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

Attitudes to ageing, biomarkers of ageing and mortality: the Lothian Birth Cohort 1936

Objective

To investigate whether people with more positive attitudes to ageing are biologically younger as defined by leucocyte telomere length, accelerated DNA methylation GrimAge (AgeAccelGrim) and brain-predicted age difference, and whether these biomarkers explain relationships between attitudes to ageing and mortality.

Methods

We used linear regression to examine cross-sectionally attitudes to ageing (measured using the Attitudes to Ageing Questionnaire) and the three biomarkers in 758 adults, mean age 72.5 years, from the Lothian Birth Cohort 1936. We used Cox proportional hazards models to examine longitudinally attitudes to ageing and mortality and the role of the biomarkers.

Results

More positive attitude to physical change was associated with younger biological age, as measured by AgeAccelGrim and brain-predicted age difference in age-adjusted and sex-adjusted models: for an SD higher score, AgeAccelGrim was lower by -0.73 (95% CI -1.03 to -0.42) of a year, and brain-predicted age difference was lower by -0.87 (1.51 to 0.23) of a year. Both associations were attenuated by adjustment for covariates and not significant after simultaneous adjustment for all covariates and correction for multiple testing. More positive attitudes to physical change were associated with lower mortality: for an SD higher score the age-adjusted and sex-adjusted HR (95% CI) was 0.66 (0.56 to 0.78). Adjustment for AgeAccelGrim or brain-predicted age difference attenuated this association slightly. It remained significant after adjustment for all covariates.

Conclusion

We found partial evidence that attitudes to ageing are linked with ageing biomarkers but they accounted for only a little of the association between attitudes and mortality.

Association of adult lung function with accelerated biological aging

Lung function, strongly associated with morbidity and mortality, decreases with age. This study examines whether poor adult lung function is associated with age accelerations (AAs). DNA methylation (DNAm) based AAs, lifespan predictors (GrimAge and plasminogen activator inhibitor 1-PAI1) and their related age-adjusted measures were estimated from peripheral blood at two time points (8-to-11 years apart) in adults from two cohorts: SAPALDIA (n=987) and ECRHS (n=509). Within each cohort and stratified by gender (except for estimators from GrimAge and PAI1), AAs were used as predictors in multivariate linear regression with cross-sectional lung function parameters, and in covariate-adjusted mixed linear regression with longitudinal change in lung function and meta-analysed.

AAs were found cross-sectionally associated with lower mean FEV1 (Forced Expiratory Volume in one second) (AA-residuals:P-value=4x10^-4; Intrinsic Epigenetic AA:P-value=2x10^-4) in females at the follow-up time point only, and the same trend was observed for FVC (Forced Vital Capacity). Both lifespan and plasma level predictors were observed strongly associated with lung function decline and the decline was stronger in the follow-up time points (strongest association between FEV1 and DNAmAge GrimAge:P-value=1.25x10^-17).

This study suggests that DNAm based lifespan and plasma level predictors can be utilised as important factors to assess lung health in adults.

Psychosocial Stress, Glucocorticoid Signaling, and Prostate Cancer Health Disparities in African American Men

Recent advances in our understanding of racial disparities in prostate cancer (PCa) incidence and mortality that disproportionately affect African American (AA) men have provided important insights into the psychosocial, socioeconomic, environmental, and molecular contributors. There is, however, limited mechanistic knowledge of how the interplay between these determinants influences prostate tumor aggressiveness in AA men and other men of African ancestry. Growing evidence indicates that chronic psychosocial stress in AA populations leads to sustained glucocorticoid signaling through the glucocorticoid receptor (GR), with negative physiological and pathological consequences. Compelling evidence indicates that treatment of castration-resistant prostate cancer (CRPC) with anti-androgen therapy activates GR signaling. This enhanced GR signaling bypasses androgen receptor (AR) signaling and transcriptionally activates both AR-target genes and GR-target genes, resulting in increased prostate tumor resistance to anti-androgen therapy, chemotherapy, and radiotherapy. Given its enhanced signaling in AA men, GR-together with specific genetic drivers-may promote CRPC progression and exacerbate tumor aggressiveness in this population, potentially contributing to PCa mortality disparities. Ongoing and future CRPC clinical trials that combine standard of care therapies with GR modulators should assess racial differences in therapy response and clinical outcomes in order to improve PCa health disparities that continue to exist for AA men.

Methodological challenges in constructing DNA methylation risk scores

Polygenic approaches often access more variance of complex traits than is possible by single variant approaches. For genotype data, genetic risk scores (GRS) are widely used for risk prediction as well as in association and interaction studies. Recently, interest has been growing in transferring GRS approaches to DNA methylation data (methylation risk scores, MRS), which can be used 1) as biomarkers for environmental exposures, 2) in association analyses in which single CpG sites do not achieve significance, 3) as dimension reduction approach in interaction and mediation analyses, and 4) to predict individual risks of disease or treatment success. Most GRS approaches can directly be transferred to methylation data. However, since methylation data is more sensitive to confounding, e.g. by age and tissue, it is more complex to find appropriate external weights. In this review, we will outline the adaption of current GRS approaches to methylation data and highlight occurring challenges.

Accelerated epigenetic age and cognitive decline among urban-dwelling adults

OBJECTIVES

Epigenetic modifications are closely linked with aging, but their relationship with cognition remains equivocal. Given known sex differences in epigenetic aging, we explored sex-specific associations of 3 DNA methylation (DNAm)-based measures of epigenetic age acceleration (EAA) with baseline and longitudinal change in cognitive performance among middle-aged urban adults.

METHODS

We used exploratory data from a subgroup of participants in the Healthy Aging in Neighborhoods of Diversity across the Life Span study with complete DNA samples and whose baseline ages were >50.0 years (2004-2009) to estimate 3 DNAm EAA measures: (1) universal EAA (AgeAccel); (2) intrinsic EAA (IEAA); and (3) extrinsic EAA (EEAA). Cognitive performance was measured at baseline visit (2004-2009) and first follow-up (2009-2013) with 11 test scores covering global mental status and specific domains such as learning/memory, attention, visuospatial, psychomotor speed, language/verbal, and executive function. A series of mixed-effects regression models were conducted adjusting for covariates and multiple testing (n = 147-156, ∼51% men, k = 1.7-1.9 observations/participant, mean follow-up time ∼4.7 years).

RESULTS

EEAA, a measure of both biological age and immunosenescence, was consistently associated with greater cognitive decline among men on tests of visual memory/visuoconstructive ability (Benton Visual Retention Test: γ₁₁ = 0.0512 ± 0.0176, p = 0.004) and attention/processing speed (Trail-Making Test, part A: γ₁₁ = 0.219 ± 0.080, p = 0.007). AgeAccel and IEAA were not associated with cognitive change in this sample.

CONCLUSIONS

EEAA capturing immune system cell aging was associated with faster decline among men in domains of attention and visual memory. Larger longitudinal studies are needed to replicate our findings.

Accelerated DNA methylation age and the use of antihypertensive medication among older adults

The discrepancy of DNA methylation age (DNAmAge) with chronological age (termed as age acceleration, AA) has been identified to be associated with many aging-related health outcomes including hypertension. Since taking antihypertensive medication (AHM) could prevent aging-related diseases caused by hypertension, we hypothesized that using AHM could also reduce the AA. We examined this hypothesis among 546 males aged 55–85 years by exploring the associations of AHM use with AA and its change rate (Δ_AA) in two visits with a median follow-up of 3.86 years. Horvath DNAmAge was derived from DNA methylation profiles measured by Illumina HumanMethylation450 BeadChip and information on AHM use was collected by physician interview. A general decreasing pattern of AA was observed between the two visits. After the fully adjusting for potential covariates including hypertension, any AHM use showed a cross-sectional significant association with higher AA at each visit, as well as a longitudinal association with increased Δ_AA between visits. Particularly, relative to participants who never took any AHM, individuals with continuous AHM use had a higher Δ_AA of 0.6 year/chronological year. This finding underlines that DNAmAge and AA may not be able to capture the preventive effects of AHMs that reduce cardiovascular risks and mortality.

DNA methylation-based age prediction and telomere length in white blood cells and cumulus cells of infertile women with normal or poor response to ovarian stimulation

An algorithm assessing the methylation levels of 353 informative CpG sites in the human genome permits accurate prediction of the chronologic age of a subject. Interestingly, when there is discrepancy between the predicted age and chronologic age (age acceleration or "AgeAccel"), patients are at risk for morbidity and mortality. Identification of infertile patients at risk for accelerated reproductive senescence may permit preventative action. This study aimed to assess the accuracy of the "epigenetic clock" concept in reproductive age women undergoing fertility treatment by applying the age prediction algorithm in peripheral (white blood cells [WBCs]) and follicular somatic cells (cumulus cells [CCs]), and to identify whether women with premature reproductive aging (diminished ovarian reserve) were at risk of AgeAccel in their age prediction. Results indicated that the epigenetic algorithm accurately predicts age when applied to WBCs but not to CCs. The age prediction of CCs was substantially younger than chronologic age regardless of the patient's age or response to stimulation. In addition, telomeres of CCs were significantly longer than that of WBCs. Our findings suggest that CCs do not demonstrate changes in methylome-predicted age or telomere-length in association with increasing female age or ovarian response to stimulation.

Systematic underestimation of the epigenetic clock and age acceleration in older subjects

Background

The Horvath epigenetic clock is widely used. It predicts age quite well from 353 CpG sites in the DNA methylation profile in unknown samples and has been used to calculate “age acceleration” in various tissues and environments.

Results

The model systematically underestimates age in tissues from older people. This is seen in all examined tissues but most strongly in the cerebellum and is consistently observed in multiple datasets. Age acceleration is thus age-dependent, and this can lead to spurious associations. The current literature includes examples of association tests with age acceleration calculated in a wide variety of ways.

Conclusions

The concept of an epigenetic clock is compelling, but caution should be taken in interpreting associations with age acceleration. Association tests of age acceleration should include age as a covariate.

Epigenetic gestational age and trajectories of weight and height during childhood: a prospective cohort study

Background

Differences between an individual’s estimated epigenetic gestational age (EGA) and their actual gestational age (GA) are defined as gestational age acceleration (GAA). GAA is associated with increased birthweight and birth length. Whether these associations persist through childhood is yet to be investigated.

Methods

We examined the association between GAA and trajectories of height and weight from birth to 10 years (n = 785) in a British birth cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). EGA of participants was estimated using DNA methylation data from cord blood using a recently developed prediction model. GAA of participants, measured in weeks, was calculated as the residuals from a regression model of EGA on actual GA. Analyses were performed using linear spline multilevel models and adjusted for maternal age, maternal pre-pregnancy BMI, maternal smoking during pregnancy, and maternal education.

Results

In adjusted analyses, offspring with a one-week greater GAA were born on average 0.14 kg heavier (95% confidence interval (CI) 0.09, 0.19) and 0.55 cm taller (95% CI 0.33, 0.78) at birth. These differences in weight persisted up to approximately age 9 months but thereafter began to attenuate. From age 5 years onwards, the association between GAA and weight reversed such that GAA was associated with lower weight and this association strengthened with age (mean difference at age 10 years − 0.60 kg, 95% CI − 1.19, − 0.01). Differences in height persisted only up to age 9 months (mean difference at 9 months 0.15 cm, 95% CI − 0.09, 0.39). From age 9 months to age 10 years, offspring with a one-week greater GAA were of comparable height with those with no GAA (mean difference at age 10 years − 0.07 cm, 95% CI − 0.64, 0.50).

Conclusions

Gestational age acceleration is associated with increased birth weight and length and these differences persist to age 9 months. From age 5 years onwards, the association of GAA and weight reverses such that by age 10 years, greater GAA is associated with lower childhood weight. Further work is required to examine whether the weight effects of GAA strengthen through adolescence and into early adulthood.

Methylation signatures in peripheral blood are associated with marked age acceleration and disease progression in patients with primary sclerosing cholangitis

Background & Aims

A DNA methylation (DNAm) signature derived from 353 CpG sites (the Horvath clock) has been proposed as an epigenetic measure of chronological and biological age. This epigenetic signature is accelerated in diverse tissue types in various disorders, including non-alcoholic steatohepatitis, and is associated with mortality. Here, we assayed whole blood DNAm to explore age acceleration in patients with primary sclerosing cholangitis (PSC).

Methods

Using the MethylationEPIC BeadChip (850K) array, DNAm signatures in whole blood were analyzed in 36 patients with PSC enrolled in a 96-week trial of simtuzumab (Ishak F0-1, n = 13; F5-6, n = 23). Age acceleration was calculated as the difference between DNAm age and chronological age. Comparisons between patients with high and low age acceleration (≥ vs. < the median) were made and Cox regression evaluated the association between age acceleration and PSC-related clinical events (e.g. decompensation, cholangitis, transplantation).

Results

Age acceleration was significantly higher in patients with PSC compared to a healthy reference cohort (median, 11.1 years, p <2.2 × 10^-16). In PSC, demographics, presence of inflammatory bowel disease, and ursodeoxycholic acid use were similar between patients with low and high age acceleration. However, patients with high age acceleration had increased serum alkaline phosphatase, gamma glutamyltransferase, alanine aminotransferase, enhanced liver fibrosis test scores, and greater hepatic collagen and α-smooth muscle actin expression on liver biopsy (all p <0.05). Moreover, patients with high age acceleration had an increased prevalence of cirrhosis (89% vs. 39%; p = 0.006) and greater likelihood of PSC-related events (hazard ratio 4.19; 95% CI 1.15–15.24).

Conclusion

This analysis of blood DNAm profiles suggests that compared with healthy controls, patients with PSC – particularly those with cirrhosis - exhibit significant acceleration of epigenetic age. Future studies are required to evaluate the prognostic implications and effect of therapies on global methylation patterns and age acceleration in PSC.

Lay summary

An epigenetic clock based on DNA methylation has been proposed as a marker of age. In liver diseases such as non-alcoholic steatohepatitis, age acceleration based on this epigenetic clock has been observed. Herein, we show that patients with primary sclerosing cholangitis have marked age acceleration, which is further accentuated by worsening fibrosis. This measure of age acceleration could be a useful marker for prognostication or risk stratification in primary sclerosing cholangitis.

•

A peripheral blood DNA methylation (DNAm) score identifies age acceleration in PSC patients vs. healthy controls.

•

PSC patients with high age acceleration had significantly more PSC-related events than those with low age acceleration.

•

These findings may enable stratification of at-risk PSC patients based on a DNAm score from peripheral blood.

DNA methylation is associated with lung function in never smokers

BACKGROUND

Active smoking is the main risk factor for COPD. Here, epigenetic mechanisms may play a role, since cigarette smoking is associated with differential DNA methylation in whole blood. So far, it is unclear whether epigenetics also play a role in subjects with COPD who never smoked. Therefore, we aimed to identify differential DNA methylation associated with lung function in never smokers.

METHODS

We determined epigenome-wide DNA methylation levels of 396,243 CpG-sites (Illumina 450 K) in blood of never smokers in four independent cohorts, LifeLines COPD&C (N = 903), LifeLines DEEP (N = 166), Rotterdam Study (RS)-III (N = 150) and RS-BIOS (N = 206). We meta-analyzed the cohort-specific methylation results to identify differentially methylated CpG-sites with FEV₁/FVC. Expression Quantitative Trait Methylation (eQTM) analysis was performed in the Biobank-based Integrative Omics Studies (BIOS).

RESULTS

A total of 36 CpG-sites were associated with FEV₁/FVC in never smokers at p-value< 0.0001, but the meta-analysis did not reveal any epigenome-wide significant CpG-sites. Of interest, 35 of these 36 CpG-sites have not been associated with lung function before in studies including subjects irrespective of smoking history. Among the top hits were cg10012512, cg02885771, annotated to the gene LTV1 Ribosome Biogenesis factor (LTV1), and cg25105536, annotated to Kelch Like Family Member 32 (KLHL32). Moreover, a total of 11 eQTMS were identified.

CONCLUSIONS

With the identification of 35 CpG-sites that are unique for never smokers, our study shows that DNA methylation is also associated with FEV₁/FVC in subjects that never smoked and therefore not merely related to smoking.

DNA methylation aging clocks: challenges and recommendations

Epigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.

A multi-tissue full lifespan epigenetic clock for mice

Human DNA-methylation data have been used to develop highly accurate biomarkers of aging ("epigenetic clocks"). Recent studies demonstrate that similar epigenetic clocks for mice (Mus Musculus) can be slowed by gold standard anti-aging interventions such as calorie restriction and growth hormone receptor knock-outs. Using DNA methylation data from previous publications with data collected in house for a total 1189 samples spanning 193,651 CpG sites, we developed 4 novel epigenetic clocks by choosing different regression models (elastic net- versus ridge regression) and by considering different sets of CpGs (all CpGs vs highly conserved CpGs). We demonstrate that accurate age estimators can be built on the basis of highly conserved CpGs. However, the most accurate clock results from applying elastic net regression to all CpGs. While the anti-aging effect of calorie restriction could be detected with all types of epigenetic clocks, only ridge regression based clocks replicated the finding of slow epigenetic aging effects in dwarf mice. Overall, this study demonstrates that there are trade-offs when it comes to epigenetic clocks in mice. Highly accurate clocks might not be optimal for detecting the beneficial effects of anti-aging interventions.

Epigenetic age acceleration and metabolic syndrome in the coronary artery risk development in young adults study

Background

The metabolic syndrome (MetS) is a collection of metabolic disturbances that can lead to various cardiovascular diseases. Previous studies have shown a more adverse metabolic risk profile is associated with more advanced biological aging. The associations between epigenetic biomarkers of age with MetS, however, are not well understood. We therefore investigated the associations between epigenetic age acceleration and MetS severity score and incident MetS.

Results

A subset of study participants with available whole blood at examination years 15 and 20 from the Coronary Artery Risk Development in Young Adults Study underwent epigenomic profiling using the Illumina MethylationEPIC Beadchip (~ 850,000 sites). Intrinsic and extrinsic epigenetic age acceleration (IEAA and EEAA) were calculated from DNA methylation levels. The MetS severity score was positively associated with IEAA at years 15 (P = 0.016) and 20 (P = 0.016) and EEAA at year 20 (P = 0.040) in cross-sectional analysis. IEAA at year 20 was significantly associated with incident MetS at year 30 (OR = 1.05 [95% CI 1.01, 1.10], P = 0.028).

Conclusions

To our knowledge, this is the first report of the longitudinal association between epigenetic age acceleration and MetS. These findings suggest that a higher MetS severity score is associated with accelerated epigenetic aging and such aging may play a role in the development of metabolic disorders, potentially serving as a useful biomarker of and early detection tool for future MetS.

Computational tools for geroscience

The rapid progress of the past three decades has led the geroscience field near a point where human interventions in aging are plausible. Advances across scientific areas, such as high throughput "-omics" approaches, have led to an exponentially increasing quantity of data available for biogerontologists. To best translate the lifespan and healthspan extending interventions discovered by basic scientists into preventative medicine, it is imperative that the current data are comprehensively utilized to generate testable hypotheses about translational interventions. Building a translational pipeline for geroscience will require both systematic efforts to identify interventions that extend healthspan across taxa and diagnostics that can identify patients who may benefit from interventions prior to the onset of an age-related morbidity. Databases and computational tools that organize and analyze both the wealth of information available on basic biogerontology research and clinical data on aging populations will be critical in developing such a pipeline. Here, we review the current landscape of databases and computational resources available for translational aging research. We discuss key platforms and tools available for aging research, with a focus on how each tool can be used in concert with hypothesis driven experiments to move closer to human interventions in aging.

A meta-analysis of genome-wide association studies of epigenetic age acceleration

'Epigenetic age acceleration' is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father's age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.

Early-life adversity and neurological disease: age-old questions and novel answers

Neurological illnesses, including cognitive impairment, memory decline and dementia, affect over 50 million people worldwide, imposing a substantial burden on individuals and society. These disorders arise from a combination of genetic, environmental and experiential factors, with the latter two factors having the greatest impact during sensitive periods in development. In this Review, we focus on the contribution of adverse early-life experiences to aberrant brain maturation, which might underlie vulnerability to cognitive brain disorders. Specifically, we draw on recent robust discoveries from diverse disciplines, encompassing human studies and experimental models. These discoveries suggest that early-life adversity, especially in the perinatal period, influences the maturation of brain circuits involved in cognition. Importantly, new findings suggest that fragmented and unpredictable environmental and parental signals comprise a novel potent type of adversity, which contributes to subsequent vulnerabilities to cognitive illnesses via mechanisms involving disordered maturation of brain 'wiring'.

A meta-analysis of genome-wide association studies of epigenetic age acceleration

'Epigenetic age acceleration' is a valuable biomarker of ageing, predictive of morbidity and mortality, but for which the underlying biological mechanisms are not well established. Two commonly used measures, derived from DNA methylation, are Horvath-based (Horvath-EAA) and Hannum-based (Hannum-EAA) epigenetic age acceleration. We conducted genome-wide association studies of Horvath-EAA and Hannum-EAA in 13,493 unrelated individuals of European ancestry, to elucidate genetic determinants of differential epigenetic ageing. We identified ten independent SNPs associated with Horvath-EAA, five of which are novel. We also report 21 Horvath-EAA-associated genes including several involved in metabolism (NHLRC, TPMT) and immune system pathways (TRIM59, EDARADD). GWAS of Hannum-EAA identified one associated variant (rs1005277), and implicated 12 genes including several involved in innate immune system pathways (UBE2D3, MANBA, TRIM46), with metabolic functions (UBE2D3, MANBA), or linked to lifespan regulation (CISD2). Both measures had nominal inverse genetic correlations with father's age at death, a rough proxy for lifespan. Nominally significant genetic correlations between Hannum-EAA and lifestyle factors including smoking behaviours and education support the hypothesis that Hannum-based epigenetic ageing is sensitive to variations in environment, whereas Horvath-EAA is a more stable cellular ageing process. We identified novel SNPs and genes associated with epigenetic age acceleration, and highlighted differences in the genetic architecture of Horvath-based and Hannum-based epigenetic ageing measures. Understanding the biological mechanisms underlying individual differences in the rate of epigenetic ageing could help explain different trajectories of age-related decline.

Epigenetic Clock and Relative Telomere Length Represent Largely Different Aspects of Aging in the Berlin Aging Study II (BASE-II)

DNA methylation age (DNAm age; "epigenetic clock") has recently been described as highly correlated with chronological age. Several studies suggest that DNAm age reflects, at least in part, biological age. Here, we adapted a recently published methylation-sensitive single nucleotide primer extension method for epigenetic age estimation and calculated the DNAm age based on only seven cytosine-phosphate-guanine sites in 1,895 DNA samples of the Berlin Aging Study II. In a second step, we explored the relationship between this new potential measure of biological age with an established marker of biological age, relative leukocyte telomere length (rLTL), in the same cohort. Our results showed a positive and significant correlation between DNAm age estimation and chronological age (N = 1,895, Rs2 = .47), which persisted after adjustment for covariates (sex, leukocyte distribution, alcohol and smoking). We found a significant but weak negative association between DNAm age acceleration and rLTL in linear regression analysis adjusted for age, sex, alcohol and smoking (β = -0.002, p = .007). Therefore, DNAm age appears to be a promising biomarker in the analysis of phenotypes of aging, which are not (only) related to pathways associated with mitotic age as measured by rLTL.

Epigenetic Clocks and Allostatic Load Reveal Potential Sex-Specific Drivers of Biological Aging

Allostatic load (AL) and epigenetic clocks both attempt to characterize the accelerated aging of biological systems, but at present it is unclear whether these measures are complementary or distinct. This study examines the cross-sectional association of AL with epigenetic age acceleration (EAA) in a subsample of 490 community-dwelling older adults participating in The Irish Longitudinal study on Aging (TILDA). A battery of 14 biomarkers representing the activity of four different physiological systems: immunological, cardiovascular, metabolic, renal, was used to construct the AL score. DNA methylation age was computed according to the algorithms described by Horvath, Hannum, and Levine allowing for estimation of whether an individual is experiencing accelerated or decelerated aging. Horvath, Hannum, and Levine EAA correlated 0.05, 0.03, and 0.21 with AL, respectively. Disaggregation by sex revealed that AL was more strongly associated with EAA in men compared with women as assessed using Horvath’s clock. Metabolic dysregulation was a strong driver of EAA in men as assessed using Horvath and Levine’s clock, while metabolic and cardiovascular dysregulation were associated with EAA in women using Levine’s clock. Results indicate that AL and the epigenetic clocks are measuring different age-related variance and implicate sex-specific drivers of biological aging.

Association between epigenetic age acceleration and depressive symptoms in a prospective cohort study of urban-dwelling adults

OBJECTIVE

This study tests associations of DNA methylation-based (DNAm) measures of epigenetic age acceleration (EAA) with cross-sectional and longitudinal depressive symptoms in an urban sample of middle-aged adults.

METHODS

White and African-American adult participants in the Healthy Aging in Neighborhoods of Diversity across the Life Span study for whom DNA samples were analyzed (baseline age: 30-65 years) we included. We estimated three DNAm based EAA measures: (1) universal epigenetic age acceleration (AgeAccel); (2) intrinsic epigenetic age acceleration (IEAA); and (3) extrinsic epigenetic age acceleration (EEAA). Depressive symptoms were assessed using the 20-item Center for Epidemiological Studies-Depression scale total and sub-domain scores at baseline (2004-2009) and follow-up visits (2009-2013). Linear mixed-effects regression models were conducted, adjusting potentially confounding covariates, selection bias and multiple testing (N = 329 participants, ∼52% men, k = 1.9 observations/participant, mean follow-up time∼4.7 years).

RESULTS

None of the epigenetic age acceleration measures were associated with total depressive symptom scores at baseline or over time. IEAA - a measure of cellular epigenetic age acceleration irrespective of white blood cell composition - was cross-sectionally associated with decrement in "positive affect" in the total population (γ011± SE = -0.090 ± 0.030, P = 0.003, Cohen's D: -0.16) and among Whites (γ011 ± SE = -0.135 ± 0.048, P = 0.005, Cohen's D: -0.23), after correction for multiple testing. Baseline "positive affect" was similarly associated with AgeAccel.

LIMITATIONS

Limitations included small sample size, weak-moderate effects and measurement error.

CONCLUSIONS

IEAA and AgeAccel, two measures of EAA using Horvath algorithm, were linked to a reduced "positive affect", overall and among Whites. Future studies are needed to replicate our findings and test bi-directional relationships.

Identifying blood-specific age-related DNA methylation markers on the Illumina MethylationEPIC® BeadChip

The past decade has seen rapid development in DNA methylation (DNAm) microarrays, including the Illumina HumanMethylation27 and HumanMethylation450 (450K) chips, which have played an essential role in identifying and evaluating age-related (AR) DNAm markers in different tissues. Recently, a new array, the Illumina MethylationEPIC (EPIC) was introduced, with nearly double the number of probes as the 450K (∼850,000 probes). In this study, we test these newly added probes for age association using a large cohort of 754 DNAm profiles from blood samples assayed on the EPIC BeadChip, for individuals aged 0-88 years old. 52 AR CpG sites (Spearman's abs(rho) >0.6 and P-value <10^-83) were identified, 21 of which were novel sites and mapped to 18 genes, nine of which (LHFPL4, SLC12A8, EGFEM1P, GPR158, TAL1, KIAA1755, LOC730668, DUSP16, and FAM65C) have never previously been reported to be associated with age. The data were subsequently split into a 527-sample training set and a 227-sample testing set to build and validate two age prediction models using elastic net regression and multivariate regression. Elastic net regression selected 425 CpG markers with a mean absolute deviation (MAD) of 2.6 years based on the testing set. To build a multivariate linear regression model, AR CpG sites with R² > 0.5 at FDR < 0.05 were input into stepwise regression to select the best subset for age prediction. The resulting six CpG markers were linearly modelled with age and explained 81% of age-correlated variation in DNAm levels. Age estimation accuracy using bootstrap analysis was 4.5 years, with 95% confidence intervals of 4.56 to 4.57 years based on the testing set. These results suggest that EPIC BeadChip probes for age estimation fall within the range of probes found on the previous Illumina HumanMethylation platforms in terms of their age-prediction ability.

The effect of age on DNA methylation in whole blood among Bangladeshi men and women

BACKGROUND

It is well-known that methylation changes occur as humans age, however, understanding how age-related changes in DNA methylation vary by sex is lacking. In this study, we characterize the effect of age on DNA methylation in a sex-specific manner and determine if these effects vary by genomic context. We used the Illumina HumanMethylation 450 K array and DNA derived from whole blood for 400 adult participants (189 males and 211 females) from Bangladesh to identify age-associated CpG sites and regions and characterize the location of these age-associated sites with respect to CpG islands (vs. shore, shelf, or open sea) and gene regions (vs. intergenic). We conducted a genome-wide search for age-associated CpG sites (among 423,604 sites) using a reference-free approach to adjust for cell type composition (the R package RefFreeEWAS) and performed an independent replication analysis of age-associated CpGs.

RESULTS

The number of age-associated CpGs (p < 5 x 10- 8) were 986 among men and 3479 among women of which 2027(63.8%) and 572 (64.1%) replicated (using Bonferroni adjusted p < 1.2 × 10- 5). For both sexes, age-associated CpG sites were more likely to be hyper-methylated with increasing age (compared to hypo-methylated) and were enriched in CpG islands and promoter regions compared with other locations and all CpGs on the array. Although we observed strong correlation between chronological age and previously-developed epigenetic age models (r ≈ 0.8), among our top (based on lowest p-value) age-associated CpG sites only 12 for males and 44 for females are included in these prediction models, and the median chronological age compared to predicted age was 44 vs. 51.7 in males and 45 vs. 52.1 in females.

CONCLUSIONS

Our results describe genome-wide features of age-related changes in DNA methylation. The observed associations between age and methylation were generally consistent for both sexes, although the associations tended to be stronger among women. Our population may have unique age-related methylation changes that are not captured in the established methylation-based age prediction model we used, which was developed to be non-tissue-specific.

Education and Lifestyle Factors Are Associated with DNA Methylation Clocks in Older African Americans

DNA methylation (DNAm) clocks are important biomarkers of cellular aging and are associated with a variety of age-related chronic diseases and all-cause mortality. Examining the relationship between education and lifestyle risk factors for age-related diseases and multiple DNAm clocks can increase the understanding of how risk factors contribute to aging at the cellular level. This study explored the association between education or lifestyle risk factors for age-related diseases and the acceleration of four DNAm clocks, including intrinsic (IEAA) and extrinsic epigenetic age acceleration (EEAA), PhenoAge acceleration (PhenoAA), and GrimAge acceleration (GrimAA) in the African American participants of the Genetic Epidemiology Network of Arteriopathy. We performed both cross-sectional and longitudinal analyses. In cross-sectional analyses, gender, education, BMI, smoking, and alcohol consumption were all independently associated with GrimAA, whereas only some of them were associated with other clocks. The effect of smoking and education on GrimAA varied by gender. Longitudinal analyses suggest that age and BMI continued to increase GrimAA, and that age and current smoking continued to increase PhenoAA after controlling DNAm clocks at baseline. In conclusion, education and common lifestyle risk factors were associated with multiple DNAm clocks. However, the association with each risk factor varied by clock, which suggests that different clocks may capture adverse effects from different environmental stimuli.

Relationships of Long-Term Smoking and Moist Snuff Consumption With a DNA Methylation Age Relevant Smoking Index: An Analysis in Buccal Cells

INTRODUCTION

Currently, there is no widely accepted, non-self-report measure that simultaneously reflects smoking behaviors and is molecularly informative of general disease processes. Recently, researchers developed a smoking index (SI) using nucleated blood cells and a multi-tissue DNA methylation-based predictor of chronological age and disease (DNA methylation age [DNAm-age]). To better understand the utility of this novel SI in readily accessible cell types, we used buccal cell DNA methylation to examine SI relationships with long-term tobacco smoking and moist snuff consumption.

METHODS

We used a publicly available dataset composed of buccal cell DNA methylation values from 120 middle-aged men (40 long-term smokers, 40 moist snuff consumers, and 40 nonsmokers). DNAm-age (353-CpGs) and SI (66-CpGs) were calculated using CpG sites measured using the Illumina HumanMethylation450 BeadChip. We estimated associations of tobacco consumption habits with both SI and DNAm-age using linear regression models adjusted for chronological age, race, and methylation technical covariates.

RESULTS

In fully adjusted models with nonsmokers as the reference, smoking (β = 1.08, 95% CI = 0.82 to 1.33, p < .0001) but not snuff consumption (β = .06, 95% CI = -0.19 to 0.32, p = .63) was significantly associated with SI. SI was an excellent predictor of smoking versus nonsmoking (area under the curve = 0.92, 95% CI = 0.85 to 0.98). Four DNAm-age CpGs were differentially methylated between smokers and nonsmokers including cg14992253 [EIF3I], which has been previously shown to be differentially methylated with exposure to long-term fine-particle air pollution (PM2.5).

CONCLUSIONS

The 66-CpG SI appears to be a useful tool for measuring smoking-specific behaviors in buccal cells. Still, further research is needed to broadly confirm our findings and SI relationships with DNAm-age.

IMPLICATIONS

Our findings demonstrate that this 66-CpG blood-derived SI can reflect long-term tobacco smoking, but not long-term snuff consumption, in buccal cells. This evidence will be useful as the field works to identify an accurate non-self-report smoking biomarker that can be measured in an easily accessible tissue. Future research efforts should focus on (1) optimizing the relationship of the SI with DNAm-age so that the metric can maximize its utility as a tool for understanding general disease processes, and (2) determining normal values for the SI CpGs so that the measure is not as study sample specific.

Novel age-associated DNA methylation changes and epigenetic age acceleration in middle-aged African Americans and whites

Background

African Americans (AAs) experience premature chronic health outcomes and longevity disparities consistent with an accelerated aging phenotype. DNA methylation (DNAm) levels at specific CpG positions are hallmarks of aging evidenced by the presence of age-associated differentially methylated CpG positions (aDMPs) that are the basis for the epigenetic clock for measuring biological age acceleration. Since DNAm has not been widely studied among non-European populations, we examined the association between DNAm and chronological age in AAs and whites, and the association between race, poverty, sex, and epigenetic age acceleration.

Results

We measured genome-wide DNA methylation (866,836 CpGs) using the Illumina MethylationEPIC BeadChip in blood DNA extracted from 487 middle-aged AA (N = 244) and white (N = 243), men (N = 248), and women (N = 239). The mean (sd) age was 48.4 (8.8) in AA and 49.0 (8.7) in whites (p = 0.48). We identified 4930 significantly associated aDMPs in AAs and 469 in whites. Of these, 75.6% and 53.1% were novel, largely driven by the increased number of measured CpGs in the EPIC array, in AA and whites, respectively. AAs had more age-associated DNAm changes than whites in genes implicated in age-related diseases and cellular pathways involved in growth and development. We assessed three epigenetic age acceleration measures (universal, intrinsic, and extrinsic). AAs had a significantly slower extrinsic aging compared to whites. Furthermore, compared to AA women, both AA and white men had faster aging in the universal age acceleration measure (+ 2.04 and + 1.24 years, respectively, p < 0.05).

Conclusions

AAs have more wide-spread methylation changes than whites. Race and sex interact to underlie biological age acceleration suggesting altered DNA methylation patterns may be important in age-associated health disparities.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0722-1) contains supplementary material, which is available to authorized users.

Age-Related DNA Methylation Changes: Potential Impact on Skeletal Muscle Aging in Humans

Human aging is accompanied by a decline in muscle mass and muscle function, which is commonly referred to as sarcopenia. Sarcopenia is associated with detrimental clinical outcomes, such as a reduced quality of life, frailty, an increased risk of falls, fractures, hospitalization, and mortality. The exact underlying mechanisms of sarcopenia are poorly delineated and the molecular mechanisms driving the development and progression of this disorder remain to be uncovered. Previous studies have described age-related differences in gene expression, with one study identifying an age-specific expression signature of sarcopenia, but little is known about the influence of epigenetics, and specially of DNA methylation, in its pathogenesis. In this review, we will focus on the available knowledge in literature on the characterization of DNA methylation profiles during skeletal muscle aging and the possible impact of physical activity and nutrition. We will consider the possible use of the recently developed DNA methylation-based biomarkers of aging called epigenetic clocks in the assessment of physical performance in older individuals. Finally, we will discuss limitations and future directions of this field.

DNA methylation-based biomarkers and the epigenetic clock theory of ageing

Identifying and validating molecular targets of interventions that extend the human health span and lifespan has been difficult, as most clinical biomarkers are not sufficiently representative of the fundamental mechanisms of ageing to serve as their indicators. In a recent breakthrough, biomarkers of ageing based on DNA methylation data have enabled accurate age estimates for any tissue across the entire life course. These 'epigenetic clocks' link developmental and maintenance processes to biological ageing, giving rise to a unified theory of life course. Epigenetic biomarkers may help to address long-standing questions in many fields, including the central question: why do we age?

Genetic and epigenetic regulation of human aging and longevity

Here we summarize the latest data on genetic and epigenetic contributions to human aging and longevity. Whereas environmental and lifestyle factors are important at younger ages, the contribution of genetics appears more important in reaching extreme old age. Genome-wide studies have implicated ~57 gene loci in lifespan. Epigenomic changes during aging profoundly affect cellular function and stress resistance. Dysregulation of transcriptional and chromatin networks is likely a crucial component of aging. Large-scale bioinformatic analyses have revealed involvement of numerous interaction networks. As the young well-differentiated cell replicates into eventual senescence there is drift in the highly regulated chromatin marks towards an entropic middle-ground between repressed and active, such that genes that were previously inactive "leak". There is a breakdown in chromatin connectivity such that topologically associated domains and their insulators weaken, and well-defined blocks of constitutive heterochromatin give way to generalized, senescence-associated heterochromatin, foci. Together, these phenomena contribute to aging.

Epigenome-wide exploratory study of monozygotic twins suggests differentially methylated regions to associate with hand grip strength

Hand grip strength is a measure of muscular strength and is used to study age-related loss of physical capacity. In order to explore the biological mechanisms that influence hand grip strength variation, an epigenome-wide association study (EWAS) of hand grip strength in 672 middle-aged and elderly monozygotic twins (age 55–90 years) was performed, using both individual and twin pair level analyses, the latter controlling the influence of genetic variation. Moreover, as measurements of hand grip strength performed over 8 years were available in the elderly twins (age 73–90 at intake), a longitudinal EWAS was conducted for this subsample. No genome-wide significant CpG sites or pathways were found, however two of the suggestive top CpG sites were mapped to the COL6A1 and CACNA1B genes, known to be related to muscular dysfunction. By investigating genomic regions using the comb-p algorithm, several differentially methylated regions in regulatory domains were identified as significantly associated to hand grip strength, and pathway analyses of these regions revealed significant pathways related to the immune system, autoimmune disorders, including diabetes type 1 and viral myocarditis, as well as negative regulation of cell differentiation. The genes contributing to the immunological pathways were HLA-B, HLA-C, HLA-DMA, HLA-DPB1, MYH10, ERAP1 and IRF8, while the genes implicated in the negative regulation of cell differentiation were IRF8, CEBPD, ID2 and BRCA1. In conclusion, this exploratory study suggests hand grip strength to associate with differentially methylated regions enriched in immunological and cell differentiation pathways, and hence merits further investigations.

DNA Methylation Age-Environmental Influences, Health Impacts, and Its Role in Environmental Epidemiology

PURPOSE OF REVIEW

DNA methylation-based aging biomarkers are valuable tools for evaluating the aging process from a molecular perspective. These epigenetic aging biomarkers can be evaluated across the lifespan and are tissue specific. This review examines the literature relating environmental exposures to DNA methylation-based aging biomarkers and also the literature evaluating these biomarkers as predictors of health outcomes.

RECENT FINDINGS

Multiple studies evaluated the association between air pollution and DNA methylation age and consistently observed that higher exposures are associated with elevated DNA methylation age. Psychosocial exposures, e.g., traumas and adolescent adversity, and infections are also associated with epigenetic aging. DNA methylation age has been repeatedly associated with mortality, cancer, and cognitive impairment. DNA methylation age is responsive to the environment and predictive of health outcomes. Studies are still needed to evaluate whether DNA methylation age acts as a mediator or modifier of environmental health effects and to understand the impact of factors such as race, gender, and genetics.

Growth disrupting mutations in epigenetic regulatory molecules are associated with abnormalities of epigenetic aging

Germline mutations in fundamental epigenetic regulatory molecules including DNA methyltransferase 3 alpha (DNMT3A) are commonly associated with growth disorders, whereas somatic mutations are often associated with malignancy. We profiled genome-wide DNA methylation patterns in DNMT3A c.2312G > A; p.(Arg771Gln) carriers in a large Amish sibship with Tatton-Brown–Rahman syndrome (TBRS), their mosaic father, and 15 TBRS patients with distinct pathogenic de novo DNMT3A variants. This defined widespread DNA hypomethylation at specific genomic sites enriched at locations annotated as genes involved in morphogenesis, development, differentiation, and malignancy predisposition pathways. TBRS patients also displayed highly accelerated DNA methylation aging. These findings were most marked in a carrier of the AML-associated driver mutation p.Arg882Cys. Our studies additionally defined phenotype-related accelerated and decelerated epigenetic aging in two histone methyltransferase disorders: NSD1 Sotos syndrome overgrowth disorder and KMT2D Kabuki syndrome growth impairment. Together, our findings provide fundamental new insights into aberrant epigenetic mechanisms, the role of epigenetic machinery maintenance, and determinants of biological aging in these growth disorders.

Can markers of biological age predict dependency in old age?

Recent research has shown that markers of biological age, such as leukocyte telomere length (LTL), epigenetic clocks and the frailty index (FI) are predictive of mortality and age-related diseases. However, whether these markers associate with the need for care in old age, thereby having utility in reflecting dependency, is unclear. This study was undertaken to analyze whether LTL, two epigenetic clocks-the DNA methylation age (DNAmAge) and DNAm PhenoAge-and the FI are associated with the need for regular care in up to 604 individuals (aged 48-94 years) participating in the Swedish Adoption/Twin Study of Aging. Need for regular care was defined as receiving formal or informal help in daily routines at least once per week. Logistic regression adjusted for age, sex and education was used in the analysis. The predictive accuracies, assessed as the area under the curve (AUC) for the significant biological age measures were further compared to the accuracies of the limitations in activities of daily living (ADL) and instrumental ADL (IADL). Neither LTL nor the epigenetic clocks were associated with the need for care, whereas the FI was; odds ratio for 10% increase in FI 3.54 (95% confidence interval 2.32-5.41). The FI also demonstrated higher predictive accuracy than the ADL score (FI AUC 0.80 vs. ADL score AUC 0.62; p < 0.001 for equality of the AUCs), whereas the difference between FI AUC (0.80) and IADL score AUC (0.75) was not significant (p = 0.238). The FI might thus be a useful marker for the need for care.

Can markers of biological age predict dependency in old age?

Recent research has shown that markers of biological age, such as leukocyte telomere length (LTL), epigenetic clocks and the frailty index (FI) are predictive of mortality and age-related diseases. However, whether these markers associate with the need for care in old age, thereby having utility in reflecting dependency, is unclear. This study was undertaken to analyze whether LTL, two epigenetic clocks-the DNA methylation age (DNAmAge) and DNAm PhenoAge-and the FI are associated with the need for regular care in up to 604 individuals (aged 48-94 years) participating in the Swedish Adoption/Twin Study of Aging. Need for regular care was defined as receiving formal or informal help in daily routines at least once per week. Logistic regression adjusted for age, sex and education was used in the analysis. The predictive accuracies, assessed as the area under the curve (AUC) for the significant biological age measures were further compared to the accuracies of the limitations in activities of daily living (ADL) and instrumental ADL (IADL). Neither LTL nor the epigenetic clocks were associated with the need for care, whereas the FI was; odds ratio for 10% increase in FI 3.54 (95% confidence interval 2.32-5.41). The FI also demonstrated higher predictive accuracy than the ADL score (FI AUC 0.80 vs. ADL score AUC 0.62; p < 0.001 for equality of the AUCs), whereas the difference between FI AUC (0.80) and IADL score AUC (0.75) was not significant (p = 0.238). The FI might thus be a useful marker for the need for care.

The role of DNA methylation and hydroxymethylation in immunosenescence

A healthy functioning immune system is critical to stave off infectious diseases, but as humans and other organisms age, their immune systems decline. As a result, diseases that were readily thwarted in early life pose nontrivial harm and can even be deadly in late life. Immunosenescence is defined as the general deterioration of the immune system with age, and it is characterized by functional changes in hematopoietic stem cells (HSCs) and specific blood cell types as well as changes in levels of numerous factors, particularly those involved in inflammation. Potential mechanisms underlying immunosenescence include epigenetic changes such as changes in DNA methylation (DNAm) and DNA hydroxymethylation (DNAhm) that occur with age. The purpose of this review is to describe what is currently known about the relationship between immunosenescence and the age-related changes to DNAm and DNAhm, and to discuss experimental approaches best suited to fill gaps in our understanding.

Epigenome-wide Analysis Identifies Genes and Pathways Linked to Neurobehavioral Variation in Preterm Infants

Neonatal molecular biomarkers of neurobehavioral responses (measures of brain-behavior relationships), when combined with neurobehavioral performance measures, could lead to better predictions of long-term developmental outcomes. To this end, we examined whether variability in buccal cell DNA methylation (DNAm) associated with neurobehavioral profiles in a cohort of infants born less than 30 weeks postmenstrual age (PMA) and participating in the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study (N = 536). We tested whether epigenetic age, age acceleration, or DNAm levels at individual loci differed between infants based on their NICU Network Neurobehavioral Scale (NNNS) profile classifications. We adjusted for recruitment site, infant sex, PMA, and tissue heterogeneity. Infants with an optimally well-regulated NNNS profile had older epigenetic age compared to other NOVI infants (β1 = 0.201, p-value = 0.026), but no significant difference in age acceleration. In contrast, infants with an atypical NNNS profile had differential methylation at 29 CpG sites (FDR < 10%). Some of the genes annotated to these CpGs included PLA2G4E, TRIM9, GRIK3, and MACROD2, which have previously been associated with neurological structure and function, or with neurobehavioral disorders. These findings contribute to the existing evidence that neonatal epigenetic variations may be informative for infant neurobehavior.

DNA Methylation Clocks in Aging: Categories, Causes, and Consequences

Age-associated changes to the mammalian DNA methylome are well documented and thought to promote diseases of aging, such as cancer. Recent studies have identified collections of individual methylation sites whose aggregate methylation status measures chronological age, referred to as the DNA methylation clock. DNA methylation may also have value as a biomarker of healthy versus unhealthy aging and disease risk; in other words, a biological clock. Here we consider the relationship between the chronological and biological clocks, their underlying mechanisms, potential consequences, and their utility as biomarkers and as targets for intervention to promote healthy aging and longevity.

Vaccination in the elderly: The challenge of immune changes with aging

The unprecedented increase of life expectancy challenges society to protect the elderly from morbidity and mortality making vaccination a crucial mean to safeguard this population. Indeed, infectious diseases, such as influenza and pneumonia, are among the top killers of elderly people in the world. Elderly individuals are more prone to severe infections and less responsive to vaccination prevention, due to immunosenescence combined with the progressive increase of a proinflammatory status characteristic of the aging process (inflammaging). These factors are responsible for most age-related diseases and correlate with poor response to vaccination. Therefore, it is of utmost interest to deepen the knowledge regarding the role of inflammaging in vaccination responsiveness to support the development of effective vaccination strategies designed for elderly. In this review we analyse the impact of age-associated factors such as inflammaging, immunosenescence and immunobiography on immune response to vaccination in the elderly, and we consider systems biology approaches as a mean for integrating a multitude of data in order to rationally design vaccination approaches specifically tailored for the elderly.

Early-Life Adversity Accelerates Child and Adolescent Development

Most developmental work regards adverse developmental experiences as forces that undermine well-being. Here, I present an alternative—or complementary—view, summarizing recent evidence on puberty, endocrinology, cellular aging, and brain connectivity that collectively reveals developmental acceleration in response to contextual adversity. Findings are cast in evolutionary-developmental terms, highlighting the trade-off between accelerated aging and (a) increased morbidity and (b) premature mortality.

Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD

Background

The causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850 K Illumina EPIC array. This is the largest single population, whole-genome epigenetic study to date.

Methods

Epigenome-wide association studies (EWASs) of respiratory function and COPD were performed in peripheral blood samples from the Generation Scotland: Scottish Family Health Study (GS:SFHS) cohort (n = 3781; 274 COPD cases and 2919 controls). In independent COPD incidence data (n = 149), significantly differentially methylated sites (DMSs; p < 3.6 × 10⁻⁸) were evaluated for their added predictive power when added to a model including clinical variables, age, sex, height and smoking history using receiver operating characteristic analysis. The Lothian Birth Cohort 1936 (LBC1936) was used to replicate association (n = 895) and prediction (n = 178) results.

Findings

We identified 28 respiratory function and/or COPD associated DMSs, which mapped to genes involved in alternative splicing, JAK-STAT signalling, and axon guidance. In prediction analyses, we observed significant improvement in discrimination between COPD cases and controls (p < .05) in independent GS:SFHS (p = .016) and LBC1936 (p = .010) datasets by adding DMSs to a clinical model.

Interpretation

Identification of novel DMSs has provided insight into the molecular mechanisms regulating respiratory function and aided prediction of COPD risk. Further studies are needed to assess the causality and clinical utility of identified associations.

Fund

Wellcome Trust Strategic Award 10436/Z/14/Z.

An epigenetic pacemaker is detected via a fast conditional expectation maximization algorithm

AIM

DNA methylation has proven to be a remarkably accurate biomarker for human age, allowing the prediction of chronological age to within a couple of years. Recently, we proposed that the Universal PaceMaker (UPM), a flexible paradigm for modeling evolution, could be applied to epigenetic aging. Nevertheless, application to real data was restricted to small datasets for technical limitations.

MATERIALS & METHODS

We partition the set of variables into to two subsets and optimize the likelihood function on each set separately. This yields an extremely efficient Conditional Expectation Maximization algorithm, alternating between the two sets while increasing the overall likelihood.

RESULTS

Using the technique, we could reanalyze datasets of larger magnitude and show significant advantage to the UPM approach.

CONCLUSION

The UPM more faithfully models epigenetic aging than the time linear approach while methylated sites accelerate and decelerate jointly.

Dynamic DNA Methylation During Aging: A "Prophet" of Age-Related Outcomes

The biological markers of aging used to predict physical health status in older people are of great interest. Telomere shortening, which occurs during the process of cell replication, was initially considered a promising biomarker for the prediction of age and age-related outcomes (e.g., diseases, longevity). However, the high instability in detection and low correlation with age-related outcomes limit the extension of telomere length to the field of prediction. Currently, a growing number of studies have shown that dynamic DNA methylation throughout human lifetime exhibits strong correlation with age and age-related outcomes. Indeed, many researchers have built age prediction models with high accuracy based on age-dependent methylation changes in certain CpG loci. For now, DNA methylation based on epigenetic clocks, namely epigenetic or DNA methylation age, serves as a new standard to track chronological age and predict biological age. Measures of age acceleration (Δage, DNA methylation age – chronological age) have been developed to assess the health status of a person. In addition, there is evidence that an accelerated epigenetic age exists in patients with certain age-related diseases (e.g., Alzheimer’s disease, cardiovascular disease). In this review, we provide an overview of the dynamic signatures of DNA methylation during aging and emphasize its practical utility in the prediction of various age-related outcomes.

Epigenetic age acceleration is associated with allergy and asthma in children in Project Viva

BACKGROUND

Epigenetic clocks have been suggested to capture one feature of the complexity between aging and the epigenome. However, little is known about the epigenetic clock in childhood allergy and asthma.

OBJECTIVE

We sought to examine associations of DNA methylation age (DNAmAge) and epigenetic age acceleration with childhood allergy and asthma.

METHODS

We calculated DNAmAge and age acceleration at birth, early childhood, and midchildhood based on the IlluminaHumanMethylation450BeadChip in Project Viva. We evaluated epigenetic clock associations with allergy and asthma using covariate-adjusted linear and logistic regressions. We attempted to replicate our findings in the Genetics of Asthma in Costa Rica Study.

RESULTS

At midchildhood (mean age, 7.8 years) in Project Viva, DNAmAge and age acceleration were cross-sectionally associated with greater total serum IgE levels and greater odds of atopic sensitization. Every 1-year increase in intrinsic epigenetic age acceleration was associated with a 1.22 (95% CI, 1.07-1.39), 1.17 (95% CI, 1.03-1.34), and 1.29 (95% CI, 1.12-1.49) greater odds of atopic sensitization and environmental and food allergen sensitization. DNAmAge and extrinsic epigenetic age acceleration were also cross-sectionally associated with current asthma at midchildhood. DNAmAge and age acceleration at birth and early childhood were not associated with midchildhood allergy or asthma. The midchildhood association between age acceleration and atopic sensitization were replicated in an independent data set.

CONCLUSIONS

Because the epigenetic clock might reflect immune and developmental components of biological aging, our study suggests pathways through which molecular epigenetic mechanisms of immunity, development, and maturation can interact along the age axis and associate with childhood allergy and asthma by midchildhood.

Early Experiences of Threat, but Not Deprivation, Are Associated With Accelerated Biological Aging in Children and Adolescents

BACKGROUND

Recent conceptual models argue that early life adversity (ELA) accelerates development, which may contribute to poor mental and physical health outcomes. Evidence for accelerated development in youths comes from studies of telomere shortening or advanced pubertal development following circumscribed ELA experiences and neuroimaging studies of circuits involved in emotional processing. It is unclear whether all ELA is associated with accelerated development across global metrics of biological aging or whether this pattern emerges following specific adversity types.

METHODS

In 247 children and adolescents 8 to 16 years of age with wide variability in ELA exposure, we evaluated the hypothesis that early environments characterized by threat, but not deprivation, would be associated with accelerated development across two global biological aging metrics: DNA methylation (DNAm) age and pubertal stage relative to chronological age. We also examined whether accelerated development explained associations of ELA with depressive symptoms and externalizing problems.

RESULTS

Exposure to threat-related ELA (e.g., violence) was associated with accelerated DNAm age and advanced pubertal stage, but exposure to deprivation (e.g., neglect, food insecurity) was not. In models including both ELA types, threat-related ELA was uniquely associated with accelerated DNAm age (β = .18) and advanced pubertal stage (β = .28), whereas deprivation was uniquely associated with delayed pubertal stage (β = -.21). Older DNAm age was related to greater depressive symptoms, and a significant indirect effect of threat exposure on depressive symptoms was observed through DNAm age.

CONCLUSIONS

Early threat-related experiences are particularly associated with accelerated biological aging in youths, which may be a mechanism linking ELA with depressive symptoms.

Frailty phenotype: a clinical marker of age acceleration in the older HIV-infected population

AIM

To evaluate the association between DNA methylation and frailty in the HIV-infected population and to investigate the usefulness of assessing frailty as a clinical marker to identify age acceleration.

METHODS

Frailty was assessed according to Fried's frailty phenotype. DNA methylation was analyzed in 10 frail patients, and compared with 10 robust control patients, all with HIV. Predicted age was inferred using the Weidner's formula. Age acceleration was assessed using the difference between predicted and chronological age.

RESULTS

HIV-infected frail patients had significantly higher biological predicted ages than chronological ages (mean acceleration: 10.3 years; p = 0.012).

CONCLUSIONS

We link age acceleration and frailty in an older HIV population. Frailty could be used in this population for implementing specific clinical approaches.

DNA methylation patterns of adult survivors of adolescent/young adult Hodgkin lymphoma compared to their unaffected monozygotic twin

DNA methylation (DNAm) silences gene expression and may play a role in immune dysregulation that is characteristic of adolescent/young adult Hodgkin lymphoma (AYAHL). We used the Infinium HumanMethylation27 BeadChip to quantify DNAm in blood (N = 9 pairs, mean age 57.4 y) or saliva (N = 36 pairs, mean age 50.0 y) from long-term AYAHL survivors and their unaffected co-twins. Epigenetic aging (DNAm age) was calculated using previously described methods and compared between survivors and co-twins using paired t-tests and analyses were stratified by sample type, histology, sex, age at sample collection and time since diagnosis. Differences in blood DNAm age were observed between survivors and unaffected co-twins (64.1 vs. 61.3 years, respectively, p = .04), especially in females (p = .01); no differences in saliva DNAm age were observed. Survivors and co-twins had 74 (in blood DNA) and 6 (in saliva DNA) differentially methylated loci. Our results suggest persistent epigenetic aging in AYAHL survivors long after HL cure.

Leisure-time physical activity and DNA methylation age-a twin study

Background

Epigenetic clocks may increase our understanding on human aging and how genetic and environmental factors regulate an individual aging process. One of the most promising clocks is Horvath’s DNA methylation (DNAm) age. Age acceleration, i.e., discrepancy between DNAm age and chronological age, tells us whether the person is biologically young or old compared to his/her chronological age. Several environmental and lifestyle factors have been shown to affect life span. We investigated genetic and environmental predictors of DNAm age in young and older monozygotic (MZ) and dizygotic (DZ) twins with a focus on leisure time physical activity.

Results

Quantitative genetic modeling revealed that the relative contribution of non-shared environmental factors was larger among older compared with younger twin pairs [47% (95% CI 35, 63) vs. 26% (95% CI: 19, 35), p < 0.001]. Correspondingly, genetic variation accounted for less of the variance in older [53% (95% CI 37, 65)] compared with younger pairs [74% (95% CI 65, 82)].

We tested the hypothesis that leisure time physical activity is one of the non-shared environmental factors that affect epigenetic aging. A co-twin control analysis with older same-sex twin pairs (seven MZ and nine DZ pairs, mean age 60.4 years) who had persistent discordance in physical activity for 32 years according to reported/interviewed physical-activity data showed no differences among active and inactive co-twins, DNAm age being 60.7 vs. 61.8 years, respectively [between-group mean-difference: − 1.17 (95%CI − 3.43,1.10)]. Results from the younger cohort of twins supported findings that LTPA is not associated with DNAm age acceleration.

Conclusions

In older subjects, a larger amount of variance in DNAm age acceleration was explained by non-shared environmental factors compared to young individuals. However, leisure time physical activity during adult years has at most a minor effect on DNAm age acceleration. This is consistent with recent findings that long-term leisure time physical activity in adulthood has little effect on mortality after controlling for genetic factors.