Intrinsic Epigenetic Age Acceleration Research Articles

Causal effects of cardiovascular health on five epigenetic clocks

BackgroundThis work delves into the relationship between cardiovascular health (CVH) and aging. Previous studies have shown an association of ideal CVH with a slower aging rate, measured by epigenetic age acceleration (EAA). However, the causal relationship between CVH and EAA has remained unexplored.Methods and resultsWe performed genome-wide association studies (GWAS) on the (12-point) CVH score and its components using the Taiwan Biobank data, in which weighted genetic risk scores were treated as instrumental variables. Subsequently, we conducted a one-sample Mendelian Randomization (MR) analysis with the two-stage least-squares method on 2383 participants to examine the causal relationship between the (12-point) CVH score and EAA. As a result, we observed a significant causal effect of the CVH score on GrimAge acceleration (GrimEAA) (β [SE]: − 0.993 [0.363] year; p = 0.0063) and DNA methylation-based plasminogen activator inhibitor-1 (DNAmPAI-1) (β [SE]: − 0.294 [0.099] standard deviation (sd) of DNAmPAI-1; p = 0.0030). Digging individual CVH components in depth, the ideal total cholesterol score (0 [poor], 1 [intermediate], or 2 [ideal]) was causally associated with DNAmPAI-1 (β [SE]: − 0.452 [0.150] sd of DNAmPAI-1; false discovery rate [FDR] q = 0.0102). The ideal body mass index (BMI) score was causally associated with GrimEAA (β [SE]: − 2.382 [0.952] years; FDR q = 0.0498) and DunedinPACE (β [SE]: − 0.097 [0.030]; FDR q = 0.0044). We also performed a two-sample MR analysis using the summary statistics from European GWAS. We observed that the (12-point) CVH score exhibits a significant causal effect on Horvath’s intrinsic epigenetic age acceleration (β [SE]: − 0.389 [0.186] years; p = 0.036) and GrimEAA (β [SE]: − 0.526 [0.244] years; p = 0.031). Furthermore, we detected causal effects of BMI (β [SE]: 0.599 [0.081] years; q = 2.91E-12), never smoking (β [SE]: − 2.981 [0.524] years; q = 1.63E-7), walking (β [SE]: − 4.313 [1.236] years; q = 0.004), and dried fruit intake (β [SE]: − 1.523 [0.504] years; q = 0.013) on GrimEAA in the European population.ConclusionsOur research confirms the causal link between maintaining an ideal CVH and epigenetic age. It provides a tangible pathway for individuals to improve their health and potentially slow aging.

Causal association of epigenetic age acceleration and risk of subacute thyroiditis: a bidirectional Mendelian randomization study

BackgroundEpigenetic age accelerations (EAAs) are a promising new avenue of research, yet their investigation in subacute thyroiditis (SAT) remains scarce. Our study endeavors to fill this void by exploring the potential causal association between EAAs and SAT.MethodsOur study utilized publicly available genome-wide association study (GWAS) data of European ancestry to conduct a bidirectional Mendelian randomization (MR) study. Five MR methods were employed to measure causal association between EAAs and SAT multiple analyses were utilized to perform quality control.ResultsOur study evaluated causal association between SAT and four EAAs, included GrimAge acceleration (GrimAA), Hannum age acceleration (HannumAA), PhenoAge acceleration (PhenoAA), intrinsic epigenetic age acceleration (IEAA). Results showed that there is a significant causal association between PhenoAA and SAT (OR 1.109, 95% CI 1.000–1.228, p = 0.049, by IVW method). On the contrary, SAT was associated with IEAA (OR 0.933, 95% CI 0.884–0.984, p = 0.011, by IVW method; OR 0.938, 95% CI 0.881–0.998, p = 0.043, by weighted median method). Leave-one-out sensitivity analysis, heterogeneity test, pleiotropy test, and MR-PRESSO analysis provide good quality control.ConclusionThe bidirectional MR analysis concluded that an increase in PhenoAA was correlated with a higher risk of SAT, indicating a potential causal relationship between PhenoAA and risk of SAT. Conversely, SAT was found to be closely associated with IEAA, suggesting that SAT may accelerate the aging process. Slowing down biological aging has emerged as a new research direction in curbing SAT.

Differential white blood cell count and epigenetic clocks: a bidirectional Mendelian randomization study

BackgroundHuman aging and white blood cell (WBC) count are complex traits influenced by multiple genetic factors. Predictors of chronological age have been developed using epigenetic clocks. However, the bidirectional causal effects between epigenetic clocks and WBC count have not been fully examined.MethodsThis study employed Mendelian randomization (MR) to analyze summary statistics from four epigenetic clocks involving 34,710 participants, alongside data from the Blood Cell Consortium encompassing 563,946 individuals. We primarily explored bidirectional causal relationships using the random-effects inverse-variance weighted method, supplemented by additional MR methods for comprehensive analysis. Additionally, multivariate MR was applied to investigate independent effects of WBC count on epigenetic age acceleration.ResultsIn the two-sample univariate MR (UVMR) analysis, we observed that a decrease in lymphocyte count markedly accelerated aging according to the PhenoAge, GrimAge, and HannumAge metrics (all P < 0.01, β < 0), though it did not affect Intrinsic Epigenetic Age Acceleration (IEAA). Conversely, an increase in neutrophil count significantly elevated PhenoAge levels (β: 0.38; 95% CI 0.14, 0.61; P = 1.65E−03 < 0.01). Reverse MR revealed no significant causal impacts of epigenetic clocks on overall WBC counts. Furthermore, in multivariate MR, the impact of lymphocyte counts on epigenetic aging metrics remained statistically significant. We also identified a marked causal association between neutrophil counts and PhenoAge, GrimAge, and HannumAge, with respective results showing strong associations (PhenoAge β: 0.78; 95% CI 0.47, 1.09; P = 8.26E−07; GrimAge β: 0.55; 95% CI 0.31, 0.79; P = 5.50E−06; HannumAge β: 0.42; 95% CI 0.18, 0.67; P = 6.30E−04). Likewise, eosinophil cell count demonstrated significant association with HannumAge (β: 0.33; 95% CI 0.13, 0.53; P = 1.43E−03 < 0.01).ConclusionThese findings demonstrated that within WBCs, lymphocyte and neutrophil counts exert irreversible and independent causal effects on the acceleration of PhenoAge, GrimAge, and HannumAge. Our findings highlight the critical role of WBCs in influencing epigenetic clocks and underscore the importance of considering immune parameters when interpreting epigenetic age.

Mendelian randomization implicates causal association between epigenetic age acceleration and age-related eye diseases or glaucoma endophenotypes

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

Impact of childhood maltreatment on aging: a comprehensive Mendelian randomization analysis of multiple age-related biomarkers

BackgroundChildhood maltreatment (CM) is linked to long-term adverse health outcomes, including accelerated biological aging and cognitive decline. This study investigates the relationship between CM and various aging biomarkers: telomere length, facial aging, intrinsic epigenetic age acceleration (IEAA), GrimAge, HannumAge, PhenoAge, frailty index, and cognitive performance.MethodsWe conducted a Mendelian randomization (MR) study using published GWAS summary statistics. Aging biomarkers included telomere length (qPCR), facial aging (subjective evaluation), and epigenetic age markers (HannumAge, IEAA, GrimAge, PhenoAge). The frailty index was calculated from clinical assessments, and cognitive performance was evaluated with standardized tests. Analyses included Inverse-Variance Weighted (IVW), MR Egger, and Weighted Median (WM) methods, adjusted for multiple comparisons.ResultsCM was significantly associated with shorter telomere length (IVW: β = − 0.1, 95% CI − 0.18 to − 0.02, pFDR = 0.032) and increased HannumAge (IVW: β = 1.33, 95% CI 0.36 to 2.3, pFDR = 0.028), GrimAge (IVW: β = 1.19, 95% CI 0.19 to 2.2, pFDR = 0.040), and PhenoAge (IVW: β = 1.4, 95% CI 0.12 to 2.68, pFDR = 0.053). A significant association was also found with the frailty index (IVW: β = 0.31, 95% CI 0.13 to 0.49, pFDR = 0.006). No significant associations were found with facial aging, IEAA, or cognitive performance.ConclusionsCM is linked to accelerated biological aging, shown by shorter telomere length and increased epigenetic aging markers. CM was also associated with increased frailty, highlighting the need for early interventions to mitigate long-term effects. Further research should explore mechanisms and prevention strategies.

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.

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

BackgroundThe 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.MethodsUsing 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.ResultsUnivariable inverse variance weighted MR analyses revealed a causal effect of dentures on greater GrimAA (β: 2.47, 95% CI: 0.93–4.01, p = 0.002), PhenoAA (β: 3.00, 95% CI: 1.15–4.85, p = 0.001), and HannumAA (β: 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).ConclusionsOur 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.

DNA methylation-based biological age and time to relapse in triple negative breast cancer.

e13126 Background: Triple negative breast cancer (TNBC) represents 15% of all breast cancer cases and is one of the most aggressive forms of breast cancer with a poorer prognosis. Due to the lack of receptors, TNBC is not amendable to hormonal or anti-HER2 therapies and current gene expression arrays have limited clinical utility in TNBC. The identification of biomarkers associated with TNBC may aid in elucidating the underlying biological mechanisms of this disease and may also have implications for risk stratification, diagnosis, and prognosis of TNBC. The purpose of this study was to investigate the association between markers of biological aging and time to relapse in TNBC. Methods: DNA methylation and clinical data from a publicly available dataset (GSE141441) were used in this analysis. Breast tissue specimens in female TNBC patients who received (n=56) and who did not receive (n=110) chemotherapy underwent DNA methylation profiling using the Illumina Infinium HumanMethylation450K BeadChip. Five DNA methylation-based biological age metrics were calculated: intrinsic epigenetic age acceleration (IEAA), extrinsic epigenetic age acceleration (EEAA), PhenoAge acceleration (PhenoAA), GrimAge acceleration (GrimAA), and DunedinPACE (Pace of Aging Calculated from the Epigenome). Multiple linear and quantile regression analyses were performed to examine the association between the aging metrics and time to TNBC relapse. Interaction and stratified analyses by Ki-67 was additionally performed. Results: After adjusting for chronological age, GrimAA ( P=0.024) and DunedinPACE ( P=0.019) were negatively associated with time to relapse among patients who did not receive chemotherapy. Specifically, a 1-year increase in GrimAA and 1 unit increase in the pace of aging were associated with a 1.77-month and a 53.62-month shorter relapse of TNBC, respectively. Additionally, Ki-67 significantly modified the association between IEAA ( P=0.023) and DunedinPACE ( P=0.035) among patients who received chemotherapy with a 2.75- and a 42.17-month shorter relapse of TNBC among those with a Ki-67 index greater than 50% per unit increase in IEAA and DunedinPACE, respectively. Conclusions: We observed DNA methylation markers of biological age were associated with time to relapse in TNBC patients and these associations were modified by Ki-67. These biomarkers may have prognostic utility in TNBC relapse and potentially, may aid in oncological precision medicine efforts for personalized treatment regimens and surveillance. [Table: see text]

Chimeric antigen receptor T-cell therapy in B-cell malignancies and DNA-methylation–based biological aging.

2562 Background: Chimeric antigen receptor T-cell (CAR T-cell) therapy, a type of cancer immunotherapy which leverages genetically altered T cells to target cancer cells, has shown to be an effective option for patients with acute lymphoblastic leukemia (ALL) and non-Hodgkin lymphoma (NHL). Despite its growing use, the effect of CAR T-cell therapy on the aging process remains limited and findings may have implications for disease relapse and age-related diseases among survivors. The purpose of this study was to investigate the association between CAR T-cell therapy and markers of biological aging. Methods: DNA methylation and clinical data from a publicly available dataset (GSE179414) were used in this analysis. Transduced and untransduced T cells from patients with ALL (n=77) and NHL (n=37) underwent DNA methylation profiling using the Illumina Infinium MethylationEPIC BeadChip. Six DNA methylation-based biological age metrics were calculated: intrinsic epigenetic age acceleration (IEAA), extrinsic epigenetic age acceleration (EEAA), PhenoAge acceleration (PhenoAA), GrimAge acceleration (GrimAA), telomere length attrition (TLA), and DunedinPACE (Pace of Aging Calculated from the Epigenome). Multiple linear regression analyses were performed to examine the association between CAR T-cell therapy and the aging metrics by B-cell malignancy. Interaction and stratified analyses by chronological age was additionally performed. Results: DunedinPACE ( P=0.002) was positively associated with CAR T-cell therapy among patients with ALL with an approximately 1-month higher pace of aging in transduced T cells compared to untransduced T cells after adjusting for chronological age and sex. Moreover, chronological age significantly ( P=0.016) modified the association between CAR T-cell therapy and TLA among ALL patients. Specifically, transduced T cells exhibited a 0.46 higher ( P=0.053) and a 0.39 lower ( P=0.142) rate of TLA among patients 16 years of age or older and those younger than 16 years of age, respectively. Conclusions: We observed CAR T-cell therapy was associated with greater biological aging as estimated from DNA methylation among ALL patients and these associations are modified by chronological age. These findings suggest CAR T-cell therapy may be associated with age-related changes to the epigenome in ALL patients and strategies to limit or reverse this effect may have implications for the aging process in cancer survivors. [Table: see text]

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

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

A Comparison of 5 Measures of Accelerated Biological Aging and Their Association With Incident Cardiovascular Disease: The CARDIA Study.

Accelerated biological aging is an increasingly popular way to track the acceleration of biology over time that may not be captured by calendar time. Biological aging has been linked to external and internal chronic stressors and has the potential to be used clinically to understand a person's personalized functioning and predict future disease. We compared the association of different measures of biological aging and incident cardiovascular disease (CVD) overall and by race. We used multiple informants models to compare the strength of clinical marker-derived age acceleration, 5 measures of epigenetic age acceleration (intrinsic and extrinsic epigenetic age acceleration, GrimAge acceleration, and PhenoAge acceleration), and 1 established clinical predictor of future CVD, Framingham 10-year risk score, with incident CVD over an 11-year period (2007-2018). Participants were 913 self-identified Black or White (41% and 59%, respectively) female or male (51% and 49%, respectively) individuals enrolled in the US-based CARDIA (Coronary Artery Risk Development in Young Adults) cohort study. The analytic baseline for this study was the 20-year follow-up examination (2005-2006; median age 45 years). We also included race-specific analysis. We found that all measures were modestly correlated with one another. However, clinical marker-derived age acceleration and Framingham 10-year risk score were more strongly associated with incident CVD than all the epigenetic measures. Clinical marker-derived age acceleration and Framingham 10-year risk score were not significantly different than one another in their association with incident CVD. The type of accelerated aging measure should be taken into consideration when comparing their association with clinical outcomes. A multisystem clinical composite shows associations with incident CVD equally to a well-known clinical predictor.

Abstract P413: Epigenetic Age Acceleration Measures Predict Cardiovascular Outcomes in Diabetic Kidney Disease

Introduction: Cardiovascular disease (CVD) remains the leading cause of mortality in the US, highlighting the need for novel approaches to its prediction, prevention, and management. Epigenetic age acceleration (EAA), or increased DNA methylation-based age relative to chronological age, is a promising biomarker of disease risk. While previous studies have prospectively linked EAA to CVD, recent work in patients with end-stage kidney disease showed no association between EAA and mortality from CVD, underscoring a need for more research across patient populations. Hypothesis: EAA measures, specifically intrinsic epigenetic age acceleration (IEAA), extrinsic epigenetic age acceleration (EEAA), phenotypic epigenetic age acceleration (PhenoAA), and Grim epigenetic age acceleration (GrimAA), are associated with incident CVD in diabetic kidney disease (DKD). Methods: In a subset of 496 participants from the Chronic Renal Insufficiency Cohort with DKD, selected based on kidney function decline over follow-up (large versus small), we examined four EAA measures: IEAA, EEAA, PhenoAA, and GrimAA. GrimAA is comprised of eight DNA methylation-based biomarkers, including plasminogen activator inhibitor-1 age acceleration (PAI-1 AA ) and tissue inhibitor of matrix metalloproteinase (TIMP-1 AA ), which were also assessed. Primary outcomes were incident CVD, atherosclerotic CVD, and CVD mortality; secondary outcomes included myocardial infarction, congestive heart failure (CHF), cerebrovascular accident, and peripheral artery disease (PAD). Cox proportional models tested associations between the EAA measures and CVD endpoints after adjusting for baseline demographics, clinical center, kidney function decline as a study design feature, lifestyle, and clinical risk factors. Results: Participants were predominantly male (63%), with a median age of 57 years, median eGFR of 44 mL/min/1.73m 2 , and mean hemoglobin A1c of 8.0%. After adjusting for multiple testing, each standard deviation increase in GrimAA was associated with incident CVD (HR=1.27; 95% confidence interval [CI], 1.08-1.50; p=0.012) and PAD (HR=1.65; 95% CI, 1.15-2.37; p=0.006). Likewise, PAI-1 AA was significantly associated with incident CVD (HR=1.24; 95% CI, 1.06-1.44; p=0.006) and PAD (HR=1.46; 95% CI, 1.17-1.81; p=0.001), while TIMP-1 AA was associated with CHF (HR=1.32; 95% CI, 1.09-1.60; p=0.005). Nominally significant associations between IEAA and atherosclerotic CVD were also identified (HR=1.24; 95% CI, 1.00-1.53; p=0.049). Similarly, EEAA was nominally associated with incident CVD (HR 1.22; 95% CI, 1.01-1.47, p=0.039). Conclusion: EAA measures, notably GrimAA, are promising CVD biomarkers in DKD patients. Associations of GrimAA components PAI-1 AA and TIMP-1 AA with incident CVD add to the accumulating evidence of their predictive and therapeutic potential.

GrimAge is elevated in older adults with mild COVID-19 an exploratory analysis.

COVID-19 has been contained; however, the side effects associated with its infection continue to be a challenge for public health, particularly for older adults. On the other hand, epigenetic status contributes to the inter-individual health status and is associated with COVID-19 severity. Nevertheless, current studies focus only on severe COVID-19. Considering that most of the worldwide population developed mild COVID-19 infection. In the present exploratory study, we aim to analyze the association of mild COVID-19 with epigenetic ages (HorvathAge, HannumAge, GrimAge, PhenoAge, SkinAge, and DNAmTL) and clinical variables obtained from a Mexican cohort of older adults. We found that all epigenetic ages significantly differ from the chronological age, but only GrimAge is elevated. Additionally, both the intrinsic epigenetic age acceleration (IEAA) and the extrinsic epigenetic age acceleration (EEAA) are accelerated in all patients. Moreover, we found that immunological estimators and DNA damage were associated with PhenoAge, SkinBloodHorvathAge, and HorvathAge, suggesting that the effects of mild COVID-19 on the epigenetic clocks are mainly associated with inflammation and immunology changes. In conclusion, our results show that the effects of mild COVID-19 on the epigenetic clock are mainly associated with the immune system and an increase in GrimAge, IEAA, and EEAA.

Epigenetic aging differentially impacts breast cancer risk by self-reported race.

Breast cancer (BrCa) is the most common cancer for women globally. BrCa incidence varies by age and differs between racial groups, with Black women having an earlier age of onset and higher mortality compared to White women. The underlying biological mechanisms of this disparity remain uncertain. Here, we address this knowledge gap by examining the association between overall epigenetic age acceleration and BrCa initiation as well as the mediating role of race. We measured whole-genome methylation (866,238 CpGs) using the Illumina EPIC array in blood DNA extracted from 209 women recruited from University Hospitals Cleveland Medical Center. Overall and intrinsic epigenetic age acceleration was calculated-accounting for the estimated white blood cell distribution-using the second-generation biological clock GrimAge. After quality control, 149 BrCa patients and 42 disease-free controls remained. The overall chronological mean age at BrCa diagnosis was 57.4 ± 11.4 years and nearly one-third of BrCa cases were self-reported Black women (29.5%). When comparing BrCa cases to disease-free controls, GrimAge acceleration was 2.48 years greater (p-value = 0.0056), while intrinsic epigenetic age acceleration was 1.72 years higher (p-value = 0.026) for cases compared to controls. After adjusting for known BrCa risk factors, we observed BrCa risk increased by 14% [odds ratio (OR) = 1.14; 95% CI: 1.05, 1.25] for a one-year increase in GrimAge acceleration. The stratified analysis by self-reported race revealed differing ORs for GrimAge acceleration: White women (OR = 1.17; 95% CI: 1.03, 1.36), and Black women (OR = 1.08; 95% CI: 0.96, 1.23). However, our limited sample size failed to detect a statistically significant interaction for self-reported race (p-value >0.05) when examining GrimAge acceleration with BrCa risk. Our study demonstrated that epigenetic age acceleration is associated with BrCa risk, and the association suggests variation by self-reported race. Although our sample size is limited, these results highlight a potential biological mechanism for BrCa risk and identifies a novel research area of BrCa health disparities requiring further inquiry.

Exploring the causal association between epigenetic clocks and menopause age: insights from a bidirectional Mendelian randomization study.

Evidence suggests a connection between DNA methylation (DNAm) aging and reproductive aging. However, the causal relationship between DNAm and age at menopause remains uncertain. Employing established DNAm epigenetic clocks, such as DNAm Hannum age acceleration (Hannum), Intrinsic epigenetic age acceleration (IEAA), DNAm-estimated granulocyte proportions (Gran), DNAm GrimAge acceleration (GrimAgeAccel), DNAm PhenoAge acceleration (PhenoAgeAccel), and DNAm-estimated plasminogen activator inhibitor-1 levels (DNAmPAIadjAge), a bidirectional Mendelian randomization (MR) study was carried out to explore the potential causality between DNAm and menopausal age. The primary analytical method used was the inverse variance weighted (IVW) estimation model, supplemented by various other estimation techniques. DNAm aging acceleration or deceleration, as indicated by Hannum, IEAA, Gran, GrimAgeAccel, PhenoAgeAccel, and DNAmPAIadjAge, did not exhibit a statistically significant causal effect on menopausal age according to forward MR analysis. However, there was a suggestive positive causal association between age at menopause and Gran (Beta = 0.0010; 95% confidence interval (CI): 0.0004, 0.0020) in reverse MR analysis. The observed increase in granulocyte DNAm levels in relation to menopausal age could potentially serve as a valuable indicator for evaluating the physiological status at the onset of menopause.

The Relationship between Telomere Length and Epigenetic Aging with Hematologic Diseases Risk: A Multivariable Mendelian Randomisation Study

Introduction: Aging is a complex phenomenon that involves multifaceted changes, including significant alterations in telomere length and epigenetic aging. When aging affects the hematopoietic system, it leads to a gradual increase in mutations in hematopoietic stem cells, making individuals more susceptible to the development of hematologic diseases. However, due to the limitations of observational studies, such as potential confounding factors and reverse causality, the precise causal direction and magnitude of the relationship between telomere length, epigenetic aging, and the incidence of hematologic diseases remain uncertain. Therefore, we conducted an investigation to determine the causal relevance of telomere length and epigenetic aging in relation to hematologic diseases using Mendelian randomization (MR). Methods: Firstly, we conducted a 2-sample single-variable Mendelian randomization (SVMR) study to examine the genetically predicted effects of telomere length and epigenetic age acceleration, as measured by HannumAge, Horvath Intrinsic Age, PhenoAge, GrimAge, and DNAm PAI-1 (DNA methylation-estimated plasminogen activator inhibitor-1) levels, on multiple hematologic diseases, including anemia, lymphoma, leukemia, myeloproliferative diseases, and hemostasis and coagulation diseases. Additionally, we used lasso regression to exclude multicollinearity in SNPs and subsequently performed multivariable MR using the screened SNPs to adjust for statistically significant risk factors, and MR Bayesian model averaging was performed to rank the significant risk factors based on their genetic evidence (Figure A). Results: Summary data were available for 19 malignant hematological neoplasms and 35 non-malignant hematological disorders, corresponding to 70,813 cases and 12,253,012 controls. Increased telomere length due to germline genetic variation was generally associated with increased risk for hematologic diseases. The strongest associations were observed for lymphoma, lymphoid leukaemia, Hodgkin lymphoma, chronic lymphocytic leukaemia, essential thrombocythaemia, unspecified types of non-Hodgkin lymphoma, multiple myeloma, Non-follicular lymphoma, unspecified iron deficiency, leukaemia, while higher levels of telomere length was associated with a reduced risk of pernicious anaemia (Figure B). Meta-analyzed IVW MR findings suggested that higher PhenoAge acceleration was associated with increased risks of myeloid leukemia, chronic lymphocytic leukemia, and lymphoid leukemia. Conversely, higher PhenoAge acceleration was linked to reduced risks of unspecified disorders of white blood cells and unspecified coagulation defects. Similarly, SVMR showed genetic predisposition for GrimAge acceleration to be associated with increased risks of amyloidosis, unspecified anemias, and myeloid leukemia. Conversely, genetically predicted GrimAge acceleration was associated with reduced risks of hemorrhagic anemia, hemolytic anemias, and idiopathic thrombocytopenic purpura. Furthermore, our findings suggested that elevated HannumAge acceleration increased the risks of lymphoma, leukemia, and lymphoid leukemia.Conversely, higher HannumAge acceleration was associated with a reduced risk of chronic myeloid leukemia. Additionally, higher levels of DNAm PAI-1 were found to be associated with an increased risk of chronic myeloid leukemia. However, there was no evidence of causality between genetically predicted Intrinsic epigenetic age acceleration and the 19 malignant hematological neoplasms and 35 non-malignant hematological disorders mentioned (Figure C). We utilized MVMR-LASSO to estimate the combined effects of telomere length and five epigenetic clocks on hematologic diseases. After adjusting for epigenetic aging, we observed a significant positive association between telomere length and various hematologic diseases, including leukemia, lymphoid leukemia, chronic lymphocytic leukemia, lymphomas, Hodgkin lymphoma, non-follicular lymphoma, unspecified types of non-Hodgkin lymphoma, essential thrombocythemia, and multiple myeloma (Figure D&amp;E). Conclusion: Longer telomeres and epigenetic aging may increase the risk of developing most hematologic malignancies, while simultaneously raising or decreasing the risk of certain non-malignant hematologic diseases.

Genetic relationship between ageing and coronary heart disease: a Mendelian randomization study.

Genetic relationship between ageing and coronary heart disease has not been well investigated. The aim of the study was to explore the association of several ageing biomarkers with the risk of several types of coronary heart disease using the Mendelian randomization approach. Summary data for telomere length, four epigenetic clocks (such as intrinsic epigenetic age acceleration), four types of coronary heart disease (such as myocardial infarction) were collected from the most updated and available genome-wide association studies. Instrumental variables were extracted from the exposure-related summary data according to correlation, independence and exclusivity assumptions. Three Mendelian randomization methods (such as inverse variance weighted) were used for causal inference. Four sensitivity analyses (such as MR-Egger intercept) were performed to prevent horizontal pleiotropy. Inverse variance weighted reported that longer telomere length was related to the lower risk of myocardial infarction, angina pectoris, unstable angina pectoris and coronary atherosclerosis (P = 8.840e-11, P = 9.830e-04, P = 1.539e-05, P = 2.607e-09). Inverse variance weighted also reported that four epigenetic clocks might be not implicated in the risk of these coronary heart diseases. Furthermore, there was not enough evidence to confirm the effect of coronary heart disease on these ageing biomarkers. Longer telomere length, but not the epigenetic clock changes, genetically decreased the risk of coronary heart disease. Considering that telomere length and epigenetic clocks were two independent ageing biomarkers, the correlation between ageing and coronary heart disease might be redefined at the genetic level.

Abstract 13528: A Comparison of Five Measures of Accelerated Biological Aging and Their Association With Incident Cardiovascular Disease: The CARDIA Study

Background: Accelerated biological aging is an increasingly popular way to track the effects of chronic stress over time. Biological aging is linked to external and internal chronic stressors and has the potential to be used clinically to understand a person’s personalized functioning and to predict future disease. Aims: The primary aim was to investigate the similarities and differences in the association of different measures of biological aging and incident cardiovascular disease (CVD). Hypotheses: Our novel predictor, Clinical Marker-Derived Age Acceleration (CAA), and the Framingham Risk Score (FRS) will be most robustly associated with incident CVD, and the associations will be stronger among Black participants. The latter is based on previous findings that Black participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study have, on average, more adverse social determinants of health. Methods: We used Multiple Informants Models (MIM) to compare the strength of five measures of accelerated aging (Intrinsic and Extrinsic Epigenetic Age Acceleration, GrimAge Acceleration, PhenoAge Acceleration, CAA (including clinical biomarkers, e.g., CRP, lung function, glucose, etc.), and one established clinical predictor of future CVD, FRS, to predict incident CVD over 11 years (2007 – 2018). Participants were 913 Black or White individuals examined by CARDIA in 2005-2006, when their mean age was 45 years. We also included race-specific analysis. Measures were standardized (M = 0, SD=1) to facilitate comparison. Results: The incidence rate of CVD within our sample was 7.8 per 1,000 person years and the prevalence of CVD was 7.5%. CAA and FRS significantly predicted incident CVD in the fully adjusted model (OR = 1.31, 95% CI: 1.06 – 1.63) and (OR = 1.28, 95% CI: 1.05 – 1.56), respectively. CAA and FRS were the best predictors of CVD, but there was no significant difference in the predictive value of CAA and FRS (Chi2 = 0.05, p = 0.828). In race-stratified models, CAA was the strongest and most consistent predictor in the Black-only models. Conclusions: Our findings support the association of CAA, a multi-system clinical composite, with incident CVD. Further, this composite may account for some of the well-known racial variation in incident CVD.

Air pollution and epigenetic aging among Black and White women in the US

BackgroundDNA methylation-based measures of biological aging have been associated with air pollution and may link pollutant exposures to aging-related health outcomes. However, evidence is inconsistent and there is little information for Black women. ObjectiveWe examined associations of ambient particulate matter <2.5 μm and <10 μm in diameter (PM2.5 and PM10) and nitrogen dioxide (NO2) with DNA methylation, including epigenetic aging and individual CpG sites, and evaluated whether associations differ between Black and non-Hispanic White (NHW) women. MethodsValidated models were used to estimate annual average outdoor residential exposure to PM2.5, PM10, and NO2 in a sample of self-identified Black (n=633) and NHW (n=3493) women residing in the contiguous US. We used sampling-weighted generalized linear regression to examine the effects of pollutants on six epigenetic aging measures (primary: DunedinPACE, GrimAgeAccel, and PhenoAgeAccel; secondary: Horvath intrinsic epigenetic age acceleration [EAA], Hannum extrinsic EAA, and skin & blood EAA) and epigenome-wide associations for individual CpG sites. Wald tests of nested models with and without interaction terms were used to examine effect measure modification by race/ethnicity. ResultsBlack participants had higher median air pollution exposure than NHW participants. GrimAgeAccel was associated with both PM10 and NO2 among Black participants, (Q4 versus Q1, PM10: β=1.09, 95% CI: 0.16–2.03; NO2: β=1.01, 95% CI 0.08–1.94) but not NHW participants (p-for-heterogeneity: PM10=0.10, NO2=0.20). In Black participants, we also observed a monotonic exposure–response relationship between NO2 and DunedinPACE (Q4 versus Q1, NO2: β=0.029, 95% CI: 0.004–0.055; p-for-trend=0.03), which was not observed in NHW participants (p-for-heterogeneity=0.09). In the EWAS, pollutants were significantly associated with differential methylation at 19 CpG sites in Black women and one in NHW women. ConclusionsIn a US-wide cohort study, our findings suggest that air pollution is associated with DNA methylation alterations consistent with higher epigenetic aging among Black, but not NHW, women.

Association of Adverse Childhood Experiences With Accelerated Epigenetic Aging in Midlife

Adverse childhood experiences (ACEs) are associated with the risk of poorer health, and identifying molecular mechanisms may lay the foundation for health promotion in people with ACEs. To investigate the associations of ACEs with changes in epigenetic age acceleration (EAA), a biomarker associated with various health outcomes in middle-aged adults, in a population with balanced race and sex demographics. Data for this cohort study were from the Coronary Artery Risk Development in Young Adults (CARDIA) study. Participants in CARDIA underwent 8 follow-up exams from baseline (year 0 [Y0]; 1985-1986) to Y30 (2015-2016), and participant blood DNA methylation information was obtained at Y15 (2000-2001) and Y20 (2005-2006). Individuals from Y15 and Y20 with available DNA methylation data and complete variables for ACEs and covariates were included. Data were analyzed from September 2021 to August 2022. Participant ACEs (general negligence, emotional negligence, physical violence, physical negligence, household substance abuse, verbal and emotional abuse, and household dysfunction) were obtained at Y15. The primary outcome consisted of results from 5 DNA methylation-based EAA measurements known to be associated with biological aging and long-term health: intrinsic EAA (IEAA), extrinsic EAA (EEAA), PhenoAge acceleration (PhenoAA), GrimAge acceleration (GrimAA), and Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE), measured at Y15 and Y20. Linear regression and generalized estimating equations were used to assess associations of the burden of ACEs (≥4 vs <4 ACEs) with EAA adjusting for demographics, health-related behaviors, and early life and adult socioeconomic status. A total of 895 participants for Y15 (mean [SD] age, 40.4 [3.5] years; 450 males [50.3%] and 445 females [49.7%]; 319 Black [35.6%] and 576 White [64.4%]) and 867 participants for Y20 (mean [SD] age, 45.4 [3.5] years; 432 males [49.8%] and 435 females [50.2%]; 306 Black [35.3%] and 561 White [64.7%]) were included after excluding participants with missing data. There were 185 participants with (20.7%) vs 710 participants without (79.3%) 4 or more ACEs at Y15 and 179 participants with (20.6%) vs 688 participants without (79.4%) 4 or more ACEs at Y20. Having 4 or more ACEs was positively associated with EAA in years at Y15 (EEAA: β = 0.60 years; 95% CI, 0.18-1.02 years; PhenoAA: β = 0.62 years; 95% CI = 0.13-1.11 years; GrimAA: β = 0.71 years; 95% CI, 0.42-1.00 years; DunedinPACE: β = 0.01; 95% CI, 0.01-0.02) and Y20 (IEAA: β = 0.41 years; 95% CI, 0.05-0.77 years; EEAA: β = 1.05 years; 95% CI, 0.66-1.44 years; PhenoAA: β = 0.57 years; 95% CI, 0.08-1.05 years; GrimAA: β = 0.57 years; 95% CI, 0.28-0.87 years; DunedinPACE: β = 0.01; 95% CI, 0.01-0.02) after adjusting for demographics, health-related behaviors, and socioeconomic status. In this cohort study, ACEs were associated with EAA among middle-aged adults after controlling for demographics, behavior, and socioeconomic status. These findings of the associations between early life experience and the biological aging process in midlife may contribute to health promotion in a life course perspective.