Universal DNA methylation age across mammalian tissues

Dnmt3a overexpression disrupts skeletal muscle homeostasis, promotes an aging-like phenotype, and reduces metabolic elasticity

Mammalian aging is reportedly driven by the loss of epigenetic information; however, its impact on skeletal muscle aging remains unclear. This study shows that aging mouse skeletal muscle exhibits increased DNA methylation, and overexpression of DNA methyltransferase 3a (Dnmt3a) induces an aging-like phenotype. Muscle-specific Dnmt3a overexpression leads to an increase in central nucleus-positive myofibers, predominantly in fast-twitch fibers, a shift toward slow-twitch fibers, elevated inflammatory and senescence markers, mitochondrial OXPHOS complex I reduction, and decreased basal autophagy. Dnmt3a overexpression resulted in reduced muscle mass and strength and impaired endurance exercise capacity with age, accompanied by an enhanced inflammatory signature. In addition, Dnmt3a overexpression reduced not only sensitivity to starvation-induced muscle atrophy but also the restorability from muscle atrophy. These findings suggest that increased DNA methylation disrupts skeletal muscle homeostasis, promotes an aging-like phenotype, and reduces muscle metabolic elasticity.

Promoting health and survival through lowered body temperature

Core body temperature (Tb) is a long-established determinant of longevity across species. In this Perspective, we first summarize evidence demonstrating that reducing Tb increases lifespan and that lowered Tb contributes to the antiaging effects of calorie restriction. Next, we discuss recent data that diverge from prior hypotheses on the mechanisms by which Tb affects longevity, suggesting these are limited neither to the thermodynamics of nonenzymatic chemical reactions, nor reduced formation of mitochondrial reactive oxygen species nor lowered metabolic rate. Instead, recent findings in invertebrates show that cold promotes longevity via specific pathways including nutrient sensing and proteostasis, as well as modulating the thermodynamics of proteins and nucleic acids by changing their structure and function, for example, affecting temperature-sensitive ion channels, long-lived temperature-sensitive dauer mutations, base-pair stability and stem-loop RNA structures. Temperature affects the epigenetic signature and inflammation, and lowering Tb can also induce RNA-binding cold shock proteins, activate cold-sensitive kinases and differential splicing to potentially reshape the cellular environment. Finally, we reflect on important future work and the translational potential of temperature management and temperature mimetics.

Evaluating transcriptional alterations associated with ageing and developing age prediction models based on the human blood transcriptome

Ageing-related DNA methylome and proteome changes and machine-learned ageing clock models have been described previously; however, there is a dearth of ageing clock prediction models based on human blood transcript information. Applying various machine learning algorithms is expected to aid in the development of age prediction models. Using blood transcriptome data from healthy subjects ranging in age from 21 to 90 in the 10 K Immunomes repository, we evaluated differentially regulated transcripts, assessed enriched gene ontology, pathway and disease ontology analysis to characterize biological functions associated with the genes associated with age. Furthermore, we constructed and compared age prediction models developed by applying the Least Absolute Shrinkage and Selection Operator (LASSO), Elastic Net (EN), eXtreme Gradient Boosting (XGBoost) and Light Gradient-Boosting Machine (LightGBM) algorithms. Compared to LASSO (7 genes) and EN (9 genes) regularized regression, XGBoost (142 genes) and LightGBM (149 genes) Gradient Boosted Decision Tree methods performed better in this dataset (training set r = 0.836 (LASSO), 0.837 (EN), 1.000 (XGBoost) and 0.995 (LightGBM); test set: r = 0.883 (LASSO), 0.876 (EN), 0.931 (XGBoost) and 0.915 (LightGBM); external validation set: r = 0.535 (LASSO), 0.534 (EN), 0.591 (XGBoost) and 0.645 (LightGBM)). Blood transcriptome-based age prediction models may provide a simple method to monitor biological ageing, and provide additional molecular insight. Future studies to externally validate these models in various diverse large populations and molecular studies to elucidate the underlying mechanisms by which the gene expression levels may be related to ageing phenotypes would be advantageous.

Quantification of Epigenetic Aging in Public Health

Estimators of biological age hold promise for use in preventive medicine, for early detection of chronic conditions, and for monitoring the effectiveness of interventions aimed at improving population health. Among the promising biomarkers in this field are DNA methylation-based biomarkers, commonly referred to as epigenetic clocks. This review provides a survey of these clocks, with an emphasis on second-generation clocks that predict human morbidity and mortality. It explores the validity of epigenetic clocks when considering factors such as race, sex differences, lifestyle, and environmental influences. Furthermore, the review addresses the current challenges and limitations in this research area.

Conserved biological processes in partial cellular reprogramming: Relevance to aging and rejuvenation

Partial or transient cellular reprogramming is defined by the limited induction of pluripotency factors without full dedifferentiation of cells to a pluripotent state. Comparing in vitro and in vivo mouse studies, and in vitro studies in humans, supported by visualizations of data interconnections, we show consistent patterns in how such reprogramming modulates key biological processes. Generally, partial reprogramming drives dynamic chromatin remodelling, involving histone modifications that regulate accessibility and facilitate pluripotency gene activation while silencing somatic identity. These changes are accompanied by modifications in stress response programs, such as inflammation, autophagy, and cellular senescence, as well as improved mitochondrial activity and dysregulation of extracellular matrix pathways. We also underscore the challenges in evaluating complex processes like aging and cellular senescence, given the variability in biomarkers used across studies. Overall, we highlight biological processes consistently influenced by reprogramming while noting that some effects are context-dependent, varying according to cell type, species, sex, recovery time, and the reprogramming method employed. These insights inform future research and potential therapeutic applications in aging and regenerative medicine.

Selection for early reproduction leads to accelerated aging and extensive metabolic remodeling in Drosophila melanogaster

Experimental evolution studies that feature selection on life-history characters are a proven approach for studying the evolution of aging and variation in rates of senescence. Recently, the incorporation of genomic and transcriptomic approaches into this framework has led to the identification of hundreds of genes associated with different aging patterns. However, our understanding of the specific molecular mechanisms underlying these aging patterns remains limited. Here, we incorporated extensive metabolomic profiling into this framework to generate mechanistic insights into aging patterns in Drosophila melanogaster . Specifically, we characterized metabolomic change over adult lifespan in populations of D. melanogaster where selection for early reproduction has led to an accelerated aging phenotype relative to their controls. Using these data we: i) evaluated evolutionary repeatability across the metabolome; ii) assessed the value of the metabolome as a predictor of "biological age" in this system; and iii) identified specific metabolites associated with accelerated aging. Generally, our findings suggest that selection for early reproduction resulted in highly repeatable alterations to the metabolome and the metabolome itself is a reliable predictor of "biological age". Specifically, we find clusters of metabolites that are associated with the different rates of senescence observed between our accelerated aging population and their controls, adding new insights into the metabolites that may be driving the accelerated aging phenotype.

Significance

While experimental evolution studies featuring Drosophila melanogaster have generated significant insights into the forces that shape aging and life history patterns, more recent efforts incorporating genomic and transcriptomic data have had comparatively little success identifying the molecular mechanisms underlying these patterns. Here we work to incorporate molecular phenotyping into this general framework as a way forward. Specifically, we characterize how the metabolome changes with age in populations of D. melanogaster where hundreds of generations of selection for early reproduction have led to enrichment for an accelerated aging phenotype. By comparing to control populations, we show that the metabolome does appear to capture true signals of "biological age" and provides a new avenue for understanding the factors that underlie complex trait variation in real populations.

The complex interplay between aging and cancer

Cancer is an age-related disease, but the interplay between cancer and aging is complex and their shared molecular drivers are deeply intertwined. This Review provides an overview of how different biological pathways affect cancer and aging, leveraging evidence mainly derived from animal studies. We discuss how genome maintenance and accumulation of DNA mutations affect tumorigenesis and tissue homeostasis during aging. We describe how age-related telomere dysfunction and cellular senescence intricately modulate tumor development through mechanisms involving genomic instability and inflammation. We examine how an aged immune system and chronic inflammation shape tumor immunosurveillance, fueling DNA damage and cellular senescence. Finally, as animal models are important to untangling the relative contributions of these aging-modulated pathways to cancer progression and to test interventions, we discuss some of the limitations of physiological and accelerated aging models, aiming to improve experimental designs and enhance translation.

A torpor-like state in mice slows blood epigenetic aging and prolongs healthspan

Torpor and hibernation are extreme physiological adaptations of homeotherms associated with pro-longevity effects. Yet the underlying mechanisms of how torpor affects aging, and whether hypothermic and hypometabolic states can be induced to slow aging and increase healthspan, remain unknown. Here we demonstrate that the activity of a spatially defined neuronal population in the preoptic area, which has previously been identified as a torpor-regulating brain region, is sufficient to induce a torpor-like state (TLS) in mice. Prolonged induction of TLS slows epigenetic aging across multiple tissues and improves healthspan. We isolate the effects of decreased metabolic rate, long-term caloric restriction, and decreased core body temperature (Tb) on blood epigenetic aging and find that the decelerating effect of TLSs on aging is mediated by decreased Tb. Taken together, our findings provide novel mechanistic insight into the decelerating effects of torpor and hibernation on aging and support the growing body of evidence that Tb is an important mediator of the aging processes.

Update of Aging Hallmarks in Idiopathic Pulmonary Fibrosis

Idiopathic Pulmonary Fibrosis (IPF) is an epithelial-driven interstitial lung disease of unknown etiology characterized by the excessive proliferation of fibroblast populations that synthesize large amounts of extracellular matrix. In this devastating disorder, all aging hallmarks appear prematurely or are altered. This review highlights key findings about IPF characteristics recently recognized as hallmarks of aging, including mechanical alterations, inflammaging, dysbiosis, alternative splicing, and disabled macroautophagy. It also revisits the classic hallmarks of aging, which encompass stem cell exhaustion, cellular senescence, and altered intercellular communication. Enhancing our understanding of the fundamental processes that underlie the altered hallmarks of aging in IPF may facilitate the development of innovative experimental strategies to improve therapeutic outcomes.

Enhancing epigenetic aging clocks in cetaceans: accurate age estimations in small endangered delphinids, killer whales, pilot whales, belugas, humpbacks, and bowhead whales

This study presents refined epigenetic clocks for cetaceans, building on previous research that estimated ages in several species from bottlenose dolphins to bowhead and humpback whales using cytosine methylation levels. We combined publicly available data (generated on the HorvathMammalMethylChip40 platform) from skin (n = 805) and blood (n = 286) samples across 13 cetacean species, aged 0 to 139 years. By combining methylation data from different sources, we enhanced our sample size, thereby strengthening the statistical validity of our clocks. We used elastic net regression with leave one sample out (LOO) and leave one species out (LOSO) cross validation to produce highly accurate blood only (Median Absolute Error [MAE] = 1.64 years, r = 0.96), skin only (MAE = 2.32 years, r = 0.94) and blood and skin multi-tissue (MAE = 2.24 years, r = 0.94) clocks. In addition, the LOSO blood and skin (MAE = 5.6 years, repeated measures r = 0.83), skin only (MAE = 6.22 years, repeated measures r = 0.81), and blood only (MAE = 4.11 years, repeated measures r = 0.95) clock analysis demonstrated relatively high correlation toward cetacean species not included within this current data set and provide evidence for a broader application of this model. Our results introduce a multi-species, two-tissue clock for broader applicability across cetaceans, alongside single-tissue multi-species clocks for blood and skin, which allow for more detailed aging analysis depending on the availability of samples. In addition, we developed species-specific clocks for enhanced precision, resulting in four blood-specific clocks and eight skin-specific clocks for individual species; all improving upon existing accuracy estimates for previously published species-specific clocks. By pooling methylation data from various studies, we increased our sample size, significantly enhancing the statistical power for building accurate clocks. These new epigenetic age estimators for cetaceans provide more accurate tools for aiding in conservation efforts of endangered cetaceans.

Cognitive rejuvenation in old rats by hippocampal OSKM gene therapy

Several studies have indicated that interrupted epigenetic reprogramming using Yamanaka transcription factors (OSKM) can rejuvenate cells from old laboratory animals and humans. However, the potential of OSKM-induced rejuvenation in brain tissue has been less explored. Here, we aimed to restore cognitive performance in 25.3-month-old female Sprague-Dawley rats using OSKM gene therapy for 39 days. Their progress was then compared with the cognitive performance of untreated 3.5-month-old rats as well as old control rats treated with a placebo adenovector. The Barnes maze test, used to assess cognitive performance, demonstrated enhanced cognitive abilities in old rats treated with OSKM compared to old control animals. In the treated old rats, there was a noticeable trend towards improved spatial memory relative to the old controls. Further, OSKM gene expression did not lead to any pathological alterations within the 39 days. Analysis of DNA methylation following OSKM treatment yielded three insights. First, epigenetic clocks for rats suggested a marginally significant epigenetic rejuvenation. Second, chromatin state analysis revealed that OSKM treatment rejuvenated the methylome of the hippocampus. Third, an epigenome-wide association analysis indicated that OSKM expression in the hippocampus of old rats partially reversed the age-related increase in methylation. In summary, the administration of Yamanaka genes via viral vectors rejuvenates the functional capabilities and the epigenetic landscape of the rat hippocampus.

Hallmarks of aging: A user's guide for comparative biologists

Since the first description of a set of characteristics of aging as so-called hallmarks or pillars in 2013/2014, these characteristics have served as guideposts for the research in aging biology. They have been examined in a range of contexts, across tissues, in response to disease conditions or environmental factors, and served as a benchmark for various anti-aging interventions. While the hallmarks of aging were intended to capture generalizable characteristics of aging, they are derived mostly from studies of rodents and humans. Comparative studies of aging including species from across the animal tree of life have great promise to reveal new insights into the mechanistic foundations of aging, as there is a great diversity in lifespan and age-associated physiological changes. However, it is unclear how well the defined hallmarks of aging apply across diverse species. Here, we review each of the twelve hallmarks of aging defined by Lopez-Otin in 2023 with respect to the availability of data from diverse species. We evaluate the current methods used to assess these hallmarks for their potential to be adapted for comparative studies. Not unexpectedly, we find that the data supporting the described hallmarks of aging are restricted mostly to humans and a few model systems and that no data are available for many animal clades. Similarly, not all hallmarks can be easily assessed in diverse species. However, for at least half of the hallmarks, there are methods available today that can be employed to fill this gap in knowledge, suggesting that these studies can be prioritized while methods are developed for comparative study of the remaining hallmarks.

Environmental DNA Epigenetics Accurately Predicts the Age of Cultured Fish Larvae

While acquiring age information is crucial for efficient stock management and biodiversity conservation, traditional aging methods fail to offer a universal, non-invasive, and precise way of estimating a wild animal's age. DNA methylation from tissue DNA (tDNA) was recently proposed as a method to overcome these issues and showed more accurate results than telomere-length-based age assessments. Here, we used environmental DNA (eDNA) for the first time as a template for age estimation, focusing on the larval phase (10-24 days post-hatch) of cultured Dicentrarchus labrax (seabass), a species of major economic and conservation interest. Using third-generation sequencing, we were able to directly detect various modification types (e.g., cytosine and adenosine methylation in all contexts) across the whole genome using amplification-free nanopore sequencing. However, aging sites were only present in the mitogenome, which could be a specific feature of eDNA methylation or the consequence of better DNA protection within mitochondria. By considering qualitative and quantitative information about aging sites according to an objective model selection framework, our epigenetic clock reached a cross-validated accuracy of 2.6 days (Median Absolute Error). Such performances are higher than those of previous clocks, notably for adult seabass even when scaling MAE to the age range, which could be linked to a more dynamic epigenome during early life stages. Overall, our pilot study proposes new methods to determine the potential of eDNA for simultaneous age and biodiversity assessments, although robust validation of our preliminary results along with methodological developments are needed before field applications can be envisaged.

Comparative Genomics and Epigenomics of Transcriptional Regulation

Transcriptional regulation in response to diverse physiological cues involves complicated biological processes. Recent initiatives that leverage whole genome sequencing and annotation of regulatory elements significantly contribute to our understanding of transcriptional gene regulation. Advances in the data sets available for comparative genomics and epigenomics can identify evolutionarily constrained regulatory variants and shed light on noncoding elements that influence transcription in different tissues and developmental stages across species. Most epigenomic data, however, are generated from healthy subjects at specific developmental stages. To bridge the genotype-phenotype gap, future research should focus on generating multidimensional epigenomic data under diverse physiological conditions. Farm animal species offer advantages in terms of feasibility, cost, and experimental design for such integrative analyses in comparison to humans. Deep learning modeling and cutting-edge technologies in sequencing and functional screening and validation also provide great promise for better understanding transcriptional regulation in this dynamic field.

Involvement of TGF-β, mTOR, and inflammatory mediators in aging alterations during myxomatous mitral valve disease in a canine model

Inflammaging, a state of chronic low-grade inflammation associated with aging, has been linked to the development and progression of various disorders. Cellular senescence, a state of irreversible growth arrest, is another characteristic of aging that contributes to the pathogenesis of cardiovascular pathology. Senescent cells accumulate in tissues over time and secrete many inflammatory mediators, further exacerbating the inflammatory environment. This senescence-associated secretory phenotype can promote tissue dysfunction and remodeling, ultimately leading to the development of age-related cardiovascular pathologies, such as mitral valve myxomatous degeneration. The species-specific form of canine myxomatous mitral valve disease (MMVD) provides a unique opportunity to investigate the early causes of induction of ECM remodeling in mitral valve leaflets in the human form of MMVD. Studies have shown that in both humans and dogs, the microenvironment of the altered leaflets is inflammatory. More recently, the focus has been on the mechanisms leading to the transformation of resting VICs (qVICs) to myofibroblast-like VICs (aVICs). Cells affected by stress fall into a state of cell cycle arrest and become senescent cells. aVICs, under the influence of TGF-β signaling pathways and the mTOR complex, enhance ECM alteration and accumulation of systemic inflammation. This review aims to create a fresh new view of the complex interaction between aging, inflammation, immunosenescence, and MMVD in a canine model, as the domestic dog is a promising model of human aging and age-related diseases.

TimeFlies: an snRNA-seq aging clock for the fruit fly head sheds light on sex-biased aging

Although multiple high-performing epigenetic aging clocks exist, few are based directly on gene expression. Such transcriptomic aging clocks allow us to extract age-associated genes directly. However, most existing transcriptomic clocks model a subset of genes and are limited in their ability to predict novel biomarkers. With the growing popularity of single-cell sequencing, there is a need for robust single-cell transcriptomic aging clocks. Moreover, clocks have yet to be applied to investigate the elusive phenomenon of sex differences in aging. We introduce TimeFlies, a pan-cell-type scRNA-seq aging clock for the Drosophila melanogaster head. TimeFlies uses deep learning to classify the donor age of cells based on genome-wide gene expression profiles. Using explainability methods, we identified key marker genes contributing to the classification, with lncRNAs showing up as highly enriched among predicted biomarkers. The top biomarker gene across cell types is lncRNA:roX1, a regulator of X chromosome dosage compensation, a pathway previously identified as a top biomarker of aging in the mouse brain. We validated this finding experimentally, showing a decrease in survival probability in the absence of roX1 in vivo. Furthermore, we trained sex-specific TimeFlies clocks and noted significant differences in model predictions and explanations between male and female clocks, suggesting that different pathways drive aging in males and females.

Precise and interpretable neural networks reveal epigenetic signatures of aging across youth in health and disease

Introduction

DNA methylation (DNAm) age clocks are powerful tools for measuring biological age, providing insights into aging risks and outcomes beyond chronological age. While traditional models are effective, their interpretability is limited by their dependence on small and potentially stochastic sets of CpG sites. Here, we propose that the reliability of DNAm age clocks should stem from their capacity to detect comprehensive and targeted aging signatures.

Methods

We compiled publicly available DNAm whole-blood samples (n = 17,726) comprising the entire human lifespan (0-112 years). We used a pre-trained network-coherent autoencoder (NCAE) to compress DNAm data into embeddings, with which we trained interpretable neural network epigenetic clocks. We then retrieved their age-specific epigenetic signatures of aging and examined their functional enrichments in age-associated biological processes.

Results

We introduce NCAE-CombClock, a novel highly precise (R2 = 0.978, mean absolute error = 1.96 years) deep neural network age clock integrating data-driven DNAm embeddings and established CpG age markers. Additionally, we developed a suite of interpretable NCAE-Age neural network classifiers tailored for adolescence and young adulthood. These clocks can accurately classify individuals at critical developmental ages in youth (AUROC = 0.953, 0.972, and 0.927, for 15, 18, and 21 years) and capture fine-grained, single-year DNAm signatures of aging that are enriched in biological processes associated with anatomic and neuronal development, immunoregulation, and metabolism. We showcased the practical applicability of this approach by identifying candidate mechanisms underlying the altered pace of aging observed in pediatric Crohn's disease.

Discussion

In this study, we present a deep neural network epigenetic clock, named NCAE-CombClock, that improves age prediction accuracy in large datasets, and a suite of explainable neural network clocks for robust age classification across youth. Our models offer broad applications in personalized medicine and aging research, providing a valuable resource for interpreting aging trajectories in health and disease.

The androgen clock is an epigenetic predictor of long-term male hormone exposure

Aging is a complex process characterized by biological decline and a wide range of molecular alterations to cells, including changes to DNA methylation. In this study, we used a male-specific epigenetic marker of aging to build an epigenetic predictor that measures long-term androgen exposure in sheep and mice (median absolute error of 4.3 and 1.4 mo, respectively). We term this predictor the androgen clock and show its "tick" is mediated by the androgen receptor and can be accelerated beyond that in normal male mice by supplementing females with dihydrotestosterone. Conversely, the removal of androgens by castration in sheep completely halted the androgen clock. In addition to potential applications in medicine and agriculture, we predict the androgen clock will prove a useful model to understand the mechanisms and processes of age-associated DNA methylation change because it can be precisely enhanced and halted using small molecule manipulation with few additional effects on the cell.

estiMAge: development of a DNA methylation clock to estimate the methylation age of single cells

Motivation

Since their introduction about 10 years ago, methylation clocks have provided broad insights into the biological age of different species, tissues, and in the context of several diseases or aging. However, their application to single-cell methylation data remains a major challenge, because of the inherent sparsity of such data, as many CpG sites are not covered. A methylation clock applicable on single-cell level could help to further disentangle the processes that drive the ticking of epigenetic clocks.

Results

We have developed estiMAge ("estimation of Methylation Age"), a framework that exploits redundancy in methylation data to substitute missing CpGs of trained methylation clocks in single cells. Using Euclidean distance as a measure of similarity, we determine which CpGs covary with the required CpG sites of an epigenetic clock and can be used as surrogates for clock CpGs not covered in single-cell experiments. estiMAge is thus a tool that can be applied to standard epigenetic clocks built on elastic net regression, to achieve bulk and single-cell resolution. We show that estiMAge can accurately predict the ages of young and old hepatocytes and can be used to generate single-cell versions of publicly available epigenetic clocks.

Availability and implementation

The source code and instructions for usage of estiMAge are available at https://github.com/DivEpigenetics/estiMAge.

Epigenetic ageing clocks: statistical methods and emerging computational challenges

Over the past decade, epigenetic clocks have emerged as powerful machine learning tools, not only to estimate chronological and biological age but also to assess the efficacy of anti-ageing, cellular rejuvenation and disease-preventive interventions. However, many computational and statistical challenges remain that limit our understanding, interpretation and application of epigenetic clocks. Here, we review these computational challenges, focusing on interpretation, cell-type heterogeneity and emerging single-cell methods, aiming to provide guidelines for the rigorous construction of interpretable epigenetic clocks at cell-type and single-cell resolution.

Somatic mutation as an explanation for epigenetic aging

DNA methylation marks have recently been used to build models known as epigenetic clocks, which predict calendar age. As methylation of cytosine promotes C-to-T mutations, we hypothesized that the methylation changes observed with age should reflect the accrual of somatic mutations, and the two should yield analogous aging estimates. In an analysis of multimodal data from 9,331 human individuals, we found that CpG mutations indeed coincide with changes in methylation, not only at the mutated site but with pervasive remodeling of the methylome out to ±10 kilobases. This one-to-many mapping allows mutation-based predictions of age that agree with epigenetic clocks, including which individuals are aging more rapidly or slowly than expected. Moreover, genomic loci where mutations accumulate with age also tend to have methylation patterns that are especially predictive of age. These results suggest a close coupling between the accumulation of sporadic somatic mutations and the widespread changes in methylation observed over the course of life.

DNA methylation of transposons pattern aging differences across a diverse cohort of dogs from the Dog Aging Project

Within a species, larger individuals often have shorter lives and higher rates of age-related disease. Despite this well-known link, we still know little about underlying age-related epigenetic differences, which could help us better understand inter-individual variation in aging and the etiology, onset, and progression of age-associated disease. Dogs exhibit this negative correlation between size, health, and longevity and thus represent an excellent system in which to test the underlying mechanisms. Here, we quantified genome-wide DNA methylation in a cohort of 864 dogs in the Dog Aging Project. Age strongly patterned the dog epigenome, with the majority (66% of age-associated loci) of regions associating age-related loss of methylation. These age effects were non-randomly distributed in the genome and differed depending on genomic context. We found the LINE1 (long interspersed elements) class of TEs (transposable elements) were the most frequently hypomethylated with age (FDR < 0.05, 40% of all LINE1 regions). This LINE1 pattern differed in magnitude across breeds of different sizes- the largest dogs lost 0.26% more LINE1 methylation per year than the smallest dogs. This suggests that epigenetic regulation of TEs, particularly LINE1s, may contribute to accelerated age and disease phenotypes within a species. Since our study focused on the methylome of immune cells, we looked at LINE1 methylation changes in golden retrievers, a breed highly susceptible to hematopoietic cancers, and found they have accelerated age-related LINE1 hypomethylation compared to other breeds. We also found many of the LINE1s hypomethylated with age are located on the X chromosome and are, when considering X chromosome inactivation, counter-intuitively more methylated in males. These results have revealed the demethylation of LINE1 transposons as a potential driver of intra-species, demographic-dependent aging variation.

Epigenetics and individuality: from concepts to causality across timescales

Traditionally, differences among individuals have been divided into genetic and environmental causes. However, both types of variation can underlie regulatory changes in gene expression - that is, epigenetic changes - that persist across cell divisions (developmental differentiation) and even across generations (transgenerational inheritance). Increasingly, epigenetic variation among individuals is recognized as an important factor in human diseases and ageing. Moreover, non-genetic inheritance can lead to evolutionary changes within populations that differ from those expected by genetic inheritance alone. Despite its importance, causally linking epigenetic variation to phenotypic differences across individuals has proven difficult, particularly when epigenetic variation operates independently of genetic variation. New genomic approaches are providing unprecedented opportunity to measure and perturb epigenetic variation, helping to elucidate the role of epigenetic variation in mediating the genotype-phenotype map. Here, we review studies that have advanced our understanding of how epigenetic variation contributes to phenotypic differences between individuals within and across generations, and provide a unifying framework that allows historical and mechanistic perspectives to more fully inform one another.

Comprehensive whole-genome sequencing reveals origins of mutational signatures associated with aging, mismatch repair deficiency and temozolomide chemotherapy

In a comprehensive study to decipher the multi-layered response to the chemotherapeutic agent temozolomide (TMZ), we analyzed 427 genomes and determined mutational patterns in a collection of ∼40 isogenic DNA repair-deficient human TK6 lymphoblast cell lines. We first demonstrate that the spontaneous mutational background is very similar to the aging-associated mutational signature SBS40 and mainly caused by polymerase zeta-mediated translesion synthesis (TLS). MSH2-/- mismatch repair (MMR) knockout in conjunction with additional repair deficiencies uncovers cryptic mutational patterns. We next report how distinct mutational signatures are induced by TMZ upon sequential inactivation of DNA repair pathways, mirroring the acquisition of chemotherapy resistance by glioblastomas. The most toxic adduct induced by TMZ, O6-meG, is directly repaired by the O6-methylguanine-DNA methyltransferase (MGMT). In MGMT-/- cells, MMR leads to cell death and limits mutagenesis. MMR deficiency results in TMZ resistance, allowing the accumulation of ∼105 C > T substitutions corresponding to signature SBS11. Under these conditions, N3-methyladenine (3-meA), processed by base excision repair (BER), limits cell survival. Without BER, 3-meA is read through via error-prone TLS, causing T > A substitutions but not affecting survival. Blocking BER after abasic site formation results in large deletions and TMZ hypersensitization. Our findings reveal potential vulnerabilities of TMZ-resistant tumors.

Decoding aging clocks: New insights from metabolomics

Chronological age is a crucial risk factor for diseases and disabilities among older adults. However, individuals of the same chronological age often exhibit divergent biological aging states, resulting in distinct individual risk profiles. Chronological age estimators based on omics data and machine learning techniques, known as aging clocks, provide a valuable framework for interpreting molecular-level biological aging. Metabolomics is an intriguing and rapidly growing field of study, involving the comprehensive profiling of small molecules within the body and providing the ultimate genome-environment interaction readout. Consequently, leveraging metabolomics to characterize biological aging holds immense potential. The aim of this review was to provide an overview of metabolomics approaches, highlighting the establishment and interpretation of metabolomic aging clocks while emphasizing their strengths, limitations, and applications, and to discuss their underlying biological significance, which has the potential to drive innovation in longevity research and development.

Histone mark age of human tissues and cell types

Aging is a complex and multifaceted process involving many epigenetic alterations. One key area of interest in aging research is the role of histone modifications, which can dynamically regulate gene expression. Here, we conducted a pan-tissue analysis of the dynamics of seven key histone modifications during human aging. Our histone-specific age prediction models showed surprisingly accurate performance, proving resilient to experimental and artificial noise. Simulation experiments for comparison with DNA methylation age predictors revealed competitive performance. Moreover, gene set enrichment analysis uncovered several critical developmental pathways for age prediction. Different from DNA methylation age predictors, genes known to be involved in aging biology are among the most important ones for the models. Last, we developed a pan-tissue pan-histone age predictor, suggesting that age-related epigenetic information is degenerated across the epigenome. This research highlights the power of histone marks as input for creating robust age predictors and opens avenues for understanding the role of epigenetic changes during aging.

Insights to aging prediction with AI based epigenetic clocks

Over the past century, human lifespan has increased remarkably, yet the inevitability of aging persists. The disparity between biological age, which reflects pathological deterioration and disease, and chronological age, indicative of normal aging, has driven prior research focused on identifying mechanisms that could inform interventions to reverse excessive age-related deterioration and reduce morbidity and mortality. DNA methylation has emerged as an important predictor of age, leading to the development of epigenetic clocks that quantify the extent of pathological deterioration beyond what is typically expected for a given age. Machine learning technologies offer promising avenues to enhance our understanding of the biological mechanisms governing aging by further elucidating the gap between biological and chronological ages. This perspective article examines current algorithmic approaches to epigenetic clocks, explores the use of machine learning for age estimation from DNA methylation, and discusses how refining the interpretation of ML methods and tailoring their inferences for specific patient populations and cell types can amplify the utility of these technologies in age prediction. By harnessing insights from machine learning, we are well-positioned to effectively adapt, customize and personalize interventions aimed at aging.

On correlative and causal links of replicative epimutations

The mitotic inheritability of DNA methylation as an epigenetic marker in higher-order eukaryotes has been established for >40 years. The DNA methylome and mitotic division interplay is now considered bidirectional and highly intertwined. Various epigenetic writers, erasers, and modulators shape the perceived replicative methylation dynamics. This Review surveys the principles and complexity of mitotic transmission of DNA methylation, emphasizing the awareness of mitotic aging in analyzing DNA methylation dynamics in development and disease. We reviewed how DNA methylation changes alter mitotic proliferation capacity, implicating age-related diseases like cancer. We link replicative epimutation to stem cell dysfunction, inflammatory response, cancer risks, and epigenetic clocks, discussing the causative role of DNA methylation in health and disease.

Epigenetic Clock: DNA Methylation as a Marker of Biological Age and Age-Associated Diseases

Age is one of the key criteria of human health used in practical medicine to predict the risk of common chronic diseases. However, biological age, which reflects the state of an individual organism, functional capabilities, social well-being, and risk of premature death from various causes, often does not coincide with chronological age. To determine biological age of a particular individuals and the rate of their aging, specific panels of DNA methylation markers called "epigenetic clock" (EC) were proposed. This review summarizes the data about the main types of ECs developed to date and their key characteristics. We described the results of works studying individual aging rates in common age-associated diseases and outlined main directions, development of which could expand application of ECs in fundamental and practical medicine. There is no doubt that revealing complex mechanisms underlying interaction between the rate of epigenetic aging and the risk of age-associated diseases could play a key role for prediction and early diagnosis, as well as for the development of preventive measures that could delay onset of the disease.

Basic Epigenetic Mechanisms

The human genome consists of 23 chromosome pairs (22 autosomes and one pair of sex chromosomes), with 46 chromosomes in a normal cell. In the interphase nucleus, the 2 m long nuclear DNA is assembled with proteins forming chromatin. The typical mammalian cell nucleus has a diameter between 5 and 15 μm in which the DNA is packaged into an assortment of chromatin assemblies. The human brain has over 3000 cell types, including neurons, glial cells, oligodendrocytes, microglial, and many others. Epigenetic processes are involved in directing the organization and function of the genome of each one of the 3000 brain cell types. We refer to epigenetics as the study of changes in gene function that do not involve changes in DNA sequence. These epigenetic processes include histone modifications, DNA modifications, nuclear RNA, and transcription factors. In the interphase nucleus, the nuclear DNA is organized into different structures that are permissive or a hindrance to gene expression. In this chapter, we will review the epigenetic mechanisms that give rise to cell type-specific gene expression patterns.

DNA methylation in mammalian development and disease

The DNA methylation field has matured from a phase of discovery and genomic characterization to one seeking deeper functional understanding of how this modification contributes to development, ageing and disease. In particular, the past decade has seen many exciting mechanistic discoveries that have substantially expanded our appreciation for how this generic, evolutionarily ancient modification can be incorporated into robust epigenetic codes. Here, we summarize the current understanding of the distinct DNA methylation landscapes that emerge over the mammalian lifespan and discuss how they interact with other regulatory layers to support diverse genomic functions. We then review the rising interest in alternative patterns found during senescence and the somatic transition to cancer. Alongside advancements in single-cell and long-read sequencing technologies, the collective insights made across these fields offer new opportunities to connect the biochemical and genetic features of DNA methylation to cell physiology, developmental potential and phenotype.

Human brain aging is associated with dysregulation of cell type epigenetic identity

Significant links between aging and DNA methylation are emerging from recent studies. On the one hand, DNA methylation undergoes changes with age, a process termed as epigenetic drift. On the other hand, DNA methylation serves as a readily accessible and accurate biomarker for aging. A key missing piece of information, however, is the molecular mechanisms underlying these processes and how they are related, if any. Addressing the limitations of previous research due to the limited number of investigated CpGs and the heterogeneous nature of tissue samples, here, we have examined DNA methylation of over 20 million CpGs across a broad age span in neurons and non-neuronal cells, primarily oligodendrocytes. We show that aging is a primary predictor of DNA methylation variation, surpassing the influence of factors such as sex and schizophrenia diagnosis, among others. On the genome-wide scale, epigenetic drift manifests as significant yet subtle trends that are influenced by the methylation level of individual CpGs. We reveal that CpGs that are highly differentiated between cell types are especially prone to age-associated DNA methylation alterations, leading to the divergence of epigenetic cell type identities as individuals age. On the other hand, CpGs that are included in commonly used epigenetic clocks tend to be those sites that are not highly cell type differentiated. Therefore, dysregulation of epigenetic cell type identities and current DNA epigenetic clocks represent distinct features of age-associated DNA methylation alterations.

Wild capuchin monkeys as a model system for investigating the social and ecological determinants of ageing

Studying biological ageing in animal models can circumvent some of the confounds exhibited by studies of human ageing. Ageing research in non-human primates has provided invaluable insights into human lifespan and healthspan. Yet data on patterns of ageing from wild primates remain relatively scarce, centred around a few populations of catarrhine species. Here, we introduce the white-faced capuchin, a long-lived platyrrhine primate, as a promising new model system for ageing research. Like humans, capuchins are highly social, omnivorous generalists, whose healthspan and lifespan relative to body size exceed that of other non-human primate model species. We review recent insights from capuchin ageing biology and outline our expanding, integrative research programme that combines metrics of the social and physical environments with physical, physiological and molecular hallmarks of ageing across the natural life courses of multiple longitudinally tracked individuals. By increasing the taxonomic breadth of well-studied primate ageing models, we generate new insights, increase the comparative value of existing datasets to geroscience and work towards the collective goal of developing accurate, non-invasive and reliable biomarkers with high potential for standardization across field sites and species, enhancing the translatability of primate studies.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.

Epigenetic Mechanisms in Aging: Extrinsic Factors and Gut Microbiome

BACKGROUND/OBJECTIVES

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

RESULTS

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

CONCLUSIONS

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

Modeling the consequences of age-linked rDNA hypermethylation with dCas9-directed DNA methylation in human cells

Ribosomal DNA (rDNA) genes encode the structural RNAs of the ribosome and are present in hundreds of copies in mammalian genomes. Age-linked DNA hypermethylation throughout the rDNA constitutes a robust "methylation clock" that accurately reports age, yet the consequences of hypermethylation on rDNA function are unknown. We confirmed that pervasive hypermethylation of rDNA occurs during mammalian aging and senescence while rDNA copy number remains stable. We found that DNA methylation is exclusively found on the promoters and gene bodies of inactive rDNA. To model the effects of age-linked methylation on rDNA function, we directed de novo DNA methylation to the rDNA promoter or gene body with a nuclease-dead Cas9 (dCas9)-DNA methyltransferase fusion enzyme in human cells. Hypermethylation at each target site had no detectable effect on rRNA transcription, nucleolar morphology, or cellular growth rate. Instead, human UBF and Pol I remain bound to rDNA promoters in the presence of increased DNA methylation. These data suggest that promoter methylation is not sufficient to impair transcription of the human rDNA and imply that the human rDNA transcription machinery may be resilient to age-linked rDNA hypermethylation.

Genetic origins, regulators, and biomarkers of cellular senescence

This review comprehensively examines the molecular biology and genetic origins of cellular senescence. We focus on various cellular stressors and pathways leading to senescence, including recent advances in the understanding of the genetic influences driving senescence, such as telomere attrition, chemotherapy-induced DNA damage, pathogens, oncogene activation, and cellular and metabolic stress. This review also highlights the complex interplay of various signaling and metabolic pathways involved in cellular senescence and provides insights into potential therapeutic targets for aging-related diseases. Furthermore, this review outlines future research directions to deepen our understanding of senescence biology and develop effective interventions targeting senescent cells (SnCs).

E5 treatment showing improved health-span and lifespan in old Sprague Dawley rats

Aging and, in particular, the emergence of age-related disorders is associated with tissue dysfunction and macromolecular damage, some of which can be attributable to accumulated oxidative damage. In the current study, we determine the potential of 'plasma-derived fraction (E5)' for cellular rejuvenation and extending the lifespan of Sprague Dawley (SD) rats. This is a unique study wherein we have used 24-month-old rats and monitored them until the end of their lifespan with and without E5 treatment. In the present investigation, the SD rats were separated into two groups old control group and the treatment group (n = 8). The treatment group received four injections of E5 every alternate day for 8 days, and eight injections every alternate day for 16 days. Body weight, grip strength, cytokines, and biochemical markers were measured for more than 400 days of the study. Clinical observation, necropsy, and histology were performed. The E5 treatment exhibited great potential by showing significantly improved grip strength, remarkably decreased pro-inflammatory markers of chronic inflammation and oxidative stress, as well as biomarkers for vital organs (BUN, SGPT, SGOT, and triglycerides), and increased anti-oxidant levels. Clinical examinations, necropsies, and histopathology revealed that the animals treated with the E5 had normal cellular structure and architecture. In conclusion, this unique 'plasma-derived exosome' treatment (E5) alone is adequate to improve the health-span and extend the lifespan of the old SD rats significantly.

Perspectives on biomarkers of reproductive aging for fertility and beyond

Reproductive aging, spanning an age-related functional decline in the female and male reproductive systems, compromises fertility and leads to a range of health complications. In this Perspective, we first introduce a comprehensive framework for biomarkers applicable in clinical settings and discuss the existing repertoire of biomarkers used in practice. These encompass functional, imaging-based and biofluid-based biomarkers, all of which reflect the physiological characteristics of reproductive aging and help to determine the reproductive biological age. Next, we delve into the molecular alterations associated with aging in the reproductive system, highlighting the gap between these changes and their potential as biomarkers. Finally, to enhance the precision and practicality of assessing reproductive aging, we suggest adopting cutting-edge technologies for identifying new biomarkers and conducting thorough validations in population studies before clinical applications. These advancements will foster improved comprehension, prognosis and treatment of subfertility, thereby increasing chances of preserving reproductive health and resilience in populations of advanced age.

Biomarkers for aging of blood - how transferable are they between mice and humans?

Aging significantly impacts the hematopoietic system, reducing its regenerative capacity and ability to restore homeostasis after stress. Mouse models have been invaluable in studying this process due to their shorter lifespan and the ability to explore genetic, treatment, and environmental influences on aging. However, not all aspects of aging are mirrored between species. This review compares three key aging biomarkers in the hematopoietic systems of mice and humans: myeloid bias, telomere attrition, and epigenetic clocks. Myeloid bias, marked by an increased fraction of myeloid cells and decreased lymphoid cells, is a significant aging marker in mice but is scarcely observed in humans after childhood. Conversely, telomere length is a robust aging biomarker in humans, whereas mice exhibit significantly different telomere dynamics, making telomere length less reliable in the murine system. Epigenetic clocks, based on DNA methylation changes at specific genomic regions, provide precise estimates of chronologic age in both mice and humans. Notably, age-associated regions in mice and humans occur at homologous genomic locations. Epigenetic clocks, depending on the epigenetic signatures used, also capture aspects of biological aging, offering powerful tools to assess genetic and environmental impacts on aging. Taken together, not all blood aging biomarkers are transferable between mice and humans. When using murine models to extrapolate human aging, it may be advantageous to focus on aging phenomena observed in both species. In conclusion, although mouse models offer significant insights, selecting appropriate biomarkers is crucial for translating findings to human aging.

Genetic-by-age interaction analyses on complex traits in UK Biobank and their potential to identify effects on longitudinal trait change

BACKGROUND

Genome-wide association studies (GWAS) have identified thousands of loci for disease-related human traits in cross-sectional data. However, the impact of age on genetic effects is underacknowledged. Also, identifying genetic effects on longitudinal trait change has been hampered by small sample sizes for longitudinal data. Such effects on deteriorating trait levels over time or disease progression can be clinically relevant.

RESULTS

Under certain assumptions, we demonstrate analytically that genetic-by-age interaction observed in cross-sectional data can be indicative of genetic association on longitudinal trait change. We propose a 2-stage approach with genome-wide pre-screening for genetic-by-age interaction in cross-sectional data and testing identified variants for longitudinal change in independent longitudinal data. Within UK Biobank cross-sectional data, we analyze 8 complex traits (up to 370,000 individuals). We identify 44 genetic-by-age interactions (7 loci for obesity traits, 26 for pulse pressure, few to none for lipids). Our cross-trait view reveals trait-specificity regarding the proportion of loci with age-modulated effects, which is particularly high for pulse pressure. Testing the 44 variants in longitudinal data (up to 50,000 individuals), we observe significant effects on change for obesity traits (near APOE, TMEM18, TFAP2B) and pulse pressure (near FBN1, IGFBP3; known for implication in arterial stiffness processes).

CONCLUSIONS

We provide analytical and empirical evidence that cross-sectional genetic-by-age interaction can help pinpoint longitudinal-change effects, when cross-sectional data surpasses longitudinal sample size. Our findings shed light on the distinction between traits that are impacted by age-dependent genetic effects and those that are not.

Stool and blood biomarkers for colorectal cancer management: an update on screening and disease monitoring

BACKGROUND

Biomarkers have revolutionized the management of colorectal cancer (CRC), facilitating early detection, prevention, personalized treatment, and minimal residual disease (MRD) monitoring. This review explores current CRC screening strategies and emerging biomarker applications.

MAIN BODY

We summarize the landscape of non-invasive CRC screening and MRD detection strategies, discuss the limitations of the current approaches, and highlight the promising potential of novel biomarker solutions. The fecal immunochemical test remained the cornerstone of CRC screening, but its sensitivity has been improved by assays that combined its performance with other stool analytes. However, their sensitivity for advanced adenomas and the patient compliance both remain suboptimal. Blood-based tests promise to increase compliance but require further refinement to compete with stool-based biomarker tests. The ideal scenario involves leveraging blood tests to increase screening participation, and simultaneously promote stool- and endoscopy-based screening among those who are compliant. Once solely reliant on upfront surgery followed by stage and pathology-driven adjuvant chemotherapy, the treatment of stage II and III colon cancer has undergone a revolutionary transformation with the advent of MRD testing after surgery. A decade ago, the concept of using a post-surgical test instead of stage and pathology to determine the need for adjuvant chemotherapy was disruptive. Today, a blood test may be more informative of the need for chemotherapy than the stage at diagnosis.

CONCLUSION

Biomarker research is not just improving, but bringing a transformative change to CRC clinical management. Early detection is not just getting better, but improving thanks to a multi-modality approach, and personalized treatment plans are not just becoming a reality, but a promising future with MRD testing.

Similarities in B Cell Defects between Aging and Obesity

The aging population is increasing worldwide, and there is also an increase in the aging population living with overweight and obesity, due to changes in lifestyle and in dietary patterns that elderly individuals experience later in life. Both aging and obesity are conditions of accelerated metabolic dysfunction and dysregulated immune responses. In this review, we summarize published findings showing that obesity induces changes in humoral immunity similar to those induced by aging and that the age-associated B cell defects are mainly due to metabolic changes. We discuss the role of the obese adipose tissue in inducing dysfunctional humoral responses and autoimmune Ab secretion.

From animal models to human individuality: Integrative approaches to the study of brain plasticity

Plasticity allows organisms to form lasting adaptive changes in neural structures in response to interactions with the environment. It serves both species-general functions and individualized skill acquisition. To better understand human plasticity, we need to strengthen the dialogue between human research and animal models. Therefore, we propose to (1) enhance the interpretability of macroscopic methods used in human research by complementing molecular and fine-structural measures used in animals with such macroscopic methods, preferably applied to the same animals, to create macroscopic metrics common to both examined species; (2) launch dedicated cross-species research programs, using either well-controlled experimental paradigms, such as motor skill acquisition, or more naturalistic environments, where individuals of either species are observed in their habitats; and (3) develop conceptual and computational models linking molecular and fine-structural events to phenomena accessible by macroscopic methods. In concert, these three component strategies can foster new insights into the nature of plastic change.

Aging drives a program of DNA methylation decay in plant organs

How organisms age is a question with broad implications for human health. In mammals, DNA methylation is a biomarker for biological age, which may predict age more accurately than date of birth. However, limitations in mammalian models make it difficult to identify mechanisms underpinning age-related DNA methylation changes. Here, we show that the short-lived model plant Arabidopsis thaliana exhibits a loss of epigenetic integrity during aging, causing heterochromatin DNA methylation decay and the expression of transposable elements. We show that the rate of epigenetic aging can be manipulated by extending or curtailing lifespan, and that shoot apical meristems are protected from this aging process. We demonstrate that a program of transcriptional repression suppresses DNA methylation maintenance pathways during aging, and that mutants of this mechanism display a complete absence of epigenetic decay. This presents a new paradigm in which a gene regulatory program sets the rate of epigenomic information loss during aging.

Exploring the potential of epigenetic clocks in aging research

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

Metformin decelerates aging clock in male monkeys

In a rigorous 40-month study, we evaluated the geroprotective effects of metformin on adult male cynomolgus monkeys, addressing a gap in primate aging research. The study encompassed a comprehensive suite of physiological, imaging, histological, and molecular evaluations, substantiating metformin's influence on delaying age-related phenotypes at the organismal level. Specifically, we leveraged pan-tissue transcriptomics, DNA methylomics, plasma proteomics, and metabolomics to develop innovative monkey aging clocks and applied these to gauge metformin's effects on aging. The results highlighted a significant slowing of aging indicators, notably a roughly 6-year regression in brain aging. Metformin exerts a substantial neuroprotective effect, preserving brain structure and enhancing cognitive ability. The geroprotective effects on primate neurons were partially mediated by the activation of Nrf2, a transcription factor with anti-oxidative capabilities. Our research pioneers the systemic reduction of multi-dimensional biological age in primates through metformin, paving the way for advancing pharmaceutical strategies against human aging.

The mitochondrial-targeted peptide therapeutic elamipretide improves cardiac and skeletal muscle function during aging without detectable changes in tissue epigenetic or transcriptomic age

Aging-related decreases in cardiac and skeletal muscle function are strongly associated with various comorbidities. Elamipretide (ELAM), a novel mitochondrial-targeted peptide, has demonstrated broad therapeutic efficacy in ameliorating disease conditions associated with mitochondrial dysfunction across both clinical and pre-clinical models. ELAM is proposed to restore mitochondrial bioenergetic function by stabilizing inner membrane structure and increasing oxidative phosphorylation coupling and efficiency. Although ELAM treatment effectively attenuates physiological declines in multiple tissues in rodent aging models, it remains unclear whether these functional improvements correlate with favorable changes in molecular biomarkers of aging. Herein, we investigated the impact of 8-week ELAM treatment on pre- and post- measures of C57BL/6J mice frailty, skeletal muscle, and cardiac muscle function, coupled with post-treatment assessments of biological age and affected molecular pathways. We found that health status, as measured by frailty index, cardiac strain, diastolic function, and skeletal muscle force are significantly diminished with age, with skeletal muscle force changing in a sex-dependent manner. Conversely, ELAM mitigated frailty accumulation and was able to partially reverse these declines, as evidenced by treatment-induced increases in cardiac strain and muscle fatigue resistance. Despite these improvements, we did not detect statistically significant changes in gene expression or DNA methylation profiles indicative of molecular reorganization or reduced biological age in most ELAM-treated groups. However, pathway analyses revealed that ELAM treatment showed pro-longevity shifts in gene expression such as upregulation of genes involved in fatty acid metabolism, mitochondrial translation and oxidative phosphorylation, and downregulation of inflammation. Together, these results indicate that ELAM treatment is effective at mitigating signs of sarcopenia and heart failure in an aging mouse model, but that these functional improvements occur independently of detectable changes in epigenetic and transcriptomic age. Thus, some age-related changes in function may be uncoupled from changes in molecular biological age.