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 Multi-tissue DNA methylation age predictor in mouse

2017 ◽  
Author(s):  
Thomas M. Stubbs ◽  
Marc Jan Bonder ◽  
Anne-Katrien Stark ◽  
Felix Krueger ◽  
Ferdinand von Meyenn ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Absolute Error ◽  
Biological Age ◽  
Epigenetic Clock ◽  
Cpg Sites ◽  
Mouse Tissues ◽  
Wide Range ◽  
Dna Methylation Age ◽  
The Impact

AbstractBackgroundDNA-methylation changes at a discrete set of sites in the human genome are predictive of chronological and biological age. However, it is not known whether these changes are causative or a consequence of an underlying ageing process. It has also not been shown whether this ‘epigenetic clock’ is unique to humans or conserved in the more experimentally tractable mouse.ResultsWe have generated a comprehensive set of genome-scale base-resolution methylation maps from multiple mouse tissues spanning a wide range of ages. Many CpG sites show significant tissue-independent correlations with age and allowed us to develop a multi-tissue predictor of age in the mouse. Our model, which estimates age based on DNA methylation at 329 unique CpG sites, has a median absolute error of 3.33 weeks, and has similar properties to the recently described human epigenetic clock. Using publicly available datasets, we find that the mouse clock is accurate enough to measure effects on biological age, including in the context of interventions. While females and males show no significant differences in predicted DNA methylation age, ovariectomy results in significant age acceleration in females. Furthermore, we identify significant differences in age-acceleration dependent on the lipid content of the offspring diet.ConclusionsHere we identify and characterize an epigenetic predictor of age in mice, the mouse epigenetic clock. This clock will be instrumental for understanding the biology of ageing and will allow modulation of its ticking rate and resetting the clock in vivo to study the impact on biological age.

scholarly journals Epigenetic clock and DNA methylation studies of roe deer in the wild

2020 ◽  
Author(s):  
Jean-François Lemaître ◽  
Benjamin Rey ◽  
Jean-Michel Gaillard ◽  
Corinne Régis ◽  
Emmanuelle Gilot ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Evolutionary Biology ◽  
Roe Deer ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Aging Effects ◽  
Methylation Array ◽  
Biomarkers Of Aging ◽  
Epigenetic Age ◽  
The Relationship

AbstractDNA methylation-based biomarkers of aging (epigenetic clocks) promise to lead to new insights in the evolutionary biology of ageing. Relatively little is known about how the natural environment affects epigenetic aging effects in wild species. In this study, we took advantage of a unique long-term (>40 years) longitudinal monitoring of individual roe deer (Capreolus capreolus) living in two wild populations (Chizé and Trois Fontaines, France) facing different ecological contexts to investigate the relationship between chronological age and levels of DNA methylation (DNAm). We generated novel DNA methylation data from n=90 blood samples using a custom methylation array (HorvathMammalMethylChip40). We present three DNA methylation-based estimators of age (DNAm or epigenetic age), which were trained in males, females, and both sexes combined. We investigated how sex differences influenced the relationship between DNAm age and chronological age through the use of sex-specific epigenetic clocks. Our results highlight that both populations and sex influence the epigenetic age, with the bias toward a stronger male average age acceleration (i.e. differences between epigenetic age and chronological ages) particularly pronounced in the population facing harsh environmental conditions. Further, we identify the main sites of epigenetic alteration that have distinct aging patterns across the two sexes. These findings open the door to promising avenues of research at the crossroad of evolutionary biology and biogerontology.

scholarly journals Pair bonding slows epigenetic aging and alters methylation in brains of prairie voles

2020 ◽  
Author(s):  
Lindsay L. Sailer ◽  
Amin Haghani ◽  
Joseph A. Zoller ◽  
Caesar Z. Li ◽  
Alexander G. Ophir ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Brain Tissue ◽  
Association Studies ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Pair Bonding ◽  
Prairie Voles ◽  
Relative Age ◽  
Biomarkers Of Aging ◽  
Epigenetic Aging

ABSTRACTThe quality of romantic relationships can be predictive of health consequences related to aging. DNA methylation-based biomarkers of aging have been developed for humans and many other mammals and could be used to assess how pair bonding impacts aging. Prairie voles (Microtus ochrogaster) have emerged as a model to study social attachment among adult pairs. Here we describe DNA methylation-based estimators of age for prairie voles based on novel DNA methylation data generated on highly conserved mammalian CpGs measured with a custom array. The multi-tissue epigenetic clock for voles was trained on 3 tissue sources (ear, liver, and samples of brain tissue from within the pair bonding circuit). A novel dual species human-vole clock accurately measured relative age defined as the ratio of chronological age to maximum age. According to the human-vole clock of relative age, sexually inexperienced voles exhibit accelerated epigenetic aging in brain tissue (p = 0.02) when compared to pair bonded animals of the same chronological age. Epigenome wide association studies identified CpGs in four genes that were strongly associated with pair bonding across the three tissue types (brain, ear, and liver): Hnrnph1, Fancl, Fam13b, and Fzd1. Further, four CpGs (near the Bmp4 exon, Eif4g2 3 prime UTR, Robo1 exon, and Nfat5 intron) exhibited a convergent methylation change between pair bonding and aging. This study describes highly accurate DNA methylation-based estimators of age in prairie voles and provides evidence that pair bonding status modulates the methylome.

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 Determining the human chronological age from the blood samples on the basis of the analysis of CpG-dinucleotides methylation

2021 ◽  
Vol 65 (5) ◽  
pp. 582-591
Author(s):  
V. A. Lemesh ◽  
V. N. Kipen ◽  
M. V. Bahdanava ◽  
A. A. Burakova ◽  
A. A. Bulgak ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Correlation Coefficients ◽  
Chronological Age ◽  
Blood Samples ◽  
Cpg Dinucleotides ◽  
Human Dna ◽  
Genome Wide ◽  
Average Accuracy ◽  
The Republic ◽  
Age Prediction

Based on the bioinformatic and statistical analysis of the GEO-projects to determine the genome-wide profile of human DNA methylation, a list of 27 CpG dinucleotides with a high predictive potential was formed to create models for prediction of the human age from blood samples. The methylation level was determined for 245 samples of individuals from the Republic of Belarus. The correlation coefficients R were calculated, and the mathematical models for determining the age of an individual were constructed. The average accuracy value of the age prediction from blood samples using 12 CpG-dinucleotides was 3.4 years (for men – 3.3, for women – 3.5). The results obtained will be used as a basis for development of calculators for predicting the age of an individual based on the biological traces for forensic experts.

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.

Abstract MP99: Cerebral Small Vessel Disease and the Epigenetic Clock: The Atherosclerosis Risk in Communities Study

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Abhay Raina ◽  
Xiaoping Zhao ◽  
Jan Bressler ◽  
Rebecca F Gottesman ◽  
Megan L Grove ◽  
...  
Keyword(s):  
Risk Factors ◽  
Dna Methylation ◽  
Small Vessel Disease ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Atherosclerosis Risk In Communities ◽  
Vessel Disease ◽  
Epigenetic Aging ◽  
Atherosclerosis Risk ◽  
Aric Study

Cerebral small vessel disease (SVD) is one of the most common degenerative vessel disorders of the aging brain. White matter hyperintensities (WMH) on magnetic resonance imaging (MRI) are viewed as typical markers of SVD and are associated with an increased risk of stroke, dementia, and death. Advancing age is the strongest predictor of WMH prevalence and severity. Recent studies have developed a novel biomarker of aging, termed “epigenetic clock”, based on DNA methylation levels at specific sites across the genome, which are strongly correlated with chronological age. The deviation of the DNA methylation (DNAm)-predicted age from the chronological age, defined as “age acceleration”, is used as an index of an individual’s rate of aging. Here, we estimated blood DNAm age in African-Americans from the Atherosclerosis Risk in Communities (ARIC) study using two methodologies, and examined the cross-sectional association between WMH on MRI and measures of accelerated epigenetic aging. We hypothesized that DNAm age acceleration, defined as the residual value from the regression of the predicted DNAm age onto chronological age, is associated with greater WMH burden independently of chronological age and other known risk factors, including sex, body mass index, systolic blood pressure, hypertension, diabetes, and current smoking. DNA methylation was measured using the Illumina HM450 array on genomic DNA extracted from blood samples of African-American participants of the ARIC study. We estimated DNAm age using two published algorithms in 713 individuals aged 51-73 with both DNAm and brain MRI data. Linear regression models were used to estimate the association of the natural log-transformed WMH burden with each measure of age acceleration adjusting for covariates. Age acceleration was significantly associated with WMH burden and results were similar for both estimates of DNAm age. Each unit increase in WMH burden (on the log scale) was associated with a 1.2 and 1.3 year increase in DNAm age after accounting for chronological age and other known risk factors (P=0.01 and 0.004). Further adjustment for blood cell composition did not meaningfully change these results. In this population-based study of middle-aged to older African-American adults, we report evidence of an association between accelerated epigenetic aging of blood and increased WMH burden, independent of known risk factors, including chronologic age. Additional studies are ongoing to clarify whether DNAm age is simply a marker of the rate of aging or reflects biological mechanisms implicated in the aging of the cerebral white matter.

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 Dysfunctional epigenetic aging of the normal colon and colorectal cancer risk

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Ting Wang ◽  
Sean K. Maden ◽  
Georg E. Luebeck ◽  
Christopher I. Li ◽  
Polly A. Newcomb ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Risk Group ◽  
Risk Groups ◽  
Biological Age ◽  
Chronological Age ◽  
Epigenetic Clock ◽  
Normal Colon ◽  
Epigenetic Aging ◽  
Epigenetic Age ◽  
Epigenetic Age Acceleration

Abstract Background Chronological age is a prominent risk factor for many types of cancers including colorectal cancer (CRC). Yet, the risk of CRC varies substantially between individuals, even within the same age group, which may reflect heterogeneity in biological tissue aging between people. Epigenetic clocks based on DNA methylation are a useful measure of the biological aging process with the potential to serve as a biomarker of an individual’s susceptibility to age-related diseases such as CRC. Methods We conducted a genome-wide DNA methylation study on samples of normal colon mucosa (N = 334). Subjects were assigned to three cancer risk groups (low, medium, and high) based on their personal adenoma or cancer history. Using previously established epigenetic clocks (Hannum, Horvath, PhenoAge, and EpiTOC), we estimated the biological age of each sample and assessed for epigenetic age acceleration in the samples by regressing the estimated biological age on the individual’s chronological age. We compared the epigenetic age acceleration between different risk groups using a multivariate linear regression model with the adjustment for gender and cell-type fractions for each epigenetic clock. An epigenome-wide association study (EWAS) was performed to identify differential methylation changes associated with CRC risk. Results Each epigenetic clock was significantly correlated with the chronological age of the subjects, and the Horvath clock exhibited the strongest correlation in all risk groups (r > 0.8, p < 1 × 10−30). The PhenoAge clock (p = 0.0012) revealed epigenetic age deceleration in the high-risk group compared to the low-risk group. Conclusions Among the four DNA methylation-based measures of biological age, the Horvath clock is the most accurate for estimating the chronological age of individuals. Individuals with a high risk for CRC have epigenetic age deceleration in their normal colons measured by the PhenoAge clock, which may reflect a dysfunctional epigenetic aging process.

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