Epigenetic clock analysis of diet, exercise, education, and lifestyle factors

Glucocorticoid exposure-induced alterations in epigenetic age from human preterm infants and human lung fibroblasts and hippocampal neuronal cells

BACKGROUND

Maternal antenatal corticosteroid treatment is standard care to accelerate fetal maturation. However, there are growing concerns that antenatal corticosteroid administration may harm fetal neurodevelopment. Quantitative assessments of the effects of antenatal corticosteroid on the neonates have not been performed and poorly understood about their complex biology.

RESULTS

We collected Methylation BeadChips-generated DNA methylation data from the Gene Expression Omnibus (GEO) database and then employed "multi-tissue predictor" to quantify the DNAm age of saliva from 36 preterm neonates, which were stratified by the absence (n = 12) or presence (n = 24) of antenatal corticosteroid exposure, as well as 36 full-term neonates. Next, the DNAm age of human lung fibroblast IMR90 cells and human fetal multipotent hippocampal progenitor HPC cells, with or without glucocorticoid treatment, was also determined. We observed that the DNAm age of full-term neonates was significantly higher than that of the preterm neonates, and antenatal corticosteroid exposure accelerated the DNAm age of preterm neonates, while glucocorticoid exposure accelerated the DNAm age of IMR90 cells. Conversely, dexamethasone exposure delayed the DNAm age of HPC cells during the proliferation phase. It is noteworthy that 65% of the differentially methylated probes (DMPs) linked to the multi-tissue predictor marked CpGs and corticosteroid exposure in IMR90 cells exhibited comparable methylation patterns with the DMPs associated with the antenatal corticosteroid exposure in preterm neonates. Conversely, the majority of these DMPs exhibited inverse methylation alterations in dexamethasone-induced HPC cells. Furthermore, the epigenome-wide association study (EWAS) trait enrichment analyses of the DMPs linked to the antenatal corticosteroid exposure in preterm neonates revealed significant associations with prenatal adverse environmental exposure, growth and development, and neuropsychiatric disorders.

CONCLUSIONS

Our results identified the cellular and molecular evidences of epigenetic clock changes in neonatal growth and developmental trajectories with the interference of antenatal corticosteroid treatment and provided potential clinical guidance for the future development of noninvasive fetal assessments to identify pregnant women who could benefit from antenatal corticosteroid in a wider gestational age.

Associations between lifestyle factors, physiological conditions, and epigenetic age acceleration in an Asian population

Epigenetic clocks use DNA methylation (DNAm) levels to predict an individual's biological age. However, relationships between lifestyle/biomarkers and epigenetic age acceleration (EAA) in Asian populations remain unknown. We here explored associations between lifestyle factors, physiological conditions, and epigenetic markers, including HannumEAA, IEAA, PhenoEAA, GrimEAA, DunedinPACE, DNAm-based smoking pack-years (DNAmPACKYRS), and DNAm plasminogen activator inhibitor 1 level (DNAmPAI1). A total of 2474 Taiwan Biobank (TWB) individuals aged between 30 and 70 provided physical health examinations, lifestyle questionnaire surveys, and blood and urine samples. Partial correlation analysis (while adjusting for chronological age, smoking, and drinking status) demonstrated that 29 factors were significantly correlated with at least one epigenetic marker (Pearson's correlation coefficient |r|> 0.15). Subsequently, by exploring the model with the smallest Akaike information criterion (AIC), we identified the best model for each epigenetic marker. As a DNAm-based marker demonstrated to predict healthspan and lifespan with greater accuracy, GrimEAA was also found to be better explained by lifestyle factors and physiological conditions. Totally 15 factors explained 44.7% variability in GrimEAA, including sex, body mass index (BMI), waist-hip ratio (WHR), smoking, hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-C), creatinine, uric acid, gamma-glutamyl transferase (GGT), hemoglobin, and five cell-type proportions. In summary, smoking, elevated HbA1c, BMI, WHR, GGT, and uric acid were associated with more than one kind of EAA. At the same time, higher HDL-C and hemoglobin were related to epigenetic age deceleration (EAD). These findings offer valuable insights into biological aging.

Individual and additive effects of vitamin D, omega-3 and exercise on DNA methylation clocks of biological aging in older adults from the DO-HEALTH trial

While observational studies and small pilot trials suggest that vitamin D, omega-3 and exercise may slow biological aging, larger clinical trials testing these treatments individually or in combination are lacking. Here, we report the results of a post hoc analysis among 777 participants of the DO-HEALTH trial on the effect of vitamin D (2,000 IU per day) and/or omega-3 (1 g per day) and/or a home exercise program on four next-generation DNA methylation (DNAm) measures of biological aging (PhenoAge, GrimAge, GrimAge2 and DunedinPACE) over 3 years. Omega-3 alone slowed the DNAm clocks PhenoAge, GrimAge2 and DunedinPACE, and all three treatments had additive benefits on PhenoAge. Overall, from baseline to year 3, standardized effects ranged from 0.16 to 0.32 units (2.9-3.8 months). In summary, our trial indicates a small protective effect of omega-3 treatment on slowing biological aging over 3 years across several clocks, with an additive protective effect of omega-3, vitamin D and exercise based on PhenoAge.

Multi-tissue transcriptomic aging atlas reveals predictive aging biomarkers in the killifish

Aging is associated with progressive tissue dysfunction, leading to frailty and mortality. Characterizing aging features, such as changes in gene expression and dynamics, shared across tissues or specific to each tissue, is crucial for understanding systemic and local factors contributing to the aging process. We performed RNA-sequencing on 13 tissues at 6 different ages in the African turquoise killifish, the shortest-lived vertebrate that can be raised in captivity. This comprehensive, sex-balanced 'atlas' dataset reveals the varying strength of sex-age interactions across killifish tissues and identifies age-altered biological pathways that are evolutionarily conserved. Demonstrating the utility of this resource, we discovered that the killifish head kidney exhibits a myeloid bias during aging, a phenomenon more pronounced in females than in males. In addition, we developed tissue-specific 'transcriptomic clocks' and identified biomarkers predictive of chronological age. We show the importance of sex-specific clocks for selected tissues and use the tissue clocks to evaluate a dietary intervention in the killifish. Our work provides a comprehensive resource for studying aging dynamics across tissues in the killifish, a powerful vertebrate aging model.

Bidirectional relationship between epigenetic age and stroke, dementia, and late-life depression

Chronological age is an imperfect estimate of molecular aging. Epigenetic age, derived from DNA methylation data, provides a more nuanced representation of aging-related biological processes. We examine the bidirectional relationship between epigenetic age and brain health events (stroke, dementia, late-life depression) using data from 4,018 participants. Participants with a prior brain health event are 4% epigenetically older (β = 0.04, SE = 0.01), indicating these conditions are associated with accelerated aging beyond that captured by chronological age. Additionally, a one standard deviation increase in epigenetic age is associated with 70% higher odds of experiencing a brain health event in the next four years (OR = 1.70, 95% CI = 1.16-2.50), suggesting epigenetic age acceleration is not just a consequence but also a predictor of poor brain health. Mendelian Randomization analyses replicate these findings, supporting their causal nature. Our results support using epigenetic age as a biomarker to evaluate interventions aimed at preventing and promoting recovery after brain health events.

A novel framework to build saliva-based DNA methylation biomarkers: Quantifying systemic chronic inflammation as a case study

Accessible and non-invasive biomarkers that measure human ageing processes and the risk of developing age-related disease are paramount in preventative healthcare. Here, we describe a novel framework to train saliva-based DNA methylation (DNAm) biomarkers that are reproducible and biologically interpretable. By leveraging a reliability dataset with replicates across tissues, we demonstrate that it is possible to transfer knowledge from blood DNAm to saliva DNAm data using DNAm proxies of blood proteins (EpiScores). We apply these methods to create a new saliva-based epigenetic clock (InflammAge) that quantifies systemic chronic inflammation (SCI) in humans. Using a large blood DNAm human cohort with linked electronic health records and over 18,000 individuals (Generation Scotland), we demonstrate that InflammAge significantly associates with all-cause mortality, disease outcomes, lifestyle factors, and immunosenescence; in many cases outperforming the widely used SCI biomarker C-reactive protein (CRP). We propose that our biomarker discovery framework and InflammAge will be useful to improve understanding of the molecular mechanisms underpinning human ageing and to assess the impact of gero-protective interventions.

Early menarche and childbirth accelerate aging-related outcomes and age-related diseases: Evidence for antagonistic pleiotropy in humans

Aging can be understood as a consequence of the declining force of natural selection with age. Consistent with this, the antagonistic pleiotropy theory of aging proposes that aging arises from trade-offs that favor early growth and reproduction. However, evidence supporting antagonistic pleiotropy in humans remains limited. Using Mendelian Randomization (MR), we demonstrated that later ages of menarche or first childbirth were genetically associated with longer parental lifespan, decreased frailty index, slower epigenetic aging, later menopause, and reduced facial aging. Moreover, later menarche or first childbirth were also genetically associated with a lower risk of several age-related diseases, including late-onset Alzheimer's disease (LOAD), type 2 diabetes, heart disease, essential hypertension, and chronic obstructive pulmonary disease (COPD). We validated the associations between the age of menarche, childbirth, and the number of childbirths with several age-related outcomes in the UK Biobank by conducting regression analysis of nearly 200,000 subjects. Our results demonstrated that menarche before the age 11 and childbirth before 21 significantly accelerated the risk of several diseases, and almost doubled the risk for diabetes, heart failure, and quadrupled the risk of obesity, supporting the antagonistic pleiotropy theory. We identified 126 significant single nucleotide polymorphisms (SNPs) that influenced age-related outcomes, some of which were involved in known longevity pathways, including IGF1, growth hormone, AMPK, and mTOR signaling. Our study also identified higher BMI as a mediating factor in causing the increased risk of certain diseases, such as type 2 diabetes and heart failure, in women with early menarche or early pregnancy, emphasizing the importance of the thrifty gene hypothesis in explaining in part the mechanisms behind antagonistic pleiotropy. Our study highlights the complex relationship between genetic legacies and modern diseases, emphasizing the need for gender-sensitive healthcare strategies that consider the unique connections between female reproductive health and aging.

The Genetic and Epigenetic Arms of Human Ageing and Longevity

This proposed review aims to shed light on the major genetic and epigenetic contributions to the ageing process and longevity of individuals. In this context, we summarize the state of knowledge on the most important longevity and ageing genetic variants, and their interactions with the environment, in achieving a healthy lifespan. We also explore the contribution of lifestyle and the influence of non-heritable environmental factors on ageing (i.e., epigenetics). Accordingly, we discuss the role of inflammageing as one of the major targets to overcome morbidity and mortality in older people for the maintenance of healthy ageing. This more integrated view of longevity will display not only the underlying mechanisms at play but also invites the reader to rethink both our ageing process and our attitudes toward age.

No association of posttraumatic stress disorder with epigenetic aging in women at mid-life: A longitudinal cohort study

Posttraumatic stress disorder (PTSD) is associated with mortality and increased risk of diseases of aging, but underlying mechanisms remain unclear. We examine associations of PTSD with one potential pathway, accelerated epigenetic aging. In a longitudinal cohort of trauma-exposed middle-aged women (n = 831, n observations = 1,516), we examined cross-sectional and longitudinal associations between PTSD, with and without comorbid depression, and epigenetic aging measured by six clocks at two time points approximately 13.5 years apart: Hannum, Horvath, PhenoAge, GrimAge, DunedinPoAM, and DunedinPACE. We further examined associations of 3 well-established predictors of aging and mortality also linked with PTSD, namely, body mass index (BMI), diet quality, and physical activity, with epigenetic aging. Cross-sectionally, across all six clocks, epigenetic aging in women with PTSD alone, depression alone, and co-occurring depression and PTSD did not differ from the reference group of women without PTSD or depression in analyses adjusted for age, self-reported race, cell proportions, and ancestry principal components. In longitudinal analyses, we similarly did not find any difference in change in epigenetic age over time by PTSD and depression status at baseline. Among the health factors, in cross-sectional analyses, higher BMI was significantly and consistently associated with greater epigenetic aging measured by the PhenoAge, GrimAge, DunedinPoAM, and DunedinPACE clocks, but not measured by the Hannum or Horvath clocks. Physical activity was not consistently associated with epigenetic aging measured by Hannum, Horvath, PhenoAge, or GrimAge. In analyses with the DunedinPoAm and DunedinPACE clocks, women who reported exercise equivalent to 1 or more hours/week walking had slower epigenetic aging than women with less exercise. Diet quality was not consistently associated with epigenetic aging measured by any of the clocks. Our data do not provide evidence that biological aging, as measured by any of the six epigenetic clocks, is a pathway linking PTSD with mortality and diseases of aging.

Remodeling the Epigenome Through Meditation: Effects on Brain, Body, and Well-being

Epigenetic mechanisms are key processes that constantly reshape genome activity carrying out physiological responses to environmental stimuli. Such mechanisms regulate gene activity without modifying the DNA sequence, providing real-time adaptation to changing environmental conditions. Both favorable and unfavorable lifestyles have been shown to influence body and brain by means of epigenetics, leaving marks on the genome that can either be rapidly reversed or persist in time and even be transmitted trans-generationally. Among virtuous habits, meditation seemingly represents a valuable way of activating inner resources to cope with adverse experiences. While unhealthy habits, stress, and traumatic early-life events may favor the onset of diseases linked to inflammation, neuroinflammation, and neuroendocrine dysregulation, the practice of mindfulness-based techniques was associated with the alleviation of many of the above symptoms, underlying the importance of lifestyles for health and well-being. Meditation influences brain and body systemwide, eliciting structural/morphological changes as well as modulating the levels of circulating factors and the expression of genes linked to the HPA axis and the immune and neuroimmune systems. The current chapter intends to give an overview of pioneering research showing how meditation can promote health through epigenetics, by reshaping the profiles of the three main epigenetic markers, namely DNA methylation, histone modifications, and non-coding RNAs.

Epigenetic Clocks: Beyond Biological Age, Using the Past to Predict the Present and Future

Predicting health trajectories and accurately measuring aging processes across the human lifespan remain profound scientific challenges. Assessing the effectiveness and impact of interventions targeting aging is even more elusive, largely due to the intricate, multidimensional nature of aging-a process that defies simple quantification. Traditional biomarkers offer only partial perspectives, capturing limited aspects of the aging landscape. Yet, over the past decade, groundbreaking advancements have emerged. Epigenetic clocks, derived from DNA methylation patterns, have established themselves as powerful aging biomarkers, capable of estimating biological age and assessing aging rates across diverse tissues with remarkable precision. These clocks provide predictive insights into mortality and age-related disease risks, effectively distinguishing biological age from chronological age and illuminating enduring questions in gerontology. Despite significant progress in epigenetic clock development, substantial challenges remain, underscoring the need for continued investigation to fully unlock their potential in the science of aging.

Differing Effects of Alcohol Use on Epigenetic and Brain Age in Adult Children of Parents with Alcohol Use Disorder

BACKGROUND

It is known that being the adult child of a parent with an alcohol use disorder (ACoA) can confer a wide variety of increased health and psychological risks, including higher rates of anxiety, depression, and post-traumatic stress disorder symptoms. Additionally, ACoAs are at greater risk of developing alcohol/substance use disorders (AUDs/SUDs) than individuals from families without a history of AUDs.

METHODS

ACoA individuals with risky hazardous alcohol use (n = 14) and those not engaged in hazardous use (n = 14) were compared to a group of healthy controls. We examined structural brain differences and applied machine learning algorithms to predict biological brain and DNA methylation ages to investigate differences and determine any accelerated aging between these groups.

RESULTS

Hazardous and non-hazardous ACoA groups had lower predicted brain ages than the healthy control group (n = 100), which may result from neuro-developmental differences between ACoA groups and controls. Within specific brain regions, we observed decreased cortical volume within bilateral pars orbitalis and frontal poles, and the left middle temporal gyrus and entorhinal cortex within the hazardous alcohol ACoA group. When looking at the epigenetic aging data, the hazardous ACoA participants had increased predicted epigenetic age difference scores compared to the control group (n = 34) and the non-hazardous ACoA participant groups.

CONCLUSIONS

The results demonstrate a decreased brain age in the ACoAs compared to control, concurrent with increased epigenetic age specifically in the hazardous ACoA group, laying the foundation for future research to identify individuals with an increased susceptibility to developing hazardous alcohol use. Together, these results provide a better understanding of the associations between epigenetic factors, brain structure, and alcohol use disorders.

Epigenetic Mechanisms in Aging: Extrinsic Factors and Gut Microbiome

BACKGROUND/OBJECTIVES

Aging is a natural physiological process involving biological and genetic pathways. Growing evidence suggests that alterations in the epigenome during aging result in transcriptional changes, which play a significant role in the onset of age-related diseases, including cancer, cardiovascular disease, diabetes, and neurodegenerative disorders. For this reason, the epigenetic alterations in aging and age-related diseases have been reviewed, and the major extrinsic factors influencing these epigenetic alterations have been identified. In addition, the role of the gut microbiome and its metabolites as epigenetic modifiers has been addressed.

RESULTS

Long-term exposure to extrinsic factors such as air pollution, diet, drug use, environmental chemicals, microbial infections, physical activity, radiation, and stress provoke epigenetic changes in the host through several endocrine and immune pathways, potentially accelerating the aging process. Diverse studies have reported that the gut microbiome plays a critical role in regulating brain cell functions through DNA methylation and histone modifications. The interaction between genes and the gut microbiome serves as a source of adaptive variation, contributing to phenotypic plasticity. However, the molecular mechanisms and signaling pathways driving this process are still not fully understood.

CONCLUSIONS

Extrinsic factors are potential inducers of epigenetic alterations, which may have important implications for longevity. The gut microbiome serves as an epigenetic effector influencing host gene expression through histone and DNA modifications, while bidirectional interactions with the host and the underexplored roles of microbial metabolites and non-bacterial microorganisms such as fungi and viruses highlight the need for further research.

Critical review of aging clocks and factors that may influence the pace of aging

Background and objectives

Aging clocks are computational models designed to measure biological age and aging rate based on age-related markers including epigenetic, proteomic, and immunomic changes, gut and skin microbiota, among others. In this narrative review, we aim to discuss the currently available aging clocks, ranging from epigenetic aging clocks to visual skin aging clocks.

Methods

We performed a literature search on PubMed/MEDLINE databases with keywords including: "aging clock," "aging," "biological age," "chronological age," "epigenetic," "proteomic," "microbiome," "telomere," "metabolic," "inflammation," "glycomic," "lifestyle," "nutrition," "diet," "exercise," "psychosocial," and "technology."

Results

Notably, several CpG regions, plasma proteins, inflammatory and immune biomarkers, microbiome shifts, neuroimaging changes, and visual skin aging parameters demonstrated roles in aging and aging clock predictions. Further analysis on the most predictive CpGs and biomarkers is warranted. Limitations of aging clocks include technical noise which may be corrected with additional statistical techniques, and the diversity and applicability of samples utilized.

Conclusion

Aging clocks have significant therapeutic potential to better understand aging and the influence of chronic inflammation and diseases in an expanding older population.

Assessing the utility of epigenetic clocks for health prediction in South Korean

Epigenetic clocks have been developed to track both chronological age and biological age, which is defined by physiological biomarkers and the risk of adverse health outcomes. Epigenetic age acceleration (EAA) has been found to predict various diseases, aging-related factors, and mortality. However, epigenetic clocks have predominantly been developed with individuals of European or Hispanic ancestry, and their association with health outcomes and environmental factors has not been sufficiently assessed in East Asian populations. Here, we investigated nine epigenetic clocks: five trained on chronological age (first-generation) and four on biological age (second-generation), using DNA methylation data from blood samples of South Koreans. EAAs of second-generation epigenetic clocks reflected the risk of chronic diseases (type 2 diabetes and hypertension), levels of health-related blood markers (alanine aminotransferase, aspartate aminotransferase, high density lipoprotein, triglyceride, and high sensitivity C-reactive protein), and lung functions (percentage of predicted FEV1 and percentage of predicted FVC), while EAAs of first generation clocks did not. Using follow-up data, we also found that EAAs of second-generation clocks were associated with the time to onset risks of chronic diseases. Health behavior factors (drinking, smoking, exercise, body mass index, and waist-hip ratio), socioeconomic status (income level and educational attainment), and psychosocial status were associated with EAAs of second-generation clocks, while only smoking status was associated with EAAs of first-generation clocks. We conducted validation analyses in an independent South Korean cohort and replicated the association of EAAs with health outcomes and environmental factors. Age acceleration of epigenetic clocks is influenced by various environmental factors and can serve as an effective predictor of health in South Korea.

Healthful plant-based diets are negatively associated with the rate of biological aging: A national study based on US adults

Plant-based diets are recognized for their health benefits. However, evidence on the association between plant-based diet quality and aging in the US population is limited. This study aimed to investigate the association between different plant-based diet indices, phenotypic age acceleration (PhenoAgeAccel), and biological age acceleration (BioAgeAccel). We hypothesized that healthful plant-based diets would negatively affect PhenoAgeAccel and BioAgeAccel in US adults. The cross-sectional analysis included 22,363 participants, and information was obtained from the National Health and Nutrition Examination Survey database. The quality of plant-based diet was assessed using 3 indices: overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI). Phenotypic age (PA) and biological age (BA) was calculated based on a linear combination of chronological age and 12 multi-system clinical chemistry biomarkers in accordance with the previously established method. PhenoAgeAccel and BioAgeAccel are the residuals of the PA and BA. Weighted linear regression analyses were performed to evaluate the relationships between PDI, hPDI and uPDI, and PhenoAgeAccel and BioAgeAccel. After adjusting for all covariates, we observed that a 10-unit higher PDI score was associated with 0.80 years lower PhenoAgeAccel (β: -0.80, 95% confidence interval [CI]: -0.94, -0.67), and 1.91 years lower BioAgeAccel (β: -1.91, 95% CI: -2.42,-1.40). A 10-unit higher hPDI score was associated with 0.83 years lower PhenoAgeAccel (β: -0.83, 95% CI: -0.96, -0.70), and 1.76 years lower BioAgeAccel (β: -1.76, 95% CI: -2.18, -1.34). Conversely, a 10-unit higher uPDI score was associated with 0.77 years higher PhenoAgeAccel (β: 0.77, 95% CI: 0.66, 0.89) and 1.21 years higher BioAgeAccel (β: 1.21, 95% CI: 0.80, 1.62). These findings suggest that US adults may be able to slow the aging process by increasing adherence to a healthy plant-based diet.

Slower Pace of Epigenetic Aging and Lower Inflammatory Indicators in Females Following a Nutrient-Dense, Plant-Rich Diet Than Those in Females Following the Standard American Diet

Background

Plant-based diets are associated with lower inflammatory biomarkers and reduced risk of age-related chronic diseases. Epigenetic biomarkers of aging are DNA methylation-based tools that estimate biological age and rate of aging, providing insights into age-related health risks. Healthy diet and lifestyle indicators correlate with slower epigenetic aging.

Objectives

Neither inflammatory biomarkers nor epigenetic aging has yet been studied in the nutrient-dense, plant-rich (Nutritarian) diet, a plant-based diet that emphasizes specific plant foods, such as cruciferous vegetables, beans and other legumes, onions and garlic, mushrooms, berries, nuts, and seeds. We aimed to compare inflammatory status and epigenetic age acceleration in females following a Nutritarian diet with those of females following a standard American diet (SAD).

Methods

We investigated dietary inflammatory potential, epigenetic age acceleration using first, second, and third-generation clocks, and additional health-related epigenetic biomarkers in this retrospective cohort study of 48 females who habitually (≥5 y) follow a Nutritarian diet and 49 females without obesity who habitually (≥5 y) follow a SAD. Participants completed a series of online questionnaires and provided a blood sample.

Results

Epigenetic age acceleration, indicated by the third-generation clock DunedinPACE, was significantly slower in the Nutritarian group than that in the SAD group (P = 4.26 × 10-6). The Nutritarian diet group showed lower dietary inflammatory potential, as indicated by Empirical Dietary Inflammatory Pattern and Dietary Inflammatory Index. We observed differences in methylation-predicted immune cell subsets (lower neutrophils and higher T regulatory cells) and a lower epigenetic biomarker proxy for C-reactive protein, both of which suggested a lower inflammatory status in the Nutritarian group. Epigenetic biomarker proxies for LDL cholesterol, body mass index (BMI), insulin-like growth factor binding protein 5, and blood glucose were also lower in the Nutritarian group.

Conclusions

Our findings suggest the Nutritarian diet could help reduce chronic inflammation and slow epigenetic aging.

The role of patient-specific variables in protein corona formation and therapeutic efficacy in nanomedicine

Despite their potential, the adoption of nanotechnology in therapeutics remains limited, with only around eighty nanomedicines approved in the past 30 years. This disparity is partly due to the "one-size-fits-all" approach in medical design, which often overlooks patient-specific variables such as biological sex, genetic ancestry, disease state, environment, and age that influence nanoparticle behavior. Nanoparticles (NPs) must be transported through systemic, microenvironmental, and cellular barriers that vary across heterogeneous patient populations. Key patient-dependent properties impacting NP delivery include blood flow rates, body fat distribution, reproductive organ vascularization, hormone and protein levels, immune responses, and chromosomal differences. Understanding these variables is crucial for developing effective, patient-specific nanotechnologies. The formation of a protein corona around NPs upon exposure to biological fluids significantly alters NP properties, affecting biodistribution, pharmacokinetics, cytotoxicity, and organ targeting. The dynamics of the protein corona, such as time-dependent composition and formation of soft and hard coronas, depend on NP characteristics and patient-specific serum components. This review highlights the importance of understanding protein corona formation across different patient backgrounds and its implications for NP design, including sex, ancestry, age, environment, and disease state. By exploring these variables, we aim to advance the development of personalized nanomedicine, improving therapeutic efficacy and patient outcomes.

Exploring the potential of epigenetic clocks in aging research

The process of aging is a notable risk factor for numerous age-related illnesses. Hence, a reliable technique for evaluating biological age or the pace of aging is crucial for understanding the aging process and its influence on the progression of disease. Epigenetic alterations are recognized as a prominent biomarker of aging, and epigenetic clocks formulated on this basis have been shown to provide precise estimations of chronological age. Extensive research has validated the effectiveness of epigenetic clocks in determining aging rates, identifying risk factors for aging, evaluating the impact of anti-aging interventions, and predicting the emergence of age-related diseases. This review provides a detailed overview of the theoretical principles underlying the development of epigenetic clocks and their utility in aging research. Furthermore, it explores the existing obstacles and possibilities linked to epigenetic clocks and proposes potential avenues for future studies in this field.

Potential Predictor of Epigenetic Age Acceleration in Men: 2D:4D Finger Pattern

OBJECTIVES

Second to fourth digit ratio is widely known indicator of prenatal sex hormones proportion. Higher prenatal androgenization results in longer fourth finger and lower 2D:4D index. The aim of this study was to determine whether the 2D:4D digit ratio is associated with DNA methylation (DNAm) age dependently on sex.

MATERIAL AND METHODS

The study included 182 adults (106 females and 76 males) with a mean age of 51.5 ± 13 years. The investigation consisted of three main parts: a survey, anthropometric dimensions measurements (fingers length) and methylome analysis using collected blood samples. Genome-wide methylation was analyzed using EPIC microarray technology. Epigenetic age and epigenetic age acceleration were calculated using several widely applied algorithms.

RESULTS

Males with the female left hand pattern had more accelerated epigenetic age than those with the male pattern as calculated with PhenoAge and DNAmTL clocks.

CONCLUSIONS

Finger female pattern 2D:4D above or equal to 1 in males is associated with epigenetic age acceleration, indicating that prenatal exposure to estrogens in males may be related to aging process in the later ontogenesis.

Evaluating the connection between diet quality, EpiNutrient intake and epigenetic age: an observational study

BACKGROUND

DNA methylation (DNAm) has unique properties which makes it a potential biomarker for lifestyle-related exposures. Epigenetic clocks, particularly DNAm-based biological age predictors [epigenetic age (EA)], represent an exciting new area of clinical research and deviations of EA from chronological age [epigenetic age acceleration (EAA)] have been linked to overall health, age-related diseases, and environmental exposures.

OBJECTIVES

This observational study investigates the relationships between biological aging and various dietary factors within the LifeLines-DEEP Cohort. These factors include diet quality, processed food consumption, dietary glycemic load, and intake of vitamins involved in maintaining the epigenetic homeostasis (vitamins B-9, B-12, B-6, B-2, and C).

METHODS

Dietary records collected using food-frequency questionnaires were used to estimate diet quality [LifeLines Diet Score (LLDS)], measure the intake of unprocessed/ultraprocessed food according to the NOVA food classification system, and the adequacy of the dietary intake of vitamins B-9, B-12, B-2, B-6, and C. EA using Horvath, Hannum, Levine, and Horvath2 epigenetic clock models and DNAm-predicted telomere length (DNAm-TL) were calculated from DNAm data in 760 subjects. Associations between dietary factors and EAA were tested, adjusting for sex, energy intake, and body composition.

RESULTS

LLDS was associated with EAA (EAA_Horvath: β: -0.148; P = 1 × 10-4; EAA_Hannum: β: -0.148; P = 9 × 10-5; EAA_Levine: β: -0.174; P = 1 × 10-5; and EAA_Horvath2: β: -0.176; P = 4 × 10-6) and DNAm-TL (β: 0.116; P = 0.003). Particularly, EAA was associated with dietary glycemic load (EAA_Horvath: β: 0.476; P = 9 × 10-10; EAA_Hannum: β: 0.565; P = 1 × 10-13; EAA_Levine: β: 0.469; P = 5 × 10-9; EAA_Horvath2: β: 0.569; P = 1 × 10-13; and DNAmTL adjusted for age: β: -0.340; P = 2 × 10-5) and different measures of food processing (NOVA classes 1 and 4). Positive EAA was also associated with inadequate intake of vitamin B-12 (EAA_Horvath: β: -0.167; P = 0.002; EAA_Hannum: β: -0.144; P = 0.007; and EAA_Horvath2: β: -0.126; P = 0.019) and C (EAA_Hannum: β: -0.136; P = 0.010 and EAA_Horvath2: β: -0.151; P = 0.005).

CONCLUSIONS

Our findings corroborate the hypothesis that nutrition plays a pivotal role in influencing epigenetic homeostasis, especially DNAm, thereby contributing to individual health trajectories and the pace of aging.

Younger epigenetic age is associated with higher cardiorespiratory fitness in individuals with airflow limitation

We hypothesized that increased cardiorespiratory fitness (CRF) slows down a person's aging, particularly in individuals with chronic airflow limitation (CAL). Participants aged ≥40 years (n = 78) had baseline blood DNA methylation profiled and underwent cardiopulmonary cycle exercise testing at baseline and at three years. Epigenetic clocks were calculated and tested for their association with CRF using linear regression. Differentially methylated genes associated with CRF were identified using a robust linear model. Higher CRF at baseline was associated with lower age acceleration in the epigenetic clocks DNAmAgeSkinBlood (p = 0.016), DNAmGrimAge (p = 0.012), and DNAmGrimAge2 (p = 0.011). These effects were consistent in individuals with CAL (DNAmGrimAge p = 0.009 and DNAmGrimAge2 p = 0.007). CRF at three years was associated with baseline DNAmGrimAge (p = 0.015) and DNAmGrimAge2 (p = 0.011). Differentially methylated genes associated with CRF enriched multiple aging-related pathways, including cellular senescence. Enhancing CRF may be one intervention that can slow biological aging and improve health outcomes in chronic respiratory diseases.

Influence of physical activity on the epigenetic clock: evidence from a Japanese cross-sectional study

BACKGROUND

Biological age, especially epigenetic age derived from the epigenetic clock, is a significant measure of aging, considering the differences in aging rates among individuals. The epigenetic clock, a machine learning-based algorithm, uses DNA methylation states to estimate biological age. Previous studies have reported inconsistent associations between physical activity (PA) and the epigenetic clock, especially second-generation clocks such as PhenoAge and GrimAge. This study aimed to clarify this relationship using cross-sectional data from Japanese participants aged 40-69.

METHODS

We used two datasets from the Saga J-MICC study, of which 867 samples were available for analysis. DNA methylation data from peripheral blood samples were used to calculate the epigenetic age using the epigenetic clocks PhenoAge and GrimAge. PA and sedentary time were measured using a single-axis accelerometer, while self-reported PA, sedentary time, and covariates were assessed using a self-administered questionnaire. The association between PA or sedentary time and epigenetic age acceleration was assessed using multiple linear regression.

RESULTS

Pearson's correlation coefficients between accelerometer-based and self-reported PA variables ranged from 0.09 to 0.20. Multivariable regression analysis showed that accelerometer-based PA and sedentary time were associated with epigenetic age decelerations and accelerations, respectively. However, self-reported PA was not associated with the epigenetic age accelerations.

CONCLUSIONS

These results indicate that reducing sedentary time and increasing PA were associated with slowing both PhenoAge and GrimAge, even in East Asian populations with different exercise habits, body shapes, and lifestyles. This study highlights the potential of objective second-generation epigenetic age acceleration as an outcome index for healthcare interventions and clinical applications.

DNA Methylation Age Mediates Effect of Metabolic Profile on Cardiovascular and General Aging

BACKGROUND

Alterations in lipid metabolism and DNA methylation are 2 hallmarks of aging. Connecting metabolomic, epigenomic, and aging outcomes help unravel the complex mechanisms underlying aging. We aimed to assess whether DNA methylation clocks mediate the association of circulating metabolites with incident atherosclerotic cardiovascular disease (ASCVD) and frailty.

METHODS

The China Kadoorie Biobank is a prospective cohort study with a baseline survey from 2004 to 2008 and a follow-up period until December 31, 2018. We used the Infinium Methylation EPIC BeadChip to measure the methylation levels of 988 participants' baseline blood leukocyte DNA. Metabolite profiles, including lipoprotein particles, lipid constituents, and various circulating metabolites, were measured using quantitative nuclear magnetic resonance. The pace of DNA methylation age acceleration (AA) was calculated using 5 widely used epigenetic clocks (the first generation: Horvath, Hannum, and Li; the second generation: Grim and Pheno). Incident ASCVD was ascertained through linkage with local death and disease registries and national health insurance databases, supplemented by active follow-up. The frailty index was constructed using medical conditions, symptoms, signs, and physical measurements collected at baseline.

RESULTS

A total of 508 incident cases of ASCVD were documented during a median follow-up of 9.5 years. The first generation of epigenetic clocks was associated with the risk of ASCVD (P<0.05). For each SD increment in LiAA, HorvathAA, and HannumAA, the corresponding hazard ratios for ASCVD risk were 1.16 (1.05-1.28), 1.10 (1.00-1.22), and 1.17 (1.04-1.31), respectively. Only LiAA mediated the association of various metabolites (lipids, fatty acids, histidine, and inflammatory biomarkers) with ASCVD, with the mediating proportion reaching up to 15% for the diameter of low-density lipoprotein (P=1.2×10-2). Regarding general aging, a 1-SD increase in GrimAA was associated with an average increase of 0.10 in the frailty index (P=2.0×10-3), and a 33% and 63% increased risk of prefrailty and frailty at baseline (P=1.5×10-2 and 5.8×10-2), respectively; this association was not observed with other clocks. GrimAA mediated the effect of various lipids, fatty acids, glucose, lactate, and inflammatory biomarkers on the frailty index, with the mediating proportion reaching up to 22% for triglycerides in very small-sized very low-density lipoprotein (P=6.0×10-3).

CONCLUSIONS

These findings suggest that epigenomic mechanisms may play a role in the associations between circulating metabolites and the aging process. Different mechanisms underlie the first and second generations of DNA methylation age in cardiovascular and general aging.

Lagged effects of childhood depressive symptoms on adult epigenetic aging

BACKGROUND

Cross-sectional studies have identified health risks associated with epigenetic aging. However, it is unclear whether these risks make epigenetic clocks 'tick faster' (i.e. accelerate biological aging). The current study examines concurrent and lagged within-person changes of a variety of health risks associated with epigenetic aging.

METHODS

Individuals from the Great Smoky Mountains Study were followed from age 9 to 35 years. DNA methylation profiles were assessed from blood, at multiple timepoints (i.e. waves) for each individual. Health risks were psychiatric, lifestyle, and adversity factors. Concurrent (N = 539 individuals; 1029 assessments) and lagged (N = 380 individuals; 760 assessments) analyses were used to determine the link between health risks and epigenetic aging.

RESULTS

Concurrent models showed that BMI (r = 0.15, PFDR < 0.01) was significantly correlated to epigenetic aging at the subject-level but not wave-level. Lagged models demonstrated that depressive symptoms (b = 1.67 months per symptom, PFDR = 0.02) in adolescence accelerated epigenetic aging in adulthood, also when models were fully adjusted for BMI, smoking, and cannabis and alcohol use.

CONCLUSIONS

Within-persons, changes in health risks were unaccompanied by concurrent changes in epigenetic aging, suggesting that it is unlikely for risks to immediately 'accelerate' epigenetic aging. However, time lagged analyses indicated that depressive symptoms in childhood/adolescence predicted epigenetic aging in adulthood. Together, findings suggest that age-related biological embedding of depressive symptoms is not instant but provides prognostic opportunities. Repeated measurements and longer follow-up times are needed to examine stable and dynamic contributions of childhood experiences to epigenetic aging across the lifespan.

Childhood adversity, accelerated GrimAge, and associated health consequences

Childhood adversity is linked to psychological, behavioral, and physical health problems, including obesity and cardiometabolic disease. Epigenetic alterations are one pathway through which the effects of early life stress and adversity might persist into adulthood. Epigenetic mechanisms have also been proposed to explain why cardiometabolic health can vary greatly between individuals with similar Body Mass Index (BMIs). We evaluated two independent cross-sectional cohorts of adults without known medical illness, one of which explicitly recruited individuals with early life stress (ELS) and control participants (n = 195), and the other a general community sample (n = 477). In these cohorts, we examine associations between childhood adversity, epigenetic aging, and metabolic health. Childhood adversity was associated with increased GrimAge Acceleration (GAA) in both cohorts, both utilizing a dichotomous yes/no classification (both p < 0.01) as well as a continuous measure using the Childhood Trauma Questionnaire (CTQ) (both p < 0.05). Further investigation demonstrated that CTQ subscales for physical and sexual abuse (both p < 0.05) were associated with increased GAA in both cohorts, whereas physical and emotional neglect were not. In both cohorts, higher CTQ was also associated with higher BMI and increased insulin resistance (both p < 0.05). Finally, we demonstrate a moderating effect of BMI on the relationship between GAA and insulin resistance where GAA correlated with insulin resistance specifically at higher BMIs. These results, which were largely replicated between two independent cohorts, suggest that interactions between epigenetics, obesity, and metabolic health may be important mechanisms through which childhood adversity contributes to long-term physical and metabolic health effects.

A combination nutritional supplement reduces DNA methylation age only in older adults with a raised epigenetic age

An increase in systemic inflammation (inflammaging) is one of the hallmarks of aging. Epigenetic (DNA methylation) clocks can quantify the degree of biological aging and this can be reversed by lifestyle and pharmacological intervention. We aimed to investigate whether a multi-component nutritional supplement could reduce systemic inflammation and epigenetic age in healthy older adults.We recruited 80 healthy older participants (mean age ± SD: 71.85 ± 6.23; males = 31, females = 49). Blood and saliva were obtained pre and post a 12-week course of a multi-component supplement, containing: Vitamin B3, Vitamin C, Vitamin D, Omega 3 fish oils, Resveratrol, Olive fruit phenols and Astaxanthin. Plasma GDF-15 and C-reactive protein (CRP) concentrations were quantified as markers of biological aging and inflammation respectively. DNA methylation was assessed in whole blood and saliva and used to derive epigenetic age using various clock algorithms.No difference between the epigenetic and chronological ages of participants was observed pre- and post-treatment by the blood-based Horvath or Hannum clocks, or the saliva-based InflammAge clock. However, in those with epigenetic age acceleration of ≥ 2 years at baseline, a significant reduction in epigenetic age (p = 0.015) and epigenetic age acceleration (p = 0.0058) was observed post-treatment using the saliva-based InflammAge clock. No differences were observed pre- and post-treatment in plasma GDF-15 and CRP, though participants with CRP indicative of an elevated cardiovascular disease risk (hsCRP ≥ 3µg/ml), had a reduction in CRP post-supplementation (p = 0.0195).Our data suggest a possible benefit of combined nutritional supplementation in individuals with an accelerated epigenetic age and inflammaging.

Associations of healthy eating patterns with biological aging: national health and nutrition examination survey (NHANES) 1999-2018

BACKGROUND

Healthy dietary patterns have been negatively associated with methylation-based measures of biological age, yet previous investigations have been unable to establish the relationship between them and biological aging assessed through blood chemistry-based clinical biomarkers. We sought to assess the associations of 4 dietary metrics with 4 measures of biological age.

METHODS

Among 16,666 participants in NHANES 1999-2018, 4 dietary metrics [Dietary inflammatory index (DII), Dietary approaches to stop hypertension index (DASH), Alternate mediterranean diet score (aMED), and Healthy eating index-2015 (HEI-2015)] were calculated through the 'dietaryindex' R package. Twelve blood chemistry parameters were utilized to compute 4 indicators of biological age [homeostatic dysregulation (HD), allostatic load (AL), Klemera-Doubal method (KDM), and phenotypic age (PA)]. Binomial logistic regression models and restricted cubic spline (RCS) regression were employed to evaluate the associations.

RESULTS

All 4 dietary metrics were significantly associated with biological age acceleration or deceleration. In comparison to the lowest DII, the odds ratios (ORs) for accelerated HD, AL, KDM, and PA were 1.25 (1.08,1.45), 1.29 (1.11,1.50), 1.34 (1.08,1.65), and 1.61 (1.39,1.87) for the highest. The multivariable-adjusted ORs of the highest quartile of DASH, aMED, and HEI-2015 were 0.85 (0.73,0.97), 0.88 (0.74,1.04), and 0.84 (0.74,0.96) for HD, 0.64 (0.54,0.75), 0.61 (0.52,0.72), and 0.70 (0.59,0.82) for AL, 0.68 (0.54,0.85), 0.62 (0.50,0.76), and 0.71 (0.58,0.87) for KDM, and 0.50 (0.42,0.59), 0.64 (0.54,0.76), and 0.51 (0.44,0.58) for PA when compared with the lowest level. The findings were validated by the best-fitting dose-response curves for the associations. Among participants consuming dietary supplements (Pinteraction < 0.05), the positive effects of a healthy dietary pattern on biological aging were more pronounced. Systemic immune inflammation index (SII) and atherogenic index of plasma (AIP) were identified as being involved in and mediating the associations.

CONCLUSIONS

Biological aging assessed through blood chemistry-based clinical biomarkers is negatively associated with diet quality. The anti-aging benefits of improving the diet may be due to its ability to reduce inflammation and lower blood lipids.

High-dimensional Ageome Representations of Biological Aging across Functional Modules

The aging process involves numerous molecular changes that lead to functional decline and increased disease and mortality risk. While epigenetic aging clocks have shown accuracy in predicting biological age, they typically provide single estimates for the samples and lack mechanistic insights. In this study, we challenge the paradigm that aging can be sufficiently described with a single biological age estimate. We describe Ageome, a computational framework for measuring the epigenetic age of thousands of molecular pathways simultaneously in mice and humans. Ageome is based on the premise that an organism's overall biological age can be approximated by the collective ages of its functional modules, which may age at different rates and have different biological ages. We show that, unlike conventional clocks, Ageome provides a high-dimensional representation of biological aging across cellular functions, enabling comprehensive assessment of aging dynamics within an individual, in a population, and across species. Application of Ageome to longevity intervention models revealed distinct patterns of pathway-specific age deceleration. Notably, cell reprogramming, while rejuvenating cells, also accelerated aging of some functional modules. When applied to human cohorts, Ageome demonstrated heterogeneity in predictive power for mortality risk, and some modules showed better performance in predicting the onset of age-related diseases, especially cancer, compared to existing clocks. Together, the Ageome framework offers a comprehensive and interpretable approach for assessing aging, providing insights into mechanisms and targets for intervention.

Dietary factors and DNA methylation-based markers of ageing in 5310 middle-aged and older Australian adults

The role of nutrition in healthy ageing is acknowledged but details of optimal dietary composition are still uncertain. We aimed to investigate the cross-sectional associations between dietary exposures, including macronutrient composition, food groups, specific foods, and overall diet quality, with methylation-based markers of ageing. Blood DNA methylation data from 5310 participants (mean age 59 years) in the Melbourne Collaborative Cohort Study were used to calculate five methylation-based measures of ageing: PCGrimAge, PCPhenoAge, DunedinPACE, ZhangAge, TelomereAge. For a range of dietary exposures, we estimated (i) the 'equal-mass substitution effect', which quantifies the effect of adding the component of interest to the diet while keeping overall food mass constant, and (ii) the 'total effect', which quantifies the effect of adding the component of interest to the current diet. For 'equal-mass substitution effects', the strongest association for macronutrients was for fibre intake (e.g. DunedinPACE, per 12 g/day - 0.10 [standard deviations]; 95%CI - 0.15, - 0.05, p < 0.001). Associations were positive for protein (e.g. PCGrimAge, per 33 g/day 0.04; 95%CI 0.01-0.08, p = 0.005). For food groups, the evidence tended to be weak, though sugar-sweetened drinks showed positive associations, as did artificially-sweetened drinks (e.g. DunedinPACE, per 91 g/day 0.06, 95%CI 0.03-0.08, p < 0.001). 'Total effect' estimates were generally very similar. Scores reflecting overall diet quality suggested that healthier diets were associated with lower levels of ageing markers. High intakes of fibre and low intakes of protein and sweetened drinks, as well as overall healthy diets, showed the most consistent associations with lower methylation-based ageing in our study.

Defining familial longevity and developing a familial longevity score for unbiased epigenetic studies in a birth cohort

Aim: Longevity accumulating in families has genetic and epigenetic components. To study early and unbiased epigenetic predictors of longevity prospectively, a birth cohort would be ideal. However, the original family longevity selection score (FLoSS) focuses on populations of elderly only.Methods: In the German birth cohort KUNO-Kids we assessed when information for such scores may be best collected and how to calculate an adapted FLoSS.Results: A total of 551 families contributed to adapted FLoSS, with a mean score of -0.15 (SD 2.33). Adapted FLoSS ≥7 as a marker of exceptional longevity occurred in 3.3% of families, comparable to original FLoSS in elderly.Conclusion: An adapted FLoSS from data collectable postnatally may be a feasible tool to study unbiased epigenetic predictors for longevity.

Lifestyle differences between co-twins are associated with decreased similarity in their internal and external exposome profiles

Whether differences in lifestyle between co-twins are reflected in differences in their internal or external exposome profiles remains largely underexplored. We therefore investigated whether within-pair differences in lifestyle were associated with within-pair differences in exposome profiles across four domains: the external exposome, proteome, metabolome and epigenetic age acceleration (EAA). For each domain, we assessed the similarity of co-twin profiles using Gaussian similarities in up to 257 young adult same-sex twin pairs (54% monozygotic). We additionally tested whether similarity in one domain translated into greater similarity in another. Results suggest that a lower degree of similarity in co-twins' exposome profiles was associated with greater differences in their behavior and substance use. The strongest association was identified between excessive drinking behavior and the external exposome. Overall, our study demonstrates how social behavior and especially substance use are connected to the internal and external exposomes, while controlling for familial confounders.

Active longevity and aging: dissecting the impacts of physical and sedentary behaviors on longevity and age acceleration

BACKGROUND

To examine the associations of physical activity (PA) and sedentary behavior (SB) with longevity and age acceleration (AA) using observational and Mendelian randomization (MR) studies, and quantify the mediating effects of lipids.

METHODS

In Guangzhou Biobank Cohort Study (GBCS), PA and SB were assessed by the Chinese Version of the International Physical Activity Questionnaire. Longevity was defined as participants whose age at follow-up or at death was at or above the 90th age percentile. AA was defined as the residual resulting from a linear model that regressed phenotypic age against chronological age. Linear regression and Poisson regression with robust error variance were used to assess the associations of total and specific PA in different intensities, and SB with AA and longevity, yielding βs or relative risks (RRs) and 95% confidence intervals (CIs). Two-sample MR was conducted to examine the causal effects. Mediation analysis was used to assess the mediating effects of lipids.

RESULTS

Of 20,924 participants aged 50 + years in GBCS, during an average follow-up of 15.0 years, compared with low PA, moderate and high PA were associated with higher likelihood of longevity (RR (95% CI): 1.56 (1.16, 2.11), 1.66 (1.24, 2.21), respectively), and also cross-sectionally associated with lower AA (β (95% CI): -1.43 (-2.41, -0.45), -2.09 (-3.06, -1.11) years, respectively). Higher levels of moderate PA (MPA) were associated with higher likelihood of longevity and lower AA, whereas vigorous PA (VPA) showed opposite effects. The association of PA with longevity observed in GBCS was mediated by low-density lipoprotein cholesterol (LDL-C) by 8.23% (95% CI: 3.58-39.61%), while the association with AA was mediated through LDL-C, triglycerides and total cholesterol by 5.13% (3.94-7.30%), 7.81% (5.98-11.17%), and 3.37% (2.59-4.80%), respectively. Additionally, in two-sample MR, SB was positively associated with AA (β (95% CI): 1.02 (0.67, 1.36) years).

CONCLUSIONS

PA showed protective effects on longevity and AA, with the effects being partly mediated through lipids. Conversely, SB had a detrimental impact on AA. MPA was associated with higher likelihood of longevity and reduced AA, whereas VPA showed adverse effects. Our findings reinforce the recommendation of "sit less and move more" to promote healthy longevity, and highlight the potential risks associated with VPA in the elderly.

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

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

GWAS of biological aging to find longevity genes in schizophrenia

Schizophrenia (SCZ) is a severe psychotic disorder associated with premature mortality and aging. Moreover, the symptoms and progression of psychiatric disorders in general are associated with decreased lifespan, biological aging, and poorer medical outcomes. In this study, we investigated the relationship between several epigenetic clocks and scanned the entire genome for association in a cohort of SCZ individuals (n = 107). Biological age was computed from blood DNA methylation (DNAm) and tested for association against  common  variants across the genome using general linear models. Genes affecting epigenetic age acceleration in our cohort were found mainly when using the telomeric length clock rather than the other biological clocks. These findings pair with existing evidence that there are some genes associated with longevity and suggest further investigations of  putative biological mechanisms for morbidity and premature mortality, not only in patients with SCZ but also in the general population.

Interplay Between Skeletal and Hematopoietic Cells in the Bone Marrow Microenvironment in Homeostasis and Aging

PURPOSE OF THE REVIEW

In this review, we discuss the most recent scientific advances on the reciprocal regulatory interactions between the skeletal and hematopoietic stem cell niche, focusing on immunomodulation and its interplay with the cell's mitochondrial function, and how this impacts osteoimmune health during aging and disease.

RECENT FINDINGS

Osteoimmunology investigates interactions between cells that make up the skeletal stem cell niche and immune system. Much work has investigated the complexity of the bone marrow microenvironment with respect to the skeletal and hematopoietic stem cells that regulate skeletal formation and immune health respectively. It has now become clear that these cellular components cooperate to maintain homeostasis and that dysfunction in their interaction can lead to aging and disease. Having a deeper, mechanistic appreciation for osteoimmune regulation will lead to better research perspective and therapeutics with the potential to improve the aging process, skeletal and hematologic regeneration, and disease targeting.

The Impact of Childhood Mental Health and Substance Use on Methylation Aging Into Adulthood

OBJECTIVE

To test whether childhood mental health symptoms, substance use, and early adversity accelerate the rate of DNA methylation (DNAm) aging from adolescence to adulthood.

METHOD

DNAm was assayed from blood samples in 381 participants in both adolescence (mean [SD] age = 13.9 [1.6] years) and adulthood (mean [SD] age = 25.9 [2.7] years). Structured diagnostic interviews were completed with participants and their parents at multiple childhood observations (1,950 total) to assess symptoms of common mental health disorders (attention-deficit/hyperactivity disorder, oppositional defiant disorder, conduct disorder, anxiety, and depression) and common types of substance use (alcohol, cannabis, nicotine) and early adversities.

RESULTS

Neither childhood mental health symptoms nor substance use variables were associated with DNAm aging cross-sectionally. In contrast, the following mental health symptoms and substance variables were associated with accelerated DNAm aging from adolescence to adulthood: depressive symptoms (b = 0.314, SE = 0.127, p = .014), internalizing symptoms (b = 0.108, SE = 0.049, p = .029), weekly cannabis use (b =1.665, SE = 0.591, p = .005), and years of weekly cannabis use (b = 0.718, SE = 0.283, p = .012). In models testing all individual variables simultaneously, the combined effect of the variables was equivalent to a potential difference of 3.17 to 3.76 years in DNAm aging. A final model tested a variable assessing cumulative exposure to mental health symptoms, substance use, and early adversities. This cumulative variable was strongly associated with accelerated aging (b = 0.126, SE = 0.044, p = .005).

CONCLUSION

Mental health symptoms and substance use accelerated DNAm aging into adulthood in a manner consistent with a shared risk mechanism.

PLAIN LANGUAGE SUMMARY

Using data from 381 participants in the Great Smoky Mountains Study, the authors examined whether childhood mental health symptoms, substance use, and early adversity accelerate biological aging, as measured by DNA methylation age, from adolescence to adulthood. Depressive symptoms and cannabis use were found to significantly accelerate biological aging. Models that tested the combined effect of mental health symptoms, substance use, and early adversity demonstrated that there was a shared effect across these types of childhood problems on accelerated aging.

Lifestyle factors and metabolomic aging biomarkers: Meta-analysis of cross-sectional and longitudinal associations in three prospective cohorts

Biological age uses biophysiological information to capture a person's age-related risk of adverse outcomes. MetaboAge and MetaboHealth are metabolomics-based biomarkers of biological age trained on chronological age and mortality risk, respectively. Lifestyle factors contribute to the extent chronological and biological age differ. The association of lifestyle factors with MetaboAge and MetaboHealth, potential sex differences in these associations, and MetaboAge's and MetaboHealth's sensitivity to lifestyle changes have not been studied yet. Linear regression analyses and mixed-effect models were used to examine the cross-sectional and longitudinal associations of scaled lifestyle factors with scaled MetaboAge and MetaboHealth in 24,332 middle-aged participants from the Doetinchem Cohort Study, Rotterdam Study, and UK Biobank. Random-effect meta-analyses were performed across cohorts. Repeated metabolomics measurements had a ten-year interval in the Doetinchem Cohort Study and a five-year interval in the UK Biobank. In the first study incorporating longitudinal information on MetaboAge and MetaboHealth, we demonstrate associations between current smoking, sleeping ≥8 hours/day, higher BMI, and larger waist circumference were associated with higher MetaboHealth, the latter two also with higher MetaboAge. Furthermore, adhering to the dietary and physical activity guidelines were inversely associated with MetaboHealth. Lastly, we observed sex differences in the associations between alcohol use and MetaboHealth.

Discovering the direct relations between nutrients and epigenetic ageing

BACKGROUND

Along with the ageing of society, the absolute prevalence of age-related diseases is expected to rise, leading to a substantial burden on healthcare systems and society. Thus, there is an urgent need to promote healthy ageing. As opposed to chronological age, biological age was introduced to accurately represent the ageing process, as it considers physiological deterioration that is linked to morbidity and mortality risk. Furthermore, biological age responds to various factors, including nutritional factors, which have the potential to mitigate the risk of age-related diseases. As a result, a promising biomarker of biological age known as the epigenetic clock has emerged as a suitable measure to investigate the direct relations between nutritional factors and ageing, thereby identifying potential intervention targets to improve healthy ageing.

METHODS

In this study, we analysed data from 3,969 postmenopausal women from the Women's Health Initiative to identify nutrients that are associated with the rate of ageing by using an accurate measure of biological age called the PhenoAge epigenetic clock. We used Copula Graphical Models, a data-driven exploratory analysis tool, to identify direct relationships between nutrient intake and age-acceleration, while correcting for every variable in the dataset.

RESULTS

We revealed that increased dietary intakes of coumestrol, beta-carotene and arachidic acid were associated with decelerated epigenetic ageing. In contrast, increased intakes of added sugar, gondoic acid, behenic acid, arachidonic acid, vitamin A and ash were associated with accelerated epigenetic ageing in postmenopausal women.

CONCLUSION

Our study discovered direct relations between nutrients and epigenetic ageing, revealing promising areas for follow-up studies to determine the magnitude and causality of our estimated diet-epigenetic relationships.

Generations of epigenetic clocks and their links to socioeconomic status in the Health and Retirement Study

Aim: This is a brief description of links between nine epigenetic clocks related to human aging and socioeconomic and behavioral characteristics as well as health outcomes.Materials & methods: We estimate frequently used and novel clocks from one data source, the Health and Retirement Study.Results: While all of these clocks are thought to reflect "aging," they use different CpG sites and do not strongly relate to each other. First and fourth generation clocks are not as linked to socioeconomic status or health outcomes as second and third generation clocks.Conclusion: Epigenetic clocks reflect exciting new tools and their continued evolution is likely to improve our understanding of how exposures get under the skin to accelerate aging.

Examining nutrition strategies to influence DNA methylation and epigenetic clocks: a systematic review of clinical trials

Nutrition has powerful impacts on our health and longevity. One of the mechanisms by which nutrition might influence our health is by inducing epigenetic modifications, modulating the molecular mechanisms that regulate aging. Observational studies have provided evidence of a relationship between nutrition and differences in DNA methylation. However, these studies are limited in that they might not provide an accurate control of the interactions between different nutrients, or between nutrition and other lifestyle behaviors. Here we systematically reviewed clinical studies examining the impact of nutrition strategies on DNA methylation. We examined clinical studies in community-dwelling adults testing the effects of nutrition interventions on i) global DNA methylation and its proxies, and ii) epigenetic clocks. We included 21 intervention studies that focused on the effects of healthy nutrition patterns, specific foods or nutrients, as well as the effect of multivitamin or multimineral supplements. In four studies on the methylation effects of healthy dietary patterns, as defined by being rich in vegetables, fruits, whole-grains, and nuts and reduced in the intake of added sugars, saturated fat, and alcohol, two of them suggested that a healthy diet, is associated with lower epigenetic age acceleration, one of them reported increases in global DNA methylation, while another one found no diet effects. Studies examining epigenetic effects of specific foods, nutrients, or mixtures of nutrients were scarce. For both folic acid and polyunsaturated fatty acids, the available independent studies produced conflicting findings. Although more evidence is still needed to draw firm conclusions, results begin to suggest that healthy dietary patterns have positive effects on DNA methylation. Additional evidence from large randomized-controlled clinical trials is needed to support the effects of healthy nutrition on the DNA methylome.

DNA Methylation-derived biological age and long-term mortality risk in subjects with type 2 diabetes

BACKGROUND

Individuals with type 2 diabetes (T2D) face an increased mortality risk, not fully captured by canonical risk factors. Biological age estimation through DNA methylation (DNAm), i.e. the epigenetic clocks, is emerging as a possible tool to improve risk stratification for multiple outcomes. However, whether these tools predict mortality independently of canonical risk factors in subjects with T2D is unknown.

METHODS

Among a cohort of 568 T2D patients followed for 16.8 years, we selected a subgroup of 50 subjects, 27 survived and 23 deceased at present, passing the quality check and balanced for all risk factors after propensity score matching. We analyzed DNAm from peripheral blood leukocytes using the Infinium Human MethylationEPIC BeadChip (Illumina) to evaluate biological aging through previously validated epigenetic clocks and assess the DNAm-estimated levels of selected inflammatory proteins and blood cell counts. We tested the associations of these estimates with mortality using two-stage residual-outcome regression analysis, creating a reference model on data from the group of survived patients.

RESULTS

Deceased subjects had higher median epigenetic age expressed with DNAmPhenoAge algorithm (57.49 [54.72; 60.58] years. vs. 53.40 [49.73; 56.75] years; p = 0.012), and accelerated DunedinPoAm pace of aging (1.05 [1.02; 1.11] vs. 1.02 [0.98; 1.06]; p = 0.012). DNAm PhenoAge (HR 1.16, 95% CI 1.05-1.28; p = 0.004) and DunedinPoAm (HR 3.65, 95% CI 1.43-9.35; p = 0.007) showed an association with mortality independently of canonical risk factors. The epigenetic predictors of 3 chronic inflammation-related proteins, i.e. CXCL10, CXCL11 and enRAGE, C-reactive protein methylation risk score and DNAm-based estimates of exhausted CD8 + T cell counts were higher in deceased subjects when compared to survived.

CONCLUSIONS

These findings suggest that biological aging, as estimated through existing epigenetic tools, is associated with mortality risk in individuals with T2D, independently of common risk factors and that increased DNAm-surrogates of inflammatory protein levels characterize deceased T2D patients. Replication in larger cohorts is needed to assess the potential of this approach to refine mortality risk in T2D.

Associations of Epigenetic Age Estimators With Cognitive Function Trajectories in the Women's Health Initiative Memory Study

BACKGROUND AND OBJECTIVES

Epigenetic age estimators indicating faster/slower biological aging vs chronological age independently associate with several age-related outcomes; however, longitudinal associations with cognitive function are understudied. We examined associations of epigenetic age estimators with cognitive function measured annually.

METHODS

This longitudinal study consisted of older women enrolled in the Women's Health Initiative Memory Study with DNA methylation (DNAm) collected at baseline (1995-1998) from 3 ancillary studies and were followed up to 13 years. Global cognitive function was measured annually by Modified Mini-Mental State Examination (3MS; baseline-2007) and by modified Telephone Interview for Cognitive Status (TICS-m, 2008-2021). We calculated 5 epigenetic age estimators: extrinsic AgeAccel, intrinsic AgeAccel, AgeAccelPheno, AgeAccelGrim2, Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE), and AgeAccelGrim2 components (DNA-based plasma protein surrogates). We estimated longitudinal epigenetic age estimator-cognitive function associations using linear mixed-effects models containing age, education, race or ethnicity, and subsequently alcohol, smoking, body mass index, and comorbidities. We examined effect modification by APOE ε4 carriage.

RESULTS

A total of 795 participants were enrolled. The mean baseline age was 70.8 ± 4 years (10.7% Black, 3.9% Hispanic or Latina, 85.4% White), A 1-SD (0.12) increment in DunedinPACE associated with faster annual declines in TICS-m scores in minimally adjusted (β = -0.118, 95% CI -0.202 to -0.034; p = 0.0006) and fully adjusted (β = -0.123, 95% CI -0.211 to -0.036; p = 0.006) models. AgeAccelPheno associated with faster annual declines in TICS-m with minimal adjustment (β = -0.091, 95% CI -0.176 to -0.006; p = 0.035) but not with full adjustment. No other epigenetic age estimators associated with changes in 3MS or TICS-m. Higher values of DNAm-based surrogates of growth differentiation factor 15, beta-2 microglobulin, Cystatin C, tissue inhibitor metalloproteinase 1, and adrenomedullin associated with faster annual declines in 3MS and TICS-m. Higher DNAm log A1c associated with faster annual declines in TICS-m only. DunedinPACE associated with faster annual declines in 3MS among APOE ε4 carriers but not among noncarriers (p-interaction = 0.020).

DISCUSSION

Higher DunedinPACE associated with faster declines in TICS-m and 3MS scores among APOE ε4 carriers. DunedinPACE may help identify older women at risk of future cognitive decline. Limitations include the ancillary studies that collected epigenetic data not designed to study epigenetics and cognitive function. We examined epigenetic age estimators with global cognitive function and not specific cognitive domains. Findings may not generalize to men and more diverse populations.

The Gut and Skin Microbiome and Its Association with Aging Clocks

Aging clocks are predictive models of biological age derived from age-related changes, such as epigenetic changes, blood biomarkers, and, more recently, the microbiome. Gut and skin microbiota regulate more than barrier and immune function. Recent studies have shown that human microbiomes may predict aging. In this narrative review, we aim to discuss how the gut and skin microbiomes influence aging clocks as well as clarify the distinction between chronological and biological age. A literature search was performed on PubMed/MEDLINE databases with the following keywords: "skin microbiome" OR "gut microbiome" AND "aging clock" OR "epigenetic". Gut and skin microbiomes may be utilized to create aging clocks based on taxonomy, biodiversity, and functionality. The top contributing microbiota or metabolic pathways in these aging clocks may influence aging clock predictions and biological age. Furthermore, gut and skin microbiota may directly and indirectly influence aging clocks through the regulation of clock genes and the production of metabolites that serve as substrates or enzymatic regulators. Microbiome-based aging clock models may have therapeutic potential. However, more research is needed to advance our understanding of the role of microbiota in aging clocks.

Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology

Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.

Individual longitudinal changes in DNA-methylome identify signatures of early-life adversity and correlate with later outcome

Adverse early-life experiences (ELA) affect a majority of the world's children. Whereas the enduring impact of ELA on cognitive and emotional health is established, there are no tools to predict vulnerability to ELA consequences in an individual child. Epigenetic markers including peripheral-cell DNA-methylation profiles may encode ELA and provide predictive outcome markers, yet the interindividual variance of the human genome and rapid changes in DNA methylation in childhood pose significant challenges. Hoping to mitigate these challenges we examined the relation of several ELA dimensions to DNA methylation changes and outcome using a within-subject longitudinal design and a high methylation-change threshold. DNA methylation was analyzed in buccal swab/saliva samples collected twice (neonatally and at 12 months) in 110 infants. We identified CpGs differentially methylated across time for each child and determined whether they associated with ELA indicators and executive function at age 5. We assessed sex differences and derived a sex-dependent 'impact score' based on sites that most contributed to methylation changes. Changes in methylation between two samples of an individual child reflected age-related trends and correlated with executive function years later. Among tested ELA dimensions and life factors including income to needs ratios, maternal sensitivity, body mass index and infant sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, high early-life unpredictability interacted with methylation changes to presage executive function. Thus, longitudinal, within-subject changes in methylation profiles may provide a signature of ELA and a potential predictive marker of individual outcome.

Bidirectional relationship between epigenetic age and brain health events

Chronological age offers an imperfect estimate of the molecular changes that occur with aging. Epigenetic age, which is derived from DNA methylation data, provides a more nuanced representation of aging-related biological processes. This study examines the bidirectional relationship between epigenetic age and the occurrence of brain health events (stroke, dementia, and late-life depression). Using data from the Health and Retirement Study, we analyzed blood samples from over 4,000 participants to determine how epigenetic age relates to past and future brain health events. Study participants with a prior brain health event prior to blood collection were 4% epigenetically older (beta 0.04, SE 0.01), suggesting that these conditions are associated with faster aging than that captured by chronological age. Furthermore, a one standard deviation increase in epigenetic age was associated with 70% higher odds of experiencing a brain health event in the next four years after blood collection (OR 1.70, 95%CI 1.16-2.50), indicating that epigenetic age is not just a consequence but also a predictor of poor brain health. Both results were replicated through Mendelian Randomization analyses, supporting their causal nature. Our findings support the utilization of epigenetic age as a useful biomarker to evaluate the role of interventions aimed at preventing and promoting recovery after a brain health event.

Survival Rate and Chronic Diseases of TCGA Cancer and KoGES Normal Samples by Clustering for DNA Methylation

Insights from public DNA methylation data derived from cancer or normal tissues from cancer patients or healthy people can be obtained by machine learning. The goal is to determine methylation patterns that could be useful for predicting the prognosis for cancer patients and correcting lifestyles for healthy people. DNA methylation data were obtained from the DNA of 446 healthy participants from the Korean Genome Epidemiology Study (KoGES) and from the DNA of normal tissues or from cancer tissues of 11 types of carcinomas from The Cancer Genome Atlas (TCGA) database. To correct for the batch effect, R's ComBat function was used. Using the K-mean clustering (k = 3), the survival rates of the cancer patients and the incidence of chronic diseases were compared between the three clusters for TCGA and KoGES, respectively. Based on the public DNA methylation and clinical data of healthy participants and cancer patients, I present an analysis pipeline that integrates and clusters the methylation data from the two groups. As a result of clustering, CpG sites from gene or genomic regions, such as AFAP1, NINJ2, and HOOK2 genes, that correlated with survival rate and chronic disease are presented.