scholarly journals Development of Epigenetic Clocks for Key Ruminant Species

Genes ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 96
Author(s):  
Alex Caulton ◽  
Ken G. Dodds ◽  
Kathryn M. McRae ◽  
Christine Couldrey ◽  
Steve Horvath ◽  
...  
Keyword(s):  
Large Body ◽  
Ovis Aries ◽  
Farm Animal ◽  
Tissue Type ◽  
Capra Hircus ◽  
Chronological Age ◽  
Individual Species ◽  
Epigenetic Clock ◽  
Cpg Sites ◽  
Age Related

Robust biomarkers of chronological age have been developed in humans and model mammalian species such as rats and mice using DNA methylation data. The concept of these so-called “epigenetic clocks” has emerged from a large body of literature describing the relationship between genome-wide methylation levels and age. Epigenetic clocks exploit this phenomenon and use small panels of differentially methylated cytosine (CpG) sites to make robust predictions of chronological age, independent of tissue type. Here, we present highly accurate livestock epigenetic clocks for which we have used the custom mammalian methylation array “HorvathMammalMethyl40” to construct the first epigenetic clock for domesticated goat (Capra hircus), cattle (Bos taurus), Red (Cervus elaphus) and Wapiti deer (Cervus canadensis) and composite-breed sheep (Ovis aries). Additionally, we have constructed a ‘farm animal clock’ for all species included in the study, which will allow for robust predictions to be extended to various breeds/strains. The farm animal clock shows similarly high accuracy to the individual species’ clocks (r > 0.97), utilizing only 217 CpG sites to estimate age (relative to the maximum lifespan of the species) with a single mathematical model. We hypothesise that the applications of this livestock clock could extend well beyond the scope of chronological age estimates. Many independent studies have demonstrated that a deviation between true age and clock derived molecular age is indicative of past and/or present health (including stress) status. There is, therefore, untapped potential to utilize livestock clocks in breeding programs as a predictor for age-related production traits.

scholarly journals Exploring Epigenetic Age in Response to Intensive Relaxing Training: A Pilot Study to Slow Down Biological Age

2019 ◽  
Vol 16 (17) ◽  
pp. 3074 ◽  
Author(s):  
Pavanello ◽  
Campisi ◽  
Tona ◽  
Lin ◽  
Iliceto
Keyword(s):  
Myocardial Infarction ◽  
Age Estimation ◽  
Healthy Subjects ◽  
Molecular Mechanisms ◽  
Biological Age ◽  
Chronological Age ◽  
Biological Aging ◽  
Epigenetic Clock ◽  
Age Related ◽  
Epigenetic Age

DNA methylation (DNAm) is an emerging estimator of biological aging, i.e., the often-defined “epigenetic clock”, with a unique accuracy for chronological age estimation (DNAmAge). In this pilot longitudinal study, we examine the hypothesis that intensive relaxing training of 60 days in patients after myocardial infarction and in healthy subjects may influence leucocyte DNAmAge by turning back the epigenetic clock. Moreover, we compare DNAmAge with another mechanism of biological age, leucocyte telomere length (LTL) and telomerase. DNAmAge is reduced after training in healthy subjects (p = 0.053), but not in patients. LTL is preserved after intervention in healthy subjects, while it continues to decrease in patients (p = 0.051). The conventional negative correlation between LTL and chronological age becomes positive after training in both patients (p < 0.01) and healthy subjects (p < 0.05). In our subjects, DNAmAge is not associated with LTL. Our findings would suggest that intensive relaxing practices influence different aging molecular mechanisms, i.e., DNAmAge and LTL, with a rejuvenating effect. Our study reveals that DNAmAge may represent an accurate tool to measure the effectiveness of lifestyle-based interventions in the prevention of age-related diseases.

scholarly journals Epigenetic clock and methylation studies in the rhesus macaque

GeroScience ◽  
2021 ◽  
Author(s):  
Steve Horvath ◽  
Joseph A. Zoller ◽  
Amin Haghani ◽  
Anna J. Jasinska ◽  
Ken Raj ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Rhesus Macaque ◽  
Mammalian Species ◽  
Vervet Monkey ◽  
Chronological Age ◽  
Biological Research ◽  
Epigenetic Clock ◽  
Methylation Array ◽  
Tissue Samples ◽  
Age Related

AbstractMethylation levels at specific CpG positions in the genome have been used to develop accurate estimators of chronological age in humans, mice, and other species. Although epigenetic clocks are generally species-specific, the principles underpinning them appear to be conserved at least across the mammalian class. This is exemplified by the successful development of epigenetic clocks for mice and several other mammalian species. Here, we describe epigenetic clocks for the rhesus macaque (Macaca mulatta), the most widely used nonhuman primate in biological research. Using a custom methylation array (HorvathMammalMethylChip40), we profiled n = 281 tissue samples (blood, skin, adipose, kidney, liver, lung, muscle, and cerebral cortex). From these data, we generated five epigenetic clocks for macaques. These clocks differ with regard to applicability to different tissue types (pan-tissue, blood, skin), species (macaque only or both humans and macaques), and measure of age (chronological age versus relative age). Additionally, the age-based human-macaque clock exhibits a high age correlation (R = 0.89) with the vervet monkey (Chlorocebus sabaeus), another Old World species. Four CpGs within the KLF14 promoter were consistently altered with age in four tissues (adipose, blood, cerebral cortex, skin). Future studies will be needed to evaluate whether these epigenetic clocks predict age-related conditions in the rhesus macaque.

scholarly journals Functional genomics analysis identifies T and NK cell activation as a driver of epigenetic clock progression

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Thomas H. Jonkman ◽  
Koen F. Dekkers ◽  
Roderick C. Slieker ◽  
Crystal D. Grant ◽  
M. Arfan Ikram ◽  
...  
Keyword(s):  
Functional Genomics ◽  
Cell Activation ◽  
Nk Cell ◽  
Cell Types ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Cpg Dinucleotides ◽  
Age Related ◽  
Gene Sets ◽  
Potential Biomarker

Abstract Background Epigenetic clocks use DNA methylation (DNAm) levels of specific sets of CpG dinucleotides to accurately predict individual chronological age. A popular application of these clocks is to explore whether the deviation of predicted age from chronological age is associated with disease phenotypes, where this deviation is interpreted as a potential biomarker of biological age. This wide application, however, contrasts with the limited insight in the processes that may drive the running of epigenetic clocks. Results We perform a functional genomics analysis on four epigenetic clocks, including Hannum’s blood predictor and Horvath’s multi-tissue predictor, using blood DNA methylome and transcriptome data from 3132 individuals. The four clocks result in similar predictions of individual chronological age, and their constituting CpGs are correlated in DNAm level and are enriched for similar histone modifications and chromatin states. Interestingly, DNAm levels of CpGs from the clocks are commonly associated with gene expression in trans. The gene sets involved are highly overlapping and enriched for T cell processes. Further analysis of the transcriptome and methylome of sorted blood cell types identifies differences in DNAm between naive and activated T and NK cells as a probable contributor to the clocks. Indeed, within the same donor, the four epigenetic clocks predict naive cells to be up to 40 years younger than activated cells. Conclusions The ability of epigenetic clocks to predict chronological age involves their ability to detect changes in proportions of naive and activated immune blood cells, an established feature of immuno-senescence. This finding may contribute to the interpretation of associations between clock-derived measures and age-related health outcomes.

scholarly journals Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex

Brain ◽  
2020 ◽  
Author(s):  
Gemma L Shireby ◽  
Jonathan P Davies ◽  
Paul T Francis ◽  
Joe Burrage ◽  
Emma M Walker ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Age Distribution ◽  
Biological Age ◽  
Supervised Machine Learning ◽  
Tissue Type ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Methylation Data ◽  
Human Cortex ◽  
Dna Methylation Age

Abstract Human DNA methylation data have been used to develop biomarkers of ageing, referred to as ‘epigenetic clocks’, which have been widely used to identify differences between chronological age and biological age in health and disease including neurodegeneration, dementia and other brain phenotypes. Existing DNA methylation clocks have been shown to be highly accurate in blood but are less precise when used in older samples or in tissue types not included in training the model, including brain. We aimed to develop a novel epigenetic clock that performs optimally in human cortex tissue and has the potential to identify phenotypes associated with biological ageing in the brain. We generated an extensive dataset of human cortex DNA methylation data spanning the life course (n = 1397, ages = 1 to 108 years). This dataset was split into ‘training’ and ‘testing’ samples (training: n = 1047; testing: n = 350). DNA methylation age estimators were derived using a transformed version of chronological age on DNA methylation at specific sites using elastic net regression, a supervised machine learning method. The cortical clock was subsequently validated in a novel independent human cortex dataset (n = 1221, ages = 41 to 104 years) and tested for specificity in a large whole blood dataset (n = 1175, ages = 28 to 98 years). We identified a set of 347 DNA methylation sites that, in combination, optimally predict age in the human cortex. The sum of DNA methylation levels at these sites weighted by their regression coefficients provide the cortical DNA methylation clock age estimate. The novel clock dramatically outperformed previously reported clocks in additional cortical datasets. Our findings suggest that previous associations between predicted DNA methylation age and neurodegenerative phenotypes might represent false positives resulting from clocks not robustly calibrated to the tissue being tested and for phenotypes that become manifest in older ages. The age distribution and tissue type of samples included in training datasets need to be considered when building and applying epigenetic clock algorithms to human epidemiological or disease cohorts.

scholarly journals A unified STR profiling system across multiple species with whole genome sequencing data

2019 ◽  
Vol 20 (S24) ◽  
Author(s):  
Yilin Liu ◽  
Jiao Xu ◽  
Miaoxia Chen ◽  
Changfa Wang ◽  
Shuaicheng Li
Keyword(s):  
Ovis Aries ◽  
Individual Identification ◽  
Whole Genome Sequence ◽  
Capra Hircus ◽  
Whole Genome Sequencing Data ◽  
Individual Species ◽  
Whole Genome ◽  
Str Loci ◽  
Str Profiling ◽  
Multiple Species

Abstract Background Short tandem repeats (STRs) serve as genetic markers in forensic scenes due to their high polymorphism in eukaryotic genomes. A variety of STRs profiling systems have been developed for species including human, dog, cat, cattle, etc. Maintaining these systems simultaneously can be costly. These mammals share many high similar regions along their genomes. With the availability of the massive amount of the whole genomics data of these species, it is possible to develop a unified STR profiling system. In this study, our objective is to propose and develop a unified set of STR loci that could be simultaneously applied to multiple species. Result To find a unified STR set, we collected the whole genome sequence data of the concerned species and mapped them to the human genome reference. Then we extracted the STR loci across the species. From these loci, we proposed an algorithm which selected a subset of loci by incorporating the optimized combined power of discrimination. Our results show that the unified set of loci have high combined power of discrimination, >1−10−9, for both individual species and the mixed population, as well as the random-match probability, <10−7 for all the involved species, indicating that the identified set of STR loci could be applied to multiple species. Conclusions We identified a set of STR loci which shared by multiple species. It implies that a unified STR profiling system is possible for these species under the forensic scenes. The system can be applied to the individual identification or paternal test of each of the ten common species which are Sus scrofa (pig), Bos taurus (cattle), Capra hircus (goat), Equus caballus (horse), Canis lupus familiaris (dog), Felis catus (cat), Ovis aries (sheep), Oryctolagus cuniculus (rabbit), and Bos grunniens (yak), and Homo sapiens (human). Our loci selection algorithm employed a greedy approach. The algorithm can generate the loci under different forensic parameters and for a specific combination of species.

scholarly journals AltumAge: A Pan-Tissue DNA-Methylation Epigenetic Clock Based on Deep Learning

2021 ◽  
Author(s):  
Lucas Paulo de Lima ◽  
Louis R Lapierre ◽  
Ritambhara Singh
Keyword(s):  
Dna Methylation ◽  
Deep Learning ◽  
Placental Tissue ◽  
Training Data ◽  
Data Sets ◽  
Epigenetic Clock ◽  
Neural Network Approach ◽  
Cpg Sites ◽  
Age Related ◽  
Model Predictions

Several age predictors based on DNA methylation, dubbed epigenetic clocks, have been created in recent years. Their accuracy and potential for generalization vary widely based on the training data. Here, we gathered 143 publicly available data sets from several human tissues to develop AltumAge, a highly accurate and precise age predictor based on deep learning. Compared to Horvath's 2013 model, AltumAge performs better across both normal and malignant tissues and is more generalizable to new data sets. Interestingly, it can predict gestational week from placental tissue with low error. Lastly, we used deep learning interpretation methods to learn which methylation sites contributed to the final model predictions. We observed that while most important CpG sites are linearly related to age, some highly-interacting CpG sites can influence the relevance of such relationships. We studied the associated genes of these CpG sites and found literary evidence of their involvement in age-related gene regulation. Using chromatin annotations, we observed that the CpG sites with the highest contribution to the model predictions were related to heterochromatin and gene regulatory regions in the genome. We also found age-related KEGG pathways for genes containing these CpG sites. In general, neural networks are better predictors due to their ability to capture complex feature interactions compared to the typically used regularized linear regression. Altogether, our neural network approach provides significant improvement and flexibility to current epigenetic clocks without sacrificing model interpretability.

scholarly journals Age-related clonal haemopoiesis is associated with increased epigenetic age

2019 ◽  
Author(s):  
Neil A. Robertson ◽  
Ian J. Deary ◽  
Kristina Kirschner ◽  
Riccardo E. Marioni ◽  
Tamir Chandra
Keyword(s):  
Somatic Mutations ◽  
Chronological Age ◽  
Accelerated Ageing ◽  
Healthy Individuals ◽  
Main Risk Factor ◽  
Cpg Sites ◽  
Age Related ◽  
Epigenetic Age ◽  
Increased Risk ◽  
Chronic Ischemic Heart Failure

Age-related clonal haemopoiesis (ARCH) in healthy individuals was initially observed through an increased skewing in X chromosome inactivation. More recently, several groups reported that ARCH is driven by somatic mutations. The most prevalent ARCH mutations are in the DNMT3A and TET2 genes, previously described as drivers of myeloid malignancies. ARCH is associated with an increased risk for haematological cancers. ARCH also confers an increased risk for non-haematological diseases such as cardiovascular disease, atherosclerosis, and chronic ischemic heart failure, for which age is a main risk factor. Whether ARCH is linked to accelerated ageing has remained unexplored. The most accurate and commonly-used tools to measure age acceleration are epigenetic clocks. They are based on age-related methylation differences at specific CpG sites correlating chronological age accurately with epigenetic age. Deviations from chronological age towards an increased epigenetic age have been associated with increased risk of earlier mortality and age-related morbidities. Here we present evidence of accelerated epigenetic age in individuals with ARCH.

scholarly journals Castration delays epigenetic aging and feminises DNA methylation at androgen-regulated loci

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Victoria J Sugrue ◽  
Joseph Alan Zoller ◽  
Pritika Narayan ◽  
Ake T Lu ◽  
Oscar J Ortega-Recalde ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Mammalian Species ◽  
Absolute Error ◽  
Ovis Aries ◽  
Receptor Expression ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Aging Rate ◽  
Cpg Dinucleotides ◽  
Mouse Tissues

In mammals, females generally live longer than males. Nevertheless, the mechanisms underpinning sex-dependent longevity are currently unclear. Epigenetic clocks are powerful biological biomarkers capable of precisely estimating chronological age and identifying novel factors influencing the aging rate using only DNA methylation data. In this study, we developed the first epigenetic clock for domesticated sheep (Ovis aries), which can predict chronological age with a median absolute error of 5.1 months. We have discovered that castrated male sheep have a decelerated aging rate compared to intact males, mediated at least in part by the removal of androgens. Furthermore, we identified several androgen-sensitive CpG dinucleotides that become progressively hypomethylated with age in intact males, but remain stable in castrated males and females. Comparable sex-specific methylation differences in MKLN1 also exist in bat skin and a range of mouse tissues that have high androgen receptor expression, indicating it may drive androgen-dependent hypomethylation in divergent mammalian species. In characterising these sites, we identify biologically plausible mechanisms explaining how androgens drive male-accelerated aging.

scholarly journals Castration delays epigenetic aging and feminises DNA methylation at androgen-regulated loci

2020 ◽  
Author(s):  
VJ Sugrue ◽  
JA Zoller ◽  
P Narayan ◽  
AT Lu ◽  
OJ Ortega-Recalde ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Mammalian Species ◽  
Accelerated Aging ◽  
Absolute Error ◽  
Ovis Aries ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Mouse Muscle ◽  
Aging Rate ◽  
Cpg Dinucleotides

SUMMARYIn mammals, females generally live longer than males. Nevertheless, the mechanisms underpinning sex-dependent longevity are currently unclear. Epigenetic clocks are powerful biological biomarkers capable of precisely estimating chronological age using only DNA methylation data. These clocks have been used to identify novel factors influencing the aging rate, but few studies have examined the performance of epigenetic clocks in divergent mammalian species. In this study, we developed the first epigenetic clock for domesticated sheep (Ovis aries), and using 185 CpG sites can predict chronological age with a median absolute error of 5.1 months from ear punch and blood samples. We have discovered that castrated male sheep have a decelerated aging rate compared to intact males, mediated at least in part by the removal of androgens. Furthermore, we identified several androgen-sensitive CpG dinucleotides that become progressively hypomethylated with age in intact males, but remain stable in castrated males and females. Many of these androgen sensitive demethylating sites are regulatory in nature and located in genes with known androgen-dependent regulation, such as MKLN1, LMO4 and FN1. Comparable sex-specific methylation differences in MKLN1 also exist in mouse muscle (p=0.003) but not blood, indicating that androgen dependent demethylation exists in multiple mammalian groups, in a tissue-specific manner. In characterising these sites, we identify biologically plausible mechanisms explaining how androgens drive male-accelerated aging.

scholarly journals Deconvolution of the epigenetic age discloses distinct inter-personal variability in epigenetic aging patterns

2021 ◽  
Author(s):  
Tamar Shahal ◽  
Elad Segev ◽  
Thomas Konstantinovsky ◽  
Yonit Marcus ◽  
Gabi Shefer ◽  
...  
Keyword(s):  
Healthy Subjects ◽  
Interindividual Variability ◽  
Chronological Age ◽  
Biological Aging ◽  
Epigenetic Clock ◽  
Cpg Sites ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
Shed Light

Epigenetic age not only correlates with chronological age but predicts morbidity and mortality. We assumed that deconvolution of epigenetic age to its individual components could shed light on the diversity of epigenetic, and by inference, biological aging. Using the Horvath original epigenetic clock, we identified several CpG sites linked to distinct genes that quantitatively explain much of the interpersonal variability in epigenetic aging, with secretagogin and malin showing the most dominant effects. The analysis shows that the same epigenetic age for any given chronological age can be accounted for by variable contributions of identifiable CpG sites; that old epigenetic relative to chronological age is mostly explained by the same CpG sites, mapped to genes showing the highest interindividual variability differences in healthy subjects but not in subjects with type 2 diabetes. This paves the way to form personalized aging cards indicating the sources of accelerated/decelerated epigenetic aging in each examinee, en route to targeting specific sites as indicators, and perhaps treatment targets of personal undesirable age drifting.

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