DNA methylation age of blood predicts future onset of lung cancer in the women's health initiative

Advancing Food Allergy Through Omics Sciences

Since the publication of the first draft of the human genome, there has been an explosion of new technologies with increasing power to interrogate the totality of biological molecules (eg, DNA, RNA, proteins, metabolites) and their modifications (eg, DNA methylation, histone modifications). These technologies, collectively called omics, have been widely applied in the last 2 decades to study biological systems to gain deeper insight into mechanisms driving the physiology and pathophysiology of human health and disease. Because of its complex, multifactorial nature, food allergy is especially well suited to be investigated using omics approaches. In this rostrum, we review how omic technologies have been applied to explore diverse aspects of food allergy, including adaptive and innate immune processes in food-allergic responses, the role of the microbiome in food allergy risk, metabolic changes in the gut and blood associated with food allergy, and the identification of biomarkers and potential therapeutic targets for the condition. We discuss the strengths and limitations of the studies performed thus far and the need to adopt systems biology approaches that integrate data from multiple omics to fully leverage the potential of these technologies to advance food allergy research and care.

Accelerated epigenetic age as a biomarker of cardiovascular sensitivity to traffic-related air pollution

BACKGROUND

Accelerated epigenetic age has been proposed as a biomarker of increased aging, which may indicate disruptions in cellular and organ system homeostasis and thus contribute to sensitivity to environmental exposures.

METHODS

Using 497 participants from the CATHGEN cohort, we evaluated whether accelerated epigenetic aging increases cardiovascular sensitivity to traffic-related air pollution (TRAP) exposure. We used residential proximity to major roadways and source apportioned air pollution models as measures of TRAP exposure, and chose peripheral arterial disease (PAD) and blood pressure as outcomes based on previous associations with TRAP. We used Horvath epigenetic age acceleration (AAD) and phenotypic age acceleration (PhenoAAD) as measures of age acceleration, and adjusted all models for chronological age, race, sex, smoking, and socioeconomic status.

RESULTS

We observed significant interactions between TRAP and both AAD and PhenoAAD. Interactions indicated that increased epigenetic age acceleration elevated associations between proximity to roadways and PAD. Interactions were also observed between AAD and gasoline and diesel source apportioned PM_2.5.

CONCLUSION

Epigenetic age acceleration may be a biomarker of sensitivity to air pollution, particularly for TRAP in urban cohorts. This presents a novel means by which to understand sensitivity to air pollution and provides a molecular measure of environmental sensitivity.

DNA methylation-based biomarkers of age acceleration and all-cause death, myocardial infarction, stroke, and cancer in two cohorts: The NAS, and KORA F4

Background

DNA methylation (DNAm) may play a role in age-related outcomes. It is not yet known which DNAm-based biomarkers of age acceleration (BoAA) has the strongest association with age-related endpoints.

Methods

We collected the blood samples from two independent cohorts: the Normative Ageing Study, and the Cooperative Health Research in the Region of Augsburg cohort. We measured epigenome-wide DNAm level, and generated five DNAm BoAA at baseline. We used Cox proportional hazards model to analyze the relationships between BoAA and all-cause death. We applied the Fine and Gray competing risk model to estimate the risk of BoAA on myocardial infarction (MI), stroke, and cancer, accounting for death of other reasons as the competing risks. We used random-effects meta-analyses to pool the individual results, with adjustment for multiple testing.

Findings

The mean chronological ages in the two cohorts were 74, and 61, respectively. Baseline GrimAgeAccel, and DNAm-related mortality risk score (DNAmRS) both had strong associations with all-cause death, MI, and stroke, independent from chronological age. For example, a one standard deviation (SD) increment in GrimAgeAccel was significantly associated with increased risk of all-cause death [hazard ratio (HR): 2.01; 95% confidence interval (CI), 1.15, 3.50], higher risk of MI (HR: 1.44; 95% CI, 1.16, 1.79), and elevated risk of stroke (HR: 1.42; 95% CI, 1.06, 1.91). There were no associations between any BoAA and cancer.

Interpretation

From the public health perspective, GrimAgeAccel is the most useful tool for identifying at-risk elderly, and evaluating the efficacy of anti-aging interventions.

Funding

National Institute of Environmental Health Sciences of U.S., Harvard Chan-NIEHS Center for Environmental Health, German Federal Ministry of Education and Research, and the State of Bavaria in Germany.

Promising biomarkers of human aging: In search of a multi-omics panel to understand the aging process from a multidimensional perspective

The aging process has been linked to the occurrence of chronic diseases and functional impairments, including cancer, sarcopenia, frailty, metabolic, cardiovascular, and neurodegenerative diseases. Nonetheless, aging is highly variable and heterogeneous and represents a challenge for its characterization. In this sense, intrinsic capacity (IC) stands as a novel perspective by the World Health Organization, which integrates the individual wellbeing, environment, and risk factors to understand aging. However, there is a lack of quantitative and qualitative attributes to define it objectively. Therefore, in this review we attempt to summarize the most relevant and promising biomarkers described in clinical studies at date over different molecular levels, including epigenomics, transcriptomics, proteomics, metabolomics, and the microbiome. To aid gerontologists, geriatricians, and biomedical researchers to understand the aging process through the IC. Aging biomarkers reflect the physiological state of individuals and the underlying mechanisms related to homeostatic changes throughout an individual lifespan; they demonstrated that aging could be measured independently of time (that may explain its heterogeneity) and to be helpful to predict age-related syndromes and mortality. In summary, we highlight the areas of opportunity and gaps of knowledge that must be addressed to fully integrate biomedical findings into clinically useful tools and interventions.

Plasma proteomic biomarker signature of age predicts health and life span

Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis-epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions.

A rat epigenetic clock recapitulates phenotypic aging and co-localizes with heterochromatin

Robust biomarkers of aging have been developed from DNA methylation in humans and more recently, in mice. This study aimed to generate a novel epigenetic clock in rats-a model with unique physical, physiological, and biochemical advantages-by incorporating behavioral data, unsupervised machine learning, and network analysis to identify epigenetic signals that not only track with age, but also relates to phenotypic aging. Reduced representation bisulfite sequencing (RRBS) data was used to train an epigenetic age (DNAmAge) measure in Fischer 344 CDF (F344) rats. This measure correlated with age at (r = 0.93) in an independent sample, and related to physical functioning (p=5.9e-3), after adjusting for age and cell counts. DNAmAge was also found to correlate with age in male C57BL/6 mice (r = 0.79), and was decreased in response to caloric restriction. Our signatures driven by CpGs in intergenic regions that showed substantial overlap with H3K9me3, H3K27me3, and E2F1 transcriptional factor binding.

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.

Prediction of Lung Function in Adolescence Using Epigenetic Aging: A Machine Learning Approach

Epigenetic aging has been found to be associated with a number of phenotypes and diseases. A few studies have investigated its effect on lung function in relatively older people. However, this effect has not been explored in the younger population. This study examines whether lung function in adolescence can be predicted with epigenetic age accelerations (AAs) using machine learning techniques. DNA methylation based AAs were estimated in 326 matched samples at two time points (at 10 years and 18 years) from the Isle of Wight Birth Cohort. Five machine learning regression models (linear, lasso, ridge, elastic net, and Bayesian ridge) were used to predict FEV₁ (forced expiratory volume in one second) and FVC (forced vital capacity) at 18 years from feature selected predictor variables (based on mutual information) and AA changes between the two time points. The best models were ridge regression (R² = 75.21% ± 7.42%; RMSE = 0.3768 ± 0.0653) and elastic net regression (R² = 75.38% ± 6.98%; RMSE = 0.445 ± 0.069) for FEV₁ and FVC, respectively. This study suggests that the application of machine learning in conjunction with tracking changes in AA over the life span can be beneficial to assess the lung health in adolescence.

Association of Neighborhood Deprivation With Epigenetic Aging Using 4 Clock Metrics

IMPORTANCE

Neighborhood deprivation is associated with age-related disease, mortality, and reduced life expectancy. However, biological pathways underlying these associations are not well understood.

OBJECTIVE

To evaluate the association between neighborhood deprivation and epigenetic measures of age acceleration and genome-wide methylation.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from the Sister Study, a prospective cohort study comprising 50 884 women living in the US and Puerto Rico aged 35 to 74 years at enrollment who had a sister with breast cancer but had not had breast cancer themselves. Cohort enrollment occurred between July 2003 and March 2009. Participants completed a computer-assisted telephone interview on demographic, socioeconomic, lifestyle, and residential factors and provided anthropometric measures and peripheral blood samples at a home examination. DNA methylation data obtained for 2630 non-Hispanic White women selected for a case-cohort study in 2014 were used in this cross-sectional analysis. DNA methylation was measured using the HumanMethylation450 BeadChips in whole blood samples collected at baseline. Data analysis for this study was performed from October 17, 2019, to August 27, 2020.

EXPOSURES

Each participants' primary address was linked to an established index of neighborhood deprivation.

MAIN OUTCOMES AND MEASURES

Epigenetic age was estimated using 4 epigenetic clocks (Horvath, Hannum, PhenoAge, and GrimAge). Age acceleration was determined using residuals from regressing chronologic age on each of the 4 epigenetic age metrics. Linear regression was used to estimate associations between neighborhood deprivation and epigenetic age acceleration as well as DNA methylation at individual cytosine-guanine sites across the genome.

RESULTS

Mean (SD) age of the 2630 participants was 56.9 (8.7) years. Those with the greatest (>75th percentile) vs least (≤25th percentile) neighborhood deprivation had higher epigenetic age acceleration estimated by Hannum (β = 0.23; 95% CI, 0.01-0.45), PhenoAge (β = 0.28; 95% CI, 0.06-.50), and GrimAge (β = 0.37; 95% CI, 0.12-0.62). Increasing US quartiles of neighborhood deprivation exhibited a trend with Hannum, PhenoAge, and GrimAge. For example, GrimAge showed a significant dose-response (P test for trend <.001) as follows: level 2 vs level 1 (β = 0.30; 95% CI, 0.17-0.42), level 3 vs level 1 (β = 0.35; 95% CI, 0.19-0.50), and level 4 vs level 1 (β = 0.37; 95% CI, 0.12-0.62). Neighborhood deprivation was found to be associated with 3 cytosine-phosphate-guanine sites, with 1 of these annotated to a known gene MAOB (P = 9.71 × 10-08).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that residing in a neighborhood with a higher deprivation index appears to be reflected by methylation-based markers of aging.

Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array

BACKGROUND

Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age.

RESULTS

We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 (n = 15), GSE115278 (n = 108), GSE132203 (n = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set.

CONCLUSIONS

Our ABECs predicted adults' chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.

The influences of DNA methylation and epigenetic clocks, on metabolic disease, in middle-aged Koreans

Background

Considering that DNA methylation (DNAm) profiles are, in large part, modifiable by lifestyle and environmental influences, it has been proposed that epigenetic clocks provide a better estimate of biological age than chronological age, as associated with current health status. Even though metabolic diseases induce precocious aging, little is known about associations between metabolic syndrome (MetS) and DNA methylation clocks, and stochastic epigenetic mutations (SEMs), in a Korean population. Therefore, we assessed four different epigenetic clocks (Pan-tissue, Hannum, PhenoAge, and GrimAge), and their accelerations, on MetS and MetS-related lifestyle factors, in Koreans. We measured genome-wide DNA methylation (485,512 CpGs), using an Illumina 450 methylation BeadChip array, with data from 349 blood samples.

Results

DNAm GrimAge strongly correlated with chronological age (r = 0.77, p < 0.001) compared to the other three epigenetic clocks and SEMs. DNAm-based surrogate markers, with regard to MetS, including the gene encoding plasminogen activator inhibitor-1 (PAI1), also correlated with chronological age. Within cohorts stratified by age group, sex, regional area, smoking, and alcohol drinking, a positive correlation was observed between DNAm GrimAge and chronological age (0.43 ≤ r ≤ 0.78). In particular, we identified MetS to associate with accelerated GrimAge, and age-adjusted PAI1, in the middle-age group. Accerelated GrimAge also associated with risk of MetS in the middle-age group (odds ratio = 1.16, p = 0.046), which appears to mediate their associations with fasting glucose. Multiple linear regression showed that DNAm GrimAge, and its acceleration, associate with MetS scores, in the middle-age group (r = 0.26, p = 0.006). Age-adjusted PAI1 was also significantly different between the MetS and control groups, and further associated with MetS scores (r = 0.31, P < 0.001), in the middle age group.

Conclusion

DNAm GrimAge is a surrogate marker for MetS, and its component score, in Koreans. This association can be observed only in middle age. Therefore, appropriate DNA methylation clocks may aid in the prediction of Korean metabolic diseases.

Epigenetic age acceleration of early stage hepatocellular carcinoma tightly associated with hepatitis B virus load, immunoactivation, and improved survival

Properly stratifying high-risk individuals with early stage hepatocellular carcinoma (HCC) is essential to identify patients in which the potentially therapies can be offered. To this context, we systematically investigated the prognostic value of epigenetic clock with early stage HCC as well as the association with other molecular characteristics.

We computed DNA methylation (DNAm) age of 256 early stage HCC patients and 50 normal samples from TCGA by Horvath clock model. The characteristics of two DNAm age subgroups were differentiated regarding HBV expression, pathway activity, epigenomic, and genomic alteration. Cox regression and restricted cubic spline (RCS) analysis were utilized to evaluate the prognostic value of epigenetic acceleration.

DNAm age was significantly associated with chronological age in normal tissue but largely disrupted in tumors (P< .001), and showed significant negative correlation with HBV expression (P< .05). We identified two DNAm age groups (DNAmAge-ACC and DNAmAge-DEC), and the former presented with an immunoactive phenotype (all FDRs<0.05 in enrichment analysis), CpG island hypermethylation (P< .001), and lower mutation burden (P= .018). Every 10-year increase in DNAm age was associated with a 18% decrease in fatality after adjustment for major clinical variables; DNAmAge-ACC had 50% lower mortality risk than DNAmAge-DEC (HR: 0.50, 95% CI: 0.27-0.94, P= .03). RCS revealed the fatality risk significantly decreased as epigenetic age accelerated (P = .04). Conclusions.

In summary, we highlighted the prognostic value of epigenetic age acceleration for early stage HCC; better prognosis, relatively lower HBV load, and higher enrichment of immune signatures were tightly associated with epigenetic age accelerated tumors.

Underlying features of epigenetic aging clocks in vivo and in vitro

Epigenetic clocks, developed using DNA methylation data, have been widely used to quantify biological aging in multiple tissues/cells. However, many existing epigenetic clocks are weakly correlated with each other, suggesting they may capture different biological processes. We utilize multi-omics data from diverse human tissue/cells to identify shared features across eleven existing epigenetic clocks. Despite the striking lack of overlap in CpGs, multi-omics analysis suggested five clocks (Horvath1, Horvath2, Levine, Hannum, and Lin) share transcriptional associations conserved across purified CD14+ monocytes and dorsolateral prefrontal cortex. The pathways enriched in the shared transcriptional association suggested links between epigenetic aging and metabolism, immunity, and autophagy. Results from in vitro experiments showed that two clocks (Levine and Lin) were accelerated in accordance with two hallmarks of aging-cellular senescence and mitochondrial dysfunction. Finally, using multi-tissue data to deconstruct the epigenetic clock signals, we developed a meta-clock that demonstrated improved prediction for mortality and robustly related to hallmarks of aging in vitro than single clocks.

Epigenetic mutation load is weakly correlated with epigenetic age acceleration

DNA methylation (DNAm) age estimators are widely used to study aging-related conditions. It is not yet known whether DNAm age is associated with the accumulation of stochastic epigenetic mutations (SEMs), which reflect dysfunctions of the epigenetic maintenance system. Here, we defined epigenetic mutation load (EML) as the total number of SEMs per individual. We assessed associations between EML and DNAm age acceleration estimators using biweight midcorrelations in four population-based studies (total n = 6,388). EML was not only positively associated with chronological age (meta r = 0.171), but also with four measures of epigenetic age acceleration: the Horvath pan tissue clock, intrinsic epigenetic age acceleration, the Hannum clock, and the GrimAge clock (meta-analysis correlation ranging from r = 0.109 to 0.179). We further conducted pathway enrichment analyses for each participant's SEMs. The enrichment result demonstrated the stochasticity of epigenetic mutations, meanwhile implicated several pathways: signaling, neurogenesis, neurotransmitter, glucocorticoid, and circadian rhythm pathways may contribute to faster DNAm age acceleration. Finally, investigating genomic-region specific EML, we found that EMLs located within regions of transcriptional repression (TSS1500, TSS200, and 1stExon) were associated with faster age acceleration. Overall, our findings suggest a role for the accumulation of epigenetic mutations in the aging process.

Association of Epigenetic Metrics of Biological Age With Cortical Thickness

IMPORTANCE

Magnetic resonance imaging (MRI) studies of aging adults have shown substantial intersubject variability across various brain metrics, and some of this variability is likely attributable to chronological age being an imprecise measure of age-related change. Accurately quantifying one's biological age could allow better quantification of healthy and pathological changes in the aging brain.

OBJECTIVE

To investigate the association of DNA methylation (DNAm)-based biological age with cortical thickness and to assess whether biological age acceleration compared with chronological age captures unique variance in cortical thinning.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used high-resolution structural brain MRI data collected from a sample of healthy aging adults who were participating in a larger ongoing neuroimaging study that began in May 2014. This population-based study accrued participants from the greater Omaha, Nebraska, metropolitan area. One hundred sixty healthy adults were contacted for the MRI component, 82 of whom participated in both DNAm and MRI study components. Data analysis was performed from March to June 2019.

MAIN OUTCOMES AND MEASURES

Vertexwise cortical thickness, DNAm-based biological age, and biological age acceleration compared with chronological age were measured. A pair of multivariable regression models were computed in which cortical thickness was regressed on DNAm-based biological age, controlling for sex in the first model and also controlling for chronological age in the second model.

RESULTS

Seventy-nine adult participants (38 women; mean [SD] age, 43.82 [14.50] years; age range, 22-72 years) were included in all final analyses. Advancing biological age was correlated with cortical thinning across frontal, superior temporal, inferior parietal, and medial occipital regions. In addition, biological age acceleration relative to chronological age was associated with cortical thinning in orbitofrontal, superior and inferior temporal, somatosensory, parahippocampal, and fusiform regions. Specifically, for every 1 year of biological age acceleration, cortical thickness would be expected to decrease by 0.024 mm (95% CI, -0.04 to -0.01 mm) in the left orbitofrontal cortex (partial r, -0.34; P = .002), 0.014 mm (95% CI, -0.02 to -0.01 mm) in the left superior temporal gyrus (partial r, -0.36; P = .001), 0.015 mm (95% CI, -0.02 to -0.01 mm) in the left fusiform gyrus (partial r, -0.38; P = .001), 0.015 mm (95% CI, -0.02 to -0.01 mm) in the right fusiform gyrus (partial r, -0.43; P < .001), 0.019 mm (95% CI, -0.03 to -0.01 mm) in the right inferior temporal sulcus (partial r, -0.34; P = .002), and 0.011 mm (95% CI, -0.02 to -0.01 mm) in the right primary somatosensory cortex (partial r, -0.37; P = .001).

CONCLUSIONS AND RELEVANCE

To our knowledge, this is the first study to investigate vertexwise cortical thickness in relation to DNAm-based biological age, and the findings suggest that this metric of biological age may yield additional insight on healthy and pathological cortical aging compared with standard measures of chronological age alone.

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.

"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.

Epigenetic age and pregnancy outcomes: GrimAge acceleration is associated with shorter gestational length and lower birthweight

BACKGROUND

Advanced biological aging, as measured by epigenetic aging indices, is associated with early mortality and morbidity. Associations between maternal epigenetic aging indices in pregnancy and pregnancy outcomes, namely gestational length and birthweight, have not been assessed. The purpose of this study was to examine whether epigenetic age during pregnancy was associated with gestational length and birthweight.

RESULTS

The sample consisted of 77 women from the Los Angeles, CA, area enrolled in the Healthy Babies Before Birth study. Whole blood samples for DNA methylation assay were obtained during the second trimester (15.6 ± 2.15 weeks gestation). Epigenetic age indices GrimAge acceleration (GrimAgeAccel), DNAm PAI-1, DNAm ADM, and DNAm cystatin C were calculated. Gestational length and birthweight were obtained from medical chart review. Covariates were maternal sociodemographic variables, gestational age at blood sample collection, and pre-pregnancy body mass index. In separate covariate-adjusted linear regression models, higher early second trimester GrimAgeAccel, b(SE) = - .171 (.056), p = .004; DNAm PAI-1, b(SE) = - 1.95 × 10-4 (8.5 × 10-5), p = .004; DNAm ADM, b(SE) = - .033 (.011), p = .003; and DNAm cystatin C, b(SE) = 2.10 × 10-5 (8.0 × 10-5), p = .012, were each associated with shorter gestational length. Higher GrimAgeAccel, b(SE) = - 75.2 (19.7), p < .001; DNAm PAI-1, b(SE) = - .079(.031), p = .013; DNAm ADM, b(SE) = - 13.8 (3.87), p = .001; and DNAm cystatin C, b(SE) = - .010 (.003), p = .001, were also associated with lower birthweight, independent of gestational length.

DISCUSSION

Higher maternal prenatal GrimAgeAccel, DNAm PAI-1, DNAm ADM, and DNAm cystatin C were associated with shorter gestational length and lower birthweight. These findings suggest that biological age, as measured by these epigenetic indices, could indicate risk for adverse pregnancy outcomes.

Accelerated epigenetic aging as a risk factor for chronic obstructive pulmonary disease and decreased lung function in two prospective cohort studies

Chronic obstructive pulmonary disease (COPD) is a frequent diagnosis in older individuals and contributor to global morbidity and mortality. Given the link between lung disease and aging, we need to understand how molecular indicators of aging relate to lung function and disease. Using data from the population-based KORA (Cooperative Health Research in the Region of Augsburg) surveys, we associated baseline epigenetic (DNA methylation) age acceleration with incident COPD and lung function. Models were adjusted for age, sex, smoking, height, weight, and baseline lung disease as appropriate. Associations were replicated in the Normative Aging Study. Of 770 KORA participants, 131 developed incident COPD over 7 years. Baseline accelerated epigenetic aging was significantly associated with incident COPD. The change in age acceleration (follow-up - baseline) was more strongly associated with COPD than baseline aging alone. The association between the change in age acceleration between baseline and follow-up and incident COPD replicated in the Normative Aging Study. Associations with spirometric lung function parameters were weaker than those with COPD, but a meta-analysis of both cohorts provide suggestive evidence of associations. Accelerated epigenetic aging, both baseline measures and changes over time, may be a risk factor for COPD and reduced lung function.

Epigenetic clocks may come out of rhythm-implications for the estimation of chronological age in forensic casework

There is a growing perception that DNA methylation may be influenced by exogenous and endogenous parameters. Knowledge of these factors is of great relevance for the interpretation of DNA-methylation data for the estimation of chronological age in forensic casework. We performed a literature review to identify parameters, which might be of relevance for the prediction of chronological age based on DNA methylation. The quality of age predictions might particularly be influenced by lifetime adversities (chronic stress, trauma/post-traumatic stress disorder (PTSD), violence, low socioeconomic status/education), cancer, obesity and related diseases, infectious diseases (especially HIV and Cytomegalovirus (CMV) infections), sex, ethnicity and exposure to toxins (alcohol, smoking, air pollution, pesticides). Such factors may alter the DNA methylation pattern and may explain the partly high deviations between epigenetic age and chronological age in single cases (despite of low mean absolute deviations) that can also be observed with “epigenetic clocks” comprising a high number of CpG sites. So far, only few publications dealing with forensic age estimation address these confounding factors. Future research should focus on the identification of further relevant confounding factors and the development of models that are “robust” against the influence of such biological factors by systematic investigations under targeted inclusion of diverse and defined cohorts.

Blood-derived DNA methylation predictors of mortality discriminate tumor and healthy tissue in multiple organs

Evidence has shown that certain methylation markers derived from blood can mirror corresponding methylation signatures in internal tissues. In the current study, we aimed to investigate two strong epigenetic predictors for life span, derived from blood DNA methylation data, in tissue samples of solid cancer patients. Using data from the Cancer Genome Atlas (TCGA) and the German DACHS study, we compared a mortality risk score (MRscore) and DNAmPhenoAge in paired tumor and adjacent normal tissue samples of patients with lung (N = 69), colorectal (n = 299), breast (n = 90), head/neck (n = 50), prostate (n = 50), and liver (n = 50) cancer. To explore the concordance across tissue and blood, we additionally assessed the two markers in blood samples of colorectal cancer (CRC) cases and matched controls (n = 93) in the DACHS+ study. The MRscore was significantly elevated in tumor tissues compared to normal tissues of all cancers except prostate cancer, for which an opposite pattern was observed. DNAmPhenoAge was consistently higher in all tumor tissues. The MRscore discriminated lung, colorectal, and prostate tumor tissues from normal tissues with very high accuracy [AUCs of 0.87, 0.99 (TCGA) /0.94 (DACHS), and 0.92, respectively]. DNAmPhenoAge accurately discriminated five types of tumor tissues from normal tissues (except prostate cancer), with AUCs of 0.82–0.93. The MRscore was also significantly higher in blood samples of CRC cases than in controls, with areas under the curve (AUC) of 0.74, whereas DNAmPhenoAge did not distinguish cases from controls, with AUC of 0.54. This study provides compelling evidence that blood‐derived DNAm markers could reflect methylation changes in less accessible tissues. Further research should explore the potential use of these findings for cancer diagnosis and early detection.

Biomarkers of aging and lung function in the normative aging study

Elderly individuals who are never smokers but have the same height and chronological age can have substantial differences in lung function. The underlying biological mechanisms are unclear. To evaluate the associations of different biomarkers of aging (BoA) and lung function, we performed a repeated-measures analysis in the Normative Aging Study using linear mixed-effect models. We generated GrimAgeAccel, PhenoAgeAccel, extrinsic and intrinsic epigenetic age acceleration using a publically available online calculator. We calculated Zhang's DNAmRiskScore based on 10 CpGs. We measured telomere length (TL) and mitochondrial DNA copy number (mtDNA-CN) using quantitative real-time polymerase chain reaction. A pulmonary function test was performed measuring forced expiratory volume in 1 second / forced vital capacity (FEV₁/FVC), FEV₁, and maximum mid-expiratory flow (MMEF). Epigenetic-based BoA were associated with lower lung function. For example, a one-year increase in GrimAgeAccel was associated with a 13.64 mL [95% confidence interval (CI), 5.11 to 22.16] decline in FEV₁; a 0.2 increase in Zhang's DNAmRiskScore was associated with a 0.009 L/s (0.005 to 0.013) reduction in MMEF. No association was found between TL/mtDNA-CN and lung function. Overall, this paper shows that epigenetics might be a potential mechanism underlying pulmonary dysfunction in the elderly.

Methylation-Based Biological Age and Breast Cancer Risk

BACKGROUND

Age is one of the strongest predictors of cancer, chronic disease, and mortality, but biological responses to aging differ among people. Epigenetic DNA modifications have been used to estimate "biological age," which may be a useful predictor of disease risk. We tested this hypothesis for breast cancer.

METHODS

Using a case-cohort approach, we measured baseline blood DNA methylation of 2764 women enrolled in the Sister Study, 1566 of whom subsequently developed breast cancer after an average of 6 years. Using three previously established methylation-based "clocks" (Hannum, Horvath, and Levine), we defined biological age acceleration for each woman by comparing her estimated biological age with her chronological age. Hazard ratios and 95% confidence intervals for breast cancer risk were estimated using Cox regression models. All statistical tests were two-sided.

RESULTS

Each of the three clocks showed that biological age acceleration was statistically significantly associated with increased risk of developing breast cancer (5-year age acceleration, Hannum's clock: hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.00 to 1.21, P = .04; Horvath's clock: HR = 1.08, 95% CI = 1.00 to 1.17, P = .04; Levine's clock: HR = 1.15, 95% CI = 1.07 to 1.23, P < .001). For Levine's clock, each 5-year acceleration in biological age corresponded with a 15% increase in breast cancer risk. Although biological age may accelerate with menopausal transition, age acceleration in premenopausal women independently predicted breast cancer. Case-only analysis suggested that, among women who develop breast cancer, increased age acceleration is associated with invasive cancer (odds ratio for invasive = 1.09, 95% CI = 0.98 to 1.22, P = .10).

CONCLUSIONS

DNA methylation-based measures of biological age may be important predictors of breast cancer risk.

Epigenetics as a key link between psychosocial stress and aging: concepts, evidence, mechanisms

Psychosocial stress—especially when chronic, excessive, or occurring early in life—has been associated with accelerated aging and increased disease risk. With rapid aging of the world population, the need to elucidate the underlying mechanisms is pressing, now more so than ever. Among molecular mechanisms linking stress and aging, the present article reviews evidence on the role of epigenetics, biochemical processes that can be set into motion by stressors and in turn influence genomic function and complex phenotypes, including aging-related outcomes. The article further provides a conceptual mechanistic framework on how stress may drive epigenetic changes at susceptible genomic sites, thereby exerting systems-level effects on the aging epigenome while also regulating the expression of molecules implicated in aging-related processes. This emerging evidence, together with work examining related biological processes, begins to shed light on the epigenetic and, more broadly, molecular underpinnings of the long-hypothesized connection between stress and aging.


Measuring Aging and Identifying Aging Phenotypes in Cancer Survivors

Observational data have shown that some cancer survivors develop chronic conditions like frailty, sarcopenia, cardiac dysfunction, and mild cognitive impairment earlier and/or at a greater burden than similarly aged individuals never diagnosed with cancer or exposed to systemic or targeted cancer therapies. In aggregate, cancer- and treatment-related physical, cognitive, and psychosocial late- and long-term morbidities experienced by cancer survivors are hypothesized to represent accelerated or accentuated aging trajectories. However, conceptual, measurement, and methodological challenges have constrained efforts to identify, predict, and mitigate aging-related consequences of cancer and cancer treatment. In July 2018, the National Cancer Institute convened basic, clinical, and translational science experts for a think tank titled "Measuring Aging and Identifying Aging Phenotypes in Cancer Survivors." Through the resulting deliberations, several research and resource needs were identified, including longitudinal studies to examine aging trajectories that include detailed data from before, during, and after cancer treatment; mechanistic studies to elucidate the pathways that lead to the emergence of aging phenotypes in cancer survivors; long-term clinical surveillance to monitor survivors for late-emerging effects; and tools to integrate multiple data sources to inform understanding of how cancer and its therapies contribute to the aging process. Addressing these needs will help expand the evidence base and inform strategies to optimize healthy aging of cancer survivors.

Epigenome-wide gene-age interaction analysis reveals reversed effects of PRODH DNA methylation on survival between young and elderly early-stage NSCLC patients

DNA methylation changes during aging, but it remains unclear whether the effect of DNA methylation on lung cancer survival varies with age. Such an effect could decrease prediction accuracy and treatment efficacy. We performed a methylation–age interaction analysis using 1,230 early-stage lung adenocarcinoma patients from five cohorts. A Cox proportional hazards model was used to investigate lung adenocarcinoma and squamous cell carcinoma patients for methylation–age interactions, which were further confirmed in a validation phase. We identified one adenocarcinoma-specific CpG probe, cg14326354_PRODH, with effects significantly modified by age (HR_interaction = 0.989; 95% CI: 0.986–0.994; P = 9.18×10–7). The effect of low methylation was reversed for young and elderly patients categorized by the boundary of 95% CI standard (HR_young = 2.44; 95% CI: 1.26–4.72; P = 8.34×10-3; HR_elderly = 0.58; 95% CI: 0.42–0.82; P = 1.67×10-3). Moreover, there was an antagonistic interaction between low cg14326354_PRODH methylation and elderly age (HR_interaction = 0.21; 95% CI: 0.11–0.40; P = 2.20×10−6). In summary, low methylation of cg14326354PRODH might benefit survival of elderly lung adenocarcinoma patients, providing new insight to age-specific prediction and potential drug targeting.

Shift work, DNA methylation and epigenetic age

BACKGROUND

Shift work has been associated with increased risk of age-related morbidity and mortality. Biological age, estimated using DNA methylation (DNAm), may quantify the biological consequences of shift work on the risk of age-related disease. We examined whether prior employment in shift-working occupations was associated with epigenetic age acceleration.

METHODS

In a sample of non-Hispanic White women aged 35-74 (n = 2574), we measured DNAm using the Illumina Infinium Human450 BeadChip and calculated DNAm age using three established epigenetic clocks. Age-acceleration metrics were derived by regressing DNAm age on chronological age and predicting the residuals. Using linear regression, we estimated associations between shift work history and age acceleration. We also conducted an epigenome-wide association study using robust linear-regression models corrected with false discovery rate (FDR) q-values.

RESULTS

Approximately 7% of women reported any shift work. Higher age acceleration was observed for a 1-year increase in overall [β = 0.11, 95% confidence interval (CI): 0.02-0.21] and night-specific shift work (β = 0.12, 95% CI: 0.03-0.21). The association was strongest for ≥10 years of night shift work (β = 3.16, 95% CI: 1.17-5.15). From the epigenome-wide association study, years of overall and night shift work were associated with DNAm at 66 and 85 CpG sites (FDR < 0.05), respectively. Years of night shift work was associated with lower methylation of a CpG in the gene body of ZFHX3 (cg04994202, q = 0.04), a gene related to circadian rhythm.

CONCLUSIONS

Shift work was associated with differential CpG site methylation and with differential DNAm patterns, measured by epigenetic age acceleration, consistent with long-term negative health effects.

Promoter hypermethylation of cysteine dioxygenase type 1 in patients with non-small cell lung cancer

In the present study, promoter hypermethylation of cysteine dioxygenase type 1 (CDO1) was evaluated in non-small cell lung cancer (NSCLC) tissues to assess the value of CDO1 as a novel biomarker to improve the diagnosis of NSCLC. Tumor tissue samples and corresponding normal lung tissue samples from 42 patients with NSCLC were obtained at the Department of Thoracic Surgery, The Second Xiangya Hospital (Changsha, China). Conventional methylation-specific PCR (cMSP) and methylation-on-beads followed by quantitative methylation-specific PCR (MOB-qMSP) were used to analyze the tumor and normal lung tissue samples. Using these two methods, promoter DNA hypermethylation of the CDO1 gene was detected in 59.4 and 71.0% of tumor tissues of patients with NSCLC and in 9.4 and 0% of normal lung tissue, respectively. Compared with the rate of methylation in the well-differentiated NSCLC tissues (15.4 and 55.6%, respectively), the rate of CDO1 gene promoter methylation was higher in the poorly differentiated tissues (89.5 and 92.3%, respectively). Overall, it was demonstrated that the MOB-qMSP method had a higher positive detection rate for CDO1 hypermethylation compared with the cMSP method. In conclusion, CDO1 gene promoter hypermethylation was more frequently observed in NSCLC tissues compared with in normal lung tissues, and a high methylation frequency of the CDO1 gene in biopsy specimens of NSCLC was associated with the degree of differentiation.

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.

DNA methylation GrimAge strongly predicts lifespan and healthspan

It was unknown whether plasma protein levels can be estimated based on DNA methylation (DNAm) levels, and if so, how the resulting surrogates can be consolidated into a powerful predictor of lifespan. We present here, seven DNAm-based estimators of plasma proteins including those of plasminogen activator inhibitor 1 (PAI-1) and growth differentiation factor 15. The resulting predictor of lifespan, DNAm GrimAge (in units of years), is a composite biomarker based on the seven DNAm surrogates and a DNAm-based estimator of smoking pack-years. Adjusting DNAm GrimAge for chronological age generated novel measure of epigenetic age acceleration, AgeAccelGrim.Using large scale validation data from thousands of individuals, we demonstrate that DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death (Cox regression P=2.0E-75), time-to-coronary heart disease (Cox P=6.2E-24), time-to-cancer (P= 1.3E-12), its strong relationship with computed tomography data for fatty liver/excess visceral fat, and age-at-menopause (P=1.6E-12). AgeAccelGrim is strongly associated with a host of age-related conditions including comorbidity count (P=3.45E-17). Similarly, age-adjusted DNAm PAI-1 levels are associated with lifespan (P=5.4E-28), comorbidity count (P= 7.3E-56) and type 2 diabetes (P=2.0E-26). These DNAm-based biomarkers show the expected relationship with lifestyle factors including healthy diet and educational attainment.Overall, these epigenetic biomarkers are expected to find many applications including human anti-aging studies.

One-year Mediterranean diet promotes epigenetic rejuvenation with country- and sex-specific effects: a pilot study from the NU-AGE project

Mediterranean diet has been proposed to promote healthy aging, but its effects on aging biomarkers have been poorly investigated. We evaluated the impact of a 1-year Mediterranean-like diet in a pilot study including 120 elderly healthy subjects from the NU-AGE study (60 Italians, 60 Poles) by measuring the changes in their epigenetic age, assessed by Horvath's clock. We observed a trend towards epigenetic rejuvenation of participants after nutritional intervention. The effect was statistically significant in the group of Polish females and in subjects who were epigenetically older at baseline. A genome-wide association study of epigenetic age changes after the intervention did not return significant (adjusted p value < 0.05) loci. However, we identified small-effect alleles (nominal p value < 10-4), mapping in genes enriched in pathways related to energy metabolism, regulation of cell cycle, and of immune functions. Together, these findings suggest that Mediterranean diet can promote epigenetic rejuvenation but with country-, sex-, and individual-specific effects, thus highlighting the need for a personalized approach to nutritional interventions.

Vasomotor Symptoms and Accelerated Epigenetic Aging in the Women's Health Initiative (WHI)

PURPOSE

The hallmark menopausal symptom, vasomotor symptoms (VMS), has been linked to adverse health indicators. However, the relationship between VMS and biological aging has not been tested. We examined associations between menopausal VMS and biological aging as assessed by 2 DNA methylation-based epigenetic aging indicators previously linked to poor health outcomes.

METHODS

Participants were members of the Women's Health Initiative Observational Study integrative genomics substudy (N = 1206) who had both ovaries and were not taking hormone therapy. Relationships between VMS at enrollment (presence, severity) or VMS timing groups (no VMS: not at menopause onset nor at study enrollment; early VMS: at menopause onset but not at enrollment; persistent VMS: at menopause onset and study enrollment; and late VMS: at enrollment but not at menopause onset) and epigenetic clock indicators predictive of physical aging and early death (DNAm PhenoAge, DNAm GrimAge) were tested in linear regression models adjusting for age, race/ethnicity, hysterectomy, education, body mass index, smoking, and, in additional models, sleep disturbance.

RESULTS

Women were on average 65 years of age at enrollment. Severe hot flashes at enrollment were associated with higher DNAm PhenoAge [relative to no hot flashes: B (SE) = 2.79 (1.27), P = 0.028, multivariable]. Further, late-occurring VMS were associated with both higher DNAm PhenoAge [B (SE) = 2.15 (0.84), P = 0.011] and DNAm GrimAge [B (SE) = 1.09 (0.42), P = 0.010, multivariable] relative to no VMS.

MAIN CONCLUSIONS

Among postmenopausal women, severe or late-occurring VMS were associated with accelerated epigenetic age, controlling for chronological age. Postmenopausal women with severe or late-occurring VMS may have greater underlying epigenetic aging.

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.

DNA Methylation Biomarkers in Aging and Age-Related Diseases

Recent research efforts provided compelling evidence of genome-wide DNA methylation alterations in aging and age-related disease. It is currently well established that DNA methylation biomarkers can determine biological age of any tissue across the entire human lifespan, even during development. There is growing evidence suggesting epigenetic age acceleration to be strongly linked to common diseases or occurring in response to various environmental factors. DNA methylation based clocks are proposed as biomarkers of early disease risk as well as predictors of life expectancy and mortality. In this review, we will summarize key advances in epigenetic clocks and their potential application in precision health. We will also provide an overview of progresses in epigenetic biomarker discovery in Alzheimer's, type 2 diabetes, and cardiovascular disease. Furthermore, we will highlight the importance of prospective study designs to identify and confirm epigenetic biomarkers of disease.

Epigenetics in age-related macular degeneration: new discoveries and future perspectives

The study of epigenetics has explained some of the 'missing heritability' of age-related macular degeneration (AMD). The epigenome also provides a substantial contribution to the organisation of the functional retina. There is emerging evidence of specific epigenetic mechanisms associated with AMD. This 'AMD epigenome' may offer the chance to develop novel AMD treatments.

Epigenetic age acceleration of cervical squamous cell carcinoma converged to human papillomavirus 16/18 expression, immunoactivation, and favourable prognosis

BACKGROUND

Ageing-associated molecular changes have been assumed to trigger malignant transformations and the epigenetic clock, and the DNA methylation age has been shown to be highly correlated with chronological age. However, the associations between the epigenetic clock and cervical squamous cell carcinoma (CSCC) prognosis, other molecular characteristics, and clinicopathological features have not been systematically investigated. To this end, we computed the DNA methylation (DNAm) age of 252 CSCC patients and 200 normal samples from TCGA and three external cohorts by using the Horvath clock model. We characterized the differences in human papillomavirus (HPV) 16/18 expression, pathway activity, genomic alteration, and chemosensitivity between two DNAm age subgroups. We then used Cox proportional hazards regression and restricted cubic spline (RCS) analysis to assess the prognostic value of epigenetic acceleration.

RESULTS

DNAm age was significantly associated with chronological age, but it was differentiated between tumour and normal tissue (P < 0.001). Two DNAm age groups, i.e. DNAmAge-ACC and DNAmAge-DEC, were identified; the former had high expression of the E6/E7 oncoproteins of HPV16/18 (P < 0.05), an immunoactive phenotype (all FDRs < 0.05 in enrichment analysis), CpG island hypermethylation (P < 0.001), and lower mutation load (P = 0.011), including for TP53 (P = 0.002). When adjusted for chronological age and tumour stage, every 10-year increase in DNAm age was associated with a 12% decrease in fatality (HR 0.88, 95% CI 0.78-0.99, P = 0.03); DNAmAge-ACC had a 41% lower mortality risk and 47% lower progression rate than DNAmAge-DEC and was more likely to benefit from chemotherapy. RCS revealed a positive non-linear association between DNAm age and both mortality and progression risk (both, P < 0.05).

CONCLUSIONS

DNAm age is an independent predictor of CSCC prognosis. Better prognosis, overexpression of HPV E6/E7 oncoproteins, and higher enrichment of immune signatures were observed in DNAmAge-ACC tumours.

The effects of bariatric surgery on clinical profile, DNA methylation, and ageing in severely obese patients

BACKGROUND

Severe obesity is a growing, worldwide burden and conventional therapies including radical change of diet and/or increased physical activity have limited results. Bariatric surgery has been proposed as an alternative therapy showing promising results. It leads to substantial weight loss and improvement of comorbidities such as type 2 diabetes. Increased adiposity is associated with changes in epigenetic profile, including DNA methylation. We investigated the effect of bariatric surgery on clinical profile, DNA methylation, and biological age estimated using Horvath's epigenetic clock.

RESULTS

To determine the impact of bariatric surgery and subsequent weight loss on clinical traits, a cohort of 40 severely obese individuals (BMI = 30-73 kg/m²) was examined at the time of surgery and at three follow-up visits, i.e., 3, 6, and 12 months after surgery. The majority of the individuals were women (65%) and the mean age at surgery was 45.1 ± 8.1 years. We observed a significant decrease over time in BMI, fasting glucose, HbA1c, HOMA-IR, insulin, total cholesterol, triglycerides, LDL and free fatty acids levels, and a significant small increase in HDL levels (all p values < 0.05). Epigenome-wide association analysis revealed 4857 differentially methylated CpG sites 12 months after surgery (at Bonferroni-corrected p value < 1.09 × 10^-7). Including BMI change in the model decreased the number of significantly differentially methylated CpG sites by 51%. Gene set enrichment analysis identified overrepresentation of multiple processes including regulation of transcription, RNA metabolic, and biosynthetic processes in the cell. Bariatric surgery in severely obese patients resulted in a decrease in both biological age and epigenetic age acceleration (EAA) (mean = - 0.92, p value = 0.039).

CONCLUSIONS

Our study shows that bariatric surgery leads to substantial BMI decrease and improvement of clinical outcomes observed 12 months after surgery. These changes explained part of the association between bariatric surgery and DNA methylation. We also observed a small, but significant improvement of biological age. These epigenetic changes may be modifiable by environmental lifestyle factors and could be used as potential biomarkers for obesity and in the future for obesity related comorbidities.

Association of adult lung function with accelerated biological aging

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

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

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

Epigenetic aging is accelerated in alcohol use disorder and regulated by genetic variation in APOL2

To investigate the potential role of alcohol use disorder (AUD) in aging processes, we employed Levine's epigenetic clock (DNAm PhenoAge) to estimate DNA methylation age in 331 individuals with AUD and 201 healthy controls (HC). We evaluated the effects of heavy, chronic alcohol consumption on epigenetic age acceleration (EAA) using clinical biomarkers, including liver function test enzymes (LFTs) and clinical measures. To characterize potential underlying genetic variation contributing to EAA in AUD, we performed genome-wide association studies (GWAS) on EAA, including pathway analyses. We followed up on relevant top findings with in silico expression quantitative trait loci (eQTL) analyses for biological function using the BRAINEAC database. There was a 2.22-year age acceleration in AUD compared to controls after adjusting for gender and blood cell composition (p = 1.85 × 10^-5). This association remained significant after adjusting for race, body mass index, and smoking status (1.38 years, p = 0.02). Secondary analyses showed more pronounced EAA in individuals with more severe AUD-associated phenotypes, including elevated gamma-glutamyl transferase (GGT) and alanine aminotransferase (ALT), and higher number of heavy drinking days (all ps < 0.05). The genome-wide meta-analysis of EAA in AUD revealed a significant single nucleotide polymorphism (SNP), rs916264 (p = 5.43 × 10^-8), in apolipoprotein L2 (APOL2) at the genome-wide level. The minor allele A of rs916264 was associated with EAA and with increased mRNA expression in hippocampus (p = 0.0015). Our data demonstrate EAA in AUD and suggest that disease severity further accelerates epigenetic aging. EAA was associated with genetic variation in APOL2, suggesting potential novel biological mechanisms for age acceleration in AUD.

The Development of Epigenetics in the Study of Disease Pathogenesis

The study of epigenetics has its roots in the study of organism change over time and response to environmental change, although over the past several decades the definition has been formalized to include heritable alterations in gene expression that are not a result of alterations in underlying DNA sequence. In this chapter, we discuss first the history and milestones in the 100+ years of epigenetic study, including early discoveries of DNA methylation, histone posttranslational modification, and noncoding RNA. We then discuss how epigenetics has changed the way that we think of both health and disease, offering as examples studies examining the epigenetic contributions to aging, including the recent development of an epigenetic "clock", and explore how antiaging therapies may work through epigenetic modifications. We then discuss a nonpathogenic role for epigenetics in the clinic: epigenetic biomarkers. We conclude by offering two examples of modern state-of-the-art integrated multi-omics studies of epigenetics in disease pathogenesis, one which sought to capture shared mechanisms among multiple diseases, and another which used epigenetic big data to better understand the pathogenesis of a single tissue from one disease.

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

Background

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

Results

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

Conclusions

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

Epigenetic mortality predictors and incidence of breast cancer

Measures derived using blood DNA methylation are increasingly under investigation as indicators of disease and mortality risk. Three existing epigenetic age measures or “epigenetic clocks” appear associated with breast cancer. Two newly-developed epigenetic mortality predictors may be related to all-cancer incidence, but associations with specific cancers have not been examined in large studies. Using HumanMethylation450 BeadChips to measure blood DNA methylation in 2,773 cancer-free women enrolled in the Sister Study, we calculated two epigenetic mortality predictors: ‘GrimAgeAccel’ and the ‘mortality score’ (MS). Using Cox proportional hazard models, neither GrimAgeAccel nor the MS were associated with overall breast cancer incidence (GrimAgeAccel hazard ratio [HR]: 1.06, 95% confidence interval [CI]: 0.98-1.14, P=0.17; MS HR: 0.99, 95% CI: 0.92-1.07, P=0.85); however, a weak, positive association was observed for GrimAgeAccel and invasive breast cancer (HR: 1.08, 95% CI: 0.99-1.17, P=0.08). Stratification of invasive cancers by menopause status at diagnoses revealed the association was predominantly observed for postmenopausal breast cancer (HR: 1.10, 95% CI: 1.01, 1.20, P=0.04). Although the MS was unrelated to breast cancer risk, we find evidence that GrimAgeAccel may be weakly associated with invasive breast cancer, particularly for women diagnosed after menopause.

Health Assessments of Common Bottlenose Dolphins (Tursiops truncatus): Past, Present, and Potential Conservation Applications

The common bottlenose dolphin (Tursiops truncatus) is a global marine mammal species for which some populations, due to their coastal accessibility, have been monitored diligently by scientists for decades. Health assessment examinations have developed a comprehensive knowledge base of dolphin biology, population structure, and environmental or anthropogenic stressors affecting their dynamics. Bottlenose dolphin health assessments initially started as stock assessments prior to acquisition. Over the last four decades, health assessments have evolved into essential conservation management tools of free-ranging dolphin populations. Baseline data enable comparison of stressors between geographic locations and associated changes in individual and population health status. In addition, long-term monitoring provides opportunities for insights into population shifts over time, with retrospective application of novel diagnostic tests on archived samples. Expanding scientific knowledge enables effective long-term conservation management strategies by facilitating informed decision making and improving social understanding of the anthropogenic effects. The ability to use bottlenose dolphins as a model for studying marine mammal health has been pivotal in our understanding of anthropogenic effects on multiple marine mammal species. Future studies aim to build on current knowledge to influence management decisions and species conservation. This paper reviews the historical approaches to dolphin health assessments, present day achievements, and development of future conservation goals.

Epigenetic ageing is distinct from senescence-mediated ageing and is not prevented by telomerase expression

The paramount role of senescent cells in ageing has prompted suggestions that re-expression of telomerase may prevent ageing; a proposition that is predicated on the assumption that senescent cells are the sole cause of ageing. Recently, several DNA methylation-based age estimators (epigenetic clocks) have been developed and they revealed that increased epigenetic age is associated with a host of age-related conditions, and is predictive of lifespan. Employing these clocks to measure epigenetic age in vitro, we interrogated the relationship between epigenetic ageing and telomerase activity. Although hTERT did not induce any perceptible change to the rate of epigenetic ageing, hTERT-expressing cells, which bypassed senescence, continued to age epigenetically. Employment of hTERT mutants revealed that neither telomere synthesis nor immortalisation is necessary for the continued increase in epigenetic age by these cells. Instead, the extension of their lifespan is sufficient to support continued epigenetic ageing of the cell. These characteristics, observed in cells from numerous donors and cell types, reveal epigenetic ageing to be distinct from replicative senescence. Hence, while re-activation of hTERT may stave off physical manifestation of ageing through avoidance of replicative senescence, it would have little impact on epigenetic ageing which continues in spite of telomerase activity.

A multi-tissue full lifespan epigenetic clock for mice

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

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

Background

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

Results

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

Conclusions

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

Computational tools for geroscience

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

Epigenetic Aging: More Than Just a Clock When It Comes to Cancer

The incidence of cancer, adjusted for secular trends, is directly related to age, and advanced chronologic age is one of the most significant risk factors for cancer. Organismal aging is associated with changes at the molecular, cellular, and tissue levels and is affected by both genetic and environmental factors. The specific mechanisms through which these age-associated molecular changes contribute to the increased risk of aging-related disease, such as cancer, are incompletely understood. DNA methylation, a prominent epigenetic mark, also changes over a lifetime as part of an "epigenetic aging" process. Here, we give an update and review of epigenetic aging, in particular, the phenomena of epigenetic drift and epigenetic clock, with regard to its implication in cancer etiology. We discuss the discovery of the DNA methylation-based biomarkers for biological tissue age and the construction of various epigenetic age estimators for human clinical outcomes and health/life span. Recent studies in various types of cancer point to the significance of epigenetic aging in tumorigenesis and its potential use for cancer risk prediction. Future studies are needed to assess the potential clinical impact of strategies focused on lowering cancer risk by preventing premature aging or promoting healthy aging.

Epigenetic clock for skin and blood cells applied to Hutchinson Gilford Progeria Syndrome and ex vivo studies

DNA methylation (DNAm)-based biomarkers of aging have been developed for many tissues and organs. However, these biomarkers have sub-optimal accuracy in fibroblasts and other cell types used in ex vivo studies. To address this challenge, we developed a novel and highly robust DNAm age estimator (based on 391 CpGs) for human fibroblasts, keratinocytes, buccal cells, endothelial cells, lymphoblastoid cells, skin, blood, and saliva samples. High age correlations can also be observed in sorted neurons, glia, brain, liver, and even bone samples. Gestational age correlates with DNAm age in cord blood. When used on fibroblasts from Hutchinson Gilford Progeria Syndrome patients, this age estimator (referred to as the skin & blood clock) uncovered an epigenetic age acceleration with a magnitude that is below the sensitivity levels of other DNAm-based biomarkers. Furthermore, this highly sensitive age estimator accurately tracked the dynamic aging of cells cultured ex vivo and revealed that their proliferation is accompanied by a steady increase in epigenetic age. The skin & blood clock predicts lifespan and it relates to many age-related conditions. Overall, this biomarker is expected to become useful for forensic applications (e.g. blood or buccal swabs) and for a quantitative ex vivo human cell aging assay.

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.