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

Back to the future: Epigenetic clock plasticity towards healthy aging

Aging is the most important risk factor for major human lifestyle diseases, including cancer, neurological and cardiometabolic disorders. Due to the complex interplay between genetics, lifestyle and environmental factors, some individuals seem to age faster than others, whereas centenarians seem to have a slower aging process. Therefore, a biochemical biomarker reflecting the relative biological age would be helpful to predict an individual's health status and aging disease risk. Although it is already known for years that cumulative epigenetic changes occur upon aging, DNA methylation patterns were only recently used to construct an epigenetic clock predictor for biological age, which is a measure of how well your body functions compared to your chronological age. Moreover, the epigenetic DNA methylation clock signature is increasingly applied as a biomarker to estimate aging disease susceptibility and mortality risk. Finally, the epigenetic clock signature could be used as a lifestyle management tool to monitor healthy aging, to evaluate preventive interventions against chronic aging disorders and to extend healthy lifespan. Dissecting the mechanism of the epigenetic aging clock will yield valuable insights into the aging process and how it can be manipulated to improve health span.

The epigenetic clock and objectively measured sedentary and walking behavior in older adults: the Lothian Birth Cohort 1936

Background

Estimates of biological age derived from DNA-methylation patterns-known as the epigenetic clock-are associated with mortality, physical and cognitive function, and frailty, but little is known about their relationship with sedentary behavior or physical activity. We investigated the cross-sectional relationship between two such estimates of biological age and objectively measured sedentary and walking behavior in older people.

Methods

Participants were 248 members of the Lothian Birth Cohort 1936. At age 79 years, sedentary behavior and physical activity were measured over 7 days using an activPAL activity monitor. Biological age was estimated using two measures of DNA methylation-based age acceleration-i.e., extrinsic and intrinsic epigenetic age acceleration. We used linear regression to assess the relationship between these two estimates of biological age and average daily time spent sedentary, number of sit-to-stand transitions, and step count.

Results

Of the six associations examined, only two were statistically significant in initial models adjusted for age and sex alone. Greater extrinsic age acceleration was associated with taking fewer steps (regression coefficient (95% CI) - 0.100 (- 0.008, - 0.001), and greater intrinsic age acceleration was associated with making more sit-to-stand transitions (regression coefficient (95% CI) 0.006 (0.0001, 0.012). When we controlled for multiple statistical testing, neither of these associations survived correction (both P ≥ 0.17).

Conclusion

In this cross-sectional study of 79-year-olds, we found no convincing evidence that biological age, as indexed by extrinsic or intrinsic epigenetic age acceleration, was associated with objectively measured sedentary or walking behavior.

Relationship of tobacco smoking and smoking-related DNA methylation with epigenetic age acceleration

Recent studies have identified biomarkers of chronological age based on DNA methylation levels. Since active smoking contributes to a wide spectrum of aging-related diseases in adults, this study intended to examine whether active smoking exposure could accelerate the DNA methylation age in forms of age acceleration (AA, residuals of the DNA methylation age estimate regressed on chronological age). We obtained the DNA methylation profiles in whole blood samples by Illumina Infinium Human Methylation450 Beadchip array in two independent subsamples of the ESTHER study and calculated their DNA methylation ages by two recently proposed algorithms. None of the self-reported smoking indicators (smoking status, cumulative exposure and smoking cessation time) or serum cotinine levels was significantly associated with AA. On the contrary, we successfully confirmed that 66 out of 150 smoking-related CpG sites were associated with AA, even after correction for multiple testing (FDR <0.05). We further built a smoking index (SI) based on these loci and demonstrated a monotonic dose-response relationship of this index with AA. In conclusion, DNA methylation-based biological indicators for current and past smoking exposure, but not self-reported smoking information or serum cotinine levels, were found to be related to DNA methylation defined AA. Further research should address potential mechanisms underlying the observed patterns, such as potential reflections of susceptibility to environmental hazards in both smoking related methylation changes and methylation defined AA.

DNA methylation age and perceived age in elderly Danish twins

Perceived age is an easily accessible biomarker of aging. Here, we studied its relation to DNA methylation age (DNAm age) as introduced in (Horvath, 2013) in 180 elderly Danish twins. We found perceived age and DNAm age to be associated with chronological age (P=0.04 resp. P=2.2e-10) when correcting for gender, but did not see an association between perceived age and DNAm age (P=0.44). Intrapair-analysis showed that the proportion of pairs where the twin with the highest perceived age also had the highest DNAm age was not different from 0.5 (P=1), and we did not see a trend when dividing pairs according to their difference in perceived age (P=0.36). Hence, intrapair analysis did not reveal links between perceived age and DNAm age. Moreover, none of the 353 CpGs underlying DNAm age was individually associated with perceived age after correction for multiple-testing (P>6e-4, FDR>0.21). Finally, when constructing an epigenetic signature based on these CpGs to predict perceived age, we only found a correlation of 0.18 (95%CI: -0.06 to 0.40) and a mean square error of 13.6 years2 between observed and predicted values in the test dataset, indicating poor predictive strength. Altogether, our results suggest that perceived age and DNAm age capture different aging aspects.

Healthy cognitive ageing in the Lothian Birth Cohort studies: marginal gains not magic bullet

In the face of shifting demographics and an increase in human longevity, it is important to examine carefully what is known about cognitive ageing, and to identify and promote possibly malleable lifestyle and health-related factors that might mitigate age-associated cognitive decline. The Lothian Birth Cohorts of 1921 (LBC1921, n = 550) and 1936 (LBC1936, n = 1091) are longitudinal studies of cognitive and brain ageing based in Scotland. Childhood IQ data are available for these participants, who were recruited in later life and then followed up regularly. This overview summarises some of the main LBC findings to date, illustrating the possible genetic and environmental contributions to cognitive function (level and change) and brain imaging biomarkers in later life. Key associations include genetic variation, health and fitness, psychosocial and lifestyle factors, and aspects of the brain's structure. It addresses some key methodological issues such as confounding by early-life intelligence and social factors and emphasises areas requiring further investigation. Overall, the findings that have emerged from the LBC studies highlight that there are multiple correlates of cognitive ability level in later life, many of which have small effects, that there are as yet few reliable predictors of cognitive change, and that not all of the correlates have independent additive associations. The concept of marginal gains, whereby there might be a cumulative effect of small incremental improvements across a wide range of lifestyle and health-related factors, may offer a useful way to think about and promote a multivariate recipe for healthy cognitive and brain ageing.

Accelerated DNA Methylation Age: Associations With Posttraumatic Stress Disorder and Mortality

OBJECTIVE

Recently developed indices of cellular age based on DNA methylation (DNAm) data, referred to as DNAm age, are being used to study factors that influence the rate of aging and the health correlates of these metrics of the epigenetic clock. This study evaluated associations between trauma exposure, posttraumatic stress disorder (PTSD) symptoms, and accelerated versus decelerated DNAm age among military veterans. We also examined whether accelerated DNAm age predicted mortality over the course of a 6.5-year medical record review period.

METHODS

Three hundred thirty-nine genotype-confirmed white, non-Hispanic, middle-aged, trauma-exposed veterans underwent psychiatric assessment and genome-wide DNAm analysis. DNAm age was calculated using a previously validated algorithm. Medical records were available for a subset of 241 veterans and were reviewed approximately 6.5 years after DNA collection and PTSD assessment.

RESULTS

PTSD hyperarousal symptoms were associated with accelerated DNAm age (β = 0.20, p = .009) but trauma exposure and total PTSD severity were not. Accelerated DNAm age was also associated with 13% increased risk for all-cause mortality (hazard ratio = 1.13, 95% confidence interval = 1.01-1.26) during the medical record review period.

CONCLUSIONS

Findings of this study replicate the association between PTSD and accelerated DNAm age and suggest that this effect may be specific to the hyperarousal symptom cluster. Results point to the potential utility of DNAm age algorithms for identifying individuals who are aging at an accelerated rate and for determining the factors that influence this process.

Change in the Rate of Biological Aging in Response to Caloric Restriction: CALERIE Biobank Analysis

Biological aging measures have been proposed as proxies for extension of healthy life span in trials of geroprotective therapies that aim to slow aging. Several methods to measure biological aging show promise but it is not known if these methods are sensitive to changes caused by geroprotective therapy. We conducted analysis of two proposed methods to quantify biological aging using data from a recently concluded trial of an established geroprotector, caloric restriction. We obtained data from the National Institute on Aging CALERIE randomized trial through its public-access biobank (https://calerie.duke.edu/). The CALERIE trial randomized N = 220 nonobese adults to 25% caloric restriction (n = 145; 11.7% caloric restriction was achieved, on average) or to maintain current diet (n = 75) for 2 years. We analyzed biomarker data collected at baseline, 12-, and 24-month follow-up assessments. We applied published biomarker algorithms to these data to calculate two biological age measures, Klemera-Doubal Method Biological Age and homeostatic dysregulation. Intent-to-treat analysis using mixed-effects growth models of within-person change over time tested if caloric restriction slowed increase in measures of biological aging across follow-up. Analyses of both measures indicated caloric restriction slowed biological aging. Weight loss did not account for the observed effects. Results suggest future directions for testing of geroprotective therapies in humans.

An epigenome-wide association study meta-analysis of educational attainment

The epigenome is associated with biological factors, such as disease status, and environmental factors, such as smoking, alcohol consumption and body mass index. Although there is a widespread perception that environmental influences on the epigenome are pervasive and profound, there has been little evidence to date in humans with respect to environmental factors that are biologically distal. Here we provide evidence on the associations between epigenetic modifications-in our case, CpG methylation-and educational attainment (EA), a biologically distal environmental factor that is arguably among the most important life-shaping experiences for individuals. Specifically, we report the results of an epigenome-wide association study meta-analysis of EA based on data from 27 cohort studies with a total of 10 767 individuals. We find nine CpG probes significantly associated with EA. However, robustness analyses show that all nine probes have previously been found to be associated with smoking. Only two associations remain when we perform a sensitivity analysis in the subset of never-smokers, and these two probes are known to be strongly associated with maternal smoking during pregnancy, and thus their association with EA could be due to correlation between EA and maternal smoking. Moreover, the effect sizes of the associations with EA are far smaller than the known associations with the biologically proximal environmental factors alcohol consumption, body mass index, smoking and maternal smoking during pregnancy. Follow-up analyses that combine the effects of many probes also point to small methylation associations with EA that are highly correlated with the combined effects of smoking. If our findings regarding EA can be generalized to other biologically distal environmental factors, then they cast doubt on the hypothesis that such factors have large effects on the epigenome.

Methylomic predictors demonstrate the role of NF-κB in old-age mortality and are unrelated to the aging-associated epigenetic drift

Changes in the DNA methylation (DNAm) landscape have been implicated in aging and cellular senescence. To unravel the role of specific DNAm patterns in late-life survival, we performed genome-wide methylation profiling in nonagenarians (n=111) and determined the performance of the methylomic predictors and conventional risk markers in a longitudinal setting. The survival model containing only the methylomic markers was superior in terms of predictive accuracy compared with the model containing only the conventional predictors or the model containing conventional predictors combined with the methylomic markers. At the 2.55-year follow-up, we identified 19 mortality-associated (false-discovery rate <0.5) CpG sites that mapped to genes functionally clustering around the nuclear factor kappa B (NF-κB) complex. Interestingly, none of the mortality-associated CpG sites overlapped with the established aging-associated DNAm sites. Our results are in line with previous findings on the role of NF-κB in controlling animal life spans and demonstrate the role of this complex in human longevity.

Translating Measures of Biological Aging to Test Effectiveness of Geroprotective Interventions: What Can We Learn from Research on Telomeres?

Intervention studies in animals suggest molecular changes underlying age-related disease and disability can be slowed or reversed. To speed translation of these so-called "geroprotective" therapies to prevent age-related disease and disability in humans, biomarkers are needed that can track changes in the rate of human aging over the course of intervention trials. Algorithm methods that measure biological processes of aging from combinations of DNA methylation marks or clinical biomarkers show promise. To identify next steps for establishing utility of these algorithm-based measures of biological aging for geroprotector trials, we considered the history a candidate biomarker of aging that has received substantial research attention, telomere length. Although telomere length possesses compelling biology to recommend it as a biomarker of aging, mixed research findings have impeded clinical and epidemiologic translation. Strengths of telomeres that should be established for algorithm biomarkers of aging are correlation with chronological age across the lifespan, prediction of disease, disability, and early death, and responsiveness to risk and protective exposures. Key challenges in telomere research that algorithm biomarkers of aging must address are measurement precision and reliability, establishing links between longitudinal rates of change across repeated measurements and aging outcomes, and clarity over whether the biomarker is a causal mechanism of aging. These strengths and challenges suggest a research agenda to advance translation of algorithm-based aging biomarkers: establish validity in young-adult and midlife individuals; test responsiveness to exposures that shorten or extend healthy lifespan; and conduct repeated-measures longitudinal studies to test differential rates of change.

A longitudinal study of DNA methylation as a potential mediator of age-related diabetes risk

DNA methylation (DNAm) has been found to show robust and widespread age-related changes across the genome. DNAm profiles from whole blood can be used to predict human aging rates with great accuracy. We sought to test whether DNAm-based predictions of age are related to phenotypes associated with type 2 diabetes (T2D), with the goal of identifying risk factors potentially mediated by DNAm. Our participants were 43 women enrolled in the Women's Health Initiative. We obtained methylation data via the Illumina 450K Methylation array on whole blood samples from participants at three timepoints, covering on average 16 years per participant. We employed the method and software of Horvath, which uses DNAm at 353 CpGs to form a DNAm-based estimate of chronological age. We then calculated the epigenetic age acceleration, or Δ_age, at each timepoint. We fit linear mixed models to characterize how Δ_age contributed to a longitudinal model of aging and diabetes-related phenotypes and risk factors. For most participants, Δ_age remained constant, indicating that age acceleration is generally stable over time. We found that Δ_age associated with body mass index (p = 0.0012), waist circumference (p = 0.033), and fasting glucose (p = 0.0073), with the relationship with BMI maintaining significance after correction for multiple testing. Replication in a larger cohort of 157 WHI participants spanning 3 years was unsuccessful, possibly due to the shorter time frame covered. Our results suggest that DNAm has the potential to act as a mediator between aging and diabetes-related phenotypes, or alternatively, may serve as a biomarker of these phenotypes.

Longitudinal study of surrogate aging measures during human immunodeficiency virus seroconversion

Persons living with human immunodeficiency virus (HIV) harbor an increased risk of age-related conditions. We measured changes in telomere length and DNA methylation in the peripheral blood of 31 intravenous drug users, who were followed longitudinally with blood samples pre-HIV (T1), immediately post-HIV (T2; 1.9±1 year from T1), and at a later follow-up time (T3; 2.2±1 year from T2). Absolute telomere length measurements were performed using polymerase chain reaction methods. Methylation profiles were obtained using the Illumina Human Methylation450 platform. Methylation aging was assessed using the Horvath method. Telomere length significantly decreased between T1 and T2 (227±46 at T1 vs. 201±48 kbp/genome at T2, p=0.045), while no differences were observed between T2 and T3 (201±48 at T2 vs. 186±27 kbp/genome at T3, p=0.244). Methylation aging as measured by the age acceleration residual increased over the time course of HIV infection (p=0.035). CpG sites corresponding to PCBP2 and CSRNP1 were differentially methylated between T1 and T2 at a q-value <0.05. Telomere shortening and methylation changes can therefore be observed in the short-term period immediately following HIV seroconversion. Further studies to confirm these results in larger sample sizes and to compare these results to non-HIV and non-injection drug users are warranted.

Ischemic stroke patients are biologically older than their chronological age

Ischemic stroke is associated with aging. It is possible to predict chronological age by measuring age-related changes in DNA methylation from multiple CpG sites across the genome, known as biological age. The difference between biological age and actual chronological age would indicate an individual's level of aging. Our aim was to determine the biological age of ischemic stroke patients and compare their aging with controls of the same chronological age. A total of 123 individuals, 41 controls and 82 patients with ischemic stroke were paired by chronological age, ranging from 39 to 82 years. Illumina HumanMethylation450 BeadChip array was used to measure DNA methylation in CpG sites in both groups, and biological age was estimated using methylation values of specific CpGs. Ischemic stroke patients were biologically an average 2.5 years older than healthy controls (p-value=0.010). Stratified by age tertiles, younger stroke patients (≤57 years old) were biologically older than controls (OR=1.19; 95%CI 1.00-1.41, p-value=0.046). The older groups showed no biological age differences between cases and controls, but were close to reaching the significance level. Ischemic stroke patients are biologically older than controls. Biological age should be considered as a potential new biomarker of stroke risk.

An epigenetic aging clock for dogs and wolves

Several articles describe highly accurate age estimation methods based on human DNA-methylation data. It is not yet known whether similar epigenetic aging clocks can be developed based on blood methylation data from canids. Using Reduced Representation Bisulfite Sequencing, we assessed blood DNA-methylation data from 46 domesticated dogs (Canis familiaris) and 62 wild gray wolves (C. lupus). By regressing chronological dog age on the resulting CpGs, we defined highly accurate multivariate age estimators for dogs (based on 41 CpGs), wolves (67 CpGs), and both combined (115 CpGs). Age related DNA methylation changes in canids implicate similar gene ontology categories as those observed in humans suggesting an evolutionarily conserved mechanism underlying age-related DNA methylation in mammals.

Are objective measures of physical capability related to accelerated epigenetic age? Findings from a British birth cohort

OBJECTIVES

Our aim was to investigate the association of epigenetic age and physical capability in later life. Having a higher epigenetic than chronological age (known as age acceleration (AA)) has been found to be associated with an increased rate of mortality. Similarly, physical capability has been proposed as a marker of ageing due to its consistent associations with mortality.

SETTING

The MRC National Survey of Health and Development (NSHD) cohort study.

PARTICIPANTS

We used data from 790 women from the NSHD who had DNA methylation data available.

DESIGN

Epigenetic age was calculated using buccal cell (n=790) and matched blood tissue (n=152) from 790 female NSHD participants. We investigated the association of AA at age 53 with changes in physical capability in women from ages 53 to 60-64. Regression models of change in each measure of physical capability on AA were conducted. Secondary analysis focused on the relationship between AA and smoking, alcohol, body mass index (BMI) and socioeconomic position.

OUTCOME MEASURES

Three objective measures of physical capability were used: grip strength, standing balance time and chair rise speed.

RESULTS

Epigenetic age was lower than chronological age (mean 53.4) for both blood (50.3) and buccal cells (42.8). AA from blood was associated with a greater decrease in grip strength from ages 53 to 60-64 (0.42 kg decrease per year of AA, 95% CI 0.03, 0.82 kg; p=0.03, n=152), but no associations were observed with standing balance time or chair rise speed. Current smoking and lower BMI were associated with lower epigenetic age from buccal cells.

CONCLUSIONS

We found evidence that AA in blood is associated with a greater decrease in grip strength in British females aged between 53 and 60-64, but no association with standing balance time or chair rise speed was found.

Epigenetic clock analysis in long-term meditators

In this paper, we examined whether meditation practice influences the epigenetic clock, a strong and reproducible biomarker of biological aging, which is accelerated by cumulative lifetime stress and with age-related chronic diseases. Using the Illumina 450K array platform, we analyzed the DNA methylome from blood cells of long-term meditators and meditation-naïve controls to estimate their Intrinsic Epigenetic Age Acceleration (IEAA), using Horvath's calculator. IEAA was similar in both groups. However, controls showed a different IEAA trajectory with aging than meditators: older controls (age≥52) had significantly higher IEAAs compared with younger controls (age <52), while meditators were protected from this epigenetic aging effect. Notably, in the meditation group, we found a significant negative correlation between IEAA and the number of years of regular meditation practice. From our results, we hypothesize that the cumulative effects of a regular meditation practice may, in the long-term, help to slow the epigenetic clock and could represent a useful preventive strategy for age-related chronic diseases. Longitudinal randomized controlled trials in larger cohorts are warranted to confirm and further characterize these findings.

Specific premature epigenetic aging of cartilage in osteoarthritis

Osteoarthritis (OA) is a disease affecting multiple tissues of the joints in the elderly, but most notably articular cartilage. Premature biological aging has been described in this tissue and in blood cells, suggesting a systemic component of premature aging in the pathogenesis of OA. Here, we have explored epigenetic aging in OA at the local (cartilage and bone) and systemic (blood) levels. Two DNA methylation age-measures (DmAM) were used: the multi-tissue age estimator for cartilage and bone; and a blood-specific biomarker for blood. Differences in DmAM between OA patients and controls showed an accelerated aging of 3.7 years in articular cartilage (95% CI = 1.1 to 6.3, P = 0.008) of OA patients. By contrast, no difference in epigenetic aging was observed in bone (0.04 years; 95% CI = -1.8 to 1.9, P = 0.3) and in blood (-0.6 years; 95% CI = -1.5 to 0.3, P = 0.2) between OA patients and controls. Therefore, premature epigenetic aging according to DNA methylation changes was specific of OA cartilage, adding further evidence and insight on premature aging of cartilage as a component of OA pathogenesis that reflects damage and vulnerability.

DNA methylation-based measures of biological age: meta-analysis predicting time to death

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10^-9), independent of chronological age, even after adjusting for additional risk factors (p<5.4x10^-4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5x10^-43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

Effects of chronic cobalt and chromium exposure after metal-on-metal hip resurfacing: An epigenome-wide association pilot study

Metal-on-metal (MOM) hip resurfacing has recently been a popular prosthesis choice for the treatment of symptomatic arthritis, but results in the release of cobalt and chromium ions into the circulation that can be associated with adverse clinical effects. The mechanism underlying these effects remains unclear. While chromosomal aneuploidy and translocations are associated with this exposure, the presence of subtle structural epigenetic modifications in patients with MOM joint replacements remains unexplored. Consequently, we analyzed whole blood DNA methylation in 34 OA patients with MOM hip resurfacing (MOM HR) compared to 34 OA patients with non-MOM total hip replacements (non-MOM THR), using the genome-wide Illumina HumanMethylation 450k BeadChip. No probes showed differential methylation significant at 5% false-discovery rate (FDR). We also tested association of probe methylation levels with blood chromium and cobalt levels directly; there were no significant associations at 5% FDR. Finally, we used the "epigenetic clock" to compare estimated to actual age at sample for all individuals. We found no significant difference between MOM HR and non-MOM THR, and no correlation of age acceleration with blood metal levels. Our results suggest the absence of large methylation differences systemically following metal exposure, however, larger sample sizes will be required to identify potential small effects. Any DNA methylation changes that may occur in the local periprosthetic tissues remain to be elucidated. © 2017 The Authors. Orthopaedic Research Society. Published by Wiley Periodicals, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 35:2323-2328, 2017.

Phenome and genome based studies into human ageing and longevity: An overview

Human ageing is an extremely personal process leading across the life course of individuals to large population heterogeneity in the decline of functional capacity, health and lifespan. The extremes of this process are witnessed by the healthy vital 100-year-olds on one end and the 60-year-olds suffering from multiple morbid conditions on the other end of the spectrum. Molecular studies into the basis of this heterogeneity have focused on a range of endpoints and methodological approaches. The phenotype definitions most prominently investigated in these studies are either lifespan-related or biomarker based indices of the biological ageing rate of individuals and their tissues. Unlike for many complex, age-related diseases, consensus on the ultimate set of multi-biomarker ageing or lifespan-related phenotypes for genetic and genomic studies has not been reached yet. Comparable to animal models, hallmarks of age-related disease risk, healthy ageing and longevity include immune and metabolic pathways. Potentially novel genomic regions and pathways have been identified among many (epi)genomic studies into chronological age and studies into human lifespan regulation, with APOE and FOXO3A representing yet the most robust loci. Functional analysis of a handful of genes in cell-based and animal models is ongoing. The way forward in human ageing and longevity studies seems through improvements in the interpretation of the biology of the genome, in application of computational and systems biology, integration with animal models and by harmonization of repeated phenotypic and omics measures in longitudinal and intervention studies. This article is part of a Special Issue entitled: Model Systems of Aging - edited by "Houtkooper Riekelt".

Systemic Age-Associated DNA Hypermethylation of ELOVL2 Gene: In Vivo and In Vitro Evidences of a Cell Replication Process

Epigenetic remodeling is one of the major features of the aging process. We recently demonstrated that DNA methylation of ELOVL2 and FHL2 CpG islands is highly correlated with age in whole blood. Here we investigated several aspects of age-associated hypermethylation of ELOVL2 and FHL2. We showed that ELOVL2 methylation is significantly different in primary dermal fibroblast cultures from donors of different ages. Using epigenomic data from public resources, we demonstrated that most of the tissues show ELOVL2 and FHL2 hypermethylation with age. Interestingly, ELOVL2 hypermethylation was not found in tissues with very low replication rate. We demonstrated that ELOVL2 hypermethylation is associated with in vitro cell replication rather than with senescence. We confirmed intra-individual hypermethylation of ELOVL2 and FHL2 in longitudinally assessed participants from the Doetinchem Cohort Study. Finally we showed that, although the methylation of the two loci is not associated with longevity/mortality in the Leiden Longevity Study, ELOVL2 methylation is associated with cytomegalovirus status in nonagenarians, which could be informative of a higher number of replication events in a fraction of whole-blood cells. Collectively, these results indicate that ELOVL2 methylation is a marker of cell divisions occurring during human aging.

Accelerated DNA methylation age in adolescent girls: associations with elevated diurnal cortisol and reduced hippocampal volume

Numerous studies have linked exposure to stress to adverse health outcomes through the effects of cortisol, a product of the stress response system, on cellular aging processes. Accelerated DNA methylation age is a promising epigenetic marker associated with stress and disease risk that may constitute a link from stress response to changes in neural structures. Specifically, elevated glucocorticoid signaling likely contributes to accelerating DNA methylation age, which may signify a maladaptive stress-related cascade that leads to hippocampal atrophy. We examined the relations among diurnal cortisol levels, DNA methylation age and hippocampal volume in a longitudinal study of 46 adolescent girls. We computed area under the curve from two daily cortisol collection periods, and calculated DNA methylation age using previously established methods based on a set of CpG sites associated with chronological age. We computed a residual score by partialling out chronological age; higher discrepancies reflect relatively accelerated DNA methylation age. We assessed hippocampal volume via T1-weighted images and automated volumetric segmentation. We found that greater diurnal cortisol production was associated with accelerated DNA methylation age, which in turn was associated with reduced left hippocampal volume. Finally, accelerated DNA methylation age significantly mediated the association between diurnal cortisol and left hippocampal volume. Thus, accelerated DNA methylation age may be an epigenetic marker linking hypothalamic-pituitary-adrenal axis dysregulation with neural structure. If these findings are replicated, the current study provides a method for advancing our understanding of mechanisms by which glucocorticoid signaling is associated with cellular aging and brain development.

Effect of methotrexate/vitamin B12 on DNA methylation as a potential factor in leukemia treatment-related neurotoxicity

Methotrexate (MTX) is administered to treat childhood acute lymphoblastic leukemia (ALL). It acts by inhibiting dihydrofolate reductase which reduces methyltetrahydrofolate, a key component in one carbon metabolism, thus reducing cell proliferation. Further perturbations to one carbon metabolism, such as reduced vitamin B₁₂ levels via the use of nitrous oxide for sedation during childhood ALL treatment, may increase neurotoxicity risk. With B₁₂ as an enzymatic cofactor, methyltetrahydrofolate is essential to produce methionine, which is critical for DNA methylation. We investigated global and gene specific DNA methylation in neuronal cell lines in response to MTX treatment and vitamin B₁₂ concentration individually, and in combination. Results: MTX treatment alone significantly increased LINE-1 methylation in SH-SY5Y (p = 0.040) and DAOY (p < 0.001), and increased FKBP5 methylation in MO3.13 cells (p = 0.009). Conclusion: We conclude that altered DNA methylation of brain/central nervous system cells could be one mechanism involved in MTX treatment-related neurotoxicities and neurocognitive late effects in ALL survivors.

DNA methylation in ELOVL2 and C1orf132 correctly predicted chronological age of individuals from three disease groups

Improving accuracy of the available predictive DNA methods is important for their wider use in routine forensic work. Information on age in the process of identification of an unknown individual may provide important hints that can speed up the process of investigation. DNA methylation markers have been demonstrated to provide accurate age estimation in forensics, but there is growing evidence that DNA methylation can be modified by various factors including diseases. We analyzed DNA methylation profile in five markers from five different genes (ELOVL2, C1orf132, KLF14, FHL2, and TRIM59) used for forensic age prediction in three groups of individuals with diagnosed medical conditions. The obtained results showed that the selected age-related CpG sites have unchanged age prediction capacity in the group of late onset Alzheimer’s disease patients. Aberrant hypermethylation and decreased prediction accuracy were found for TRIM59 and KLF14 markers in the group of early onset Alzheimer’s disease suggesting accelerated aging of patients. In the Graves’ disease patients, altered DNA methylation profile and modified age prediction accuracy were noted for TRIM59 and FHL2 with aberrant hypermethylation observed for the former and aberrant hypomethylation for the latter. Our work emphasizes high utility of the ELOVL2 and C1orf132 markers for prediction of chronological age in forensics by showing unchanged prediction accuracy in individuals affected by three diseases. The study also demonstrates that artificial neural networks could be a convenient alternative for the forensic predictive DNA analyses.

Impacts of the Mitochondrial Genome on the Relationship of Long-Term Ambient Fine Particle Exposure with Blood DNA Methylation Age

The mitochondrial genome has long been implicated in age-related disease, but no studies have examined its role in the relationship of long-term fine particle (PM2.5) exposure and DNA methylation age (DNAm-age)-a novel measure of biological age. In this analysis based on 940 observations between 2000 and 2011 from 552 Normative Aging Study participants, we determined the roles of mitochondrial DNA haplogroup variation and mitochondrial genome abundance in the relationship of PM2.5 with DNAm-age. We used the GEOS-chem transport model to estimate address-specific, one-year PM2.5 levels for each participant. DNAm-age and mitochondrial DNA markers were measured from participant blood samples. Nine haplogroups (H, I, J, K, T, U, V, W, and X) were present in the population. In fully adjusted linear mixed-effects models, the association of PM2.5 with DNAm-age (in years) was significantly diminished in carriers of haplogroup V (Pinteraction = 0.01; β = 0.18, 95%CI: -0.41, 0.78) compared to noncarriers (β = 1.25, 95%CI: 0.58, 1.93). Mediation analysis estimated that decreases in mitochondrial DNA copy number, a measure of mitochondrial genome abundance, mediated 12% of the association of PM2.5 with DNAm-age. Our data suggests that the mitochondrial genome plays a role in DNAm-age relationships particularly in the context of long-term PM2.5 exposure.

The relation between DNA methylation patterns and serum cytokine levels in community-dwelling adults: a preliminary study

Background

The levels of circulating cytokines fluctuate with age, acute illness, and chronic disease, and are predictive of mortality; this is also true for patterns of DNA (CpG) methylation. Given that immune cells are particularly sensitive to changes in the concentration of cytokines in their microenvironment, we hypothesized that serum levels of TNF, IL-6, IL-8 and IL-10 would correlate with genome-wide alterations in the DNA methylation levels of blood leukocytes. To test this, we evaluated community-dwelling adults (n = 14; 48–78 years old) recruited to a pilot study for the Canadian Longitudinal Study on Aging (CLSA), examining DNA methylation patterns in peripheral blood mononuclear cells using the Illumina HumanMethylation 450 K BeadChip.

Results

We show that, apart from age, serum IL-10 levels exhibited the most substantial association to DNA methylation patterns, followed by TNF, IL-6 and IL-8. Furthermore, while the levels of these cytokines were higher in elderly adults, no associations with epigenetic accelerated aging, derived using the epigenetic clock, were observed.

Conclusions

As a preliminary study with a small sample size, the conclusions drawn from this work must be viewed with caution; however, our observations are encouraging and certainly warrant more suitably powered studies of this relationship.

Electronic supplementary material

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DNA Methylation Profiling of Human Prefrontal Cortex Neurons in Heroin Users Shows Significant Difference between Genomic Contexts of Hyper- and Hypomethylation and a Younger Epigenetic Age

We employed Illumina 450 K Infinium microarrays to profile DNA methylation (DNAm) in neuronal nuclei separated by fluorescence-activated sorting from the postmortem orbitofrontal cortex (OFC) of heroin users who died from heroin overdose (N = 37), suicide completers (N = 22) with no evidence of heroin use and from control subjects who did not abuse illicit drugs and died of non-suicide causes (N = 28). We identified 1298 differentially methylated CpG sites (DMSs) between heroin users and controls, and 454 DMSs between suicide completers and controls (p < 0.001). DMSs and corresponding genes (DMGs) in heroin users showed significant differences in the preferential context of hyper and hypo DM. HyperDMSs were enriched in gene bodies and exons but depleted in promoters, whereas hypoDMSs were enriched in promoters and enhancers. In addition, hyperDMGs showed preference for genes expressed specifically by glutamatergic as opposed to GABAergic neurons and enrichment for axonogenesis- and synaptic-related gene ontology categories, whereas hypoDMGs were enriched for transcription factor activity- and gene expression regulation-related terms. Finally, we found that the DNAm-based “epigenetic age” of neurons from heroin users was younger than that in controls. Suicide-related results were more difficult to interpret. Collectively, these findings suggest that the observed DNAm differences could represent functionally significant marks of heroin-associated plasticity in the OFC.

Genetic architecture of epigenetic and neuronal ageing rates in human brain regions

Identifying genes regulating the pace of epigenetic ageing represents a new frontier in genome-wide association studies (GWASs). Here using 1,796 brain samples from 1,163 individuals, we carry out a GWAS of two DNA methylation-based biomarkers of brain age: the epigenetic ageing rate and estimated proportion of neurons. Locus 17q11.2 is significantly associated (P=4.5 × 10⁻⁹) with the ageing rate across five brain regions and harbours a cis-expression quantitative trait locus for EFCAB5 (P=3.4 × 10⁻²⁰). Locus 1p36.12 is significantly associated (P=2.2 × 10⁻⁸) with epigenetic ageing of the prefrontal cortex, independent of the proportion of neurons. Our GWAS of the proportion of neurons identified two genome-wide significant loci (10q26 and 12p13.31) and resulted in a gene set that overlaps significantly with sets found by GWAS of age-related macular degeneration (P=1.4 × 10⁻¹²), ulcerative colitis (P<1.0 × 10⁻²⁰), type 2 diabetes (P=2.8 × 10⁻¹³), hip/waist circumference in men (P=1.1 × 10⁻⁹), schizophrenia (P=1.6 × 10⁻⁹), cognitive decline (P=5.3 × 10⁻⁴) and Parkinson's disease (P=8.6 × 10⁻³).

Studies on the ‘epigenetic clock', a recently identified ageing biomarker, suggest that pathology might be linked to tissue-specific accelerated ageing. Here, the authors investigate ageing in the human brain and identify genetic loci associated with accelerated ageing in different brain regions.

Associations between maternal risk factors of adverse pregnancy and birth outcomes and the offspring epigenetic clock of gestational age at birth

Background

A recent study has shown that it is possible to accurately estimate gestational age (GA) at birth from the DNA methylation (DNAm) of fetal umbilical cord blood/newborn blood spots. This DNAm GA predictor may provide additional information relevant to developmental stage. In 814 mother-neonate pairs, we evaluated the associations between DNAm GA and a number of maternal and offspring characteristics. These characteristics reflect prenatal environmental adversity and are expected to influence newborn developmental stage.

Results

DNAm GA acceleration (GAA; i.e., older DNAm GA than chronological GA) of the offspring at birth was associated with maternal age of over 40 years at delivery, pre-eclampsia and fetal demise in a previous pregnancy, maternal pre-eclampsia and treatment with antenatal betamethasone in the index pregnancy, lower neonatal birth size, lower 1-min Apgar score, and female sex. DNAm GA deceleration (GAD; i.e., younger DNAm GA than chronological GA) of the offspring at birth was associated with insulin-treated gestational diabetes mellitus (GDM) in a previous pregnancy and Sjögren’s syndrome. These findings were more accentuated when the DNAm GA calculation was based on the raw difference between DNAm GA and GA than on the residual from the linear regression of DNAm GA on GA.

Conclusions

Our findings show that variations in the DNAm GA of the offspring at birth are associated with a number of maternal and offspring characteristics known to reflect exposure to prenatal environmental adversity. Future studies should be aimed at determining if this biological variation is predictive of developmental adversity.

Electronic supplementary material

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Aging, exceptional longevity and comparisons of the Hannum and Horvath epigenetic clocks

AIM

To examine the relationships between two epigenetic clocks, aging and exceptional longevity.

MATERIALS & METHODS

Participants were from three adult cohorts with blood DNA methylation data (Illumina 450 K, n = 275, 34-103 years). Epigenetic age (DNAmage) and age acceleration measures were calculated using the Hannum and Horvath epigenetic clocks.

RESULTS

Across all cohorts, DNAmage was correlated with chronological age. In the long-lived cohort (Sydney Centenarian Study; 95+, n = 23), DNAmage was lower than chronological age for both clocks. Mean Sydney Centenarian Study Hannum age acceleration was negative, while the converse was observed for the Horvath model.

CONCLUSION

Long-lived individuals have a young epigenetic age compared with their chronological age.

Cadmium exposure and age-associated DNA methylation changes in non-smoking women from northern Thailand

DNA methylation changes with age, and may serve as a biomarker of aging. Cadmium (Cd) modifies cellular processes that promote aging and disrupts methylation globally. Whether Cd modifies aging processes by influencing establishment of age-associated methylation marks is currently unknown. In this pilot study, we characterized methylation profiles in > 450 000 CpG sites in 40 non-smoking women (age 40-80) differentially exposed to environmental Cd from Thailand. Based on specific gravity adjusted urinary Cd, we classified them as high (HE) and low (LE) exposed and age-matched within 5 years. Urinary Cd was defined as below 2 µg/l in the LE group. We predicted epigenetic age (DNAm-age) using two published methods by Horvath and Hannum and examined the difference between epigenetic age and chronologic age (Δage). We assessed differences by Cd exposure using linear mixed models adjusted for estimated white blood cell proportions, BMI, and urinary creatinine. We identified 213 age-associated CpG sites in our population (P < 10^-4). Counterintuitively, the mean Δage was smaller in HE vs. LE (Hannum: 3.6 vs. 7.6 years, P = 0.0093; Horvath: 2.4 vs. 4.5 years, P = 0.1308). The Cd exposed group was associated with changes in methylation (P < 0.05) at 12, 8, and 20 age-associated sites identified in our population, Hannum, and Horvath. From the results of this pilot study, elevated Cd exposure is associated with methylation changes at age-associated sites and smaller differences between DNAm-age and chronologic age, in contrast to expected age-accelerating effects. Cd may modify epigenetic aging, and biomarkers of aging warrant further investigation when examining Cd and its relationship with chronic disease and mortality.

Associations between long-term exposure to PM2.5 component species and blood DNA methylation age in the elderly: The VA normative aging study

BACKGROUND

Long-term PM_2.5 exposure and aging have been implicated in multiple shared diseases; studying their relationship is a promising strategy to further understand the adverse impact of PM_2.5 on human health.

OBJECTIVE

We assessed the relationship of major PM_2.5 component species (ammonium, elemental carbon, organic carbon, nitrate, and sulfate) with Horvath and Hannum DNA methylation (DNAm) age, two DNA methylation-based predictors of chronological age.

METHODS

This analysis included 552 participants from the Normative Aging Study with multiple visits between 2000 and 2011 (n=940 visits). We estimated 1-year PM_2.5 species levels at participants' addresses using the GEOS-chem transport model. Blood DNAm-age was calculated using CpG sites on the Illumina HumanMethylation450 BeadChip. We fit linear mixed-effects models, controlling for PM_2.5 mass and lifestyle/environmental factors as fixed effects, with the adaptive LASSO penalty to identify PM_2.5 species associated with DNAm-age.

RESULTS

Sulfate and ammonium were selected by the LASSO in the Horvath DNAm-age models. In a fully-adjusted multiple-species model, interquartile range increases in both 1-year sulfate (95%CI: 0.28, 0.74, P<0.0001) and ammonium (95%CI: 0.02, 0.70, P=0.04) levels were associated with at least a 0.36-year increase in Horvath DNAm-age. No PM_2.5 species were selected by the LASSO in the Hannum DNAm-age models. Our findings persisted in sensitivity analyses including only visits with 1-year PM_2.5 levels within US EPA national ambient air quality standards.

CONCLUSION

Our results demonstrate that sulfate and ammonium were most associated with Horvath DNAm-age and suggest that DNAm-age measures differ in their sensitivity to ambient particle exposures and potentially disease.

Differential DNA methylation and lymphocyte proportions in a Costa Rican high longevity region

Background

The Nicoya Peninsula in Costa Rica has one of the highest old-age life expectancies in the world, but the underlying biological mechanisms of this longevity are not well understood. As DNA methylation is hypothesized to be a component of biological aging, we focused on this malleable epigenetic mark to determine its association with current residence in Nicoya versus elsewhere in Costa Rica. Examining a population’s unique DNA methylation pattern allows us to differentiate hallmarks of longevity from individual stochastic variation. These differences may be characteristic of a combination of social, biological, and environmental contexts.

Methods

In a cross-sectional subsample of the Costa Rican Longevity and Healthy Aging Study, we compared whole blood DNA methylation profiles of residents from Nicoya (n = 48) and non-Nicoya (other Costa Rican regions, n = 47) using the Infinium HumanMethylation450 microarray.

Results

We observed a number of differences that may be markers of delayed aging, such as bioinformatically derived differential CD8+ T cell proportions. Additionally, both site- and region-specific analyses revealed DNA methylation patterns unique to Nicoyans. We also observed lower overall variability in DNA methylation in the Nicoyan population, another hallmark of younger biological age.

Conclusions

Nicoyans represent an interesting group of individuals who may possess unique immune cell proportions as well as distinct differences in their epigenome, at the level of DNA methylation.

Electronic supplementary material

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Multi-tissue DNA methylation age predictor in mouse

Background

DNA 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.

Results

We 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 which 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 diet.

Conclusions

Here we identify and characterise 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.

Electronic supplementary material

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Epigenetic Age Acceleration Assessed with Human White-Matter Images

The accurate estimation of age using methylation data has proved a useful and heritable biomarker, with acceleration in epigenetic age predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are also heritable and highly sensitive to both normal and pathological aging processes across adulthood. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity in humans. Our goal was to investigate processes that underlie interindividual variability in age-related changes in the brain. Using blood taken from a Mexican-American extended pedigree sample (n = 628; age = 23.28-93.11 years), epigenetic age was estimated using the method developed by Horvath (2013). For n = 376 individuals, diffusion tensor imaging scans were also available. The interrelationship between epigenetic age acceleration and global white matter integrity was investigated with variance decomposition methods. To test for neuroanatomical specificity, 16 specific tracts were additionally considered. We observed negative phenotypic correlations between epigenetic age acceleration and global white matter tract integrity (ρ_pheno = -0.119, p = 0.028), with evidence of shared genetic (ρ_gene = -0.463, p = 0.013) but not environmental influences. Negative phenotypic and genetic correlations with age acceleration were also seen for a number of specific white matter tracts, along with additional negative phenotypic correlations between granulocyte abundance and white matter integrity. These findings (i.e., increased acceleration in epigenetic age in peripheral blood correlates with reduced white matter integrity in the brain and shares common genetic influences) provide a window into the neurobiology of aging processes within the brain and a potential biomarker of normal and pathological brain aging.SIGNIFICANCE STATEMENT Epigenetic measures can be used to predict age with a high degree of accuracy and so capture acceleration in biological age, relative to chronological age. The white matter tracts within the brain are also highly sensitive to aging processes. We show that increased biological aging (measured using epigenetic data from blood samples) is correlated with reduced integrity of white matter tracts within the human brain (measured using diffusion tensor imaging) with data from a large sample of Mexican-American families. Given the family design of the sample, we are also able to demonstrate that epigenetic aging and white matter tract integrity also share common genetic influences. Therefore, epigenetic age may be a potential, and accessible, biomarker of brain aging.

Acceleration of leukocytes' epigenetic age as an early tumor and sex-specific marker of breast and colorectal cancer

Changes in blood epigenetic age have been associated with several pathological conditions and have recently been described to anticipate cancer development. In this work, we analyze a publicly available leukocytes methylation dataset to evaluate the relation between DNA methylation age and the prospective development of specific types of cancer. We calculated DNA methylation age acceleration using five state-of-the-art estimators (three multi-site: Horvath, Hannum, Weidner; and two CpG specific: ELOV2 and FHL2) in a cohort including 845 subjects from the EPIC-Italy project and we compared 424 samples that remained cancer-free over the approximately ten years of follow-up with 235 and 166 subjects who developed breast and colorectal cancer, respectively. We show that the epigenetic age estimated from blood DNA methylation data is statistically significantly associated to future breast and male colorectal cancer development. These results are corroborated by survival analysis that shows significant association between age acceleration and cancer incidence suggesting that the chance of developing age-related diseases may be predicted by circulating epigenetic markers, with a dependence upon tumor type, sex and age estimator. These are encouraging results towards the non-invasive and perspective usage of epigenetic biomarkers.

DNA methylome analysis identifies accelerated epigenetic ageing associated with postmenopausal breast cancer susceptibility

AIM OF THE STUDY

A vast majority of human malignancies are associated with ageing, and age is a strong predictor of cancer risk. Recently, DNA methylation-based marker of ageing, known as 'epigenetic clock', has been linked with cancer risk factors. This study aimed to evaluate whether the epigenetic clock is associated with breast cancer risk susceptibility and to identify potential epigenetics-based biomarkers for risk stratification.

METHODS

Here, we profiled DNA methylation changes in a nested case-control study embedded in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (n = 960) using the Illumina HumanMethylation 450K BeadChip arrays and used the Horvath age estimation method to calculate epigenetic age for these samples. Intrinsic epigenetic age acceleration (IEAA) was estimated as the residuals by regressing epigenetic age on chronological age.

RESULTS

We observed an association between IEAA and breast cancer risk (OR, 1.04; 95% CI, 1.007-1.076, P = 0.016). One unit increase in IEAA was associated with a 4% increased odds of developing breast cancer (OR, 1.04; 95% CI, 1.007-1.076). Stratified analysis based on menopausal status revealed that IEAA was associated with development of postmenopausal breast cancers (OR, 1.07; 95% CI, 1.020-1.11, P = 0.003). In addition, methylome-wide analyses revealed that a higher mean DNA methylation at cytosine-phosphate-guanine (CpG) islands was associated with increased risk of breast cancer development (OR per 1 SD = 1.20; 95 %CI: 1.03-1.40, P = 0.02) whereas mean methylation levels at non-island CpGs were indistinguishable between cancer cases and controls.

CONCLUSION

Epigenetic age acceleration and CpG island methylation have a weak, but statistically significant, association with breast cancer susceptibility.

Biological Age Predictors

The search for reliable indicators of biological age, rather than chronological age, has been ongoing for over three decades, and until recently, largely without success. Advances in the fields of molecular biology have increased the variety of potential candidate biomarkers that may be considered as biological age predictors. In this review, we summarize current state-of-the-art findings considering six potential types of biological age predictors: epigenetic clocks, telomere length, transcriptomic predictors, proteomic predictors, metabolomics-based predictors, and composite biomarker predictors. Promising developments consider multiple combinations of these various types of predictors, which may shed light on the aging process and provide further understanding of what contributes to healthy aging. Thus far, the most promising, new biological age predictor is the epigenetic clock; however its true value as a biomarker of aging requires longitudinal confirmation.

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Telomere length is the most well studied biological age predictor, but many new predictors are emerging.

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The epigenetic clock is currently the best biological age predictor, as it correlates well with age and predicts mortality.

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The various biological age predictors tend to reflect different aspects of the aging process.

The epigenetic landscape of age-related diseases: the geroscience perspective

In this review, we summarize current knowledge regarding the epigenetics of age-related diseases, focusing on those studies that have described DNA methylation landscape in cardio-vascular diseases, musculoskeletal function and frailty. We stress the importance of adopting the conceptual framework of “geroscience”, which starts from the observation that advanced age is the major risk factor for several of these pathologies and aims at identifying the mechanistic links between aging and age-related diseases. DNA methylation undergoes a profound remodeling during aging, which includes global hypomethylation of the genome, hypermethylation at specific loci and an increase in inter-individual variation and in stochastic changes of DNA methylation values. These epigenetic modifications can be an important contributor to the development of age-related diseases, but our understanding on the complex relationship between the epigenetic signatures of aging and age-related disease is still poor. The most relevant results in this field come from the use of the so called “epigenetics clocks” in cohorts of subjects affected by age-related diseases. We report these studies in final section of this review.

Systematic review of lung function and COPD with peripheral blood DNA methylation in population based studies

BACKGROUND

Epigenetic variations in peripheral blood have potential as biomarkers for disease. This systematic review assesses the association of lung function and chronic obstructive pulmonary disease (COPD) with DNA methylation profiles in peripheral blood from population-based studies.

METHODS

Online databases Medline, Embase, and Web of Science were searched. Google Scholar was searched to identify grey literature. After removing duplicate articles, 1155 articles were independently screened by two investigators. Peer reviewed reports on population-based studies that examined peripheral blood DNA methylation in participants with measured lung function (FEV1, FEV1/FVC ratio) or known COPD status were selected for full-text review. Six articles were suitable for inclusion. Information regarding study characteristics, designs, methodologies and conclusions was extracted. A narrative synthesis was performed based on published results.

RESULTS

Three of the six articles assessed the association of COPD with DNA methylation, and two of these also included associations with lung function. Overall, five reports examined the association of lung function with DNA methylation profiles. Five of the six articles reported 'significant' results. However, no consistent CpG sites were identified across studies for COPD status or lung function values.

CONCLUSIONS

DNA methylation patterns in peripheral blood from individuals with reduced lung function or COPD may be different to those in people with normal lung function. However, this systematic review did not find any consistent associations of lung function or COPD with differentially methylated CpG sites. Large studies with a longitudinal design to address reverse causality may prove a more fruitful area of research.

TRIAL REGISTRATION

PROSPERO 2016: CRD42016037352 .

Conserved effect of aging on DNA methylation and association with EZH2 polycomb protein in mice and humans

In humans, DNA methylation at specific CpG sites can be used to estimate the 'epigenetic clock', a biomarker of aging and health. The mechanisms that regulate the aging epigenome and level of conservation are not entirely clear. We performed affinity-based enrichment with methyl-CpG binding domain protein followed by high-throughput sequencing (MBD-seq) to assay DNA methylation in mouse samples. Consistent with previous reports, aging is associated with increase in methylation at CpG islands that likely overlap regulatory regions of genes that have been implicated in cancers (e.g., C1ql3, Srd5a2 and Ptk7). The differentially methylated regions in mice have high sequence conservation in humans and the pattern of methylation is also largely conserved between the two species. Based on human ENCODE data, these sites are targeted by polycomb proteins, including EZH2. Chromatin immunoprecipitation confirmed that these regions interact with EZH2 in mice as well, and there may be reduction in EZH2 occupancy with age at C1ql3. This adds to the growing evidence that EZH2 is part of the protein machinery that shapes the aging epigenome. The conservation in both sequence and methylation patterns of the age-dependent CpGs indicate that the epigenetic clock is a fundamental feature of aging in mammals.

Cerebral white matter hyperintensities on MRI and acceleration of epigenetic aging: the atherosclerosis risk in communities study

Background

Cerebral white matter hyperintensities (WMH) on magnetic resonance imaging (MRI) are part of the spectrum of brain vascular injury accompanying aging and are associated with a substantial risk of stroke and dementia. We investigated the association of cerebral WMH burden on MRI with a DNA methylation-based biomarker of aging, termed DNA methylation age acceleration, which represents the deviation of the DNA methylation-predicted age from the chronologic age.

Results

In this cross-sectional observational study of 713 African-American participants of the Atherosclerosis Risk in Communities study, aged 51–73 years, estimates of predicted age were obtained based on two algorithms (Hannum et al. and Horvath) from DNA methylation measured using the Illumina HM450 array on genomic DNA extracted from blood. Age acceleration, calculated as the residual values from the regression of each of the predicted age measures onto the chronologic age, was significantly associated with WMH burden after accounting for chronologic age and sex, body mass index, systolic blood pressure, hypertension, diabetes, current smoking, and blood cell composition, and results were similar for either Hannum et al.- or Horvath-derived estimates (P = 0.016 and 0.026). An age acceleration increase by 1 year was associated with an increase of WMH burden by ~1 grade. To shed light on possible biological mechanisms underlying this association, we conducted a genome-wide association study of age acceleration and identified four loci harboring genes implicated in hemostasis, cell proliferation, protein degradation, and histone methylation. However, none of these loci were associated with WMH burden.

Conclusions

In this population-based study of middle-aged to older African-American adults, we report an association between accelerated epigenetic aging and increased WMH burden, independent of known risk factors, including chronologic age. Additional studies are needed to clarify whether DNA methylation age reflects biological mechanisms implicated in the aging of the cerebral white matter.

Electronic supplementary material

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Obesity accelerates epigenetic aging in middle-aged but not in elderly individuals

Background

Human aging is associated with profound changes in one of the major epigenetic mechanisms, DNA methylation. Some of these changes occur in a clock-like fashion, i.e., correlating with the calendar age of an individual, thus providing a new aging biomarker. Some reports have identified factors associated with the acceleration of the epigenetic age. However, it is also important to analyze the temporal changes in the epigenetic age, i.e., the duration of the observed acceleration, and the effects of the possible therapeutic and lifestyle modifications.

Methods

To address this issue, we determined the epigenetic age for a cohort of 183 healthy individuals using blood samples derived from two time points that were 25 years apart (between 15–24 and 40–49 years of age). Additionally, we also determined the epigenetic ages of 119 individuals in a cohort consisting of 90-year-old participants (nonagenarians). These were determined by using the Horvath algorithm based on the methylation level of 353 CpG sites. The data are indicated as the deviation of the epigenetic age from the calendar age (calendar age minus epigenetic age = delta age, ΔAGE). As obesity is often associated with accelerating aging and degenerative phenotypes, the correlation of the body mass index (BMI) with the ΔAGE was analyzed in the following three age groups: young adults, middle-aged, and nonagenarian.

Results

The data showed that BMI is associated with decreased ΔAGE, i.e., increased epigenetic age, in middle-aged individuals. This effect is also seen during the 25-year period from early adulthood to middle age, in which an increase in the BMI is significantly associated with a decrease in the ΔAGE. We also analyzed the association between BMI and epigenetic age in young and elderly individuals, but these associations were not significant.

Conclusion

Taken together, the main finding on this report suggests that association between increased BMI and accelerated epigenetic aging in the blood cells of middle-aged individuals can be observed, and this effect is also detectable if the BMI has increased in adulthood. The fact that the association between BMI and epigenetic age can only be observed in the middle-aged group does not exclude the possibility that this association could be present throughout the human lifespan; it might just be masked by confounding factors in young adults and nonagenarian individuals.

Electronic supplementary material

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Epigenetic clock analysis of diet, exercise, education, and lifestyle factors

Behavioral and lifestyle factors have been shown to relate to a number of health-related outcomes, yet there is a need for studies that examine their relationship to molecular aging rates. Toward this end, we use recent epigenetic biomarkers of age that have previously been shown to predict all-cause mortality, chronic conditions, and age-related functional decline. We analyze cross-sectional data from 4,173 postmenopausal female participants from the Women's Health Initiative, as well as 402 male and female participants from the Italian cohort study, Invecchiare nel Chianti.Extrinsic epigenetic age acceleration (EEAA) exhibits significant associations with fish intake (p=0.02), moderate alcohol consumption (p=0.01), education (p=3x10-5), BMI (p=0.01), and blood carotenoid levels (p=1x10-5)-an indicator of fruit and vegetable consumption, whereas intrinsic epigenetic age acceleration (IEAA) is associated with poultry intake (p=0.03) and BMI (p=0.05). Both EEAA and IEAA were also found to relate to indicators of metabolic syndrome, which appear to mediate their associations with BMI. Metformin-the first-line medication for the treatment of type 2 diabetes-does not delay epigenetic aging in this observational study. Finally, longitudinal data suggests that an increase in BMI is associated with increase in both EEAA and IEAA.Overall, the epigenetic age analysis of blood confirms the conventional wisdom regarding the benefits of eating a high plant diet with lean meats, moderate alcohol consumption, physical activity, and education, as well as the health risks of obesity and metabolic syndrome.

Individual CpG sites that are associated with age and life expectancy become hypomethylated upon aging

BACKGROUND

There is a growing interest in simple molecular biomarkers for biological aging. Age-associated DNA methylation (DNAm) changes at specific CG dinucleotides can be combined into epigenetic age predictors to estimate chronological age-and the deviation of chronological and predicted age (∆_age) seems to be associated with all-cause mortality. In this study, we have further validated this association and analyzed whether or not individual age-associated CG-dinucleotides (CpGs) are related to life expectancy.

FINDINGS

In the German ESTHER cohort, we used 864 DNAm profiles of blood samples as the discovery set and 1000 DNAm profiles as the validation set to predict chronological age with three previously reported age predictors-based on 99, 71, or 353 age-associated CpGs. Several of these individual CpGs were significantly associated with life expectancy, and for some of these CpGs, this was even reproducible in the independent datasets. Notably, those CpGs that revealed significant association with life expectancy were overall rather hypomethylated upon aging.

CONCLUSION

Individual age-associated CpGs may provide biomarkers for all-cause mortality-but confounding factors need to be critically taken into consideration, and alternative methods, which facilitate more quantitative measurements at individual CpGs, might be advantageous. Our data suggest that particularly specific CpGs that become hypomethylated upon aging are indicative of biological aging.

Linking the Epigenome with Exposure Effects and Susceptibility: The Epigenetic Seed and Soil Model

The epigenome is a dynamic mediator of gene expression that shapes the way that cells, tissues, and organisms respond to their environment. Initial studies in the emerging field of "toxicoepigenetics" have described either the impact of an environmental exposure on the epigenome or the association of epigenetic signatures with the onset or progression of disease; however, the majority of these pioneering studies examined the relationship between discrete epigenetic modifications and the effects of a single environmental factor. Although these data provide critical blocks with which we construct our understanding of the role of the epigenome in susceptibility and disease, they are akin to individual letters in a complex alphabet that is used to compose the language of the epigenome. Advancing the use of epigenetic data to gain a more comprehensive understanding of the mechanisms underlying exposure effects, identify susceptible populations, and inform the next generation risk assessment depends on our ability to integrate these data in a way that accounts for their cumulative impact on gene regulation. Here we will review current examples demonstrating associations between the epigenetic impacts of intrinsic factors, such as such as age, genetics, and sex, and environmental exposures shape the epigenome and susceptibility to exposure effects and disease. We will also demonstrate how the "epigenetic seed and soil" model can be used as a conceptual framework to explain how epigenetic states are shaped by the cumulative impacts of intrinsic and extrinsic factors and how these in turn determine how an individual responds to subsequent exposure to environmental stressors.