentary time and increasing PA were associated with slowing both PhenoAge and GrimAge, even in East Asian populations with different exercise habits, body shapes, and lifestyles. This study highlights the potential of objective second-generation epigenetic age acceleration as an outcome index for healthcare interventions and clinical applications. [ABSTRACT FROM AUTHOR]

The Izpisua‐Belmonte group identified a cocktail of metabolites that promote partial reprogramming in cultured muscle cells. We tested the effect of brain injection of these metabolites in the dentate gyrus of aged wild‐type mice. The dentate gyrus is a brain region essential for memory function and is extremely vulnerable to aging. A single injection of the cocktail containing four compounds (putrescine, glycine, methionine and threonine) partially reversed brain aging phenotypes and epigenetic alterations in age‐associated genes. Our analysis revealed three levels: chromatin methylation, RNA sequencing, and protein expression. Functional studies complemented the previous ones, showing cognitive improvement. In summary, we report the reversal of various age‐associated epigenetic changes, such as the transcription factor Zic4, and several changes related to cellular rejuvenation in the dentate gyrus (DG). These changes include increased expression of the Sox2 protein. Finally, the increases in the survival of newly generated neurons and the levels of the NMDA receptor subunit GluN2B were accompanied by improvements in both short‐term and long‐term memory performance. Based on these results, we propose the use of these metabolites to explore new strategies for the development of potential treatments for age‐related brain diseases. [ABSTRACT FROM AUTHOR]

Background: Epigenetic clocks are mathematical models used to estimate epigenetic age based on DNA methylation at specific CpG sites. As new methylation microarrays are developed and older models discontinued, existing epigenetic clocks might become obsolete. Here, we explored the effects of the changes introduced in the new EPICv2 DNA methylation array on existing epigenetic clocks. Methods: We tested the performance of four epigenetic clocks on the probeset of the EPICv2 array using a dataset of 10,835 samples. We developed a new epigenetic age prediction model compatible across the 450 k, EPICv1, and EPICv2 microarrays and validated it on 2095 samples. We estimated technical noise and intra-subject variation using two datasets with repeated sampling. We used data from (i) cancer survivors who had undergone different therapies, (ii) breast cancer patients and controls, and (iii) an exercise-based interventional study, to test the ability of our model to detect alterations in epigenetic age acceleration in response to theoretically antiaging interventions. Results: The results of the four epiclocks tested are significantly distorted by the EPICv2 probeset, causing an average difference of up to 25 years. Our new model produced highly accurate chronological age predictions, comparable to a state-of-the-art epiclock. The model reported the lowest epigenetic age acceleration in normal populations, as well as the lowest variation across technical replicates and repeated samples from the same subjects. Finally, our model reproduced previous results of increased epigenetic age acceleration in cancer patients and in survivors treated with radiation therapy, and no changes from exercise-based interventions. Conclusion: Existing epigenetic clocks require updates for full EPICv2 compatibility. Our new model translates the capabilities of state-of-the-art epigenetic clocks to the EPICv2 platform and is cross-compatible with older microarrays. The characterization of epigenetic age prediction variation provides useful metrics to contextualize the relevance of epigenetic age alterations. The analysis of data from subjects influenced by radiation, cancer, and exercise-based interventions shows that despite being good predictors of chronological age, neither a pathological state like breast cancer, a hazardous environmental factor (radiation), nor exercise (a beneficial intervention) caused significant changes in the values of the "epigenetic age" determined by these first-generation models. [ABSTRACT FROM AUTHOR]

Reactivation of retroelements in the human genome has been linked to aging. However, whether the epigenetic state of specific retroelements can predict chronological age remains unknown. We provide evidence that locus‐specific retroelement DNA methylation can be used to create retroelement‐based epigenetic clocks that accurately measure chronological age in the immune system, across human tissues, and pan‐mammalian species. We also developed a highly accurate retroelement epigenetic clock compatible with EPICv.2.0 data that was constructed from CpGs that did not overlap with existing first‐ and second‐generation epigenetic clocks, suggesting a unique signal for epigenetic clocks not previously captured. We found retroelement‐based epigenetic clocks were reversed during transient epigenetic reprogramming, accelerated in people living with HIV‐1, and responsive to antiretroviral therapy. Our findings highlight the utility of retroelement‐based biomarkers of aging and support a renewed emphasis on the role of retroelements in geroscience. [ABSTRACT FROM AUTHOR]

Background: Social exposures are linked to an array of health outcomes, especially around aging. In this study, we examined the association of social capital, defined as social relationships and networks, with clinical and biological outcomes including cognitive health, oral inflammation, and epigenetic aging. Methods: We used data from the Canadian Longitudinal Study on Aging (CLSA) (n = 1,479; aged 45–85 years), categorizing social capital as structural and cognitive capital. Oral inflammation was determined as the presence of gum bleeding. Epigenetic aging was computed as the difference between chronological age and DNA methylation age. We constructed multivariable regression models adjusted for covariates to assess the relationships of interest. Results: Higher structural social capital was associated with decelerated epigenetic aging and better cognitive health outcomes, while higher cognitive social capital was associated with better cognitive outcomes and less oral inflammation. Conclusion: Enhanced social capital may contribute to better clinical and biological outcomes around aging. [ABSTRACT FROM AUTHOR]

Understanding the demography of wildlife populations is a key component for ecological research, and where necessary, supporting the conservation and management of long‐lived animals. However, many animals lack phenological changes with which to determine individual age; therefore, gathering this fundamental information presents difficulties. More so for species that are rare, highly mobile, migratory and those that reside in inaccessible habitats. Until recently, the primary method to measure demography is through labour intensive mark‐recapture approaches, necessitating decades of effort for long‐lived species. Gadfly petrels (genus: Pterodroma) are one such taxa that are overrepresented with threatened and declining species, and for which numerous aspects of their ecology present challenges for research, monitoring and recovery efforts. To overcome some of these challenges, we developed the first DNA methylation (DNAm) demography technique to estimate the age of petrels, using the epigenetic clock of Gould's petrels (Pterodroma leucoptera). We collected reference blood samples from known‐aged Gould's petrels at a long‐term monitored population on Cabbage Tree Island, Australia. Epigenetic ages were successfully estimated for 121 individuals ranging in age from zero (fledgling) to 30 years of age, showing a mean error of 2.24 ± 0.17 years between the estimated and real age across the population. This is the first development of an epigenetic clock using multiplex PCR sequencing in a bird. This method enables demography to be measured with relative accuracy in a single sampling trip. This technique can provide information for emerging demographic risks that can mask declines in long‐lived seabird populations and be applied to other Pterodroma populations. [ABSTRACT FROM AUTHOR]

Background DNA methylation-derived epigenetic clocks and frailty are well-established biological age measures capturing different aging processes. However, whether they are dynamically linked to each other across chronological age remains poorly understood. Methods This analysis included 1 309 repeated measurements in 524 individuals aged 50–90 years from the Swedish Adoption/Twin Study of Aging. Frailty was measured using a validated 42-item frailty index (FI). Five epigenetic clocks were calculated, including 4 principal component (PC)-based clocks trained on chronological age (PCHorvathAge and PCHannumAge) and aging-related physiological conditions (PCPhenoAge and PCGrimAge), and a pace of aging clock (DunedinPACE). Using dual change score models, we examined the dynamic, bidirectional associations between each of the epigenetic clocks and the FI over age to test for potential causal associations. Results The FI exhibited a nonlinear, accelerated increase across the older adulthood, whereas the epigenetic clocks mostly increased linearly with age. For PCHorvathAge, PCHannumAge, PCPhenoAge, and PCGrimAge, their associations with the FI were primarily due to correlated levels at age 50 but with no evidence of a dynamic longitudinal association. In contrast, we observed a unidirectional association between DunedinPACE and the FI, where a higher DunedinPACE predicted a subsequent increase in the FI, but not vice versa. Conclusions Our results highlight a temporal order between epigenetic aging and frailty such that changes in DunedinPACE precede changes in the FI. This potentially suggests that the pace of aging clock can be used as an early marker of the overall physiological decline at system level. [ABSTRACT FROM AUTHOR]

The causative mechanisms underlying the genetic relationships of neurodegenerative diseases with epigenetic aging and human longevity remain obscure. We aimed to detect causal associations and shared genetic etiology of neurodegenerative diseases with epigenetic aging and human longevity. We obtained large‐scale genome‐wide association study summary statistics data for four measures of epigenetic age (GrimAge, PhenoAge, IEAA, and HannumAge) (N = 34,710), multivariate longevity (healthspan, lifespan, and exceptional longevity) (N = 1,349,462), and for multiple neurodegenerative diseases (N = 6618–482,730), including Lewy body dementia, Alzheimer's disease (AD), Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis. Main analyses were conducted using multiplicative random effects inverse‐variance weighted Mendelian randomization (MR), and conditional/conjunctional false discovery rate (cond/conjFDR) approach. Shared genomic loci were functionally characterized to gain biological understanding. Evidence showed that AD patients had 0.309 year less in exceptional longevity (IVW beta = −0.309, 95% CI: −0.38 to −0.24, p = 1.51E‐19). We also observed suggestively significant causal evidence between AD and GrimAge age acceleration (IVW beta = −0.10, 95% CI: −0.188 to −0.013, p = 0.02). Following the discovery of polygenic overlap, we identified rs78143120 as shared genomic locus between AD and GrimAge age acceleration, and rs12691088 between AD and exceptional longevity. Among these loci, rs78143120 was novel for AD. In conclusion, we observed that only AD had causal effects on epigenetic aging and human longevity, while other neurodegenerative diseases did not. The genetic overlap between them, with mixed effect directions, suggested complex shared genetic etiology and molecular mechanisms. [ABSTRACT FROM AUTHOR]

Background: Gestational age (GEAA) estimated by newborn DNA methylation (GAmAge) is associated with maternal prenatal exposures and immediate birth outcomes. However, the association of GAmAge with long-term overweight or obesity (OWO) trajectories is yet to be determined. Methods: GAmAge was calculated for 831 children from a US predominantly urban, low-income, multi-ethnic birth cohort based on cord blood DNA methylation profile using Illumina EPIC array. Repeated anthropometric measurements aligned with pediatric primary care schedule allowed us to calculate body-mass-index percentiles (BMIPCT) at specific age and to define long-term weight trajectories from birth to 18 years. Results: GAmAge was associated with BMIPCT trajectories, defined by 4 groups: stable (consistent OWO: "early OWO"; constant normal weight: "NW") or non-stable (OWO by year 1 of follow-up: "late OWO"; OWO by year 6 of follow-up: "NW to very late OWO"). GAmAge differentiated between the group with consistently normal BMIPCT pattern and the non-stable groups with late and very late OWO development. Such differentiation was observed in the age periods of birth to 1year, 3years, 6years, 10years, and 14years (p < 0.05 for all). The findings persisted after adjusting for GEAA, maternal smoking, delivery method, and child's sex in multivariate models. Birth weight was a mediator for the GAmAge effect on OWO status for specific groups at multiple age periods. Conclusions: GAmAge is associated with BMIPCT trajectories from birth to age 18 years, independent of GEAA and birth weight. If further confirmed, GAmAge may serve as an early biomarker for predicting BMI trajectory to inform early risk assessment and prevention of OWO. Trial registration: ClinicalTrials.gov (NCT03228875). [ABSTRACT FROM AUTHOR]

Degenerative diseases oftentimes occur within the continuous process of aging, and the corresponding clinical manifestations may be neurodegeneration, neoplastic diseases, or various human complex diseases. DNA methylation provides the opportunity to explore aging and degenerative diseases as epigenetic traits. It has already been applied to age prediction and disease diagnosis. It has been shown that various degenerative diseases share co-physiology mechanisms with each other, clues of which may be gained from studying the aging process. Here, we endeavor to predict the risk of degenerative diseases in an aging-relevant comorbid mechanism perspective. Firstly, an epigenetic clock method was implemented based on a multi-scale convolutional neural network, and a Shapley feature attribution analysis was applied to discover the aging-related CpG sites. Then, these sites were further screened to a smaller subset composed of 196 sites by using biomics analysis according to their biological functions and mechanisms. Finally, we constructed a multilayer perceptron (MLP)-based degenerative disease risk prediction model, Mlp-DDR, which was well trained and tested to accurately classify nine degenerative diseases. Recent studies also suggest that DNA methylation plays a significant role in conditions like osteoporosis and osteoarthritis, broadening the potential applications of our model. This approach significantly advances the ability to understand degenerative diseases and represents a substantial shift from traditional diagnostic methods. Despite the promising results, limitations regarding model complexity and dataset diversity suggest directions for future research, including the development of tissue-specific epigenetic clocks and the inclusion of a wider range of diseases. [ABSTRACT FROM AUTHOR]

We examined whether prenatal exposure to two classes of endocrine-disrupting chemicals (EDCs) was associated with infant epigenetic age acceleration (EAA), a DNA methylation biomarker of aging. Participants included 224 maternal–infant pairs from a Canadian pregnancy cohort study. Two bisphenols and 12 phthalate metabolites were measured in maternal second trimester urines. Buccal epithelial cell cheek swabs were collected from 3 month old infants and DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The Pediatric-Buccal-Epigenetic tool was used to estimate EAA. Sex-stratified robust regressions examined individual chemical associations with EAA, and Bayesian kernel machine regression (BKMR) examined chemical mixture effects. Adjusted robust models showed that in female infants, prenatal exposure to total bisphenol A (BPA) was positively associated with EAA (B = 0.72, 95% CI: 0.21, 1.24), and multiple phthalate metabolites were inversely associated with EAA (Bs from −0.36 to −0.66, 95% CIs from −1.28 to −0.02). BKMR showed that prenatal BPA was the most important chemical in the mixture and was positively associated with EAA in both sexes. No overall chemical mixture effects or male-specific associations were noted. These findings indicate that prenatal EDC exposures are associated with sex-specific deviations in biological aging, which may have lasting implications for child health and development. [ABSTRACT FROM AUTHOR]

Age-associated changes in DNA methylation have been characterized across various animals, but not yet in amphibians, which are of particular interest because they include widely studied model organisms. In this study, we present clear evidence that the aquatic vertebrate species Xenopus tropicalis displays patterns of age-associated changes in DNA methylation. We have generated whole-genome bisulfite sequencing (WGBS) profiles from skin samples of nine frogs representing young, mature, and old adults and characterized the gene- and chromosome-scale DNA methylation changes with age. Many of the methylation features and changes we observe are consistent with what is known in mammalian species, suggesting that the mechanism of age-related changes is conserved. Moreover, we selected a few thousand age-associated CpG sites to build an assay based on targeted DNA methylation analysis (TBSseq) to expand our findings in future studies involving larger cohorts of individuals. Preliminary results of a pilot TBSeq experiment recapitulate the findings obtained with WGBS setting the basis for the development of an epigenetic clock assay. The results of this study will allow us to leverage the unique resources available for Xenopus to study how DNA methylation relates to other hallmarks of ageing.

Abstract Age data are essential for estimating life history parameters and are thus critical for population assessment, management, and conservation. Traditional vertebrae-based age estimation in elasmobranchs can be costly, time intensive, of low accuracy, and is by necessity lethal. Herein, epigenetic clocks were developed for an elasmobranch, the cownose ray (Rhinoptera bonasus), using aquarium-born individuals (n = 42) with known dates of birth (age range: 7−7,878 days or 0−21 years) and two tissue types (fin clips and whole blood) that can be sampled in a relatively non-invasive manner. Enzymatically-converted restriction site-associated DNA sequencing (ECrad-seq) was used to identify CpG sites that exhibited age-correlated DNA methylation. The epigenetic clocks developed were highly accurate (mean absolute error, MAE, < 0.75 years) and precise (R 2 > 0.98). Age-associated CpG sites were identified across tissues, and a multi-tissue clock was also highly accurate (MAE 22 years were predicted to be 22.10−23.49 years old. Overall, the results have important implications for future epigenetic clock development and noninvasive age estimation in elasmobranchs.

Abstract Background Biological age, especially epigenetic age derived from the epigenetic clock, is a significant measure of aging, considering the differences in aging rates among individuals. The epigenetic clock, a machine learning-based algorithm, uses DNA methylation states to estimate biological age. Previous studies have reported inconsistent associations between physical activity (PA) and the epigenetic clock, especially second-generation clocks such as PhenoAge and GrimAge. This study aimed to clarify this relationship using cross-sectional data from Japanese participants aged 40–69. Methods We used two datasets from the Saga J-MICC study, of which 867 samples were available for analysis. DNA methylation data from peripheral blood samples were used to calculate the epigenetic age using the epigenetic clocks PhenoAge and GrimAge. PA and sedentary time were measured using a single-axis accelerometer, while self-reported PA, sedentary time, and covariates were assessed using a self-administered questionnaire. The association between PA or sedentary time and epigenetic age acceleration was assessed using multiple linear regression. Results Pearson's correlation coefficients between accelerometer-based and self-reported PA variables ranged from 0.09 to 0.20. Multivariable regression analysis showed that accelerometer-based PA and sedentary time were associated with epigenetic age decelerations and accelerations, respectively. However, self-reported PA was not associated with the epigenetic age accelerations. Conclusions These results indicate that reducing sedentary time and increasing PA were associated with slowing both PhenoAge and GrimAge, even in East Asian populations with different exercise habits, body shapes, and lifestyles. This study highlights the potential of objective second-generation epigenetic age acceleration as an outcome index for healthcare interventions and clinical applications.

Abstract Background Epigenetic clocks are mathematical models used to estimate epigenetic age based on DNA methylation at specific CpG sites. As new methylation microarrays are developed and older models discontinued, existing epigenetic clocks might become obsolete. Here, we explored the effects of the changes introduced in the new EPICv2 DNA methylation array on existing epigenetic clocks. Methods We tested the performance of four epigenetic clocks on the probeset of the EPICv2 array using a dataset of 10,835 samples. We developed a new epigenetic age prediction model compatible across the 450 k, EPICv1, and EPICv2 microarrays and validated it on 2095 samples. We estimated technical noise and intra-subject variation using two datasets with repeated sampling. We used data from (i) cancer survivors who had undergone different therapies, (ii) breast cancer patients and controls, and (iii) an exercise-based interventional study, to test the ability of our model to detect alterations in epigenetic age acceleration in response to theoretically antiaging interventions. Results The results of the four epiclocks tested are significantly distorted by the EPICv2 probeset, causing an average difference of up to 25 years. Our new model produced highly accurate chronological age predictions, comparable to a state-of-the-art epiclock. The model reported the lowest epigenetic age acceleration in normal populations, as well as the lowest variation across technical replicates and repeated samples from the same subjects. Finally, our model reproduced previous results of increased epigenetic age acceleration in cancer patients and in survivors treated with radiation therapy, and no changes from exercise-based interventions. Conclusion Existing epigenetic clocks require updates for full EPICv2 compatibility. Our new model translates the capabilities of state-of-the-art epigenetic clocks to the EPICv2 platform and is cross-compatible with older microarrays. The characterization of epigenetic age prediction variation provides useful metrics to contextualize the relevance of epigenetic age alterations. The analysis of data from subjects influenced by radiation, cancer, and exercise-based interventions shows that despite being good predictors of chronological age, neither a pathological state like breast cancer, a hazardous environmental factor (radiation), nor exercise (a beneficial intervention) caused significant changes in the values of the “epigenetic age” determined by these first-generation models.

Abstract Background Gestational age (GEAA) estimated by newborn DNA methylation (GAmAge) is associated with maternal prenatal exposures and immediate birth outcomes. However, the association of GAmAge with long-term overweight or obesity (OWO) trajectories is yet to be determined. Methods GAmAge was calculated for 831 children from a US predominantly urban, low-income, multi-ethnic birth cohort based on cord blood DNA methylation profile using Illumina EPIC array. Repeated anthropometric measurements aligned with pediatric primary care schedule allowed us to calculate body-mass-index percentiles (BMIPCT) at specific age and to define long-term weight trajectories from birth to 18 years. Results GAmAge was associated with BMIPCT trajectories, defined by 4 groups: stable (consistent OWO: “early OWO”; constant normal weight: “NW”) or non-stable (OWO by year 1 of follow-up: “late OWO”; OWO by year 6 of follow-up: “NW to very late OWO”). GAmAge differentiated between the group with consistently normal BMIPCT pattern and the non-stable groups with late and very late OWO development. Such differentiation was observed in the age periods of birth to 1year, 3years, 6years, 10years, and 14years (p

BACKGROUND: Epigenetic clocks are promising tools for assessing biological age. We assessed the accuracy of pediatric epigenetic clocks in gestational and chronological age determination. RESULTS: Our study used data from seven tissue types on three DNA methylation profiling microarrays and found that the Knight and Bohlin clocks performed similarly for blood cells, while the Lee clock was superior for placental samples. The pediatric-buccal-epigenetic clock performed the best for pediatric buccal samples, while the Horvath clock is recommended for childrens blood cell samples. The NeoAge clock stands out for its unique ability to predict post-menstrual age with high correlation with the observed age in infant buccal cell samples. CONCLUSIONS: Our findings provide valuable guidance for future research and development of epigenetic clocks in pediatric samples, enabling more accurate assessments of biological age.

BACKGROUND: Cancer and its treatments may accelerate aging in survivors; however, research has not examined epigenetic markers of aging in longer term breast cancer survivors. This study examined whether older breast cancer survivors showed greater epigenetic aging than noncancer controls and whether epigenetic aging related to functional outcomes. METHODS: Nonmetastatic breast cancer survivors (n = 89) enrolled prior to systemic therapy and frequency-matched controls (n = 101) ages 62 to 84 years provided two blood samples to derive epigenetic aging measures (Horvath, Extrinsic Epigenetic Age [EEA], PhenoAge, GrimAge, Dunedin Pace of Aging) and completed cognitive (Functional Assessment of Cancer Therapy-Cognitive Function) and physical (Medical Outcomes Study Short Form-12) function assessments at approximately 24 to 36 and 60 months after enrollment. Mixed-effects models tested survivor-control differences in epigenetic aging, adjusting for age and comorbidities; models for functional outcomes also adjusted for racial group, site, and cognitive reserve. RESULTS: Survivors were 1.04 to 2.22 years biologically older than controls on Horvath, EEA, GrimAge, and DunedinPACE measures (p = .001-.04) at approximately 24 to 36 months after enrollment. Survivors exposed to chemotherapy were 1.97 to 2.71 years older (p = .001-.04), and among this group, an older EEA related to worse self-reported cognition (p = .047) relative to controls. An older epigenetic age related to worse physical function in all women (p

Abstract Background The epigenetic status of patients 6-month post-COVID-19 infection remains largely unexplored. The existence of long-COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), suggests potential long-term changes. Long-COVID includes symptoms like fatigue, neurological issues, and organ-related problems, regardless of initial infection severity. The mechanisms behind long-COVID are unclear, but virus-induced epigenetic changes could play a role. Methods and results Our study explores the lasting epigenetic impacts of SARS-CoV-2 infection. We analyzed genome-wide DNA methylation patterns in an Italian cohort of 96 patients 6 months after COVID-19 exposure, comparing them to 191 healthy controls. We identified 42 CpG sites with significant methylation differences (FDR

Abstract Background Gestational DNA methylation age (GAmAge) has been developed and validated in European ancestry samples. Its applicability to other ethnicities and associations with fetal stress and newborn phenotypes such as inflammation markers are still to be determined. This study aims to examine the applicability of GAmAge developed from cord blood samples of European decedents to a racially diverse birth cohort, and associations with newborn phenotypes. Methods GAmAge based on 176 CpGs (Haftorn GAmAge) was calculated for 940 children from a US predominantly urban, low-income, multiethnic birth cohort. Cord blood DNA methylation was profiled by Illumina EPIC array. Newborn phenotypes included anthropometric measurements and, for a subset of newborns (N = 194), twenty-seven cord blood inflammatory markers (sandwich immunoassays). Results GAmAge had a stronger correlation with GEAA in boys (r = 0.89, 95% confidence interval (CI) [0.87,0.91]) compared with girls (r = 0.83, 95% CI [0.80,0.86]), and was stronger among extremely preterm to very preterm babies (r = 0.91, 95% CI [0.81,0.96]), compared with moderate (r = 0.48, 95% CI [0.34,0.60]) and term babies (r = 0.58, 95% CI [0.53,0.63]). Among White newborns (N = 51), the correlation between GAmAge vs. GEAA was slightly stronger (r = 0.89, 95% CI [0.82,0.94]) compared with Black/African American newborns (N = 668; r = 0.87, 95% CI [0.85,0.89]) or Hispanic (N = 221; r = 0.79, 95% CI [0.74,0.84]). Adjusting for GEAA and sex, GAmAge was associated with anthropometric measurements, cord blood brain-derived neurotrophic factor (BDNF), and monocyte chemoattractant protein-1 (MCP-1) (p

Abstract Background Age-related eye diseases (AREDs) have become increasingly prevalent with the aging population, serving as the leading causes of visual impairment worldwide. Epigenetic clocks are generated based on DNA methylation (DNAm) levels and are considered one of the most promising predictors of biological age. This study aimed to investigate the bidirectional causal association between epigenetic clocks and common AREDs or glaucoma endophenotypes. Methods Instrumental variables for epigenetic clocks, AREDs, and glaucoma endophenotypes were obtained from corresponding genome-wide association study data of European descent. Bidirectional two-sample Mendelian randomization (MR) was employed to explore the causal relationship between epigenetic clocks and AREDs or glaucoma endophenotypes. Multivariable MR (MVMR) was used to determine whether glaucoma endophenotypes mediated the association of epigenetic clocks with glaucoma. Multiple sensitivity analyses were conducted to confirm the robustness of MR estimates. Results The results showed that an increased intrinsic epigenetic age acceleration (HorvathAge) was significantly associated with an increased risk of primary open-angle glaucoma (OR = 1.04, 95% CI 1.02 to 1.06, P = 6.1E−04). The epigenetic age acceleration (EEA) of HannumAge was related to a decreased risk of primary angle-closure glaucoma (OR = 0.92, 95% CI 0.86 to 0.99, P = 0.035). Reverse MR analysis showed that age-related cataract was linked to decreased HannumAge (β = −0.190 year, 95% CI −0.374 to −0.008, P = 0.041). The EEA of HannumAge (β = −0.85 μm, 95% CI −1.57 to −0.14, P = 0.019) and HorvathAge (β = −0.63 μm, 95% CI −1.18 to −0.08, P = 0.024) were associated with decreased central corneal thickness (CCT). PhenoAge was related to an increased retinal nerve fiber layer thickness (β = 0.06 μm, 95% CI 0.01 to 0.11, P = 0.027). MVMR analysis found no mediation effect of CCT in the association of HannumAge and HorvathAge with glaucoma. DNAm-based granulocyte proportions were significantly associated with presbyopia, rhegmatogenous retinal detachment, and intraocular pressure (P

Abstract The quality of romantic relationships can predict health consequences related to aging. DNA methylation-based biomarkers of aging accurately estimate chronological age. We developed several highly accurate epigenetic aging clocks, based on highly conserved mammalian CpGs, for the socially monogamous prairie vole (Microtus ochrogaster). In addition, our dual-species human-vole clock accurately measured relative age and illustrates high species conservation of epigenetic aging effects. Next, we assessed how pair bonding impacts epigenetic aging. We did not find evidence that pair-bonded voles exhibit accelerated or decelerated epigenetic aging effects in blood, ear, liver, or brain tissue. Our epigenome wide association study identified CpGs in five genes strongly associated with pair bonding: Foxp4, Phf2, Mms22l, Foxb1, and Eif1ad. Overall, we present accurate DNA methylation-based estimators of age for a species of great interest to researchers studying monogamy in animals. We did not find any evidence that sex-naive animals age differently from pair-bonded animals.

Abstract Introduction Walking stands as the most prevalent physical activity in the daily lives of individuals and is closely associated with physical functioning and the aging process. Nonetheless, the precise cause-and-effect connection between walking and aging remains unexplored. The epigenetic clock emerges as the most promising biological indicator of aging, capable of mirroring the biological age of the human body and facilitating an investigation into the association between walking and aging. Our primary objective is to investigate the causal impact of walking with epigenetic age acceleration (EAA). Methods We conducted a two-sample two-way Mendelian randomization (MR) study to investigate the causal relationship between walking and EAA. Walking and Leisure sedentary behavior data were sourced from UK Biobank, while EAA data were gathered from a total of 28 cohorts. The MR analysis was carried out using several methods, including the inverse variance weighted (IVW), weighted median, MR-Egger, and robust adjusted profile score (RAPS). To ensure the robustness of our findings, we conducted sensitivity analyses, which involved the MR-Egger intercept test, Cochran’s Q test, and MR-PRESSO, to account for and mitigate potential pleiotropy. Results The IVW MR results indicate a significant impact of usual walking pace on GrimAge (BETA = − 1.84, 95% CI (− 2.94, − 0.75)), PhenoAge (BETA = − 1.57, 95% CI (− 3.05, − 0.08)), Horvath (BETA = − 1.09 (− 2.14, − 0.04)), and Hannum (BETA = − 1.63, 95% CI (− 2.70, − 0.56)). Usual walking pace is significantly associated with a delay in epigenetic aging acceleration (EAA) (P 0.05). Conclusion Our evidence demonstrates that a higher usual walking pace is associated with a deceleration of the acceleration of all four classical epigenetic clocks acceleration.

Abstract Background Epigenetic clocks were known as promising biomarkers of aging, including original clocks trained by individual CpG sites and principal component (PC) clocks trained by PCs of CpG sites. The effects of genetic and environmental factors on epigenetic clocks are still unclear, especially for PC clocks. Methods We constructed univariate twin models in 477 same-sex twin pairs from the Chinese National Twin Registry (CNTR) to estimate the heritability of five epigenetic clocks (GrimAge, PhenoAge, DunedinPACE, PCGrimAge, and PCPhenoAge). Besides, we investigated the longitudinal changes of genetic and environmental influences on epigenetic clocks across 5 years in 134 same-sex twin pairs. Results Heritability of epigenetic clocks ranged from 0.45 to 0.70, and those for PC clocks were higher than those for original clocks. For five epigenetic clocks, the longitudinal stability was moderate to high and was largely due to genetic effects. The genetic correlations between baseline and follow-up epigenetic clocks were moderate to high. Special unique environmental factors emerged both at baseline and at follow-up. PC clocks showed higher longitudinal stability and unique environmental correlations than original clocks. Conclusions For five epigenetic clocks, they have the potential to identify aging interventions. High longitudinal stability is mainly due to genetic factors, and changes of epigenetic clocks over time are primarily due to changes in unique environmental factors. Given the disparities in genetic and environmental factors as well as longitudinal stability between PC and original clocks, the results of studies with original clocks need to be further verified with PC clocks.

The biological age of an individual depends mainly on the genetic status and different epigenetic influences experienced by the individual and it has a direct relationship with aging and suffering from different diseases. It can be understood from the observable physiological parameters like the level of specific health indicators in the body, status of vision and hearing, condition of joints, immunity, nutritional status, presence of inflammatory markers and certain proteins in the blood, etc. Determining factors of biological age include the level of oxidative stress, glycation pattern of the DNA, protein, and lipid; different epigenetic factors, etc. The main genetic biomarkers of biological aging are the length of the telomeres, DNA methylation pattern, and the status of the epigenetic clock of an individual. The epigenetic and other related factors causing early aging and more susceptibility towards gene-related or unrelated diseases can be prevented and reversed by the exclusion of the detrimental practices from the lifestyle along with the inclusion of some positive factors. Lifestyle and nutrigenetics are the subjects engaged in the related study. The 'unique disease principle' describes diseases as an outcome of the disease reasons and environmental conditions (including health status) at the individual level. The microbiome profile and individual immunity status are given importance for the selection of ways to combat diseases in the Molecular Pathological Epidemiology (MPE). A specific diet plan, the DIP diet, is advocated along with following a designed lifestyle and getting assistance with some diseasespecific physical measures for combating lifestyle diseases. The succulent parts of the effective medicinal plants are recommended for their direct therapeutic use in unaltered conditions in the form of biocapsules prepared without the addition of any materials of synthetic origin along with following a designed lifestyle is another branch of research related to the topic.

Background: Gestational DNA methylation age (GAmAge) has been developed and validated in European ancestry samples. Its applicability to other ethnicities and associations with fetal stress and newborn phenotypes such as inflammation markers are still to be determined. This study aims to examine the applicability of GAmAge developed from cord blood samples of European decedents to a racially diverse birth cohort, and associations with newborn phenotypes. Methods: GAmAge based on 176 CpGs (Haftorn GAmAge) was calculated for 940 children from a US predominantly urban, low-income, multiethnic birth cohort. Cord blood DNA methylation was profiled by Illumina EPIC array. Newborn phenotypes included anthropometric measurements and, for a subset of newborns (N = 194), twenty-seven cord blood inflammatory markers (sandwich immunoassays). Results: GAmAge had a stronger correlation with GEAA in boys (r = 0.89, 95% confidence interval (CI) [0.87,0.91]) compared with girls (r = 0.83, 95% CI [0.80,0.86]), and was stronger among extremely preterm to very preterm babies (r = 0.91, 95% CI [0.81,0.96]), compared with moderate (r = 0.48, 95% CI [0.34,0.60]) and term babies (r = 0.58, 95% CI [0.53,0.63]). Among White newborns (N = 51), the correlation between GAmAge vs. GEAA was slightly stronger (r = 0.89, 95% CI [0.82,0.94]) compared with Black/African American newborns (N = 668; r = 0.87, 95% CI [0.85,0.89]) or Hispanic (N = 221; r = 0.79, 95% CI [0.74,0.84]). Adjusting for GEAA and sex, GAmAge was associated with anthropometric measurements, cord blood brain-derived neurotrophic factor (BDNF), and monocyte chemoattractant protein-1 (MCP-1) (p < 0.05 for all). Conclusions: GAmAge estimation is robust across different populations and racial/ethnic subgroups. GAmAge may be utilized as a proxy for GEAA and for assessing fetus development, indicated by inflammatory state and birth outcomes. [ABSTRACT FROM AUTHOR]

Background: The epigenetic status of patients 6-month post-COVID-19 infection remains largely unexplored. The existence of long-COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), suggests potential long-term changes. Long-COVID includes symptoms like fatigue, neurological issues, and organ-related problems, regardless of initial infection severity. The mechanisms behind long-COVID are unclear, but virus-induced epigenetic changes could play a role. Methods and results: Our study explores the lasting epigenetic impacts of SARS-CoV-2 infection. We analyzed genome-wide DNA methylation patterns in an Italian cohort of 96 patients 6 months after COVID-19 exposure, comparing them to 191 healthy controls. We identified 42 CpG sites with significant methylation differences (FDR < 0.05), primarily within CpG islands and gene promoters. Dysregulated genes highlighted potential links to glutamate/glutamine metabolism, which may be relevant to PASC symptoms. Key genes with potential significance to COVID-19 infection and long-term effects include GLUD1, ATP1A3, and ARRB2. Furthermore, Horvath's epigenetic clock showed a slight but significant age acceleration in post-COVID-19 patients. We also observed a substantial increase in stochastic epigenetic mutations (SEMs) in the post-COVID-19 group, implying potential epigenetic drift. SEM analysis identified 790 affected genes, indicating dysregulation in pathways related to insulin resistance, VEGF signaling, apoptosis, hypoxia response, T-cell activation, and endothelin signaling. Conclusions: Our study provides valuable insights into the epigenetic consequences of COVID-19. Results suggest possible associations with accelerated aging, epigenetic drift, and the disruption of critical biological pathways linked to insulin resistance, immune response, and vascular health. Understanding these epigenetic changes could be crucial for elucidating the complex mechanisms behind long-COVID and developing targeted therapeutic interventions. [ABSTRACT FROM AUTHOR]

Background: Age-related eye diseases (AREDs) have become increasingly prevalent with the aging population, serving as the leading causes of visual impairment worldwide. Epigenetic clocks are generated based on DNA methylation (DNAm) levels and are considered one of the most promising predictors of biological age. This study aimed to investigate the bidirectional causal association between epigenetic clocks and common AREDs or glaucoma endophenotypes. Methods: Instrumental variables for epigenetic clocks, AREDs, and glaucoma endophenotypes were obtained from corresponding genome-wide association study data of European descent. Bidirectional two-sample Mendelian randomization (MR) was employed to explore the causal relationship between epigenetic clocks and AREDs or glaucoma endophenotypes. Multivariable MR (MVMR) was used to determine whether glaucoma endophenotypes mediated the association of epigenetic clocks with glaucoma. Multiple sensitivity analyses were conducted to confirm the robustness of MR estimates. Results: The results showed that an increased intrinsic epigenetic age acceleration (HorvathAge) was significantly associated with an increased risk of primary open-angle glaucoma (OR = 1.04, 95% CI 1.02 to 1.06, P = 6.1E−04). The epigenetic age acceleration (EEA) of HannumAge was related to a decreased risk of primary angle-closure glaucoma (OR = 0.92, 95% CI 0.86 to 0.99, P = 0.035). Reverse MR analysis showed that age-related cataract was linked to decreased HannumAge (β = −0.190 year, 95% CI −0.374 to −0.008, P = 0.041). The EEA of HannumAge (β = −0.85 μm, 95% CI −1.57 to −0.14, P = 0.019) and HorvathAge (β = −0.63 μm, 95% CI −1.18 to −0.08, P = 0.024) were associated with decreased central corneal thickness (CCT). PhenoAge was related to an increased retinal nerve fiber layer thickness (β = 0.06 μm, 95% CI 0.01 to 0.11, P = 0.027). MVMR analysis found no mediation effect of CCT in the association of HannumAge and HorvathAge with glaucoma. DNAm-based granulocyte proportions were significantly associated with presbyopia, rhegmatogenous retinal detachment, and intraocular pressure (P < 0.05). DNAm-based plasminogen activator inhibitor-1 levels were significantly related to age-related macular degeneration and intraocular pressure (P < 0.05). Conclusion: The present study revealed a causal association between epigenetic clocks and AREDs. More research is warranted to clarify the potential mechanisms of the biological aging process in AREDs. [ABSTRACT FROM AUTHOR]

Biological age, reflecting the cumulative damage in the body over a lifespan, is a dynamic measure more indicative of individual health than chronological age. Accelerated aging, when biological age surpasses chronological age, is implicated in poorer clinical outcomes, especially for breast cancer (BC) survivors undergoing treatments. This preliminary study investigates the impact of a 16-week online supervised physical activity (PA) intervention on biological age in post-surgery female BC patients. Telomere length was measured using qPCR, and the ELOVL2-based epigenetic clock was assessed via DNA methylation pyrosequencing of the ELOVL2 promoter region. Telomere length remained unchanged, but the ELOVL2 epigenetic clock indicated a significant decrease in biological age in the PA group, suggesting the potential of PA interventions to reverse accelerated aging processes in BC survivors. The exercise group showed improved cardiovascular fitness, highlighting PA's health impact. Finally, the reduction in biological age, as measured by the ELOVL2 epigenetic clock, was significantly associated with improvements in cardiovascular fitness and handgrip strength, supporting improved recovery. Epigenetic clocks can potentially assess health status and recovery progress in BC patients, identifying at-risk individuals in clinical practice. This study provides potential and valuable insights into how PA benefits BC survivors' health, supporting the immediate benefits of a 16-week exercise intervention in mitigating accelerated aging. The findings could suggest a holistic approach to improving the health and recovery of post-surgery BC patients. [ABSTRACT FROM AUTHOR]

Polyploidy in hepatocytes has been proposed as a genetic mechanism to buffer against transcriptional dysregulation. Here, we aim to demonstrate the role of polyploidy in modulating gene regulatory networks in hepatocytes during ageing. We performed single-nucleus RNA sequencing in hepatocyte nuclei of different ploidy levels isolated from young and old wild-type mice. Changes in the gene expression and regulatory network were compared to three independent strains that were haploinsufficient for HNF4A, CEBPA or CTCF, representing non-deleterious perturbations. Phenotypic characteristics of the liver section were additionally evaluated histologically, whereas the genomic allele composition of hepatocytes was analysed by BaseScope. We observed that ageing in wild-type mice results in nuclei polyploidy and a marked increase in steatosis. Haploinsufficiency of liver-specific master regulators (HFN4A or CEBPA) results in the enrichment of hepatocytes with tetraploid nuclei at a young age, affecting the genomic regulatory network, and dramatically suppressing ageing-related steatosis tissue wide. Notably, these phenotypes are not the result of subtle disruption to liver-specific transcriptional networks, since haploinsufficiency in the CTCF insulator protein resulted in the same phenotype. Further quantification of genotypes of tetraploid hepatocytes in young and old HFN4A-haploinsufficient mice revealed that during ageing, tetraploid hepatocytes lead to the selection of wild-type alleles, restoring non-deleterious genetic perturbations. Our results suggest a model whereby polyploidisation leads to fundamentally different cell states. Polyploid conversion enables pleiotropic buffering against age-related decline via non-random allelic segregation to restore a wild-type genome. The functional role of hepatocyte polyploidisation during ageing is poorly understood. Using single-nucleus RNA sequencing and BaseScope approaches, we have studied ploidy dynamics during ageing in murine livers with non-deleterious genetic perturbations. We have identified that hepatocytes present different cellular states and the ability to buffer ageing-associated dysfunctions. Tetraploid nuclei exhibit robust transcriptional networks and are better adapted to genomically overcome perturbations. Novel therapeutic interventions aimed at attenuating age-related changes in tissue function could be exploited by manipulation of ploidy dynamics during chronic liver conditions. [Display omitted] • In hepatocytes, an increase in nuclear ploidy is a fundamental cellular state that preserves tissue function. • Tetraploid hepatocyte nuclei, carrying multiple copies of the genome, attenuate age-related transcriptomic changes. • Early accumulation of tetraploid nuclei in hepatocytes reduces age-related steatosis. • The impact of gene haploinsufficiency is modulated in tetraploid hepatocyte nuclei. • The protective phenotype from polyploidisation relies on non-random selection of wild-type alleles during ageing. [ABSTRACT FROM AUTHOR]

Healthcare workers (HCWs) are a high-risk group for hepatitis B virus (HBV) infection. Notably, about 5–10% of the general population does not respond to the HBV vaccination. In this study, we aimed to investigate DNA methylation (DNAm) in order to estimate the biological age of B cells from HCW of both sexes, either responder (R) or non-responder (NR), to HBV vaccination. We used genome-wide DNA methylation data to calculate a set of biomarkers in B cells collected from 41 Rs and 30 NRs between 22 and 62 years old. Unresponsiveness to HBV vaccination was associated with accelerated epigenetic aging (DNAmAge, AltumAge, DunedinPoAm) and was accompanied by epigenetic drift. Female non-responders had higher estimates of telomere length and lower CRP inflammation risk score when compared to responders. Overall, epigenetic differences between responders and non-responders were more evident in females than males. In this study we demonstrated that several methylation DNAm-based clocks and biomarkers are associated with an increased risk of non-response to HBV vaccination, particularly in females. Based on these results, we propose that accelerated epigenetic age could contribute to vaccine unresponsiveness. These insights may help improve the evaluation of the effectiveness of vaccination strategies, especially among HCWs and vulnerable patients. [ABSTRACT FROM AUTHOR]

The quality of romantic relationships can predict health consequences related to aging. DNA methylation-based biomarkers of aging accurately estimate chronological age. We developed several highly accurate epigenetic aging clocks, based on highly conserved mammalian CpGs, for the socially monogamous prairie vole (Microtus ochrogaster). In addition, our dual-species human-vole clock accurately measured relative age and illustrates high species conservation of epigenetic aging effects. Next, we assessed how pair bonding impacts epigenetic aging. We did not find evidence that pair-bonded voles exhibit accelerated or decelerated epigenetic aging effects in blood, ear, liver, or brain tissue. Our epigenome wide association study identified CpGs in five genes strongly associated with pair bonding: Foxp4, Phf2, Mms22l, Foxb1, and Eif1ad. Overall, we present accurate DNA methylation-based estimators of age for a species of great interest to researchers studying monogamy in animals. We did not find any evidence that sex-naive animals age differently from pair-bonded animals. [ABSTRACT FROM AUTHOR]

The existence of a shared genetic basis for mental disorders has long been documented, yet research on whether acquired epigenetic modifications exhibit common alterations across diseases is limited. Previous studies have found that abnormal methylation of cg14631053 at the SSTR4 promoter region mediates the onset of alcohol use disorder. However, whether aberrant methylation of the SSTR4 gene promoter is involved in other mental health disorders remains unclear. In this study, leveraging publicly available data, we identified that changes in methylation of cg14631053 from the SSTR4 promoter region are involved in the development of bipolar disorder and schizophrenia. Furthermore, the direction of methylation changes in the SSTR4 promoter region is diseasespecific: hypomethylation is associated with the onset of bipolar disorder and schizophrenia, rather than major depressive disorder. Methylation levels of cg14631053 correlate with chronological age, a correlation that can be disrupted in patients with mental health disorders including schizophrenia and bipolar disorder. In conclusion, SSTR4 promoter methylation may serve as a marker for identifying bipolar disorder and schizophrenia, providing insights into a transdiagnostic mechanism for precision medicine in the future. [ABSTRACT FROM AUTHOR]

Introduction: Walking stands as the most prevalent physical activity in the daily lives of individuals and is closely associated with physical functioning and the aging process. Nonetheless, the precise cause-and-effect connection between walking and aging remains unexplored. The epigenetic clock emerges as the most promising biological indicator of aging, capable of mirroring the biological age of the human body and facilitating an investigation into the association between walking and aging. Our primary objective is to investigate the causal impact of walking with epigenetic age acceleration (EAA). Methods: We conducted a two-sample two-way Mendelian randomization (MR) study to investigate the causal relationship between walking and EAA. Walking and Leisure sedentary behavior data were sourced from UK Biobank, while EAA data were gathered from a total of 28 cohorts. The MR analysis was carried out using several methods, including the inverse variance weighted (IVW), weighted median, MR-Egger, and robust adjusted profile score (RAPS). To ensure the robustness of our findings, we conducted sensitivity analyses, which involved the MR-Egger intercept test, Cochran's Q test, and MR-PRESSO, to account for and mitigate potential pleiotropy. Results: The IVW MR results indicate a significant impact of usual walking pace on GrimAge (BETA = − 1.84, 95% CI (− 2.94, − 0.75)), PhenoAge (BETA = − 1.57, 95% CI (− 3.05, − 0.08)), Horvath (BETA = − 1.09 (− 2.14, − 0.04)), and Hannum (BETA = − 1.63, 95% CI (− 2.70, − 0.56)). Usual walking pace is significantly associated with a delay in epigenetic aging acceleration (EAA) (P < 0.05). Moreover, the direction of effect predicted by the gene remained consistent across RAPS outcomes and sensitivity MR analyses. There is a lack of robust causal relationships between other walking conditions, such as walking duration and walking frequency, on EAA (P > 0.05). Conclusion: Our evidence demonstrates that a higher usual walking pace is associated with a deceleration of the acceleration of all four classical epigenetic clocks acceleration. Key messages: In recent years, observational studies have found that there is a correlation between walking and aging, but the specific relationship is not clear We used a Mendelian randomization approach to test the causal effect of walking and sedentarism on epigenetic clock acceleration Mendelian randomization studies have found that faster walking speed may delay physiological aging through causal analysis at the genetic level [ABSTRACT FROM AUTHOR]

Background: Epigenetic clocks were known as promising biomarkers of aging, including original clocks trained by individual CpG sites and principal component (PC) clocks trained by PCs of CpG sites. The effects of genetic and environmental factors on epigenetic clocks are still unclear, especially for PC clocks. Methods: We constructed univariate twin models in 477 same-sex twin pairs from the Chinese National Twin Registry (CNTR) to estimate the heritability of five epigenetic clocks (GrimAge, PhenoAge, DunedinPACE, PCGrimAge, and PCPhenoAge). Besides, we investigated the longitudinal changes of genetic and environmental influences on epigenetic clocks across 5 years in 134 same-sex twin pairs. Results: Heritability of epigenetic clocks ranged from 0.45 to 0.70, and those for PC clocks were higher than those for original clocks. For five epigenetic clocks, the longitudinal stability was moderate to high and was largely due to genetic effects. The genetic correlations between baseline and follow-up epigenetic clocks were moderate to high. Special unique environmental factors emerged both at baseline and at follow-up. PC clocks showed higher longitudinal stability and unique environmental correlations than original clocks. Conclusions: For five epigenetic clocks, they have the potential to identify aging interventions. High longitudinal stability is mainly due to genetic factors, and changes of epigenetic clocks over time are primarily due to changes in unique environmental factors. Given the disparities in genetic and environmental factors as well as longitudinal stability between PC and original clocks, the results of studies with original clocks need to be further verified with PC clocks. [ABSTRACT FROM AUTHOR]

Epigenetic clocks based on DNA methylation have been known as biomarkers of aging, including principal component (PC) clocks representing the degree of aging and DunedinPACE representing the pace of aging. Prior studies have shown the associations between epigenetic aging and T2DM, but the results vary by epigenetic age metrics and people. This study explored the associations between epigenetic age metrics and T2DM or glycemic traits, based on 1070 twins (535 twin pairs) from the Chinese National Twin Registry. It also explored the temporal relationships of epigenetic age metrics and glycemic traits in 314 twins (157 twin pairs) who participated in baseline and follow‐up visits after a mean of 4.6 years. DNA methylation data were used to calculate epigenetic age metrics, including PCGrimAge acceleration (PCGrimAA), PCPhenoAge acceleration (PCPhenoAA), DunedinPACE, and the longitudinal change rate of PCGrimAge/PCPhenoAge. Mixed‐effects and cross‐lagged modelling assessed the cross‐sectional and temporal relationships between epigenetic age metrics and T2DM or glycemic traits, respectively. In the cross‐sectional analysis, positive associations were identified between DunedinPACE and glycemic traits, as well as between PCPhenoAA and fasting plasma glucose, which may be not confounded by shared genetic factors. Cross‐lagged models revealed that glycemic traits (fasting plasma glucose, HbA1c, and TyG index) preceded DunedinPACE increases, and TyG index preceded PCGrimAA increases. Glycemic traits are positively associated with epigenetic age metrics, especially DunedinPACE. Glycemic traits preceded the increases in DunedinPACE and PCGrimAA. Lowering the levels of glycemic traits may reduce DunedinPACE and PCGrimAA, thereby mitigating age‐related comorbidities. [ABSTRACT FROM AUTHOR]

Simple Summary: Bladder cancer, an age-related disorder, primarily affects individuals aged 65 and older. Accelerated biological aging, which is linked to increased cancer susceptibility, raises questions about its association with bladder cancer risk. We evaluated four widely recognized epigenetic clocks—HannumAge, HorvathAge, GrimAge, and PhenoAge—for their relationship with bladder cancer risk in a large case–control study. By leveraging genome-wide-association study (GWAS) data and constructing weighted genetic risk scores (GRS), we found that higher HannumAge and HorvathAge GRS were significantly associated with increased bladder cancer risk (OR = 1.69, 95% CI: 1.44–1.98, p = 1.56 × 10−10 and OR = 1.09, 95% CI: 1.00–1.19, p = 0.04, respectively). Mendelian randomization (MR) analysis using inverse-variance weighting (IVW) confirmed these associations, which was also supported by sensitivity analyses. However, GrimAge and PhenoAge showed no significant association with bladder cancer risks. Our findings highlighted the link between accelerated biological aging and elevated bladder cancer risk. Bladder cancer is an age-related disease, with over three-quarters of cases occurring in individuals aged 65 years and older. Accelerated biological aging has been linked to elevated cancer risks. Epigenetic clocks serve as excellent predictors of biological age, yet it remains unclear whether they are associated with bladder cancer risk. In this large case–control study, we assessed the associations between four well-established epigenetic clocks—HannumAge, HorvathAge, GrimAge, and PhenoAge—and bladder cancer risk. Utilizing single nucleotide polymorphisms (SNPs), which were identified in a genome-wide association study (GWAS), linked to these clocks as instruments, we constructed a weighted genetic risk score (GRS) for each clock. We discovered that higher HannumAge and HorvathAge GRS were significantly associated with increased bladder cancer risk (OR = 1.69 per SD increase, 95% CI, 1.44–1.98, p = 1.56 × 10−10 and OR = 1.09 per SD increase, 95% CI, 1.00–1.19, p = 0.04, respectively). Employing a summary statistics-based Mendelian randomization (MR) method, inverse-variance weighting (IVW), we found consistent risk estimates for bladder cancer with both HannumAge and HorvathAge. Sensitivity analyses using weighted median analysis and MR-Egger regression further supported the validity of the IVW method. However, GrimAge and PhenoAge were not associated with bladder cancer risk. In conclusion, our data provide the first evidence that accelerated biological aging is associated with elevated bladder cancer risk. [ABSTRACT FROM AUTHOR]

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

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. [ABSTRACT FROM AUTHOR]

Down syndrome (DS) is a segmental progeroid genetic disorder associated with multi-systemic precocious aging phenotypes, which are particularly evident in the immune and nervous systems. Accordingly, people with DS show an increased biological age as measured by epigenetic clocks. The Ts65Dn trisomic mouse, which harbors extra-numerary copies of chromosome 21 (Hsa21)- syntenic regions, was shown to recapitulate several progeroid features of DS, but no biomarkers of age have been applied to it so far. In this pilot study, we used a mouse-specific epigenetic clock to measure the epigenetic age of hippocampi from Ts65Dn and euploid mice at 20 weeks. Ts65Dn mice showed an increased epigenetic age in comparison with controls, and the observed changes in DNA methylation partially recapitulated those observed in hippocampi from people with DS. Collectively, our results support the use of the Ts65Dn model to decipher the molecular mechanisms underlying the progeroid DS phenotypes. [ABSTRACT FROM AUTHOR]

The biological age of an individual depends mainly on the genetic status and different epigenetic influences experienced by the individual and it has a direct relationship with aging and suffering from different diseases. It can be understood from the observable physiological parameters like the level of specific health indicators in the body, status of vision and hearing, condition of joints, immunity, nutritional status, presence of inflammatory markers and certain proteins in the blood, etc. Determining factors of biological age include the level of oxidative stress, glycation pattern of the DNA, protein, and lipid; different epigenetic factors, etc. The main genetic biomarkers of biological aging are the length of the telomeres, DNA methylation pattern, and the status of the epigenetic clock of an individual. The epigenetic and other related factors causing early aging and more susceptibility towards gene-related or unrelated diseases can be prevented and reversed by the exclusion of the detrimental practices from the lifestyle along with the inclusion of some positive factors. Lifestyle and nutrigenetics are the subjects engaged in the related study. The 'unique disease principle' describes diseases as an outcome of the disease reasons and environmental conditions (including health status) at the individual level. The microbiome profile and individual immunity status are given importance for the selection of ways to combat diseases in the Molecular Pathological Epidemiology (MPE). A specific diet plan, the DIP diet, is advocated along with following a designed lifestyle and getting assistance with some diseasespecific physical measures for combating lifestyle diseases. The succulent parts of the effective medicinal plants are recommended for their direct therapeutic use in unaltered conditions in the form of biocapsules prepared without the addition of any materials of synthetic origin along with following a designed lifestyle is another branch of research related to the topic. [ABSTRACT FROM AUTHOR]

We have previously shown accelerated ageing in adolescents perinatally infected with HIV (PHIV +), based on discrepancies between epigenetic and chronological age. The current study examines follow-up longitudinal patterns of epigenetic ageing and the association of epigenetic ageing with cognition as well as whole brain structure changes in PHIV + and healthy controls enrolled in the Cape Town Adolescent Antiretroviral Cohort Study (CTAAC). The Illumina EPIC array was used to generate blood DNA methylation data from 60 PHIV + adolescents and 36 age-matched controls aged 9-12 years old at baseline and again at a 36-month follow-up. Epigenetic clock software estimated two measures of epigenetic age acceleration: extrinsic epigenetic accelerated ageing (EEAA) and age acceleration difference (AAD) at both time points. At follow-up, each participant completed neuropsychological testing, structural magnetic resonance imaging, and diffusion tensor imaging. At follow-up, PHIV infection remains associated with increased EEAA and AAD. Accelerated epigenetic ageing remained positively associated with viral load and negatively associated with CD4 ratio. EEAA was positively associated with whole brain grey matter volume and alterations in whole brain white matter integrity. AAD and EEAA were not associated with cognitive function within the PHIV + group. Measures of epigenetic ageing, as detected in DNA methylation patterns, remain increased in PHIV + adolescents across a 36-month period. Associations between epigenetic ageing measures, viral biomarkers, and alterations in brain micro- and macrostructure also persist at 36-month follow-up. Further study should determine if epigenetic age acceleration is associated with cognitive functional changes due to brain alterations in later life.

Summary: Background: Amyotrophic lateral sclerosis (ALS) is linked to ageing and genetic and environmental risk factors, yet underlying mechanisms are incompletely understood. We aimed to evaluate epigenetic age acceleration (EAA), i.e., DNA methylation (DNAm) age acceleration, and its association with ALS case status and survival. Methods: In this study, we included 428 ALS and 288 control samples collected between 2011 and 2021. We calculated EAA using the GrimAge residual method from ALS and control blood samples and grouped participants with ALS into three ageing groups (fast, normal, slow). We associated EAA with ALS case status and survival, stratified by sex, and correlated it with environmental and biological factors through occupational exposure assessments, immune cell proportions, and transcriptome changes. Findings: Participants with ALS had higher average EAA by 1.80 ± 0.30 years (p

Mathematical algorithms known as “epigenetic clocks” use methylation values at a set of CpG sites to estimate the biological age of an individual in a tissue-specific manner. These clocks have demonstrated both acceleration and delays in epigenetic aging in multiple neuropsychiatric conditions, including schizophrenia and neurodevelopmental disorders such as autism spectrum disorder. However, no study to date has examined epigenetic aging in ADHD despite its status as one of the most prevalent neurodevelopmental conditions, with 1 in 9 children having ever received an ADHD diagnosis in the US. Only a handful of studies have examined epigenetic age in brain tissue from neurodevelopmental conditions, with none focused on ADHD, despite the obvious relevance to pathogenesis. Thus, here we asked if post-mortem brain tissue in those with lifetime histories of ADHD would show accelerated or delayed epigenetic age, as has been found for other neurodevelopmental conditions. We applied four different epigenetic clocks to estimate epigenetic age in individuals with ADHD and unaffected controls from cortical (anterior cingulate cortex, N = 55) and striatal (caudate, N = 56) post-mortem brain tissue, as well as peripheral blood (N = 84) and saliva (N = 112). After determining which epigenetic clock performed best in each tissue, we asked if ADHD was associated with altered biological aging in corticostriatal brain and peripheral tissues. We found that a range of epigenetic clocks accurately predicted chronological age in all tissues. We also found that a diagnosis of ADHD was not significantly associated with differential epigenetic aging, neither for the postmortem ACC or caudate, nor for peripheral tissues. These findings held when accounting for comorbid psychiatric diagnoses, substance use, and stimulant medication. Thus, in this study of epigenetic clocks in ADHD, we find no evidence of altered epigenetic aging in corticostriatal brain regions nor in peripheral tissue. We consider reasons for this unexpected finding, including the limited sampling of brain regions, the age range of individuals studied, and the possibility that processes that accelerate epigenetic age may be counteracted by the developmental delay posited in some models of ADHD.

Background: Along with the ageing of society, the absolute prevalence of age-related diseases is expected to rise, leading to a substantial burden on healthcare systems and society. Thus, there is an urgent need to promote healthy ageing. As opposed to chronological age, biological age was introduced to accurately represent the ageing process, as it considers physiological deterioration that is linked to morbidity and mortality risk. Furthermore, biological age responds to various factors, including nutritional factors, which have the potential to mitigate the risk of age-related diseases. As a result, a promising biomarker of biological age known as the epigenetic clock has emerged as a suitable measure to investigate the direct relations between nutritional factors and ageing, thereby identifying potential intervention targets to improve healthy ageing. Methods: In this study, we analysed data from 3,969 postmenopausal women from the Women's Health Initiative to identify nutrients that are associated with the rate of ageing by using an accurate measure of biological age called the PhenoAge epigenetic clock. We used Copula Graphical Models, a data-driven exploratory analysis tool, to identify direct relationships between nutrient intake and age-acceleration, while correcting for every variable in the dataset. Results: We revealed that increased dietary intakes of coumestrol, beta-carotene and arachidic acid were associated with decelerated epigenetic ageing. In contrast, increased intakes of added sugar, gondoic acid, behenic acid, arachidonic acid, vitamin A and ash were associated with accelerated epigenetic ageing in postmenopausal women. Conclusion: Our study discovered direct relations between nutrients and epigenetic ageing, revealing promising areas for follow-up studies to determine the magnitude and causality of our estimated diet-epigenetic relationships.