DNA Methylation Clocks in Aging: Categories, Causes, and Consequences

Exercise epigenetics is fueled by cell bioenergetics: Supporting role on brain plasticity and cognition

Exercise has the unique aptitude to benefit overall health of body and brain. Evidence indicates that the effects of exercise can be saved in the epigenome for considerable time to elevate the threshold for various diseases. The action of exercise on epigenetic regulation seems central to building an "epigenetic memory" to influence long-term brain function and behavior. As an intrinsic bioenergetic process, exercise engages the function of the mitochondria and redox pathways to impinge upon molecular mechanisms that regulate synaptic plasticity and learning and memory. We discuss how the action of exercise uses mechanisms of bioenergetics to support a "epigenetic memory" with long-term implications for neural and behavioral plasticity. This information is crucial for directing the power of exercise to reduce the burden of neurological and psychiatric disorders.

Role of epigenetic regulation on catecholamine synthesis in pheochromocytoma and paraganglioma

INTRODUCTION

Pheochromocytomas and paragangliomas (PPGLs) typically secrete catecholamines and their metabolites (metanephrines [MN] and normetanephrine [NMN]). Catecholamines are synthesized by several enzymes: phenylalanine hydroxylase (encoded by PAH), tyrosine hydroxylase (TH), aromatic L-amino acid decarboxylase (DDC), dopamine β-hydroxylase (DBH), and phenylethanolamine N-methyltransferase (PNMT). MN/NMN secretion varies between anatomical and molecular subgroups. The aim of this study was to assess the correlation between DNA methylation of catecholamine synthesis genes and MN/NMN secretion.

METHODS

Gene promoter methylation of PAH, TH, AADC, DBH, and PNMT were extracted and calculated based on publicly available data. Comparisons and correlation analysis were performed between MN ± NMN (MN/NMN), NMN only, and neither/unknown secretion patterns. Methylation levels and MN/NMN patterns were compared by three genetic alteration subgroups: pseudohypoxia (PH), kinase signaling (KS), and others.

RESULTS

A total of 178 cases were included. Methylation of PAH CpGs negatively correlated with probability for MN/NMN secretion (p < .05 for all CpGs) and positively with NMN-only secretion. NMN-only secreting tumors had significantly higher promoter methylation of PAH, DBH, and PNMT compared with MN/NMN-secreting tumors. MN/NMN-secreting PPGLs had mainly KS alterations (52.1%), whereas NMN-only PPGLs had PH alterations (41.9%). PPGLs in the PH versus KS group had gene promoter hypermethylation of PAH (p = .002), DBH (p = .02), and PNMT (p = .003).

CONCLUSIONS

Promoter methylation of genes encoding catecholamine synthesis enzymes is strongly and inversely correlated with MN/NMN patterns in PPGLs. KS and PH-related tumors have distinct methylation patterns. These results imply that methylation is a key regulatory mechanism of catecholamine synthesis in PPGLs.

Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.

Adding intrinsically disordered proteins to biological ageing clocks

Research into how the young and old differ, and which biomarkers reflect the diverse biological processes underlying ageing, is a current and fast-growing field. Biological clocks provide a means to evaluate whether a molecule, cell, tissue or even an entire organism is old or young. Here we summarize established and emerging molecular clocks as timepieces. We emphasize that intrinsically disordered proteins (IDPs) tend to transform into a β-sheet-rich aggregated state and accumulate in non-dividing or slowly dividing cells as they age. We hypothesize that understanding these protein-based molecular ageing mechanisms might provide a conceptual pathway to determining a cell's health age by probing the aggregation state of IDPs, which we term the IDP clock.

An epigenetic toolbox for conservation biologists

Ongoing climatic shifts and increasing anthropogenic pressures demand an efficient delineation of conservation units and accurate predictions of populations' resilience and adaptive potential. Molecular tools involving DNA sequencing are nowadays routinely used for these purposes. Yet, most of the existing tools focusing on sequence-level information have shortcomings in detecting signals of short-term ecological relevance. Epigenetic modifications carry valuable information to better link individuals, populations, and species to their environment. Here, we discuss a series of epigenetic monitoring tools that can be directly applied to various conservation contexts, complementing already existing molecular monitoring frameworks. Focusing on DNA sequence-based methods (e.g. DNA methylation, for which the applications are readily available), we demonstrate how (a) the identification of epi-biomarkers associated with age or infection can facilitate the determination of an individual's health status in wild populations; (b) whole epigenome analyses can identify signatures of selection linked to environmental conditions and facilitate estimating the adaptive potential of populations; and (c) epi-eDNA (epigenetic environmental DNA), an epigenetic-based conservation tool, presents a non-invasive sampling method to monitor biological information beyond the mere presence of individuals. Overall, our framework refines conservation strategies, ensuring a comprehensive understanding of species' adaptive potential and persistence on ecologically relevant timescales.

Targeting the epigenetically older individuals for geroprotective trials: the use of DNA methylation clocks

Chronological age is the most important risk factor for the incidence of age-related diseases. The pace of ageing determines the magnitude of that risk and can be expressed as biological age. Targeting fundamental pathways of human aging with geroprotectors has the potential to lower the biological age and therewith prolong the healthspan, the period of life one spends in good health. Target populations for geroprotective interventions should be chosen based on the ageing mechanisms being addressed and the expected effect of the geroprotector on the primary outcome. Biomarkers of ageing, such as DNA methylation age, can be used to select populations for geroprotective interventions and as a surrogate outcome. Here, the use of DNA methylation clocks for selecting target populations for geroprotective intervention is explored.

Cell-type-specific effects of age and sex on human cortical neurons

Altered transcriptional and epigenetic regulation of brain cell types may contribute to cognitive changes with advanced age. Using single-nucleus multi-omic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex from young adult and aged donors, we found widespread age- and sex-related variation in specific neuron types. The proportion of inhibitory SST- and VIP-expressing neurons was reduced in aged donors. Excitatory neurons had more profound age-related changes in their gene expression and DNA methylation than inhibitory cells. Hundreds of genes involved in synaptic activity, including EGR1, were less expressed in aged adults. Genes located in subtelomeric regions increased their expression with age and correlated with reduced telomere length. We further mapped cell-type-specific sex differences in gene expression and X-inactivation escape genes. Multi-omic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.

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.

An improved epigenetic counter to track mitotic age in normal and precancerous tissues

The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC's mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.

Can long-read sequencing tackle the barriers, which the next-generation could not? A review

The large-scale heterogeneity of genetic diseases necessitated the deeper examination of nucleotide sequence alterations enhancing the discovery of new targeted drug attack points. The appearance of new sequencing techniques was essential to get more interpretable genomic data. In contrast to the previous short-reads, longer lengths can provide a better insight into the potential health threatening genetic abnormalities. Long-reads offer more accurate variant identification and genome assembly methods, indicating advances in nucleotide deflect-related studies. In this review, we introduce the historical background of sequencing technologies and show their benefits and limits, as well. Furthermore, we highlight the differences between short- and long-read approaches, including their unique advances and difficulties in methodologies and evaluation. Additionally, we provide a detailed description of the corresponding bioinformatics and the current applications.

Cell-free DNA methylation patterns in aging and their association with inflamm-aging

Aim: Liquid biopsies analyzing cell-free DNA (cfDNA) methylation in plasma offer a noninvasive diagnostic for diseases, with the potential of aging biomarkers underexplored. Methods: Utilizing enzymatic methyl-seq (EM-seq), this study assessed cfDNA methylation patterns in aging with blood from 35 healthy individuals. Results: It found aging signatures, including higher cfDNA levels and variations in fragment sizes, plus approximately 2000 age-related differentially methylated CpG sites. A biological age predictive model based on 48 CpG sites showed a strong correlation with chronological age, verified by two datasets. Age-specific epigenetic shifts linked to inflammation were revealed through differentially methylated regions profiling and Olink proteomics. Conclusion: These findings suggest cfDNA methylation as a potential aging biomarker and might exacerbate immunoinflammatory reactivity in older individuals.

Biomarkers of Aging and Relevant Evaluation Techniques: A Comprehensive Review

The risk of developing chronic illnesses and disabilities is increasing with age. To predict and prevent aging, biomarkers relevant to the aging process must be identified. This paper reviews the known molecular, cellular, and physiological biomarkers of aging. Moreover, we discuss the currently available technologies for identifying these biomarkers, and their applications and potential in aging research. We hope that this review will stimulate further research and innovation in this emerging and fast-growing field.

MammalMethylClock R package: software for DNA methylation-based epigenetic clocks in mammals

MOTIVATION

Epigenetic clocks are prediction methods based on DNA methylation levels in a given species or set of species. Defined as multivariate regression models, these DNA methylation-based biomarkers of age or mortality risk are useful in species conservation efforts and in preclinical studies.

RESULTS

We present an R package called MammalMethylClock for the construction, assessment, and application of epigenetic clocks in different mammalian species. The R package includes the utility for implementing pre-existing mammalian clocks from the Mammalian Methylation Consortium.

AVAILABILITY AND IMPLEMENTATION

The source code and documentation manual for MammalMethylClock, and clock coefficient .csv files that are included within this software package, can be found on Zenodo at https://doi.org/10.5281/zenodo.10971037.

On epigenetic stochasticity, entropy and cancer risk

Epigenetic changes are known to accrue in normal cells as a result of ageing and cumulative exposure to cancer risk factors. Increasing evidence points towards age-related epigenetic changes being acquired in a quasi-stochastic manner, and that they may play a causal role in cancer development. Here, I describe the quasi-stochastic nature of DNA methylation (DNAm) changes in ageing cells as well as in normal cells at risk of neoplastic transformation, discussing the implications of this stochasticity for developing cancer risk prediction strategies, and in particular, how it may require a conceptual paradigm shift in how we select cancer risk markers. I also describe the mounting evidence that a significant proportion of DNAm changes in ageing and cancer development are related to cell proliferation, reflecting tissue-turnover and the opportunity this offers for predicting cancer risk via the development of epigenetic mitotic-like clocks. Finally, I describe how age-associated DNAm changes may be causally implicated in cancer development via an irreversible suppression of tissue-specific transcription factors that increases epigenetic and transcriptomic entropy, promoting a more plastic yet aberrant cancer stem-cell state. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Epigenomic insights into common human disease pathology

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Meta-analysis of epigenetic aging in schizophrenia reveals multifaceted relationships with age, sex, illness duration, and polygenic risk

BACKGROUND

The study of biological age acceleration may help identify at-risk individuals and reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a whole blood DNAm sample of 1090 SCZ cases and 1206 controls across four European cohorts, we performed a meta-analysis of differential aging using three DNAm clocks (i.e., Hannum, Horvath, and Levine). To dissect how DNAm aging contributes to SCZ, we integrated information on duration of illness and SCZ polygenic risk, as well as stratified our analyses by chronological age and biological sex.

RESULTS

We found that blood-based DNAm aging is significantly altered in SCZ independent from duration of the illness since onset. We observed sex-specific and nonlinear age effects that differed between clocks and point to possible distinct age windows of altered aging in SCZ. Most notably, intrinsic cellular age (Horvath clock) is decelerated in SCZ cases in young adulthood, while phenotypic age (Levine clock) is accelerated in later adulthood compared to controls. Accelerated phenotypic aging was most pronounced in women with SCZ carrying a high polygenic burden with an age acceleration of + 3.82 years (CI 2.02-5.61, P = 1.1E-03). Phenotypic aging and SCZ polygenic risk contributed additively to the illness and together explained up to 14.38% of the variance in disease status.

CONCLUSIONS

Our study contributes to the growing body of evidence of altered DNAm aging in SCZ and points to intrinsic age deceleration in younger adulthood and phenotypic age acceleration in later adulthood in SCZ. Since increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. Our study did not find that DNAm aging could be explained by the duration of illness of patients, but we did observe age- and sex-specific effects that warrant further investigation. Finally, our results show that combining genetic and epigenetic predictors can improve predictions of disease outcomes and may help with disease management in schizophrenia.

Application of a mathematical model to clarify the statistical characteristics of a pan-tissue DNA methylation clock

DNA methylation clocks estimate biological age based on DNA methylation profiles. This study developed a mathematical model to describe DNA methylation aging and the establishment of a pan-tissue DNA methylation clock. The model simulates the aging dynamics of DNA methylation profiles based on passive demethylation as well as the process of cross-sectional bulk data acquisition. As a result, this study identified two conditions under which the pan-tissue DNA methylation clock can successfully predict biological age: one condition is that the target tissues are sufficiently well represented in the training dataset, and the other condition is that the target sample contains cell subsets that are common among different tissues. When either of these conditions is met, the clock performs well. It is also suggested that the epigenetic age of all samples in the target tissue tends to be either over or underestimated when biological age prediction fails. The model can reveal the statistical characteristics of DNA methylation clocks.

Histone H3.1 is a chromatin-embedded redox sensor triggered by tumor cells developing adaptive phenotypic plasticity and multidrug resistance

Chromatin structure is regulated through posttranslational modifications of histone variants that modulate transcription. Although highly homologous, histone variants display unique amino acid sequences associated with specific functions. Abnormal incorporation of histone variants contributes to cancer initiation, therapy resistance, and metastasis. This study reports that, among its biologic functions, histone H3.1 serves as a chromatin redox sensor that is engaged by mitochondrial H2O2. In breast cancer cells, the oxidation of H3.1Cys96 promotes its eviction and replacement by H3.3 in specific promoters. We also report that this process facilitates the opening of silenced chromatin domains and transcriptional activation of epithelial-to-mesenchymal genes associated with cell plasticity. Scavenging nuclear H2O2 or amino acid substitution of H3.1(C96S) suppresses plasticity, restores sensitivity to chemotherapy, and induces remission of metastatic lesions. Hence, it appears that increased levels of H2O2 produced by mitochondria of breast cancer cells directly promote redox-regulated H3.1-dependent chromatin remodeling involved in chemoresistance and metastasis.

Epigenetic Reprogramming Drives Epithelial Disruption in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) remains a major public health challenge that contributes greatly to mortality and morbidity worldwide. Although it has long been recognized that the epithelium is altered in COPD, there has been little focus on targeting it to modify the disease course. Therefore, mechanisms that disrupt epithelial cell function in patients with COPD are poorly understood. In this study, we sought to determine whether epigenetic reprogramming of the cell-cell adhesion molecule E-cadherin, encoded by the CDH1 gene, disrupts epithelial integrity. By reducing these epigenetic marks, we can restore epithelial integrity and rescue alveolar airspace destruction. We used differentiated normal and COPD-derived primary human airway epithelial cells, genetically manipulated mouse tracheal epithelial cells, and mouse and human precision-cut lung slices to assess the effects of epigenetic reprogramming. We show that the loss of CDH1 in COPD is due to increased DNA methylation site at the CDH1 enhancer D through the downregulation of the ten-eleven translocase methylcytosine dioxygenase (TET) enzyme TET1. Increased DNA methylation at the enhancer D region decreases the enrichment of RNA polymerase II binding. Remarkably, treatment of human precision-cut slices derived from patients with COPD with the DNA demethylation agent 5-aza-2'-deoxycytidine decreased cell damage and reduced air space enlargement in the diseased tissue. Here, we present a novel mechanism that targets epigenetic modifications to reverse the tissue remodeling in human COPD lungs and serves as a proof of concept for developing a disease-modifying target.

Cellular senescence of renal tubular epithelial cells in acute kidney injury

Cellular senescence represents an irreversible state of cell-cycle arrest during which cells secrete senescence-associated secretory phenotypes, including inflammatory factors and chemokines. Additionally, these cells exhibit an apoptotic resistance phenotype. Cellular senescence serves a pivotal role not only in embryonic development, tissue regeneration, and tumor suppression but also in the pathogenesis of age-related degenerative diseases, malignancies, metabolic diseases, and kidney diseases. The senescence of renal tubular epithelial cells (RTEC) constitutes a critical cellular event in the progression of acute kidney injury (AKI). RTEC senescence inhibits renal regeneration and repair processes and, concurrently, promotes the transition of AKI to chronic kidney disease via the senescence-associated secretory phenotype. The mechanisms underlying cellular senescence are multifaceted and include telomere shortening or damage, DNA damage, mitochondrial autophagy deficiency, cellular metabolic disorders, endoplasmic reticulum stress, and epigenetic regulation. Strategies aimed at inhibiting RTEC senescence, targeting the clearance of senescent RTEC, or promoting the apoptosis of senescent RTEC hold promise for enhancing the renal prognosis of AKI. This review primarily focuses on the characteristics and mechanisms of RTEC senescence, and the impact of intervening RTEC senescence on the prognosis of AKI, aiming to provide a foundation for understanding the pathogenesis and providing potentially effective approaches for AKI treatment.

DNA repair-deficient premature aging models display accelerated epigenetic age

Several premature aging mouse models have been developed to study aging and identify interventions that can delay age-related diseases. Yet, it is still unclear whether these models truly recapitulate natural aging. Here, we analyzed DNA methylation in multiple tissues of four previously reported mouse models of premature aging (Ercc1, LAKI, Polg, and Xpg). We estimated DNA methylation (DNAm) age of these samples using the Horvath clock. The most pronounced increase in DNAm age could be observed in Ercc1 mice, a strain which exhibits a deficit in DNA nucleotide excision repair. Similarly, we detected an increase in epigenetic age in fibroblasts isolated from patients with progeroid syndromes associated with mutations in DNA excision repair genes. These findings highlight that mouse models with deficiencies in DNA repair, unlike other premature aging models, display accelerated epigenetic age, suggesting a strong connection between DNA damage and epigenetic dysregulation during aging.

DNA methylation clocks for clawed frogs reveal evolutionary conservation of epigenetic aging

To address how conserved DNA methylation-based epigenetic aging is in diverse branches of the tree of life, we generated DNA methylation data from African clawed frogs (Xenopus laevis) and Western clawed frogs (Xenopus tropicalis) and built multiple epigenetic clocks. Dual species clocks were developed that apply to both humans and frogs (human-clawed frog clocks), supporting that epigenetic aging processes are evolutionary conserved outside mammals. Highly conserved positively age-related CpGs are located in neural-developmental genes such as uncx, tfap2d as well as nr4a2 implicated in age-associated disease. We conclude that signatures of epigenetic aging are evolutionary conserved between frogs and mammals and that the associated genes relate to neural processes, altogether opening opportunities to employ Xenopus as a model organism to study aging.

Biologically informed deep learning for explainable epigenetic clocks

Ageing is often characterised by progressive accumulation of damage, and it is one of the most important risk factors for chronic disease development. Epigenetic mechanisms including DNA methylation could functionally contribute to organismal aging, however the key functions and biological processes may govern ageing are still not understood. Although age predictors called epigenetic clocks can accurately estimate the biological age of an individual based on cellular DNA methylation, their models have limited ability to explain the prediction algorithm behind and underlying key biological processes controlling ageing. Here we present XAI-AGE, a biologically informed, explainable deep neural network model for accurate biological age prediction across multiple tissue types. We show that XAI-AGE outperforms the first-generation age predictors and achieves similar results to deep learning-based models, while opening up the possibility to infer biologically meaningful insights of the activity of pathways and other abstract biological processes directly from the model.

Development of an epigenetic clock to predict visual age progression of human skin

Aging is a complex process characterized by the gradual decline of physiological functions, leading to increased vulnerability to age-related diseases and reduced quality of life. Alterations in DNA methylation (DNAm) patterns have emerged as a fundamental characteristic of aged human skin, closely linked to the development of the well-known skin aging phenotype. These changes have been correlated with dysregulated gene expression and impaired tissue functionality. In particular, the skin, with its visible manifestations of aging, provides a unique model to study the aging process. Despite the importance of epigenetic age clocks in estimating biological age based on the correlation between methylation patterns and chronological age, a second-generation epigenetic age clock, which correlates DNAm patterns with a particular phenotype, specifically tailored to skin tissue is still lacking. In light of this gap, we aimed to develop a novel second-generation epigenetic age clock explicitly designed for skin tissue to facilitate a deeper understanding of the factors contributing to individual variations in age progression. To achieve this, we used methylation patterns from more than 370 female volunteers and developed the first skin-specific second-generation epigenetic age clock that accurately predicts the skin aging phenotype represented by wrinkle grade, visual facial age, and visual age progression, respectively. We then validated the performance of our clocks on independent datasets and demonstrated their broad applicability. In addition, we integrated gene expression and methylation data from independent studies to identify potential pathways contributing to skin age progression. Our results demonstrate that our epigenetic age clock, VisAgeX, specifically predicting visual age progression, not only captures known biological pathways associated with skin aging, but also adds novel pathways associated with skin aging.

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.

Application of array-based age prediction models to post-mortem tissue samples

Since DNA methylation at specific CpG sites exhibits a strong age association, researchers have developed numerous age prediction models based on the methylation BeadChip array. These models harness epigenetic clocks that hold the potential to narrow down the search range for unknown suspects and unidentified victims. This study collected 180 post-mortem tissue samples comprising nine tissue types (blood, brain, heart, lung, liver, kidney, muscle, epidermis, and dermis) from autopsies of 20 Koreans aged 18-78. Subsequently, DNA methylation profiling was conducted using the Infinium MethylationEPIC array. We tested several array-based age prediction models using the data obtained from various tissues. The pan-tissue clock exhibited a moderately accurate prediction across all nine tissue types (MAE = 8.7 years, r = 0.88). Notably, the DNAm ages of the Hannum clock, the skin & blood clock, and the Zhang clock strongly correlated with the actual age in blood samples (MAE < approximately 5 years, r > 0.9). PhenoAge yielded an MAE of 10.1 years and an r-value of 0.92. The muscle-specific epigenetic clock, the MEAT package, demonstrated high prediction accuracy in muscle samples (MAE = 4.7 years, r = 0.93). Those previously reported array-based age prediction models were mainly constructed in Europeans but performed well in Koreans. In addition, tests involving various quantities of DNA and fragmented DNA have shown that DNA quantity and quality affected methylation measurements and age prediction results. However, robust age prediction models exist under low amounts of DNA and fragmented DNA conditions.

Hypertrophic cardiomyopathy in MYBPC3 carriers in aging

Hypertrophic cardiomyopathy (HCM) is characterized by abnormal thickening of the myocardium, leading to arrhythmias, heart failure, and elevated risk of sudden cardiac death, particularly among the young. This inherited disease is predominantly caused by mutations in sarcomeric genes, among which those in the cardiac myosin binding protein-C3 (MYBPC3) gene are major contributors. HCM associated with MYBPC3 mutations usually presents in the elderly and ranges from asymptomatic to symptomatic forms, affecting numerous cardiac functions and presenting significant health risks with a spectrum of clinical manifestations. Regulation of MYBPC3 expression involves various transcriptional and translational mechanisms, yet the destiny of mutant MYBPC3 mRNA and protein in late-onset HCM remains unclear. Pathogenesis related to MYBPC3 mutations includes nonsense-mediated decay, alternative splicing, and ubiquitin-proteasome system events, leading to allelic imbalance and haploinsufficiency. Aging further exacerbates the severity of HCM in carriers of MYBPC3 mutations. Advancements in high-throughput omics techniques have identified crucial molecular events and regulatory disruptions in cardiomyocytes expressing MYBPC3 variants. This review assesses the pathogenic mechanisms that promote late-onset HCM through the lens of transcriptional, post-transcriptional, and post-translational modulation of MYBPC3, underscoring its significance in HCM across carriers. The review also evaluates the influence of aging on these processes and MYBPC3 levels during HCM pathogenesis in the elderly. While pinpointing targets for novel medical interventions to conserve cardiac function remains challenging, the emergence of personalized omics offers promising avenues for future HCM treatments, particularly for late-onset cases.

Exercise is associated with younger methylome and transcriptome profiles in human skeletal muscle

Exercise training prevents age-related decline in muscle function. Targeting epigenetic aging is a promising actionable mechanism and late-life exercise mitigates epigenetic aging in rodent muscle. Whether exercise training can decelerate, or reverse epigenetic aging in humans is unknown. Here, we performed a powerful meta-analysis of the methylome and transcriptome of an unprecedented number of human skeletal muscle samples (n = 3176). We show that: (1) individuals with higher baseline aerobic fitness have younger epigenetic and transcriptomic profiles, (2) exercise training leads to significant shifts of epigenetic and transcriptomic patterns toward a younger profile, and (3) muscle disuse "ages" the transcriptome. Higher fitness levels were associated with attenuated differential methylation and transcription during aging. Furthermore, both epigenetic and transcriptomic profiles shifted toward a younger state after exercise training interventions, while the transcriptome shifted toward an older state after forced muscle disuse. We demonstrate that exercise training targets many of the age-related transcripts and DNA methylation loci to maintain younger methylome and transcriptome profiles, specifically in genes related to muscle structure, metabolism, and mitochondrial function. Our comprehensive analysis will inform future studies aiming to identify the best combination of therapeutics and exercise regimes to optimize longevity.

Skeletal muscle DNA methylation: Effects of exercise and HIV

Aging, human immunodeficiency virus (HIV) infection, and antiretroviral therapy modify the epigenetic profile and function of cells and tissues, including skeletal muscle (SkM). In some cells, accelerated epigenetic aging begins very soon after the initial HIV infection, potentially setting the stage for the early onset of frailty. Exercise imparts epigenetic modifications in SkM that may underpin some health benefits, including delayed frailty, in people living with HIV (PWH). In this first report of exercise-related changes in SkM DNA methylation among PWH, we investigated the impact of 24 weeks of aerobic and resistance exercise training on SkM (vastus lateralis) DNA methylation profiles and epigenetic age acceleration (EAA) in older, virally suppressed PWH (n = 12) and uninfected controls (n = 18), and associations of EAA with physical function at baseline. We identified 983 differentially methylated positions (DMPs) in PWH and controls at baseline and 237 DMPs after training. The influence of HIV serostatus on SkM methylation was more pronounced than that of exercise training. There was little overlap in the genes associated with the probes most significantly differentiated by exercise training within each group. Baseline EAA (mean ± SD) was similar between PWH (-0.4 ± 2.5 years) and controls (0.2 ± 2.6 years), and the exercise effect was not significant (p = 0.79). EAA and physical function at baseline were not significantly correlated (all p ≥ 0.10). This preliminary investigation suggests HIV-specific epigenetic adaptations in SkM with exercise training but confirmation in a larger study that includes transcriptomic analysis is warranted.

Non-Pharmacological Approach to Diet and Exercise in Metabolic-Associated Fatty Liver Disease: Bridging the Gap between Research and Clinical Practice

This review provides a practical and comprehensive overview of non-pharmacological interventions for metabolic-associated fatty liver disease (MASLD), focusing on dietary and exercise strategies. It highlights the effectiveness of coffee consumption, intermittent fasting, and Mediterranean and ketogenic diets in improving metabolic and liver health. The review emphasizes the importance of combining aerobic and resistance training as a critical approach to reducing liver fat and increasing insulin sensitivity. Additionally, it discusses the synergy between diet and exercise in enhancing liver parameters and the role of gut microbiota in MASLD. The paper underscores the need for a holistic, individualized approach, integrating diet, exercise, gut health, and patient motivation. It also highlights the long-term benefits and minimal risks of lifestyle interventions compared to the side effects of pharmacological and surgical options. The review calls for personalized treatment strategies, continuous patient education, and further research to optimize therapeutic outcomes in MASLD management.

Biological Aging Acceleration Due to Environmental Exposures: An Exciting New Direction in Toxicogenomics Research

Biological clock technologies are designed to assess the acceleration of biological age (B-age) in diverse cell types, offering a distinctive opportunity in toxicogenomic research to explore the impact of environmental stressors, social challenges, and unhealthy lifestyles on health impairment. These clocks also play a role in identifying factors that can hinder aging and promote a healthy lifestyle. Over the past decade, researchers in epigenetics have developed testing methods that predict the chronological and biological age of organisms. These methods rely on assessing DNA methylation (DNAm) levels at specific CpG sites, RNA levels, and various biomolecules across multiple cell types, tissues, and entire organisms. Commonly known as 'biological clocks' (B-clocks), these estimators hold promise for gaining deeper insights into the pathways contributing to the development of age-related disorders. They also provide a foundation for devising biomedical or social interventions to prevent, reverse, or mitigate these disorders. This review article provides a concise overview of various epigenetic clocks and explores their susceptibility to environmental stressors.

Novel urine cell-free DNA methylation markers for hepatocellular carcinoma

An optimized hepatocellular carcinoma (HCC)-targeted methylation next generation sequencing assay was developed to discover HCC-associated methylation markers directly from urine for HCC screening. Urine cell-free DNA (ucfDNA) isolated from a discovery cohort of 31 non-HCC and 30 HCC was used for biomarker discovery, identifying 29 genes with differentially methylated regions (DMRs). Methylation-specific qPCR (MSqPCR) assays were developed to verify the selected DMRs corresponding to 8 genes (GRASP, CCND2, HOXA9, BMP4, VIM, EMX1, SFRP1, and ECE). Using archived ucfDNA, methylation of GRASP, HOXA9, BMP4, and ECE1, were found to be significantly different (p < 0.05) between HCC and non-HCC patients. The four markers together with previously reported GSTP1 and RASSF1A markers were assessed as a 6-marker panel in an independent training cohort of 87 non-HCC and 78 HCC using logistic regression modeling. AUROC of 0.908 (95% CI, 0.8656-0.9252) was identified for the 6-marker panel with AFP, which was significantly higher than AFP-alone (AUROC 0.841 (95% CI, 0.778-0.904), p = 0.0026). Applying backward selection method, a 4-marker panel was found to exhibit similar performance to the 6-marker panel with AFP having 80% sensitivity compared to 29.5% by AFP-alone at a specificity of 85%. This study supports the potential use of methylated transrenal ucfDNA for HCC screening.

Combination of the biomarkers for aging and cancer? - Challenges and current status

The proportion of patients diagnosed with cancer has been shown to rise with the increasing aging global population. Advanced age is a major risk factor for morbidity and mortality in older adults. As individuals experience varying health statuses, particularly with age, it poses a challenge for medical professionals in the cancer field to obtain standardized treatment outcomes. Hence, relying solely on chronological age and disease-related parameters is inadequate for clinical decision-making for elderly patients. With functional, multimorbidity-related, and psychosocial changes that occur with aging, oncologic diseases may develop and be treated differently from younger patients, leading to unique challenges in treatment efficacy and tolerance. To overcome this challenge, personalized therapy using biomarkers has emerged as a promising solution. Various categories of biomarkers, including inflammatory, hematological, metabolic, endocrine, and DNA modification-related indicators, may display features related to both cancer and aging, aiding in the development of innovative therapeutic approaches for patients with cancer in old age. Furthermore, physical functional measurements as non-molecular phenotypic biomarkers are being investigated for their potential complementary role in structured multidomain strategies to combat age-related diseases such as cancer. This review provides insight into the current developments, recent discoveries, and significant challenges in cancer and aging biomarkers, with a specific focus on their application in advanced age.

Early life adversity predicts an accelerated cellular aging phenotype through early timing of puberty

BACKGROUND

The current study examined if early adversity was associated with accelerated biological aging, and if effects were mediated by the timing of puberty.

METHODS

In early mid-life, 187 Black and 198 White (Mage = 39.4, s.d.age = 1.2) women reported on early abuse and age at first menstruation (menarche). Women provided saliva and blood to assess epigenetic aging, telomere length, and C-reactive protein. Using structural equation modeling, we created a latent variable of biological aging using epigenetic aging, telomere length, and C-reactive protein as indicators, and a latent variable of early abuse using indicators of abuse/threat events before age 13, physical abuse, and sexual abuse. We estimated the indirect effects of early abuse and of race on accelerated aging through age at menarche. Race was used as a proxy for adversity in the form of systemic racism.

RESULTS

There was an indirect effect of early adversity on accelerated aging through age at menarche (b = 0.19, 95% CI 0.03-0.44), in that women who experienced more adversity were younger at menarche, which was associated with greater accelerated aging. There was also an indirect effect of race on accelerated aging through age at menarche (b = 0.25, 95% CI 0.04-0.52), in that Black women were younger at menarche, which led to greater accelerated aging.

CONCLUSIONS

Early abuse and being Black in the USA may both induce a phenotype of accelerated aging. Early adversity may begin to accelerate aging during childhood, in the form of early pubertal timing.

Childhood environment influences epigenetic age and methylation concordance of a CpG clock locus in British-Bangladeshi migrants

Migration from one location to another often comes with a change in environmental conditions. Here, we analysed features of DNA methylation in young, adult British-Bangladeshi women who experienced different environments during their childhoods: a) migrants, who grew up in Bangladesh with exposure to comparatively higher pathogen loads and poorer health care, and b) second-generation British-Bangladeshis, born to Bangladeshi parents, who grew up in the UK. We used buccal DNA to estimate DNA methylation-based age (DNAm age) from 14 migrants and 11 second-generation migrants, aged 18-35 years. 'AgeAccel,' a measure of DNAm age, independent of chronological age, showed that the group of women who spent their childhood in Bangladesh had higher AgeAccel (P = 0.028), compared to their UK peers. Since epigenetic clocks have been proposed to be associated with maintenance processes of epigenetic systems, we evaluated the preference for concordant DNA methylation at the luteinizing hormone/choriogonadotropin receptor (LHCGR/LHR) locus, which harbours one of the CpGs contributing to Horvath's epigenetic clock. Measurements on both strands of individual, double-stranded DNA molecules indicate higher stability of DNA methylation states at this LHCGR/LHR locus in samples of women who grew up in Bangladesh. Together, our two independent analytical approaches imply that childhood environments may induce subtle changes that are detectable long after exposure occurred, which might reflect altered activity of the epigenetic maintenance system or a difference in the proportion of cell types in buccal tissue. This exploratory work supports our earlier findings that adverse childhood environments lead to phenotypic life history trade-offs.

Epigenetic clocks in neurodegenerative diseases: a systematic review

BACKGROUND

Biological ageing is one of the principal risk factors for neurodegenerative diseases. It is becoming increasingly clear that acceleration of DNA methylation age, as measured by the epigenetic clock, is closely associated with many age-related diseases.

METHODS

We searched the PubMed and Web of Science databases to identify eligible studies reporting epigenetic clocks in several neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS) and Huntington's disease (HD).

RESULTS

Twenty-three studies (12 for AD, 4 for PD, 5 for ALS, and 2 for HD) were included. We systematically summarised the clinical utility of 11 epigenetic clocks (based on blood and brain tissues) in assessing the risk factors, age of onset, diagnosis, progression, prognosis and pathology of AD, PD, ALS and HD. We also critically described our current understandings to these evidences, and further discussed key challenges, potential mechanisms and future perspectives of epigenetic ageing in neurodegenerative diseases.

CONCLUSIONS

Epigenetic clocks hold great potential in neurodegenerative diseases. Further research is encouraged to evaluate the clinical utility and promote the application.

PROSPERO REGISTRATION NUMBER

CRD42022365233.

Pleiotropic influence of DNA methylation QTLs on physiological and ageing traits

DNA methylation is influenced by genetic and non-genetic factors. Here, we chart quantitative trait loci (QTLs) that modulate levels of methylation at highly conserved CpGs using liver methylome data from mouse strains belonging to the BXD family. A regulatory hotspot on chromosome 5 had the highest density of trans-acting methylation QTLs (trans-meQTLs) associated with multiple distant CpGs. We refer to this locus as meQTL.5a. Trans-modulated CpGs showed age-dependent changes and were enriched in developmental genes, including several members of the MODY pathway (maturity onset diabetes of the young). The joint modulation by genotype and ageing resulted in a more 'aged methylome' for BXD strains that inherited the DBA/2J parental allele at meQTL.5a. Further, several gene expression traits, body weight, and lipid levels mapped to meQTL.5a, and there was a modest linkage with lifespan. DNA binding motif and protein-protein interaction enrichment analyses identified the hepatic nuclear factor, Hnf1a (MODY3 gene in humans), as a strong candidate. The pleiotropic effects of meQTL.5a could contribute to variations in body size and metabolic traits, and influence CpG methylation and epigenetic ageing that could have an impact on lifespan.

Ectoine Globally Hypomethylates DNA in Skin Cells and Suppresses Cancer Proliferation

Epigenetic modifications, mainly aberrant DNA methylation, have been shown to silence the expression of genes involved in epigenetic diseases, including cancer suppression genes. Almost all conventional cancer therapeutic agents, such as the DNA hypomethylation drug 5-aza-2-deoxycytidine, have insurmountable side effects. To investigate the role of the well-known DNA protectant (ectoine) in skin cell DNA methylation and cancer cell proliferation, comprehensive methylome sequence analysis, 5-methyl cytosine (5mC) analysis, proliferation and tumorigenicity assays, and DNA epigenetic modifications-related gene analysis were performed. The results showed that extended ectoine treatment globally hypomethylated DNA in skin cells, especially in the CpG island (CGIs) element, and 5mC percentage was significantly reduced. Moreover, ectoine mildly inhibited skin cell proliferation and did not induce tumorigenicity in HaCaT cells injected into athymic nude mice. HaCaT cells treated with ectoine for 24 weeks modulated the mRNA expression levels of Dnmt1, Dnmt3a, Dnmt3b, Dnmt3l, Hdac1, Hdac2, Kdm3a, Mettl3, Mettl14, Snrpn, and Mest. Overall, ectoine mildly demethylates DNA in skin cells, modulates the expression of epigenetic modification-related genes, and reduces cell proliferation. This evidence suggests that ectoine is a potential anti-aging agent that prevents DNA hypermethylation and subsequently activates cancer-suppressing genes.

Imaging-based chromatin and epigenetic age, ImAge, quantitates aging and rejuvenation

Biomarkers of biological age that predict the risk of disease and expected lifespan better than chronological age are key to efficient and cost-effective healthcare1-3. To advance a personalized approach to healthcare, such biomarkers must reliably and accurately capture individual biology, predict biological age, and provide scalable and cost-effective measurements. We developed a novel approach - image-based chromatin and epigenetic age (ImAge) that captures intrinsic progressions of biological age, which readily emerge as principal changes in the spatial organization of chromatin and epigenetic marks in single nuclei without regression on chronological age. ImAge captured the expected acceleration or deceleration of biological age in mice treated with chemotherapy or following a caloric restriction regimen, respectively. ImAge from chronologically identical mice inversely correlated with their locomotor activity (greater activity for younger ImAge), consistent with the widely accepted role of locomotion as an aging biomarker across species. Finally, we demonstrated that ImAge is reduced following transient expression of OSKM cassette in the liver and skeletal muscles and reveals heterogeneity of in vivo reprogramming. We propose that ImAge represents the first-in-class imaging-based biomarker of aging with single-cell resolution.

Recent omics advances in hair aging biology and hair biomarkers analysis

Aging is a complex natural process that leads to a decline in physiological functions, which is visible in signs such as hair graying, thinning, and loss. Although hair graying is characterized by a loss of pigment in the hair shaft, the underlying mechanism of age-associated hair graying is not fully understood. Hair graying and loss can have a significant impact on an individual's self-esteem and self-confidence, potentially leading to mental health problems such as depression and anxiety. Omics technologies, which have applications beyond clinical medicine, have led to the discovery of candidate hair biomarkers and may provide insight into the complex biology of hair aging and identify targets for effective therapies. This review provides an up-to-date overview of recent omics discoveries, including age-associated alterations of proteins and metabolites in the hair shaft and follicle, and highlights the significance of hair aging and graying biomarker discoveries. The decline in hair follicle stem cell activity with aging decreased the regeneration capacity of hair follicles. Cellular senescence, oxidative damage and altered extracellular matrix of hair follicle constituents characterized hair follicle and hair shaft aging and graying. The review attempts to correlate the impact of endogenous and exogenous factors on hair aging. We close by discussing the main challenges and limitations of the field, defining major open questions and offering an outlook for future research.

Racial and Ethnic Residential Segregation and Monocyte DNA Methylation Age Acceleration

Importance

Neighborhood segregation and poverty may be important drivers of health inequities. Epigenomic factors, including DNA methylation clocks that may mark underlying biological aging, have been implicated in the link between social factors and health.

Objective

To examine the associations of neighborhood segregation and poverty with 4 DNA methylation clocks trained to capture either chronological age or physiological dysregulation.

Design, Setting, and Participants

This cohort study uses data from the Multi-Ethnic Study of Atherosclerosis (MESA), a longitudinal study that started in 2000 to 2002, with follow-up in 2002 to 2004, 2004 to 2005, 2005 to 2007, and 2010 to 2012. In 2000 to 2002, adults who identified as White or Black race or Hispanic or Chinese ethnicity in 6 US sites (Baltimore, Maryland; Chicago, Illinois; Forsyth County, North Carolina; Los Angeles County, California; Northern Manhattan, New York; and St. Paul, Minnesota) were sampled for recruitment. A random subsample of 4 sites (Maryland, North Carolina, New York, and Minnesota) were selected for inclusion in the MESA epigenomics ancillary study at examination 5 (2010-2012). Participants who identified as White or Black race or Hispanic ethnicity, were aged 45 to 84 years, and did not have clinical cardiovascular disease were included in this analysis. Data were analyzed from May 2021 to October 2023.

Exposure

Information on 2000 census tract poverty and Getis-Ord G statistic segregation of Hispanic residents, non-Hispanic Black residents, or non-Hispanic White residents were linked to participant addresses at examination 1 (2000-2002).

Main Outcomes and Measures

At examination 5, DNA methylation was measured in purified monocytes. DNA methylation age acceleration was calculated using 4 clocks trained on either chronological age or physiological dysregulation. Linear regressions were used to test associations.

Results

A total of 1102 participants (mean [SD] age, 69.7 [9.4] years; 562 [51%] women) were included, with 348 Hispanic participants, 222 non-Hispanic Black participants, and 533 non-Hispanic White participants. For non-Hispanic Black participants, living in tracts with greater segregation of Black residents was associated with GrimAge DNA methylation age acceleration, a clock designed to capture physiological dysregulation. A 1-SD increase in segregation was associated with 0.42 (95% CI, 0.20-0.64) years age acceleration (P < .001); this association was not observed with other clocks. This association was particularly pronounced for participants living in high poverty tracts (interaction term, 0.24; 95% CI, 0.07-0.42; P = .006). In the overall sample, census tract poverty level was associated with GrimAge DNA methylation age acceleration (β = 0.45; 95% CI, 0.20-0.71; adjusted P = .005).

Conclusions and Relevance

These findings suggest that epigenomic mechanisms may play a role in the associations of segregated and poor neighborhoods with chronic conditions.

Differences in epigenetic age by HIV status among patients with a non-AIDS defining cancer

OBJECTIVE

People with HIV (PWH) are living longer and experiencing higher numbers of non-AIDS-defining cancers (NADC). Epigenetic aging biomarkers have been linked to cancer risk, and cancer is now a leading cause of death in PWH, but these biomarkers have not been investigated in PWH and cancer.

DESIGN

In order to compare epigenetic age by HIV status, HIV-uninfected participants were matched to PWH by reported age, tumor site, tumor sequence number, and cancer treatment status.

METHODS

DNA from blood was assayed using Illumina MethylationEPIC BeadChip, and we estimated immune cell composition and aging from three epigenetic clocks: Horvath, GrimAge, and epiTOC2. Age acceleration by clock was computed as the residual from the expected value, calculated using linear regression, for each study participant. Comparisons across HIV status used the Wilcoxon rank sum test. Hazard ratios and 95% confidence intervals for the association between age acceleration and survival in PWH were estimated with Cox regression.

RESULTS

Among 65 NADC participants with HIV and 64 without, biological age from epiTOC2 ( P  < 0.0001) and GrimAge ( P  = 0.017) was significantly higher in PWH. Biological age acceleration was significantly higher in PWH using epiTOC2 ( P  < 0.01) and GrimAge ( P  < 0.0001), with the difference in GrimAge remaining statistically significant after adjustment for immune cell composition. Among PWH, GrimAge acceleration was significantly associated with increased risk of death (hazard ratio 1.11; 95% confidence interval (CI) 1.04-1.18).

CONCLUSION

We observed a higher epigenetic age in PWH with a NADC diagnosis compared with their HIV-uninfected counterparts, as well as a significant association between this accelerated biological aging and survival for patients diagnosed with a NADC.

Epigenetic age acceleration as a biomarker for impaired cognitive abilities in adulthood following early life adversity and psychiatric disorders

Background

Early life adversity and psychiatric disorders are associated with earlier declines in neurocognitive abilities during adulthood. These declines may be preceded by changes in biological aging, specifically epigenetic age acceleration, providing an opportunity to uncover genome-wide biomarkers that identify individuals most likely to benefit from early screening and prevention.

Methods

Five unique epigenetic age acceleration clocks derived from peripheral blood were examined in relation to latent variables of general and speeded cognitive abilities across two independent cohorts: 1) the Female Growth and Development Study (FGDS; n = 86), a 30-year prospective cohort study of substantiated child sexual abuse and non-abused controls, and 2) the Biological Classification of Mental Disorders study (BeCOME; n = 313), an adult community cohort established based on psychiatric disorders.

Results

A faster pace of biological aging (DunedinPoAm) was associated with lower general cognitive abilities in both cohorts and slower speeded abilities in the BeCOME cohort. Acceleration in the Horvath clock was significantly associated with slower speeded abilities in the BeCOME cohort but not the FGDS. Acceleration in the Hannum clock and the GrimAge clock were not significantly associated with either cognitive ability. Accelerated PhenoAge was associated with slower speeded abilities in the FGDS but not the BeCOME cohort.

Conclusions

The present results suggest that epigenetic age acceleration has the potential to serve as a biomarker for neurocognitive decline in adults with a history of early life adversity or psychiatric disorders. Estimates of epigenetic aging may identify adults at risk of cognitive decline that could benefit from early neurocognitive screening.

TET2 modulates spatial relocalization of heterochromatin in aged hematopoietic stem and progenitor cells

DNA methylation deregulation at partially methylated domains (PMDs) represents an epigenetic signature of aging and cancer, yet the underlying molecular basis and resulting biological consequences remain unresolved. We report herein a mechanistic link between disrupted DNA methylation at PMDs and the spatial relocalization of H3K9me3-marked heterochromatin in aged hematopoietic stem and progenitor cells (HSPCs) or those with impaired DNA methylation. We uncover that TET2 modulates the spatial redistribution of H3K9me3-marked heterochromatin to mediate the upregulation of endogenous retroviruses (ERVs) and interferon-stimulated genes (ISGs), hence contributing to functional decline of aged HSPCs. TET2-deficient HSPCs retain perinuclear distribution of heterochromatin and exhibit age-related clonal expansion. Reverse transcriptase inhibitors suppress ERVs and ISGs expression, thereby restoring age-related defects in aged HSPCs. Collectively, our findings deepen the understanding of the functional interplay between DNA methylation and histone modifications, which is vital for maintaining heterochromatin function and safeguarding genome stability in stem cells.

Association between infectious exposures in infancy and epigenetic age acceleration in young adulthood in metropolitan Cebu, Philippines

OBJECTIVES

The drivers of human life expectancy gains over the past 200 years are not well-established, with a potential role for historical reductions in infectious disease. We investigate whether infectious exposures in infancy predict biological aging using DNA methylation-based markers that forecast patterns of morbidity and mortality later in life.

METHODS

N = 1450 participants from the Cebu Longitudinal Health and Nutrition Survey-a prospective birth cohort initiated in 1983-provided complete data for the analyses. Mean chronological age was 20.9 years when venous whole blood samples were drawn for DNA extraction and methylation analysis, with subsequent calculation of three epigenetic age markers: Horvath, GrimAge, and DunedinPACE. Unadjusted and adjusted least squares regression models were evaluated to test the hypothesis that infectious exposures in infancy are associated with epigenetic age.

RESULTS

Birth in the dry season, a proxy measure for increased infectious exposure in the first year of life, as well as the number of symptomatic infections in the first year of infancy, predicted lower epigenetic age. Infectious exposures were associated with the distribution of white blood cells in adulthood, which were also associated with measures of epigenetic age.

CONCLUSIONS

We document negative associations between measures of infectious exposure in infancy and DNA methylation-based measures of aging. Additional research, across a wider range of epidemiological settings, is needed to clarify the role of infectious disease in shaping immunophenotypes and trajectories of biological aging and human life expectancy.

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

Yearning for machine learning: applications for the classification and characterisation of senescence

Senescence is a widely appreciated tumour suppressive mechanism, which acts as a barrier to cancer development by arresting cell cycle progression in response to harmful stimuli. However, senescent cell accumulation becomes deleterious in aging and contributes to a wide range of age-related pathologies. Furthermore, senescence has beneficial roles and is associated with a growing list of normal physiological processes including wound healing and embryonic development. Therefore, the biological role of senescent cells has become increasingly nuanced and complex. The emergence of sophisticated, next-generation profiling technologies, such as single-cell RNA sequencing, has accelerated our understanding of the heterogeneity of senescence, with distinct final cell states emerging within models as well as between cell types and tissues. In order to explore data sets of increasing size and complexity, the senescence field has begun to employ machine learning (ML) methodologies to probe these intricacies. Most notably, ML has been used to aid the classification of cells as senescent, as well as to characterise the final senescence phenotypes. Here, we provide a background to the principles of ML tasks, as well as some of the most commonly used methodologies from both traditional and deep ML. We focus on the application of these within the context of senescence research, by addressing the utility of ML for the analysis of data from different laboratory technologies (microscopy, transcriptomics, proteomics, methylomics), as well as the potential within senolytic drug discovery. Together, we aim to highlight both the progress and potential for the application of ML within senescence research.

Getting the chronological age out of DNA: using insights of age-dependent DNA methylation for forensic DNA applications

BACKGROUND

DNA analysis for forensic investigations has a long tradition with important developments and optimizations since its first application. Traditionally, short tandem repeats analysis has been the most powerful method for the identification of individuals. However, in addition, epigenetic changes, i.e., DNA methylation, came into focus of forensic DNA research. Chronological age prediction is one promising application to allow for narrowing the pool of possible individuals who caused a trace, as well as to support the identification of unknown bodies and for age verification of living individuals.

OBJECTIVE

This review aims to provide an overview of the current knowledge, possibilities, and (current) limitations about DNA methylation-based chronological age prediction with emphasis on forensic application.

METHODS

The development, implementation and application of age prediction tools requires a deep understanding about the biological background, the analysis methods, the age-dependent DNA methylation markers, as well as the mathematical models for age prediction and their evaluation. Furthermore, additional influences can have an impact. Therefore, the literature was evaluated in respect to these diverse topics.

CONCLUSION

The numerous research efforts in recent years have led to a rapid change in our understanding of the application of DNA methylation for chronological age prediction, which is now on the way to implementation and validation. Knowledge of the various aspects leads to a better understanding and allows a more informed interpretation of DNAm quantification results, as well as the obtained results by the age prediction tools.

Development of a model for the prediction of biological age

BACKGROUND AND OBJECTIVE

Rates of aging vary markedly among individuals, and biological age serves as a more reliable predictor of current health status than does chronological age. As such, the ability to predict biological age can support appropriate and timely active interventions aimed at improving coping with the aging process. However, the aging process is highly complex and multifactorial. Therefore, it is more scientific to construct a prediction model for biological age from multiple dimensions systematically.

METHODS

Physiological and biochemical parameters were evaluated to gage individual health status. Then, age-related indices were screened for inclusion in a model capable of predicting biological age. For subsequent modeling analyses, samples were divided into training and validation sets for subsequent deep learning model-based analyses (e.g. linear regression, lasso model, ridge regression, bayesian ridge regression, elasticity network, k-nearest neighbor, linear support vector machine, support vector machine, and decision tree models, and so on), with the model exhibiting the best ability to predict biological age thereby being identified.

RESULTS

First, we defined the individual biological age according to the individual health status. Then, after 22 candidate indices (DNA methylation, leukocyte telomere length, and specific physiological and biochemical indicators) were screened for inclusion in a model capable of predicting biological age, 14 age-related indices and gender were used to construct a model via the Bagged Trees method, which was found to be the most reliable qualitative prediction model for biological age (accuracy=75.6%, AUC=0.84) by comparing 30 different classification algorithm models. The most reliable quantitative predictive model for biological age was found to be the model developed using the Rational Quadratic method (R2=0.85, RMSE=8.731 years) by comparing 24 regression algorithm models.

CONCLUSIONS

Both qualitative model and quantitative model of biological age were successfully constructed from a multi-dimensional and systematic perspective. The predictive performance of our models was similar in both smaller and larger datasets, making it well-suited to predicting a given individual's biological age.

Effect of women's fertility and sexual development on epigenetic clock: Mendelian randomization study

BACKGROUND AND OBJECTIVES

In observational studies, women's fertility and sexual development traits may have implications for DNA methylation patterns, and pregnancy-related risk factors can also affect maternal DNA methylation patterns. The aim of our study is to disentangle any potential causal associations between women's fertility and sexual development traits and epigenetic clocks, as well as to search for probable mediators by using the Mendelian randomization (MR) method.

METHODS

Instrumental variables for exposures, mediators, and outcomes were adopted from genome-wide association studies data of European ancestry individuals. The potential causal relationship between women's fertility and sexual development traits and four epigenetic clocks were evaluated by inverse variance weighted method and verified by other two methods. Furthermore, we employed multivariable MR (MVMR) adjusting for hypertension, hyperglycemia, BMI changes, and insomnia. Then, combining the MVMR results and previous research, we performed two-step MR to explore the mediating effects of BMI, AFS, and AFB. Multiple sensitivity analyses were further performed to verify the robustness of our findings.

RESULTS

Leveraging two-sample MR analysis, we observed statistically significant associations between earlier age at first birth (AFB) with a higher HannumAge, PhenoAge and GrimAge acceleration(β = - 0.429, 95% CI [- 0.781 to - 0.077], p = 0.017 for HannumAge; β = - 0.571, 95% CI [- 1.006 to - 0.136], p = 0.010 for PhenoAge, and β = - 1.136, 95% CI [- 1.508 to - 0.765], p = 2.03E-09 for GrimAge respectively) and age at first sexual intercourse (AFS) with a higher HannumAge and GrimAge acceleration(β = - 0.175, 95% CI [- 0.336 to - 0.014], p = 0.033 for HannumAge; β = - 0.210, 95% CI [- 0.350 to - 0.070], p = 0.003 for GrimAge, respectively). Further analyses indicated that BMI, AFB and AFS played mediator roles in the path from women's fertility and sexual development traits to epigenetic aging.

CONCLUSIONS

Our study suggested that AFS and AFB are associated with epigenetic aging. These findings may prove valuable in informing the development of prevention strategies and interventions targeted towards women's fertility and sexual development experiences and their relationship with epigenetic aging-related diseases.