Genome-wide methylation profiles reveal quantitative views of human aging rates

Multidomain intervention for delaying aging in community-dwelling older adults (MIDA): study design and protocol

BACKGROUND

The exploration of interventions to delay aging is an emerging topic that promotes healthy aging. The multidomain intervention has the potential to be applied in the field of aging because it concentrates on the functional ability of older adults. There is currently no literature reporting on a multidomain intervention involving cognition, exercise and nutrition for delaying aging.

METHODS

The Multidomain Intervention for Delaying Aging in Community-dwelling Older Adults (MIDA) is a Zelen-design randomized controlled trial with a 6-month intervention duration. The multidomain intervention comprises cognitive training, exercise training, and nutritional guidance, delivered through both group sessions and individual family interventions. A total of 248 participants aged 60 to 85 years will be randomized to the intervention group or control group and followed up for 12 months. The primary outcome is the change in epigenetic age acceleration and pace of aging following the multidomain intervention. The secondary outcomes are the changes in frailty score and intrinsic capacity Z-score. Other outcomes include physical functions, body composition, aging biomarkers, inflammatory markers, haematology and biochemistry parameters, and lifestyle factors.

CONCLUSIONS

This study will explore the effects of the multidomain intervention on delaying aging in community-dwelling older adults. We aim to introduce a new approach to delaying aging and offer a practical multidomain intervention strategy for healthcare institutions.

Blood transcriptomic associations of epigenetic age in adolescents

Epigenetic aging in early life remains poorly characterized, and patterns of gene expression can provide biologically meaningful insights. Blood DNA methylation was measured using the Illumina EPICv1.0 array and RNA sequencing was performed in blood in 174 adolescent participants (age range: 14-15 years) from the CHAMACOS cohort. Thirteen widely used epigenetic clocks were calculated, and their associations with transcriptome-wide RNA expression were tested using the limma-voom pipeline. We found evidence for substantial shared associations with RNA expression between different epigenetic clocks, including differential expression of MYO6 and ZBTB38 across five clocks. The epiTOC2, principal component (PC) PhenoAge, Hannum, PedBE and PC Hannum clocks were associated with differential expression of the highest number of RNAs, exhibiting associations with 22, 8, 5, 3, and 2 transcripts respectively. Generally, biological clocks were associated with differential expression of more genes than chronological clocks, and PC clocks were associated with differential expression of more genes relative to their CpG-trained counterparts. A total of 17 associations in our study were replicated in an independent adult sample (age range: 40-54 years). Our findings support the biological relevance of epigenetic clocks in adolescents and provide direction for selection of epigenetic ageing biomarkers in adolescent research.

Taiwan population-based epigenetic clocks and their application to long-term air pollution exposure

Most epigenetic clocks have been developed in populations of European or Hispanic descent; therefore, population-specific models are needed for Asian cohorts to enhance predictive accuracy and generalizability. This study aims to develop epigenetic clocks in a Taiwanese cohort and examine the association between long-term air pollution exposure and epigenetic age acceleration (EAA). The Taiwan Biobank (TWB) has been recruiting community-based adults aged 30-70 years since 2012, enrolling 173,806 participants by the end of 2022. Among them, 2,469 participants were selected for serum DNA methylation (DNAm) analysis. Epigenetic ages were estimated using penalized elastic net regression, with residuals defined as TWB-based epigenetic age acceleration (TWBEAA) and healthy-subset-based acceleration (TWBhEAA). Additionally, four previously established EAAs were obtained using Horvath's online DNA Methylation Age Calculator: DNAmEAA, DNAmSBEAA, PhenoEAA, and GrimEAA. Air pollution exposure levels at participants' residential townships were estimated from pre-1 day to pre-1 year using a kriging-based spatial interpolation method. Associations were assessed using multiple linear regression models, with robustness verified through Bayesian Kernel Machine Regression (BKMR). The TWBAge (325 CpG sites) and TWBhAge (179 CpG sites) prediction models demonstrated high accuracy (R2 = 0.95) in predicting chronological age. In the single-pollutant model, pre-1 year PM2.5 exposure was significantly associated with TWBhEAA (β = 0.67 [0.14-1.19], year) and DNAmEAA (β = 0.93 [0.03-1.83], year), while O3 exposure showed a positive association with DNAmSBEAA (β = 0.53 [0.29-0.77], year) and a negative association with GrimEAA (β = -0.44 [-0.70 to -0.17], year). BKMR analysis confirmed these findings. This study is among the first attempts to develop epigenetic clocks tailored for Asian population, providing evidence of air pollution's role in accelerating biological aging. Our findings highlight PM2.5 and O3 exposure as major contributors to EAA, emphasizing the need for air pollution mitigation strategies to promote healthier aging.

DNA methylation predicts infection risk in kidney transplant recipients

Kidney transplantation (KTx) is the method of choice for treating kidney failure. Identifying biomarkers predictive of transplant (Tx) outcomes is critical to optimize KTx; however, the immunosuppressive therapies required after KTx must also be considered. We applied targeted bisulfite sequencing (TBS-seq) to PBMCs isolated from 90 patients, with samples collected pre- and post-Tx (day 90), to measure DNA methylation changes. Our findings indicate that the PBMC DNA methylome is significantly affected by induction immunosuppression with anti-thymocyte globulin (ATG). We discovered that the risk of infection can be predicted using DNA methylation profiles, but not gene expression profiles. Specifically, 515 CpG loci associated with 275 genes were significantly impacted by ATG induction, even after accounting for age, sex, and cell-type composition. Notably, ATG-associated hyper-methylation down-regulates genes critical for immune response. In conclusion, this clinical omics study reveals that the immunosuppressant ATG profoundly impacts the DNA methylome of KTx recipients and identifies biomarkers that could be used in pre-Tx screening of patients vulnerable to infection, thereby informing immunosuppression strategies post-Tx.

Cancer-treatment-induced accelerated aging in older adult cancer survivors: A call for actions for future perspectives in geriatric oncology

Cancer treatment has significantly improved survival rates, but older adult cancer survivors remain at risk of cancer-treatment-induced late effects such as cardiac complications and second primary cancers. A new hypothesis emerged in the literature suggesting that such late effects can indeed be the manifestation of an accelerated aging process induced by cancer treatments. The cancer-treatment-induced accelerated aging could first arise from clinical and biological manifestations such as frailty, sarcopenia, cognitive impairments, cellular senescence, telomere attrition, and chronic inflammation, paralleling hallmarks of aging. Older adult cancer survivors frequently demonstrated early-onset frailty, sarcopenia, osteoporosis, cognitive impairments, diminished physical function, and increased levels of aging biomarkers compared to cancer-free age-matched older adults. However, existing studies are limited by their narrow focus on specific cancers, the use of single aging outcome measures, and short follow-up durations. A holistic research approach, incorporating comprehensive geriatric assessments and aging biomarkers, is crucial for describing the induced health burden and the mechanisms underlying these induced aging vulnerabilities. Addressing these gaps through large-scale longitudinal studies could lead to personalized interventions, improved treatment protocols, and supportive care strategies in older adult cancer survivors. Such efforts will enhance quality of life, promote healthy aging trajectories, and mitigate societal and economic burdens. To this end, concrete actions, such as establishing international consortia that include patient advocacy, are encouraged. Efforts should also include developing a centralized, registry-based repository for clinical and biological aging outcomes.

Association between frailty index and epigenetic aging acceleration in older adults: Evidence from the health and retirement study

BACKGOUND

This study aimed to examine the associations between the frailty index and four epigenetic aging acceleration (EAA) estimators in cross-sectional and longitudinal settings.

METHODS

The frailty index in the older adults was measured according to a cumulative health-deficit model. Four different epigenetic age measures (Hannum, PhenoAge, GrimAge, and DunedinPoAm38) were regressed against chronological age, and the resulting standardized residuals were indicative of EAA. The longitudinal relationship between EAA at baseline and changes in the frailty index during the 4-year follow-up were examined using a mixed linear model.

RESULTS

A single standard deviation (SD) increment in the frailty index was associated with a faster EAA, as indicated by the four clocks in Hannum (b = 0.057; P = 0.015), PhenoAge (b = 0.096; P < 0.001), GrimAge (b = 0.120; P < 0.001), and DunedinPoAm38 (b = 0.062; P = 0.002) in the fully adjusted model. A 1-SD increment in the GrimAge EAA was associated with a 0.003 frailty index increase (b = 0.003; P = 0.002). A 1-SD increment in DunedinPoAm38 EAA was associated with a 0.002 frailty index increase (b = 0.002; P = 0.009).

CONCLUSIONS

The frailty index was cross-sectionally associated with EAA, while only GrimAge and DunedinPoAm38 EAA predicted changes in the frailty index. More research is needed to understand the interplay between pathways.

Development of a microRNA-Based age estimation model using whole-blood microRNA expression profiling

Age estimation is a critical aspect of human identification. Traditional methods, reliant on morphological examinations, are often suitable for living subjects. However, there are relatively few studies on age estimation based on biological samples, such as blood. Recent advancements have concentrated on DNA methylation for forensic age prediction. However, to explore further possibilities, this study investigated microRNAs (miRNAs) as alternative molecular markers for age estimation. Peripheral blood samples from 127 healthy individuals were analyzed for miRNA expression using small RNA sequencing. Lasso regression selected 103 candidate miRNAs, and Shapley additive explanations (SHAP) analysis identified 38 key miRNAs significant for age prediction. Five machine learning models were developed, with the elastic net model achieving the best performance (MAE of 4.08 years) on the testing set, surpassing current miRNA age estimation results. Additionally, we observed significant changes in the expression levels of miRNAs in healthy individuals aged 48-52 years. This study demonstrated the potential of blood miRNA biomarkers in age prediction and provides a set of miRNA markers for developing more accurate age prediction methods.

The association of prenatal ambient air pollution with placental epigenetic gestational age at birth

Background

Prenatal air pollutants have been associated with adverse birth outcomes, and DNA methylation (DNAm) changes in placenta may contribute to these associations. DNAm-based epigenetic gestational age (GA) estimators are emerging biomarkers for aging/biological age that can reflect early-life exposures and predict long-term health outcomes. We leveraged 103 mother-offspring pairs from the Early Autism Risk Longitudinal Investigation cohort to assess associations between prenatal air pollution and placental epigenetic GA at birth.

Methods

Prenatal air pollution concentrations (NO2, O3, PM2.5, and PM10) were estimated from weekly data from monitoring stations near maternal residence and calculated for preconception and pregnancy periods. DNAm from fetal-side placenta samples was measured on Illumina HumanMethylation450 BeadChip. Epigenetic GA was computed using Lee's robust placenta clock algorithm. GA acceleration/deceleration was the residual of predicted epigenetic GA on chronologic GA, adjusted (intrinsic) or unadjusted (extrinsic) for cell type proportions. We used linear regressions to examine associations between average air pollution levels in each period and GA acceleration/deceleration, and weekly distributed lag models to examine critical exposure windows.

Results

Higher pregnancy average O3 and PM10 exposures were associated with decelerated intrinsic (β = -0.65 and -0.79) and extrinsic GA (β = -0.69 and -0.74) at birth (per 10-unit increment). Trimester-specific analyses revealed higher O3 and PM10 exposures in trimesters 2 to 3 associated with decelerated GA at birth. Weekly distributed lag models suggested pregnancy weeks 21 to 31 and 21 to 29 were critical windows of O3 and PM10 exposures, respectively.

Conclusions

Prenatal air pollution exposures, especially during mid- to late-pregnancy, were associated with lower biological maturity at birth.

Uncertainty Quantification in Epigenetic Clocks via Conformalized Quantile Regression

DNA methylation (DNAm) is a chemical modification of DNA that can be influenced by various factors, including age, the environment, and lifestyle. An epigenetic clock is a predictive tool that measures biological age based on DNAm levels. It can provide insights into an individual's biological age, which may differ from their chronological age. This difference, known as the epigenetic age acceleration, may reflect health status and the risk for age-related diseases. Moreover, epigenetic clocks are used in studies of aging to assess the effectiveness of antiaging interventions and to understand the underlying mechanisms of aging and disease. Various epigenetic clocks have been developed using samples from different populations, tissues, and cell types, typically by training high-dimensional linear regression models with an elastic net penalty. While these models can predict mean biological age based on DNAm with high precision, there is a lack of uncertainty quantification which is important for interpreting the precision of age estimations and for clinical decision-making. To understand the distribution of a biological age clock beyond its mean, we propose a general pipeline for training epigenetic clocks, based on an integration of high-dimensional quantile regression and conformal prediction, to effectively reveal population heterogeneity and construct prediction intervals. Our approach produces adaptive prediction intervals not only achieving nominal coverage but also accounting for the inherent variability across individuals. By using the data collected from 728 blood samples in 11 DNAm data sets from children, we find that our quantile regression-based prediction intervals are narrower than those derived from conventional mean regression-based epigenetic clocks. This observation demonstrates an improved statistical efficiency over the existing pipeline for training epigenetic clocks. In addition, the resulting intervals have a synchronized varying pattern to age acceleration, effectively revealing cellular evolutionary heterogeneity in age patterns in different developmental stages during individual childhoods and adolescent cohort. Our findings suggest that conformalized high-dimensional quantile regression can produce valid prediction intervals and uncover underlying population heterogeneity. Although our methodology focuses on the distribution of measures of biological aging in children, it is applicable to a broader range of age groups to improve understanding of epigenetic age beyond the mean. This inference-based toolbox could provide valuable insights for future applications of epigenetic interventions for age-related diseases.

The association of DNA methylation-based epigenetic age acceleration with facial expression recognition in older adults

BACKGROUND

Facial expression recognition (FER) abilities play a crucial role in fostering beneficial social relationships for healthy aging, however, these abilities tend to decline as people age. We investigated the association between epigenetic age acceleration (EAA) and FER among older individuals.

METHODS

Accuracy rates and response times for six emotions, anger, disgust, fear, happiness, sadness, and surprise, were assessed in outpatients who visited the Veterans Health Service Medical Center. We calculated six EAA measures (intrinsic EAA, extrinsic EAA, PhenoAge acceleration, GrimaAge2 acceleration, skin and blood Age Acceleration, and Dunedin Pace of Aging Calculated from the Epigenome), based on DNA methylation levels across 935,000 CpGs. We employed multiple linear regression models adjusting for demographic and socioeconomic variables.

RESULTS

In men, EAA was associated with a lower accuracy rate for fear (DunedinPACE: β= -7.53, 95 % CI= -12.12, -2.95) and a higher rate for sadness (Grim2AA: β= 5.44, 95 % CI= 0.37, 10.51). In women, EAA was associated with a lower accuracy rate for anger (SBAA: β= -5.06, 95 % CI= -9.43, -0.70) and a higher rate for happiness (EEAA: β= 4.79, 95 % CI= 0.85, 8.73). In men, EAA had an association with a faster response for fear (EEAA: β= -0.24, 95 % CI= -0.44, -0.05) and in women, for all emotions except sadness.

CONCLUSIONS

Greater EAA was associated with higher accuracy rates in recognizing happiness among women and sadness among men. Our findings suggest that biological aging may enhance recognition of positive emotions and empathy for others' sadness, rather than simply reducing FER abilities.

T cell aging and exhaustion: Mechanisms and clinical implications

T cell senescence and exhaustion represent critical aspects of adaptive immune system dysfunction, with profound implications for health and the development of disease prevention and therapeutic strategies. These processes, though distinct, are interconnected at the molecular level, leading to impaired effector functions and reduced proliferative capacity of T cells. Such impairments increase susceptibility to diseases and diminish the efficacy of vaccines and treatments. Importantly, T cell senescence and exhaustion can dynamically influence each other, particularly in the context of chronic diseases. A deeper understanding of the molecular mechanisms underlying T cell senescence and exhaustion, as well as their interplay, is essential for elucidating the pathogenesis of related diseases and restoring dysfunctional immune responses. This knowledge will pave the way for the development of targeted therapeutic interventions and strategies to enhance immune competence. This review aims to summarize the characteristics, mechanisms, and disease associations of T cell senescence and exhaustion, while also delineating the distinctions and intersections between these two states to enhance our comprehension.

Association between phenotypic age and in-hospital outcomes in patients with acute myocardial infarction: A retrospective observational study

Background

Phenotypic age (PhenoAge) has emerged as a superior predictor of age-related morbidity and mortality. This study aimed to assess the associations between PhenoAge and in-hospital outcomes in patients with acute myocardial infarction (AMI).

Methods

2896 AMI patients admitted to the First Affiliated Hospital of Xi'an Jiaotong University from 2019 to 2022 were analyzed in this retrospective study. PhenoAge was calculated by using the phenotypic age calculator, an equation for chronologic age and 9 clinical biomarkers, and Phenotypic Age Accelerate (PhenoAgeAccel) was measured using the residuals of regression PhenoAge on chronological age. Clinical outcomes were defined as in-hospital major adverse cardiovascular events (MACEs), including cardiogenic shock, malignant arrhythmia, acute heart failure, and mechanical complications.

Results

Overall, patients with high PhenoAge had a higher Gensini score and a higher likelihood of receiving supportive care, as well as worse clinical outcomes. The same results were observed in patients with positive PhenoAgeAccel. Moreover, PhenoAge and PhenoAgeAccel were significantly associated with in-hospital MACEs even after adjusting for multiple traditional risk factors. The area under the curve for PhenoAge was 0.714 (P < 0.001), which significantly outperformed chronologic age (AUC: 0.601, P < 0.001) and other cardiovascular risk factors. Re-examination of the ROC curves using different combinations of variables, PhenoAge was also able to significantly improve the predictive value of several models.

Conclusions

PhenoAge is significantly associated with clinical outcomes and reliably predicts in-hospital MACEs. Compared with chronological age, PhenoAge is a better complementary biomarker for predicting the risk of in-hospital adverse cardiovascular events in patients with AMI.

Health insurance and epigenetic aging: Trends in a United States adult population

Background

Health insurance plays an important role in reducing morbidity and mortality. Still, there is limited data examining the relationships of health insurance with biomarkers of aging that reflect morbidity and mortality risk.

Methods

We conducted a cross-sectional study of United States adults using data from the National Health and Nutrition Examination Survey (NHANES) to examine the relationships of health insurance with seven DNA methylation-based biomarkers of aging (epigenetic age): HannumAge, HorvathAge, SkinBloodAge, PhenoAge, GrimAge2, DNAm Telomere Length, and DunedinPoAm.

Results

Our analyses included 2315 participants with available health insurance and epigenetic aging data (mean [sd] age, 65.1 [9.3] years). Compared to the uninsured, having health insurance was associated with a 2.25-year lower GrimAge2 (95 %CI: -3.49, -1.02, P = 0.001) and a slower DunedinPoAm pace of aging (β = -0.04, 95 %CI: -0.06, -0.02, P < 0.001) in basic demographic-adjusted models. GrimAge2 (β = -1.42, 95 %CI: -2.75, -0.09, P = 0.04) and DunedinPoAm (β = -0.03, 95 %CI: -0.06, -0.01, P = 0.02) relationships were attenuated after additional adjustments for general health, body mass index (BMI), education, occupation, and poverty-to-income ratio. Model estimates were larger if insurance plans were more comprehensive and included dental coverage and/or single service plans. When considering categories of insurance, similar trends were observed with private insurance and public insurance plans (i.e. Medicare, Medicaid/CHIP, and other government plans), although private insurance relationships were more often statistically significant.

Conclusion

Our findings suggest that epigenetic aging measures may be useful for examining the relationship between health insurance and population health, with potential implications for policy decisions.

The Epigenetic Landscape: From Molecular Mechanisms to Biological Aging

Epigenetics, the study of heritable changes in gene expression that do not involve alterations to the deoxyribonucleic acid (DNA) sequence, plays a pivotal role in cellular function, development, and aging. This review explores key epigenetic mechanisms, including DNA methylation (DNAm), histone modifications, chromatin remodeling, RNA-based regulation, and long-distance chromosomal interactions. These modifications contribute to cellular differentiation and function, mediating the dynamic interplay between the genome and environmental factors. Epigenetic clocks, biomarkers based on DNAm patterns, have emerged as powerful tools to measure biological age and predict health span. This article highlights the evolution of epigenetic clocks, from first-generation models such as Horvath's multi-tissue clock to advanced second- and third-generation clocks such as DNAGrimAge and DunedinPACE, which incorporate biological parameters and clinical biomarkers for precise age estimation. Moreover, the role of epigenetics in aging and age-related diseases is discussed, emphasizing its impact on genomic stability, transcriptional regulation, and cellular senescence. Epigenetic dysregulation is implicated in cancer, genetic disorders, and neurodegenerative diseases, making it a promising target for therapeutic interventions. The reversibility of epigenetic modifications offers hope for mitigating age acceleration and enhancing health span through lifestyle changes and pharmacological approaches.

Chemical and climatic environmental exposures and epigenetic aging: A systematic review

Epigenetic aging biomarkers are used for evaluating morbidity and mortality, monitoring therapies, and direct-to-consumer testing. However, the influence of environmental exposures on epigenetic age acceleration (EAA), also known as epigenetic age deviation, has not been systematically evaluated. In this systematic review, we synthesized findings from human epidemiologic studies on chemical and climatic environmental exposures, particularly air pollution, chemicals, metals, climate, and cigarette smoke, and EAA. A total of 102 studies analyzing epigenetic data from over 180,000 subjects were evaluated. Overall, studies in each exposure category frequently included adult participants, used a variety of epigenetic clocks, analyzed whole blood samples, and had a low risk of bias. Exposure to air pollution (15/19 of studies; 79%), cigarette smoke (53/66; 80%), and synthetic and occupational chemicals (5/8; 63%) were notably associated with increased EAA. Results for essential and non-essential metal exposure were more equivocal: 7/13 studies (54%) reported increased EAA. One study reported increased EAA with greater temperature exposure. In summary, we identified environmental exposures, such as air pollution and cigarette smoke, that were strongly associated with increased EAA. Further research is needed with larger and more diverse samples and high-quality exposure assessment.

Epigenetic age acceleration mediates the association between low-grade systemic inflammation and cardiovascular diseases: insight from the NHANES 1999-2002

BACKGROUND

Currently, with the global aging of the population, inflammation, recognized as a hallmark in age-related diseases, has been studied and linked to cardiovascular diseases (CVD). However, limited evidence on whether inflammation modifies epigenetic aging and affects CVD risk.

METHODS

This study included 404 CVD patients and 1941 non-CVD individuals from the 1999-2002 National Health and Nutrition Examination Survey cross-sectional data. Low-grade systemic inflammation was assessed using C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), and systemic inflammation response index (SIRI). Epigenetic age accelerations (EAAs) were calculated as the residuals between chronological and epigenetic ages: Horvath age acceleration (AgeAccel), AgeAccelHannum, and AgeAccelPheno. Weighted linear and logistic regression analyzed the associations between exposures and outcomes, with mediating effects assessed using the Sobel test.

RESULTS

After adjusting confoundings, the log-transformed NLR and SIRI were positively associated with CVD risk, and the odds ratio (OR) ranges from 1.260 to 1.354 (all P < 0.05). Furthermore, the ln-transformed CRP was positively associated with AgeAccelHannum and AgeAccelPheno, and the coefficient (β) ranges from 0.505 to 1.304 (all P < 0.05); the ln-transformed NLR and SIRI were positively associated with all three EAAs, and the β ranges from 0.392 to 2.212 (all P < 0.005). Additionally, 1-unit increase in AgeAccelHannum and AgeAccelPheno was associated with 2.8% (OR: 1.028, 95% CI 1.007-1.049, P = 0.011) and 3.5% (OR: 1.035, 95% CI 1.014-1.056, P = 0.002) increase in CVD risk, respectively. After adjusting confoundings, mediation analysis showed that AgeAccelHannum mediates 10.44% (P = 0.046) of the association between NLR and CVD risk; and AgeAccelPheno mediates 24.03% (P = 0.009) and 18.16% (P = 0.015) of the NLR-CVD and SIRI-CVD risk associations, respectively.

CONCLUSION

Our results demonstrate that EAAs mediate the association between systemic inflammation and CVD risk, highlighting the potential of a multi-target approach to inflammation and epigenetic modifications for personalized management to reduce CVD risk.

Sleep patterns and DNA methylation age acceleration in middle-aged and older Chinese adults

BACKGROUND

Sleep is a biological necessity and fundamental to health. However, the associations of sleep patterns (integrating sleep determinants) with DNA methylation age acceleration (DNAm AA) remain unknown. We aimed to investigate the associations of sleep patterns with DNAm AA.

METHODS

This cross-sectional and prospective cohort study used data from the Dongfeng-Tongji cohort collected from 2013 to December 31, 2018. Sleep patterns were reflected by sleep scores (range 0-4, with higher scores indicating healthier sleep patterns) characterized by bedtime, sleep duration, sleep quality, and midday napping. DNAm AA was estimated by PhenoAge acceleration (PhenoAgeAccel), GrimAge acceleration (GrimAgeAccel), DunedinPACE, and DNAm mortality risk score (DNAm MS). Linear regression models were used to estimate β and 95% confidence intervals (CIs) for the cross-sectional associations between sleep patterns and DNAm AA. Mediation models were applied to assess the mediating role of DNAm AA in the associations between sleep patterns and all-cause mortality in a prospective cohort.

RESULTS

Among 3566 participants (mean age 65.5 years), 426 participants died during a mean 5.4-year follow-up. A higher sleep score was associated with lower DNAm AA in a dose-response manner. Each 1-point increase in sleep score was associated with significantly lower PhenoAgeAccel (β = - 0.208; 95% CI - 0.369 to - 0.047), GrimAgeAccel (β = - 0.107; 95% CI - 0.207 to - 0.007), DunedinPACE (β = - 0.008; 95% CI - 0.012 to - 0.004), and DNAm MS (β = - 0.019; 95% CI - 0.030 to - 0.008). Chronological age modified the associations between higher sleep scores and lower PhenoAgeAccel (p for interaction = 0.031) and DunedinPACE (p for interaction = 0.027), with stronger associations observed in older adults. Moreover, a slower DunedinPACE mediated 6.2% (95% CI 0.8% to 11.5%) of the association between a higher sleep score and a lower all-cause mortality risk.

CONCLUSION

In this cohort study, individuals with a higher sleep score had a slower DNAm AA, particularly in older adults. A slower DunedinPACE partially explained the association between higher sleep scores and lower all-cause mortality risk. These findings suggest that adopting healthy sleep patterns may promote healthy aging and further benefit premature mortality prevention, highlighting the value of sleep patterns as a potential tool for clinical management in aging.

Nucleotides as an Anti-Aging Supplementation in Older Adults: A Randomized Controlled Trial (TALENTs study)

Aging impairs nutrient metabolism and accelerates biological aging, negatively affecting health and longevity. The Targeting Aging and Longevity with Exogenous Nucleotides (TALENTs) trial (ClinicalTrials.gov: NCT05243108) aimed to explore whether nucleotides (NTs) supplementation can delay biological aging and improve health outcomes in the elderly. The trial is a 19-week, double-blind, randomized, placebo-controlled study in Chengdu, China, with 121 participants (60-70 years). Participants are randomly assigned to either NTs (1.2 g day-1) or placebo group (1:1). The results of primary outcomes showed that NTs had significantly greater reduction in median DNA methylation age compared to placebo over 19 weeks (β = -3.08 years, 95% CI: -5.07 to -1.10, P = 0.0023), with a trend toward reduction observed over 11 weeks (β = -1.94 years, 95% CI: -4.32 to 0.45, P = 0.11); whereas no significant difference changes of leukocyte telomere length are showed between groups (week 11: β = 0.09, 95% CI: -0.10 to 0.29, P = 0.36; week 19: β = 0.12, 95% CI: -0.05 to 0.28, P = 0.18). Insulin sensitivity improved in the NTs group, with a significant reduction in HOMA-IR over 19 weeks (β = -0.45, 95% CI: -0.86 to -0.04, P = 0.033). No severe adverse events or significant changes in safety indicators are reported. Together, our findings establish that NTs may delay biological aging and improve insulin sensitivity with a well-tolerated safety profile.

Geroprotective applications of oleuropein and hydroxytyrosol through the hallmarks of ageing

Geroprotectors are compounds that target the underlying mechanisms of ageing to delay the onset of age-related diseases and extend both lifespan and health span. As ageing is driven by the accumulation of cellular damage, DNA instability, epigenetic changes, mitochondrial dysfunction, and chronic inflammation, the concept of geroprotection focuses on compounds that can mitigate these processes. Oleuropein (OLE) and its derivative hydroxytyrosol (HT), both phenolic molecules derived from Olea europaea (olive tree), have gained significant attention as potential geroprotectors due to their potent antioxidant and anti-inflammatory properties. These phytochemicals, central to the Mediterranean diet, activate key molecular pathways such as nuclear factor erythroid 2-related factor 2, reducing oxidative stress and modulating inflammatory responses. Through these mechanisms, OLE and HT help counteract inflammageing, a critical factor in age-related dysfunction. This review highlights the role of OLE and HT as geroprotective agents, emphasising their ability to target the hallmarks of ageing and their potential to improve health span by slowing the progression of age-related conditions. With proven efficacy in various biological models, these compounds represent promising tools in the ongoing search for strategies to enhance the quality of life in ageing populations.

Unified high-resolution immune cell fraction estimation in blood tissue from birth to old age

Variations in immune-cell fractions can confound or hamper interpretation of DNAm-based biomarkers in blood. Although cell-type deconvolution can address this challenge for cord and adult blood, currently there is no method applicable to blood from other age groups, including infants and children. Here we construct and extensively validate a DNAm reference panel, called UniLIFE, for 19 immune cell-types, applicable to blood tissue of any age. We use UniLIFE to delineate the dynamics of immune-cell fractions from birth to old age, and to infer disease associated immune cell fraction variations in newborns, infants, children and adults. In a prospective longitudinal study of type-1 diabetes in infants and children, UniLIFE identifies differentially methylated positions that precede type-1 diabetes diagnosis and that map to diabetes related signaling pathways. In summary, UniLIFE will improve the identification and interpretation of blood-based DNAm biomarkers for any age group, but specially for longitudinal studies that include infants and children. The UniLIFE panel and algorithms to estimate cell-type fractions are available from our EpiDISH Bioconductor R-package: https://bioconductor.org/packages/release/bioc/html/EpiDISH.html.

Interaction between gender and age on the methylation levels of KLF14 promoter

This study investigated the relationship between age, sex, and methylation levels of the Krüppel-like factor 14 (KLF14) promoter. Utilizing data from the Taiwan Biobank (TWB), established in 2005, we analyzed a cohort of 1,141 participants. DNA methylation analyses were conducted by Health GeneTech Corp., commissioned by TWB. Methylation levels of the KLF14 promoter were determined by averaging the values of 10 CpG sites: cg09823095, cg25109431, cg21449170, cg05651960, cg18751682, cg08097417, cg07955995, cg22285878, cg21520933, and cg06533629. Participants were divided into four age groups (30-40, 40-50, 50-60, and 60-70 years). Multiple linear regression analyses were performed to assess the impact of age and sex on KLF14 promoter methylation and to evaluate the interaction between these variables. Our findings revealed that men exhibited higher KLF14 promoter methylation levels, with a significant age-dependent increase. Notably, in participants aged over 50, KLF14 methylation levels were substantially higher in men compared to women (β = 0.00336, P = 0.0108 for the 50-60 age group; β = 0.00472, P = 0.0238 for the 60-70 age group). Our study reveals a sex-specific increase in KLF14 promoter methylation among men over 50, with no significant differences observed in individuals younger than 50. This finding suggests that age and sex may play a crucial role in the epigenetic regulation of KLF14.

Causal impact of genetically-determined fish and fish oil intake on epigenetic age acceleration and related serum markers

BACKGROUND

The interplay between diet and healthspan is a topic of great interest in biomedical research. Toward this end, consumption of marine omega-3 fatty acids is of particular significance, as reports suggest that diets focused on seafood can prolong the disease-free portion of the human lifespan. Fish consumption has also been linked to reduced biological aging as measured by epigenetic clocks, but there is no conclusive evidence of a causal relationship. Moreover, fish oils reduce triglycerides, and may affect other lipid profiles, as well as systemic inflammation. To investigate further, we used two-sample Mendelian randomization to investigate potential causality between fish intake and healthspan markers.

METHODS

Bidirectional Mendelian randomization was performed in the two-sample setting with publicly available GWAS summary statistics. GWAS data from the UK Biobank for oily fish consumption (n = 460,443) and fish oil supplementation (n = 461,384) were used as the primary exposures. First-generation epigenetic clocks Hannum age and intrinsic epigenetic age acceleration (IEAA), as well as second-generation clocks GrimAge and PhenoAge were collected from an independent dataset of individuals of European ancestry (n = [34,449-34,667]). Finally, data from the Integrative Epidemiology Unit database was used for serum proxies of lipidemia and systemic inflammation (n = [61,308-78,700]). Additional sensitivity analyses, such as reverse causation testing and the Cochran's Q test were performed for exposure-outcome pairs where the inverse variance weighted (IVW) method was significant (p-value < 0.05), and where the MR Egger method indicated an effect in the same direction as the IVW result.

RESULTS

We report that oily fish consumption appears to decrease PhenoAge acceleration (p < 0.0086), whereas fish oil supplementation appears to decrease GrimAge (p = 0.037). Both omega-3 exposures modify the epigenetic clocks in the expected negative, or age-decelerating, direction. For the serum biomarkers, we find evidence that fish oil consumption leads to a reduction in triglycerides (p = 0.004), although HDL and LDL were not significantly modified. Finally, we also detected a suggestive inverse relationship between oily fish consumption and hsCRP (p = 0.064).

CONCLUSIONS

Our analysis shows that consuming fish oil, whether through whole food or as a supplement, can have a rejuvenating impact as measured by PhenoAge and GrimAge acceleration. We have also provided evidence further linking fish oil intake and lower triglyceride levels. These results, based on robust MR-based analyses, emphasize the effectiveness of dietary choices in modifying emerging measures of healthspan.

Sensory impairments and epigenetic aging: insights from self-rated hearing and vision in United States adults

Sensory impairments are common with aging, but studies examining the relationships of these impairments with DNA methylation-based biomarkers of aging, strong predictors of morbidity and mortality, remain sparse. We investigated whether subjective measures of sensory impairment are associated with epigenetic age biomarkers. We conducted a cross-sectional analysis in a representative sample of 2344 U.S. adults from the 1999-2000 and 2001-2002 cycles of the National Health and Nutrition Examination Survey (NHANES). We examined the relationships of self-rated auditory and vision function with seven epigenetic aging biomarkers: HannumAge, HorvathAge, SkinBloodAge, PhenoAge, GrimAge2, DNA methylation telomere length, and DunedinPoAm. We adjusted for potential confounders including chronological age, other demographics, lifestyle factors, and general health. In adjusted survey-weighted models, self-reported deafness was associated with a significantly higher GrimAge2 (β = 4.19-years, 95% CI 2.29, 6.09, P = 0.004) and DunedinPoAm (β = 0.07, 95% CI 0.04, 0.09, P = 0.002) compared to good hearing. Deafness was also associated with significantly higher GrimAge2 estimates of TIMP1 (β = 459.51, 95% CI 287.00, 632.03 P = 0.002) and marginally higher estimated levels of ADM (β = 10.06, 95% CI 1.76, 18.36, P = 0.03), CRP (β = 0.34, 95% CI 0.11, 0.56, P = 0.01), and cigarette pack-years (β = 6.55, 95% CI 2.62, 10.47, P = 0.01). No associations were observed with self-rated vision. We describe associations of self-rated deafness with accelerated epigenetic aging, as measured by GrimAge2 and DunedinPoAm. These results provide a foundation for future research exploring epigenetic biomarkers as tools for predicting and understanding the biological processes underlying sensory impairments like deafness.

Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing

Characterizing DNA methylation patterns is important for addressing key questions in evolutionary biology, development, geroscience, and medical genomics. While costs are decreasing, whole-genome DNA methylation profiling remains prohibitively expensive for most population-scale studies, creating a need for cost-effective, reduced representation approaches (i.e., assays that rely on microarrays, enzyme digests, or sequence capture to target a subset of the genome). Most common whole genome and reduced representation techniques rely on bisulfite conversion, which can damage DNA resulting in DNA loss and sequencing biases. Enzymatic methyl sequencing (EM-seq) was recently proposed to overcome these issues, but thorough benchmarking of EM-seq combined with cost-effective, reduced representation strategies is currently lacking. To address this gap, we optimized the Targeted Methylation Sequencing protocol (TMS)-which profiles ~4 million CpG sites-for miniaturization, flexibility, and multispecies use at a cost of ~USD 80. First, we tested modifications to increase throughput and reduce cost, including increasing multiplexing, decreasing DNA input, and using enzymatic rather than mechanical fragmentation to prepare DNA. Second, we compared our optimized TMS protocol to commonly used techniques, specifically the Infinium MethylationEPIC BeadChip (n = 55 paired samples) and whole genome bisulfite sequencing (n = 6 paired samples). In both cases, we found strong agreement between technologies (R2 = 0.97 and 0.99, respectively). Third, we tested the optimized TMS protocol in three non-human primate species (rhesus macaques, geladas, and capuchins). We captured a high percentage (mean = 77.1%) of targeted CpG sites and produced methylation level estimates that agreed with those generated from reduced representation bisulfite sequencing (R2 = 0.98). Finally, we confirmed that estimates of 1) epigenetic age and 2) tissue-specific DNA methylation patterns are strongly recapitulated using data generated from TMS versus other technologies. Altogether, our optimized TMS protocol will enable cost-effective, population-scale studies of genome-wide DNA methylation levels across human and non-human primate species.

Epigenetic Clocks and EpiScore for Preventive Medicine: Risk Stratification and Intervention Models for Age-Related Diseases

Aging is the primary risk factor for chronic diseases such as cardiovascular disease, cancer, and dementia. However, chronological age alone fails to capture individual variability in aging trajectories and disease susceptibility. Recent advances in epigenetic clocks-DNA methylation-based models that estimate biological age-have opened new possibilities for personalized and preventive medicine. This review explores the clinical potential of epigenetic clocks and EpiScores, composite biomarkers that predict health risks and physiological status. We present a comparative evaluation of widely used epigenetic clocks, including Horvath, GrimAge, PhenoAge, and DunedinPACE, and summarize their predictive performance for mortality, cognitive decline, and cardiovascular outcomes. EpiScores linked to inflammation, glycemic control, and immunosenescence are highlighted as tools for stratified risk assessment. When integrated with multi-omics data and electronic health records, these measures enhance the precision of population health management. Special emphasis is placed on applications in longevity clinics and anti-aging clinics, community-based care, and national health checkup systems. We also explore global standardization efforts and ethical considerations, as well as Japan's unique initiatives-including the "Aging Measurement" project at the Osaka-Kansai Expo 2025. Furthermore, we propose the development of a Global Health and Aging Index that integrates the biological, functional, and subjective dimensions of aging, aligned with the WHO concept of Intrinsic Capacity. In conclusion, epigenetic clocks and EpiScores represent transformative tools for shifting from reactive treatment to proactive health optimization, and from chronological to biological metrics in aging science and public health policy.

Immunosenescence Profile Is Associated With Increased Susceptibility to Severe COVID-19

In this study, we tested the hypothesis that the immunosenescence profile could account for the disproportional susceptibility of the elderly to severe forms of COVID-19. The immunological profiles of volunteers residing in endemic and non-endemic areas for chronic infectious diseases were analyzed at the early stage of SARS-CoV-2 infection. A unique signature of inflammatory plasma mediators was identified in COVID-19 volunteers when compared to individuals with other flu-like syndromes. COVID-19 severity correlated with high levels of inflammatory mediators; among them, CXCL9, a serum marker of aging. Patients who progressed to hospitalization displayed high frequencies of CD8+ and CD4+ T cells expressing exhaustion and senescence markers and showed reduced and more mature B cell repertoires, which are typical of senescence. They also had an acceleration of epigenetic age measured by DNA methylation. Therefore, severe COVID-19 correlated with phenotypic, functional, and epigenetic features of accelerated immunosenescence at the onset of infection.

Characterizing the Social Epigenome in Mexican Patients with Early-Onset Psychosis

Background: Psychosis is one of the leading causes of disability worldwide. Individuals with early-onset psychosis (EOP) tend to experience a worse prognosis and shorter life expectancy. The etiology of EOP remains unclear, but epigenetic mechanisms are known to serve as the interface between environmental exposures and biological processes to better understand its etiology. Objectives: We characterized the sociodemographic and clinical characteristics, as well as genome-wide epigenetic markers, in Mexican patients with EOP. Methods: We estimated epigenetic age, performed an epigenome-wide association study, and finally developed an epigenetic risk score (MRS) to predict manifestations of psychosis. Results: We found that patients with EOP have a higher epigenetic age using Wu's clock (p = 0.015). Moreover, accelerated epigenetic age was correlated with chronological age (PedBE clock, p = 0.046), global functioning (Wu's clock, p = 0.027), and psychiatric admissions (DNAmTL, p = 0.038). In addition, we observed that a reduction in years of schooling is associated with an increase on epigenetic age (Levine's clock, β = 5.07, p = 0.001). In our epigenome-wide association study, we identified eight CpGs associated with EOP. Noteworthy, a psychosis-methylation risk score (EOP-MRS) was associated with panic disorder (β = 1.36, p = 0.03), as well as auditory (β = 1.28, p = 0.04) and visual (β = 1.22, p = 0.04) hallucinations. Conclusions: Years of education have an impact on epigenetic age. Additionally, our study suggests associations of DNA methylation with EOP. Finally, we developed an MRS that associates clinical manifestations of psychosis.

Unveiling the impact of DNA-methylation age acceleration on mortality risk in diabetes and pre-diabetes: insights from the US NHANES program

BACKGROUND

Diabetes ranks as the ninth leading cause of death globally, and DNA-methylation age acceleration (DNAmAA) is closely linked to lifespan. However, the impact of DNAmAA on long-term outcomes in specific populations with diabetes and pre-diabetes has not yet been comprehensively studied.

METHODS

This retrospective cohort study utilized data from the National Health and Nutrition Examination Survey (NHANES) 1999-2002, including participants aged 20 years or older diagnosed with diabetes or pre-diabetes. DNAmAA was defined as the difference between epigenetic age and chronological age. Multiple generations of DNAmAA measures were included. Cox proportional hazards regression models were employed to estimate the associations between DNAmAAs and all-cause, cardiovascular, and non-cardiovascular mortality.

RESULTS

A total of 1,199 participants were included, with a mean age of 64.20 (0.46) years; 621 (51.8%) were male. Significant correlations were observed between chronological age and all DNA-methylation ages in both diabetes and pre-diabetes groups. Over a mean follow-up of 14.13 (5.90) years, 662 deaths were recorded. AgeAccelGrim2 exhibited the strongest association with mortality. Each 5-unit increase in AgeAccelGrim2 was associated with an elevated risk of all-cause mortality (HR 1.35, 95% CI 1.23-1.49), cardiovascular mortality (HR 1.50, 95% CI 1.25-1.80), and non-cardiovascular mortality (HR 1.30, 95% CI 1.16-1.46). These associations remained significant in participants with diabetes and pre-diabetes. Mediation analysis revealed that AgeAccelGrim2 significantly mediates the association between health-related exposures (including the Oxidative Balance Score, Life's Simple 7 score, and frailty score) and all-cause mortality in diabetes and pre-diabetes populations.

CONCLUSIONS

AgeAccelGrim2 could serve as a valuable biomarker for mortality risk specific to populations with diabetes and pre-diabetes, offering potential applications in personalized management strategies and risk stratification.

Cross-sectional associations of epigenetic clocks with intrinsic capacity and functional ability in older adults with frailty and cognitive impairment: the COGFRAIL study

Functional ability and intrinsic capacity (IC) have been proposed as determinants of healthy aging, but the extent to which these indicators are affected by biological aging remains unknown. We explored the association of biological age acceleration (BAA) with functional ability and IC in older adults with physical and cognitive impairments. This cross-sectional study used data from 163 individuals (84.0 ± 5.2 years [range 72-99], 61.8% women) of the COGFRAIL cohort. Functional ability on basic (BADL-Katz Index) and instrumental activities of daily living (IADL-Lawton Index) was assessed. IC was measured as a composite score (0-100, higher is better) including the locomotion, cognition, psychology, sensory, and vitality domains. BAA was assessed by Horvath's, Hannum's, PhenoAge, and GrimAge epigenetic clocks. In the fully adjusted model, higher BAAPhenoAGe was associated to lower functional ability in BADLs (β = - 0.021, 95% confidence interval = - 0.038 to - 0.003, p = 0.022), with no significant results observed for the remaining clocks. No significant association was found between BAA and IC, but some associations were found with specific IC domains. Particularly, BAAGrimAge was associated with lower locomotion scores (β = - 1.179, 2.286 to - 0.072, p = 0.037), while BAAPhenoAge tended to be associated with lower scores in vitality (β = - 0.257, - 0.539 to 0.025, p = 0.073). Higher BAAPhenoage was associated with lower functional ability in very old adults with frailty and cognitive impairment. Although no biological clock was associated with a composite IC score, some associations were found between second-generation epigenetic clocks and specific IC domains.

Microglia Single-Cell RNA-Seq Enables Robust and Applicable Markers of Biological Aging

"Biological aging clocks"-composite molecular markers thought to capture an individual's biological age-have been traditionally developed through bulk-level analyses of mixed cells and tissues. However, recent evidence highlights the importance of gaining single-cell-level insights into the aging process. Microglia are key immune cells in the brain shown to adapt functionally in aging and disease. Recent studies have generated single-cell RNA-sequencing (scRNA-seq) datasets that transcriptionally profile microglia during aging and development. Leveraging such datasets in humans and mice, we develop and compare computational approaches for generating transcriptome-wide summaries from microglia to establish robust and applicable aging clocks. Our results reveal that unsupervised, frequency-based summarization approaches, which encode distributions of cells across molecular subtypes, strike a balance in accuracy, interpretability, and computational efficiency. Notably, our computationally derived microglia markers achieve strong accuracy in predicting chronological age across three diverse single-cell datasets, suggesting that microglia exhibit characteristic changes in gene expression during aging and development that can be computationally summarized to create robust markers of biological aging. We further extrapolate and demonstrate the applicability of single-cell-based microglia clocks to readily available bulk RNA-seq data with an environmental input (early life stress), indicating the potential for broad utility of our models across genomic modalities and for testing hypotheses about how environmental inputs affect brain age. Such single-cell-derived markers can yield insights into the determinants of brain aging, ultimately promoting interventions that beneficially modulate health and disease trajectories.

Associations of epigenetic aging with self-rated health, access to care, and healthcare utilization in a representative sample of United States adults

BACKGROUND

Health status is closely linked to both healthcare access and utilization. While previous research has identified associations between health status and DNA methylation-based biomarkers of aging (epigenetic aging), studies exploring these relationships in the context of healthcare access and utilization remain limited. To address this gap, we analyzed cross-sectional associations in a representative sample of 2,343 U.S. adults from the 1999-2000 and 2001-2002 cycles of the National Health and Nutrition Examination Survey (NHANES). Our study examined the relationships of self-rated health status, healthcare access, and healthcare utilization with seven epigenetic aging biomarkers: HannumAge, HorvathAge, SkinBloodAge, PhenoAge, GrimAge2, DNAm Telomere Length (DNAmTL), and DunedinPoAm.

RESULTS

After adjusting for chronological age, demographics, lifestyle factors, and health insurance, participants with good-excellent self-rated health had a 1.58-year lower PhenoAge (95% CI - 2.54, - 0.62 P = 0.006) and a 1.16-year lower GrimAge2 (95% CI - 1.80, - 0.53, P = 0.004) than participants with poor-fair health. Participants who reported having a routine place where they received healthcare had a lower GrimAge2 (β = - 1.44-years, 95% CI - 2.66, - 0.22, P = 0.03) than participants without a routine healthcare location. Participants with ≥ 10 healthcare visits in the prior year had a shorter DNAmTL (β = - 0.05-kb, 95% CI - 0.09, - 0.01, P = 0.02) than participants with < 10 visits. After including additional adjustments for estimated leukocyte proportions, participants who were hospitalized overnight in the prior year had a shorter DNAmTL (β = - 0.05-kb, 95% CI - 0.08, - 0.01, P = 0.02) than non-hospitalized individuals.

CONCLUSIONS

Our findings reinforce previous reports linking better health status to lower epigenetic aging and provide new evidence of associations of epigenetic aging with measures of healthcare access and utilization. If validated, these findings suggest that epigenetic aging biomarkers may be useful in studying disease processes and assessing health outcomes related to access and utilization.

A deep learning sex-specific body composition ageing biomarker using dual-energy X-ray absorptiometry scan

BACKGROUND

Chronic diseases are closely linked to alterations in body composition, yet there is a need for reliable biomarkers to assess disease risk and progression. This study aimed to develop and validate a biological age indicator based on body composition derived from dual-energy X-ray absorptiometry (DXA) scans, offering a novel approach to evaluating health status and predicting disease outcomes.

METHODS

A deep learning model was trained on a reference population from the UK Biobank to estimate body composition biological age (BCBA). The model's performance was assessed across various groups, including individuals with typical and atypical body composition, those with pre-existing diseases, and those who developed diseases after DXA imaging. Key metrics such as c-index were employed to examine BCBA's diagnostic and prognostic potential for type 2 diabetes, major adverse cardiovascular events (MACE), atherosclerotic cardiovascular disease (ASCVD), and hypertension.

RESULTS

Here we show that BCBA strongly correlates with chronic disease diagnoses and risk prediction. BCBA demonstrated significant associations with type 2 diabetes (odds ratio 1.08 for females and 1.04 for males, p < 0.0005), MACE (odds ratio 1.10 for females and 1.11 for males, p < 0.0005), ASCVD (odds ratio 1.07 for females and 1.10 for males, p < 0.0005), and hypertension (odds ratio 1.06 for females and 1.04 for males, p < 0.0005). It outperformed standard cardiovascular risk profiles in predicting MACE and ASCVD.

CONCLUSIONS

BCBA is a promising biomarker for assessing chronic disease risk and progression, with potential to improve clinical decision-making. Its integration into routine health assessments could aid early disease detection and personalised interventions.

Association of proBNPage with all-cause and cardiovascular mortality among US adults: an analysis of data from the National Health and Nutrition Examination Survey

OBJECTIVE

Biological age assessed by the Klemera and Doubal method (KDM) and phenotypic age (PhenoAge) was considered as a marker for ageing-related outcomes because it reflects different aspects of biological ageing and health, which are associated with increased risk of death. proBNPage based on N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a novel index for biological age estimation. However, the independence of its relationship with clinical outcomes from established risk factors, KDM or PhenoAge remains uncertain. Their identification could provide valuable information to prognosis.

DESIGN, SETTING AND PARTICIPANTS

This study analysed data from the general population included in the National Health and Nutrition Examination Survey (NHANES). Participants who took part in the cross-sectional survey from 1999 to 2004 were included, and all-cause as well as cardiovascular mortality was recorded (up to 31 December 2019).

OUTCOME MEASURES

All-cause and cardiovascular mortality were considered as outcomes. Clinical risk factors were collected, and biological age was estimated by proBNPage, KDM and PhenoAge. Cox proportional hazards models were used to determine the relationship between proBNPage and outcomes with adjustment for risk factors or other biological age indexes. Restricted cubic spline (RCS) analysis based on multivariate Cox regressions was performed to examine whether there was a non-linear relationship between proBNPage and outcomes.

RESULTS

A total of 9 925 participants were included in this study. The association between proBNPage and outcomes remained significant after adjusting for risk factors, including NT-proBNP (for all-cause mortality, HR 1.14; 95% CI 1.10 to 1.17; for cardiovascular mortality, HR 1.20; 95% CI 1.14 to 1.27). Similar results were obtained after adjusting for KDM plus NT-proBNP (for all-cause mortality, HR 1.31; 95% CI 1.22 to 1.41; for cardiovascular mortality, HR 1.21; 95% CI 1.11 to 1.28) or PhenoAge plus NT-proBNP (for all-cause mortality, HR 1.21; 95% CI 1.16 to 1.28; for cardiovascular mortality, HR 1.35; 95% CI 1.24 to 1.47). These findings were confirmed in most subgroups. A non-linear relationship was observed between proBNPage and all-cause and cardiovascular mortality with an inflection point.

CONCLUSIONS

A non-linear positive relationship was observed between proBNPage and clinical outcomes. After adjusting for established risk factors and other biological age estimation indices (KDM or PhenoAge), proBNPage was significantly associated with mortality. The results remain similar after further adjustment for NT-proBNP. These results suggest that proBNPage is a useful surrogate for biological age estimation.

Twin pair analysis uncovers links between DNA methylation, mitochondrial DNA quantity and obesity

Alterations in mitochondrial metabolism in obesity may indicate disrupted communication between mitochondria and nucleus, and DNA methylation may influence this interplay. Here, we leverage data from the Finnish Twin Cohort study subcohort (n = 173; 86 full twin pairs, 1 singleton), including comprehensive measurements of obesity-related outcomes, mitochondrial DNA quantity and nuclear DNA methylation levels in adipose and muscle tissue, to identify one CpG at SH3BP4 significantly associated with mitochondrial DNA quantity in adipose tissue (FDR < 0.05). We also show that SH3BP4 methylation correlates with its gene expression. Additionally, we find that 14 out of the 35 obesity-related traits display significant associations with both SH3BP4 methylation and mitochondrial DNA quantity in adipose tissue. We use data from TwinsUK and the Scandinavian T2D-discordant monozygotic twin cohort, to validate the observed associations. Further analysis using ICE FALCON suggests that mitochondrial DNA quantity, insulin sensitivity and certain body fat measures are causal to SH3BP4 methylation. Examining mitochondrial DNA quantity and obesity-related traits suggests causation from mitochondrial DNA quantity to obesity, but unmeasured within-individual confounding cannot be ruled out. Our findings underscore the impact of mitochondrial DNA quantity on DNA methylation and expression of the SH3BP4 gene within adipose tissue, with potential implications for obesity.

The predictive power of profiling the DNA methylome in human health and disease

Early and accurate diagnosis significantly improves the chances of disease survival. DNA methylation (5mC), the major DNA modification in the human genome, is now recognized as a biomarker of immense clinical potential. This is due to its ability to delineate precisely cell-type, quantitate both internal and external exposures, as well as tracking chronological and biological components of the aging process. Here, we survey the current state of DNA methylation as a biomarker and predictor of traits and disease. This includes Epigenome-wide association study (EWAS) findings that inform Methylation Risk Scores (MRS), EpiScore long-term estimators of plasma protein levels, and machine learning (ML) derived DNA methylation clocks. These all highlight the significant benefits of accessible peripheral blood DNA methylation as a surrogate measure. However, detailed DNA methylation biopsy analysis in real-time is also empowering pathological diagnosis. Furthermore, moving forward, in this multi-omic and biobank scale era, novel insights will be enabled by the amplified power of increasing sample sizes and data integration.

The associations between biological markers of aging and appetite loss across adulthood: retrospective case-control data from the INSPIRE-T study

Appetite loss is a common clinical condition in older adulthood, but how this condition associates with biological aging remains unknown. The present study aims to examine the associations of biological aging markers with appetite loss in community-dwelling people aged 21 to 102 years. This retrospective case-control study used baseline data from the INSPIRE-T cohort in Toulouse, France. Each of the 49 cases with appetite loss was sex- and age-matched to two controls without appetite loss (n = 147; median age of 79 years, interquartile range: 19.5; 67% women). Appetite loss was assessed using a single yes-no question from the World Health Organization´s Integrated Care for Older People screening tool. Biomarkers (first- and second-generation DNA methylation-based epigenetic clocks [Horvath, Hannum, PhenoAge, and GrimAge], the inflammatory aging clock iAge, and Adenosine triphosphatase inhibitory factor 1-IF1) were derived from blood samples. Logistic regression analyzed the associations of these markers with appetite loss. In fully adjusted models, accelerated aging using GrimAge was the only biomarker associated with appetite loss (Odds Ratio = 1.21, 95% Confidence Interval: 1.03, 1.43). When stratified by age (≤ 65 years vs. > 65 years) and sex, this association remained significant only in individuals over 65 years and men. Future research is needed to explore the potential mechanisms involved, as well as how other biological drivers of aging (e.g., cell senescence, deregulated nutrient sensing) relate to appetite loss.

Methylation-based biological age and cardiotoxicity risk in breast cancer patients treated with trastuzumab

BACKGROUND

Trastuzumab is an effective treatment for HER2-positive cancers that has known cardiotoxic properties. Discovering biomarkers that assess cardiotoxicity risk before trastuzumab therapy is essential for protecting the cardiovascular health of cancer patients.

OBJECTIVE

To examine the associations between pre-treatment epigenetic age acceleration, circulating leukocyte composition, and candidate single nucleotide polymorphisms (SNPs) with cardiotoxicity risk in breast cancer patients receiving trastuzumab.

METHODS

Among a retrospective cohort of HER2-positive breast cancer patients treated with trastuzumab at Moffitt Cancer Center, we profiled blood DNA methylation and genetic profiles. Epigenetic clocks and circulating leukocyte subsets were derived from MethylationEPIC BeadChip data, and candidate SNPs were measured using the Global Screening Array. Cardiotoxicity events (i.e., reductions in left ventricular ejection fraction, symptomatic heart failure), were identified in medical records. Logistic regression models, adjusted for traditional risk factors, estimated odds ratios (ORs) for biomarker associations with cardiotoxicity risk.

RESULTS

Among 157 patients selected for this study, 39 (25%) experienced cardiotoxicities within one year of treatment initiation. rs776746 was inversely associated with cardiotoxicity risk (OR: 0.38, 95% CI: 0.14, 1.00, P = 0.05). After adjusting for traditional risk factors and leukocyte composition, the Hannum AgeAccel, Horvath AgeAccel, and Horvath Skin and Blood AgeAccel metrics were significantly positively associated with cardiotoxicity risk (ORs ranging between 1.62 and 1.89). Adding Horvath Skin and Blood AgeAccel to traditional cardiotoxicity risk factors significantly improved cardiotoxicity risk prediction (AUC: 0.75 vs. 0.79; P-diff = 0.04).

CONCLUSIONS

Pre-treatment epigenetic age acceleration appears to be a novel biomarker for cardiotoxicity risk that improves cardiotoxicity risk prediction.

Sex-specific associations between per- and polyfluoroalkyl substance exposure and epigenetic age: Findings from the National Health and Nutrition Examination survey 1999-2000

Per-and polyfluoroalkyl substances (PFAS) are a pervasive family of synthetic compounds with a wide range of reported health effects. Epigenetic clocks, DNA methylation-based predictors of chronological and biological age, are promising biomarkers for characterizing biological aging in humans. The potential impact of PFAS exposure on epigenetic aging in the general US population remains unclear. In the 1999-2000 National Health and Nutrition Examination Survey (NHANES) cycle (N = 262), eleven PFASs were measured in serum and DNA methylation was measured in blood with the EPICv1 array. Seven epigenetic clocks and their respective epigenetic age acceleration (EAA) measures were calculated. Survey-design weighted generalized linear regression models were used to test adjusted associations between individual log2-transformed PFAS concentrations and EAA stratified by sex. Among male participants, doubling of PFNA concentrations was associated with greater EAA across several clocks including the Horvath clock (beta = 1.48, 95 % CI: 0.35, 2.61), Skin&Blood clock (beta = 1.27, 95 % CI: 0.21, 2.32), and PhenoAge (beta = 1.43, 95 % CI: 0.41, 2.44), and doubling of PFOS exposure was associated with greater Skin&Blood EAA (beta = 1.14, 95 % CI: 0.04, 2.24). When considering cell-adjusted EAA measures, each of these associations among male participants remained significant, and PFOSA was associated with decreased PhenoAge EAA (beta = -0.84, 95 % CI: -1.49, -0.18) and GrimAge2 EAA (beta = -0.81, 95 % CI: -1.51, -0.11) among female participants. In summary, we found evidence of sex-specific associations between PFAS exposure and epigenetic aging in a sample of older adults representative of the general US population.

Emergence of CpG-cluster blanket methylation in aged tissues: a novel signature of epigenomic aging

Aging is accompanied by widespread DNA methylation changes across the genome. While age-related methylation studies typically focus on individual CpGs, cluster analysis provides more robust data and improved interpretation. We characterized age-associated CpG-cluster methylation changes in mouse spleens, peripheral blood mononuclear cells, and livers. We identified a novel signature termed blanket methylations (BMs), fully methylated CpG clusters absent in young tissues but appearing in aged tissues. BM formation was locus- and cell-dependent, with minimal overlap among tissues. Statistical analysis, heterogeneity assessment, and random modeling demonstrated that BMs arise through nonrandom mechanisms and correlate with accelerated aging. Notably, BMs appeared in chronologically young mice with progeroid or disease-driven aging, including in 4-month-old Zmpste24-/- (lifespan ∼5 months) and 3-month-old Huntington's disease model mice (lifespan ∼4 months). The detection of BMs in purified CD4+ T cells demonstrated that their occurrence is intrinsic to aging cells rather than a result of infiltration from other tissues. Further investigation revealed age-related downregulation of zinc-finger-CxxC-domain genes, including Tet1 and Tet3, which protect CpG islands from methylation. Importantly, TET1 or TET3 depletion induced BM formation, linking their loss to age-associated methylation drift. These findings establish BMs as a robust marker of epigenomic aging, providing insight into age-related methylation changes.

CpG island methylator phenotype classification improves risk assessment in pediatric T-cell acute lymphoblastic leukemia

ABSTRACT

Current intensive treatment of pediatric T-cell acute lymphoblastic leukemia (T-ALL) has substantial side effects, highlighting a need for novel biomarkers to improve risk stratification. Canonical biomarkers, such as genetics and immunophenotype, are largely not used in pediatric T-ALL stratification. This study aimed to validate the prognostic relevance of DNA methylation CpG island methylator phenotype (CIMP) risk stratification in 2 pediatric T-ALL patient cohorts: the Nordic Society of Paediatric Haematology (NOPHO) ALL2008 T-ALL study cohort (n = 192) and the Dutch Childhood Oncology Group (DCOG) ALL-10/ALL-11 validation cohorts (n = 156). Both cohorts revealed that combining CIMP classification at diagnosis with measurable residual disease (MRD) at treatment day 29 (D29) or 33 (D33) significantly improved outcome prediction. The poor prognosis subgroup, characterized by CIMP low/D29 or D33 MRD ≥ 0.1%, had a cumulative incidence of relapse (pCIR5yr) of 29% and 23% and overall survival (pOS5yr) of 59.7% and 65.4%, in NOPHO and DCOG, respectively. Conversely, a good prognosis subgroup was also identified representing CIMP high/D29 or D33 MRD < 0.1% with pCIR5yr of 0% and 3.4% and pOS5yr of 98.2% and 94.8%, in NOPHO and DCOG, respectively. For NOPHO, MRD was also evaluated on D15, and the relapse prediction accuracy of CIMP/D29 MRD (0.79) and CIMP/D15 MRD (0.75) classification was comparable, indicating potential for earlier stratification. The evaluation of the biology behind the CIMP subgroups revealed associations with transcriptome profiles, genomic aberrations, and mitotic history, suggesting distinct routes for leukemia development. In conclusion, integrating MRD assessment with the novel CIMP biomarker has the potential to improve risk stratification in pediatric T-ALL and guide future therapeutic decisions.

Social determinants of health and epigenetic clocks: Meta-analysis of 140 studies

Social determinants of health are social factors that affect health and survival. Two of the most powerful social determinants are socioeconomic status (SES) and race/ethnicity; people with lower SES or marginalized race/ethnicity tend to experience earlier onset of aging-related diseases and have shorter lifespans. DNA methylation (DNAm) measures of biological aging, often referred to as "epigenetic clocks", are increasingly used to study the social determination of health. However, there are several generations of epigenetic clocks and it remains unclear which are most sensitive to social factors affecting health. Moreover, there is uncertainty about how technical factors, such as the tissue from which DNA is derived or the technology used to measure DNA methylation may affect associations of social determinants with epigenetic clocks. We conducted a pre-registered multi-level meta-analysis of 140 studies, including N = 65,919 participants, encompassing 1,065 effect sizes for associations of SES and racial/ethnic identity with three generations of epigenetic clocks. We found that associations were weakest for the first generation of epigenetic clocks developed to predict age differences between people. Associations were stronger for the second generation of epigenetic clocks developed to predict mortality and health risks. The strongest associations were observed for a third generation of epigenetic clocks, sometimes referred to as "epigenetic speedometers", developed to predict the pace of aging. In studies of children, only the speedometers showed significant associations with SES. Effects of sex and technical factors were minimal and there was no evidence of publication bias.

Joint association between physical exercise, caffeine intake, and biological ageing: A cross-sectional analysis of population-based study

BACKGROUND

Ageing is a significant risk factor for age-related diseases, accounting for 51% of global total disease burden. As thus, promoting healthy ageing is crucial. Although several potential anti-ageing drugs show promise, none have been approved for anti-ageing purpose. The World Health Organization (WHO) recommends physical exercise exceeding 600 metabolic equivalent of task (MET) minutes per week for adults. However, whether physical exercise positively impacts healthy biological ageing remains unclear.

OBJECTIVE

This study aimed to investigate the joint correlation between MET level, caffeine consumption, and biological ageing.

METHODS

We analyzed data from seven survey cycles (2007-2020) of the National Health and Nutrition Examination Survey (NHANES), involving 23,739 participants. Physical activity levels were measured in MET minutes per week, and biological ageing was assessed using both the PhenoAge and ENABL Age algorithms. Generalized linear regression for survey data was employed to test correlations, adjusting for confounding factors. A cubic spline model was used to detect non-linear relationships. Pre-specified subgroup analyses explored effect modifications, while predefined sensitivity analyses confirmed the robustness of the results.

RESULTS

Each 100-MET increase in weekly physical exercise was associated with a 0.2-year delay in biological ageing (p < 0.001 for both PhenoAge and ENABL Age). Individuals with less than 600 MET minutes of weekly exercise had a higher risk of accelerated ageing compared to those exceeding 600 MET minutes (mean difference [MD]: 2.2 PhenoAge years, 95% CI [1.5-2.8], p < 0.001; MD: 2.1 ENABL Age years, 95% CI [1.1-3.1], p < 0.001). A L-shaped association was observed, with diminishing benefits of delayed ageing beyond 292 MET minutes for PhenoAge and 259 MET minutes for ENABL Age. Daily caffeine intake did not modify the correlation between MET levels and biological ageing (p for interaction > 0.05). Stronger effects were observed in non-Hispanic Black individuals, those with obesity, and low-income populations, but no benefit was found in cancer patients.

CONCLUSIONS

Our findings highlight a positive correlation between higher levels of weekly physical exercise and delayed biological ageing. However, the benefits plateau beyond specific MET thresholds. Caffeine intake does not influence this relationship. These results underscore the importance of promoting physical exercise at appropriate MET levels as a strategy for healthy ageing management in the general population.

Regulatory roles of transposable elements on autism molecular neuropathology

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by challenges in social communication and the presence of repetitive behaviors, typically diagnosed in early childhood. In this review, we searched PubMed and Google Scholar databases for relevant articles. ASD displays considerable heterogeneity in symptomatology and is more common in males, though shifting demographics indicate rising rates among minority populations. Transposable elements (TEs), which constitute approximately 50% of the mammalian genome, are increasingly recognized for their contribution to neurodevelopmental disorders, including ASD. These mobile genetic elements can induce genomic instability and modulate gene expression, thereby influencing ASD pathology. Evidence suggests that specific TEs, such as L1 and Alu elements, can disrupt genes critical for neurodevelopment and contribute to the disorder's genetic complexity. Furthermore, prenatal environmental exposures may activate TEs, potentially contributing to neuroinflammation observed in ASD. While the precise regulatory roles of non-coding TEs in ASD are still under investigation and require careful interpretation, integrating epigenetic aging markers like epigenetic clocks holds promise for advancing the field. Future research focused on the intricate relationship between TEs, environmental factors, epigenetic mechanisms, and neurodevelopmental processes is essential for identifying novel biomarkers and therapeutic targets, ultimately improving early diagnosis and interventions for ASD.

Distinct methylomic signatures of high-altitude acclimatization and adaptation in the Tibetan Plateau

High altitude presents a challenging environment for human settlement. DNA methylation is an essential epigenetic mechanism that responds to environmental stimuli, but its roles in high-altitude short-term acclimatization (STA) and long-term adaptation (LTA) are poorly understood. Here, we conducted a methylome-wide association study involving 687 native highlanders and 299 acclimatized newcomers in the Tibetan Plateau and 462 native lowlanders to identify differentially methylated sites (DMSs) associated with STA or LTA. We identified 93 and 4070 DMSs for STA and LTA, respectively, which had no overlap, showed opposite asymmetric effect size patterns, and resided near genes enriched in distinct biological pathways/processes (e.g., cell cycle for STA and immune diseases and calcium signalling pathway for LTA). Epigenetic clock analysis revealed evidence of accelerated ageing in the acclimatized newcomers compared to the native lowlanders. Our research provides novel insights into epigenetic regulation in relation to high altitude and intervention strategies for altitude-related ageing or illnesses.

Designing Epigenetic Clocks for Wildlife Research

The applications of epigenetic clocks - statistical models that predict an individual's age based on DNA methylation patterns - are expanding in wildlife conservation and management. This growing interest highlights the need for field-specific design best practices. Here, we provide recommendations for two main applications of wildlife epigenetic clocks: estimating the unknown ages of individuals and assessing their biological ageing rates. Epigenetic clocks were originally developed to measure biological ageing rates of human tissues, which presents challenges for their adoption in wildlife research. Most notably, the estimated chronological ages of sampled wildlife can be unreliable, and sampling restrictions limit the number and variety of tissues with which epigenetic clocks can be constructed, reducing their accuracy. To address these challenges, we present a detailed workflow for designing, validating applying accurate wildlife epigenetic clocks. Using simulations and analyses applied to an extensive polar bear dataset from across the Canadian Arctic, we demonstrate that accurate epigenetic clocks for wildlife can be constructed and validated using a limited number of samples, accommodating projects with small budgets and sampling constraints. The concerns we address are critical for clock design, whether researchers or third-party service providers perform the bioinformatics. With our workflow and examples, we hope to support the accessible and widespread use of epigenetic clocks in wildlife conservation and management.

Associations of DNA Methylation Algorithms of Aging With Cardiovascular Disease and Mortality Risk Among US Older Adults

BACKGROUND

Several DNA methylation (DNAm) algorithms have recently emerged as robust predictors of aging and adverse health outcomes in older adults, offering valuable insights into cardiovascular disease (CVD) risk stratification. However, their predictive performance for CVD varies significantly. This study aimed to systematically investigate the associations of 12 widely used DNAm algorithms with CVD and mortality risk.

METHODS

Data from the NHANES (National Health and Nutrition Examination Survey) 1999 to 2002 were used to assess 12 DNAm algorithms (eg, HannumAgeacc, PhenoAgeacc, GrimAgeMortacc, GrimAge2Mortacc) in relation to CVD risk and mortality. Two cohorts were analyzed: one for CVD risk (n=1230) and another for CVD mortality risk (n=1606). DNAm was measured using the Infinium Methylation EPIC BeadChip kit (Illumina). Odds ratios (ORs) and hazard ratios (HRs), along with 95% CIs per SD increase of these DNAm algorithms, were calculated.

RESULTS

Significant associations were observed for GrimAgeMortacc and GrimAge2Mortacc with coronary heart disease and heart attack, with multivariable-adjusted ORs per SD increase ranging from 2.15 to 2.76. However, several algorithms exhibited no significant association with self-reported prevalent CVD. For mortality risk, HannumAgeacc, PhenoAgeacc, ZhangAgeacc, GrimAgeMortacc, and GrimAge2Mortacc were significantly associated with CVD mortality. The multivariable-adjusted HRs per SD increase were 1.19 (95% CIs, 1.05-1.34), 1.13 (95% CIs, 1.01-1.26), 1.63 (95% CI, 1.08-2.47), 1.90 (95% CIs, 1.51-2.40), and 1.87 (95% CIs, 1.51-2.32), respectively. These associations were consistent across biological sex, age (≥50 and <65 versus ≥65 years), and race and ethnicity groups.

CONCLUSIONS

DNAm algorithms, particularly GrimAgeMortacc and GrimAge2Mortacc, may serve as valuable tools for CVD risk stratification and mortality risk assessment.

Multi-Omic Associations of Epigenetic Age Acceleration Are Heterogeneously Shaped by Genetic and Environmental Influences

Connections between the multi-ome and epigenetic age acceleration (EAA), and especially whether these are influenced by genetic or environmental factors, remain underexplored. We therefore quantified associations between the multi-ome comprising four layers-the proteome, metabolome, external exposome (here, sociodemographic factors), and specific exposome (here, lifestyle)-with six different EAA estimates. Two twin cohorts were used in a discovery-replication scheme, comprising, respectively, young (N = 642; mean age = 22.3) and older (N = 354; mean age = 62.3) twins. Within-pair twin designs were used to assess genetic and environmental effects on associations. We identified 40 multi-omic factors, of which 28 were proteins, associated with EAA in the young twins while adjusting for sex, smoking, and body mass index. Within-pair analyses revealed that genetic confounding influenced these associations heterogeneously, with six multi-omic factors -matrix metalloproteinase 9, complement component C6, histidine, glycoprotein acetyls, lactate, and neighborhood percentage of nonagenarians- remaining significantly associated with EAA, independent of genetic effects. Replication analyses showed that some associations assessed in young twins were consistent in older twins. Our study highlights the differential influence of genetic effects on the associations between the multi-ome and EAA and shows that some, but not all, of the associations persist into adulthood.

Causal associations between epigenetic age and thromboembolism: a bi-directional two-sample Mendelian randomization study

BACKGROUND

Thromboembolism is one of the most prevalent cardiovascular conditions affecting the elder population. The associations between epigenetic aging and thromboembolism risks remain incompletely elucidated. Through Mendelian randomization (MR), this research seeks to assess the causal links between genetically determined epigenetic aging factors and thromboembolism.

RESULTS

Genetic variants were extracted from genome-wide association studies (GWAS) under stringent threshold as instrumental variables (IVs). Bi-directional two-sample MR analyses were conducted to determine the direction of causal associations. We employed the inverse variance weighted (IVW), weighted median, weighted mode and MR Egger to estimate the causal effect, with sensitivity analyses such as Cochran's Q tests, MR-PRESSO and leave-one-out performed to avoid potential heterogeneity and pleiotropy. Our MR analysis revealed a causal association between intrinsic epigenetic age acceleration and deep vein thrombosis of lower extremities (IVW: OR 0.963, 95% CI 0.934-0.992, P = 0.014), and between the genetically determined levels of plasminogen activator inhibitor-1 and other arterial embolism and thrombosis (IVW: OR 1.000, 95% CI 1.000-1.0005, P = 0.029). Causality was also identified between the genetically predicted levels of FGF23 and other arterial embolism and thrombosis (IVW: OR: 1.661, 95% CI 1.051-2.624, P = 0.029) and arterial embolism and thrombosis of lower extremity artery (IVW: OR 1.68, 95% CI 1.031-2.725, P = 0.037). Moreover, bi-directional MR showed reverse effects between portal vein thrombosis and PhenoAge (IVW: OR 0.871, 95% CI 0.765-0.992, P = 0.037) and between venous thromboembolism and GrimAge (IVW: OR 1.186, 95% CI 1.048-1.341, P = 0.007). Sensitivity analysis using Cochran's Q tests, MR-PRESSO and leave-one-out excluded the influence of heterogeneity, horizontal pleiotropy, and outliers.

CONCLUSION

Our results identified a causal association between genetically predicted epigenetic aging factors and thromboembolism. The findings highlight the necessity for further exploration into the underlying etiology of thromboembolism.

There Are Multiple Clocks That Time Us: Cross-Sectional and Longitudinal Associations Among 14 Alternative Indicators of Age and Aging

Aging is a complex process influenced by mechanisms operating at numerous levels of functioning. Multiple biomarkers of age have been identified, yet we know little about how the different alternative age indicators are intertwined. In the Berlin Aging Study II (nmin = 328; nmax = 1 517, women = 51%; 14.27 years of education), we examined how levels and 7-year changes in indicators derived from blood assays, magnetic resonance imaging brain scans, other-ratings, and self-reports converge among older adults. We included 8 epigenetic biomarkers (incl. 5 epigenetic "clocks"), a BioAge composite from clinical laboratory parameters, brain age, skin age, subjective age, subjective life expectancy, and subjective health horizon. We found moderate associations within aging domains, both cross-sectionally and longitudinally over 7 years. However, associations across different domains were infrequent and modest. Notably, participants with older BioAge had correspondingly older epigenetic ages. Our results suggest that different aging clocks are only loosely interconnected and that more specific measures are needed to differentiate healthy from unhealthy aging.

Discrimination, Coping, and DNAm Accelerated Aging Among African American Mothers of the InterGEN Study

Background: Racial discrimination experiences are associated with the activation of stress biology pathways and signs of accelerated biological aging, including alterations in DNA methylation (DNAm). Coping strategies may mitigate stress from racial discrimination and protect against long-term adverse health outcomes. Methods: We conducted a secondary analysis of data from the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure cohort, an all-African-American sample, to test the hypothesis that social support can protect against accelerated biological aging associated with experiences of racial discrimination. We measured biological aging from saliva DNAm using six epigenetic clocks. Clock values were residualized on participant age and the estimated proportion of epithelial cells contributing to the DNA sample and standardized to M = 0, SD = 1 within the analysis sample. The primary analysis was focused on the second-generation PhenoAge and GrimAge clocks and the third-generation DunedinPACE "speedometer," which previous studies have linked with racial discrimination. Results: In our sample (n = 234; mean age = 31.9 years; SD = 5.80), we found evidence consistent with our hypothesis in the case of the PhenoAge clock, but not the other clocks. Among mothers who did not seek social support, experiences of racial discrimination were associated with an older PhenoAge (b = 0.26, 95% CI = 0.02-0.50, p = 0.03). However, social-support seeking mitigated this risk; at the highest levels of social support, no adverse consequences of discrimination were observed (interaction b = -0.01, 95% CI = -0.02--0.00, p = 0.03). Conclusions: The replication of results is needed. Future research should also investigate additional adaptive and maladaptive coping strategies utilized by African American women and mothers to identify protective measures that influence health outcomes.