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Elevated plasma total homocysteine (tHcy) is associated with the development of Alzheimer's disease and other forms of dementia. In this study, we report the relationship between tHcy and epigenetic age in older adults with mild cognitive impairment from the VITACOG study. Epigenetic age and rate of aging (ROA) were assessed using various epigenetic clocks, including those developed by Horvath and Hannum, DNAmPhenoAge, and with a focus on Index, a new principal component‐based epigenetic clock that, like DNAmPhenoAge, is trained to predict an individual's "PhenoAge." We identified significant associations between tHcy levels and ROA, suggesting that hyperhomocysteinemic individuals were aging at a faster rate. Moreover, Index revealed a normalization of accelerated epigenetic aging in these individuals following treatment with tHcy‐lowering B‐vitamins. Our results indicate that elevated tHcy is a risk factor for accelerated epigenetic aging, and this can be ameliorated with B‐vitamins. These findings have broad relevance for the sizable proportion of the worldwide population with elevated tHcy. [ABSTRACT FROM AUTHOR]

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

ABSTRACT Objectives Material and Methods Results Conclusions Second to fourth digit ratio is widely known indicator of prenatal sex hormones proportion. Higher prenatal androgenization results in longer fourth finger and lower 2D:4D index. The aim of this study was to determine whether the 2D:4D digit ratio is associated with DNA methylation (DNAm) age dependently on sex.The study included 182 adults (106 females and 76 males) with a mean age of 51.5 ± 13 years. The investigation consisted of three main parts: a survey, anthropometric dimensions measurements (fingers length) and methylome analysis using collected blood samples. Genome‐wide methylation was analyzed using EPIC microarray technology. Epigenetic age and epigenetic age acceleration were calculated using several widely applied algorithms.Males with the female left hand pattern had more accelerated epigenetic age than those with the male pattern as calculated with PhenoAge and DNAmTL clocks.Finger female pattern 2D:4D above or equal to 1 in males is associated with epigenetic age acceleration, indicating that prenatal exposure to estrogens in males may be related to aging process in the later ontogenesis. [ABSTRACT FROM AUTHOR]

Early-life adversity increases the risk of health problems. Interventions supporting protective and responsive caregiving offer a promising approach to attenuating adversity-induced changes in stress-sensitive biomarkers. This study tested whether participation in an evidence-based dyadic psychosocial intervention, child-parent psychotherapy (CPP), was related to lower epigenetic age acceleration, a trauma-sensitive biomarker of accelerated biological aging that is associated with later health impairment, in a sample of children with trauma histories. Within this quasi-experimental, repeated-measures study, we examined epigenetic age acceleration at baseline and postintervention in a low-income sample of children receiving CPP treatment (n = 45; age range = 2-6 years; 76% Latino) compared with a weighted, propensity-matched community-comparison sample (n = 110; age range = 3-6 years; 40% Latino). Baseline epigenetic age acceleration was equivalent across groups. However, posttreatment, epigenetic age acceleration in the treatment group was lower than in the matched community sample. Findings highlight the potential for a dyadic psychosocial intervention to ameliorate accelerated biological aging in trauma-exposed children. [ABSTRACT FROM AUTHOR]

Psoriasis (PsO) is a chronic inflammatory skin condition, often accompanied by psoriatic arthritis (PsA) and linked to various comorbidities and increased mortality rates. This study aimed to explore the relationship between PsO and accelerated biological aging, specifically focusing on epigenetic DNA methylation clocks. Using a matched case-control design, 20 PsO cases were selected along with age, race, and sex-matched 20 controls without PsO from the Skin Disease Biorepository at Brown Dermatology, Inc, Providence, Rhode Island. Blood samples retrieved from both groups were analyzed for DNA methylation, and epigenetic ages were calculated using DNA methylation clocks, including Horvath, Hannum, Pheno, SkinBlood, and Grim ages. Generalized estimation equations were employed to test the differences in epigenetic and chronological ages between PsO cases and controls, as well as within various subgroups in comparison to their respective controls. There were no statistically significant differences in epigenetic ages between PsO cases and controls. However, notably, PsO cases with PsA demonstrated an accelerated PhenoAge, compared to their matched controls. This study represents a pioneering investigation into the potential link between PsO and epigenetic aging, shedding light on the possibility of accelerated epigenetic aging in PsA, possibly associated with heightened inflammatory burden. These findings emphasize the systemic impact of PsA on the aging process, prompting the need for deeper exploration into autoimmune pathways, inflammation, and epigenetic modifications underlying PsO pathogenesis and aging mechanisms. Larger-scale studies with diverse populations are imperative to discern PsO subgroups experiencing accelerated biological aging and decipher the intricate interplay between PsO, inflammation, and aging pathways. [ABSTRACT FROM AUTHOR]

Background Chronic pain has been associated with accelerated biological aging, which may be related to epigenetic alterations. We evaluated the association of high-impact pain (ie, pain that limits activities and function) with epigenetic aging, a measure of biological aging, in a nationally representative sample of middle-aged and older adults in the United States. Methods Cross-sectional analysis of adults 50 years of age and older from the 2016 Health and Retirement Study. Epigenetic aging was derived from 13 epigenetic clocks based on DNA methylation patterns that predict aging correlates of morbidity and mortality. Ordinary least squares regressions were performed to test for differences in the epigenetic clocks, adjusting for the complex survey design, as well as biological, social, and behavioral factors. Results The analysis consisted of 3 855 adults with mean age of 68.5 years, including 59.8% with no pain and 25.8% with high-impact pain. Consistent with its operational definition, high-impact pain was associated with greater functional and activity limitations. High-impact pain was associated with accelerated epigenetic aging compared to no pain, as measured via second (Zhang, PhenoAge, GrimAge) and third (DunedinPoAm) generation epigenetic clocks. Additionally, GrimAge was accelerated in high-impact pain as compared to low-impact pain. Conclusions High-impact pain is associated with accelerated epigenetic aging among middle-aged and older adults in the United States. These findings highlight aging-associated epigenetic alterations in high-impact chronic pain and suggest a potential for epigenetic therapeutic approaches for pain management and the preservation of physical function in older adults. [ABSTRACT FROM AUTHOR]

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

Abstract Hypertension is a disease associated with epigenetic aging. However, the pathogenic mechanism underlying this relationship remains unclear. We aimed to characterize the shared genetic architecture of hypertension and epigenetic aging, and identify novel risk loci. Leveraging genome-wide association studies (GWAS) summary statistics of hypertension (129,909 cases and 354,689 controls) and four epigenetic clocks (N = 34,710), we investigated genetic architectures and genetic overlap using bivariate casual mixture model and conditional/conjunctional false discovery rate methods. Functional gene-sets pathway analyses were performed by functional mapping and gene annotation (FUMA) protocol. Hypertension was polygenic with 2.8 K trait-influencing genetic variants. We observed cross-trait genetic enrichment and genetic overlap between hypertension and all four measures of epigenetic aging. Further, we identified 32 distinct genomic loci jointly associated with hypertension and epigenetic aging. Notably, rs1849209 was shared between hypertension and three epigenetic clocks (HannumAge, IEAA, and PhenoAge). The shared loci exhibited a combination of concordant and discordant allelic effects. Functional gene-set analyses revealed significant enrichment in biological pathways related to sensory perception of smell and nervous system processes. We observed genetic overlaps with mixed effect directions between hypertension and all four epigenetic aging measures, and identified 32 shared distinct loci with mixed effect directions, 25 of which were novel for hypertension. Shared genes enriched in biological pathways related to olfaction.

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

Epigenetic aging clocks are computational models that predict age using DNA methylation information. Initially, first-generation clocks were developed to make predictions using CpGs that change with age. Over time, next-generation clocks were created using CpGs that relate to both age and health. Since existing next-generation clocks were constructed in blood, we sought to develop a next-generation clock optimized for prediction in cheek swabs, which are non-invasive and easy to collect. To do this, we collected MethylationEPIC data as well as lifestyle and health information from 8045 diverse adults. Using a novel simulated annealing approach that allowed us to incorporate lifestyle and health factors into training as well as a combination of CpG filtering, CpG clustering, and clock ensembling, we constructed CheekAge, an epigenetic aging clock that has a strong correlation with age, displays high test–retest reproducibility across replicates, and significantly associates with a plethora of lifestyle and health factors, such as BMI, smoking status, and alcohol intake. We validated CheekAge in an internal dataset and multiple publicly available datasets, including samples from patients with progeria or meningioma. In addition to exploring the underlying biology of the data and clock, we provide a free online tool that allows users to mine our methylomic data and predict epigenetic age. [ABSTRACT FROM AUTHOR]

Case presentation: Scientific documentation on lifelong repeated cycles of long-term fasting doesn't exist. We report the case of a 92-year-old man who fasted 3 weeks yearly for 45 years. Results: Body weight and clinical parameters showed cyclic variations, returning to baseline after food reintroduction. Biological age analysis indicated that the patient was 5.9 years younger than his chronological age. Mental and physical health tests documented the absence of frailty, that the patient could function independently, had excellent cognitive functions, and a good mobility. Conclusion: It can be reasonably assumed that this subject have had protective effects from his yearly fasting. [ABSTRACT FROM AUTHOR]

Dynamic changes in genomic DNA methylation patterns govern the epigenetic developmental programs and accompany the organism's aging. Epigenetic clock (eAge) algorithms utilize DNA methylation to estimate the age and risk factors for diseases as well as analyze the impact of various interventions. High-throughput bisulfite sequencing methods, such as reduced-representation bisulfite sequencing (RRBS) or whole genome bisulfite sequencing (WGBS), provide an opportunity to identify the genomic regions of disordered or heterogeneous DNA methylation, which might be associated with cell-type heterogeneity, DNA methylation erosion, and allele-specific methylation. We systematically evaluated the applicability of five scores assessing the variability of methylation patterns by evaluating within-sample heterogeneity (WSH) to construct human blood epigenetic clock models using RRBS data. The best performance was demonstrated by the model based on a metric designed to assess DNA methylation erosion with an MAE of 3.686 years. We also trained a prediction model that uses the average methylation level over genomic regions. Although this region-based model was relatively more efficient than the WSH-based model, the latter required the analysis of just a few short genomic regions and, therefore, could be a useful tool to design a reduced epigenetic clock that is analyzed by targeted next-generation sequencing. [ABSTRACT FROM AUTHOR]

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

ObjectiveThe aim of the study is to examine associations between years of firefighting service and eight chronological age-adjusted measures of blood leukocyte epigenetic age acceleration: Horvath, Hannum, SkinBloodClock, Intrinsic, Extrinsic, PhenoAge, GrimAge, and DNAm telomere length.MethodsThe study used a repeated measures analysis of data from 379 incumbent firefighters from eight career departments and 100 recruit firefighters from two of the departments, across the United States.ResultsIncumbent firefighters had on average greater epigenetic age acceleration compared with recruit firefighters, potentially due to the cumulative effect of occupational exposures. However, among incumbent firefighters, additional years of service were associated with epigenetic age deceleration, particularly for GrimAge, a strong predictor of mortality.ConclusionsLong-term studies with more specific occupational exposure classification are needed to better understand the relationship between years of service and aging biomarkers.

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: This study investigated the association of prenatal and early childhood exposure to air pollution with epigenetic age acceleration (EAA) at six years of age using the Environment and Development of Children Cohort (EDC Cohort) Materials & methods: Air pollution, including particulate matter [< 2.5 µm (PM2.5) and < 10 µm (PM10) in an aerodynamic diameter], nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and sulfur dioxide (SO2) were estimated based on the residential address for two periods: 1) during the whole pregnancy, and 2) for one year before the follow-up in children at six years of age. The methylation levels in whole blood at six years of age were measured, and the methylation clocks, including Horvath’s clock, Horvath’s skin and blood clock, PedBE, and Wu’s clock, were estimated. Multivariate linear regression models were constructed to analyze the association between EAA and air pollutants. Results: A total of 76 children in EDC cohort were enrolled in this study. During the whole pregnancy, interquartile range (IQR) increases in exposure to PM2.5 (4.56 μg/m3) and CO (0.156 ppm) were associated with 0.406 years and 0.799 years of EAA (Horvath’s clock), respectively. An IQR increase in PM2.5 (4.76 μg/m3) for one year before the child was six years of age was associated with 0.509 years of EAA (Horvath’s clock) and 0.289 years of EAA (Wu’s clock). PM10 (4.30 μg/m3) and O3 (0.003 ppm) exposure in the period were also associated with EAA in Horvath’s clock (0.280 years) and EAA in Horvath’s skin and blood clock (0.163 years), respectively. Conclusion: We found that prenatal and childhood exposure to ambient air pollutants is associated with EAA among children. The results suggest that air pollution could induce excess biological aging even in prenatal and early life.

Abstract Background In observational studies, there exists an association between obesity and epigenetic age as well as telomere length. However, varying and partially conflicting outcomes have notably arisen from distinct studies on this topic. In the present study, two-way Mendelian randomization was used to identify potential causal associations between obesity and epigenetic age and telomeres. Methods A genome-wide association study was conducted using data from individuals of European ancestry to investigate bidirectional Mendelian randomization (MR) regarding the causal relationships between obesity, as indicated by three obesity indicators (body mass index or BMI, waist circumference adjusted for BMI or WCadjBMI, and waist-to-hip ratio adjusted for BMI or WHRadjBMI), and four epigenetic age measures (HannumAge, HorvathAge, GrimAge, PhenoAge), as well as telomere length. To assess these causal associations, various statistical methods were employed, including Inverse Variance Weighted (IVW), Weighted Median, MR Egger, Weighted Mode, and Simple Mode. To address the issue of multiple testing, we applied the Bonferroni correction. These methods were used to determine whether there is a causal link between obesity and epigenetic age, as well as telomere length, and to explore potential bidirectional relationships. Forest plots and scatter plots were generated to show causal associations between exposures and outcomes. For a comprehensive visualization of the results, leave-one-out sensitivity analysis plots, individual SNP-based forest plots for MR analysis, and funnel plots were included in the presentation of the results. Results A strong causal association was identified between obesity and accelerated HannumAge, GrimAge, PhenoAge and telomere length shrinkage. The causal relationship between WCadjBMI and PhenoAge acceleration (OR: 2.099, 95%CI: 1.248—3.531, p = 0.005) was the strongest among them. However, only the p-values for the causal associations of obesity with GrimAge, PhenoAge, and telomere length met the criteria after correction using the Bonferroni multiple test. In the reverse MR analysis, there were statistically significant causal associations between HorvathAge, PhenoAge and GrimAge and BMI, but these associations exhibited lower effect sizes, as indicated by their Odds Ratios (ORs). Notably, sensitivity analysis revealed the robustness of the study results. Conclusions The present findings reveal a causal relationship between obesity and the acceleration of epigenetic aging as well as the reduction of telomere length, offering valuable insights for further scientific investigations aimed at developing strategies to mitigate the aging process in humans.

Breast cancer is the most common cancer diagnosed in women and is often treated with chemotherapy. Although previous studies have demonstrated increasing biological age in patients who receive chemotherapy, evaluation of this association with DNA methylation-based markers of biological ageing may provide novel insight into the role of chemotherapy on the ageing process. We therefore sought to investigate the association between chemotherapy and markers of biological ageing as estimated from DNA methylation in women with breast cancer. DNA methylation profiling was performed on peripheral blood collected from 18 patients before and after the first cycle of chemotherapy using the Infinium HumanMethylation450 BeadChip. Six markers of biological age acceleration were estimated from DNA methylation levels. Multiple linear regression analyses were performed to evaluate the association between each metric of biological age acceleration and chemotherapy. After adjusting for chronological age and race, intrinsic epigenetic age acceleration (p = 0.041), extrinsic epigenetic age acceleration (p = 0.050), PhenoAge acceleration (p = 0.001), GrimAge acceleration (p

Alcohol is a widely consumed substance in the United States, however its effect on aging remains understudied. In this study of young adults, we examined whether cumulative alcohol consumption, i.e., alcohol years of beer, liquor, wine, and total alcohol, and recent binge drinking, were associated with four measures of age-related epigenetic changes via blood DNA methylation. A random subset of study participants in the Coronary Artery Risk Development in Young Adults Study underwent DNA methylation profiling using the Illumina MethylationEPIC Beadchip. Participants with alcohol consumption and methylation data at examination years 15 (n = 1,030) and 20 (n = 945) were included. Liquor and total alcohol consumption were associated with a 0.31-year (P = 0.002) and a 0.12-year (P = 0.013) greater GrimAge acceleration (GAA) per additional five alcohol years, while beer and wine consumption observed marginal (P = 0.075) and no associations (P = 0.359) with GAA, respectively. Any recent binge drinking and the number of days of binge drinking were associated with a 1.38-year (P < 0.001) and a 0.15-year (P < 0.001) higher GAA, respectively. We observed statistical interactions between cumulative beer (P < 0.001) and total alcohol (P = 0.004) consumption with chronological age, with younger participants exhibiting a higher average in GAA compared to older participants. No associations were observed with the other measures of epigenetic aging. These results suggest cumulative liquor and total alcohol consumption and recent binge drinking may alter age-related epigenetic changes as captured by GAA. With the increasing aging population and widespread consumption of alcohol, these findings may have potential implications for lifestyle modification to promote healthy aging.

Epigenetic changes may be biomarkers of health. Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corresponding miRNA-based health implications have not been evaluated. We analyzed DNA methylation and miRNA profiles from blood sampled among 332 individuals enrolled across 2 U.S.-based firefighter occupational studies (2015-2018 and 2018-2020). We considered 7 measures of EAA in leukocytes (PhenoAge, GrimAge, Horvath, skin-blood, and Hannum epigenetic clocks, and extrinsic and intrinsic epigenetic age acceleration). We identified miRNAs associated with EAA using individual linear regression models, adjusted for sex, race/ethnicity, chronological age, and cell type estimates, and investigated downstream effects of associated miRNAs with miRNA enrichment analyses and genomic annotations. On average, participants were 38 years old, 88% male, and 75% non-Hispanic white. We identified 183 of 798 miRNAs associated with EAA (FDR q

Gestational age (GA) is an important determinant of child health and disease risk. Two epigenetic GA clocks have been developed using DNA methylation (DNAm) patterns in cord blood. We investigate the accuracy of GA clocks and determinants of epigenetic GA acceleration (GAA), a biomarker of biological ageing. We hypothesize that prenatal and birth characteristics are associated with altered GAA, thereby disrupting foetal biological ageing. We examined 372 mother-child pairs from the Center for the Health Assessment of Mothers and Children of Salinas study of primarily Latino farmworkers in California. Chronological GA was robustly correlated with epigenetic GA (DNAm GA) estimated by the Knight (r = 0.48, p

Parental age is a known risk factor for autism spectrum disorder (ASD), however, studies to identify the biologic changes underpinning this association are limited. In recent years, "epigenetic clock" algorithms have been developed to estimate biologic age and to evaluate how the epigenetic aging impacts health and disease. In this study, we examined the relationship between parental epigenetic aging and their child's prospective risk of ASD and autism related quantitative traits in the Early Autism Risk Longitudinal Investigation study. Estimates of epigenetic age were computed using three robust clock algorithms and DNA methylation measures from the Infinium HumanMethylation450k platform for maternal blood and paternal blood specimens collected during pregnancy. Epigenetic age acceleration was defined as the residual of regressing chronological age on epigenetic age while accounting for cell type proportions. Multinomial logistic regression and linear regression models were completed adjusting for potential confounders for both maternal epigenetic age acceleration (n = 163) and paternal epigenetic age acceleration (n = 80). We found accelerated epigenetic aging in mothers estimated by Hannum's clock was significantly associated with lower cognitive ability and function in offspring at 12 months, as measured by Mullen Scales of Early Learning scores (β = -1.66, 95% CI: -3.28, -0.04 for a one-unit increase). We also observed a marginal association between accelerated maternal epigenetic aging by Horvath's clock and increased odds of ASD in offspring at 36 months of age (aOR = 1.12, 95% CI: 0.99, 1.26). By contrast, fathers accelerated aging was marginally associated with decreased ASD risk in their offspring (aOR = 0.83, 95% CI: 0.68, 1.01). Our findings suggest epigenetic aging could play a role in parental age risks on child brain development.

Treatments that target fundamental processes of aging are expected to delay several aging-related conditions simultaneously. Testing the efficacy of these treatments for potential anti-aging benefits will require clinical trials with endpoints that reflect the potential benefits of slowing processes of aging. There are several potential types of endpoints to capture the benefits of slowing a process of aging, and a consensus is needed to standardize and compare the results of these trials and to guide the analysis of observational data to support trial planning. Using biomarkers instead of clinical outcomes would substantially reduce the size and the duration of clinical trials. This requires validation of surrogate markers showing that treatment induced change in the marker reliably predicts the magnitude of change in the clinical outcome. The surrogate marker must also reflect the biological mechanism for the effect of treatment on the clinical outcome. "Biological age" is a superficially attractive marker for such trials. However, it is essential to establish that treatment induced change in biological age reliably predict the magnitude of benefits in the clinical outcome. Reaching consensus on clinical outcomes for geroscience trials and then validating potential surrogate biomarkers requires time, effort, and coordination that will be worthwhile to develop surrogate outcomes that can be trusted to efficiently test the value of many anti-aging treatments under development.

Background: In observational studies, there exists an association between obesity and epigenetic age as well as telomere length. However, varying and partially conflicting outcomes have notably arisen from distinct studies on this topic. In the present study, two-way Mendelian randomization was used to identify potential causal associations between obesity and epigenetic age and telomeres. Methods: A genome-wide association study was conducted using data from individuals of European ancestry to investigate bidirectional Mendelian randomization (MR) regarding the causal relationships between obesity, as indicated by three obesity indicators (body mass index or BMI, waist circumference adjusted for BMI or WCadjBMI, and waist-to-hip ratio adjusted for BMI or WHRadjBMI), and four epigenetic age measures (HannumAge, HorvathAge, GrimAge, PhenoAge), as well as telomere length. To assess these causal associations, various statistical methods were employed, including Inverse Variance Weighted (IVW), Weighted Median, MR Egger, Weighted Mode, and Simple Mode. To address the issue of multiple testing, we applied the Bonferroni correction. These methods were used to determine whether there is a causal link between obesity and epigenetic age, as well as telomere length, and to explore potential bidirectional relationships. Forest plots and scatter plots were generated to show causal associations between exposures and outcomes. For a comprehensive visualization of the results, leave-one-out sensitivity analysis plots, individual SNP-based forest plots for MR analysis, and funnel plots were included in the presentation of the results. Results: A strong causal association was identified between obesity and accelerated HannumAge, GrimAge, PhenoAge and telomere length shrinkage. The causal relationship between WCadjBMI and PhenoAge acceleration (OR: 2.099, 95%CI: 1.248—3.531, p = 0.005) was the strongest among them. However, only the p-values for the causal associations of obesity with GrimAge, PhenoAge, and telomere length met the criteria after correction using the Bonferroni multiple test. In the reverse MR analysis, there were statistically significant causal associations between HorvathAge, PhenoAge and GrimAge and BMI, but these associations exhibited lower effect sizes, as indicated by their Odds Ratios (ORs). Notably, sensitivity analysis revealed the robustness of the study results. Conclusions: The present findings reveal a causal relationship between obesity and the acceleration of epigenetic aging as well as the reduction of telomere length, offering valuable insights for further scientific investigations aimed at developing strategies to mitigate the aging process in humans. [ABSTRACT FROM AUTHOR]

Sex hormones are hypothesized to drive sex-specific health disparities. Here, we study the association between sex steroid hormones and DNA methylation-based (DNAm) biomarkers of age and mortality risk including Pheno Age Acceleration (AA), Grim AA, and DNAm-based estimators of Plasminogen Activator Inhibitor 1 (PAI1), and leptin concentrations. We pooled data from three population-based cohorts, the Framingham Heart Study Offspring Cohort, the Baltimore Longitudinal Study of Aging, and the InCHIANTI Study, including 1,062 postmenopausal women without hormone therapy and 1,612 men of European descent. Sex-stratified analyses using a linear mixed regression were performed, with a Benjamini-Hochberg (BH) adjustment for multiple testing. Sex Hormone Binding Globulin (SHBG) was associated with a decrease in DNAm PAI1 among men (per 1 standard deviation (SD): -478 pg/mL; 95%CI: -614 to -343; P:1e-11; BH-P: 1e-10), and women (-434 pg/mL; 95%CI: -589 to -279; P:1e-7; BH-P:2e-6). The testosterone/estradiol (TE) ratio was associated with a decrease in Pheno AA (-0.41 years; 95%CI: -0.70 to -0.12; P:0.01; BH-P: 0.04), and DNAm PAI1 (-351 pg/mL; 95%CI: -486 to -217; P:4e-7; BH-P:3e-6) among men. In men, testosterone was associated with a decrease in DNAm PAI1 (-481 pg/mL; 95%CI: -613 to -349; P:2e-12; BH-P:6e-11). SHBG was associated with lower DNAm PAI1 among men and women. Higher testosterone and testosterone/estradiol ratio were associated with lower DNAm PAI and a younger epigenetic age in men. A decrease in DNAm PAI1 is associated with lower mortality and morbidity risk indicating a potential protective effect of testosterone on lifespan and conceivably cardiovascular health via DNAm PAI1. [ABSTRACT FROM AUTHOR]

Abstract Objective Mitochondrial dysfunction and nuclear epigenetic alterations, two hallmarks of aging, are associated with aberrant development and complex disease risk. Here, we report a method for the simultaneous assessment of mitochondrial DNA copy number (mtDNA-CN) and DNA methylation age (DNAm age) from the same DNA extraction using quantitative polymerase chain reaction (qPCR) and array data, respectively. Result We present methods for the concurrent estimation of mtDNA-CN and DNAm age from the same DNA samples. This includes qPCR to estimate mtDNA-CN, representing the number of circular mitochondrial genomes in a cell, and DNA methylation microarray data to estimate the epigenetic age of an individual. Further, we provide a method for the combination of these metrics into a shared metric termed ‘mtEpiAge’. This approach provides a valuable tool for exploring the interplay between mitochondrial dysfunction and nuclear epigenetic alterations, and their associations with disease and aging.

Abstract Background The relationship between aging and osteoporosis is well established. However, the relationship between the body's physiological age, i.e. epigenetic age, and osteoporosis is not known. Our goal is to analyze the bidirectional causal relationship between epigenetic clocks and osteoporosis using a bidirectional Mendelian randomization study. Methods We used SNPs closely associated with GrimAge, Hannum, PhenoAge, and HorvathAge in epigenetic age and SNPs closely associated with femoral neck bone mineral density, lumbar spine bone mineral density, and forearm bone mineral density as instrumental variables, respectively, using the inverse variance weighting method and several other MR methods to assess the bidirectional causal relationship between epigenetic age and osteoporosis. Result There was no evidence of a clear causal relationship of epigenetic age (GrimAge, Hannum, PhenoAge, and HorvathAge) on femoral neck bone mineral density, lumbar spine bone mineral density, and forearm bone mineral density. In reverse Mendelian randomization analysis showed a significant causal effect of lumbar spine bone mineral density on GrimAge: odds ratio (OR) = 0.692, 95% confidence interval (CI) = (0.538–0.890), p = 0.004. The results suggest that a decrease in lumbar spine bone mineral density promotes an acceleration of GrimAge. Conclusion There was no significant bidirectional causal relationship between epigenetic age and osteoporosis A decrease in lumbar spine bone density may lead to an acceleration of the epigenetic clock "GrimAge". Our study provides partial evidence for a bidirectional causal effect between epigenetic age and Osteoporosis.

Objective: Mitochondrial dysfunction and nuclear epigenetic alterations, two hallmarks of aging, are associated with aberrant development and complex disease risk. Here, we report a method for the simultaneous assessment of mitochondrial DNA copy number (mtDNA-CN) and DNA methylation age (DNAm age) from the same DNA extraction using quantitative polymerase chain reaction (qPCR) and array data, respectively. Result: We present methods for the concurrent estimation of mtDNA-CN and DNAm age from the same DNA samples. This includes qPCR to estimate mtDNA-CN, representing the number of circular mitochondrial genomes in a cell, and DNA methylation microarray data to estimate the epigenetic age of an individual. Further, we provide a method for the combination of these metrics into a shared metric termed 'mtEpiAge'. This approach provides a valuable tool for exploring the interplay between mitochondrial dysfunction and nuclear epigenetic alterations, and their associations with disease and aging. [ABSTRACT FROM AUTHOR]

The anti‐diabetic drug metformin may promote healthy aging. However, few clinical trials of metformin assessing biomarkers of aging have been completed. In this communication, we retrospectively examined the effect of metformin on epigenetic age using principal component (PC)‐based epigenetic clocks, mitotic clocks, and pace of aging in peripheral monocytes and CD8+ T cells from participants in two clinical trials of virologically‐suppressed people living with HIV (PLWH) with normal glucose receiving metformin. In a small 24‐week clinical trial that randomized participants to receive either adjunctive metformin or observation, we observed significantly decreased PCPhenoAge and PCGrimAge estimates of monocytes from only participants in the metformin arm by a mean decrease of 3.53 and 1.84 years from baseline to Week 24. In contrast, we observed no significant differences in all PC clocks for participants in the observation arm over 24 weeks. Notably, our analysis of epigenetic mitotic clocks revealed significant increases for monocytes in the metformin arm when comparing baseline to Week 24, suggesting an impact of metformin on myeloid cell kinetics. Analysis of a single‐arm clinical trial of adjunctive metformin in eight PLWH revealed no significant differences across all epigenetic clocks assessed in CD8+ T cells at 4‐ and 8‐week time points. Our results suggest cell‐type‐specific myeloid effects of metformin captured by PC‐based epigenetic clock biomarkers. Larger clinical studies of metformin are needed to validate these observations and this report highlights the need for further inclusion of PLWH in geroscience trials evaluating the effect of metformin on increasing healthspan and lifespan. [ABSTRACT FROM AUTHOR]

Life history theory applied to human development stipulates that humans have evolved to detect and encode information from the early developmental environment that entrain coordinated development pathways. One possible mechanism is epigenetic age acceleration but few studies have prospectively examined associations between epigenetic aging and life-history related phenotypes. The purpose of this study was to examine the relations between epigenetic age acceleration when children were age 7 years and indices of reproductive development during adolescence using a sample of N = 512 youth from the Avon Longitudinal Study of Parents and Children (ALSPAC). A path model was used to test direct and indirect associations between epigenetic age acceleration and age at menarche (AAM), age at first sex, and lifetime and past year sexual partner number. Results showed epigenetic age acceleration was directly associated with earlier age at first sex and increased sexual partner number. There were further indirect associations with sexual partner number via age at first sex. Epigenetic age acceleration was not associated with AAM. Follow-up analyses to determine if aspects of the early developmental environment were associated with age acceleration were null. Implications for life history theory and the need for additional research are discussed. [ABSTRACT FROM AUTHOR]

Objectives Loneliness may influence aging biomarkers related to cognitive functioning, for example, through accelerated DNA methylation (DNAm) aging. Methods In the present study, we tested whether six common DNAm age acceleration measures mediated the effects of baseline loneliness and five different longitudinal loneliness trajectories on general cognitive ability, immediate memory recall, delayed memory recall, and processing speed in 1,814 older adults in the Health and Retirement Study. Results We found that baseline loneliness and individuals who belong to the highest loneliness trajectories had poorer general cognitive ability and memory scores. Only DNAm age acceleration measures that index physiological comorbidities, unhealthy lifestyle factors (e.g. smoking), and mortality risk-mediated effects of baseline loneliness on general cognitive ability and memory functioning but not processing speed. These same DNAm measures mediated effects of the moderate-but-declining loneliness trajectory on cognitive functioning. Additionally, immediate and delayed memory scores were mediated by GrimAge Accel in the lowest and two highest loneliness trajectory groups. Total and mediated effects of loneliness on cognitive functioning outcomes were mainly accounted for by demographic, social, psychological, and physiological covariates, most notably self-rated health, depressive symptomatology, objective social isolation, and body mass index. Discussion Current findings suggest that DNAm biomarkers of aging, particularly GrimAge Accel, have promise for explaining the prospective association between loneliness and cognitive functioning outcomes. [ABSTRACT FROM AUTHOR]

Background: The causal relationship and the direction of the effect between depression and aging remain controversial. Methods: We used a bidirectional two-sample Mendelian randomization analysis to examine the relationship between depression and age proxy indicators. We obtained pooled statistics from genome-wide association studies (GWAS) on depression and the age proxy indicators. We employed five MR analysis methods to address potential biases and ensure robustness of our results, with the inverse variance weighted (IVW) method being the primary outcome. We also conducted outlier exclusion using Radial MR, MRPRESSO, and MR Steiger filters. Additionally, sensitivity analyses were performed to assess heterogeneity and pleiotropy. Results: Our MR analysis revealed that depression causally leads to shortened telomere length (β = − 0.014; P = 0.038), increased frailty index (β = 0.076; P = 0.000), and accelerated GrimAge (β = 0.249; P = 0.024). Furthermore, our findings showed that the frailty index (OR = 1.679; P = 0.001) was causally associated with an increased risk of depression. Additionally, we found that appendicular lean mass (OR = 0.929; P = 0.000) and left-hand grip strength (OR = 0.836; P = 0.014) were causally associated with a reduced risk of depression. Sensitivity analyses demonstrated the robustness of our findings. Conclusions: Our study provides evidence that depression contributes to the accelerated aging process, resulting in decreased telomere length, increased frailty index, and accelerated GrimAge. Additionally, we found that the frailty index increases the risk of depression, while appendicular lean mass and left-handed grip strength reduce the risk of depression. [ABSTRACT FROM AUTHOR]

Aberrant DNA methylation (DNAm) is known to be associated with the aetiology of cancer, including colorectal cancer (CRC). In the past, the availability of open access data has been the main driver of innovative method development and research training. However, this is increasingly being eroded by the move to controlled access, particularly of medical data, including cancer DNAm data. To rejuvenate this valuable tradition, we leveraged DNAm data from 1,845 samples (535 CRC tumours, 522 normal colon tissues adjacent to tumours, 72 colorectal adenomas, and 716 normal colon tissues from healthy individuals) from 14 open access studies deposited in NCBI GEO and ArrayExpress. We calculated each sample's epigenetic age (EA) using eleven epigenetic clock models and derived the corresponding epigenetic age acceleration (EAA). For EA, we observed that most first- and second-generation epigenetic clocks reflect the chronological age in normal tissues adjacent to tumours and healthy individuals [e.g., Horvath (r = 0.77 and 0.79), Zhang elastic net (EN) (r = 0.70 and 0.73)] unlike the epigenetic mitotic clocks (EpiTOC, HypoClock, MiAge) (r < 0.3). For EAA, we used PhenoAge, Wu, and the above mitotic clocks and found them to have distinct distributions in different tissue types, particularly between normal colon tissues adjacent to tumours and cancerous tumours, as well as between normal colon tissues adjacent to tumours and normal colon tissue from healthy individuals. Finally, we harnessed these associations to develop a classifier using elastic net regression (with lasso and ridge regularisations) that predicts CRC diagnosis based on a patient's sex and EAAs calculated from histologically normal controls (i.e., normal colon tissues adjacent to tumours and normal colon tissue from healthy individuals). The classifier demonstrated good diagnostic potential with ROC-AUC = 0.886, which suggests that an EAA-based classifier trained on relevant data could become a tool to support diagnostic/prognostic decisions in CRC for clinical professionals. Our study also reemphasises the importance of open access clinical data for method development and training of young scientists. Obtaining the required approvals for controlled access data would not have been possible in the timeframe of this study. [ABSTRACT FROM AUTHOR]

Epigenetic changes may be biomarkers of health. Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corresponding miRNA-based health implications have not been evaluated. We analyzed DNA methylation and miRNA profiles from blood sampled among 332 individuals enrolled across 2 U.S.-based firefighter occupational studies (2015-2018 and 2018-2020). We considered 7 measures of EAA in leukocytes (PhenoAge, GrimAge, Horvath, skin-blood, and Hannum epigenetic clocks, and extrinsic and intrinsic epigenetic age acceleration). We identified miRNAs associated with EAA using individual linear regression models, adjusted for sex, race/ethnicity, chronological age, and cell type estimates, and investigated downstream effects of associated miRNAs with miRNA enrichment analyses and genomic annotations. On average, participants were 38 years old, 88% male, and 75% non-Hispanic white. We identified 183 of 798 miRNAs associated with EAA (FDR q < 0.05); 126 with PhenoAge, 59 with GrimAge, 1 with Horvath, and 1 with the skin-blood clock. Among miRNAs associated with Horvath and GrimAge, there were 61 significantly enriched disease annotations including age-related metabolic and cardiovascular conditions and several cancers. Enriched pathways included those related to proteins and protein modification. We identified miRNAs associated with EAA of multiple epigenetic clocks. PhenoAge had more associations with individual miRNAs, but GrimAge and Horvath had greater implications for miRNA-associated pathways. Understanding the relationship between these epigenetic markers could contribute to our understanding of the molecular underpinnings of aging and aging-related diseases. [ABSTRACT FROM AUTHOR]

Background: The relationship between aging and osteoporosis is well established. However, the relationship between the body's physiological age, i.e. epigenetic age, and osteoporosis is not known. Our goal is to analyze the bidirectional causal relationship between epigenetic clocks and osteoporosis using a bidirectional Mendelian randomization study. Methods: We used SNPs closely associated with GrimAge, Hannum, PhenoAge, and HorvathAge in epigenetic age and SNPs closely associated with femoral neck bone mineral density, lumbar spine bone mineral density, and forearm bone mineral density as instrumental variables, respectively, using the inverse variance weighting method and several other MR methods to assess the bidirectional causal relationship between epigenetic age and osteoporosis. Result: There was no evidence of a clear causal relationship of epigenetic age (GrimAge, Hannum, PhenoAge, and HorvathAge) on femoral neck bone mineral density, lumbar spine bone mineral density, and forearm bone mineral density. In reverse Mendelian randomization analysis showed a significant causal effect of lumbar spine bone mineral density on GrimAge: odds ratio (OR) = 0.692, 95% confidence interval (CI) = (0.538–0.890), p = 0.004. The results suggest that a decrease in lumbar spine bone mineral density promotes an acceleration of GrimAge. Conclusion: There was no significant bidirectional causal relationship between epigenetic age and osteoporosis A decrease in lumbar spine bone density may lead to an acceleration of the epigenetic clock "GrimAge". Our study provides partial evidence for a bidirectional causal effect between epigenetic age and Osteoporosis. [ABSTRACT FROM AUTHOR]

Atrial fibrillation (AF) is the most common arrhythmia in humans. AF is characterized by irregular and increased atrial muscle activation. This high-frequency activation obliterates the synchronous work of the atria and ventricles, reducing myocardial performance, which can lead to severe heart failure or stroke. The risk of developing atrial fibrillation depends largely on the patient's history. Cardiovascular diseases are considered aging-related pathologies; therefore, deciphering the role of telomeres and DNA methylation (mDNA), two hallmarks of aging, is likely to contribute to a better understanding and prophylaxis of AF. In honor of Prof. Elizabeth Blackburn's 75th birthday, we dedicate this review to the discovery of telomeres and her contribution to research on aging. [ABSTRACT FROM AUTHOR]

Introduction: DNA methylation, specifically the formation of 5-methylcytosine at the C5 position of cytosine, undergoes reproducible changes as organisms age, establishing it as a significant biomarker in aging studies. Epigenetic clocks, which integrate methylation patterns to predict age, often employ linear models based on penalized regression, yet they encounter challenges in handling missing data, count-based bisulfite sequence data, and interpretation.Methods: To address these limitations, we introduce BayesAge, an extension of the scAge methodology originally designed for single-cell DNA methylation analysis. BayesAge employs maximum likelihood estimation (MLE) for age inference, models count data using binomial distributions, and incorporates LOWESS smoothing to capture non-linear methylation-age dynamics. This approach is tailored for bulk bisulfite sequencing datasets.Results: BayesAge demonstrates superior performance compared to scAge. Notably, its age residuals exhibit no age association, offering a less biased representation of epigenetic age variation across populations. Furthermore, BayesAge facilitates the estimation of error bounds on age inference. When applied to down-sampled data, BayesAge achieves a higher coefficient of determination between predicted and actual ages compared to both scAge and penalized regression.Discussion: BayesAge presents a promising advancement in epigenetic age prediction, addressing key challenges encountered by existing models. By integrating robust statistical techniques and tailored methodologies for count-based data, BayesAge offers improved accuracy and interpretability in predicting age from bulk bisulfite sequencing datasets. Its ability to estimate error bounds enhances the reliability of age inference, thereby contributing to a more comprehensive understanding of epigenetic aging processes.

The proportion of aging populations affected by dementia is increasing. There is an urgent need to identify biological aging markers in mid-life before symptoms of age-related dementia present for early intervention to delay the cognitive decline and the onset of dementia. In this cohort study involving 1,676 healthy participants (mean age 40) with up to 15 years of follow up, we evaluated the associations between cognitive function and two classes of novel biological aging markers: blood-based epigenetic aging and neuroimaging-based brain aging. Both accelerated epigenetic aging and brain aging were prospectively associated with worse cognitive outcomes. Specifically, every year faster epigenetic or brain aging was on average associated with 0.19-0.28 higher (worse) Stroop score, 0.04-0.05 lower (worse) RAVLT score, and 0.23-0.45 lower (worse) DSST (all false-discovery-rate-adjusted p

Germán Alberto Nolasco-Rosales,1,&ast; Cecilia Yazmin Alonso-García,1,&ast; David Gustavo Hernández-Martínez,1 Mario Villar-Soto,2 José J Martínez-Magaña,3 Alma Delia Genis-Mendoza,4 Thelma Beatriz González-Castro,5 Carlos Alfonso Tovilla-Zarate,6 Crystell Guadalupe Guzmán-Priego,1 Mirian Carolina Martínez-López,1 Humberto Nicolini,7 Isela Esther Juárez-Rojop1 1División Académica de Ciencias de la Salud, Universidad Juarez Autónoma de Tabasco, Villahermosa, Tabasco, México; 2Hospital Regional de Alta Especialidad de Salud Mental, Villahermosa, Tabasco, México; 3Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; 4Hospital Psiquiátrico Infantil “Dr. Juan N. Navarro”, Ciudad de México, México; 5División Académica Multidisciplinaria de Jalpa de Méndez, Universidad Juarez Autónoma de Tabasco, Jalpa de Méndez, Tabasco, México; 6División Académica Multidisciplinaria de Comalcalco, Universidad Juarez Autónoma de Tabasco, Comalcalco, Tabasco, México; 7Departamento de Genética Psiquiátrica, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, México&ast;These authors contributed equally to this workCorrespondence: Isela Esther Juárez-Rojop, División Académica de Ciencias de la Salud, Universidad Juarez Autónoma de Tabasco, Av. Gregorio Méndez 2838-A, Col. Tamulté, Villahermosa, 86100, México, Email iselajuarezrojop@hotmail.com Humberto Nicolini, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, 86100, México, Email hnicolini@inmegen.gob.mxPurpose: Epigenetic age and inflammatory markers have been proposed as indicators of severity and mortality in patients with COVID-19. Furthermore, they have been associated with the occurrence of neurological symptoms, psychiatric manifestations, and cognitive impairment. Therefore, we aimed to explore the possible associations between epigenetic age, neuropsychiatric manifestations and inflammatory markers (neutrophil-lymphocyte ratio [NLR], platelet-lymphocyte ratio [PLR], monocyte-lymphocyte ratio [MLR], and systemic immune-inflammation index [SII]) in healthcare personnel with post-COVID condition.Patients and Methods: We applied the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) tests to 51 Mexican healthcare workers with post-COVID-19 condition; we also estimated their epigenetic age using the PhenoAge calculator.Results: The participants had a post-COVID condition that lasted a median of 14 months (range: 1– 20). High NLR (> 1.73) had association with mild cognitive impairment by MMSE (p=0.013). Likewise, high MLR (> 0.24) were associated with language domain in MOCA (p=0.046). Low PLR (< 103.9) was also related to delayed recall in MOCA (p=0.040). Regarding comorbidities, hypertension was associated with SII (p=0.007), overweight with PLR (p=0.047) and alcoholism was associated with MLR (p=0.043). Interestingly, we observed associations of low PLR (< 103.9) and low SII (< 1.35) levels with increased duration of post-COVID condition (p=0.027, p=0.031). Likewise, increases in PhenoAge were associated with high levels of SII (OR=1.11, p=0.049), PLR (OR=1.12, p=0.035) and MLR (OR=1.12, p=0.030).Conclusion: We observed neurocognitive changes related to inflammatory markers and increases in epigenetic age in healthcare personnel with post-COVID-19 condition. Future research is required to assess mental and physical health in individuals with post-COVID-19 symptoms.Keywords: post-COVID-19, cognitive manifestation, inflammatory markers, epigenetic age

Abstract Aims Heart failure (HF) is a prevalent age‐related cardiovascular disease with poor prognosis in the elderly population. This study aimed to establish the causal relationship between ageing and HF by conducting a bidirectional Mendelian randomization (MR) analysis on epigenetic age (a marker of ageing) and HF. Methods and results Genome‐wide association study data for epigenetic age (GrimAge, HorvathAge, HannumAge, and PhenoAge) and HF were collected and assessed for significant genetic variables. A bidirectional MR analysis was carried out using the random‐effects inverse–variance weighted (IVW) method as the primary approach, while other methods (MR–Egger, weighted median, simple mode, and weighted mode) and multiple sensitivity analyses (heterogeneity analysis, leave‐one‐out sensitivity analysis, and horizontal pleiotropy analysis) were employed to evaluate the impact of epigenetic age on HF and vice versa. Bidirectional MR analysis of two samples revealed that the epigenetic PhenoAge clock increased the risk of HF [IVW odds ratio (OR) 1.015, 95% confidence interval (CI) 1.002–1.028, P = 0.028 and weighted median OR 1.020, 95% CI 1.001–1.038, P = 0.039]. Other results were not statistically significant. Conclusions The bidirectional MR analysis demonstrated a causal link between genetically predicted epigenetic age and HF in individuals of European descent. Further research into epigenetic age in other populations and additional genetic information related to HF is warranted.

Abstract Background Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, “epiphenotyping” approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied. Results Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry-informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, as well as over very long placental processing times. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component. Conclusions This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. We further demonstrate the specific utility of epiphenotyping tools developed for use with placental DNAme data, and show that these variables (i) provide an independent check of clinically obtained data and (ii) provide a robust approach to compare variables across different datasets. Finally, we present a general framework for the processing and analysis of placental DNAme data, integrating the epiphenotype variables discussed here.

Epigenetic aging biomarkers are associated with increased morbidity and mortality. We evaluated if occupational exposure to three established chemical carcinogens is associated with acceleration of epigenetic aging. We studied workers in China occupationally exposed to benzene, trichloroethylene (TCE) or formaldehyde by measuring personal air exposures prior to blood collection. Unexposed controls matched by age and sex were selected from nearby factories. We measured leukocyte DNA methylation (DNAm) in peripheral white blood cells using the Infinium HumanMethylation450 BeadChip to calculate five epigenetic aging clocks and DNAmTL, a biomarker associated with leukocyte telomere length and cell replication. We tested associations between exposure intensity and epigenetic age acceleration (EAA), defined as the residuals of regressing the DNAm aging biomarker on chronological age, matching factors and potential confounders. Median differences in EAA between exposure groups were tested using a permutation test with exact p-values. Epigenetic clocks were strongly correlated with age (Spearman r > 0.8) in all three occupational studies. There was a positive exposure-response relationship between benzene and the Skin-Blood Clock EAA biomarker: median EAA was -0.91 years in controls (n = 44), 0.78 years in workers exposed to

Emerging research suggests associations of physical and psychosocial stressors with epigenetic aging. Although this work has included early-life exposures, data on maternal exposures and epigenetic aging of their children remain sparse. Using longitudinally collected data from the California, Salinas Valley CHAMACOS study, we examined relationships between maternal Adverse Childhood Experiences (ACEs) reported up to 18 years of life, prior to pregnancy, with eight measures (Horvath, Hannum, SkinBloodClock, Intrinsic, Extrinsic, PhenoAge, GrimAge, and DNAm telomere length) of blood leukocyte epigenetic age acceleration (EAA) in their children at ages 7, 9, and 14 years (N = 238 participants with 483 observations). After adjusting for maternal chronological age at delivery, pregnancy smoking/alcohol use, parity, child gestational age, and estimated leukocyte proportions, higher maternal ACEs were significantly associated with at least a 0.76-year increase in child Horvath and Intrinsic EAA. Higher maternal ACEs were also associated with a 0.04 kb greater DNAm estimate of telomere length of children. Overall, our data suggests that maternal preconception ACEs are associated with biological aging in their offspring in childhood and that preconception ACEs have differential relationships with EAA measures, suggesting different physiologic utilities of EEA measures. Studies are necessary to confirm these findings and to elucidate potential pathways to explain these relationships, which may include intergenerational epigenetic inheritance and persistent physical and social exposomes.

BackgroundObsessive-compulsive disorder (OCD) is characterized by intrusive thoughts and repetitive actions, that presents the involvement of the cortico-striatal areas. The contribution of environmental risk factors to OCD development suggests that epigenetic mechanisms may contribute to its pathophysiology. DNA methylation changes and gene expression were evaluated in post-mortem brain tissues of the cortical (anterior cingulate gyrus and orbitofrontal cortex) and ventral striatum (nucleus accumbens, caudate nucleus and putamen) areas from eight OCD patients and eight matched controls.ResultsThere were no differentially methylated CpG (cytosine-phosphate-guanine) sites (DMSs) in any brain area, nevertheless gene modules generated from CpG sites and protein-protein-interaction (PPI) showed enriched gene modules for all brain areas between OCD cases and controls. All brain areas but nucleus accumbens presented a predominantly hypomethylation pattern for the differentially methylated regions (DMRs). Although there were common transcriptional factors that targeted these DMRs, their targeted differentially expressed genes were different among all brain areas. The protein-protein interaction network based on methylation and gene expression data reported that all brain areas were enriched for G-protein signaling pathway, immune response, apoptosis and synapse biological processes but each brain area also presented enrichment of specific signaling pathways. Finally, OCD patients and controls did not present significant DNA methylation age differences.ConclusionsDNA methylation changes in brain areas involved with OCD, especially those involved with genes related to synaptic plasticity and the immune system could mediate the action of genetic and environmental factors associated with OCD.

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

Dynamic changes in genomic DNA methylation patterns govern the epigenetic developmental programs and accompany the organism‘s aging. Epigenetic clock (eAge) algorithms utilize DNA methylation to estimate the age and risk factors for diseases as well as analyze the impact of various interventions. High-throughput bisulfite sequencing methods, such as reduced-representation bisulfite sequencing (RRBS) or whole genome bisulfite sequencing (WGBS), provide an opportunity to identify the genomic regions of disordered or heterogeneous DNA methylation, which might be associated with cell-type heterogeneity, DNA methylation erosion, and allele-specific methylation. We systematically evaluated the applicability of five scores assessing the variability of methylation patterns by evaluating within-sample heterogeneity (WSH) to construct human blood epigenetic clock models using RRBS data. The best performance was demonstrated by the model based on a metric designed to assess DNA methylation erosion with an MAE of 3.686 years. We also trained a prediction model that uses the average methylation level over genomic regions. Although this region-based model was relatively more efficient than the WSH-based model, the latter required the analysis of just a few short genomic regions and, therefore, could be a useful tool to design a reduced epigenetic clock that is analyzed by targeted next-generation sequencing.

Abstract Background Young adult cancer survivors experience early aging‐related morbidities and mortality. Biological aging biomarkers may identify at‐risk survivors and increase our understanding of mechanisms underlying this accelerated aging. Methods Using an observational study design, we cross‐sectionally measured DNA methylation‐based epigenetic age in young adult cancer survivors at a tertiary, academic state cancer hospital. Participants were a convenience sample of consecutively enrolled survivors of childhood, adolescent, and young adult cancers treated with either an anthracycline or alkylating agent, and who were at least 3 months post‐treatment. Similarly aged healthy comparators were consecutively enrolled. Cancer treatment and treatment intensity were compared to DNA methylation‐based epigenetic age and pace of aging. Results Sixty survivors (58 completing assessments, mean age 20.5 years, range 18–29) and 27 comparators (mean age 20 years, range 17–29) underwent DNA methylation measurement. Survivors were predominantly female (62%) and white (60%) and averaged nearly 6 years post‐treatment (range 0.2–25 years). Both epigenetic age (AgeAccelGrim: 1.5 vs. −2.4, p