The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936

Background: The DNA methylation-based 'epigenetic clock' correlates strongly with chronological age, but it is currently unclear what drives individual differences. We examine cross-sectional and longitudinal associations between the epigenetic clock and four mortality-linked markers of physical and mental fitness: lung function, walking speed, grip strength and cognitive ability. Methods: DNA methylation-based age acceleration (residuals of the epigenetic clock estimate regressed on chronological age) were estimated in the Lothian Birth Cohort 1936 at ages 70 (n=920), 73 (n=299) and 76 (n=273) years. General cognitive ability, walking speed, lung function and grip strength were measured concurrently. Cross-sectional correlations between age acceleration and the fitness variables were calculated. Longitudinal change in the epigenetic clock estimates and the fitness variables were assessed via linear mixed models and latent growth curves. Epigenetic age acceleration at age 70 was used as a predictor of longitudinal change in fitness. Epigenome-wide association studies (EWASs) were conducted on the four fitness measures. Results: Cross-sectional correlations were significant between greater age acceleration and poorer performance on the lung function, cognition and grip strength measures (r range: -0.07 to -0.05, P range: 9.7 x 10 to 0.024). All of the fitness variables declined over time but age acceleration did not correlate with subsequent change over 6 years. There were no EWAS hits for the fitness traits. Conclusions: Markers of physical and mental fitness are associated with the epigenetic clock (lower abilities associated with age acceleration). However, age acceleration does not associate with decline in these measures, at least over a relatively short follow-up

Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment

Background: Global but predictable changes impact the DNA methylome as we age, acting as a type of molecular clock. This clock can be hastened by conditions that decrease lifespan, raising the question of whether it can also be slowed, for example, by conditions that increase lifespan. Mice are particularly appealing organisms for studies of mammalian aging; however, epigenetic clocks have thus far been formulated only in humans. Results: We first examined whether mice and humans experience similar patterns of change in the methylome with age. We found moderate conservation of CpG sites for which methylation is altered with age, with both species showing an increase in methylome disorder during aging. Based on this analysis, we formulated an epigenetic-aging model in mice using the liver methylomes of 107 mice from 0.2 to 26.0 months old. To examine whether epigenetic aging signatures are slowed by longevity-promoting interventions, we analyzed 28 additional methylomes from mice subjected to lifespan-extending conditions, including Prop1df/df dwarfism, calorie restriction or dietary rapamycin. We found that mice treated with these lifespan-extending interventions were significantly younger in epigenetic age than their untreated, wild-type age-matched controls. Conclusions: This study shows that lifespan-extending conditions can slow molecular changes associated with an epigenetic clock in mice livers

Epigenetic clock as a correlate of anxiety

DNA methylation changes consistently throughout life and age-dependent alterations in DNA methylation can be used to estimate one’s epigenetic age. Post-mortem studies revealed higher epigenetic age in brains of patients with major depressive disorder, as compared with controls. Since MDD is highly correlated with anxiety, we hypothesized that symptoms of anxiety, as well as lower volume of grey matter (GM) in depression-related cortical regions, will be associated with faster epigenetic clock in a community-based sample of young adults. Participants included 88 young adults (53% men; 23–24 years of age) from the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) who participated in its neuroimaging follow-up and provided saliva samples for epigenetic analysis. Epigenetic age was calculated according to Horvath (Horvath, 2013). Women had slower epigenetic clock than men (Cohen’s d = 0.48). In women (but not men), slower epigenetic clock was associated with less symptoms of anxiety. In the brain, women (but not men) with slower epigenetic clock had greater GM volume in the cerebral cortex (brain size-corrected; R2 = 0.07). Lobe-specific analyses showed that in women (but not men), slower epigenetic clock was associated with greater GM volume in frontal lobe (R2 = 0.16), and that GM volume in frontal lobe mediated the relationship between the speed of epigenetic clock and anxiety trait (ab = 0.15, SE = 0.15, 95% CI [0.007; 0.369]). These findings were not replicated, however, in a community-based sample of adolescents (n = 129; 49% men; 12–19 years of age), possibly due to the different method of tissue collection (blood vs. saliva) or additional sources of variability in the cohort of adolescents (puberty stages, socioeconomic status, prenatal exposure to maternal smoking during pregnancy)

Epigenetic Control of Circadian Clock Operation during Development

The molecular players of circadian clock oscillation have been identified and extensively characterized. The epigenetic mechanisms behind the circadian gene expression control has also been recently studied, although there are still details to be illucidated. In this review, we briefly summarize the current understanding of the mammalian clock. We also provide evidence for the lack of circadian oscillation in particular cell types. As the circadian clock has intimate interaction with the various cellular functions in different type of cells, it must have plasticity and specicity in its operation within different epigenetic environments. The lack of circadian oscillation in certain cells provide an unique opportunity to study the required epigenetic environment in the cell that permit circadian oscillation and to idenfify key influencing factors for proper clock function. How epigenetic mechansims, including DNA methylaiton and chromatin modifications, participate in control of clock oscillation still awaits future studies at the genomic scale

An epigenetic clock for human skeletal muscle.

BACKGROUND: Ageing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan-tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue. METHODS: To address this, we developed a more accurate, muscle-specific epigenetic clock based on the genome-wide DNA methylation data of 682 skeletal muscle samples from 12 independent datasets (18-89 years old, 22% women, 99% Caucasian), all generated with Illumina HumanMethylation (HM) arrays (HM27, HM450, or HMEPIC). We also took advantage of the large number of samples to conduct an epigenome-wide association study of age-associated DNA methylation patterns in skeletal muscle. RESULTS: The newly developed clock uses 200 cytosine-phosphate-guanine dinucleotides to estimate chronological age in skeletal muscle, 16 of which are in common with the 353 cytosine-phosphate-guanine dinucleotides of the pan-tissue clock. The muscle clock outperformed the pan-tissue clock, with a median error of only 4.6 years across datasets (vs. 13.1 years for the pan-tissue clock, P < 0.0001) and an average correlation of ρ = 0.62 between actual and predicted age across datasets (vs. ρ = 0.51 for the pan-tissue clock). Lastly, we identified 180 differentially methylated regions with age in skeletal muscle at a false discovery rate < 0.005. However, gene set enrichment analysis did not reveal any enrichment for gene ontologies. CONCLUSIONS: We have developed a muscle-specific epigenetic clock that predicts age with better accuracy than the pan-tissue clock. We implemented the muscle clock in an r package called Muscle Epigenetic Age Test available on Bioconductor to estimate epigenetic age in skeletal muscle samples. This clock may prove valuable in assessing the impact of environmental factors, such as exercise and diet, on muscle-specific biological ageing processes

Screening for genes that accelerate the epigenetic aging clock in humans reveals a role for the H3K36 methyltransferase NSD1

Background: Epigenetic clocks are mathematical models that predict the biological age of an individual using DNA methylation data and have emerged in the last few years as the most accurate biomarkers of the aging process. However, little is known about the molecular mechanisms that control the rate of such clocks. Here, we have examined the human epigenetic clock in patients with a variety of developmental disorders, harboring mutations in proteins of the epigenetic machinery. Results: Using the Horvath epigenetic clock, we perform an unbiased screen for epigenetic age acceleration in the blood of these patients. We demonstrate that loss-of-function mutations in the H3K36 histone methyltransferase NSD1, which cause Sotos syndrome, substantially accelerate epigenetic aging. Furthermore, we show that the normal aging process and Sotos syndrome share methylation changes and the genomic context in which they occur. Finally, we found that the Horvath clock CpG sites are characterized by a higher Shannon methylation entropy when compared with the rest of the genome, which is dramatically decreased in Sotos syndrome patients. Conclusions: These results suggest that the H3K36 methylation machinery is a key component of the epigenetic maintenance system in humans, which controls the rate of epigenetic aging, and this role seems to be conserved in model organisms. Our observations provide novel insights into the mechanisms behind the epigenetic aging clock and we expect will shed light on the different processes that erode the human epigenetic landscape during aging

Screening for genes that accelerate the epigenetic aging clock in humans reveals a role for the H3K36 methyltransferase NSD1.

BACKGROUND: Epigenetic clocks are mathematical models that predict the biological age of an individual using DNA methylation data and have emerged in the last few years as the most accurate biomarkers of the aging process. However, little is known about the molecular mechanisms that control the rate of such clocks. Here, we have examined the human epigenetic clock in patients with a variety of developmental disorders, harboring mutations in proteins of the epigenetic machinery. RESULTS: Using the Horvath epigenetic clock, we perform an unbiased screen for epigenetic age acceleration in the blood of these patients. We demonstrate that loss-of-function mutations in the H3K36 histone methyltransferase NSD1, which cause Sotos syndrome, substantially accelerate epigenetic aging. Furthermore, we show that the normal aging process and Sotos syndrome share methylation changes and the genomic context in which they occur. Finally, we found that the Horvath clock CpG sites are characterized by a higher Shannon methylation entropy when compared with the rest of the genome, which is dramatically decreased in Sotos syndrome patients. CONCLUSIONS: These results suggest that the H3K36 methylation machinery is a key component of the epigenetic maintenance system in humans, which controls the rate of epigenetic aging, and this role seems to be conserved in model organisms. Our observations provide novel insights into the mechanisms behind the epigenetic aging clock and we expect will shed light on the different processes that erode the human epigenetic landscape during aging

Inverse relationship between genetic diversity and epigenetic complexity

Early studies of molecular evolution revealed a correlation between genetic distance and time of species divergence. This observation provoked the molecular clock hypothesis and in turn the &#x2018;Neutral Theory&#x2019;, which however remains an incomplete explanation since it predicts a constant mutation rate per generation whereas empirical evidence suggests a constant rate per year. Data inconsistent with the molecular clock hypothesis have steadily accumulated in recent years that show no correlation between genetic distance and time of divergence. It has therefore become a challenge to find a testable idea that can reconcile the seemingly conflicting data sets. Here, an inverse relationship between genetic diversity and epigenetic complexity was deduced from a simple intuition in building complex systems. Genetic diversity, i.e., genetic distance or dissimilarity in DNA or protein sequences between individuals or species, is restricted by the complexity of epigenetic programs. This inverse relationship logically deduces the maximum genetic diversity hypothesis, which suggests that macroevolution from simple to complex organisms involves a punctuational increase in epigenetic complexity that in turn causes a punctuational loss in genetic diversity. The hypothesis explains a diverse set of biological phenomena, including both for and against the correlation between genetic distance and time of divergence.&#xd;&#xa

Exploring the Relationship of Relative Telomere Length and the Epigenetic Clock in the LipidCardio Cohort

Telomere length has been accepted widely as a biomarker of aging. Recently, a novel candidate biomarker has been suggested to predict an individual’s chronological age with high accuracy: The epigenetic clock is based on the weighted DNA methylation (DNAm) fraction of a number of cytosine-phosphate-guanine sites (CpGs) selected by penalized regression analysis. Here, an established methylation-sensitive single nucleotide primer extension method was adapted, to estimate the epigenetic age of the 1005 participants of the LipidCardio Study, a patient cohort characterised by high prevalence of cardiovascular disease, based on a seven CpGs epigenetic clock. Furthermore, we measured relative leukocyte telomere length (rLTL) to assess the relationship between the established and the promising new measure of biological age. Both rLTL (0.79 ± 0.14) and DNAm age (69.67 ± 7.27 years) were available for 773 subjects (31.6% female; mean chronological age= 69.68 ± 11.01 years; mean DNAm age acceleration = −0.01 ± 7.83 years). While we detected a significant correlation between chronological age and DNAm age (n = 779, R = 0.69), we found neither evidence of an association between rLTL and the DNAm age (β = 3.00, p = 0.18) nor rLTL and the DNAm age acceleration (β = 2.76, p = 0.22) in the studied cohort, suggesting that DNAm age and rLTL measure different aspects of biological age

Epigenetic ageing accelerates before antiretroviral therapy and decelerates after viral suppression in people with HIV in Switzerland: a longitudinal study over 17 years

BACKGROUND: Accelerated epigenetic ageing can occur in untreated HIV infection and is partially reversible with effective antiretroviral therapy (ART). We aimed to make a long-term comparison of epigenetic ageing dynamics in people with HIV during untreated HIV infection and during suppressive ART. METHODS: In this longitudinal study, conducted over 17 years in HIV outpatient clinics in Switzerland, we applied 5 established epigenetic age estimators (epigenetic clocks) in peripheral blood mononuclear cells (PBMCs) in Swiss HIV Cohort Study participants before or during suppressive ART. All participants had a longitudinal set of PBMC samples available at four timepoints (T1-T4). T1 and T2 had to be 3 years or longer apart, as did T3 and T4. We assessed epigenetic age acceleration (EAA) and a novel rate of epigenetic ageing. FINDINGS: Between March 13, 1990, and Jan 18, 2018, we recruited 81 people with HIV from the Swiss HIV Cohort Study. We excluded one participant because a sample did not meet quality checks (transmission error). 52 (65%) of 80 patients were men, 76 (95%) were white, and the median patient age was 43 (IQR 37·5-47) years. Per year of untreated HIV infection (median observation 8·08 years, IQR 4·83-11·09), mean EAA was 0·47 years (95% CI 0·37 to 0·57) for Horvath's clock, 0·43 years (0·3 to 0·57) for Hannum's clock, 0·36 years (0·27 to 0·44) for SkinBlood clock, and 0·69 years (0·51 to 0·86) for PhenoAge. Per year of suppressive ART (median observation 9·8 years, IQR 7·2-11), mean EAA was -0·35 years (95% CI -0·44 to -0·27) for Horvath's clock, -0·39 years (-0·50 to -0·27) for Hannum's clock, -0·26 years (-0·33 to -0·18) for SkinBlood clock, and -0·49 years (-0·64 to -0·35) for PhenoAge. Our findings indicate that people with HIV epigenetically aged by a mean of 1·47 years for Horvath's clock, 1·43 years for Hannum's clock, 1·36 years for SkinBlood clock, and 1·69 years for PhenoAge per year of untreated HIV infection; and 0·65 years for Horvath's clock, 0·61 years for Hannum's clock, 0·74 years for SkinBlood clock, and 0·51 years for PhenoAge, per year of suppressive ART. GrimAge showed some change in the mean EAA during untreated HIV infection (0·10 years, 0·02 to 0·19) and suppressive ART (-0·05 years, -0·12 to 0·02). We obtained very similar results using the rate of epigenetic ageing. Contribution of multiple HIV-related, antiretroviral, and immunological variables, and of a DNA methylation-associated polygenic risk score to EAA was small. INTERPRETATION: In a longitudinal study over more than 17 years, epigenetic ageing accelerated during untreated HIV infection and decelerated during suppressive ART, highlighting the importance of limiting the duration of untreated HIV infection