DNA methylation age is elevated in breast tissue of healthy women

Dissecting the impact of differentiation stage, replicative history, and cell type composition on epigenetic clocks

Epigenetic clocks, built on DNA methylation patterns of bulk tissues, are powerful age predictors, but their biological basis remains incompletely understood. Here, we conducted a comparative analysis of epigenetic age in murine muscle, epithelial, and blood cell types across lifespan. Strikingly, our results show that cellular subpopulations within these tissues, including adult stem and progenitor cells as well as their differentiated progeny, exhibit different epigenetic ages. Accordingly, we experimentally demonstrate that clocks can be skewed by age-associated changes in tissue composition. Mechanistically, we provide evidence that the observed variation in epigenetic age among adult stem cells correlates with their proliferative state, and, fittingly, forced proliferation of stem cells leads to increases in epigenetic age. Collectively, our analyses elucidate the impact of cell type composition, differentiation state, and replicative potential on epigenetic age, which has implications for the interpretation of existing clocks and should inform the development of more sensitive clocks.

Exploring the causal association between epigenetic clocks and menopause age: insights from a bidirectional Mendelian randomization study

Background

Evidence suggests a connection between DNA methylation (DNAm) aging and reproductive aging. However, the causal relationship between DNAm and age at menopause remains uncertain.

Methods

Employing established DNAm epigenetic clocks, such as DNAm Hannum age acceleration (Hannum), Intrinsic epigenetic age acceleration (IEAA), DNAm-estimated granulocyte proportions (Gran), DNAm GrimAge acceleration (GrimAgeAccel), DNAm PhenoAge acceleration (PhenoAgeAccel), and DNAm-estimated plasminogen activator inhibitor-1 levels (DNAmPAIadjAge), a bidirectional Mendelian randomization (MR) study was carried out to explore the potential causality between DNAm and menopausal age. The primary analytical method used was the inverse variance weighted (IVW) estimation model, supplemented by various other estimation techniques.

Results

DNAm aging acceleration or deceleration, as indicated by Hannum, IEAA, Gran, GrimAgeAccel, PhenoAgeAccel, and DNAmPAIadjAge, did not exhibit a statistically significant causal effect on menopausal age according to forward MR analysis. However, there was a suggestive positive causal association between age at menopause and Gran (Beta = 0.0010; 95% confidence interval (CI): 0.0004, 0.0020) in reverse MR analysis.

Conclusion

The observed increase in granulocyte DNAm levels in relation to menopausal age could potentially serve as a valuable indicator for evaluating the physiological status at the onset of menopause.

Epigenetic biomarkers in aging and longevity: Current and future application

The aging process has been one of the most necessary research fields in the current century, and knowing different theories of aging and the role of different genetic, epigenetic, molecular, and environmental modulating factors in increasing the knowledge of aging mechanisms and developing appropriate diagnostic, therapeutic, and preventive ways would be helpful. One of the most conserved signs of aging is epigenetic changes, including DNA methylation, histone modifications, chromatin remodeling, noncoding RNAs, and extracellular RNAs. Numerous biological processes and hallmarks are vital in aging development, but epigenomic alterations are especially notable because of their importance in gene regulation and cellular identity. The mounting evidence points to a possible interaction between age-related epigenomic alterations and other aging hallmarks, like genome instability. To extend a healthy lifespan and possibly reverse some facets of aging and aging-related diseases, it will be crucial to comprehend global and locus-specific epigenomic modifications and recognize corresponding regulators of health and longevity. In the current study, we will aim to discuss the role of epigenomic mechanisms in aging and the most recent developments in epigenetic diagnostic biomarkers, which have the potential to focus efforts on reversing the destructive signs of aging and extending the lifespan.

Maximizing Insights from Longitudinal Epigenetic Age Data: Simulations, Applications, and Practical Guidance

Background

Epigenetic Age (EA) is an age estimate, developed using DNA methylation (DNAm) states of selected CpG sites across the genome. Although EA and chronological age are highly correlated, EA may not increase uniformly with time. Departures, known as epigenetic age acceleration (EAA), are common and have been linked to various traits and future disease risk. Limited by available data, most studies investigating these relationships have been cross-sectional - using a single EA measurement. However, the recent growth in longitudinal DNAm studies has led to analyses of associations with EA over time. These studies differ in (i) their choice of model; (ii) the primary outcome (EA vs. EAA); and (iii) in their use of chronological age or age-independent time variables to account for the temporal dynamic. We evaluated the robustness of each approach using simulations and tested our results in two real-world examples, using biological sex and birthweight as predictors of longitudinal EA.

Results

Our simulations showed most accurate effect sizes in a linear mixed model or generalized estimating equation, using chronological age as the time variable. The use of EA versus EAA as an outcome did not strongly impact estimates. Applying the optimal model in real-world data uncovered an accelerated EA rate in males and an advanced EA that decelerates over time in children with higher birthweight.

Conclusion

Our results can serve as a guide for forthcoming longitudinal EA studies, aiding in methodological decisions that may determine whether an association is accurately estimated, overestimated, or potentially overlooked.

Insights into ageing rates comparison across tissues from recalibrating cerebellum DNA methylation clock

DNA methylation (DNAm)-based age clocks have been studied extensively as a biomarker of human ageing and a risk factor for age-related diseases. Despite different tissues having vastly different rates of proliferation, it is still largely unknown whether they age at different rates. It was previously reported that the cerebellum ages slowly; however, this claim was drawn from a single clock using a relatively small sample size and so warrants further investigation. We collected the largest cerebellum DNAm dataset (N = 752) to date. We found the respective epigenetic ages are all severely underestimated by six representative DNAm age clocks, with the underestimation effects more pronounced in the four clocks whose training datasets do not include brain-related tissues. We identified 613 age-associated CpGs in the cerebellum, which accounts for only 14.5% of the number found in the middle temporal gyrus from the same population (N = 404). From the 613 cerebellum age-associated CpGs, we built a highly accurate age prediction model for the cerebellum named CerebellumClockspecific (Pearson correlation=0.941, MAD=3.18 years). Ageing rate comparisons based on the two tissue-specific clocks constructed on the 201 overlapping age-associated CpGs support the cerebellum has younger DNAm age. Nevertheless, we built BrainCortexClock to prove a single DNAm clock is able to unbiasedly estimate DNAm ages of both cerebellum and cerebral cortex, when they are adequately and equally represented in the training dataset. Comparing ageing rates across tissues using DNA methylation multi-tissue clocks is flawed. The large underestimation of age prediction for cerebellums by previous clocks mainly reflects the improper usage of these age clocks. There exist strong and consistent ageing effects on the cerebellar methylome, and we suggest the smaller number of age-associated CpG sites in cerebellum is largely attributed to its extremely low average cell replication rates.

ELF5: A Molecular Clock for Breast Aging and Cancer Susceptibility

Breast cancer is predominantly an age-related disease, with aging serving as the most significant risk factor, compounded by germline mutations in high-risk genes like BRCA1/2. Aging induces architectural changes in breast tissue, particularly affecting luminal epithelial cells by diminishing lineage-specific molecular profiles and adopting myoepithelial-like characteristics. ELF5 is an important transcription factor for both normal breast and breast cancer development. This review focuses on the role of ELF5 in normal breast development, its altered expression throughout aging, and its implications in cancer. It discusses the lineage-specific expression of ELF5, its regulatory mechanisms, and its potential as a biomarker for breast-specific biological age and cancer risk.

High DNA methylation age deceleration defines an aggressive phenotype with immunoexclusion environments in endometrial carcinoma

Like telomere shortening, global DNA hypomethylation occurs progressively with cellular divisions or in vivo aging and functions as a mitotic clock to restrain malignant transformation/progression. Several DNA-methylation (DNAm) age clocks have been established to precisely predict chronological age using normal tissues, but show DNAm age drift in tumors, which suggests disruption of this mitotic clock during carcinogenesis. Little is known about DNAm age alterations and biological/clinical implications in endometrial cancer (EC). Here we address these issues by analyzing TCGA and GSE67116 cohorts of ECs. Horvath clock analysis of these tumors unexpectedly revealed that almost 90% of them exhibited DNAm age deceleration (DNAmad) compared to patient chronological age. Combined with an additional clock named Phenoage, we identified a subset of tumors (82/429) with high DNAmad (hDNAmad+) as assessed by both clocks. Clinically, hDNAmad+ tumors were associated with advanced diseases and shorter patient survival, compared to hDNAmad- ones. Genetically, hDNAmad+ tumors were characterized by higher copy number alterations (CNAs) whereas lower tumor mutation burden. Functionally, hDNAmad+ tumors were enriched with cell cycle and DNA mismatch repair pathways. Increased PIK3CA alterations and downregulation of SCGB2A1, the inhibitor of PI3K kinase, in hDNAmad+ tumors, might promote tumor growth/proliferation and stemness. In addition, the inactivation of aging drivers/tumor suppressors (TP53, RB1, and CDKN2A) while enhanced telomere maintenance occurred more frequently in hDNAmad+ tumors, which supports sustained tumor growth. Prominently, hDNAmad+ tumors were featured with immunoexclusion microenvironments, accompanied by significantly higher levels of VTCN1 expression while lower PD-L1 and CTLA4 expression, which indicates their poor response to immune checkpoint inhibitor (ICI)-based immunotherapy. We further showed significantly higher levels of DNMT3A and 3B expression in hDNAmad+ than in hDNAmad- tumors. Thus, the tumor suppressive function of aging-like DNA hypomethylation is severely impaired in hDNAmad+ tumors, likely due to enhanced expression of DNMT3A/3B and dysregulated aging regulators. Our findings not only enrich biological knowledge of EC pathogenesis but also help improve EC risk stratification and precision ICI immunotherapy.

DNA methylation age in paired tumor and adjacent normal breast tissue in Chinese women with breast cancer

BACKGROUND

Few studies have examined epigenetic age acceleration (AA), the difference between DNA methylation (DNAm) predicted age and chronological age, in relation to somatic genomic features in paired cancer and normal tissue, with less work done in non-European populations. In this study, we aimed to examine DNAm age and its associations with breast cancer risk factors, subtypes, somatic genomic profiles including mutation and copy number alterations and other aging markers in breast tissue of Chinese breast cancer (BC) patients from Hong Kong.

METHODS

We performed genome-wide DNA methylation profiling of 196 tumor and 188 paired adjacent normal tissue collected from Chinese BC patients in Hong Kong (HKBC) using Illumina MethylationEPIC array. The DNAm age was calculated using Horvath's pan-tissue clock model. Somatic genomic features were based on data from RNA sequencing (RNASeq), whole-exome sequencing (WES), and whole-genome sequencing (WGS). Pearson's correlation (r), Kruskal-Wallis test, and regression models were used to estimate associations of DNAm AA with somatic features and breast cancer risk factors.

RESULTS

DNAm age showed a stronger correlation with chronological age in normal (Pearson r = 0.78, P < 2.2e-16) than in tumor tissue (Pearson r = 0.31, P = 7.8e-06). Although overall DNAm age or AA did not vary significantly by tissue within the same individual, luminal A tumors exhibited increased DNAm AA (P = 0.004) while HER2-enriched/basal-like tumors exhibited markedly lower DNAm AA (P = < .0001) compared with paired normal tissue. Consistent with the subtype association, tumor DNAm AA was positively correlated with ESR1 (Pearson r = 0.39, P = 6.3e-06) and PGR (Pearson r = 0.36, P = 2.4e-05) gene expression. In line with this, we found that increasing DNAm AA was associated with higher body mass index (P = 0.039) and earlier age at menarche (P = 0.035), factors that are related to cumulative exposure to estrogen. In contrast, variables indicating extensive genomic instability, such as TP53 somatic mutations, high tumor mutation/copy number alteration burden, and homologous repair deficiency were associated with lower DNAm AA.

CONCLUSIONS

Our findings provide additional insights into the complexity of breast tissue aging that is associated with the interaction of hormonal, genomic, and epigenetic mechanisms in an East Asian population.

Epigenetic age provides insight into tissue origin in endometriosis

Endometriosis is a common reproductive disease with a heterogeneous presentation. Classification attempts have thus far not offered insight into its cause or its symptoms. Endometriosis may result from the migration of shed endometrium to the peritoneal cavity. However, there are cases reported in girls without uteruses and men. While a non-retrograde menstruation origin of ectopic tissue is certain in these cases, we explored the use of DNA methylation age (DNAm age) to distinguish between retrograde and non-retrograde tissue origin in endometriosis. Using publicly available DNA methylation data and Horvath's pan-tissue epigenetic clock, we compared DNAm age and epigenetic age acceleration (EAA) of ectopic lesions to eutopic endometrium of diseased and control endometrium. We examined EAA in cancer metastasis and teratomas to control for migration and developmental origin. Disease status does not change DNAm age of eutopic endometrium, but the effect of ectopic status was profound: - 16.88 years (p = 4.82 × 10^-7). There were no differences between EAA of primary/metastatic tumor paired samples, suggesting that the observed effect is not due to tissue migration or ectopic location. Immature or mature teratoma compartments decreased DNAm age by 9.44 and 7.40 years respectively, suggesting that developmental state correlates with DNAm age. Ectopic endometriotic tissue exhibits decelerated DNAm age, similar to that observed in teratomas composed of multipotent tissue, but distinct from eutopic tissue. The migration process does not change DNAm age and eutopic endometrium is concordant with chronological age regardless of disease status. We conclude that DNAm age of ectopic lesions suggests a distinct developmental origin for a subset of lesions. This finding may assist in classifying endometriosis into distinct subtypes that may be clinically relevant.

Advancing understanding of maternal age: correlating epigenetic clocks in blood and myometrium

Background:

Advanced maternal age is currently a term defined by chronological age. However, a group of biomarkers known as epigenetic clocks, which can predict morbidity and mortality, has been used to estimate measures of biological aging. Uterine myometrial function during the process of parturition may be influenced by aging, as labor dystocia, unplanned intrapartum cesarean birth, and postpartum hemorrhage are more common in older individuals. The purpose of this study was to evaluate the use of epigenetic clocks in maternal myometrium and blood for predicting age and to evaluate the correlation of epigenetic age between the tissues.

Results:

We compared epigenetic age in blood and myometrial samples provided by women undergoing planned cesarean birth at term gestation. Chronological age ranged from 20 to 50 with a median (IQR) age of 35.5(8) years. The MethylationEPIC BeadChip was used to obtain DNA methylation data, and then epigenetic age was calculated using the Horvath, Hannum, GrimAge, and PhenoAge clocks. Spearman correlations of epigenetic age with chronological age were calculated. We tested the relationship of epigenetic age in maternal blood to epigenetic age in myometrium. Age acceleration, for each clock, was also correlated between tissues. Twenty-seven participants provided samples, and 21 matched specimens were included in the final analysis after quality control. Spearman correlation between maternal chronological age and epigenetic age were significant in three of the four clocks (pan-tissue Horvath, Hannum, and GrimAge), for both myometrium and blood samples. Correlations between blood epigenetic age and maternal age ranged from 0.72 to 0.87 (all p < 0.001). Correlations between myometrial epigenetic age and maternal age were also significant (0.62–0.70, p = 0.002), though lower than correlations seen in blood. Maternal blood epigenetic age also correlated with epigenetic age in myometrium with each of these three clocks 0.60 (p = 0.004, Horvath), 0.63 (p = 0.003, Hannum), and 0.80 (p < 0.001, GrimAge). GrimAge age acceleration had the highest correlation between tissues among the clocks (0.49, p = 0.02).

Conclusions:

Given the limited sample, this study provides insight into the potential use of epigenetic age derived from blood as a proxy for myometrial epigenetic age, which may be a useful biomarker in estimating myometrial biological age in relationship to myometrial dysfunction. GrimAge outperformed the other tested clocks in terms of concordance of epigenetic age and age acceleration between tissues; however, the Horvath and Hannum clocks may be useful depending on the outcome of interest in pregnancy.

Epigenetic clock: A promising biomarker and practical tool in aging

As a complicated process, aging is characterized by various changes at the cellular, subcellular and nuclear levels, one of which is epigenetic aging. With increasing awareness of the critical role that epigenetic alternations play in aging, DNA methylation patterns have been employed as a measure of biological age, currently referred to as the epigenetic clock. This review provides a comprehensive overview of the epigenetic clock as a biomarker of aging and a useful tool to manage healthy aging. In this burgeoning scientific field, various kinds of epigenetic clocks continue to emerge, including Horvath's clock, Hannum's clock, DNA PhenoAge, and DNA GrimAge. We hereby present the most classic epigenetic clocks, as well as their differences. Correlations of epigenetic age with morbidity, mortality and other factors suggest the potential of epigenetic clocks for risk prediction and identification in the context of aging. In particular, we summarize studies on promising age-reversing interventions, with epigenetic clocks employed as a practical tool in the efficacy evaluation. We also discuss how the lack of higher-quality information poses a major challenge, and offer some suggestions to address existing obstacles. Hopefully, our review will help provide an appropriate understanding of the epigenetic clocks, thereby enabling novel insights into the aging process and how it can be manipulated to promote healthy aging.

DNA Methylation, Aging, and Cancer Risk: A Mini-Review

Accumulation of somatic mutations and genomic instability are hallmarks of both aging and cancer. Epigenetic alterations occur across cell types and tissues with advancing age. DNA methylation-based estimates of biologic age can predict important age-related outcomes, including risk of frailty and mortality, and most recently have been shown to be associated with risk of developing cancer. In this mini-review, we examine pathways known to exhibit altered methylation in aging tissues, pre-malignant lesions, and tumors and review methodologies of epigenetic clocks that reliably predict cancer risk, including those derived from methylation studies of peripheral blood, as well as those methylation levels from within the tissues at high risk of cancer.

The impact of reproductive factors on DNA methylation-based telomere length in healthy breast tissue

Estrogen promotes breast tissue proliferation and telomerase activation. We investigated the effects of reproductive history on cell cycling and telomere length using a DNA methylation-based estimate of telomere length (DNAmTL) in breast and blood from healthy women donors. We demonstrate that DNAmTL is shorter in breast than in blood, and that nulliparous women have longer age-adjusted DNAmTL in both breast and blood, potentially explaining their higher risk of breast cancer.

Integrating Environment and Aging Research: Opportunities for Synergy and Acceleration

Despite significant overlaps in mission, the fields of environmental health sciences and aging biology are just beginning to intersect. It is increasingly clear that genetics alone does not predict an individual’s neurological aging and sensitivity to disease. Accordingly, aging neuroscience is a growing area of mutual interest within environmental health sciences. The impetus for this review came from a workshop hosted by the National Academies of Sciences, Engineering, and Medicine in June of 2020, which focused on integrating the science of aging and environmental health research. It is critical to bridge disciplines with multidisciplinary collaborations across toxicology, comparative biology, epidemiology to understand the impacts of environmental toxicant exposures and age-related outcomes. This scoping review aims to highlight overlaps and gaps in existing knowledge and identify essential research initiatives. It begins with an overview of aging biology and biomarkers, followed by examples of synergy with environmental health sciences. New areas for synergistic research and policy development are also discussed. Technological advances including next-generation sequencing and other-omics tools now offer new opportunities, including exposomic research, to integrate aging biomarkers into environmental health assessments and bridge disciplinary gaps. This is necessary to advance a more complete mechanistic understanding of how life-time exposures to toxicants and other physical and social stressors alter biological aging. New cumulative risk frameworks in environmental health sciences acknowledge that exposures and other external stressors can accumulate across the life course and the advancement of new biomarkers of exposure and response grounded in aging biology can support increased understanding of population vulnerability. Identifying the role of environmental stressors, broadly defined, on aging biology and neuroscience can similarly advance opportunities for intervention and translational research. Several areas of growing research interest include expanding exposomics and use of multi-omics, the microbiome as a mediator of environmental stressors, toxicant mixtures and neurobiology, and the role of structural and historical marginalization and racism in shaping persistent disparities in population aging and outcomes. Integrated foundational and translational aging biology research in environmental health sciences is needed to improve policy, reduce disparities, and enhance the quality of life for older individuals.

Aberrant epigenetic and transcriptional events associated with breast cancer risk

BACKGROUND

Genome-wide association studies have identified several breast cancer susceptibility loci. However, biomarkers for risk assessment are still missing. Here, we investigated cancer-related molecular changes detected in tissues from women at high risk for breast cancer prior to disease manifestation. Disease-free breast tissue cores donated by healthy women (N = 146, median age = 39 years) were processed for both methylome (MethylCap) and transcriptome (Illumina's HiSeq4000) sequencing. Analysis of tissue microarray and primary breast epithelial cells was used to confirm gene expression dysregulation.

RESULTS

Transcriptomic analysis identified 69 differentially expressed genes between women at high and those at average risk of breast cancer (Tyrer-Cuzick model) at FDR < 0.05 and fold change ≥ 2. Majority of the identified genes were involved in DNA damage checkpoint, cell cycle, and cell adhesion. Two genes, FAM83A and NEK2, were overexpressed in tissue sections (FDR < 0.01) and primary epithelial cells (p < 0.05) from high-risk breasts. Moreover, 1698 DNA methylation changes were identified in high-risk breast tissues (FDR < 0.05), partially overlapped with cancer-related signatures, and correlated with transcriptional changes (p < 0.05, r ≤ 0.5). Finally, among the participants, 35 women donated breast biopsies at two time points, and age-related molecular alterations enhanced in high-risk subjects were identified.

CONCLUSIONS

Normal breast tissue from women at high risk of breast cancer bears molecular aberrations that may contribute to breast cancer susceptibility. This study is the first molecular characterization of the true normal breast tissues, and provides an opportunity to investigate molecular markers of breast cancer risk, which may lead to new preventive approaches.

DNA Methylation Age Drift Is Associated with Poor Outcomes and De-Differentiation in Papillary and Follicular Thyroid Carcinomas

Simple Summary

Normal human tissues contain an epigenetic clock resulting from the age-dependent DNA methylation signature, which is the so-called DNA methylation (DNAm) age and can be used to precisely predict chronological age of healthy individuals. Abnormal DNAm age drift has been implicated in cancer risk and pathogenesis. Here, we observed that highly drifted DNAm age (HDDA) occurred in approximately 1/3 tumors derived from patients with papillary and follicular thyroid carcinomas. HDDA is significantly associated with dedifferentiation of tumor cells and poor patient outcomes. Thus, HDDA may serve as a new prognostic factor for thyroid carcinoma.

Abstract

Alterations in global DNA methylation play a critical role in both aging and cancer, and DNA methylation (DNAm) age drift has been implicated in cancer risk and pathogenesis. In the present study, we analyzed the TCGA cohort of papillary and follicular thyroid carcinoma (PTC and FTC) for their DNAm age and association with clinic-pathological features. In 54 noncancerous thyroid (NT) samples, DNAm age was highly correlated with patient chronological age (R² = 0.928, p = 2.6 × 10⁻³¹), but drifted to younger than chronological age in most specimens, especially those from patients >50 years old. DNAm age in 502 tumors was also correlated with patient chronological age, but to a much lesser extent (R² = 0.403). Highly drifted DNAm age (HDDA) was identified in 161 tumors, among which were 101 with DNAm age acceleration while 60 with DNAm age deceleration. Tumors with HDDA were characterized by the robust aberrations in metabolic activities, extracellular microenvironment components and inflammation/immunology responses, and dedifferentiation. Importantly, HDDA in tumors independently predicted shorter disease-free survival of patients. Collectively, NT thyroids from TC patients have younger DNAm age, while HDDA frequently occurs in TCs, and contributes to the TC progression and poor patient outcomes. HDDA may serve as a new prognostic factor for TCs.

Breast-Specific Molecular Clocks Comprised of ELF5 Expression and Promoter Methylation Identify Individuals Susceptible to Cancer Initiation

A robust breast cancer prevention strategy requires risk assessment biomarkers for early detection. We show that expression of ELF5, a transcription factor critical for normal mammary development, is downregulated in mammary luminal epithelia with age. DNA methylation of the ELF5 promoter is negatively correlated with expression in an age-dependent manner. Both ELF5 methylation and gene expression were used to build biological clocks to estimate chronological ages of mammary epithelia. ELF5 clock-based estimates of biological age in luminal epithelia from average-risk women were within three years of chronological age. Biological ages of breast epithelia from BRCA1 or BRCA2 mutation carriers, who were high risk for developing breast cancer, suggested they were accelerated by two decades relative to chronological age. The ELF5 DNA methylation clock had better performance at predicting biological age in luminal epithelial cells as compared with two other epigenetic clocks based on whole tissues. We propose that the changes in ELF5 expression or ELF5-proximal DNA methylation in luminal epithelia are emergent properties of at-risk breast tissue and constitute breast-specific biological clocks. PREVENTION RELEVANCE: ELF5 expression or DNA methylation level at the ELF5 promoter region can be used as breast-specific biological clocks to identify women at higher than average risk of breast cancer.

Castration delays epigenetic aging and feminizes DNA methylation at androgen-regulated loci

In mammals, females generally live longer than males. Nevertheless, the mechanisms underpinning sex-dependent longevity are currently unclear. Epigenetic clocks are powerful biological biomarkers capable of precisely estimating chronological age and identifying novel factors influencing the aging rate using only DNA methylation data. In this study, we developed the first epigenetic clock for domesticated sheep (Ovis aries), which can predict chronological age with a median absolute error of 5.1 months. We have discovered that castrated male sheep have a decelerated aging rate compared to intact males, mediated at least in part by the removal of androgens. Furthermore, we identified several androgen-sensitive CpG dinucleotides that become progressively hypomethylated with age in intact males, but remain stable in castrated males and females. Comparable sex-specific methylation differences in MKLN1 also exist in bat skin and a range of mouse tissues that have high androgen receptor expression, indicating that it may drive androgen-dependent hypomethylation in divergent mammalian species. In characterizing these sites, we identify biologically plausible mechanisms explaining how androgens drive male-accelerated aging.

Association of mammographic density with blood DNA methylation

Background: Altered DNA methylation may be an intermediate phenotype between breast cancer risk factors and disease. Mammographic density is a strong risk factor for breast cancer. However, no studies to date have identified an epigenetic signature of mammographic density. We performed an epigenome-wide association study of mammographic density.

Methods: White blood cell DNA methylation was measured for 385 postmenopausal women using the Illumina Infinium MethylationEPIC BeadChip array. Differential methylation was assessed using genome-wide, probe-level, and regional analyses. We implemented a resampling-based approach to improve the stability of our findings.

Results: On average, women with elevated mammographic density exhibited DNA hypermethylation within CpG islands and gene promoters compared to women with lower mammographic density. We identified 250 CpG sites for which DNA methylation was significantly associated with mammographic density. The top sites were located within genes associated with cancer, including HDLBP, TGFB2, CCT4, and PAX8, and were more likely to be located in regulatory regions of the genome. We also identified differential DNA methylation in 37 regions, including within the promoters of PAX8 and PF4, a gene involved in the regulation of angiogenesis. Overall, our results paint a picture of epigenetic dysregulation associated with mammographic density.

Conclusion: Mammographic density is associated with differential DNA methylation throughout the genome, including within genes associated with cancer. Our results suggest the potential involvement of several genes in the biological mechanisms behind differences in breast density between women. Further studies are warranted to explore these potential mechanisms and potential links to breast cancer risk.

Accelerated aging in normal breast tissue of women with breast cancer

Background

DNA methylation alterations have similar patterns in normal aging tissue and in cancer. In this study, we investigated breast tissue-specific age-related DNA methylation alterations and used those methylation sites to identify individuals with outlier phenotypes. Outlier phenotype is identified by unsupervised anomaly detection algorithms and is defined by individuals who have normal tissue age-dependent DNA methylation levels that vary dramatically from the population mean.

Methods

We generated whole-genome DNA methylation profiles (GSE160233) on purified epithelial cells and used publicly available Infinium HumanMethylation 450K array datasets (TCGA, GSE88883, GSE69914, GSE101961, and GSE74214) for discovery and validation.

Results

We found that hypermethylation in normal breast tissue is the best predictor of hypermethylation in cancer. Using unsupervised anomaly detection approaches, we found that about 10% of the individuals (39/427) were outliers for DNA methylation from 6 DNA methylation datasets. We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) than in normal samples (15/228, 5.2%). Additionally, we found significant differences between the predicted ages based on DNA methylation and the chronological ages among outliers and not-outliers. Additionally, we found that accelerated outliers (older predicted age) were more frequent in normal-adjacent to cancer (14/17, 82%) compared to normal samples from individuals without cancer (3/17, 18%). Furthermore, in matched samples, we found that the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer.

Conclusions

A subset of patients with breast cancer has severely altered epigenomes which are characterized by accelerated aging in their normal-appearing tissue. In the future, these DNA methylation sites should be studied further such as in cell-free DNA to determine their potential use as biomarkers for early detection of malignant transformation and preventive intervention in breast cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01434-7.

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.

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.

An aging and p53 related marker: HOXA5 promoter methylation negatively correlates with mRNA and protein expression in old age

The process of aging has been associated with differential patterns of DNA methylation which relate to changes in gene expression. Hence, we aimed to identify genes with significant age-related methylation differences and to study their mRNA and protein expression profile. Genome-wide DNA methylation analysis was performed with the Illumina Infinium Methylation EPIC BeadChip Microarray on bisulfite-converted DNA prepared from monocytes derived from young (average age: 23.8 yrs) and old (average age: 81.5 yrs) volunteers that are separated by at least 50 years of age difference, n=4, respectively. Differentially methylated CpG sites were assigned to the associated genes and validated by deep sequencing analysis (n=20). Demonstrating an age-associated significant increase of methylation in the promoter region (p=1x10^-8), Homeobox A5 (HOXA5), also known to activate p53, emerged as an interesting candidate for further expression analyses by Realtime PCR, ELISA and Western Blot Analysis (n=30, respectively). Consistent with its hypermethylation we observed significant HOXA5 mRNA downregulation (p=0.0053) correlating with significant p53 downregulation (p=0.0431) in the old cohort. Moreover, we observed a significant change in HOXA5 protein expression (p=3x10^-5) negatively correlating with age and promoter methylation thus qualifying HOXA5 for an eligible p53-related aging marker.

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.

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.

An epigenetic clock for human skeletal muscle

BACKGROUND

Ageing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan-tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue.

METHODS

To address this, we developed a more accurate, muscle-specific epigenetic clock based on the genome-wide DNA methylation data of 682 skeletal muscle samples from 12 independent datasets (18-89 years old, 22% women, 99% Caucasian), all generated with Illumina HumanMethylation (HM) arrays (HM27, HM450, or HMEPIC). We also took advantage of the large number of samples to conduct an epigenome-wide association study of age-associated DNA methylation patterns in skeletal muscle.

RESULTS

The newly developed clock uses 200 cytosine-phosphate-guanine dinucleotides to estimate chronological age in skeletal muscle, 16 of which are in common with the 353 cytosine-phosphate-guanine dinucleotides of the pan-tissue clock. The muscle clock outperformed the pan-tissue clock, with a median error of only 4.6 years across datasets (vs. 13.1 years for the pan-tissue clock, P < 0.0001) and an average correlation of ρ = 0.62 between actual and predicted age across datasets (vs. ρ = 0.51 for the pan-tissue clock). Lastly, we identified 180 differentially methylated regions with age in skeletal muscle at a false discovery rate < 0.005. However, gene set enrichment analysis did not reveal any enrichment for gene ontologies.

CONCLUSIONS

We have developed a muscle-specific epigenetic clock that predicts age with better accuracy than the pan-tissue clock. We implemented the muscle clock in an r package called Muscle Epigenetic Age Test available on Bioconductor to estimate epigenetic age in skeletal muscle samples. This clock may prove valuable in assessing the impact of environmental factors, such as exercise and diet, on muscle-specific biological ageing processes.

The acute effects of adjuvant radiation and chemotherapy on peripheral blood epigenetic age in early stage breast cancer patients

Survival has increased in early stage breast cancer (BC), and the late effects of treatment persist for decades. Molecular mechanisms underlying the acceleration of age-related diseases after chemotherapy and radiotherapy are poorly understood. We examined epigenetic changes in peripheral whole blood cells in early stage BC patients undergoing surgery followed by adjuvant radiotherapy, or surgery followed by adjuvant chemotherapy and radiotherapy. DNA methylation experiments were performed on whole blood samples collected before and after adjuvant therapy. Methylation profiles were used to estimate four measures of epigenetic age acceleration-intrinsic, extrinsic, phenotypic, and Grim-and cell counts. We found significant increases in extrinsic, phenotypic, and Grim epigenetic age acceleration and in estimated proportions of senescent T lymphocytes from pre- to post-treatment. When examining differential effects by treatment category, most of these increases were significant only in women undergoing radiation alone. Further studies are needed to examine whether these effects are related to the risk of cognitive and functional decline in BC survivors.

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.

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.

Estimating breast tissue-specific DNA methylation age using next-generation sequencing data

Background

DNA methylation (DNAm) age has been widely accepted as an epigenetic biomarker for biological aging. Emerging evidence suggests that DNAm age can be tissue-specific and female breast tissue ages faster than other parts of the body. The Horvath clock, which estimates DNAm age across multiple tissues, has been shown to be poorly calibrated in breast issue. We aim to develop a model to estimate breast tissue-specific DNAm age.

Methods

Genome-wide DNA methylation sequencing data were generated for 459 normal, 107 tumor, and 45 paired adjacent-normal breast tissue samples. We determined a novel set of 286 breast tissue-specific clock CpGs using penalized linear regression and developed a model to estimate breast tissue-specific DNAm age. The model was applied to estimate breast tissue-specific DNAm age in different breast tissue types and in tumors with distinct clinical characteristics to investigate cancer-related aging effects.

Results

Our estimated breast tissue-specific DNAm age was highly correlated with chronological age (r = 0.88; p = 2.9 × 10⁻³¹) in normal breast tissue. Breast tumor tissue samples exhibited a positive epigenetic age acceleration, where DNAm age was on average 7 years older than respective chronological age (p = 1.8 × 10⁻⁸). In age-matched analyses, tumor breast tissue appeared 12 and 13 years older in DNAm age than adjacent-normal and normal breast tissue (p = 4.0 × 10⁻⁶ and 1.0 × 10⁻⁶, respectively). Both HER2+ and hormone-receptor positive subtypes demonstrated significant acceleration in DNAm ages (p = 0.04 and 3.8 × 10⁻⁶, respectively), while no apparent DNAm age acceleration was observed for triple-negative breast tumors. We observed a non-linear pattern of epigenetic age acceleration with breast tumor grade. In addition, early-staged tumors showed a positive epigenetic age acceleration (p = 0.003) while late-staged tumors exhibited a non-significant negative epigenetic age acceleration (p = 0.10).

Conclusions

The intended applications for this model are wide-spread and have been shown to provide biologically meaningful results for cancer-related aging effects in breast tumor tissue. Future studies are warranted to explore whether breast tissue-specific epigenetic age acceleration is predictive of breast cancer development, treatment response, and survival as well as the clinical utility of whether this model can be extended to blood samples.

Epigenetic programming-The important first 1000 days

The perinatal period is a time of fast physiological change, including epigenetic programming. Adverse events may lead to epigenetic changes, with implications for health and disease. Our review covers the basics of clinical epigenetics and explores the latest research, including the role of epigenetic processes in complex disease phenotypes, such as neurodevelopmental, neurodegenerative and immunological disorders. Some studies suggest that epigenetic alterations are linked to early life environmental stressors, including mode of delivery, famine, psychosocial stress, severe institutional deprivation and childhood abuse. CONCLUSION: Epigenetic modifications due to perinatal environmental exposures can lead to lifelong, but potentially reversible, phenotypic alterations and disease.

Measuring biological aging in humans: A quest

The global population of individuals over the age of 65 is growing at an unprecedented rate and is expected to reach 1.6 billion by 2050. Most older individuals are affected by multiple chronic diseases, leading to complex drug treatments and increased risk of physical and cognitive disability. Improving or preserving the health and quality of life of these individuals is challenging due to a lack of well-established clinical guidelines. Physicians are often forced to engage in cycles of "trial and error" that are centered on palliative treatment of symptoms rather than the root cause, often resulting in dubious outcomes. Recently, geroscience challenged this view, proposing that the underlying biological mechanisms of aging are central to the global increase in susceptibility to disease and disability that occurs with aging. In fact, strong correlations have recently been revealed between health dimensions and phenotypes that are typical of aging, especially with autophagy, mitochondrial function, cellular senescence, and DNA methylation. Current research focuses on measuring the pace of aging to identify individuals who are "aging faster" to test and develop interventions that could prevent or delay the progression of multimorbidity and disability with aging. Understanding how the underlying biological mechanisms of aging connect to and impact longitudinal changes in health trajectories offers a unique opportunity to identify resilience mechanisms, their dynamic changes, and their impact on stress responses. Harnessing how to evoke and control resilience mechanisms in individuals with successful aging could lead to writing a new chapter in human medicine.

Protein synthesis and quality control in aging

Aging is characterized by the accumulation of damage and other deleterious changes, leading to the loss of functionality and fitness. Age-related changes occur at most levels of organization of a living organism (molecular, organellar, cellular, tissue and organ). However, protein synthesis is a major biological process, and thus understanding how it changes with age is of paramount importance. Here, we discuss the relationships between lifespan, aging, protein synthesis and translational control, and expand this analysis to the various aspects of proteome behavior in organisms with age. Characterizing the consequences of changes in protein synthesis and translation fidelity, and determining whether altered translation is pathological or adaptive is necessary for understanding the aging process, as well as for developing approaches to target dysfunction in translation as a strategy for extending lifespan.

DNA Methylation Analysis Validates Organoids as a Viable Model for Studying Human Intestinal Aging

BACKGROUND & AIMS

The epithelia of the intestine and colon turn over rapidly and are maintained by adult stem cells at the base of crypts. Although the small intestine and colon have distinct, well-characterized physiological functions, it remains unclear if there are fundamental regional differences in stem cell behavior or region-dependent degenerative changes during aging. Mesenchyme-free organoids provide useful tools for investigating intestinal stem cell biology in vitro and have started to be used for investigating age-related changes in stem cell function. However, it is unknown whether organoids maintain hallmarks of age in the absence of an aging niche. We tested whether stem cell-enriched organoids preserved the DNA methylation-based aging profiles associated with the tissues and crypts from which they were derived.

METHODS

To address this, we used standard human methylation arrays and the human epigenetic clock as a biomarker of age to analyze in vitro-derived, 3-dimensional, stem cell-enriched intestinal organoids.

RESULTS

We found that human stem cell-enriched organoids maintained segmental differences in methylation patterns and that age, as measured by the epigenetic clock, also was maintained in vitro. Surprisingly, we found that stem cell-enriched organoids derived from the small intestine showed striking epigenetic age reduction relative to organoids derived from colon.

CONCLUSIONS

Our data validate the use of organoids as a model for studying human intestinal aging and introduce methods that can be used when modeling aging or age-onset diseases in vitro.

Development of Tissue-Specific Age Predictors Using DNA Methylation Data

DNA methylation patterns have been shown to change throughout the normal aging process. Several studies have found epigenetic aging markers using age predictors, but these studies only focused on blood-specific or tissue-common methylation patterns. Here, we constructed nine tissue-specific age prediction models using methylation array data from normal samples. The constructed models predict the chronological age with good performance (mean absolute error of 5.11 years on average) and show better performance in the independent test than previous multi-tissue age predictors. We also compared tissue-common and tissue-specific aging markers and found that they had different characteristics. Firstly, the tissue-common group tended to contain more positive aging markers with methylation values that increased during the aging process, whereas the tissue-specific group tended to contain more negative aging markers. Secondly, many of the tissue-common markers were located in Cytosine-phosphate-Guanine (CpG) island regions, whereas the tissue-specific markers were located in CpG shore regions. Lastly, the tissue-common CpG markers tended to be located in more evolutionarily conserved regions. In conclusion, our prediction models identified CpG markers that capture both tissue-common and tissue-specific characteristics during the aging process.

Acceleration in the DNA methylation age in breast cancer tumours from very young women

Breast cancer in very young women (≤35 years; BCVY) presents more aggressive and complex biological features than their older counterparts (BCO). Our aim was to evaluate methylation differences between BCVY and BCO and their DNA epigenetic age. EPIC and 450k Illumina methylation arrays were used in 67 breast cancer tumours, including 32 from BCVY, for methylation study and additionally we analysed their epigenetic age. We identified 2 219 CpG sites differently-methylated in BCVY vs. BCO (FDR < 0.05; β-value difference ± 0.1). The signature showed a general hypomethylation profile with a selective small hypermethylation profile located in open-sea regions in BCVY against BCO and normal tissue. Strikingly, BCVY presented a significant increased epigenetic age-acceleration compared with older women. The affected genes were enriched for pathways in neuronal-system pathways, cell communication, and matrix organisation. Validation in an independent sample highlighted consistent higher expression of HOXD9, and PCDH10 genes in BCVY. Regions implicated in the hypermethylation profile were involved in Notch signalling pathways, the immune system or DNA repair. We further validated HDAC5 expression in BCVY. We have identified a DNA methylation signature that is specific to BCVY and have shown that epigenetic age-acceleration is increased in BCVY.

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.

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.

Breast cancer treatment and its effects on aging

Breast cancer is the most common cancer of women in the United States. It is also proving to be one of the most treatable. Early detection, surgical intervention, therapeutic radiation, cytotoxic chemotherapies and molecularly targeted agents are transforming the lives of patients with breast cancer, markedly improving their survival. Although current breast cancer treatments are largely successful in producing cancer remission and extending lifespan, there is concern that these treatments may have long lasting detrimental effects on cancer survivors, in part, through their impact on non-tumor cells. Presently, the impact of breast cancer treatment on normal cells, its impact on cellular function and its effect on the overall function of the individual are incompletely understood. In particular, it is unclear whether breast cancer and/or its treatments are associated with an accelerated aging phenotype. In this review, we consider breast cancer survivorship from the perspective of accelerated aging, and discuss the evidence suggesting that women treated for breast cancer may suffer from an increased rate of physical and cognitive decline that likely corresponds with underlying vulnerabilities of genome instability, epigenetic changes, and cellular senescence.

Decelerated DNA methylation age predicts poor prognosis of breast cancer

BACKGROUND

DNA methylation (DNAm) age was found to be an indicator for all-cause mortality, cancer incidence, and longevity, but no study has involved in the associations of DNAm age with the prognosis of breast cancer.

METHODS

We retrieved information of 1076 breast cancer patients from Genomic Data Commons (GDC) data portal on March 30, 2017, including breast cancer DNAm profiling, demographic features, clinicopathological parameters, recurrence, and all-cause fatality. Horvath's method was applied to calculate the DNAm age. Cox proportional hazards regression models were used to test the associations between DNAm age of the cancerous tissues and the prognosis (recurrence of breast cancer and all-cause fatality) with or without adjusting for chronological age and clinicopathological parameters.

RESULTS

The DNAm age was markedly decelerated in the patients who were premenopausal, ER or PR negative, HER2-enriched or basal-like than their counterparts. In the first five-year follow-up dataset for survival, every ten-year increase in DNAm age was associated with a 15% decrease in fatality; subjects with DNAm age in the second (HR: 0.52; 95%CI: 0.29-0.92), the third (HR: 0.49; 95%CI: 0.27-0.87) and the fourth quartile (HR: 0.38; 95%CI: 0.20-0.72) had significant longer survival time than those in the first quartile. In the first five-year follow-up dataset for recurrence, every ten-year increase in DNAm age was associated with a 14% decrease of the recurrence; in the categorical analysis, a clear dose-response was shown (P for trend =0.02) and the fourth quartile was associated with a longer recurrence free survival (HR: 0.32; 95%CI: 0.14-0.74). In the full follow-up dataset, similar results were obtained.

CONCLUSIONS

DNAm age of breast cancer tissue, which associated with menopausal status and pathological features, was a strong independent predictor of the prognosis. It was suggested that the prognosis of breast cancer was related to intrinsic biological changes and specific molecular targets for treatment of breast cancer may be implicit.

Increased epigenetic age in normal breast tissue from luminal breast cancer patients

BACKGROUND

Age is one of the most important risk factors for developing breast cancer. However, age-related changes in normal breast tissue that potentially lead to breast cancer are incompletely understood. Quantifying tissue-level DNA methylation can contribute to understanding these processes. We hypothesized that occurrence of breast cancer should be associated with an acceleration of epigenetic aging in normal breast tissue.

RESULTS

Ninety-six normal breast tissue samples were obtained from 88 subjects (breast cancer = 35 subjects/40 samples, unaffected = 53 subjects/53 samples). Normal tissue samples from breast cancer patients were obtained from distant non-tumor sites of primary mastectomy specimens, while samples from unaffected women were obtained from the Komen Tissue Bank (n = 25) and from non-cancer-related breast surgery specimens (n = 28). Patients were further stratified into four cohorts: age < 50 years with and without breast cancer and age ≥ 50 with and without breast cancer. The Illumina HumanMethylation450k BeadChip microarray was used to generate methylation profiles from extracted DNA samples. Data was analyzed using the "Epigenetic Clock," a published biomarker of aging based on a defined set of 353 CpGs in the human genome. The resulting age estimate, DNA methylation age, was related to chronological age and to breast cancer status. The DNAmAge of normal breast tissue was strongly correlated with chronological age (r = 0.712, p < 0.001). Compared to unaffected peers, breast cancer patients exhibited significant age acceleration in their normal breast tissue (p = 0.002). Multivariate analysis revealed that epigenetic age acceleration in the normal breast tissue of subjects with cancer remained significant after adjusting for clinical and demographic variables. Additionally, smoking was found to be positively correlated with epigenetic aging in normal breast tissue (p = 0.012).

CONCLUSIONS

Women with luminal breast cancer exhibit significant epigenetic age acceleration in normal adjacent breast tissue, which is consistent with an analogous finding in malignant breast tissue. Smoking is also associated with epigenetic age acceleration in normal breast tissue. Further studies are needed to determine whether epigenetic age acceleration in normal breast tissue is predictive of incident breast cancer and whether this mediates the risk of chronological age on breast cancer risk.

Cell-type deconvolution from DNA methylation: a review of recent applications

Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation (DNAm) can be used as a biomarker of cell types, and through deconvolution approaches, to infer underlying cell type proportions. Cell-type deconvolution algorithms have two main categories: reference-based and reference-free. Reference-based algorithms are supervised methods that determine the underlying composition of cell types within a sample by leveraging differentially methylated regions (DMRs) specific to cell type, identified from DNAm measures of purified cell populations. Reference-free algorithms are unsupervised methods for use when cell-type specific DMRs are not available, allowing scientists to estimate putative cellular proportions or control for potential confounding from cell type. Reference-based deconvolution is typically applied to blood samples and has potentiated our understanding of the relation between immune profiles and disease by allowing estimation of immune cell proportions from archival DNA. Bioinformatic analyses using DNAm to infer immune cell proportions, part of a new field known as Immunomethylomics, provides a new direction for consideration in epigenome wide association studies (EWAS).

Back to the future: Epigenetic clock plasticity towards healthy aging

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

Biological age of the endometrium using DNA methylation

Age has a detrimental effect on reproduction and as an increasing number of women postpone motherhood, it is imperative to assess biological age in terms of fertility prognosis and optimizing fertility treatment individually. Horvath's epigenetic clock is a mathematical algorithm that calculates the biological age of human cells, tissues or organs based on DNA methylation levels. The clock, however, was previously shown to be highly inaccurate for the human endometrium, most likely because of the hormonal responsive nature of this tissue. The aim of this study was to determine if epigenetically based biological age of the human endometrium correlated with chronological age, when strictly timed to the same time point in the menstrual cycle. Endometrial biopsies from nine women were obtained in two consecutive cycles, both strictly timed to the LH surge (LH + 7) and additionally, peripheral whole blood samples were analyzed. Using the Illumina HumanMethylation 450 K array and Horvath's epigenetic clock, we found a significant correlation between the biological age of the endometrium and the chronological age of the participants, although the endometrial biological age was accelerated by comparison with blood and chronological age. Moreover, similar biological ages were found in pairs of consecutive biopsies, indicating that an endometrial biopsy does not alter the biological age in the following cycle. In conclusion, as long as endometrial samples are timed to the same time point in the menstrual cycle, Horvath's epigenetic clock could be a powerful new biomarker of reproductive aging in the human endometrium.