Development of DNA methylation-based epigenetic age predictors in loblolly pine (Pinus taeda)

Biological ageing is connected to life history variation across ecological scales and informs a basic understanding of age-related declines in organismal function. Altered DNA methylation dynamics are a conserved aspect of biological ageing and have recently been modelled to predict chronological age among vertebrate species. In addition to their utility in estimating individual age, differences between chronological and predicted ages arise due to acceleration or deceleration of epigenetic ageing, and these discrepancies are linked to disease risk and multiple life history traits. Although evidence suggests that patterns of DNA methylation can describe ageing in plants, predictions with epigenetic clocks have yet to be performed. Here, we resolve the DNA methylome across CpG, CHG, and CHH-methylation contexts in the loblolly pine tree (Pinus taeda) and construct epigenetic clocks capable of predicting ages in this species within 6% of its maximum lifespan. Although patterns of CHH-methylation showed little association with age, both CpG and CHG-methylation contexts were strongly associated with ageing, largely becoming hypomethylated with age. Among age-associated loci were those in close proximity to malate dehydrogenase, NADH dehydrogenase, and 18S and 26S ribosomal RNA genes. This study reports one of the first epigenetic clocks in plants and demonstrates the universality of age-associated DNA methylation dynamics which can inform conservation and management practices, as well as our ecological and evolutionary understanding of biological ageing in plants.     

Many chronological aging clocks can be found throughout the epigenome: Implications for quantifying biological aging

Epigenetic alterations are a hallmark of aging and age‐related diseases. Computational models using DNA methylation data can create “epigenetic clocks” which are proposed to reflect “biological” aging. Thus, it is important to understand the relationship between predictive clock sites and aging biology. To do this, we examined over 450,000 methylation sites from 9,699 samples. We found ~20% of the measured genomic cytosines can be used to make many different epigenetic clocks whose age prediction performance surpasses that of telomere length. Of these predictive sites, the average methylation change over a lifetime was small (~1.5%) and these sites were under‐represented in canonical regions of epigenetic regulation. There was only a weak association between “accelerated” epigenetic aging and disease. We also compare tissue‐specific and pan‐tissue clock performance. This is critical to applying clocks both to new sample sets in basic research, as well as understanding if clinically available tissues will be feasible samples to evaluate “epigenetic aging” in unavailable tissues (e.g., brain). Despite the reproducible and accurate age predictions from DNA methylation data, these findings suggest they may have limited utility as currently designed in understanding the molecular biology of aging and may not be suitable as surrogate endpoints in studies of anti‐aging interventions. Purpose‐built clocks for specific tissues age ranges or phenotypes may perform better for their specific purpose. However, if purpose‐built clocks are necessary for meaningful predictions, then the utility of clocks and their application in the field needs to be considered in that context.     

Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell-type deconvolution applied to human blood epigenetic clocks

Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.     

Biological clocks as age estimation markers in animals: a systematic review and meta-analysis

Various biological attributes associated with individual fitness in animals change predictably over the lifespan of an organism. Therefore, the study of animal ecology and the work of conservationists frequently relies upon the ability to assign animals to functionally relevant age classes to model population fitness. Several approaches have been applied to determining individual age and, while these methods have proved useful, they are not without limitations and often lack standardisation or are only applicable to specific species. For these reasons, scientists have explored the potential use of biological clocks towards creating a universal age-determination method. Two biological clocks, tooth layer annulation and otolith layering have found universal appeal. Both methods are highly invasive and most appropriate for post-mortem age-at-death estimation. More recently, attributes of cellular ageing previously explored in humans have been adapted to studying ageing in animals for the use of less-invasive molecular methods for determining age. Here, we review two such methods, assessment of methylation and telomere length, describing (i) what they are, (ii) how they change with age, and providing (iii) a summary and meta-analysis of studies that have explored their utility in animal age determination. We found that both attributes have been studied across multiple vertebrate classes, however, telomere studies were used before methylation studies and telomere length has been modelled in nearly twice as many studies. Telomere length studies included in the review often related changes to stress responses and illustrated that telomere length is sensitive to environmental and social stressors and, in the absence of repair mechanisms such as telomerase or alternative lengthening modes, lacks the ability to recover. Methylation studies, however, while also detecting sensitivity to stressors and toxins, illustrated the ability to recover from such stresses after a period of accelerated ageing, likely due to constitutive expression or reactivation of repair enzymes such as DNA methyl transferases. We also found that both studied attributes have parentally heritable features, but the mode of inheritance differs among taxa and may relate to heterogamy. Our meta-analysis included more than 40 species in common for methylation and telomere length, although both analyses included at least 60 age-estimation models. We found that methylation outperforms telomere length in terms of predictive power evidenced from effect sizes (more than double that observed for telomeres) and smaller prediction intervals. Both methods produced age correlation models using similar sample sizes and were able to classify individuals into young, middle, or old age classes with high accuracy. Our review and meta-analysis illustrate that both methods are well suited to studying age in animals and do not suffer significantly from variation due to differences in the lifespan of the species, genome size, karyotype, or tissue type but rather that quantitative method, patterns of inheritance, and environmental factors should be the main considerations. Thus, provided that complex factors affecting the measured trait can be accounted for, both methylation and telomere length are promising targets to develop as biomarkers for age determination in animals.     

Region-based epigenetic clock design improves RRBS-based age prediction

Recent studies suggest that epigenetic rejuvenation can be achieved using drugs that mimic calorie restriction and techniques such as reprogramming-induced rejuvenation. To effectively test rejuvenation in vivo, mouse models are the safest alternative. However, we have found that the recent epigenetic clocks developed for mouse reduced-representation bisulphite sequencing (RRBS) data have significantly poor performance when applied to external datasets. We show that the sites captured and the coverage of key CpGs required for age prediction vary greatly between datasets, which likely contributes to the lack of transferability in RRBS clocks. To mitigate these coverage issues in RRBS-based age prediction, we present two novel design strategies that use average methylation over large regions rather than individual CpGs, whereby regions are defined by sliding windows (e.g. 5 kb), or density-based clustering of CpGs. We observe improved correlation and error in our regional blood clocks (RegBCs) compared to published individual-CpG-based techniques when applied to external datasets. The RegBCs are also more robust when applied to low coverage data and detect a negative age acceleration in mice undergoing calorie restriction. Our RegBCs offer a proof of principle that age prediction of RRBS datasets can be improved by accounting for multiple CpGs over a region, which negates the lack of read depth currently hindering individual-CpG-based approaches.     

Current perspectives on the cellular and molecular features of epigenetic ageing

It has been noted for quite some time that DNA methylation levels decline with age. The significance of this change remained unknown until it became possible to measure methylation status of specific sites on the DNA. It was observed that while the methylation of some sites does indeed decrease with age, that of others increase or remain unchanged. The application of machine learning methods to these quantitative changes in multiple sites, allowed the generation of a highly accurate estimator of age, called the epigenetic clock. The application of this clock on large human epidemiological data sets revealed that discordance between the predicted (epigenetic age) and chronological age is associated with many age-related pathologies, particularly when the former is greater than the latter. The epigenetic clock clearly captures to some degree, biological features that accompany the ageing process. Despite the ever-increasing scope of pathologies that are found to be associated with accelerated epigenetic ageing, the basic principles that underlie the ticking of the clock remain elusive. Here, we describe the known molecular and cellular attributes of the clock and consider their properties, and proffer opinions as to how they may be connected and what might be the underlying mechanism. Emerging from these considerations is the inescapable view that epigenetic ageing begins from very early moments after the embryonic stem cell stage and continues un-interrupted through the entire life-course. This appears to be a consequence of processes that are necessary for the development of the organism from conception and to maintain it thereafter through homeostasis. Hence, while the speed of ageing can, and is affected by external factors, the essence of the ageing process itself is an integral part of, and the consequence of the development of life.Impact statementThe field of epigenetic ageing is relatively new, and the speed of its expansion presents a challenge in keeping abreast with new discoveries and their implications. Several reviews have already addressed the great number of pathologies, health conditions, life-style, and external stressors that are associated with changes to the rate of epigenetic ageing. While these associations highlight and affirm the ability of epigenetic clock to capture biologically meaningful changes associated with age, they do not inform us about the underlying mechanisms. In this very early period since the development of the clock, there have been rather limited experimental research that are aimed at uncovering the mechanism. Hence, the perspective that we proffer is derived from available but nevertheless limited lines of evidence that together provide a seemingly coherent narrative that can be tested. This, we believe would be helpful towards uncovering the workings of the epigenetic clock.     

Physical activity is associated with slower epigenetic ageing—Findings from the Rhineland study

Epigenetic ageing, i.e., age-associated changes in DNA methylation patterns, is a sensitive marker of biological ageing, a major determinant of morbidity and functional decline. We examined the association of physical activity with epigenetic ageing and the role of immune function and cardiovascular risk factors in mediating this relation. Moreover, we aimed to identify novel molecular processes underlying the association between physical activity and epigenetic ageing. We analysed cross-sectional data from 3567 eligible participants (mean age: 55.5 years, range: 30–94 years, 54.8% women) of the Rhineland Study, a community-based cohort study in Bonn, Germany. Physical activity components (metabolic equivalent (MET)-Hours, step counts, sedentary, light-intensity and moderate-to-vigorous intensity activities) were recorded with accelerometers. DNA methylation was measured with the Illumina HumanMethylationEPIC BeadChip. Epigenetic age acceleration (Hannum's age, Horvath's age, PhenoAge and GrimAge) was calculated based on published algorithms. The relation between physical activity and epigenetic ageing was examined with multivariable regression, while structural equation modeling was used for mediation analysis. Moreover, we conducted an epigenome-wide association study of physical activity across 850,000 CpG sites. After adjustment for age, sex, season, education, smoking, cell proportions and batch effects, physical activity (step counts, MET-Hours and %time spend in moderate-to-vigorous activities) was non-linearly associated with slower epigenetic ageing, in part through its beneficial effects on immune function and cardiovascular health. Additionally, we identified 12 and 7 CpGs associated with MET-Hours and %time spent in moderate-to-vigorous activities, respectively (p < 1 × 10⁻⁵). Our findings suggest that regular physical activity slows epigenetic ageing by counteracting immunosenescence and lowering cardiovascular risk.     

How does the body know how old it is? Introducing the epigenetic clock hypothesis

Animals and plants have biological clocks that help to regulate circadian cycles, seasonal rhythms, growth, development, and sexual maturity. It is reasonable to suspect that the timing of senescence is also influenced by one or more biological clocks. Evolutionary reasoning first articulated by G. Williams suggests that multiple, redundant clocks might influence organismal aging. Some aging clocks that have been proposed include the suprachiasmatic nucleus, the hypothalamus, involution of the thymus, and cellular senescence. Cellular senescence, mediated by telomere attrition, is in a class by itself, having recently been validated as a primary regulator of aging. Gene expression is known to change in characteristic ways with age, and in particular DNA methylation changes in age-related ways. Herein, I propose a new candidate for an aging clock, based on epigenetics and the state of chromosome methylation, particularly in stem cells. If validated, this mechanism would present a challenging target for medical intervention.     

The Role of Circadian Clocks in Metabolic Disease

The circadian clock is a highly conserved timing system, resonating physiological processes to 24-hour environmental cycles. Circadian misalignment is emerging as a risk factor of metabolic disease. The molecular clock resides in all metabolic tissues, the dysfunction of which is associated with perturbed energy metabolism. In this article, we will review current knowledge about molecular mechanisms of the circadian clock and the role of clocks in the physiology and pathophysiology of metabolic tissues.     

Computational design and evolution of the oscillatory response under light-dark cycles

Circadian clocks are biological systems behaving as oscillators even in constant dark conditions. We propose to use a new strategy based on computational design to provide evidence on the origin and evolution of molecular clocks. We design synthetic molecular clocks having a reduced number of genes and some of them showing architectures found in nature. We analyse the response of our models under diverse forcing light-dark (LD) cycles. Our methodology allows us to evolve networks in silico using various selective pressures, which we apply to the analysis of clocks evolved to be either autonomous or phase locked. Our designed networks either have an oscillatory response with the same period as the forcing LD cycle, or they maintain their free-running period. Our methodology will allow analysing the automatic creation of a free-running period under various LD forcing functions and learning new design principles for circadian clocks.     

Epigenetic clock and methylation studies in elephants

Age‐associated DNA‐methylation profiles have been used successfully to develop highly accurate biomarkers of age ("epigenetic clocks") in humans, mice, dogs, and other species. Here we present epigenetic clocks for African and Asian elephants. These clocks were developed using novel DNA methylation profiles of 140 elephant blood samples of known age, at loci that are highly conserved between mammalian species, using a custom Infinium array (HorvathMammalMethylChip40). We present epigenetic clocks for Asian elephants (Elephas maximus), African elephants (Loxodonta africana), and both elephant species combined. Two additional human‐elephant clocks were constructed by combining human and elephant samples. Epigenome‐wide association studies identified elephant age‐related CpGs and their proximal genes. The products of these genes play important roles in cellular differentiation, organismal development, metabolism, and circadian rhythms. Intracellular events observed to change with age included the methylation of bivalent chromatin domains, and targets of polycomb repressive complexes. These readily available epigenetic clocks can be used for elephant conservation efforts where accurate estimates of age are needed to predict demographic trends.     

BIOLOGICAL TIMING AND THE CLOCK METAPHOR: OSCILLATORY AND HOURGLASS MECHANISMS

Living organisms have developed a multitude of timing mechanisms— “biological clocks.” Their mechanisms are based on either oscillations (oscillatory clocks) or unidirectional processes (hourglass clocks). Oscillatory clocks comprise circatidal, circalunidian, circadian, circalunar, and circannual oscillations—which keep time with environmental periodicities—as well as ultradian oscillations, ovarian cycles, and oscillations in development and in the brain, which keep time with biological timescales. These clocks mainly determine time points at specific phases of their oscillations. Hourglass clocks are predominantly found in development and aging and also in the brain. They determine time intervals (duration). More complex timing systems combine oscillatory and hourglass mechanisms, such as the case for cell cycle, sleep initiation, or brain clocks, whereas others combine external and internal periodicities (photoperiodism, seasonal reproduction). A definition of a biological clock may be derived from its control of functions external to its own processes and its use in determining temporal order (sequences of events) or durations. Biological and chemical oscillators are characterized by positive and negative feedback (or feedforward) mechanisms. During evolution, living organisms made use of the many existing oscillations for signal transmission, movement, and pump mechanisms, as well as for clocks. Some clocks, such as the circadian clock, that time with environmental periodicities are usually compensated (stabilized) against temperature, whereas other clocks, such as the cell cycle, that keep time with an organismic timescale are not compensated. This difference may be related to the predominance of negative feedback in the first class of clocks and a predominance of positive feedback (autocatalytic amplification) in the second class. The present knowledge of a compensated clock (the circadian oscillator) and an uncompensated clock (the cell cycle), as well as relevant models, are briefly reviewed. Hourglass clocks are based on linear or exponential unidirectional processes that trigger events mainly in the course of development and aging. An important hourglass mechanism within the aging process is the limitation of cell division capacity by the length of telomeres. The mechanism of this clock is briefly reviewed. In all clock mechanisms, thresholds at which “dependent variables” are triggered play an important role. (Chronobiology International, 18(3), 329–369, 2001)     

Determinants of accelerated metabolomic and epigenetic aging in a UK cohort

Markers of biological aging have potential utility in primary care and public health. We developed a model of age based on untargeted metabolic profiling across multiple platforms, including nuclear magnetic resonance spectroscopy and liquid chromatography–mass spectrometry in urine and serum, within a large sample (N = 2,239) from the UK Airwave cohort. We validated a subset of model predictors in a Finnish cohort including repeat measurements from 2,144 individuals. We investigated the determinants of accelerated aging, including lifestyle and psychological risk factors for premature mortality. The metabolomic age model was well correlated with chronological age (mean r = .86 across independent test sets). Increased metabolomic age acceleration (mAA) was associated after false discovery rate (FDR) correction with overweight/obesity, diabetes, heavy alcohol use and depression. DNA methylation age acceleration measures were uncorrelated with mAA. Increased DNA methylation phenotypic age acceleration (N = 1,110) was associated after FDR correction with heavy alcohol use, hypertension and low income. In conclusion, metabolomics is a promising approach for the assessment of biological age and appears complementary to established epigenetic clocks.     

Emerging rejuvenation strategies—Reducing the biological age

Several interventions have recently emerged that were proposed to reverse rather than just attenuate aging, but the criteria for what it takes to achieve rejuvenation remain controversial. Distinguishing potential rejuvenation therapies from other longevity interventions, such as those that slow down aging, is challenging, and these anti‐aging strategies are often referred to interchangeably. We suggest that the prerequisite for a rejuvenation intervention is a robust, sustained, and systemic reduction in biological age, which can be assessed by biomarkers of aging, such as epigenetic clocks. We discuss known and putative rejuvenation interventions and comparatively analyze them to explore underlying mechanisms.     

DNA methylation-based biomarkers for ageing long-lived cetaceans

Epigenetic approaches for estimating the age of living organisms are revolutionizing studies of long-lived species. Molecular biomarkers that allow age estimates from small tissue biopsies promise to enhance studies of long-lived whales, addressing a fundamental and challenging parameter in wildlife management. DNA methylation (DNAm) can affect gene expression, and strong correlations between DNAm patterns and age have been documented in humans and nonhuman vertebrates and used to construct “epigenetic clocks”. We present several epigenetic clocks for skin samples from two of the longest-lived cetaceans, killer whales and bowhead whales. Applying the mammalian methylation array to genomic DNA from skin samples we validate four different clocks with median errors of 2.3–3.7 years. These epigenetic clocks demonstrate the validity of using cytosine methylation data to estimate the age of long-lived cetaceans and have broad applications supporting the conservation and management of long-lived cetaceans using genomic DNA from remote tissue biopsies.     

A clockwork fish: Age prediction using DNA methylation‐based biomarkers in the European seabass

Age‐related changes in DNA methylation do occur. Taking advantage of this, mammalian and avian epigenetic clocks have been constructed to predict age. In fish, studies on age‐related DNA methylation changes are scarce and no epigenetic clocks have been constructed. However, in fisheries and population dynamics studies there is a need for accurate estimation of age, something that is often impossible for some economically important species with the currently available methods. Here, we used the European sea bass, a marine fish the age of which can be determined with accuracy, to construct a piscine epigenetic clock, the first one in a cold‐blooded vertebrate. We used targeted bisulfite sequencing to amplify 48 CpGs from four genes in muscle samples and applied penalized regressions to predict age. We thus developed an age predictor in fish that is highly accurate (0.824) and precise (2.149 years). In juvenile fish, accelerated growth due to elevated temperatures had no effect on age prediction, indicating that the clock is able to predict the chronological age independently of environmentally‐driven perturbations. An epigenetic clock developed using muscle samples accurately predicted age in samples of testis but not ovaries, possibly reflecting the reproductive biology of fish. In conclusion, we report the development of the first piscine epigenetic clock, paving the way for similar studies in other species. Piscine epigenetic clocks should be of great utility for fisheries management and conservation purposes, where age determination is of crucial importance.     

Type 2 diabetes mellitus in relation to global LINE-1 DNA methylation in peripheral blood: A cohort study

In the last years, epigenetic processes have emerged as a promising area of complex diseases research. DNA methylation measured in Long Interspersed Nucleotide Element 1 (LINE-1) sequences has been considered a surrogate marker for global genome methylation. New findings have suggested the potential involvement of epigenetic mechanisms in Type 2 diabetes (T2DM) as a crucial interface between the effects of genetic predisposition and environmental influences. Our study evaluated whether global DNA methylation predicted increased risk from T2DM or other carbohydrate metabolism disorders in a cohort study. We used a prospective cohort intervention study and a control group. We collected phenotypic, anthropometric, biochemical, and nutritional information from all subjects. Global LINE-1 DNA methylation was quantified by pyrosequencing technology. Subjects that did not improve their carbohydrate metabolism status showed lower levels of global LINE-1 DNA methylation (63.9 ± 1.7 vs. 64.7 ± 2.4) and they practiced less intense physical activity (5.8% vs. 21.5%). Logistic regression analyses showed a significant association between LINE-1 DNA methylation and metabolic status after adjustment for sex, age, BMI, and physical activity. Our study showed that lower LINE-1 DNA methylation levels were associated with a higher risk metabolic status worsening, independent of other classic risk factors. This finding highlights the potential role for epigenetic biomarkers as predictors of T2DM risk or other related metabolic disorders.