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Age-associated DNA methylation at the three CpG sites in different tissues. Different tissues were isolated of three young (9.6 weeks) and three old mice (56.9 weeks) and DNAm was analyzed at the three relevant CpGs in (a) Prima1, (b) Hsf4, and (c) Kcns1. Epigenetic age-predictions using the 3 CpG model for blood demonstrated also significant differences between young and old mice in skin, intestine, brain, and testis (mean ± standard deviation; Student t-tests: *p<0.05; **p<0.01; ***p<0.001). DOI: https://doi.org/10.7554/eLife.37462.006
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Epigenetic marks are chemical modifications found throughout the genome – the DNA within cells. By influencing the activity of nearby genes, the marks govern developmental processes and help cells to adapt to changes in their surroundings. Some epigenetic marks can be gained or lost with age. A lot of aging research focuses on one type...
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... DNAm data can be obtained from a variety of sources of DNA, including hair or faecal collection (Hao et al., 2021;Liu et al., 2021). Identifying a small number of CpG sites that strongly correlate with chronological age can facilitate the development of diagnostic markers, lowering processing costs of age estimation without sacrificing accuracy (Han et al., 2018). This approach has relevance for harvested and managed populations, where age information is often directly used to better understand processes such as survival, population growth and harvest sustainability (Harris & Metzgar, 1987;Hecht, 2021;Udevitz & Ballachey, 1998). ...
The development of epigenetic clocks, or the DNA methylation‐based inference of age, is an emerging tool for ageing in free ranging populations. In this study, we developed epigenetic clocks for three species of large mammals that are the focus of extensive management throughout their range in North America: white‐tailed deer, black bear and mountain goat. We quantified differential DNA methylation patterns at over 30,000 cytosine‐guanine sites (CpGs) from tissue samples of all three species (black bear n = 49; white‐tailed deer n = 47; mountain goat n = 45). We used a penalized regression model (elastic net) to build explanatory (black bear r = .95; white‐tailed deer r = .99; mountain goat r = .97) and robust (black bear Median Absolute Error or MAE = 1.33; white‐tailed deer MAE = 0.29; mountain goat MAE = 0.61) models of age or clocks. We also characterized individual CpG sites within each species that demonstrated clear differences in methylation levels between age classes and sex, which can be used to develop a suite of accessible diagnostic markers. This tool has the potential to contribute to wildlife monitoring by providing easily obtainable representations of age structure in managed populations.
... However, such models involve hundreds of CpGs. Therefore, a model for predicting epigenetic age in mouse blood samples using only three cytosines has been developed, which was first trained using pyrosequencing data [20] and later using bisulfite amplicon NGS data with a slightly modified set of CpGs within the same loci [21]. The 3-CpG age estimator was found to predict the chronological age of blood from C57BL/6 mice with an accuracy of ~ 7 weeks. ...
... The 3-CpG age estimator was found to predict the chronological age of blood from C57BL/6 mice with an accuracy of ~ 7 weeks. Interestingly, increased levels of EAA have been shown in DBA/2 mice, which are known to have a shorter lifespan [20]. ...
... In summary, the murine epigenetic clock for the aorta developed here as well as in blood samples using DNA methylation measurements at three CpG sites in the Prima1, Hsf4 and Kcns1 genes reflect the age-dependent deterioration of systemic endothelial function and thus rate of vascular biological ageing and provides a useful tool for monitoring vascular biological ageing in mice. In particular, given that various dietary or pharmacological treatments can regulate the rate of epigenetic ageing and susceptibility to age-related diseases [17,20,28], this novel tool may be useful for studies aimed at rejuvenating ageing vasculature in mice. Further studies are however warranted to verify whether, this novel tool will provide a useful and a reliable parameter to monitor rejuvenating effects of experimental interventions on epigenetic ageing and age-dependent deterioration of endothelial function in mice. ...
While epigenetic age (EA) of mouse blood can be determined using DNA methylation analysis at three CpG sites in the Prima1 , Hsf4 and Kcns1 genes it is not known whether this approach is useful for predicting vascular biological age. In this study we validated the 3-CpG estimator for age prediction in mouse blood, developed a new predictive model for EA in mouse aorta, and assessed whether epigenetic age acceleration (EAA) measured with blood and aorta samples correlates with age-dependent endothelial dysfunction. Endothelial function was characterized in vivo by MRI in 8–96-week-old C57BL/6 mice. Arterial stiffness was measured by USG-doppler. EA-related changes within 41 CpG sites in Prima1 , Kcns1 and Hsf4 loci, were analyzed in the aorta and blood using bisulfite amplicon high-throughput sequencing. Progressive age-dependent endothelial dysfunction and changes in arterial stiffness were observed in 36-96-week-old C57BL/6 mice. Methylation levels of the investigated loci correlated with chronological age in blood and the aorta. The new model for EA estimation in aorta included three cytosines located in the Kcns1 and Hsf4 , explained R ² = 87.8% of the variation in age, and predicted age with an mean absolute error of 9.6 weeks in the independent test set. EAA in the aorta was associated with endothelial dysfunction in the abdominal aorta and femoral artery what was consistent with the EAA direction estimated in blood samples. The rate of vascular biological ageing in mice, reflected by the age-dependent systemic endothelial dysfunction, could be estimated using DNA methylation measurements at three loci in aorta and blood samples.
... Utilizing the R package "glmnet", we executed the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, setting the response type to binomial and identifying alpha identified as 1. By minimizing the binominal deviation criterion, the optimal λ (representing the number of candidate RAR-DEGs of SCZ) was determined through a 10-fold cross-validation that aimed to achieve the smallest cross-validation errors [28,29]. Subsequently, a logistic "Count" is the number of genes in the user-provided lists with membership in the given ontology term. ...
Autophagy, a cellular process where cells degrade and recycle their own components, has garnered attention for its potential role in psychiatric disorders, including schizophrenia (SCZ). This study aimed to construct and validate a new autophagy-related gene (ARG) risk model for SCZ. First, we analyzed differential expressions in the GSE38484 training set, identifying 4,754 differentially expressed genes (DEGs) between SCZ and control groups. Using the Human Autophagy Database (HADb) database, we cataloged 232 ARGs and pinpointed 80 autophagy-related DEGs (AR-DEGs) after intersecting them with DEGs. Subsequent analyses, including metascape gene annotation, pathway and process enrichment, and protein-protein interaction enrichment, were performed on the 80 AR-DEGs to delve deeper into their biological roles and associated molecular pathways. From this, we identified 34 candidate risk AR-DEGs (RAR-DEGs) and honed this list to final RAR-DEGs via a constructed and optimized logistic regression model. These genes include VAMP7, PTEN, WIPI2, PARP1, DNAJB9, SH3GLB1, ATF4, EIF4G1, EGFR, CDKN1A, CFLAR, FAS, BCL2L1 and BNIP3. Using these findings, we crafted a nomogram to predict SCZ risk for individual samples. In summary, our study offers deeper insights into SCZ’s molecular pathogenesis and paves the way for innovative approaches in risk prediction, gene-targeted diagnosis, and community-based SCZ treatments.
... While these methods are useful for biomarker discovery because they measure hundreds of thousands to millions of CpGs, they are excessive for the accurate measurement of epigenetic clocks that typically only require several hundred loci to be measured. Highly targeted approaches can predict chronological age accurately [24][25][26] , such as pyrosequencing or digital PCR. However, these methods are still not optimally cost-effective or scalable and their reliance on low-CpG clocks (for example, 1-15 CpGs) limits the number of aging modules they reflect, making them less relevant to diverse intervention studies. ...
Epigenetic ‘clocks’ based on DNA methylation have emerged as the most robust and widely used aging biomarkers, but conventional methods for applying them are expensive and laborious. Here we develop tagmentation-based indexing for methylation sequencing (TIME-seq), a highly multiplexed and scalable method for low-cost epigenetic clocks. Using TIME-seq, we applied multi-tissue and tissue-specific epigenetic clocks in over 1,800 mouse DNA samples from eight tissue and cell types. We show that TIME-seq clocks are accurate and robust, enriched for polycomb repressive complex 2-regulated loci, and benchmark favorably against conventional methods despite being up to 100-fold less expensive. Using dietary treatments and gene therapy, we find that TIME-seq clocks reflect diverse interventions in multiple tissues. Finally, we develop an economical human blood clock (R > 0.96, median error = 3.39 years) in 1,056 demographically representative individuals. These methods will enable more efficient epigenetic clock measurement in larger-scale human and animal studies.
... These studies concordantly suggest that people with DS are older than their chronological age. Murine models are largely employed in the study of ageing and age-related disease (Palliyaguru et al. 2021) and mouse epigenetic biomarkers of age have been developed (Coninx et al. 2020;Lu et al. 2023;Han et al. 2018;Zhou et al. 2022;Wang & Lemos 2019). So far, however, these epigenetic clocks have been applied to a limited extent and, to the best of our knowledge, no data are available for mouse models of DS. ...
Down syndrome (DS) is a segmental progeroid genetic disorder associated to multi-systemic precocious ageing phenotypes, which are particularly evident at the immune and nervous systems. Accordingly, people with DS show an increased biological age as measured by epigenetic clocks. Ts65Dn trisomic mouse, which harbors extra-numerary copies of Hsa21-syntenic regions, was shown to recapitulate several progeroid features of DS, but no biomarkers of age have been applied to it so far. Here we used a mouse specific epigenetic clock to measure epigenetic age of hippocampi from Ts65Dn and euploid mice at 20 weeks. Ts65Dn mice showed an increased hippocampal epigenetic age respect to controls, and the observed changes in DNA methylation partially recapitulated those observed in hippocampi from people with DS. Collectively, our results support the use of the Ts65Dn model to decipher the molecular mechanisms underlying the progeroid DS phenotypes.
... These expression signatures can serve as transcriptional clocks, effectively indicating an individual's age [40]. It is worth noting that the construction of these signatures involved iterative correlations with chronological age, aiming to create molecular clocks, rather than unraveling the mechanisms by which gene expression influences the aging process [41]. Notably, different research groups have generated signatures that exhibit limited overlaps with each other and with epigenetic clocks, which are also derived from correlation analyses [42]. ...
Mammals experience similar stages of embryonic development, birth, infancy, youth, adolescence, maturity, and senescence. While embryonic developmental processes have been extensively researched, many molecular mechanisms regulating the different life stages after birth, such as aging, remain unresolved. We investigated the conserved and global molecular transitions in transcriptional remodeling with age in dogs of 15 breeds, which revealed that genes underlying hormone level regulation and developmental programs were differentially regulated during aging. Subsequently, we show that the candidate genes associated with tumorigenesis also exhibit age-dependent DNA methylation patterns, which might have contributed to the tumor state through inhibiting the plasticity of cell differentiation processes during aging, and ultimately suggesting the molecular events that link the processes of aging and cancer. These results highlight that the rate of age-related transcriptional remodeling is influenced not only by the lifespan, but also by the timing of critical physiological milestones.
... The age-associated changes in DNA methylation levels in CpG sites in gene promoters affect gene transcription levels and result in loss of body functions (Field et al., 2018). DNA methylation-based epigenetic clock has been developed in many species, such as humans (Homo sapiens ), house mice (Mus musculus ), domestic dogs (Canis familiaris ), gray wolves (Canis lupus ), domestic cats (Felis catus ), chimpanzees (Pan troglodytes ), humpback whales (Megaptera novaeangliae ), Bechstein's bats (Myotis bechsteinii ), and plains zebras (Equus quagga ) (Han et al., 2018;Horvath, 2013;Ito et al., 2018;Larison et al., 2021;Maegawa et al., 2010;Polanowski et al., 2014;Qi et al., 2021;Thompson et al., 2017;Wright et al., 2018;Zbieć-Piekarska et al., 2015), etc. ...
... (MAD = 1.55 yr, 93.5% of 23.7 yr), which include jaguars, Amur leopards, African lions, snow leopards, and Amur tigers. Although the accuracy of domestic cats was lower than the previously reported MAD = 0.83 yr in Raj et al. (2021), in which 34 CpGs were selected from 38k CpGs available from the HorvathMammalMethylChip40, the accuracy obtained in this study is still comparable to the accuracies from previous age estimation studies that used less than 30 CpGs, e.g., 95% in house mouses (Mus musculus ; Han et al., 2018), 73% in chimpanzees (Pan troglodytes , Ito et al., 2018), and 93% in beluga whales (Delphinapterus leucas , (Bors et al., 2021). Unlike Raj et al. (2021), we aimed to achieve an acceptable age estimation accuracy using only a few gene regions, allowing the design of a project with a scale and budget more suitable for conservation applications. ...
Knowledge of individual age can help both in-situ and ex-situ conservation programs to design more efficient and suitable management plans for targeted wildlife species. DNA methylation is one of the epigenetic aging markers that has emerged as a promising tool that can estimate age with high accuracy using only a tiny amount of biological material, which can be collected in a minimally invasive way. Although the conservation of Felidae species has received great attention, studies rarely focus on the development of age estimation models. Here, we sequenced five genetic regions and used 4–25 selected CpG sites to build age estimation models with several machine learning methods, using blood samples of seven Felidae species—ranging from small to big, and domestic to endangered species: domestic cats ( Felis catus , 139 samples), Tsushima leopard cats ( Prionailurus bengalensis euptilurus , 84 samples), and five Panthera species (96 samples). The models built achieved satisfactory accuracy—the mean absolute deviation of the best models was 1.80, 1.30, and 1.55 years in domestic cats, Tsushima leopard cats, and Panthera spp., respectively. Our models in domestic cats and Tsushima leopard cats were applicable to all individuals regardless of health conditions and sex, indicating high applicability of our models to samples collected from diverse situations, e.g., rescued individuals in the context of conservation. We also showed the possibility of developing universal age estimation models for the five Panthera spp. using two of the five genetic regions, suggesting an even lower cost to use our models for future applications.
... In addition, the majority of hypermethylating regions in our regional clocks were overlapping with CpG islands. This is, however, expected as CpG islands are commonly hypomethylated and, therefore, can only gain in methylation with age, which is a well documented phenomenon (Gopalan et al., 2017;Heyn et al., 2012;Johansson et al., 2013;Slieker et al., 2018 (Han et al., 2018(Han et al., , 2020. Techniques such as this offer certain benefits for age prediction since they have a higher coverage at a small selection of CpGs, whereas RRBS experiments vary in coverage necessary for the CpG-specific approach for age prediction (Figure 1e,f). ...
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.
... Borkan and Norris, 1980). The most accurate "biological clocks," however, are modern multivariate models including a large number of molecular variables (though one recently published biological clock for lab mice claims to be able to estimate biological age based on methylation status at just 3 CpG sites; Han et al., 2018). Those biological clocks that effectively estimate both chronological age at the population level as well as future health and remaining lifespan at the individual level are generally based on animals' methylome or transcriptome (Belsky et al., 2022;Horvath, 2013;Horvath et al., 2016;Jylhävä et al., 2017;Simpson and Chandra, 2021;. ...
... The re-wilded approach in house mice represents an un-paralleled opportunity to understand social impacts on the biological aging process. Multiple epigenetic clocks have already been calibrated for laboratory mice living in the lab (Ding et al., 2023;Han et al., 2018;Meer et al., 2018;Stubbs et al., 2017;. But none of these clocks have yet been used to study biological aging of mice under ecologically realistic social conditions. ...
Social experiences are strongly associated with individuals' health, aging, and survival in many mammalian taxa, including humans. Despite their role as models of many other physiological and developmental bases of health and aging, biomedical model organisms (particularly lab mice) remain an underutilized tool in resolving outstanding questions regarding social determinants of health and aging, including causality, context-dependence, reversibility, and effective interventions. This status is largely due to the constraints of standard laboratory conditions on animals' social lives. Even when kept in social housing, lab animals rarely experience social and physical environments that approach the richness, variability, and complexity they have evolved to navigate and benefit from. Here we argue that studying biomedical model organisms outside under complex, semi-natural social environments ("re-wilding") allows researchers to capture the methodological benefits of both field studies of wild animals and laboratory studies of model organisms. We review recent efforts to re-wild mice and highlight discoveries that have only been made possible by researchers studying mice under complex, manipulable social environments.
... In humans, epigenetic clocks have been shown to accurately estimate chronological and biological age and predict survival [9][10][11][12]. In mice, a three CpG clock, analyzing methylation sites in Prima1, Hsf4 and Kcns1 genes, was recently demonstrated to be highly correlated with chronological age [13,14]. This kind of epigenetic clock provides exceptional advantages in terms of time and costs, especially in longitudinal studies involving hundreds of mice. ...
... The epigenetic age was measured through the three CpG clock method [13] in blood cells of aged mice before (time 0, t0; age: 19.2-26.6 months) and after (time 1, t1; age: 21.5-29 months) two i.v. injections of LAV-BPIFB4 or GFP (control) -encoding adenoassociated viral vectors (AAV) ( Figure 1A). ...
... In the present study, we investigated the effect of the systemic gene transfer of human LAV-BPIFB4 in geriatric C57BL/6J mice on epigenetic mechanisms associated with aging through the three CpG clock methylation analysis [13] and the calculation of its ticking rate [28]. Moreover, we combined the methylation analysis with the frailty assessment, to investigate the relationship between epigenetic age, clinical and physical decline, and longevity. ...
The homozygous genotype of the Longevity-Associated Variant (LAV) in Bactericidal/Permeability-Increasing Fold-Containing Family B member 4 (BPIFB4) is enriched in long-living individuals of three independent populations and its genetic transfer in C57BL/6J mice showed a delay in frailty progression and improvement of several biomarkers of aging and multiple aspects of health. The C57BL/6J strain is a suitable model for studying therapies aimed at extending healthy aging and longevity due to its relatively short lifespan and the availability of aging biomarkers. Epigenetic clocks based on DNA methylation profiles are reliable molecular biomarkers of aging, while frailty measurement tools are used to evaluate overall health during aging. In this study, we show that the systemic gene transfer of LAV-BPIFB4 in aged C57BL/6J mice was associated with a significant reduction in the epigenetic clock-based biological age, as measured by a three CpG clock method. Furthermore, LAV-BPIFB4 gene transfer resulted in an improvement of the Vitality Score with a reduction in the Frailty Index. These findings further support the use of LAV-BPIFB4 gene therapy to induce beneficial effects on epigenetic mechanisms associated with aging and frailty in aged mice, with potential implications for future therapies to prevent frailty in humans.
