DNA methylation-based age clocks: From age prediction to age reversion

Causal relationship between molecular markers of biological aging and orthopedic diseases: A two-sample bidirectional Mendelian randomization study

BACKGROUND

Studies indicate an association between biological aging and orthopedic diseases, but the causality remains unclear.

AIMS

This study aims to investigate the bidirectional causal relationship between molecular markers of biological aging age and orthopedic conditions.

METHODS

A two-sample Mendelian randomization (MR) analysis based on a genome-wide association study (GWAS) was conducted to explore these causal relationships. Analysis methods included inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode. Sensitivity analyses involved Cochran's Q, MR-Egger, leave-one-out, and MR pleiotropy residual sum and outlier (MR-PRESSO) tests.

RESULTS

The forward MR analysis identified several causal relationships: granulocyte proportions influenced intervertebral disc degeneration (IVDD) (OR 0.2316, P = 0.0101) and low back pain (LBP) (OR 0.2624, P = 0.007); telomere length (TL) affected cervical spondylosis (C/S) (OR 0.8759, P = 0.0167) and IVDD (OR 0.9184, P = 0.023); fibroblast growth factor-23 (FGF-23) impacted frozen shoulder (FS) (OR 1.2424, P = 0.0316); and HannumAge influenced C/S (OR 0.9518, P = 0.0233). The reverse MR analysis found that FS influenced TL (OR 0.9582, P = 0.0002) and α-Klotho (OR 0.7592, P = 0.0256), while sciatica affected TL (OR 0.9344, P = 0.0055) and C/S impacted PhenoAge (OR 1.6583, P = 0.0131) after outlier exclusion. Cochran's Q indicated heterogeneity in certain analyses, and MR-Egger showed no horizontal pleiotropy in significant causal associations.

CONCLUSIONS

This study suggests a potential causal associations between molecular markers of biological aging and orthopedic diseases, suggesting avenues for future research into the underlying mechanisms.

DNA methylation and hydroxymethylation dynamics in the aging brain and its impact on ischemic stroke

DNA methylation and hydroxymethylation patterns at the 5th carbon of cytosine (5mC and 5hmC) in CpG dinucleotides tightly regulate gene transcription in normal physiology, aging, and associated diseases, including ischemic stroke. Resilience to ischemic brain injury depends on the interplay of diverse neural and non-neural cell types, whose gene expression and identity are predominantly regulated by brain-enriched epigenetic mechanisms, particularly the dynamics of 5mC and 5hmC in response to changing transcriptional demands under ischemic stress. In this review, we discussed the role of 5mC and 5hmC in aging and the pathophysiology of stroke. Given the high degree of inter-individual variability in stroke studies and its multifactorial etiology, we emphasize the need for personalized, temporally controlled, epigenome-based therapies to improve stroke outcomes.

Association between epigenetic clock acceleration and malnutrition among adults in the United States: A cross-sectional study

BACKGROUND

We investigated relationships between nutrition assessment tools (Controlling Nutritional Status [CONUT], Geriatric Nutritional Risk Index [GNRI], and Naples Prognostic Score [NPS]) and epigenetic clocks, evaluating malnutrition's impact on biological aging.

METHODS

Using National Health and Nutrition Examination Survey database (1999-2002), 2532 participants aged ≥50 years were assessed with three nutrition tools and analyzed against 12 epigenetic clocks using multiple linear regression models adjusted for confounding factors.

RESULTS

Malnutrition prevalence rates were 13.5% (CONUT), 4.2% (GNRI), and 46.8% (NPS). Compared with no-risk groups, moderate-to-severe malnutrition showed significant epigenetic age acceleration, particularly in NPS assessment. GrimAge2Mort demonstrated up to 4.19 years acceleration (in NPS model 3, P < 0.01), DunedinPoAm showed significant increase (in NPS model 3, β = 0.083, P < 0.01), and YangCell significantly decreased (in NPS model 3, β = -0.019, P < 0.01). These associations remained significant after adjusting for confounding factors. A clear dose-response relationship existed between malnutrition and epigenetic age acceleration.

CONCLUSION

This study provides first systematic evidence of significant associations between malnutrition and epigenetic age acceleration, particularly in moderate-to-severe malnutrition, leading to substantial biological aging acceleration. GrimAge2Mort, DunedinPoAm, and YangCell emerged as stable indicators for assessing nutrition-related biological aging. These findings provide new insights into malnutrition's impact on aging and offer important references for clinical nutrition intervention strategies.

The application of epigenetic clocks in degenerative musculoskeletal diseases: A systematic review

OBJECTIVE

Epigenetic clocks have emerged as powerful tools for quantifying biological aging. Degenerative musculoskeletal disorders (e.g., osteoarthritis [OA], osteoporosis) represent a group of age-related conditions characterized by progressive tissue deterioration. While their epidemiological association with aging is well-established, the precise relationship with epigenetic aging markers remains to be systematically elucidated. This review synthesizes current evidence on the application of epigenetic clocks as biomarkers and their clinical potential in managing these conditions.

METHODS

We systematically searched four major biomedical databases (PubMed, PMC, Web of Science, ScienceDirect) from inception through December 2024 for observational studies examining the association between the epigenetic clock and degenerative musculoskeletal diseases using controlled vocabulary (e.g., DNA methylation age) combined with disease-specific terms. The protocol was registered with PROSPERO (CRD42024623554).

RESULTS

After screening, 14 studies (case-control, cross-sectional, cohort) were included. We identified eight epigenetic clocks (based on cartilage, bone, and blood biomarkers) for assessing degenerative musculoskeletal diseases. DunedinPACE showed significant associations with chronic low back pain severity (r = 0.39-0.45) and functional impairment, while Horvath's clock revealed tissue-specific epigenetic aging in OA cartilage (ΔAge = 3.7 years). GrimAge exhibited the strongest correlations with chronic pain (ρ = 0.47) and mediated socioeconomic influences (β = 0.81).

CONCLUSIONS

This systematic review of 14 clinical studies establishes epigenetic clocks as promising biomarkers for degenerative musculoskeletal diseases. The differential associations observed across epigenetic metrics highlight the need for disease-specific algorithm development. Future research should prioritize longitudinal validation and mechanistic investigations into socioeconomic influences on epigenetic aging.

Identification of Occupations in Different Populations Based on Skin Microbial Characteristics

The composition and diversity of the skin microbiome are affected by several factors, including the working environment, which plays an active role in shaping microbial communities in human skin. Previous studies have shown that residual microbial communities on personal items can be used to identify their owners. However, few studies have used the skin microbiome to identify occupations in different populations or evaluate whether the skin microbiome can be used as a tool for forensic investigations. Here, we collected palm and cuff swabs from three occupational groups-cooks, medical staff, and students-and performed next-generation sequencing targeting the 16S rRNA gene to characterise the microbial communities associated with each profession. We found that different occupational environments resulted in different skin microbial community compositions. Actinobacteria and Firmicutes were the dominant phyla in the student samples. Compared with the other two occupations, cooks had the highest relative abundances of Bacteroides and Cyanobacteria. Additionally, cuff samples from medical staff had the highest relative abundances of Proteobacteria. Principal co-ordinate analysis results indicated that the samples were roughly divided into three clusters according to their occupation. Furthermore, linear discriminant analysis effect size results showed that cooks, medical staff, and students had their own unique biomarkers, cooks exhibited seven shared biomarkers between palm and cuff samples, medical staff showed 2, while students demonstrated the highest congruence which was 13 shared biomarkers. This suggested that some palm skin microbial communities could be transferred to the cuffs through contact friction. Thus, there were also microbial communities present in cuff samples that could be used to identify the owner's occupations, suggesting that skin microorganisms left on personal items via daily contact could also be used to provide information about an individual's occupation. Finally, we constructed a random forest model based on the composition and relative abundance of the microbiota to infer the subject's occupation, achieving an accuracy of 76.92% for the palm testing dataset and 73.33% for the cuff testing dataset; all of the cuff sample datasets showed an accuracy of 70.97%. These findings suggested that an individual's occupation can be inferred not only from the skin microbiota but also from the microbiota left on the cuffs of the individual's clothes. Further studies are needed; however, these results demonstrate the potential of the skin microbiota as a forensic tool for predicting population occupations.

DNA methylation age acceleration is associated with incident cognitive impairment in the health and retirement study

BackgroundDNA methylation clocks have emerged as promising biomarkers for cognitive impairment and dementia. Longitudinal studies exploring the association between DNA methylation clocks and cognitive decline have been constrained by limited sample sizes and a lack of diversity.ObjectiveOur study aimed to investigate associations between DNA methylation clocks and incident cognitive impairment using a larger and US nationally-representative sample from the Health and Retirement Study.MethodsWe measured DNA methylation age acceleration in 2016 by regressing the DNA methylation clocks, including GrimAge, against chronological age. Cognitive change over time was determined by Langa-Weir cognition status from 2016 to 2018. Multivariable logistic regression evaluated the association between DNA methylation age acceleration and cognitive change, adjusting for cell-type proportions, demographic, and health factors. We also applied inverse probability weighting to address potential selection bias from varying loss-to-follow-up rates.ResultsThe analytic sample (N = 2713) was 54% female, 8.4% Black/African American, 86% White, 7.5% Hispanic, and 68 years old at baseline. During the two years of follow-up, 12% experienced cognitive change and had higher baseline GrimAge (mean = 1.2 years) acceleration compared to those maintaining normal cognition (mean = -0.8 years). A one-year increase in GrimAge acceleration was associated with 1.05 times higher adjusted and survey-weighted odds of cognitive change during follow-up (95% CI: 1.01-1.10). This association was consistent after accounting for loss-to-follow-up (OR = 1.07, 95% CI: 1.04-1.11).ConclusionsOur study offers insights into DNA methylation age acceleration associated with cognitive change over time, suggesting avenues for improved prevention, diagnosis, and treatment.

Developmental epigenomic effects of maternal financial problems

Early-life adversity as neglect or low socioeconomic status is associated with negative physical/mental health outcomes and plays an important role in health trajectories through life. The early-life environment has been shown to be encoded as changes in epigenetic markers that are retained for many years.We investigated the effect of maternal major financial problems (MFP) and material deprivation (MD) on their children's epigenome in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Epigenetic aging, measured with epigenetic clocks, was weakly accelerated with increased MFP. In subsequent EWAS, MFP, and MD showed strong, independent programing effects on children's genomes. MFP in the period from birth to age seven was associated with genome-wide epigenetic modifications on children's genome visible at age 7 and partially remaining at age 15.These results support the hypothesis that physiological processes at least partially explain associations between early-life adversity and health problems later in life. Both maternal stressors (MFP/MD) had similar effects on biological pathways, providing preliminary evidence for the mechanisms underlying the effects of low socioeconomic status in early life and disease outcomes later in life. Understanding these associations is essential to explain disease susceptibility, overall life trajectories and the transition from health to disease.

Preliminary findings of DNA hypermethylation of MDGA1 in idiopathic restless legs syndrome

BACKGROUND

Both genetic and environmental factors contribute to the development of restless legs syndrome (RLS). Epigenetic mechanisms might play a vital role in RLS but remain underexplored. MDGA1, involved in synaptic inhibition, has been identified by genome-wide association studies as a potential risk gene for RLS. However, its role and underlying mechanisms in RLS are largely unknown.

OBJECTIVE

To investigate the relationship between DNA methylation levels in the promotor region of MDGA1 and RLS susceptibility and phenotypes.

METHODS

Two independent RLS cohorts (including three large RLS families) and healthy controls (HCs) were recruited. Clinical characteristics were recorded, and DNA methylation levels of CpG islands in the MDGA1 gene from peripheral blood mononuclear cells were measured. Associations between MDGA1 methylation (MDGA1m) and RLS phenotypes (age, sex, and family history) were also analyzed.

RESULTS

A total of 62 idiopathic RLS (iRLS) patients (29 from Cohort 1 and 33 from Cohort 2) and 45 healthy controls (24 from Cohort 1 and 21 from Cohort 2) were included. MDGA1 methylation levels were significantly higher in iRLS patients compared to HCs. Among RLS families, both RLS patients and non-RLS family members showed hypermethylation compared to HCs. Moreover, a positive family history of RLS was associated with an increased risk of MDGA1 hypermethylation.

CONCLUSION

Our study identified hypermethylation of the MDGA1 gene in the peripheral blood of RLS cases, which may be linked to family history.

Integrative DNA methylome and transcriptome analysis identify potential genes on the influence of dilated cardiomyopathy-associated heart failure

OBJECTIVE

Dilated cardiomyopathy (DCM)-associated heart failure (HF) presents a significant clinical challenge, underlying epigenetic mechanisms remaining poorly understood. This study aims to investigate the interplay between DNA methylation and gene expression in the hearts of patients with DCM-associated HF (DCM-HF).

METHODS

Atrial tissues were collected from five healthy donors and five heart transplant recipients suffering from heart failure due to DCM. We conducted RNA-sequencing (RNA-seq) to analyze mRNA expression profiles and performed whole-genome bisulfite sequencing (WGBS) to evaluate DNA methylation levels. Correlation analyses between RNA-seq and WGBS data were executed by integrating differentially expressed genes (DEGs) with genes associated with differentially methylated regions (DMRs) located in the promoter regions.

RESULTS

The RNA-seq analysis identified a total of 681 DEGs, comprising 406 significantly downregulated genes and 275 upregulated genes in DCM-HF tissues, which were enriched in pathways related to cardiomyopathy. WGBS revealed 16,158 hypomethylated and 6,857 hypermethylated differentially methylated regions (DMRs), with 3,185 of these located in promoter regions. The integration of promoter-hypomethylated and hypermethylated DMRs-related genes (DMGs) with DEGs resulted in the identification of 46 hub genes associated with cardiac development and function. Protein-protein interaction and disease association analyses highlighted five key genes-NPPA, NPPB, ACTN2, NEBL, and MYO18B-that exhibited promoter hypomethylation and increased expression, potentially linked to the activity of transcription factors such as HIF1A and KLF4.

CONCLUSIONS

These findings suggest that the epigenetic dysregulation of cardiac stress-response and structural genes contributes to the pathogenesis of DCM-HF. Furthermore, the detection of promoter methylation levels in these loci may offer new opportunities for developing diagnostic tools and therapeutic strategies for DCM-HF management.

Dyslipidemia and aging: the non-linear association between atherogenic index of plasma (AIP) and aging acceleration

BACKGROUND

Dyslipidemia has been proved to play a pivotal role in biological aging. Atherogenic Index of Plasma (AIP), derived from serum triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C), is an effective biomarker of dyslipidemia. However, whether AIP can be used as an indicator of biological aging remains unclear. This study aims to investigate the relationship between AIP and biological aging in the US adult population.

METHODS

4,471 American adults with age over 20 years from the National Health and Nutrition Examination Survey (NHANES) database were included in this study. Biological aging was assessed by phenotypic age acceleration (PhenoAgeAccel). Multivariable linear regression models, subgroup analyses and interaction tests were employed to explore the association between AIP and PhenoAgeAccel. Furthermore, adjusted restricted cubic spline (RCS) analyses were employed to assess potential nonlinear relationships, while mediation analysis was utilized to identify the mediating effects of homeostatic model assessment of insulin resistance (HOMA-IR). Besides, network pharmacology was performed to determine the potential mechanisms underlying dyslipidemia-related aging acceleration.

RESULTS

A total of 4,471 participants were included in this study, the median chronological age, PhenoAge and PhenoAgeAccel for the overall population were 49 (35-64) years, 42.85 (27.30-59.68) years, and - 6.92 (- 10.52 to -2.46) years, respectively. In the fully adjusted model, one unit increase of AIP was correlated with 1.820-year increase in PhenoAgeAccel (β = 1.820, 95% CI: 1.085-2.556), which was more pronounced among individuals being female, diabetic and hypertensive. Furthermore, RCS analysis revealed a nonlinear relationship between AIP and PhenoAgeAccel, with an inflection point identified at -0.043 for AIP via threshold and saturation effect analysis. AIP demonstrated a positive correlation with PhenoAgeAccel both before (β = 6.550, 95% CI: 5.070-8.030) and after (β = 3.898, 95% CI: 2.474-5.322) this inflection point. Additionally, HOMA-IR was found to mediate 39.21% of the association between AIP and PhenoAgeAccel. Finally, network pharmacology analysis identified INS, APOE, APOB, IL6, IL10, PPARG, MTOR, ACE, PPARGC1A, and SERPINE1 as core targets in biological aging, which were functionally linked to key signaling pathways like AMPK, apelin, JAK-STAT, FoxO, etc. CONCLUSIONS: An elevated AIP was notably and positively correlated with accelerated aging, suggesting that AIP may serve as an effective predictor to evaluate accelerated aging.

Unveiling the potential impact of RNA m5C methyltransferases NSUN2 and NSUN6 on cellular aging

NSUN2 and NSUN6, two family members of NOL1/NSUN protein, are mainly responsible for catalyzing the formation of 5-methylcytosine (m5C) in RNA and highly involved in the physiological and pathological processes of many diseases. To investigate the biological functions of NSUN2 and NSUN6, NSUN2-/- and NSUN6-/- HEK293T cell lines were separately constructed by CRISPR/Cas9. We found no significant interaction between the protein expression of NSUN2 and NSUN6. Notably, the ablation of NSUN2 or NSUN6 reduced cell proliferation and increased expression of the senescence-associated marker P27, whereas more β-galactosidase-positive cells were observed in response to H2O2-induced oxidative stress. Moreover, the expression of NSUN2 and NSUN6 was significantly reduced in the HGPS premature aging cell lines by the LMNAG609G mutation. Taken together, we demonstrated that NSUN2 and NSUN6 may be inextricably linked to cellular aging and thus provide potential novel strategies for the clinical therapeutics of aging and age-associated disease in the future.

A Sex-Specific Minimal CpG-Based Model for Biological Aging Using ELOVL2 Methylation Analysis

Significant deviations between chronological and biological age can signal the early risk of chronic diseases, driving the need for tools that accurately determine biological age. While DNA methylation-based clocks have demonstrated strong predictive power for biological aging determination, their clinical application is limited by several barriers including high costs, the need to analyze hundreds of methylation sites using sophisticated platforms and the lack of standardized measurement tools and protocols. In this study, we developed a multivariate linear model using the analysis of eight CpGs within the promoter region of the very long chain fatty acid elongase 2 gene (ELOVL2). The model generated predicts biological age with a mean absolute error (MAE) of 5.04, providing a simplified, cost-effective alternative to more complex methylation-based clocks. Additionally, we identified sex-specific biological clocks, achieving MAEs of 4.37 for males and 5.38 for females, highlighting sex-related molecular differences in the methylation of this gene during aging. Our minimal CpG-based clock offers a practical solution for estimating biological age, with potential applications in clinical practice for assessing age-related disease risks and providing personalized healthcare interventions.

The Role of Ginseng and Its Bioactive Compounds in Aging: Cells and Animal Studies

Aging is an inevitable process that is characterized by physiological deterioration and increased vulnerability to stressors. Therefore, the interest in hallmarks, mechanisms, and ways to delay or prevent aging has grown for decades. Natural plant products and their bioactive compounds have been studied as a promising strategy to overcome aging. Ginseng, a traditional herbal medicine, and its bioactive compound, the ginsenosides, have increasingly gained attention because of various pharmacological functions. This review introduces the species, useful parts, characteristics, and active components of ginseng. It primarily focuses on the bioconversion of ginsenosides through the unique steaming and drying process. More importantly, this review enumerates the antiaging mechanisms of ginseng, ginsenosides, and other bioactive compounds, highlighting their potential to extend the health span and mitigate age-related diseases based on twelve representative hallmarks of aging.

Impact of DNA-Methylation Age Acceleration on Long-Term Mortality Among US Adults With Cardiovascular-Kidney-Metabolic Syndrome

BACKGROUND

The association between DNA methylation age acceleration (DNAmAA) and cardiovascular-kidney-metabolic (CKM) syndrome stages and long-term mortality in the population with CKM syndrome remains unclear.

METHODS AND RESULTS

This cohort study included 1889 participants from the National Health and Nutrition Examination Survey (1999-2002) with CKM stages and DNA methylation age data. DNAmAA was calculated as residuals from the regression of DNA methylation age on chronological age. The primary outcome was all-cause mortality, with cardiovascular and noncardiovascular mortality as secondary outcomes. Proportional odds models assessed the associations between DNAmAAs and CKM stages, and Cox proportional hazards regression models estimated the associations between DNAmAAs and mortality. Significant associations were found between DNAmAAs and advanced CKM stages, particularly for GrimAge2Mort acceleration (GrimAA) (odds ratio [OR], 1.547 [95% CI, 1.316-1.819]). Over an average follow-up of 14 years, 1015 deaths occurred. Each 5-unit increase in GrimAA was associated with a 50% increase in all-cause mortality (95% CI, 1.39-1.63), a 77% increase in cardiovascular mortality (95% CI, 1.46-2.15), and a 42% increase in noncardiovascular mortality (95% CI, 1.27-1.59). With the lowest GrimAA tertile as a reference, the highest GrimAA tertile showed hazard ratios of 1.95 (95% CI, 1.56-2.45) for all-cause mortality, 3.06 (95% CI, 2.13-4.40) for cardiovascular mortality, and 1.65 (95% CI, 1.20-2.29) for noncardiovascular mortality. Mediation analysis indicated that GrimAA mediates the association between various exposures (including physical activity, Healthy Eating Index-2015 score, hemoglobin A1c, etc.) and mortality.

CONCLUSIONS

GrimAA may serve as a valuable biomarker for assessing CKM stages and mortality risk in individuals with CKM syndrome, thereby informing personalized management strategies.

Whole-genome bisulfite sequencing of cell-free DNA unveils age-dependent and ALS-associated methylation alterations

BACKGROUND

Cell-free DNA (cfDNA) in plasma carries epigenetic signatures specific to tissue or cell of origin. Aberrant methylation patterns in circulating cfDNA have emerged as valuable tools for noninvasive cancer detection, prenatal diagnostics, and organ transplant assessment. Such epigenetic changes also hold significant promise for the diagnosis of neurodegenerative diseases, which often progresses slowly and has a lengthy asymptomatic period. However, genome-wide cfDNA methylation changes in neurodegenerative diseases remain poorly understood.

RESULTS

We used whole-genome bisulfite sequencing (WGBS) to profile age-dependent and ALS-associated methylation signatures in cfDNA from 30 individuals, including young and middle-aged controls, as well as ALS patients with matched controls. We identified 5,223 age-related differentially methylated loci (DMLs) (FDR < 0.05), with 51.6% showing hypomethylation in older individuals. Our results significantly overlapped with age-associated CpGs identified in a large blood-based epigenome-wide association study (EWAS). Comparing ALS patients to controls, we detected 1,045 differentially methylated regions (DMRs) in gene bodies, promoters, and intergenic regions. Notably, these DMRs were linked to key ALS-associated pathways, including endocytosis and cell adhesion. Integration with spinal cord transcriptomics revealed that 31% of DMR-associated genes exhibited differential expression in ALS patients compared to controls, with over 20 genes significantly correlating with disease duration. Furthermore, comparison with published single-nucleus RNA sequencing (snRNA-Seq) data of ALS demonstrated that cfDNA methylation changes reflects cell-type-specific gene dysregulation in the brain of ALS patients, particularly in excitatory neurons and astrocytes. Deconvolution of cfDNA methylation profiles suggested altered proportions of immune and liver-derived cfDNA in ALS patients.

CONCLUSIONS

cfDNA methylation is a powerful tool for assessing age-related changes and ALS-specific molecular dysregulation by revealing perturbed locus, genes, and the proportional contributions of different tissues/cells to the plasma. This technique holds promise for clinical application in biomarker discovery across a broad spectrum of neurodegenerative disorders.

Genetic and epigenetic bases of long-term adverse effects of childhood cancer therapy

Over the past decade, genome-scale molecular profiling of large childhood cancer survivorship cohorts has led to unprecedented advances in our understanding of the genetic and epigenetic bases of therapy-related adverse health outcomes in this vulnerable population. To facilitate the integration of knowledge generated from these studies into formulating next-generation precision care for survivors of childhood cancer, we summarize key findings of genetic and epigenetic association studies of long-term therapy-related adverse effects including subsequent neoplasms and cardiomyopathies among others. We also discuss therapy-related genotoxicities including clonal haematopoiesis and DNA methylation, which may underlie accelerated molecular ageing. Finally, we highlight enhanced risk prediction models for survivors of childhood cancer that incorporate both genetic factors and treatment exposures, aiming to achieve enhanced accuracy in predicting risks for this population. These new insights will hopefully inspire future studies that harness both expanding omics resources and evolving data science methodology to accelerate the translation of precision medicine for survivors of childhood cancer.

The association of visceral and subcutaneous fat areas with phenotypic age in non-elderly adults, mediated by HOMA-IR and HDL-C

BACKGROUND

Ageing results in diminished adaptability, as well as declines in physiological and psychological functions and resilience. The epigenetic clock 'Phenotypic Age' (PhenoAge) represents 'preclinical ageing'. Phenotypic Age Acceleration (PhenoAgeAccel) is defined as the residual from a linear regression model predicting PhenoAge on the basis of chronological age. Abdominal subcutaneous adipose tissue, visceral adipose tissue, the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), and high-density lipoprotein cholesterol (HDL-C) have all been shown to correlate with ageing; however, the connections between these factors and PhenoAge are still insufficiently investigated.

METHODS

Data for this study were sourced from the National Health and Nutrition Examination Survey (2015-2018), comprising 2580 participants. Complex survey designs were considered. To examine the association between body fat area and PhenoAgeAccel, logistic regression was applied. Additionally, subgroup analysis was used to identify variations in population characteristics. The dose‒response relationship between body fat area and PhenoAgeAccel was determined via restricted cubic spline analysis. Mediation and interaction analyses were further employed to investigate the roles of the HOMA-IR and HDL-C in this association.

RESULTS

In nonelderly adults, the relationships between body fat area and PhenoAgeAccel differed chronological age. For abdominal subcutaneous fat area (SFA), this relationship was nonlinear in individuals aged 18-44 years and 45-59 years, with thresholds of 2.969 m² and 3.394 m², respectively. In contrast, a nonlinear relationship of visceral fat area (VFA) with PhenoAgeAccel was observed in individuals aged 18-44 years, while this relationship was linear in individuals aged 45-59 years, with thresholds of 0.769 m² and 1.220 m², respectively. Mediation effect analysis revealed that the HOMA-IR had a more pronounced mediation effect in individuals aged 18-44 years, accounting for 13.4% of the relationship between VFA and PhenoAgeAccel and 6.9% of the relationship between SFA and PhenoAgeAccel. Conversely, HDL-C had a greater mediating effect in individuals aged 45-59 years, accounting for 21.7% of the relationship between VFA and PhenoAgeAccel and 11.6% of the relationship between abdominal SFA and PhenoAgeAccel. HOMA-IR ≥ 2.73 or VFA > 0.925 m², as well as HOMA-IR ≥ 2.73 or abdominal SFA > 3.137 m², accelerated PhenoAge, whereas 1.60 < HDL-C ≤ 3.90 mmol/L combined with abdominal SFA ≤ 3.137 m² or VFA ≤ 0.925 m² decelerated PhenoAge.

CONCLUSION

In this study, the nonlinear relationships among abdominal SFA, VFA, and PhenoAgeAccel were elucidated, while characteristic thresholds across different age groups were identified. The results of this study emphasize the complex influence of fat distribution on the ageing process and refine the roles of HOMA-IR and HDL-C in various age cohorts. These findings provide a biological basis for future screening for accelerated ageing and appropriate intervention in high-risk populations and offer valuable insights for guiding personalized clinical interventions and health management strategies.

"Aging Clocks" Based on Cell-Free DNA

Aging is associated with systemic changes in the physiological and molecular parameters of the body. These changes are referred to as biomarkers of aging. Statistical models that link changes in individual biomarkers to biological age are called aging clocks. These tools facilitate a comprehensive evaluation of bodily health and permit the quantitative determination of the rate of aging. A particularly promising area for the development of aging clocks is the analysis of cell-free DNA (cfDNA), which is present in the blood and contains numerous potential biomarkers. This review explores in detail the fragmentomics, topology, and epigenetic landscape of cfDNA as possible biomarkers of aging. The review further underscores the potential of leveraging single-molecule sequencing of cfDNA in conjunction with long-read technologies to simultaneously profile multiple biomarkers, a strategy that could lead to the development of more precise aging clocks.

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.

Neighborhood Stressors and Epigenetic Age Acceleration Among Older Americans

OBJECTIVES

Exposure to stressful neighborhood environments is a well-established risk factor for health deterioration and premature death. However, the biological underpinnings are not fully understood. Epigenetic aging may function as a key molecular pathway to adverse health outcomes among residents of high-stress neighborhoods. This study examines the associations between neighborhood social stressors (socioeconomic deprivation, observed and perceived disorder, and low social cohesion) and epigenetic age (DunedinPACE and Principal component adjusted [PC] PCHorvath, PCHannum, PCPhenoAge, PCGrimAge). Further, we identify subpopulations most vulnerable to neighborhood stressors.

METHODS

Respondent data are from the 2016 Health and Retirement Study (HRS) DNA methylation subsample. Neighborhood data come from respondent reports (2014/2016) and the census (2012-2016 ACS). The analytic sample included 3,146 adults ages 56 and older (mean age = 68.8), of whom 54.9% were women and 19.3% were non-White.

RESULTS

In multilevel regression models adjusting for sociodemographic covariates, all neighborhood stressors were associated with faster DunedinPACE (B = 0.008 to 0.017). Neighborhood deprivation, perceived disorder, and low cohesion were associated with PCPhenoAge (B = 0.27 to 0.40) or PCGrimAge acceleration (B = 0.23). Health behaviors explained these associations to some degree. However, no significant associations were found with PCHorvath and PCHannum. In interaction analyses, adverse associations with deprivation, observed disorder, and low cohesion were more pronounced for women. No consistent interactions were found for race/ethnic and education groups.

DISCUSSION

Our findings indicate that neighborhood stressors can accelerate epigenetic aging, with older women particularly vulnerable to their effects. These findings provide insights into the biological foundations of health disparities rooted in neighborhood environments.

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

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

Pharmacogenomics and pediatric drug development: science and political power. A narrative review

INTRODUCTION

Pharmacogenomics (PGx) investigates how genomes control enzyme expression. Developmental pharmacology (DP) describes the temporal sequence of enzymes impacting absorption, distribution, metabolism, and excretion (ADME) of food and drugs.

AREAS COVERED

US and European Union (EU) legislation facilitate and/or enforce pediatric studies for all new drugs, called overall 'pediatric drug development' (PDD). DP and PDD look at patients' chronological age, but oscillate between legal and physiological meanings of the term 'child.' Children's bodies become mature with puberty.

EXPERT OPINION

Decades after first DP observations in babies, PGx offers a better understanding of the variability of safety and efficacy of drugs, of the process of aging, and of shifting enzyme patterns across aging. We should rethink and revise outdated interpretations of ADME changes in minors. The Declaration of Helsinki forbids pointless studies that some pediatric researchers and regulatory agencies, more so the EMA than the FDA, demand pointless pediatric studies is regrettable. Medicine needs to differentiate between legal and physiological meanings of the term 'child' and should use objective measures of maturity.

Epigenetic age and long-term cancer risk following a stroke

BACKGROUND

The association between increased cancer risk following a cerebrovascular event (CVE) has been previously reported. We hypothesize that biological age (B-age) acceleration is involved in this association. Our study aims to examine B-age as a novel contributing factor to cancer development post-CVE.

METHODS

From our prospective stroke registry (BasicMar), we selected 940 cases with epigenetic data. For this study, we specifically analyzed 648 of these patients who had available data, no prior history of cancer, and a minimum follow-up of 3 months. The primary outcome was cancer incidence. B-age was estimated using DNA methylation data derived from whole blood samples obtained within 24 h of stroke onset, employing various epigenetic clocks (including Hannum, Horvath, PhenoAge, ZhangBLUP, ZhangEN, and the mitotic epiTOC). Extrinsic epigenetic age acceleration (EEAA) was calculated as the residuals from the regression of B-age against chronological age (C-age). For epiTOC, the age-adjusted values were obtained by regressing out the effect of age from the raw epiTOC measurements. Estimated white cell counts were derived from DNA methylation data, and these cell fractions were used to compute the intrinsic epigenetic age acceleration (IEAA). Subsequently, we evaluated the independent association between EEAA, IEAA, and cancer incidence while controlling for potential confounding variables.

RESULTS

Among 648 patients with a median follow-up of 8.15 years, 83 (12.8%) developed cancer. Cox multivariable analyses indicated significant associations between Hannum, Zhang, and epiTOC EEAA and the risk of cancer after CVE. After adjusting for multiple testing and competing risks, EEAA measured by Hannum clock maintained an independent association with cancer risk. Specifically, for each year increase in Hannum's EEAA, we observed a 6.0% increased incidence of cancer (HR 1.06 [1.02-1.10], p value = 0.002).

CONCLUSIONS

Our findings suggest that epigenetic accelerated aging, as indicated by Hannum's EEAA, may play a significant role in the increased cancer risk observed in CVE survivors.

The Quest for Eternal Youth: Hallmarks of Aging and Rejuvenating Therapeutic Strategies

The impressive achievements made in the last century in extending the lifespan have led to a significant growth rate of elderly individuals in populations across the world and an exponential increase in the incidence of age-related conditions such as cardiovascular diseases, diabetes mellitus type 2, and neurodegenerative diseases. To date, geroscientists have identified 12 hallmarks of aging (genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, impaired macroautophagy, mitochondrial dysfunction, impaired nutrient sensing, cellular senescence, stem cell exhaustion, defective intercellular communication, chronic inflammation, and gut dysbiosis), intricately linked among each other, which can be targeted with senolytic or senomorphic drugs, as well as with more aggressive approaches such as cell-based therapies. To date, side effects seriously limit the use of these drugs. However, since rejuvenation is a dream of mankind, future research is expected to improve the tolerability of the available drugs and highlight novel strategies. In the meantime, the medical community, healthcare providers, and society should decide when to start these treatments and how to tailor them individually.

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.

Epigenetic clocks and programmatic aging

The last decade has seen remarkable progress in the characterization of methylation clocks that can serve as indicators of biological age in humans and many other mammalian species. While the biological processes of aging that underlie these clocks have remained unclear, several clues have pointed to a link to developmental mechanisms. These include the presence in the vicinity of clock CpG sites of genes that specify development, including those of the Hox (homeobox) and polycomb classes. Here we discuss how recent advances in programmatic theories of aging provide a framework within which methylation clocks can be understood as part of a developmental process of aging. This includes how such clocks evolve, how developmental mechanisms cause aging, and how they give rise to late-life disease. The combination of ideas from evolutionary biology, biogerontology and developmental biology open a path to a new discipline, that of developmental gerontology (devo-gero). Drawing on the properties of methylation clocks, we offer several new hypotheses that exemplify devo-gero thinking. We suggest that polycomb controls a trade-off between earlier developmental fidelity and later developmental plasticity. We also propose the existence of an evolutionarily-conserved developmental sequence spanning ontogenesis, adult development and aging, that both constrains and determines the evolution of aging.

DNA methylation at AHRR as a master predictor of smoke exposure and a biomarker for sleep and exercise

BACKGROUND

DNA methylation profiling may provide a more accurate measure of the smoking status than self-report and may be useful in guiding clinical interventions and forensic investigations. In the current study, blood DNA methylation profiles of nearly 800 Polish individuals were assayed using Illuminia EPIC and the inference of smoking from epigenetic data was explored. In addition, we focused on the role of the AHRR gene as a top marker for smoking and investigated its responsiveness to other lifestyle behaviors.

RESULTS

We found > 450 significant CpGs associated with cigarette consumption, and overrepresented in various biological functions including cell communication, response to stress, blood vessel development, cell death, and atherosclerosis. The model consisting of cg05575921 in AHRR (p = 4.5 × 10-32) and three additional CpGs (cg09594361, cg21322436 in CNTNAP2 and cg09842685) was able to predict smoking status with a high accuracy of AUC = 0.8 in the test set. Importantly, a gradual increase in the probability of smoking was observed, starting from occasional smokers to regular heavy smokers. Furthermore, former smokers displayed the intermediate DNA methylation profiles compared to current and never smokers, and thus our results indicate the potential reversibility of DNA methylation after smoking cessation. The AHRR played a key role in a predictive analysis, explaining 21.5% of the variation in smoking. In addition, the AHRR methylation was analyzed for association with other modifiable lifestyle factors, and showed significance for sleep and physical activity. We also showed that the epigenetic score for smoking was significantly correlated with most of the epigenetic clocks tested, except for two first-generation clocks.

CONCLUSIONS

Our study suggests that a more rapid return to never-smoker methylation levels after smoking cessation may be achievable in people who change their lifestyle in terms of physical activity and sleep duration. As cigarette smoking has been implicated in the literature as a leading cause of epigenetic aging and AHRR appears to be modifiable by multiple exogenous factors, it emerges as a promising target for intervention and investment.

Microbiota-immune-brain interactions: A new vision in the understanding of periodontal health and disease

This review highlights the significance of interactions between the microbiota, immune system, nervous and hormonal systems, and the brain on periodontal health and disease. Microorganisms in the microbiota, immune cells, and neurons communicate via homeostatic nervous and hormonal systems, regulating vital body functions. By modulating pro-inflammatory and anti-inflammatory adaptive immune responses, these systems control the composition and number of microorganisms in the microbiota. The strength of these brain-controlled responses is genetically determined but is sensitive to early childhood stressors, which can permanently alter their responsiveness via epigenetic mechanisms, and to adult stressors, causing temporary changes. Clinical evidence and research with humans and animal models indicate that factors linked to severe periodontitis enhance the responsiveness of these homeostatic systems, leading to persistent hyperactivation. This weakens the immune defense against invasive symbiotic microorganisms (pathobionts) while strengthening the defense against non-invasive symbionts at the gingival margin. The result is an increased gingival tissue load of pathobionts, including Gram-negative bacteria, followed by an excessive innate immune response, which prevents infection but simultaneously destroys gingival and periodontal tissues. Thus, the balance between pro-inflammatory and anti-inflammatory adaptive immunity is crucial in controlling the microbiota, and the responsiveness of brain-controlled homeostatic systems determines periodontal health.

Sex as a biological variable in ageing: insights and perspectives on the molecular and cellular hallmarks

Sex-specific differences in lifespan and ageing are observed in various species. In humans, women generally live longer but are frailer and suffer from different age-related diseases compared to men. The hallmarks of ageing, such as genomic instability, telomere attrition or loss of proteostasis, exhibit sex-specific patterns. Sex chromosomes and sex hormones, as well as the epigenetic regulation of the inactive X chromosome, have been shown to affect lifespan and age-related diseases. Here we review the current knowledge on the biological basis of sex-biased ageing. While our review is focused on humans, we also discuss examples of model organisms such as the mouse, fruit fly or the killifish. Understanding these molecular differences is crucial as the elderly population is expected to double worldwide by 2050, making sex-specific approaches in the diagnosis, treatment, therapeutic development and prevention of age-related diseases a pressing need.

Relationship of dietary natural folate and synthetic folic acid co-exposure patterns with biological aging: findings from NHANES 2003-2018

Background: The mandatory folic acid fortification program in the United States has inevitably exposed most Americans to both natural folate and synthetic folic acid. We aim to examine the association of dietary folate co-exposure patterns with biological aging indicators. Methods: A total of 18 889 participants were enrolled from 2003 to 2018. Dietary intake of folate from diverse sources was evaluated by 24-hour dietary recall. Biological aging indicators were developed based on age-related clinical indicators, including the phenotypic age (PA), Klemera-Doubal method (KDM), homeostatic dysregulation (HD), and allostatic load (AL). The unsupervised K-means clustering method, logistic regression model, and restricted cubic spline (RCS) regression model were used to explore the relationship of natural folate and synthetic folic acid co-exposure with biological aging indicators. Results: The results indicated that higher intake of total folate, dietary folate, and food natural folate was associated with lower PA [OR = 0.75 (0.64, 0.88); OR = 0.79 (0.70, 0.90); OR = 0.65 (0.57, 0.75)], KDM [OR = 0.63 (0.53, 0.75); OR = 0.80 (0.65, 0.98); OR = 0.62 (0.49, 0.77)], HD [OR = 0.69 (0.56, 0.84); OR = 0.78 (0.67, 0.92); OR = 0.78 (0.68, 0.90)], and AL [OR = 0.69 (0.58, 0.82); OR = 0.73 (0.63, 0.85); OR = 0.74 (0.62, 0.90)], consistently. Four co-exposure patterns were generated based on the intake of folate from diverse sources, as follows: "low folate exposure group" to cluster 1, "dietary folate exposure group" to cluster 2, "mixed source high folate exposure group" to cluster 3, and "mixed source excessive folate exposure group" to cluster 4. Compared with cluster 1, participants in cluster 2 are associated with lower biological age indicators (ORPA = 0.82 [0.72, 0.93]; ORKDM = 0.58 [0.47, 0.70]; ORHD = 0.85 [0.75, 0.97]; ORAL = 0.87 [0.77, 0.98]), while participants in cluster 3 and cluster 4 are not. Conclusion: For individuals subjected to folic acid fortification programs, a higher intake of dietary folate, especially natural folate, coupled with a lower consumption of folic acid supplements, was found to be associated with lower biological age indicators.

Causal effects of cardiovascular health on five epigenetic clocks

BACKGROUND

This work delves into the relationship between cardiovascular health (CVH) and aging. Previous studies have shown an association of ideal CVH with a slower aging rate, measured by epigenetic age acceleration (EAA). However, the causal relationship between CVH and EAA has remained unexplored.

METHODS AND RESULTS

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

CONCLUSIONS

Our research confirms the causal link between maintaining an ideal CVH and epigenetic age. It provides a tangible pathway for individuals to improve their health and potentially slow aging.

DNA methylation age acceleration is associated with incident cognitive impairment in the Health and Retirement Study

Background

DNA methylation clocks have emerged as promising biomarkers for cognitive impairment and dementia. Longitudinal studies exploring the link between DNA methylation clocks and cognitive decline have been constrained by limited sample sizes and a lack of diversity.

Objective

Our study aimed to investigate the longitudinal associations between DNA methylation clocks and incident cognitive impairment using a larger sample size encompassing a US nationally representative sample from the Health and Retirement Study.

Methods

We measured DNA methylation age acceleration in 2016 by comparing the residuals of DNA methylation clocks, including GrimAge, against chronological age. Cognitive decline was determined by the change in Langa-Weir cognition status from 2016 to 2018. Using multivariable logistic regression, we evaluated the link between DNA methylation age acceleration and cognitive decline, adjusting for cell-type proportions, demographic, and health factors. We also conducted an inverse probability weighting analysis to address potential selection bias from varying loss-to-follow-up rates.

Results

The analytic sample (N=2,713) at baseline had an average of 68 years old, and during the two years of follow-up, 12% experienced cognitive decline. Participants who experienced cognitive decline during follow-up had higher baseline GrimAge (mean = 1.2 years) acceleration compared to those who maintained normal cognitive function (mean = -0.8 years, p < 0.001). A one-year increase in GrimAge acceleration was associated with 1.05 times higher adjusted and survey-weighted odds of cognitive decline during follow-up (95% CI: 1.01-1.10). This association was consistent after accounting for loss-to-follow-up (OR = 1.07, 95% CI: 1.04-1.11).

Conclusion

Our study offers insights into DNA methylation age acceleration associated with cognitive decline, suggesting avenues for improved prevention, diagnosis, and treatment.

Exploring the Relationships between Lifestyle Patterns and Epigenetic Biological Age Measures in Men

DNA methylation, validated as a surrogate for biological age, is a potential tool for predicting future morbidity and mortality outcomes. This study aims to explore how lifestyle patterns are associated with epigenetic changes in British men. Five biological age clocks were utilised to investigate the relationship between these epigenetic markers and lifestyle-related factors in a prospective study involving 221 participants. Spearman's correlation test, Pearson's correlation test, and univariate linear regression were employed for analysis. The results indicate that higher consumption of saturated fat and total daily calories, and a higher body mass index (BMI) are associated with accelerated biological aging. Conversely, higher vitamin D intake and a higher healthy lifestyle index (HLI) are linked to decelerated biological aging. These findings highlight the potential impact of specific lifestyle-related factors on biological aging and can serve as a reference for applying healthy lifestyle improvements in future disease prevention studies.

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

BACKGROUND

Childhood maltreatment (CM) is linked to long-term adverse health outcomes, including accelerated biological aging and cognitive decline. This study investigates the relationship between CM and various aging biomarkers: telomere length, facial aging, intrinsic epigenetic age acceleration (IEAA), GrimAge, HannumAge, PhenoAge, frailty index, and cognitive performance.

METHODS

We conducted a Mendelian randomization (MR) study using published GWAS summary statistics. Aging biomarkers included telomere length (qPCR), facial aging (subjective evaluation), and epigenetic age markers (HannumAge, IEAA, GrimAge, PhenoAge). The frailty index was calculated from clinical assessments, and cognitive performance was evaluated with standardized tests. Analyses included Inverse-Variance Weighted (IVW), MR Egger, and Weighted Median (WM) methods, adjusted for multiple comparisons.

RESULTS

CM was significantly associated with shorter telomere length (IVW: β = - 0.1, 95% CI - 0.18 to - 0.02, pFDR = 0.032) and increased HannumAge (IVW: β = 1.33, 95% CI 0.36 to 2.3, pFDR = 0.028), GrimAge (IVW: β = 1.19, 95% CI 0.19 to 2.2, pFDR = 0.040), and PhenoAge (IVW: β = 1.4, 95% CI 0.12 to 2.68, pFDR = 0.053). A significant association was also found with the frailty index (IVW: β = 0.31, 95% CI 0.13 to 0.49, pFDR = 0.006). No significant associations were found with facial aging, IEAA, or cognitive performance.

CONCLUSIONS

CM is linked to accelerated biological aging, shown by shorter telomere length and increased epigenetic aging markers. CM was also associated with increased frailty, highlighting the need for early interventions to mitigate long-term effects. Further research should explore mechanisms and prevention strategies.

Development of an epigenetic clock resistant to changes in immune cell composition

Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG methylation values to predict chronological or biological age. Increases in predicted epigenetic age relative to chronological age (epigenetic age acceleration) are connected to aging-associated pathologies, and changes in epigenetic age are linked to canonical aging hallmarks. However, epigenetic clocks rely on training data from bulk tissues whose cellular composition changes with age. Here, we found that human naive CD8+ T cells, which decrease in frequency during aging, exhibit an epigenetic age 15-20 years younger than effector memory CD8+ T cells from the same individual. Importantly, homogenous naive T cells isolated from individuals of different ages show a progressive increase in epigenetic age, indicating that current epigenetic clocks measure two independent variables, aging and immune cell composition. To isolate the age-associated cell intrinsic changes, we created an epigenetic clock, the IntrinClock, that did not change among 10 immune cell types tested. IntrinClock shows a robust predicted epigenetic age increase in a model of replicative senescence in vitro and age reversal during OSKM-mediated reprogramming.

CCDC12 gene methylation in peripheral blood as a potential biomarker for breast cancer detection

BACKGROUND

Aberrant DNA methylation has been identified as biomarkers for breast cancer detection. Coiled-coil domain containing 12 gene (CCDC12) implicated in tumorigenesis. This study aims to investigate the potential of blood-based CCDC12 methylation for breast cancer detection.

METHODS

DNA methylation level of CpG sites (Cytosine-phosphate Guanine dinucleotides) in CCDC12 gene was measured by mass spectrometry in 255 breast cancer patients, 155 patients with benign breast nodules and 302 healthy controls. The association between CCDC12 methylation and breast cancer risk was evaluated by logistic regression and receiver operating characteristic curve analysis.

RESULTS

A total of eleven CpG sites were analyzed. The CCDC12 methylation levels were higher in breast cancer patients. Compared to the lowest tertile of methylation level in CpG_6,7, CpG_10 and CpG_11, the highest quartile was associated with 82, 91 and 95% increased breast cancer risk, respectively. The CCDC12 methylation levels were associated with estrogen receptor (ER) and human epidermal growth factor 2 (HER2) status. In ER-negative and HER2-positive (ER-/HER2+) breast cancer subtype, the combination of four sites CpG_2, CpG_5, CpG_6,7 and CpG_11 methylation levels could distinguish ER-/HER2+ breast cancer from the controls (AUC = 0.727).

CONCLUSION

The hypermethylation levels of CCDC12 in peripheral blood could be used for breast cancer detection.

The Significant Associations between Epigenetic Clocks and Bladder Cancer Risks

Bladder cancer is an age-related disease, with over three-quarters of cases occurring in individuals aged 65 years and older. Accelerated biological aging has been linked to elevated cancer risks. Epigenetic clocks serve as excellent predictors of biological age, yet it remains unclear whether they are associated with bladder cancer risk. In this large case-control study, we assessed the associations between four well-established epigenetic clocks-HannumAge, HorvathAge, GrimAge, and PhenoAge-and bladder cancer risk. Utilizing single nucleotide polymorphisms (SNPs), which were identified in a genome-wide association study (GWAS), linked to these clocks as instruments, we constructed a weighted genetic risk score (GRS) for each clock. We discovered that higher HannumAge and HorvathAge GRS were significantly associated with increased bladder cancer risk (OR = 1.69 per SD increase, 95% CI, 1.44-1.98, p = 1.56 × 10-10 and OR = 1.09 per SD increase, 95% CI, 1.00-1.19, p = 0.04, respectively). Employing a summary statistics-based Mendelian randomization (MR) method, inverse-variance weighting (IVW), we found consistent risk estimates for bladder cancer with both HannumAge and HorvathAge. Sensitivity analyses using weighted median analysis and MR-Egger regression further supported the validity of the IVW method. However, GrimAge and PhenoAge were not associated with bladder cancer risk. In conclusion, our data provide the first evidence that accelerated biological aging is associated with elevated bladder cancer risk.

Lung tumor discrimination by deep neural network model CanDo via DNA methylation in bronchial lavage

Bronchoscopic-assisted discrimination of lung tumors presents challenges, especially in cases with contraindications or inaccessible lesions. Through meta-analysis and validation using the HumanMethylation450 database, this study identified methylation markers for molecular discrimination in lung tumors and designed a sequencing panel. DNA samples from 118 bronchial washing fluid (BWF) specimens underwent enrichment via multiplex PCR before targeted methylation sequencing. The Recursive Feature Elimination Cross-Validation and deep neural network algorithm established the CanDo classification model, which incorporated 11 methylation features (including 8 specific to the TBR1 gene), demonstrating a sensitivity of 98.6% and specificity of 97.8%. In contrast, bronchoscopic rapid on-site evaluation (bronchoscopic-ROSE) had lower sensitivity (87.7%) and specificity (80%). Further validation in 33 individuals confirmed CanDo's discriminatory potential, particularly in challenging cases for bronchoscopic-ROSE due to pathological complexity. CanDo serves as a valuable complement to bronchoscopy for the discriminatory diagnosis and stratified management of lung tumors utilizing BWF specimens.

Evaluation of DNAmAge in paired fresh, frozen, and formalin-fixed paraffin-embedded heart tissues

The continued development in methylome analysis has enabled a more precise assessment of DNA methylation, but treatment of target tissue prior to analysis may affect DNA analysis. Prediction of age based on methylation levels in the genome (DNAmAge) has gained much interest in disease predisposition (biological age estimation), but also in chronological donor age estimation in crime case samples. Various epigenetic clocks were designed to predict the age. However, it remains unknown how the storage of the tissues affects the DNAmAge estimation. In this study, we investigated the storage method impact of DNAmAge by the comparing the DNAmAge of the two commonly used storage methods, freezing and formalin-fixation and paraffin-embedding (FFPE) to DNAmAge of fresh tissue. This was carried out by comparing paired heart tissue samples of fresh tissue, samples stored by freezing and FFPE to chronological age and whole blood samples from the same individuals. Illumina EPIC beadchip array was used for methylation analysis and the DNAmAge was evaluated with the following epigenetic clocks: Horvath, Hannum, Levine, Horvath skin+blood clock (Horvath2), PedBE, Wu, BLUP, EN, and TL. We observed differences in DNAmAge among the storage conditions. FFPE samples showed a lower DNAmAge compared to that of frozen and fresh samples. Additionally, the DNAmAge of the heart tissue was lower than that of the whole blood and the chronological age. This highlights caution when evaluating DNAmAge for FFPE samples as the results were underestimated compared with fresh and frozen tissue samples. Furthermore, the study also emphasizes the need for a DNAmAge model based on heart tissue samples for an accurate age estimation.

Analysis of epigenetic clocks links yoga, sleep, education, reduced meat intake, coffee, and a SOCS2 gene variant to slower epigenetic aging

DNA methylation (DNAm) clocks hold promise for measuring biological age, useful for guiding clinical interventions and forensic identification. This study compared the commonly used DNAm clocks, using DNA methylation and SNP data generated from nearly 1000 human blood or buccal swab samples. We evaluated different preprocessing methods for age estimation, investigated the association of epigenetic age acceleration (EAA) with various lifestyle and sociodemographic factors, and undertook a series of novel genome-wide association analyses for different EAA measures to find associated genetic variants. Our results highlighted the Skin&Blood clock with ssNoob normalization as the most accurate predictor of chronological age. We provided novel evidence for an association between the practice of yoga and a reduction in the pace of aging (DunedinPACE). Increased sleep and physical activity were associated with lower mortality risk score (MRS) in our dataset. University degree, vegetable consumption, and coffee intake were associated with reduced levels of epigenetic aging, whereas smoking, higher BMI, meat consumption, and manual occupation correlated well with faster epigenetic aging, with FitAge, GrimAge, and DunedinPACE clocks showing the most robust associations. In addition, we found a novel association signal for SOCS2 rs73218878 (p = 2.87 × 10-8) and accelerated GrimAge. Our study emphasizes the importance of an optimized DNAm analysis workflow for accurate estimation of epigenetic age, which may influence downstream analyses. The results support the influence of genetic background on EAA. The associated SOCS2 is a member of the suppressor of cytokine signaling family known for its role in human longevity. The reported association between various risk factors and EAA has practical implications for the development of health programs to improve quality of life and reduce premature mortality associated with age-related diseases.

Unveiling Gene Interactions in Alzheimer's Disease by Integrating Genetic and Epigenetic Data with a Network-Based Approach

Alzheimer's Disease (AD) is a complex disease and the leading cause of dementia in older people. We aimed to uncover aspects of AD's pathogenesis that may contribute to drug repurposing efforts by integrating DNA methylation and genetic data. Implementing the network-based tool, a dense module search of genome-wide association studies (dmGWAS), we integrated a large-scale GWAS dataset with DNA methylation data to identify gene network modules associated with AD. Our analysis yielded 286 significant gene network modules. Notably, the foremost module included the BIN1 gene, showing the largest GWAS signal, and the GNAS gene, the most significantly hypermethylated. We conducted Web-based Cell-type-Specific Enrichment Analysis (WebCSEA) on genes within the top 10% of dmGWAS modules, highlighting monocyte as the most significant cell type (p < 5 × 10-12). Functional enrichment analysis revealed Gene Ontology Biological Process terms relevant to AD pathology (adjusted p < 0.05). Additionally, drug target enrichment identified five FDA-approved targets (p-value = 0.03) for further research. In summary, dmGWAS integration of genetic and epigenetic signals unveiled new gene interactions related to AD, offering promising avenues for future studies.

Epigenetic reprogramming as a key to reverse ageing and increase longevity

The pursuit for the fountain of youth has long been a fascination amongst scientists and humanity. Ageing is broadly characterized by a cellular decline with increased susceptibility to age-related diseases, being intimately associated with epigenetic modifications. Recently, reprogramming-induced rejuvenation strategies have begun to greatly alter longevity research not only to tackle age-related defects but also to possibly reverse the cellular ageing process. Hence, in this review, we highlight the major epigenetic changes during ageing and the state-of-art of the current emerging epigenetic reprogramming strategies leveraging on transcription factors. Notably, partial reprogramming enables the resetting of the ageing clock without erasing cellular identity. Promising chemical-based rejuvenation strategies harnessing small molecules, including DNA methyltransferase and histone deacetylase inhibitors are also discussed. Moreover, in parallel to longevity interventions, the foundations of epigenetic clocks for accurate ageing assessment and evaluation of reprogramming approaches are briefly presented. Going further, with such scientific breakthroughs, we are witnessing a rise in the longevity biotech industry aiming to extend the health span and ideally achieve human rejuvenation one day. In this context, we overview the main scenarios proposed for the future of the socio-economic and ethical challenges associated with such an emerging field. Ultimately, this review aims to inspire future research on interventions that promote healthy ageing for all.

Estimation of cadaveric age in crime scenes using Raman spectroscopy

The number of unidentified corpses has been increasing in recent years. There is a need for an objective and readily applicable method to estimate age, which is important information for identification. In previous reports, we reported that the protein folding ratio (RPF) of skin, as measured by Raman spectroscopy using cross sections of skin samples, is highly correlated with age. In this study, we investigated the possibility of estimating age by measuring Raman spectra from the skin surface of cadavers using a portable device. The resultant intercept, slope, and root mean square error were 97.9, - 63.7 (p < 0.0001), and 11.68, respectively. We evaluated this regression formula by using 10-fold cross-validation, resulting in a coefficient of determination of 0.51. The portable Raman spectrometer may be of assistance in estimating age at death of corpses at the scene of discovery.

Estimation of Human Chronological Age from Buccal Swab Samples through a DNA Methylation Analysis Approach of a Five-Locus Multiple Regression Model

Recent advancements in forensic genetics have facilitated the extraction of additional characteristics from unidentified samples. This study delves into the predictive potential of a five-gene (ELOVL2, FHL2, KLF14, C1orf132, and TRIM59) methylation rate analysis for human age estimation using buccal swabs collected from 60 Italian volunteers. The methylation levels of specific CpG sites in the five genes were analyzed through bisulfite conversion, single-base extension, and capillary electrophoresis. A multivariate linear regression model was crafted on the training set, then the test set was employed to validate the predictive model. The multivariate predictive model revealed a mean absolute deviation of 3.49 years in the test set of our sample. While limitations include a modest sample size, the study provides valuable insights into the potential of buccal swab-based age prediction, aiding in criminal investigations where accurate age determination is crucial. Our results also highlight that it is necessary to investigate the effectiveness of predictive models specific to biological tissues and individual populations, since models already proven effective for other populations or different tissues did not show the same effectiveness in our study.

Geniposide alleviated hydrogen peroxide-induced apoptosis of human hepatocytes via altering DNA methylation

Geniposide (GP) is the homology of medicine and food with bioactive effects of antioxidation and resistance to apoptosis in the liver. It's of great significance to explore the biosafety exposure limits and action mechanisms of GP. This study detected the global DNA methylation microenvironment and the regulation of specific genes in GP against cellular apoptosis induced by hydrogen peroxide (H2O2) of human hepatocyte L-02 cells. The half inhibitory concentration (IC50) of GP on normal L-02 cells was 57.7 mg/mL. GP exerted new epigenetic activity, increased DNMT1, decreased TET1 and TET2 expression, and reversed the demethylation effect to some extent, thereby increasing the overall genomic DNA methylation level at the concentration of 900 μg/mL. GP pretreatment could also adjust the level of P53, Bcl-2 and AKT altered by H2O2, reducing their specific DNA methylation levels in the promoter regions of AKT and Bcl-2 to inhibit apoptosis. Taken together, GP regulates the global DNA methylation level and controls the expression changes of P53, Bcl-2 and AKT, jointly inhibiting the occurrence of apoptosis in human hepatocytes and providing the newly theoretical references for its safety evaluation.

Development of an epigenetic age predictor for costal cartilage with a simultaneous somatic tissue differentiation system

Age prediction from DNA has been a topic of interest in recent years due to the promising results obtained when using epigenetic markers. Since DNA methylation gradually changes across the individual's lifetime, prediction models have been developed accordingly for age estimation. The tissue-dependence for this biomarker usually necessitates the development of tissue-specific age prediction models, in this way, multiple models for age inference have been constructed for the most commonly encountered forensic tissues (blood, oral mucosa, semen). The analysis of skeletal remains has also been attempted and prediction models for bone have now been reported. Recently, the VISAGE Enhanced Tool was developed for the simultaneous DNA methylation analysis of 8 age-correlated loci using targeted high-throughput sequencing. It has been shown that this method is compatible with epigenetic age estimation models for blood, buccal cells, and bone. Since when dealing with decomposed cadavers or postmortem samples, cartilage samples are also an important biological source, an age prediction model for cartilage has been generated in the present study based on methylation data collected using the VISAGE Enhanced Tool. In this way, we have developed a forensic cartilage age prediction model using a training set composed of 109 samples (19-74 age range) based on DNA methylation levels from three CpGs in FHL2, TRIM59 and KLF14, using multivariate quantile regression which provides a mean absolute error (MAE) of ± 4.41 years. An independent testing set composed of 72 samples (19-75 age range) was also analyzed and provided an MAE of ± 4.26 years. In addition, we demonstrate that the 8 VISAGE markers, comprising EDARADD, TRIM59, ELOVL2, MIR29B2CHG, PDE4C, ASPA, FHL2 and KLF14, can be used as tissue prediction markers which provide reliable blood, buccal cells, bone, and cartilage differentiation using a developed multinomial logistic regression model. A training set composed of 392 samples (n = 87 blood, n = 86 buccal cells, n = 110 bone and n = 109 cartilage) was used for building the model (correct classifications: 98.72%, sensitivity: 0.988, specificity: 0.996) and validation was performed using a testing set composed of 192 samples (n = 38 blood, n = 36 buccal cells, n = 46 bone and n = 72 cartilage) showing similar predictive success to the training set (correct classifications: 97.4%, sensitivity: 0.968, specificity: 0.991). By developing both a new cartilage age model and a tissue differentiation model, our study significantly expands the use of the VISAGE Enhanced Tool while increasing the amount of DNA methylation-based information obtained from a single sample and a single forensic laboratory analysis. Both models have been placed in the open-access Snipper forensic classification website.

Evaluation of pediatric epigenetic clocks across multiple tissues

BACKGROUND

Epigenetic clocks are promising tools for assessing biological age. We assessed the accuracy of pediatric epigenetic clocks in gestational and chronological age determination.

RESULTS

Our study used data from seven tissue types on three DNA methylation profiling microarrays and found that the Knight and Bohlin clocks performed similarly for blood cells, while the Lee clock was superior for placental samples. The pediatric-buccal-epigenetic clock performed the best for pediatric buccal samples, while the Horvath clock is recommended for children's blood cell samples. The NeoAge clock stands out for its unique ability to predict post-menstrual age with high correlation with the observed age in infant buccal cell samples.

CONCLUSIONS

Our findings provide valuable guidance for future research and development of epigenetic clocks in pediatric samples, enabling more accurate assessments of biological age.

No evidence of accelerated epigenetic aging among black heroin users: A case vs control analysis

This study sought to assess the association between illicit opioid use and accelerated epigenetic aging (A.K.A. DNAm Age) among people of African ancestry who use heroin. DNA was obtained from participants with opioid use disorder (OUD) who confirmed heroin as their primary drug of choice. Clinical inventories of drug use included: the Addiction Severity Index (ASI) Drug-Composite Score (range: 0-1), and Drug Abuse Screening Test (DAST-10; range: 0-10). A control group of participants of African ancestry who did not use heroin was recruited and matched to heroin users on sex, age, socioeconomic level, and smoking status. Methylation data were assessed in an epigenetic clock to determined and compare Epigenetic Age to Chronological Age (i.e., age acceleration or deceleration). Data were obtained from 32 controls [mean age 36.3 (±7.5) years] and 64 heroin users [mean age 48.1 (±6.6) years]. The experimental group used heroin for an average of 18.1 (±10.6) years, reported use of 6.4 (±6.1) bags of heroin/day, with a mean DAST-10 score of 7.0 (±2.6) and ASI Score of 0.33 (±0.19). Mean age acceleration for heroin users [+0.56 (± 9.5) years] was significantly (p< 0.05) lower than controls [+5.19 (± 9.1) years]. This study did not find evidence that heroin use causes epigenetic age acceleration.

Introduction of a multiplex amplicon sequencing assay to quantify DNA methylation in target cytosine markers underlying four selected epigenetic clocks

BACKGROUND

DNA methylation analysis has proven to be a powerful tool for age assessment. However, the implementation of epigenetic age prediction in diagnostics or routine forensic casework requires appropriate laboratory methods. In this study, we aimed to compare the performance of large-scale DNA methylation analysis protocols that show promise in terms of accuracy, throughput, multiplexing capacity, and high sensitivity.

RESULTS

The protocols were designed to target a predefined panel of 161 genomic CG/CA sites from four known estimators of epigenetic age-related parameters, optimized and validated using artificially methylated controls or blood samples. We successfully targeted 96% of these loci using two enrichment protocols: Ion AmpliSeq™, an amplicon-based method integrated with Ion Torrent S5, and SureSelectXT Methyl-Seq, a hybridization-based method followed by MiSeq FGx sequencing. Both protocols demonstrated high accuracy and robustness. Although hybridization assays have greater multiplexing capabilities, the best overall performance was observed for the amplicon-based protocol with the lowest variability in DNA methylation at 25 ng of starting DNA, mean observed marker coverage of ~ 6.7 k reads, and accuracy of methylation quantification with a mean absolute difference between observed and expected methylation beta value of 0.054. The Ion AmpliSeq method correlated strongly with genome-scale EPIC microarray data (R = 0.91) and showed superiority in terms of methylation measurement accuracy. Method-to-method bias was accounted for by the use of linear transformation, which provided a highly accurate prediction of calendar age with a mean absolute error of less than 5 years for the VISAGE and Hannum age clocks used. The pace of aging (PoAm) and the mortality risk score (MRS) estimators included in our panel represent next-generation clocks, were found to have low to moderate correlations with the VISAGE and Hannum models (R < 0.75), and thus may capture different aspects of epigenetic aging.

CONCLUSIONS

We propose a laboratory tool that allows the quantification of DNA methylation in cytosines underlying four different clocks, thus providing broad information on epigenetic aging while maintaining a reasonable number of CpG markers, opening the way to a wide range of applications in forensics, medicine, and healthcare.

Associations between medium- and long-term exposure to air temperature and epigenetic age acceleration

Climate change poses a serious threat to human health worldwide, while aging populations increase. However, no study has ever investigated the effects of air temperature on epigenetic age acceleration. This study involved 1,725 and 1,877 participants from the population-based KORA F4 (2006-2008) and follow-up FF4 (2013-2014) studies, respectively, conducted in Augsburg, Germany. The difference between epigenetic age and chronological age was referred to as epigenetic age acceleration and reflected by Horvath's epigenetic age acceleration (HorvathAA), Hannum's epigenetic age acceleration (HannumAA), PhenoAge acceleration (PhenoAA), GrimAge acceleration (GrimAA), and Epigenetic Skin and Blood Age acceleration (SkinBloodAA). Daily air temperature was estimated using hybrid spatiotemporal regression-based models. To explore the medium- and long-term effects of air temperature modeled in time and space on epigenetic age acceleration, we applied generalized estimating equations (GEE) with distributed lag non-linear models, and GEE, respectively. We found that high temperature exposure based on the 8-week moving average air temperature (97.5th percentile of temperature compared to median temperature) was associated with increased HorvathAA, HannumAA, GrimAA, and SkinBloodAA: 1.83 (95% CI: 0.29-3.37), 11.71 (95% CI: 8.91-14.50), 2.26 (95% CI: 1.03-3.50), and 5.02 (95% CI: 3.42-6.63) years, respectively. Additionally, we found consistent results with high temperature exposure based on the 4-week moving average air temperature was associated with increased HannumAA, GrimAA, and SkinBloodAA: 9.18 (95% CI: 6.60-11.76), 1.78 (95% CI: 0.66-2.90), and 4.07 (95% CI: 2.56-5.57) years, respectively. For the spatial variation in annual average temperature, a 1 °C increase was associated with an increase in all five measures of epigenetic age acceleration (HorvathAA: 0.41 [95% CI: 0.24-0.57], HannumAA: 2.24 [95% CI: 1.95-2.53], PhenoAA: 0.32 [95% CI: 0.05-0.60], GrimAA: 0.24 [95%: 0.11-0.37], and SkinBloodAA: 1.17 [95% CI: 1.00-1.35] years). In conclusion, our results provide first evidence that medium- and long-term exposures to high air temperature affect increases in epigenetic age acceleration.