Faster ticking rate of the epigenetic clock is associated with faster pubertal development in girls

Childhood growth and development and DNA methylation age in mid-life

BACKGROUND

In the first study of its kind, we examine the association between growth and development in early life and DNAm age biomarkers in mid-life.

METHODS

Participants were from the Medical Research Council National Survey of Health and Development (n = 1376). Four DNAm age acceleration (AgeAccel) biomarkers were measured when participants were aged 53 years: AgeAccelHannum; AgeAccelHorvath; AgeAccelLevine; and AgeAccelGrim. Exposure variables included: relative weight gain (standardised residuals from models of current weight z-score on current height, and previous weight and height z-scores); and linear growth (standardised residuals from models of current height z-score on previous height and weight z-scores) during infancy (0-2 years, weight gain only), early childhood (2-4 years), middle childhood (4-7 years) and late childhood to adolescence (7-15 years); age at menarche; and pubertal stage for men at 14-15 years. The relationship between relative weight gain and linear growth and AgeAccel was investigated using conditional growth models. We replicated analyses from the late childhood to adolescence period and pubertal timing among 240 participants from The National Child and Development Study (NCDS).

RESULTS

A 1SD increase in relative weight gain in late childhood to adolescence was associated with 0.50 years (95% CI 0.20, 0.79) higher AgeAccelGrim. Although the CI includes the null, the estimate was similar in NCDS [0.57 years (95% CI - 0.01, 1.16)] There was no strong evidence that relative weight gain and linear growth in childhood was associated with any other AgeAccel biomarker. There was no relationship between pubertal timing in men and AgeAccel biomarkers. Women who reached menarche ≥ 12 years had 1.20 years (95% CI 0.15, 2.24) higher AgeAccelGrim on average than women who reached menarche < 12 years; however, this was not replicated in NCDS and was not statistically significant after Bonferroni correction.

CONCLUSIONS

Our findings generally do not support an association between growth and AgeAccel biomarkers in mid-life. However, we found rapid weight gain during pubertal development, previously related to higher cardiovascular disease risk, to be associated with older AgeAccelGrim. Given this is an exploratory study, this finding requires replication.

DNA methylation-based age clocks: From age prediction to age reversion

Aging as an irretrievable occurrence throughout the entire life is characterized by a progressive decline in physiological functionality and enhanced disease vulnerability. Numerous studies have demonstrated that epigenetic modifications, particularly DNA methylation (DNAm), correlate with aging and age-related diseases. Several investigations have attempted to predict chronological age using the age-related alterations in the DNAm of certain CpG sites. Here we categorize different studies that tracked the aging process in the DNAm landscape to show how epigenetic age clocks evolved from a chronological age estimator to an indicator of lifespan and healthspan. We also describe the health and disease predictive potential of estimated epigenetic age acceleration regarding different clinical conditions and lifestyle factors. Considering the revealed age-related epigenetic changes, the recent age-reprogramming strategies are discussed which are promising methods for resetting the aging clocks.

The Impact of Stress Within and Across Generations: Neuroscientific and Epigenetic Considerations

The impact of stress and trauma on biological systems in humans can be substantial. They can result in epigenetic changes, accelerated brain development and sexual maturation, and predisposition to psychopathology. Such modifications may be accompanied by behavioral, emotional, and cognitive overtones during one's lifetime. Exposure during sensitive periods of neural development may lead to long-lasting effects that may not be affected by subsequent environmental interventions. The cumulative effects of life stressors in an individual may affect offspring's methylome makeup and epigenetic clocks, neurohormonal modulation and stress reactivity, and physiological and reproductive development. While offspring may suffer deleterious effects from parental stress and their own early-life adversity, these factors may also confer traits that prove beneficial and enhance fitness to their own environment. This article synthesizes the data on how stress shapes biological and behavioral dimensions, drawing from preclinical and human models. Advances in this field of knowledge should potentially allow for an improved understanding of how interventions may be increasingly tailored according to individual biomarkers and developmental history.

Determination of saliva epigenetic age in infancy, and its association with parental socio-economic characteristics and pregnancy outcomes

Epigenetic age acceleration (AA) has been associated with adverse environmental exposures and many chronic conditions. We estimated, in the NINFEA birth cohort, infant saliva epigenetic age, and investigated whether parental socio-economic position (SEP) and pregnancy outcomes are associated with infant epigenetic AA. A total of 139 saliva samples collected at on average 10.8 (range 7-17) months were used to estimate Horvath's DNA methylation age. Epigenetic AA was defined as the residual from a linear regression of epigenetic age on chronological age. Linear regression models were used to test the associations of parental SEP and pregnancy outcomes with saliva epigenetic AA. A moderate positive association was found between DNA methylation age and chronological age, with the median absolute difference of 6.8 months (standard deviation [SD] 3.9). The evidence of the association between the indicators of low SEP and epigenetic AA was weak; infants born to unemployed mothers or with low education had on average 1 month higher epigenetic age than infants of mothers with high education and employment (coefficient 0.78 months, 95% confidence intervals [CIs]: -0.79 to 2.34 for low/medium education; 0.96, 95% CI: -1.81 to 3.73 for unemployment). There was no evidence for association of gestational age, birthweight or caesarean section with infant epigenetic AA. Using the Horvath's method, DNA methylation age can be fairly accurately predicted from saliva samples already in the first months of life. This study did not reveal clear associations between either pregnancy outcomes or parental socio-economic characteristics and infant saliva epigenetic AA.

The Effects of Lifetime Estrogen Exposure on Breast Epigenetic Age

BACKGROUND

Estrogens are thought to contribute to breast cancer risk through cell cycling and accelerated breast aging. We hypothesize that lifetime estrogen exposure drives early epigenetic breast aging observed in healthy women. In this study, we examined associations between hormonal factors and epigenetic aging measures in healthy breast tissues.

METHODS

We extracted DNA from breast tissue specimens from 192 healthy female donors to the Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center. Methylation experiments were performed using the Illumina EPIC 850K array platform. Age-adjusted regression models were used to examine for associations between factors related to estrogen exposure and five DNA methylation-based estimates: Grim age, pan-tissue age, Hannum age, phenotypic age, and skin and blood clock age.

RESULTS

Women were aged 19-90 years, with 95 premenopausal, and 97 nulliparous women. The age difference (Grim age - chronologic age) was higher at earlier ages close to menarche. We found significant associations between earlier age at menarche and age-adjusted accelerations according to the Grim clock, the skin and blood clock, and between higher body mass index (BMI) and age-adjusted accelerations in the Grim clock, Hannum clock, phenotypic clock, and skin and blood clock.

CONCLUSIONS

Earlier age at menarche and higher BMI are associated with elevations in DNA methylation-based age estimates in healthy breast tissues, suggesting that cumulative estrogen exposure drives breast epigenetic aging.

IMPACT

Epigenetic clock measures may help advance inquiry into the relationship between accelerated breast tissue aging and an elevated incidence of breast cancer in younger women.

Internalizing symptoms associate with the pace of epigenetic aging in childhood

Childhood psychiatric symptoms may be associated with advanced biological aging. This study examined whether epigenetic age acceleration (EAA) associates with internalizing and externalizing symptoms that were prospectively collected across childhood in a longitudinal cohort study. At age 6 buccal epithelial cells from 148 children (69 girls) were collected to survey genome-wide DNA methylation. EAA was estimated using the Horvath clock. Internalizing symptoms at ages 2.5 and 4 years significantly predicted higher EAA at age 6, which in turn was significantly associated with internalizing symptoms at ages 6-10 years. Similar trends for externalizing symptoms did not reach statistical significance. These findings indicate advanced biological aging in relation to child mental health and may help better identify those at risk for lasting impairments associated with internalizing disorders.

Early life adversity, pubertal timing, and epigenetic age acceleration in adulthood

BACKGROUND

Given associations linking early life adversity, pubertal timing, and biological aging, we examined the direct and indirect effects of early life trauma on adult biological aging (via age of menarche).

METHODS

Participants were premenopausal women (N = 183). Path models evaluated whether early life trauma predicted early pubertal timing and thereby, adult epigenetic age acceleration (indexed via four epigenetic clocks: Horvath DNAm Age, Hannum DNAm Age, DNAm PhenoAge, and DNAm GrimAge). Secondary analyses explored the effects of type of trauma (abuse and neglect) and adult chronic stress status (caregiver of child with autism and non-caregiver).

RESULTS

Early life trauma and earlier age at menarche independently predicted accelerated aging based on one of the four epigenetic clocks, DNAm GrimAge, though early life trauma was not associated with age of menarche. Childhood abuse, but not neglect, predicted faster epigenetic aging; results did not differ by chronic stress status.

CONCLUSIONS

Early trauma and early menarche appear to exert independent effects on DNAm GrimAge, which has been shown to be the strongest epigenetic predictor of mortality risk. This study identifies a potential correlate or determinant of accelerated epigenetic aging-menarcheal age. Future research should address the limitations of this study by using racially diverse samples.

Pubertal mammary gland development is a key determinant of adult mammographic density

Mammographic density refers to the radiological appearance of fibroglandular and adipose tissue on a mammogram of the breast. Women with relatively high mammographic density for their age and body mass index are at significantly higher risk for breast cancer. The association between mammographic density and breast cancer risk is well-established, however the molecular and cellular events that lead to the development of high mammographic density are yet to be elucidated. Puberty is a critical time for breast development, where endocrine and paracrine signalling drive development of the mammary gland epithelium, stroma, and adipose tissue. As the relative abundance of these cell types determines the radiological appearance of the adult breast, puberty should be considered as a key developmental stage in the establishment of mammographic density. Epidemiological studies have pointed to the significance of pubertal adipose tissue deposition, as well as timing of menarche and thelarche, on adult mammographic density and breast cancer risk. Activation of hypothalamic-pituitary axes during puberty combined with genetic and epigenetic molecular determinants, together with stromal fibroblasts, extracellular matrix, and immune signalling factors in the mammary gland, act in concert to drive breast development and the relative abundance of different cell types in the adult breast. Here, we discuss the key cellular and molecular mechanisms through which pubertal mammary gland development may affect adult mammographic density and cancer risk.

A Systematic Review and Meta-analysis of Environmental, Lifestyle, and Health Factors Associated With DNA Methylation Age

DNA methylation (DNAm) algorithms of biological age provide a robust estimate of an individual's chronological age and can predict their risk of age-related disease and mortality. This study reviewed the evidence that environmental, lifestyle and health factors are associated with the Horvath and Hannum epigenetic clocks. A systematic search identified 61 studies. Chronological age was correlated with DNAm age in blood (median .83, range .13-.99). In a meta-analysis body mass index (BMI) was associated with increased DNAm age (Hannum β: 0.07, 95% CI 0.04 to 0.10; Horvath β: 0.06, 95% CI 0.02 to 0.10), but there was no association with smoking (Hannum β: 0.12, 95% CI -0.50 to 0.73; Horvath β:0.18, 95% CI -0.10 to 0.46). DNAm age was positively associated with frailty (three studies, n = 3,093), and education was negatively associated with the Hannum estimate of DNAm age specifically (four studies, n = 13,955). For most other exposures, findings were too inconsistent to draw conclusions. In conclusion, BMI was positively associated with biological aging measured using DNAm, with some evidence that frailty also increased aging. More research is needed to provide conclusive evidence regarding other exposures. This field of research has the potential to provide further insights into how to promote slower biological aging and ultimately prolong healthy life.

The use of DNA methylation clock in aging research

One of the key characteristics of aging is a progressive loss of physiological integrity, which weakens bodily functions and increases the risk of death. A robust biomarker is important for the assessment of biological age, the rate of aging, and a person's health status. DNA methylation clocks, novel biomarkers of aging, are composed of a group of cytosine-phosphate-guanine dinucleotides, the DNA methylation status of which can be used to accurately measure subjective age. These clocks are considered accurate biomarkers of chronological age for humans and other vertebrates. Numerous studies have demonstrated these clocks to quantify the rate of biological aging and the effects of longevity and anti-aging interventions. In this review, we describe the purpose and use of DNA methylation clocks in aging research.

DNA methylation-based age estimation in pediatric healthy tissues and brain tumors

Several DNA methylation clocks have been developed to reflect chronological age of human tissues, but most clocks have been trained on adult samples. The rapid methylome changes in children and the role of epigenetics in pediatric tumors calls for tools accurately estimating methylation age in children. We aimed to evaluate seven methylation clocks in multiple tissues from healthy children to inform future studies on the optimal clock for pediatric cohorts, and analyzed the methylation age in brain tumors. We found that clocks trained on pediatric samples were the best in all tested tissues, highlighting the need for dedicated clocks. For blood samples, the Skin and blood clock had the best correlation with chronological age, while PedBE was the most accurate for saliva and buccal samples, and Horvath for brain tissue. Horvath methylation age was accelerated in pediatric brain tumors and the acceleration was subtype-specific for atypical teratoid rhabdoid tumor (ATRT), ependymoma, medulloblastoma and glioma. The subtypes with the highest acceleration corresponded to the worst prognostic categories in ATRT, ependymoma and glioma, whereas the relationship was reversed in medulloblastoma. This suggests that methylation age has potential as a prognostic biomarker in pediatric brain tumors and should be further explored.

Genetic and environmental causes of variation in epigenetic aging across the lifespan

Background

DNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan.

Results

In order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0–92 years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent–offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were − 0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P < 0.02) at different rates (MZ > DZ and siblings > parent–offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent–offspring pairs. Genetic factors explained 13% (95% CI − 10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation.

Conclusions

Variation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging.

Epigenetic clock as a correlate of anxiety

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In young adult women, slower epigenetic clock predicted less symptoms of anxiety.

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In young adult women, slower epigenetic clock predicted greater cortical GM volume.

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This effect of epigenetic clock in young adult women was largest in frontal lobe.

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The link of epigenetic clock and anxiety was mediated by GM volume in frontal lobe.

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No similar relationships were found in young adult men or adolescents.

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

Association of Early-Life Adversity With Measures of Accelerated Biological Aging Among Children in China

IMPORTANCE

A growing body of literature suggests that exposure to early-life adversity (ELA) is associated with accelerated biological aging, offering 1 mechanism through which ELA may be associated with an increased risk for age-related disease. These investigations, however, have been predominantly cross-sectional and focused on adults and females.

OBJECTIVE

To evaluate associations of threat-related (ie, physical abuse) and deprivation-related (ie, emotional neglect) ELA exposure with cellular and reproductive strategy metrics of biological aging among boys and girls with specific genetic backgrounds around the period of pubertal onset.

DESIGN, SETTING, AND PARTICIPANTS

In this cohort study, 997 boys and girls in grade 1 to grade 3 from 3 large elementary schools were recruited from Bengbu, Anhui Province, China, and were followed up from March 21, 2016 (baseline; wave 1), for 4 consecutive years, through March 25, 2019.

MAIN OUTCOMES AND MEASURES

The outcome was accelerated biological aging in both cellular and reproductive strategy metrics: telomere attrition and age at thelarche (for girls) and testicular maturation (for boys). Multi-informant assessment of exposure to threat-related and deprivation-related ELA was done at baseline (wave 1) and 1-year follow-up (wave 2). The polygenic risk score (PRS) was computed based on 17 single-nucleotide variations for early pubertal timing.

RESULTS

Of the 997 participants (579 girls [58.1%]; mean [SD] age at baseline, 8.0 [0.8] years), 550 (55.2%) reported exposure to threat-related ELA and 443 (44.4%) reported exposure to deprivation-related ELA. Threat-related ELA was associated with onset of thelarche 2.6 months earlier and deprivation-related ELA with onset of thelarche 3.3 months earlier in exposed girls than in unexposed peers; these associations were observed only among girls with a low PRS. Among boys, a similar pattern was found. Threat-related ELA was associated with testicular volume of 4 mL or more 1.4 months earlier and deprivation-related ELA was associated with testicular volume of 4 mL or more 2.3 months earlier than in unexposed peers but only among those with a low PRS. Boys and girls with greater exposure to threats showed a significantly higher percentage of telomere length change during 1-year follow-up, but only among those with low PRS (boys: β = 1.50; 95% CI, 0.80-2.21; P < .001; girls: β = 2.40; 95% CI, 1.78-3.05; P < .001) and moderate PRS (boys: β = 1.09; 95% CI, 0.43-1.75; P = .001; and girls: β = 1.27; 95% CI, 0.77-1.77; P < .001). No associations of deprivation-related ELA with percentage of telomere length change were found.

CONCLUSIONS AND RELEVANCE

This study suggests that the accelerating association of ELA with biological aging might occur at an earlier age and in a genetic background-dependent and dimension-specific manner.

Cell Reprogramming Preserving Epigenetic Age: Advantages and Limitations

Our understanding of cell aging advanced significantly since the discovery of this phenomenon by Hayflick and Moorhead in 1961. In addition to the well-known shortening of telomeric regions of chromosomes, cell aging is closely associated with changes of the DNA methylation profile. Establishing, maintaining, or reversing epigenetic age of a cell is central to the technology of cell reprogramming. Two distinct approaches - iPSC- and transdifferentiation-based cell reprogramming - affect differently epigenetic age of the cells. The iPSC-based reprogramming protocols are generally believed to result in the reversion of DNA methylation profiles towards less differentiated states, while the original methylation profiles are preserved in the direct trans-differentiation protocols. Clearly, in order to develop adequate model of CNS pathologies, one has to have thorough understanding of the biological roles of DNA methylation in the development, maintenance of functional activity, tissue and cell diversity, restructuring of neural networks during learning, as well as in aging-associated neuronal decline. Direct cell reprogramming is an excellent alternative and a valuable supplement to the iPSC-based technologies both as a source of mature cells for modeling of neurodegenerative diseases, and as a novel powerful strategy for in vivo cell replacement therapy. Further advancement of the regenerative and personalized medicine will strongly depend on optimization of the production of patient-specific autologous cells involving alternative approaches of direct and indirect cell reprogramming that take into account epigenetic age of the starting cell material.

Unravelling the role of epigenetics in reproductive adaptations to early-life environment

Reproductive function adjusts in response to environmental conditions in order to optimize success. In humans, this plasticity includes age of pubertal onset, hormone levels and age at menopause. These reproductive characteristics vary across populations with distinct lifestyles and following specific childhood events, and point to a role for the early-life environment in shaping adult reproductive trajectories. Epigenetic mechanisms respond to external signals, exert long-term effects on gene expression and have been shown in animal and cellular studies to regulate normal reproductive function, strongly implicating their role in these adaptations. Moreover, human cohort data have revealed differential DNA methylation signatures in proxy tissues that are associated with reproductive phenotypic variation, although the cause-effect relationships are difficult to discern, calling for additional complementary approaches to establish functionality. In this Review, we summarize how adult reproductive function can be shaped by childhood events. We discuss why the influence of the childhood environment on adult reproductive function is an important consideration in understanding how reproduction is regulated and necessitates consideration by clinicians treating women with diverse life histories. The resolution of the molecular mechanisms responsible for human reproductive plasticity could also lead to new approaches for intervention by targeting these epigenetic modifications.

"Epigenetic clocks": Theory and applications in human biology

All humans age, but how we age-and how fast-differs considerably from person to person. This deviation between apparent age and chronological age is often referred to as "biological age" (BA) and until recently robust tools for studying BA have been scarce. "Epigenetic clocks" are starting to change this. Epigenetic clocks use predictable changes in the epigenome, usually DNA methylation, to estimate chronological age with unprecedented accuracy. More importantly, deviations between epigenetic age and chronological age predict a broad range of health outcomes and mortality risks better than chronological age alone. Thus, epigenetic clocks appear to capture fundamental molecular processes tied to BA and can serve as powerful tools for studying health, development, and aging across the lifespan. In this article, I review epigenetic clocks, especially as they relate to key theoretical and applied issues in human biology. I first provide an overview of how epigenetic clocks are constructed and what we know about them. I then discuss emerging applications of particular relevance to human biologists-those related to reproduction, life-history, stress, and the environment. I conclude with an overview of the methods necessary for implementing epigenetic clocks, including considerations of study design, sample collection, and technical considerations for processing and interpreting epigenetic clocks. The goal of this review is to highlight some of the ways that epigenetic clocks can inform questions in human biology, and vice versa, and to provide human biologists with the foundational knowledge necessary to successfully incorporate epigenetic clocks into their research.

Biological aging in childhood and adolescence following experiences of threat and deprivation: A systematic review and meta-analysis

Life history theory argues that exposure to early life adversity (ELA) accelerates development, although existing evidence for this varies. We present a meta-analysis and systematic review testing the hypothesis that ELA involving threat (e.g., violence exposure) will be associated with accelerated biological aging across multiple metrics, whereas exposure to deprivation (e.g., neglect, institutional rearing) and low-socioeconomic status (SES) will not. We meta-analyze 54 studies (n = 116,010) examining associations of ELA with pubertal timing and cellular aging (telomere length and DNA methylation age), systematically review 25 studies (n = 3,253) examining ELA and neural markers of accelerated development (cortical thickness and amygdala-prefrontal cortex functional connectivity) and evaluate whether associations of ELA with biological aging vary according to the nature of adversity experienced. ELA overall was associated with accelerated pubertal timing (d = -0.10) and cellular aging (d = -0.21), but these associations varied by adversity type. Moderator analysis revealed that ELA characterized by threat was associated with accelerated pubertal development (d = -0.26) and accelerated cellular aging (d = -0.43), but deprivation and SES were unrelated to accelerated development. Systematic review revealed associations between ELA and accelerated cortical thinning, with threat-related ELA consistently associated with thinning in ventromedial prefrontal cortex, and deprivation and SES associated with thinning in frontoparietal, default, and visual networks. There was no consistent association of ELA with amygdala-PFC connectivity. These findings suggest specificity in the types of early environmental experiences associated with accelerated biological aging and highlight the importance of evaluating how accelerated aging contributes to health disparities and whether this process can be mitigated through early intervention. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

A distinctive epigenetic ageing profile in human granulosa cells

STUDY QUESTION

Does women’s age affect the DNA methylation (DNAm) profile differently in mural granulosa cells (MGCs) from other somatic cells?

SUMMARY ANSWER

Accumulation of epimutations by age and a higher number of age-related differentially methylated regions (DMR) in MGCs were found compared to leukocytes from the same woman, suggesting that the MGCs have a distinctive epigenetic profile.

WHAT IS KNOWN ALREADY

The mechanisms underlying the decline in women’s fertility from the mid-30s remain to be fully elucidated. The DNAm age of many healthy tissues changes predictably with and follows chronological age, but DNAm age in some reproductive tissues has been shown to depart from chronological age (older: endometrium; younger: cumulus cells, spermatozoa).

STUDY DESIGN, SIZE, DURATION

This study is a multicenter cohort study based on retrospective analysis of prospectively collected data and material derived from healthy women undergoing IVF or ICSI treatment following ovarian stimulation with antagonist protocol. One hundred and nineteen women were included from September 2016 to June 2018 from four clinics in Denmark and Sweden.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Blood samples were obtained from 118 healthy women with varying ovarian reserve status. MGCs were collected from 63 of the 119 women by isolation from pooled follicles immediately after oocyte retrieval. DNA from leukocytes and MGCs was extracted and analysed with a genome-wide methylation array. Data from the methylation array were processed using the ENmix package. Subsequently, DNAm age was calculated using established and tailored age predictors and DMRs were analysed with the DMRcate package.

MAIN RESULTS AND ROLE OF CHANCE

Using established age predictors, DNAm age in MGCs was found to be considerable younger and constant (average: 2.7 years) compared to chronological age (average: 33.9 years). A Granulosa Cell clock able to predict the age of both MGCs (average: 32.4 years) and leukocytes (average: 38.8 years) was successfully developed. MGCs differed from leukocytes in having a higher number of epimutations (P = 0.003) but predicted telomere lengths unaffected by age (Pearson’s correlation coefficient = −0.1, P = 0.47). DMRs associated with age (age-DMRs) were identified in MGCs (n = 335) and in leukocytes (n = 1) with a significant enrichment in MGCs for genes involved in RNA processing (45 genes, P = 3.96 × 10−08) and gene expression (152 genes, P = 2.3 × 10−06). The top age-DMRs included the metastable epiallele VTRNA2-1, the DNAm regulator ZFP57 and the anti-Müllerian hormone (AMH) gene. The apparent discordance between different epigenetic measures of age in MGCs suggests that they reflect difference stages in the MGC life cycle.

LARGE SCALE DATA

N/A.

LIMITATIONS, REASONS FOR CAUTION

No gene expression data were available to associate with the epigenetic findings. The MGCs are collected during ovarian stimulation, which may influence DNAm; however, no correlation between FSH dose and number of epimutations was found.

WIDER IMPLICATIONS OF THE FINDINGS

Our findings underline that the somatic compartment of the follicle follows a different methylation trajectory with age than other somatic cells. The higher number of epimutations and age-DMRs in MGCs suggest that their function is affected by age.

STUDY FUNDING/COMPETING INTEREST(S)

This project is part of ReproUnion collaborative study, co-financed by the European Union, Interreg V ÖKS, the Danish National Research Foundation and the European Research Council. The authors declare no conflict of interest.

Immune epigenetic age in pregnancy and 1 year after birth: Associations with weight change

PROBLEM

Epigenetic age indices are markers of biological aging determined from DNA methylation patterns. Accelerated epigenetic age predicts morbidity and mortality. Women tend to demonstrate slower blood epigenetic aging compared to men, possibly due to female-specific hormones and reproductive milestones. Pregnancy and the post-partum period are critical reproductive periods that have not been studied yet with respect to epigenetic aging. The purpose of this paper was to examine whether pregnancy itself and an important pregnancy-related variable, changes in body mass index (BMI) between pregnancy and the post-partum period, are associated with epigenetic aging.

METHOD OF STUDY

A pilot sample of 35 women was recruited as part of the Healthy Babies Before Birth (HB3) project. Whole blood samples were collected at mid-pregnancy and 1 year post-partum. DNA methylation at both time points was assayed using Infinium 450K and EPIC chips. Epigenetic age indices were calculated using an online calculator.

RESULTS

Paired-sample t-tests were used to test differences in epigenetic age indices from pregnancy to 1 year after birth. Over this critical time span, women became younger with respect to phenotypic epigenetic age, GrimAge, DNAm PAI-1, and epigenetic age indices linked to aging-related shifts in immune cell populations, known as extrinsic epigenetic age. Post-partum BMI retention, but not prenatal BMI increases, predicted accelerated epigenetic aging.

CONCLUSION

Women appear to become younger from pregnancy to the post-partum period based on specific epigenetic age indices. Further, BMI at 1 year after birth that reflects weight retention predicted greater epigenetic aging during this period.

Current perspectives on the cellular and molecular features of epigenetic ageing

IMPACT STATEMENT

The field of epigenetic ageing is relatively new, and the speed of its expansion presents a challenge in keeping abreast with new discoveries and their implications. Several reviews have already addressed the great number of pathologies, health conditions, life-style, and external stressors that are associated with changes to the rate of epigenetic ageing. While these associations highlight and affirm the ability of epigenetic clock to capture biologically meaningful changes associated with age, they do not inform us about the underlying mechanisms. In this very early period since the development of the clock, there have been rather limited experimental research that are aimed at uncovering the mechanism. Hence, the perspective that we proffer is derived from available but nevertheless limited lines of evidence that together provide a seemingly coherent narrative that can be tested. This, we believe would be helpful towards uncovering the workings of the epigenetic clock.

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.

Psychosocial stress and epigenetic aging

Aging is the single most important risk factor for diseases that are currently the leading causes of morbidity and mortality. However, there is considerable inter-individual variability in risk for aging-related disease, and studies suggest that biological age can be influenced by multiple factors, including exposure to psychosocial stress. Among markers of biological age that can be affected by stress, the present article focuses on the so-called measures of epigenetic aging: DNA methylation-based age predictors that are measured in a range of tissues, including the brain, and can predict lifespan and healthspan. We review evidence linking exposure to diverse types of psychosocial stress, including early-life stress, cumulative stressful experiences, and low socioeconomic status, with accelerated epigenetic aging as a putative mediator of the effects of psychosocial environment on health and disease. The chapter also discusses methodological differences that may contribute to discordant findings across studies to date and plausible mechanisms that may underlie the effects of stress on the aging epigenome. Future studies examining the effects of adversity on epigenetic and other indicators of biological weathering may provide important insights into the pathogenesis of aging-related disease states.

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.

DNA methylation-based biological age, genome-wide average DNA methylation, and conventional breast cancer risk factors

DNA methylation-based biological age (DNAm age), as well as genome-wide average DNA methylation, have been reported to predict breast cancer risk. We aimed to investigate the associations between these DNA methylation-based risk factors and 18 conventional breast cancer risk factors for disease-free women. A sample of 479 individuals from the Australian Mammographic Density Twins and Sisters was used for discovery, a sample of 3354 individuals from the Melbourne Collaborative Cohort Study was used for replication, and meta-analyses pooling results from the two studies were conducted. DNAm age based on three epigenetic clocks (Hannum, Horvath and Levine) and genome-wide average DNA methylation were calculated using the HumanMethylation 450 K BeadChip assay data. The DNAm age measures were positively associated with body mass index (BMI), smoking, alcohol drinking and age at menarche (all nominal P < 0.05). Genome-wide average DNA methylation was negatively associated with smoking and number of live births, and positively associated with age at first live birth (all nominal P < 0.05). The association of DNAm age with BMI was also evident in within-twin-pair analyses that control for familial factors. This study suggests that some lifestyle and hormonal risk factors are associated with these DNA methylation-based breast cancer risk factors, and the observed associations are unlikely to be due to familial confounding but are likely causal. DNA methylation-based risk factors could interplay with conventional risk factors in modifying breast cancer risk.

Exposure to polybrominated biphenyl and stochastic epigenetic mutations: application of a novel epigenetic approach to environmental exposure in the Michigan polybrominated biphenyl registry

Endocrine-disrupting compounds are associated with altered epigenetic regulation and adverse health outcomes, although inconsistent results suggest that people have varied responses to the same exposure. Interpersonal variation in response to environmental exposures is not identified using standard, population-based methods. However, methods that capture an individual's response, such as analyzing stochastic epigenetic mutations (SEMs), may capture currently missed effects of environmental exposure. To test whether polybrominated biphenyl (PBB) was associated with SEMs, DNA methylation was measured using Illumina's MethylationEPIC array in PBB-exposed individuals, and SEMs were identified. Association was tested using a linear regression with robust sandwich variance estimators, controlling for age, sex, lipids, and cell types. The number of SEMs was variable (range: 119-18,309), and positively associated with age (p = 1.23e-17), but not with sex (p = 0.97). PBBs and SEMs were only positively associated in people who were older when they were exposed (p = 0.02 vs. p = 0.91). Many subjects had SEMs enriched in biological pathways, particularly in pathways involved with xenobiotic metabolism and endocrine function. Higher number of SEMs was also associated with higher age acceleration (intrinsic: p = 1.70e-3; extrinsic: p = 3.59e-11), indicating that SEMs may be associated with age-related health problems. Finding an association between environmental contaminants and higher SEMs may provide insight into individual differences in response to environmental contaminants, as well as into the biological mechanism behind SEM formation. Furthermore, these results suggest that people may be particularly vulnerable to epigenetic dysregulation from environmental exposures as they age.

Environmental exposure to polybrominated biphenyl (PBB) associates with an increased rate of biological aging

Advanced age increases risk for cancer, cardiovascular disease, and all-cause mortality. However, people do not age at the same rate, and biological age (frequently measured through DNA methylation) can be older than chronological age. Environmental factors have been associated with the rate of biological aging, but it is not known whether persistent endocrine-disrupting compounds (EDCs) like polybrominated biphenyl (PBB) would associate with age acceleration. Three different epigenetic age acceleration measures (intrinsic, extrinsic, and phenotypic) were calculated from existing epigenetic data in whole blood from a population highly exposed to PBB (N=658). Association between serum PBB concentration and these measures was tested, controlling for sex, lipid levels, and estimated cell type proportions. Higher PBB levels associated with increased age acceleration (intrinsic: β=0.24, 95%CI=0.01-0.46, p = 0.03; extrinsic: β=0.39, 95%CI=0.12-0.65, p = 0.004; and phenotypic: β=0.30, 95%CI=0.05-0.54, p = 0.01). Neither age when exposed to PBB nor sex statistically interacted with PBB to predict age acceleration, but, in stratified analyses, the association between PBB and age acceleration was only in people exposed before finishing puberty and in men. This suggests that EDCs can associate with the biological aging process, and further studies are warranted to investigate other environmental pollutants' effect on aging.

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?

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.

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.

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.

Developmental Tuning of Epigenetic Clock

Research in the field of gerontology has traditionally focused on later life stages. There is increasing evidence, however, that both the rate of age-related functional decline and the later-life health status can be programmed during early development. The central role of epigenetic mechanisms (methylation of DNA, histone modifications and regulation by non-coding RNAs) in mediating these long-term effects has been elucidated. Both rate and direction of age-associated change of epigenetic patterns (“epigenetic drift”) were shown to be largely dependent on early-life environmental conditions. Inter-individual divergences in epigenetic profiles may arise following the stochastic errors in maintaining epigenetic marks, but they may also be adaptively mediated by specific environmental cues. Recent cohort studies indicate that ticking rate of epigenetic clock, estimated by a DNA methylation-based methods, may be developmentally adjusted, and that individual’s discrepancies among epigenetic and chronological age would be likely programmed early in development. In this Perspective article, recent findings suggesting the importance of early-life determinants for life-course dynamics of epigenetic drift are summarized and discussed.

Developmental programming of aging trajectory

There is accumulating evidence that aging phenotype and longevity may be developmentally programmed. Main mechanisms linking developmental conditions to later-life health outcomes include persistent changes in epigenetic regulation, (re)programming of major endocrine axes such as growth hormone/insulin-like growth factor axis and hypothalamic-pituitary-adrenal axis and also early-life immune maturation. Recently, evidence has also been generated on the role of telomere biology in developmental programming of aging trajectory. In addition, persisting changes of intestinal microbiota appears to be crucially involved in these processes. In this review, experimental and epidemiological evidence on the role of early-life conditions in programming of aging phenotypes are presented and mechanisms potentially underlying these associations are discussed.

Epigenetic Clocks

Recent research has revealed clock-like patterns of epigenetic change across the life span in humans. Models describing these epigenetic changes have been dubbed "epigenetic clocks," and they can not only predict chronological age but also reveal biological age, which measures physiological homeostasis and deterioration over the life span. Comparative studies of the epigenetic clocks of different primate species are likely to provide insights into the evolution of life history schedules, as well as shed light on the physiological and genetic bases of aging and aging-related diseases. Chronological age estimation using clock-based calculators may also offer biological anthropologists a useful tool for applying to forensic and demographic studies.

Genetics of pubertal timing

PURPOSE OF REVIEW

To summarize advances in the genetics underlying variation in normal pubertal timing, precocious puberty, and delayed puberty, and to discuss mechanisms by which genes may regulate pubertal timing.

RECENT FINDINGS

Genome-wide association studies have identified hundreds of loci that affect pubertal timing in the general population in both sexes and across ethnic groups. Single genes have been implicated in both precocious and delayed puberty. Potential mechanisms for how these genetic loci influence pubertal timing may include effects on the development and function of the GnRH neuronal network and the responsiveness of end-organs.

SUMMARY

There has been significant progress in identifying genetic loci that affect normal pubertal timing, and the first single-gene causes of precocious and delayed puberty are being described. How these genes influence pubertal timing remains to be determined.

Multi-tissue DNA methylation age: Molecular relationships and perspectives for advancing biomarker utility

The multi-tissue DNA methylation estimator of chronological age (DNAm-age) has been associated with a wide range of exposures and health outcomes. Still, it is unclear how DNAm-age can have such broad relationships and how it can be best utilized as a biomarker. Understanding DNAm-age's molecular relationships is a promising approach to address this critical knowledge gap. In this review, we discuss the existing literature regarding DNAm-age's molecular relationships in six major categories: animal model systems, cancer processes, cellular aging processes, immune system processes, metabolic processes, and nucleic acid processes. We also present perspectives regarding the future of DNAm-age research, including the need to translate a greater number of ongoing research efforts to experimental and animal model systems.