Factors influencing accelerated aging in patients with type 2 diabetes mellitus and coronary heart disease.

Objective: To investigate the factors influencing accelerated aging in patients with type 2 diabetes mellitus (T2DM) and coronary heart disease (CHD). Methods: A total of 216 patients diagnosed with T2DM and CHD between August 2019 and August 2023 at Xuzhou Central Hospital were selected. Patients were divided into an aging group and a non-aging group, based on the positive or negative values of phenotypic age acceleration (PhenoAgeAccel). Logistic regression analysis was conducted. Variables that had a univariate analysis P< 0.05 were included in the multivariate analysis to identify factors influencing aging in patients with T2DM and CHD, and the area under the curve of the model was reported. Results: This study included 216 patients, with 89 in the accelerated aging group, and 127 in the non-accelerated aging group. The average age of patients was 70.40 (95% CI: 69.10-71.69) years, with 137 males (63.4%). Compared with the non-accelerated aging group, patients in the accelerated aging group were older, with a higher proportion of males, and a higher prevalence of hypertension, stable angina pectoris, and unstable angina pectoris. Multivariate Logistic regression analysis indicated that the absolute value of neutrophils (NEUT#), urea (UREA), adenosine deaminase (ADA), and the triglyceride-glucose index (TyG) were risk factors for accelerated aging, while cholinesterase (CHE) was a protective factor. For each unit increase in NEUT#, UREA, ADA, and TyG, the risk of aging increased by 64%, 48%, 10%, and 789%, respectively. The overall area under the receiver operating characteristic (ROC) curve of the model in the training set was 0.894, with a 95% confidence interval (CI) of 0.851-0.938. Conclusion: NEUT#, CHE, UREA, ADA, and TyG are predictors of accelerated aging in patients with T2DM and CHD, with the model showing favorable overall predictive performance.

DNA methylation-estimated phenotypes, telomere length and risk of ischemic stroke: epigenetic age acceleration of screening and a Mendelian randomization study.

BACKGROUND: Aging is a complex biological process that may be accelerated in certain pathological conditions. DNA methylation age (DNAmAge) has emerged as a biomarker for biological age, which can differ from chronological age. This research peels back the layers of the relationship between fast-forward aging and ischemic stroke, poking and prodding the potential two-way causal influences between stroke and biological aging indicators. METHODS: We analyzed a cohort of ischemic stroke patients, comparing DNAmAge with chronological age to measure age acceleration. We assessed variations in age acceleration among stroke subtypes and between sexes. Using Mendelian randomization, we examined the causal links between stroke, aging biomarkers like telomere length, and age acceleration's effect on stroke risk. RESULTS: Our investigation reveals a pronounced association between ischemic stroke and age acceleration, most notably in patients with cardioembolic strokes, who exhibited a striking median difference of 9 years between DNAmAge and chronological age. Furthermore, age acceleration differed significantly across stroke subtypes and was higher in women than in men. In terms of causality, MR analysis indicated a modest negative effect of stroke on telomere length, but no causal effect of age phenotypes on stroke or its subtypes. However, some indication of a potential causal effect of ischemic stroke on PhenoAge acceleration was observed. CONCLUSION: The study provides insight into the relationship between DNAmAge and ischemic stroke, particularly cardioembolic stroke, and suggests possible gender differences. These insights carry profound clinical significance and set stage for future investigations into the entwined pathways of stroke and accelerated aging.

Unraveling the influence of childhood emotional support on adult aging: Insights from the UK Biobank.

BACKGROUND: Exploring the association between Childhood Emotional Support (CES) and the mechanisms of aging is pivotal for understanding its potential to lessen the incidence of age-related pathologies and promote a milieu for healthy aging. METHODS: Utilizing data from the UK Biobank comprising nearly 160,000 individuals, comprehensive analyses were conducted to explore associations between CES levels and age-related diseases, biological age and aging hallmarks. Cox proportional hazards regression models were used to investigate the relationship between CES and the risk of hospitalization for age-related diseases. Linear regression models were employed to explore the associations between CES and the frailty index (FI), Klemera-Doubal method (KDM) biological age acceleration, homeostatic dysregulation (HD), C-reactive protein (CRP), white blood cell (WBC) count, and telomere length. RESULTS: The analyses revealed a significant association between higher CES levels and a decreased risk of hospitalization for age-related diseases in later life. After adjustments for covariates, the hazard ratio for age-related diseases was 0.87 (95 % confidence interval, 0.83-0.91, p < 0.001) in those with the highest CES level compared to those with the lowest CES level. Participants with the highest CES level exhibited lower FI scores (coefficient = -0.033, p < 0.001), reduced CRP level (coefficient = -0.097, p < 0.05) and lower WBC counts (coefficient = -0.034, p < 0.05). Stratified analyses based on genetic susceptibility further elucidated the protective role of CES against age-related diseases. CONCLUSION: These findings underscore the potential of early interventions targeting CES to promote healthy aging and alleviating the burden of age-related diseases.

Association Between Phenotypic Age and the Risk of Mortality in Patients With Heart Failure: A Retrospective Cohort Study.

BACKGROUND: Chronological age (CA) is an imperfect proxy for the true biological aging state of the body. As novel measures of biological aging, Phenotypic age (PhenoAge) and Phenotypic age acceleration (PhenoAgeAccel), have been shown to identify morbidity and mortality risks in the general population. HYPOTHESIS: PhenoAge and PhenoAgeAccel might be associated with mortality in heart failure (HF) patients. METHODS: This cohort study extracted adult data from the National Health and Nutrition Examination Survey (NHANES) databases. Weighted univariable and multivariable Cox models were performed to analyze the effect of PhenoAge and PhenoAgeAccel on all-cause mortality in HF patients, and hazard ratio (HR) with 95% confidence intervals (CI) was calculated. RESULTS: In total, 845 HF patients were identified, with 626 all-cause mortality patients. The findings suggested that (1) each 1- and 10-year increase in PhenoAge were associated with a 3% (HR = 1.03, 95% CI: 1.03-1.04) and 41% (HR = 1.41, 95% CI: 1.29-1.54) increased risk of all-cause mortality, respectively; (2) when the PhenoAgeAccel < 0 as reference, the ≥ 0 group was associated with higher risk of all-cause mortality (HR = 1.91, 95% CI = 1.49-2.45). Subgroup analyses showed that (1) older PhenoAge was associated with an increased risk of all-cause mortality in all subgroups; (2) when the PhenoAgeAccel < 0 as a reference, PhenoAgeAccel ≥ 0 was associated with a higher risk of all-cause mortality in all subgroups. CONCLUSION: Older PhenoAge was associated with an increased risk of all-cause mortality in HF patients. PhenoAge and PhenoAgeAccel can be used as convenient tools to facilitate the identification of at-risk individuals with HF and the evaluation of intervention efficacy.

Map of epigenetic age acceleration: A worldwide analysis.

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

The association between sleep quality and accelerated epigenetic aging with metabolic syndrome in Korean adults.

BACKGROUND: Healthy sleep is vital for maintaining optimal mental and physical health. Accumulating evidence suggests that sleep loss and disturbances play a significant role in the biological aging process, early onset of disease, and reduced lifespan. While numerous studies have explored the association between biological aging and its drivers, only a few studies have examined its relationship with sleep quality. In this study, we investigated the associations between sleep quality and epigenetic age acceleration using whole blood samples from a cohort of 692 Korean adults. Sleep quality of each participant was assessed using the validated Pittsburgh Sleep Quality Index (PSQI), which encompassed seven domains: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication, and daytime dysfunction. Four epigenetic age accelerations (HorvathAgeAccel, HannumAgeAccel, PhenoAgeAccel, and GrimAgeAccel) and the pace of aging, DunedinPACE, were investigated for epigenetic aging estimates. RESULTS: Among the 692 participants (good sleepers [n = 441, 63.7%]; poor sleepers [n = 251, 36.3%]), DunedinPACE was positively correlated with PSQI scores in poor sleepers ( γ =0.18, p < 0.01). GrimAgeAccel ( ß =0.18, p = 0.02) and DunedinPACE ( ß =0.01, p < 0.01) showed a statistically significant association with PSQI scores only in poor sleepers by multiple linear regression. In addition, every one-point increase in PSQI was associated with a 15% increase in the risk of metabolic syndrome (MetS) among poor sleepers (OR = 1.15, 95% CI = 1.03-1.29, p = 0.011). In MetS components, a positive correlation was observed between PSQI score and fasting glucose ( γ = 0.19, p < 0.01). CONCLUSIONS: This study suggests that worsening sleep quality, especially in poor sleepers, is associated with accelerated epigenetic aging for GrimAgeAccel and DundinePACE with risk of metabolic syndrome. This finding could potentially serve as a promising strategy for preventing age-related diseases in the future.

Effects of walking on epigenetic age acceleration: a Mendelian randomization study.

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.

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

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

Causal effects of denture wearing on epigenetic age acceleration and the mediating pathways: a mendelian randomization study.

BACKGROUND: The epigenetic-age acceleration (EAA) represents the difference between chronological age and epigenetic age, reflecting accelerated biological aging. Observational studies suggested that oral disorders may impact DNA methylation patterns and aging, but their causal relationship remains largely unexplored. This study aimed to investigate potential causal associations between dental traits and EAA, as well as to identify possible mediators. METHODS: Using summary statistics of genome-wide association studies of predominantly European ancestry, we conducted univariable and multivariable Mendelian randomization (MR) to estimate the overall and independent effects of ten dental traits (dentures, bleeding gums, painful gums, loose teeth, toothache, ulcers, periodontitis, number of teeth, and two measures of caries) on four EAA subtypes (GrimAge acceleration [GrimAA], PhenoAge acceleration [PhenoAA], HannumAge acceleration [HannumAA] and intrinsic EAA [IEAA]), and used two-step Mendelian randomization to evaluate twelve potential mediators of the associations. Comprehensive sensitivity analyses were used to verity the robustness, heterogeneity, and pleiotropy. RESULTS: Univariable inverse variance weighted MR analyses revealed a causal effect of dentures on greater GrimAA (ß: 2.47, 95% CI: 0.93-4.01, p = 0.002), PhenoAA (ß: 3.00, 95% CI: 1.15-4.85, p = 0.001), and HannumAA (ß: 1.96, 95% CI: 0.58-3.33, p = 0.005). In multivariable MR, the associations remained significant after adjusting for periodontitis, caries, number of teeth and bleeding gums. Three out of 12 aging risk factors were identified as mediators of the association between dentures and EAA, including body mass index, body fat percentage, and waist circumference. No evidence for reverse causality and pleiotropy were detected (p > 0.05). CONCLUSIONS: Our findings supported the causal effects of genetic liability for denture wearing on epigenetic aging, with partial mediation by obesity. More attention should be paid to the obesity-monitoring and management for slowing EAA among denture wearers.

Causal benefits of 25 dietary intakes on epigenetic ageing: a Mendelian randomisation study.

DNA methylation GrimAge acceleration (DMGA) and intrinsic epigenetic age acceleration (IEAA) are important physiological markers for assessing the ageing process. Evidence from cross-sectional studies suggests that some dietary intake is associated with DMGA and IEAA. However, the causal relationship between them has yet to be elucidated. This Mendelian randomisation study uses genetic variants associated with different dietary intakes as instrumental variables to explore the causal benefits of multiple dietary intakes on DMGA and IEAA. Cheese intake, dark chocolate intake, average weekly red wine intake, dried fruit intake, fresh fruit intake, porridge intake, cereal intake, and liver intake had a negative causal association with DMGA, and poultry intake and doughnut intake had a positive causal association with DMGA (p < 0.05). Muesli and bran cereal intake had a negative causal association with IEAA, and pineapple intake had a positive causal association with IEAA (p < 0.05). Dietary intake positively causally associated with IEAA or DMGA may have accelerated biological ageing; conversely, dietary intake negatively causally associated with IEAA or DMGA may have contributed to delaying biological ageing. Based on genetic evidence, this study demonstrated some significant causal benefits of dietary intake on DMGA and IEAA, suggesting the possibility of intervening in DNA methylation acceleration and epigenetic age acceleration by adjusting these food intakes, thereby promoting health and delaying ageing. However, the findings of this study are exploratory and preliminary and need to be supported and validated by evidence from further clinical studies and mechanistic studies.

Association of visceral adiposity index with phenotypic age acceleration: insight from NHANES 1999-2010.

BACKGROUND: Obesity correlates with accelerated aging. This study aims to investigate the association between the visceral adiposity index (VAI) and accelerated aging. METHODS: Biological aging was evaluated by phenotypic age acceleration (PhenoAgeAccel). Utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2010, we employed weighted multivariable logistic regression models, along with subgroup analysis, to examine the association between VAI and PhenoAgeAccel. Moreover, smooth curve fitting was utilized to identify potential nonlinear association, complemented by a two-piece linear regression model to investigate threshold effects. RESULTS: Of the included 11,340 participants aged 20 years and older, the mean (95% CI) age was 46.569 (45.946, 47.191) years, and 49.189% were male. The mean (95% CI) VAI for all participants was 2.176 (2.114, 2.238), and the mean (95% CI) PhenoAgeAccel was -6.306 (-6.618, -5.994) years. In the fully adjusted model, each incremental unit increase of VAI was associated with a 0.312-year increase in PhenoAgeAccel (ß = 0.312, 95% CI: 0.217, 0.408). This positive association was more statistically significant among individuals with cancer. Furthermore, a segmented association was observed between VAI and PhenoAgeAccel, with a turning point identified at 10.543. Below this threshold, VAI exhibited a positive correlation with PhenoAgeAccel (ß = 0.617, 95% CI: 0.499, 0.735), while beyond it, the association became nonsignificant. CONCLUSION: This study demonstrated a positive association between VAI and accelerated aging within a nationally representative population. The findings suggest that controlling adiposity may exert anti-aging effects and help prevent aging-related diseases.

Epigenetic age acceleration and the risk of frailty, and persistent activities of daily living (ADL) disability.

BACKGROUND: Epigenetic ageing is among the most promising ageing biomarkers and may be a useful marker of physical function decline, beyond chronological age. This study investigated whether epigenetic age acceleration (AA) is associated with the change in frailty scores over 7 years and the 7-year risk of incident frailty and persistent Activities of Daily Living (ADL) disability among 560 Australians (50.7% females) aged ≥70 years. METHODS: Seven AA indices, including GrimAge, GrimAge2, FitAge and DunedinPACE, were estimated from baseline peripheral-blood DNA-methylation. Frailty was assessed using both the 67-item deficit-accumulation frailty index (FI) and Fried phenotype (Fried). Persistent ADL disability was defined as loss of ability to perform one or more basic ADLs for at least 6 months. Linear mixed models and Cox proportional-hazard regression models were used as appropriate. RESULTS: Accelerated GrimAge, GrimAge2, FitAge and DunedinPACE at baseline were associated with increasing FI scores per year (adjusted-Beta ranged from 0.0015 to 0.0021, P < 0.05), and accelerated GrimAge and GrimAge2 were associated with an increased risk of incident FI-defined frailty (adjusted-HRs 1.43 and 1.39, respectively, P < 0.05). The association between DunedinPACE and the change in FI scores was stronger in females (adjusted-Beta 0.0029, P 0.001 than in males (adjusted-Beta 0.0002, P 0.81). DunedinPACE, but not the other AA measures, was also associated with worsening Fried scores (adjusted-Beta 0.0175, P 0.04). No associations were observed with persistent ADL disability. CONCLUSION: Epigenetic AA in later life is associated with increasing frailty scores per year and the risk of incident FI-defined frailty.

Inflammation, nutrition, and biological aging: The prognostic role of Naples prognostic score in nonalcoholic fatty liver disease outcomes.

AIM: This study aimed to evaluate the prognostic value of the Naples Prognostic Score (NPS) for predicting mortality in patients with nonalcoholic fatty liver disease (NAFLD) and compare its performance with established non-invasive fibrosis scores, including the fibrosis-4 index (FIB-4) and NAFLD fibrosis score (NFS). METHODS: Data from 10,035 NAFLD patients identified within the 1999-2018 National Health and Nutrition Examination Survey (NHANES) were analyzed. Cox regression models assessed the association between NPS and all-cause mortality, while time-dependent ROC analysis compared its predictive accuracy with FIB-4 and NFS. Mediation analysis explored the role of phenotypic age acceleration (PhenoAgeAccel). RESULTS: NPS was significantly associated with all-cause mortality, with each point increase corresponding to a 26 % increased risk (HR = 1.26, 95 % CI: 1.19-1.34). NPS demonstrated comparable predictive performance to FIB-4 and NFS, with further improvement when combined with either score (HRs of 2.03 and 2.11 for NPS + FIB-4 and NPS + NFS, respectively). PhenoAgeAccel mediated 31.5 % of the effect of NPS on mortality. CONCLUSIONS: This study found that NPS has the potential to be an independent, cost-effective, and reliable novel prognostic indicator for NAFLD that may complement existing tools and help improve risk stratification and management strategies for NAFLD, thereby preventing adverse outcomes.

Effect of Modifiable Lifestyle Factors on Biological Aging.

Biological age is a concept that uses bio-physiological parameters to account for individual heterogeneity in the biological processes driving aging and aims to enhance the prediction of age-related clinical conditions compared to chronological age. Although engaging in healthy lifestyle behaviors has been linked to a lower mortality risk and a reduced incidence of chronic diseases, it remains unclear to what extent these health benefits result from slowing the pace of the biological aging process. This short review summarized how modifiable lifestyle factors - including diet, physical activity, smoking, alcohol consumption, and the aggregate of multiple healthy behaviors - were associated with established estimates of biological age based on clinical or cellular/molecular markers, including Klemera-Doubal Method biological age, homeostatic dysregulation, phenotypic age, DNA methylation age, and telomere length. In brief, the available studies tend to show a consistent association of lifestyle factors with physiological measures of biological age, while findings regarding molecular-based metrics vary. The limited evidence highlights the need for further research in this field, particularly with a life-course approach.

Epigenetic age acceleration in follicular fluid and markers of ovarian response among women undergoing IVF.

STUDY QUESTION: Are markers of epigenetic age acceleration in follicular fluid associated with outcomes of ovarian stimulation? SUMMARY ANSWER: Increased epigenetic age acceleration of follicular fluid using the Horvath clock, but not other epigenetic clocks (GrimAge and Granulosa Cell), was associated with lower peak estradiol levels and decreased number of total and mature oocytes. WHAT IS KNOWN ALREADY: In granulosa cells, there are inconsistent findings between epigenetic age acceleration and ovarian response outcomes. STUDY DESIGN, SIZE, DURATION: Our study included 61 women undergoing IVF at an academic fertility clinic in the New England area who were part of the Environment and Reproductive Health Study (2006-2016). PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants provided a follicular fluid sample during oocyte retrieval. DNA methylation of follicular fluid was assessed using a genome-wide methylation screening tool. Three established epigenetic clocks (Horvath, GrimAge, and Granulosa Cell) were used to predict DNA-methylation-based epigenetic age. To calculate the age acceleration, we regressed epigenetic age on chronological age and extracted the residuals. The association between epigenetic age acceleration and ovarian response outcomes (peak estradiol levels, follicle stimulation hormone, number of total, and mature oocytes) was assessed using linear and Poisson regression adjusted for chronological age, three surrogate variables (to account for cellular heterogeneity), race, smoking status, initial infertility diagnosis, and stimulation protocol. MAIN RESULTS AND ROLE OF CHANCE: Compared to the median chronological age of our participants (34 years), the Horvath clock predicted, on an average, a younger epigenetic age (median: 24.2 years) while the GrimAge (median: 38.6 years) and Granulosa Cell (median: 39.0 years) clocks predicted, on an average, an older epigenetic age. Age acceleration based on the Horvath clock was associated with lower peak estradiol levels (-819.4 unit decrease in peak estradiol levels per standard deviation increase; 95% CI: -1265.7, -373.1) and fewer total (% change in total oocytes retrieved per standard deviation increase: -21.8%; 95% CI: -37.1%, -2.8%) and mature oocytes retrieved (% change in mature oocytes retrieved per standard deviation increase: -23.8%; 95% CI: -39.9%, -3.4%). The age acceleration based on the two other epigenetic clocks was not associated with markers of ovarian response. LIMITATIONS, REASONS FOR CAUTION: Our sample size was small and we did not specifically isolate granulosa cells from follicular fluid samples so our samples could have included mixed cell types. WIDER IMPLICATIONS OF THE FINDINGS: Our results highlight that certain epigenetic clocks may be predictive of ovarian stimulation outcomes when applied to follicular fluid; however, the inconsistent findings for specific clocks across studies indicate a need for further research to better understand the clinical utility of epigenetic clocks to improve IVF treatment. STUDY FUNDING/COMPETING INTEREST(S): The study was supported by grants ES009718, ES022955, ES000002, and ES026648 from the National Institute of Environmental Health Sciences (NIEHS) and a pilot grant from the NIEHS-funded HERCULES Center at Emory University (P30 ES019776). RBH was supported by the Emory University NIH Training Grant (T32-ES012870). TRIAL REGISTRATION NUMBER: N/A.

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

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

Signatures of epigenetic, biological and mitotic age acceleration and telomere shortening are associated with arsenic-induced skin lesions.

Chronic arsenic exposure is a global health hazard significantly associated with the development of deleterious cutaneous changes and increased keratinocyte cancer risk. Although arsenic exposure is associated with broad-scale cellular and molecular changes, gaps exist in understanding how these changes impact the skin and facilitate malignant transformation. Recently developed epigenetic "clocks" can accurately predict chronological, biological and mitotic age, as well as telomere length, on the basis of tissue DNA methylation state. Deviations of predicted from expected age (epigenetic age dysregulation) have been associated with numerous complex diseases, increased all-cause mortality and higher cancer risk. We investigated the ability of these algorithms to detect molecular changes associated with chronic arsenic exposure in the context of associated skin lesions. To accomplish this, we utilized a multi-algorithmic approach incorporating seven "clocks" (Horvath, Skin&Blood, PhenoAge, PCPhenoAge, GrimAge, DNAmTL and epiTOC2) to analyze peripheral blood of pediatric and adult cohorts of arsenic-exposed (n = 84) and arsenic-naïve (n = 33) individuals, among whom n = 18 were affected by skin lesions. Arsenic-exposed adults with skin lesions exhibited accelerated epigenetic (Skin&Blood: + 7.0 years [95% CI 3.7; 10.2], q = 6.8 × 10-4), biological (PhenoAge: + 5.8 years [95% CI 0.7; 11.0], q = 7.4 × 10-2, p = 2.8 × 10-2) and mitotic age (epiTOC2: + 19.7 annual cell divisions [95% CI 1.8; 37.7], q = 7.4 × 10-2, p = 3.2 × 10-2) compared to healthy arsenic-naïve individuals; and accelerated epigenetic age (Skin&Blood: + 2.8 years [95% CI 0.2; 5.3], q = 2.4 × 10-1, p = 3.4 × 10-2) compared to lesion-free arsenic-exposed individuals. Moreover, lesion-free exposed adults exhibited accelerated Skin&Blood age (+ 4.2 [95% CI 1.3; 7.1], q = 3.8 × 10-2) compared to their arsenic-naïve counterparts. Compared to the pediatric group, arsenic-exposed adults exhibited accelerated epigenetic (+ 3.1 to 4.4 years (95% CI 1.2; 6.4], q = 2.4 × 10-4-3.1 × 10-3), biological (+ 7.4 to 7.8 years [95% CI 3.0; 12.1] q = 1.6 × 10-3-2.8 × 10-3) and mitotic age (+ 50.0 annual cell divisions [95% CI 15.6; 84.5], q = 7.8 × 10-3), as well as shortened telomere length (- 0.23 kilobases [95% CI - 0.13; - 0.33], q = 2.4 × 10-4), across all seven algorithms. We demonstrate that lifetime arsenic exposure and presence of arsenic-associated skin lesions are associated with accelerated epigenetic, biological and mitotic age, and shortened telomere length, reflecting altered immune signaling and genomic regulation. Our findings highlight the usefulness of DNA methylation-based algorithms in identifying deleterious molecular changes associated with chronic exposure to the heavy metal, serving as potential prognosticators of arsenic-induced cutaneous malignancy.