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

DNA methylation near MAD1L1, KDM2B, and SOCS3 mediates the effect of socioeconomic status on elevated body mass index in African American adults

Obesity and poverty disproportionally affect African American persons. Epigenetic mechanisms could partially explain the association between socioeconomic disadvantage and body mass index (BMI). We examined the extent to which epigenetic mechanisms mediate the effect of socioeconomic status (SES) on BMI. Using data from African American adults from the Atherosclerosis Risk in Communities (ARIC) Study (n = 2664, mean age = 57 years), education, income, and occupation were used to create a composite SES score at visit 1 (1987-1989). We conducted two methylation-wide association analyses to identify associations between SES (visit 1), BMI and cytosine-phosphate-guanine (CpG) sites measured at a subsequent visit (1990-1995). We then utilized structural equation modeling (SEM) to test whether identified sites mediated the association between earlier SES and BMI in sex-stratified models adjusted for demographic and risk factor covariates. Independent replication and meta-analyses were conducted using the Jackson Heart Study (JHS, n = 874, mean age 51 years, 2000-2004). Three CpG sites near MAD1L1, KDM2B, and SOCS3 (cg05095590, cg1370865, and cg18181703) were suggestively associated (P-value < 1.3×10-5) in ARIC and at array-wide significance (P-value < 1.3×10-7) in a combined meta-analysis of ARIC with JHS. SEM of these three sites revealed significant indirect effects in females (P-value < 5.8×10-3), each mediating 7%-20% of the total effect of SES on BMI. Nominally significant indirect effects were observed for two sites near MAD1L1 and KDM2B in males (P-value < 3.4×10-2), mediating -17 and -22% of the SES-BMI effect. These results provide further evidence that epigenetic modifications may be a potential pathway through which SES may "get under the skin" and contribute to downstream health disparities.

Map of epigenetic age acceleration: A worldwide analysis

We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.

Natural Compounds for Preventing Age-Related Diseases and Cancers

Aging is a multifaceted process influenced by hereditary factors, lifestyle, and environmental elements. As time progresses, the human body experiences degenerative changes in major functions. The external and internal signs of aging manifest in various ways, including skin dryness, wrinkles, musculoskeletal disorders, cardiovascular diseases, diabetes, neurodegenerative disorders, and cancer. Additionally, cancer, like aging, is a complex disease that arises from the accumulation of various genetic and epigenetic alterations. Circadian clock dysregulation has recently been identified as an important risk factor for aging and cancer development. Natural compounds and herbal medicines have gained significant attention for their potential in preventing age-related diseases and inhibiting cancer progression. These compounds demonstrate antioxidant, anti-inflammatory, anti-proliferative, pro-apoptotic, anti-metastatic, and anti-angiogenic effects as well as circadian clock regulation. This review explores age-related diseases, cancers, and the potential of specific natural compounds in targeting the key features of these conditions.

The Impact of Early Life Adversity on Peripubertal Accelerated Epigenetic Aging and Psychopathology

OBJECTIVE

To examine longitudinal associations between early life threat and deprivation on epigenetic age acceleration at ages 9 and 15 years, and to examine associations of age acceleration on later internalizing and externalizing symptoms.

METHOD

The study examines a large (n = 2,039) and racially diverse (Black/African American = 44%, Latino = 18%, White = 5%) sample from a national dataset. Epigenetic age acceleration was estimated using the pediatric buccal epigenetic clock. Early life threat and deprivation were measured using composites from the Parent-Child Conflict Tactics Scale and county-level violent and property crime rate data. Internalizing and externalizing symptoms came from parent-reported Child Behavior Checklist. Path analysis models examined associations of threat and deprivation at age 3 years on epigenetic age acceleration at ages 9 and 15. Experiences of threat were further broken down into threat experienced in the home and in the community.

RESULTS

Home threat experienced at age 3 years predicted age acceleration at 9 and 15, and community threat experienced at 3 predicted age acceleration at 15, but not at 9. Deprivation was not a significant predictor of accelerated aging. Age acceleration at age 9 predicted externalizing, but not internalizing, symptoms at age 15. Community threat had a direct effect on externalizing. No association emerged with internalizing.

CONCLUSION

Findings revealed that threat, not deprivation, was predictive of age acceleration, demonstrating support for this pattern longitudinally, using an epigenetic clock that is accurate in children. The findings provide critical nuance to the examination of threat, and highlight associated risks and possible intervention points for externalizing symptoms.

Epigenetics in Alzheimer's Disease: A Critical Overview

Epigenetic modifications have been implicated in a number of complex diseases as well as being a hallmark of organismal aging. Several reports have indicated an involvement of these changes in Alzheimer's disease (AD) risk and progression, most likely contributing to the dysregulation of AD-related gene expression measured by DNA methylation studies. Given that DNA methylation is tissue-specific and that AD is a brain disorder, the limitation of these studies is the ability to identify clinically useful biomarkers in a proxy tissue, reflective of the tissue of interest, that would be less invasive, more cost-effective, and easily obtainable. The age-related DNA methylation changes have also been used to develop different generations of epigenetic clocks devoted to measuring the aging in different tissues that sometimes suggests an age acceleration in AD patients. This review critically discusses epigenetic changes and aging measures as potential biomarkers for AD detection, prognosis, and progression. Given that epigenetic alterations are chemically reversible, treatments aiming at reversing these modifications will be also discussed as promising therapeutic strategies for AD.

Age Prediction Using DNA Methylation Heterogeneity Metrics

Dynamic changes in genomic DNA methylation patterns govern the epigenetic developmental programs and accompany the organism's aging. Epigenetic clock (eAge) algorithms utilize DNA methylation to estimate the age and risk factors for diseases as well as analyze the impact of various interventions. High-throughput bisulfite sequencing methods, such as reduced-representation bisulfite sequencing (RRBS) or whole genome bisulfite sequencing (WGBS), provide an opportunity to identify the genomic regions of disordered or heterogeneous DNA methylation, which might be associated with cell-type heterogeneity, DNA methylation erosion, and allele-specific methylation. We systematically evaluated the applicability of five scores assessing the variability of methylation patterns by evaluating within-sample heterogeneity (WSH) to construct human blood epigenetic clock models using RRBS data. The best performance was demonstrated by the model based on a metric designed to assess DNA methylation erosion with an MAE of 3.686 years. We also trained a prediction model that uses the average methylation level over genomic regions. Although this region-based model was relatively more efficient than the WSH-based model, the latter required the analysis of just a few short genomic regions and, therefore, could be a useful tool to design a reduced epigenetic clock that is analyzed by targeted next-generation sequencing.

Uncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation

Age estimation is a critical aspect of reconstructing a biological profile in forensic sciences. Diverse biochemical processes have been studied in their correlation with age, and the results have driven DNA methylation to the forefront as a promising biomarker. DNA methylation, an epigenetic modification, has been extensively studied in recent years for developing age estimation models in criminalistics and forensic anthropology. Epigenetic clocks, which analyze DNA sites undergoing hypermethylation or hypomethylation as individuals age, have paved the way for improved prediction models. A wide range of biomarkers and methods for DNA methylation analysis have been proposed, achieving different accuracies across samples and cell types. This review extensively explores literature from the past 5 years, showing scientific efforts toward the ultimate goal: applying age prediction models to assist in human identification.

Characterizing epigenetic aging in an adult sickle cell disease cohort

ABSTRACT

Sickle cell disease (SCD) affects ∼100 000 predominantly African American individuals in the United States, causing significant cellular damage, increased disease complications, and premature death. However, the contribution of epigenetic factors to SCD pathophysiology remains relatively unexplored. DNA methylation (DNAm), a primary epigenetic mechanism for regulating gene expression in response to the environment, is an important driver of normal cellular aging. Several DNAm epigenetic clocks have been developed to serve as a proxy for cellular aging. We calculated the epigenetic ages of 89 adults with SCD (mean age, 30.64 years; 60.64% female) using 5 published epigenetic clocks: Horvath, Hannum, PhenoAge, GrimAge, and DunedinPACE. We hypothesized that in chronic disease, such as SCD, individuals would demonstrate epigenetic age acceleration, but the results differed depending on the clock used. Recently developed clocks more consistently demonstrated acceleration (GrimAge, DunedinPACE). Additional demographic and clinical phenotypes were analyzed to explore their association with epigenetic age estimates. Chronological age was significantly correlated with epigenetic age in all clocks (Horvath, r = 0.88; Hannum, r = 0.89; PhenoAge, r = 0.85; GrimAge, r = 0.88; DunedinPACE, r = 0.34). The SCD genotype was associated with 2 clocks (PhenoAge, P = .02; DunedinPACE, P < .001). Genetic ancestry, biological sex, β-globin haplotypes, BCL11A rs11886868, and SCD severity were not associated. These findings, among the first to interrogate epigenetic aging in adults with SCD, demonstrate epigenetic age acceleration with recently developed epigenetic clocks but not older-generation clocks. Further development of epigenetic clocks may improve their predictive ability and utility for chronic diseases such as SCD.

Associations between cardiorespiratory fitness and lifestyle-related factors with DNA methylation-based ageing clocks in older men: WASEDA'S Health Study

DNA methylation-based age estimators (DNAm ageing clocks) are currently one of the most promising biomarkers for predicting biological age. However, the relationships between cardiorespiratory fitness (CRF), measured directly by expiratory gas analysis, and DNAm ageing clocks are largely unknown. We investigated the relationships between CRF and the age-adjusted value from the residuals of the regression of DNAm ageing clock to chronological age (DNAmAgeAcceleration: DNAmAgeAccel) and attempted to determine the relative contribution of CRF to DNAmAgeAccel in the presence of other lifestyle factors. DNA samples from 144 Japanese men aged 65-72 years were used to appraise first- (i.e., DNAmHorvath and DNAmHannum) and second- (i.e., DNAmPhenoAge, DNAmGrimAge, and DNAmFitAge) generation DNAm ageing clocks. Various surveys and measurements were conducted, including physical fitness, body composition, blood biochemical parameters, nutrient intake, smoking, alcohol consumption, disease status, sleep status, and chronotype. Both oxygen uptake at ventilatory threshold (VO2 /kg at VT) and peak oxygen uptake (VO2 /kg at Peak) showed a significant negative correlation with GrimAgeAccel, even after adjustments for chronological age and smoking and drinking status. Notably, VO2 /kg at VT and VO2 /kg at Peak above the reference value were also associated with delayed GrimAgeAccel. Multiple regression analysis showed that calf circumference, serum triglyceride, carbohydrate intake, and smoking status, rather than CRF, contributed more to GrimAgeAccel and FitAgeAccel. In conclusion, although the contribution of CRF to GrimAgeAccel and FitAgeAccel is relatively low compared to lifestyle-related factors such as smoking, the results suggest that the maintenance of CRF is associated with delayed biological ageing in older men.

Longitudinal changes and variation in human DNA methylation analysed with the Illumina MethylationEPIC BeadChip assay and their implications on forensic age prediction

DNA methylation, a pivotal epigenetic modification, plays a crucial role in regulating gene expression and is known to undergo dynamic changes with age. The present study investigated epigenome-wide methylation profiles in 64 individuals over two time points, 15 years apart, using the Illumina EPIC850k arrays. A mixed-effects model identified 2821 age-associated differentially methylated CpG positions (aDMPs) with a median rate of change of 0.18% per year, consistent with a 10-15% change during a human lifespan. Significant variation in the baseline DNA methylation levels between individuals of similar ages as well as inconsistent direction of change with time across individuals were observed for all the aDMPs. Twenty-three of the 2821 aDMPs were previously incorporated into forensic age prediction models. These markers displayed larger changes in DNA methylation with age compared to all the aDMPs and less variation among individuals. Nevertheless, the forensic aDMPs also showed inter-individual variations in the direction of DNA methylation changes. Only cg16867657 in ELOVL2 exhibited a uniform direction of the age-related change among the investigated individuals, which supports the current knowledge that CpG sites in ELOVL2 are the best markers for age prediction.

Sex differences in frailty among older adults

By definition, aging is a natural, gradual and continuous process. On the other hand, frailty reflects the increase in vulnerability to stressors and shortens the time without disease (health span) while longevity refers to the length of life (lifespan). The average life expectancy has significantly increased during the last few decades. A longer lifespan has been accompanied by an increase in frailty and decreased independence in older adults, with major differences existing between men and women. For example, women tend to live longer than men but also experience higher rates of frailty and disability. Sex differences prevent optimization of lifestyle interventions and therapies to effectively prevent frailty. Sex differences in frailty and aging are rooted in a complex interplay between uncontrollable (genetic, epigenetic, physiological), and controllable factors (psychosocial and lifestyle factors). Thus, understanding the underlying causes of sex differences in frailty and aging is essential for developing personalized interventions to promote healthy aging and improve quality of life in older men and women. In this review, we have discussed the key contributors and knowledge gaps related to sex differences in aging and frailty.

Epigenetic aging differences between Wichí and Criollos from Argentina: Insights from genomic history and ecology

Background and objectives

Epigenetic estimators based on DNA methylation levels have emerged as promising biomarkers of human aging. These estimators exhibit natural variations across human groups, but data about indigenous populations remain underrepresented in research. This study aims to investigate differences in epigenetic estimators between two distinct human populations, both residing in the Gran Chaco region of Argentina, the Native-American Wichí, and admixed Criollos who are descendants of intermarriages between Native Americans and the first European colonizers, using a population genetic approach.

Methodology

We analyzed 24 Wichí (mean age: 39.2 ± 12.9 yo) and 24 Criollos (mean age: 41.1 ± 14.0 yo) for DNA methylation levels using the Infinium MethylationEPIC (Illumina) to calculate 16 epigenetic estimators. Additionally, we examined genome-wide genetic variation using the HumanOmniExpress BeadChip (Illumina) to gain insights into the genetic history of these populations.

Results

Our results indicate that Native-American Wichí are epigenetically older compared to Criollos according to five epigenetic estimators. Analyses within the Criollos population reveal that global ancestry does not influence the differences observed, while local (chromosomal) ancestry shows positive associations between specific SNPs located in genomic regions over-represented by Native-American ancestry and measures of epigenetic age acceleration (AgeAccelHannum). Furthermore, we demonstrate that differences in population ecologies also contribute to observed epigenetic differences.

Conclusions and implications

Overall, our study suggests that while the genomic history may partially account for the observed epigenetic differences, non-genetic factors, such as lifestyle and ecological factors, play a substantial role in the variability of epigenetic estimators, thereby contributing to variations in human epigenetic aging.

Top Alzheimer's disease risk allele frequencies differ in HABS-HD Mexican- versus Non-Hispanic White Americans

INTRODUCTION: Here we evaluate frequencies of the top 10 Alzheimer's disease (AD) risk alleles for late-onset AD in Mexican American (MA) and non-Hispanic White (NHW) American participants enrolled in the Health and Aging Brain Study-Health Disparities Study cohort. METHODS: Using DNA extracted from this community-based diverse population, we calculated the genotype frequencies in each population to determine whether a significant difference is detected between the different ethnicities. DNA genotyping was performed per manufacturers' protocols. RESULTS: Allele and genotype frequencies for 9 of the 11 single nucleotide polymorphisms (two apolipoprotein E variants, CR1, BIN1, DRB1, NYAP1, PTK2B, FERMT2, and ABCA7) differed significantly between MAs and NHWs. DISCUSSION: The significant differences in frequencies of top AD risk alleles observed here across MAs and NHWs suggest that ethnicity-specific genetic risks for AD exist. Given our results, we are advancing additional projects to further elucidate ethnicity-specific differences in AD.

How does loneliness "get under the skin" to become biologically embedded?

Loneliness is linked to declining physical health across cardiovascular, inflammatory, metabolic, and cognitive domains. As a result, loneliness is increasingly being recognized as a public health threat, though the mechanisms that have been studied do not yet explain all loneliness-related health risk. Potential mechanisms include loneliness having 1.) direct, causal impacts on health, possibly maintained by epigenetic modification, 2.) indirect effects mediated through health-limiting behaviors, and 3.) artifactual associations perhaps related to genetic overlap and reverse causation. In this scoping review, we examine the evidence surrounding each of these pathways, with a particular emphasis on emerging research on epigenetic effects, in order to evaluate how loneliness becomes biologically embedded. We conclude that there are significant gaps in our knowledge of how psychosocial stress may lead to physiological changes, so more work is needed to understand if, how, and when loneliness has a direct influence on health. Hypothalamic-pituitary adrenocortical axis disruptions that lead to changes in gene expression through methylation and the activity of transcription factor proteins are one promising area of research but are confounded by a number of unmeasured factors. Therefore, wok is needed using causally informative designs, such as twin and family studies and intensively longitudinal diary studies.

No evidence of accelerated epigenetic aging among black heroin users: A case vs control analysis

This study sought to assess the association between illicit opioid use and accelerated epigenetic aging (A.K.A. DNAm Age) among people of African ancestry who use heroin. DNA was obtained from participants with opioid use disorder (OUD) who confirmed heroin as their primary drug of choice. Clinical inventories of drug use included: the Addiction Severity Index (ASI) Drug-Composite Score (range: 0-1), and Drug Abuse Screening Test (DAST-10; range: 0-10). A control group of participants of African ancestry who did not use heroin was recruited and matched to heroin users on sex, age, socioeconomic level, and smoking status. Methylation data were assessed in an epigenetic clock to determined and compare Epigenetic Age to Chronological Age (i.e., age acceleration or deceleration). Data were obtained from 32 controls [mean age 36.3 (±7.5) years] and 64 heroin users [mean age 48.1 (±6.6) years]. The experimental group used heroin for an average of 18.1 (±10.6) years, reported use of 6.4 (±6.1) bags of heroin/day, with a mean DAST-10 score of 7.0 (±2.6) and ASI Score of 0.33 (±0.19). Mean age acceleration for heroin users [+0.56 (± 9.5) years] was significantly (p< 0.05) lower than controls [+5.19 (± 9.1) years]. This study did not find evidence that heroin use causes epigenetic age acceleration.

Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study

DNA methylation studies of incident type 2 diabetes in US populations are limited, and to our knowledge none included individuals of African descent living in the US. We performed an epigenome-wide association analysis of blood-based methylation levels at CpG sites with incident type 2 diabetes using Cox regression in 2,091 Black and 1,029 White individuals from the Atherosclerosis Risk in Communities study. At an epigenome-wide significance threshold of 10-7, we detected 7 novel diabetes-associated CpG sites in C1orf151 (cg05380846: HR= 0.89, p = 8.4 × 10-12), ZNF2 (cg01585592: HR= 0.88, p = 1.6 × 10-9), JPH3 (cg16696007: HR= 0.87, p = 7.8 × 10-9), GPX6 (cg02793507: HR= 0.85, p = 2.7 × 10-8 and cg00647063: HR= 1.20, p = 2.5 × 10-8), chr17q25 (cg16865890: HR= 0.8, p = 6.9 × 10-8), and chr11p15 (cg13738793: HR= 1.11, p = 7.7 × 10-8). The CpG sites at C1orf151, ZNF2, JPH3 and GPX6, were identified in Black adults, chr17q25 was identified in White adults, and chr11p15 was identified upon meta-analyzing the two groups. The CpG sites at JPH3 and GPX6 were likely associated with incident type 2 diabetes independent of BMI. All the CpG sites, except at JPH3, were likely consequences of elevated glucose at baseline. We additionally replicated known type 2 diabetes-associated CpG sites including cg19693031 at TXNIP, cg00574958 at CPT1A, cg16567056 at PLBC2, cg11024682 at SREBF1, cg08857797 at VPS25, and cg06500161 at ABCG1, 3 of which were replicated in Black adults at the epigenome-wide threshold. We observed modest increase in type 2 diabetes variance explained upon addition of the significantly associated CpG sites to a Cox model that included traditional type 2 diabetes risk factors and fasting glucose (increase from 26.2% to 30.5% in Black adults; increase from 36.9% to 39.4% in White adults). We examined if groups of proximal CpG sites were associated with incident type 2 diabetes using a gene-region specific and a gene-region agnostic differentially methylated region (DMR) analysis. Our DMR analyses revealed several clusters of significant CpG sites, including a DMR consisting of a previously discovered CpG site at ADCY7 and promoter regions of TP63 which were differentially methylated across all race groups. This study illustrates improved discovery of CpG sites/regions by leveraging both individual CpG site and DMR analyses in an unexplored population. Our findings include genes linked to diabetes in experimental studies (e.g., GPX6, JPH3, and TP63), and future gene-specific methylation studies could elucidate the link between genes, environment, and methylation in the pathogenesis of type 2 diabetes.

Epigenetic clocks and research implications of the lack of data on whom they have been developed: a review of reported and missing sociodemographic characteristics

Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population.

Epigenomic Links Between Social Determinants of Health and Symptoms: A Scoping Review

Social determinants of health (SDoH) impact health and wellness. The link between SDoH and adverse health outcomes, including symptom occurrence and severity, may be explained by an individual's physiologic response to one or more SDoH. One potential mechanism underlying this physiologic response linking SDoH and symptoms is the dynamic epigenome. The purpose of this scoping review of the literature was to examine differential susceptibility for symptoms by identifying and summarizing research linking SDoH and symptoms through epigenomic mechanisms. PubMed was searched to identify empirical research where at least one SDoH was an independent or dependent variable, at least one symptom was investigated, and the investigation included an epigenomic measure. Of the 484 articles initially retrieved, after thorough vetting, 41 articles met eligibility. The most studied symptom was depressive symptoms followed by anxiety, cognitive function, sleep dysfunction, and pain. The most frequently studied SDoH were: 1) stress, particularly early life stress and acculturative stress; and 2) trauma, predominantly childhood trauma. DNA methylation and telomere length were the most studied epigenomic measures. Four genes (SLC6A4, BDNF, NR3C1, OXTR) had evidence from multiple studies and across methodological approaches linking SDoH to symptoms. This review supports the inclusion of epigenomic approaches to better understand the link between SDoH and symptoms and provides evidence that SDoH impact telomere length and the methylation of genes involved in neurotransmitter signaling, neuronal survival, behavior, inflammation and stress response.

Utility of DNA Methylation as a Biomarker in Aging and Alzheimer's Disease

Epigenetic mechanisms such as DNA methylation have been implicated in a number of diseases including cancer, heart disease, autoimmune disorders, and neurodegenerative diseases. While it is recognized that DNA methylation is tissue-specific, a limitation for many studies is the ability to sample the tissue of interest, which is why there is a need for a proxy tissue such as blood, that is reflective of the methylation state of the target tissue. In the last decade, DNA methylation has been utilized in the design of epigenetic clocks, which aim to predict an individual's biological age based on an algorithmically defined set of CpGs. A number of studies have found associations between disease and/or disease risk with increased biological age, adding weight to the theory of increased biological age being linked with disease processes. Hence, this review takes a closer look at the utility of DNA methylation as a biomarker in aging and disease, with a particular focus on Alzheimer's disease.

An integrative framework and recommendations for the study of DNA methylation in the context of race and ethnicity

Human social epigenomics research is critical to elucidate the intersection of social and genetic influences underlying racial and ethnic differences in health and development. However, this field faces major challenges in both methodology and interpretation with regard to disentangling confounded social and biological aspects of race and ethnicity. To address these challenges, we discuss how these constructs have been approached in the past and how to move forward in studying DNA methylation (DNAm), one of the best-characterized epigenetic marks in humans, in a responsible and appropriately nuanced manner. We highlight self-reported racial and ethnic identity as the primary measure in this field, and discuss its implications in DNAm research. Racial and ethnic identity reflects the biological embedding of an individual's sociocultural experience and environmental exposures in combination with the underlying genetic architecture of the human population (i.e., genetic ancestry). Our integrative framework demonstrates how to examine DNAm in the context of race and ethnicity, while considering both intrinsic factors-including genetic ancestry-and extrinsic factors-including structural and sociocultural environment and developmental niches-when focusing on early-life experience. We reviewed DNAm research in relation to health disparities given its relevance to race and ethnicity as social constructs. Here, we provide recommendations for the study of DNAm addressing racial and ethnic differences, such as explicitly acknowledging the self-reported nature of racial and ethnic identity, empirically examining the effects of genetic variants and accounting for genetic ancestry, and investigating race-related and culturally regulated environmental exposures and experiences.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44155-023-00039-z.

Developmental Brain Injury and Social Determinants of Health: Opportunities to Combine Preclinical Models for Mechanistic Insights into Recovery

Epidemiological studies show that social determinants of health are among the strongest factors associated with developmental outcomes after prenatal and perinatal brain injuries, even when controlling for the severity of the initial injury. Elevated socioeconomic status and a higher level of parental education correlate with improved neurologic function after premature birth. Conversely, children experiencing early life adversity have worse outcomes after developmental brain injuries. Animal models have provided vital insight into mechanisms perturbed by developmental brain injuries, which have indicated directions for novel therapeutics or interventions. Animal models have also been used to learn how social environments affect brain maturation through enriched environments and early adverse conditions. We recognize animal models cannot fully recapitulate human social circumstances. However, we posit that mechanistic studies combining models of developmental brain injuries and early life social environments will provide insight into pathways important for recovery. Some studies combining enriched environments with neonatal hypoxic injury models have shown improvements in developmental outcomes, but further studies are needed to understand the mechanisms underlying these improvements. By contrast, there have been more limited studies of the effects of adverse conditions on developmental brain injury extent and recovery. Uncovering the biological underpinnings for early life social experiences has translational relevance, enabling the development of novel strategies to improve outcomes through lifelong treatment. With the emergence of new technologies to analyze subtle molecular and behavioral phenotypes, here we discuss the opportunities for combining animal models of developmental brain injury with social construct models to deconvolute the complex interactions between injury, recovery, and social inequity.

A Race-Specific, DNA Methylation Analysis of Aging in Normal Rectum: Implications for the Biology of Aging and Its Relationship to Rectal Cancer

Approximately 90% of colorectal cancer (CRC) develop over the age of 50, highlighting the important role of aging in CRC risk. African Americans (AAs) shoulder a greater CRC burden than European Americans (EA) and are more likely to develop CRC at a younger age. The effects of aging in AA and EA normal rectal tissue have yet to be defined. Here, we performed epigenome-wide DNA methylation analysis in the first, large-scale biracial cohort of normal rectum (n = 140 samples). We identified increased epigenetic age acceleration in EA than AA rectum (p = 3.91 × 10^-4) using linear regression. We also identified differentially methylated regions (DMRs) associated with chronological aging in AA and EA, separately using DMRcate. Next, a consensus set of regions associated with cancer was identified through DMR analysis of two rectal cancer cohorts. The vast majority of AA DMRs were present in our analysis of aging in rectum of EA subjects, though rates of epigenetic drift were significantly greater in AA (p = 1.94 × 10^-45). However, 3.66-fold more DMRs were associated with aging in rectum of EA subjects, many of which were also associated with rectal cancer. Our findings reveal a novel relationship between race, age, DNA methylation and rectal cancer risk that warrants further investigation.

Disrupted methylation patterns at birth persist in early childhood: a prospective cohort analysis

BACKGROUND

Alterations in the epigenome are a risk factor in multiple disease states. We have demonstrated in the past that disruption of the epigenome during early pregnancy or periconception, as demonstrated by altered methylation, may be associated with both assisted reproductive technology and undesirable clinical outcomes at birth, such as low birth weight. We have previously defined this altered methylation, calculated based on statistical upper and lower limits of outlier CpGs compared to the population, as an 'outlier methylation phenotype' (OMP). Our aim in this study was to determine whether children thus identified as possessing an OMP at birth by DNA methylation in cord blood persist as outliers in early childhood based on salivary DNA methylation.

RESULTS

A total of 31 children were included in the analysis. Among 24 children for whom both cord blood DNA and salivary DNA were available, DNA methylation patterns, analyzed using the Illumina Infinium MethylationEPIC BeadChip (850 K), between cord blood at birth and saliva in childhood at age 6-12 years remain stable (R2 range 0.89-0.97). At birth, three out of 28 children demonstrated an OMP in multiple cord blood datasets and hierarchical clustering. Overall DNA methylation among all three OMP children identified as outliers at birth was remarkably stable (individual R2 0.908, 0.92, 0.915), even when only outlier CpG sites were considered (R2 0.694, 0.738, 0.828).

CONCLUSIONS

DNA methylation signatures in cord blood remain stable over time as demonstrated by a strong correlation with epigenetic salivary signatures in childhood. Future work is planned to identify whether a clinical phenotype is associated with OMP and, if so, could undesirable clinical outcomes in childhood and adulthood be predicted at birth.

Association between work characteristics and epigenetic age acceleration: cross-sectional results from UK - Understanding Society study

Occupation-related stress and work characteristics are possible determinants of social inequalities in epigenetic aging but have been little investigated. Here, we investigate the association of several work characteristics with epigenetic age acceleration (AA) biomarkers. The study population included employed and unemployed men and women (n = 631) from the UK Understanding Society study. We evaluated the association of employment and work characteristics related to job type, job stability; job schedule; autonomy and influence at work; occupational physical activity; and feelings regarding the job with four epigenetic age acceleration biomarkers (Hannum, Horvath, PhenoAge, GrimAge) and pace of aging (DunedinPoAm, DunedinPACE). We fitted linear regression models, unadjusted and adjusted for established risk factors, and found the following associations for unemployment (years of acceleration): HorvathAA (1.51, 95% CI 0.08, 2.95), GrimAgeAA (1.53, 95% CI 0.16, 2.90) and 3.21 years for PhenoAA (95% CI 0.89, 5.33). Job insecurity increased PhenoAA (1.83, 95% CI 0.003, 3.67), while working at night was associated with an increase of 2.12 years in GrimAgeAA (95% CI 0.69, 3.55). We found effects of unemployment to be stronger in men and effects of night shift work to be stronger in women. These results provide evidence of associations between unemployment with accelerated ageing and suggest that insecure employment and night work may also increase age acceleration. Our findings have implications for policies relating to current changes in working conditions and highlight the utility of biological age biomarkers in studies in younger populations without long-term health information.

Sex-specific transcriptome differences in a middle-aged frailty cohort

BACKGROUND

Frailty is a clinical syndrome described as reduced physiological reserve and increased vulnerability. Typically examined in older adults, recent work shows frailty occurs in middle-aged individuals and is associated with increased mortality. Previous investigation of global transcriptome changes in a middle-aged cohort from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study demonstrated inflammatory genes and pathways were significantly altered by frailty status and race. Transcriptome differences in frailty by sex remain unclear. We sought to discover novel genes and pathways associated with sex and frailty in a diverse middle-aged cohort using RNA-Sequencing.

METHODS

Differential gene expression and pathway analyses were performed in peripheral blood mononuclear cells for 1) frail females (FRAF, n = 4) vs non-frail females (NORF, n = 4), 2) frail males (FRAM, n = 4) vs non-frail males (NORM, n = 4), 3) FRAM vs FRAF, and 4) NORM vs NORF. We evaluated exclusive significant genes and pathways, as well as overlaps, between the comparison groups.

RESULTS

Over 80% of the significant genes exclusive to FRAF vs NORF, FRAM vs NORM, and FRAM vs FRAF, respectively, were novel and associated with various biological functions. Pathways exclusive to FRAF vs NORF were associated with reduced inflammation, while FRAM vs NORM exclusive pathways were related to aberrant musculoskeletal physiology. Pathways exclusive to FRAM vs FRAF were associated with reduced cell cycle regulation and activated catabolism and Coronavirus pathogenesis.

CONCLUSIONS

Our results indicate sex-specific transcriptional changes occur in middle-aged frailty, enhancing knowledge on frailty progression and potential therapeutic targets to prevent frailty.

APOE gene region methylation is associated with cognitive performance in middle-aged urban adults

Apolipoprotein (APOE) ε4 allele is a strong risk factor for Alzheimer's disease (AD) and cognitive decline. Epigenetic modifications such as DNA methylation (DNAm) play a central role in cognition. This study sought to identify DNAm sites in the APOE genomic region associated with cognitive performance in a racially diverse middle-aged cohort (n = 411). Cognitive performance was measured by 11 standard neuropsychological tests. Two CpG sites were associated with the Card Rotation and Benton Visual Retention cognitive tests. The methylation level of the CpG site cg00397545 was associated with Card Rotation Test score (p = 0.000177) and a novel CpG site cg10178308 was associated with Benton Visual Retention Test score (p = 0.000084). Significant associations were observed among the dietary inflammatory index, which reflects the inflammatory potential of the diet, cognitive performance and the methylation level of several CpG sites. Our results indicate that DNAm in the APOE genomic area is correlated with cognitive performance and may presage cognitive decline.

DNA methylation profile of a rural cohort exposed to early-adversity and malnutrition: An exploratory analysis

Barker's hypothesis affirms that undernourishment in early-life induces metabolic reprogramming that compromises organism functions later in life, leading to age-related diseases. We are exposed to environmental and social conditions that impact our life trajectories, leading to ageing phenotypes as we grow. Epigenetic mechanisms constitute the link between both external stimuli and genetic programming. Studies have focused on describing the effect of early adverse events such as trauma, famines, or childhood labor on epigenetic markers in adulthood and the elderly. However, we lack information on epigenetic programming in individuals born in rural communities from underdeveloped countries, exposed to negative influences during fetal and postnatal development, particularly chronic malnutrition. Hence, in this exploratory analysis, we characterize the epigenome of individuals and some parents from Tlaltizapan (a rural community in Mexico originally studied almost 50 years ago) and collect anthropometric data on growth and development, as well on the living conditions of the families. Our results help build a biological hypothesis indicating that most of the epigenetic age measures of the subjects are significantly different among them. Interestingly, the most affected methylated regions correspond to pathways involved in neuronal system development, reproductive behaviour, learning and memory regulation.

A cautionary note on altered pace of aging in the COVID-19 era

Coronavirus disease 2019 (COVID-19) is highly age-dependent due to hi-jacking the molecular control of the immune cells by the severe acute respiratory syndrome-corona virus 2 (SARS-CoV-2) leading to aberrant DNA methylation (DNAm) pattern of blood in comparison to normal individuals. These epigenetic modifications have been linked to perturbations to the epigenetic clock, development of long COVID-19 syndrome, and all-cause mortality risk. I reviewed the effects of COVID-19 on different molecular age markers such as the DNAm, telomere length (TL), and signal joint T-cell receptor excision circle (sjTREC). Integrating the accumulated clinical research data, COVID-19 and novel medical management may alter the pace of aging in adult individuals (<60 years). As such, COVID-19 might be a confounder in epigenetic age estimation similar to life style diversities, pathogens and pathologies which may influence the interpretation of DNAm data. Similarly, the SARS-CoV-2 affects T-lymphocyte function with possible influence on sjTREC levels. In contrast, TL measurements performed years before the SARS-CoV-2 pandemic proved that short TL predisposes to severe COVID- 19 independently from chronological age. However, the persistence of COVID-19 epigenetic scars and the durability of the immune response after vaccination and their effect on the ongoing pace of aging are still unknown. In the light of these data, the heterogeneous nature of the samples in these studies mandates a systematic evaluation of the currrent methods. SARS-CoV-2 may modify the reliability of the age estimation models in real casework because blood is the most common biological sample encountered in forensic contexts.

A biosocial return to race? A cautionary view for the postgenomic era

Recent studies demonstrating epigenetic and developmental sensitivity to early environments, as exemplified by fields like the Developmental Origins of Health and Disease (DOHaD) and environmental epigenetics, are bringing new data and models to bear on debates about race, genetics, and society. Here, we first survey the historical prominence of models of environmental determinism in early formulations of racial thinking to illustrate how notions of direct environmental effects on bodies have been used to naturalize racial hierarchy and inequalities in the past. Next, we conduct a scoping review of postgenomic work in environmental epigenetics and DOHaD that looks at the role of race/ethnicity in human health (2000-2021). Although there is substantial heterogeneity in how race is conceptualized and interpreted across studies, we observe practices that may unwittingly encourage typological thinking, including: using DNA methylation as a novel marker of racial classification; neglect of variation and reversibility within supposedly homogenous racial groups; and a tendency to label and reify whole groups as pathologized or impaired. Even in the very different politico-economic and epistemic context of contemporary postgenomic science, these trends echo deeply held beliefs in Western thinking which claimed that different environments shape different bodies and then used this logic to argue for essential differences between Europeans and non-Europeans. We conclude with a series of suggestions on interpreting and reporting findings in these fields that we feel will help researchers harness this work to benefit disadvantaged groups while avoiding the inadvertent dissemination of new and old forms of stigma or prejudice.

Associations Between DNA Methylation Age Acceleration, Depressive Symptoms, and Cardiometabolic Traits in African American Mothers From the InterGEN Study

Background

African American women (AAW) have a high risk of both cardiometabolic (CM) illness and depressive symptoms. Depressive symptoms co-occur in individuals with CM illness at higher rates than the general population, and accelerated aging may explain this. In this secondary analysis, we examined associations between age acceleration; depressive symptoms; and CM traits (hypertension, diabetes mellitus [DM], and obesity) in a cohort of AAW.

Methods

Genomic and clinical data from the InterGEN cohort (n = 227) were used. Age acceleration was based on the Horvath method of DNA methylation (DNAm) age estimation. Accordingly, DNAm age acceleration (DNAm AA) was defined as the residuals from a linear regression of DNAm age on chronological age. Spearman's correlations, linear and logistic regression examined associations between DNAm AA, depressive symptoms, and CM traits.

Results

DNAm AA did not associate with total depressive symptom scores. DNAm AA correlated with specific symptoms including self-disgust/self-hate (-0.13, 95% CI -0.26, -0.01); difficulty with making decisions (-0.15, 95% CI -0.28, -0.02); and worry over physical health (0.15, 95% CI 0.02, 0.28), but were not statistically significant after multiple comparison correction. DNAm AA associated with obesity (0.08, 95% CI 1.02, 1.16), hypertension (0.08, 95% CI 1.01, 1.17), and DM (0.20, 95% CI 1.09, 1.40), after adjustment for potential confounders.

Conclusions

Associations between age acceleration and depressive symptoms may be highly nuanced and dependent on study design contexts. Factors other than age acceleration may explain the connection between depressive symptoms and CM traits. AAW with CM traits may be at increased risk of accelerated aging.

Plasma neurofilament light and its association with all-cause mortality risk among urban middle-aged men and women

BACKGROUND

Neurofilament light chain (NfL) is released into the blood during neuronal damage. NfL is linked to mortality in neurological disorders, remaining unexplored in population studies. We investigated whether initial (v1) and annualized change (δ) in plasma NfL can predict all-cause mortality in middle-aged dementia-free urban adults.

METHODS

Longitudinal data were from 694 participants in the Healthy Aging in Neighborhoods of Diversity Across the Life Span study (HANDLS, mean agev1: 47.8 years, 42% male, 55.8% African American). Plasma NfL was measured prospectively at three visits. Analyses included Cox proportional hazards models for all-cause mortality risk and 4-way decomposition testing for interaction and mediation.

RESULTS

Unlike men, women exhibited a direct association between δNfL (above vs. below median) and all-cause mortality risk in both the minimally (HR = 3.91, 95% CI 1.10-13.9, p = 0.036) and fully adjusted models (HR = 4.92, 95% CI 1.26-19.2, p = 0.022), and for δNfL (per unit increase) in the full model (HR = 1.65, 95% CI 1.04-2.61, p = 0.034). In both models, and among women, 1 standard deviation of NfLv1 was associated with an increased all-cause mortality risk (reduced model: HR = 2.01, 95% CI 1.24-3.25, p = 0.005; full model: HR = 1.75, 95% CI 1.02-2.98, p = 0.041). Only few interactions were detected for cardio-metabolic risk factors. Notably, NfLv1 was shown to be a better prognostic indicator at normal hsCRP values among women, while HbA1c and δNfL interacted synergistically to determine mortality risk, overall.

CONCLUSIONS

These findings indicate that plasma NfL levels at baseline and over time can predict all-cause mortality in women and interacts with hsCRP and HbA1c to predict that risk.

The Socioeconomic Gradient in Epigenetic Ageing Clocks: Evidence from the Multi-Ethnic Study of Atherosclerosis and the Health and Retirement Study

Epigenetic clocks have been widely used to predict disease risk in multiple tissues or cells. Their success as a measure of biological ageing has prompted research on the connection between epigenetic pathways of ageing and the socioeconomic gradient in health and mortality. However, studies examining social correlates of epigenetic ageing have yielded inconsistent results. We conducted a comprehensive, comparative analysis of associations between various dimensions of socioeconomic status (SES) (education, income, wealth, occupation, neighbourhood environment, and childhood SES) and eight epigenetic clocks in two well-powered US ageing studies: The Multi-Ethnic Study of Atherosclerosis (MESA) (n = 1,211) and the Health and Retirement Study (HRS) (n = 4,018). In both studies, we found robust associations between SES measures in adulthood and the GrimAge and DunedinPoAm clocks (Bonferroni-corrected p-value < 0.01). In the HRS, significant associations with the Levine and Yang clocks were also evident. These associations were only partially mediated by smoking, alcohol consumption, and obesity, which suggests that differences in health behaviours alone cannot explain the SES gradient in epigenetic ageing in older adults. Further analyses revealed concurrent associations between polygenic risk for accelerated intrinsic epigenetic ageing, SES, and the Levine clock, indicating that genetic risk and social disadvantage may contribute additively to faster biological aging.

Assessing the causal role of epigenetic clocks in the development of multiple cancers: a Mendelian randomization study

Background

Epigenetic clocks have been associated with cancer risk in several observational studies. Nevertheless, it is unclear whether they play a causal role in cancer risk or if they act as a non-causal biomarker.

Methods

We conducted a two-sample Mendelian randomization (MR) study to examine the genetically predicted effects of epigenetic age acceleration as measured by HannumAge (nine single-nucleotide polymorphisms (SNPs)), Horvath Intrinsic Age (24 SNPs), PhenoAge (11 SNPs), and GrimAge (4 SNPs) on multiple cancers (i.e. breast, prostate, colorectal, ovarian and lung cancer). We obtained genome-wide association data for biological ageing from a meta-analysis (N = 34,710), and for cancer from the UK Biobank (N cases = 2671-13,879; N controls = 173,493-372,016), FinnGen (N cases = 719-8401; N controls = 74,685-174,006) and several international cancer genetic consortia (N cases = 11,348-122,977; N controls = 15,861-105,974). Main analyses were performed using multiplicative random effects inverse variance weighted (IVW) MR. Individual study estimates were pooled using fixed effect meta-analysis. Sensitivity analyses included MR-Egger, weighted median, weighted mode and Causal Analysis using Summary Effect Estimates (CAUSE) methods, which are robust to some of the assumptions of the IVW approach.

Results

Meta-analysed IVW MR findings suggested that higher GrimAge acceleration increased the risk of colorectal cancer (OR = 1.12 per year increase in GrimAge acceleration, 95% CI 1.04-1.20, p = 0.002). The direction of the genetically predicted effects was consistent across main and sensitivity MR analyses. Among subtypes, the genetically predicted effect of GrimAge acceleration was greater for colon cancer (IVW OR = 1.15, 95% CI 1.09-1.21, p = 0.006), than rectal cancer (IVW OR = 1.05, 95% CI 0.97-1.13, p = 0.24). Results were less consistent for associations between other epigenetic clocks and cancers.

Conclusions

GrimAge acceleration may increase the risk of colorectal cancer. Findings for other clocks and cancers were inconsistent. Further work is required to investigate the potential mechanisms underlying the results.

Funding

FMB was supported by a Wellcome Trust PhD studentship in Molecular, Genetic and Lifecourse Epidemiology (224982/Z/22/Z which is part of grant 218495/Z/19/Z). KKT was supported by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme) and by the Hellenic Republic's Operational Programme 'Competitiveness, Entrepreneurship & Innovation' (OΠΣ 5047228). PH was supported by Cancer Research UK (C18281/A29019). RMM was supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). RMM is a National Institute for Health Research Senior Investigator (NIHR202411). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. GDS and CLR were supported by the Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5, respectively) and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). REM was supported by an Alzheimer's Society project grant (AS-PG-19b-010) and NIH grant (U01 AG-18-018, PI: Steve Horvath). RCR is a de Pass Vice Chancellor's Research Fellow at the University of Bristol.

DNA methylation changes in cord blood and the developmental origins of health and disease – a systematic review and replication study

Background

Environmental exposures in utero which modify DNA methylation may have a long-lasting impact on health and disease in offspring. We aimed to identify and replicate previously published genomic loci where DNA methylation changes are attributable to in utero exposures in the NutriGen birth cohort studies Alliance.

Methods

We reviewed the literature to identify differentially methylated sites of newborn DNA which are associated with the following five traits of interest maternal diabetes, pre-pregnancy body mass index (BMI), diet during pregnancy, smoking, and gestational age. We then attempted to replicate these published associations in the Canadian Healthy Infant Longitudinal Development (CHILD) and the South Asian birth cohort (START) cord blood epigenome-wide data.

Results

We screened 68 full-text articles and identified a total of 17 cord blood epigenome-wide association studies (EWAS) of the traits of interest. Out of the 290 CpG sites reported, 19 were identified in more than one study; all of them associated with maternal smoking. In CHILD and START EWAS, thousands of sites associated with gestational age were identified and maintained significance after correction for multiple testing. In CHILD, there was differential methylation observed for 8 of the published maternal smoking sites. No other traits tested (i.e., folate levels, gestational diabetes, birthweight) replicated in the CHILD or START cohorts.

Conclusions

Maternal smoking during pregnancy and gestational age are strongly associated with differential methylation in offspring cord blood, as assessed in the EWAS literature and our birth cohorts. There are a limited number of reported methylation sites associated in more than two independent studies related to pregnancy. Additional large studies of diverse populations with fine phenotyping are needed to produce robust epigenome-wide data in order to further elucidate the effect of intrauterine exposures on the infants’ methylome.

Evidence for differences in DNA methylation between Germans and Japanese

As a contribution to the discussion about the possible effects of ethnicity/ancestry on age estimation based on DNA methylation (DNAm) patterns, we directly compared age-associated DNAm in German and Japanese donors in one laboratory under identical conditions. DNAm was analyzed by pyrosequencing for 22 CpG sites (CpGs) in the genes PDE4C, RPA2, ELOVL2, DDO, and EDARADD in buccal mucosa samples from German and Japanese donors (N = 368 and N = 89, respectively).Twenty of these CpGs revealed a very high correlation with age and were subsequently tested for differences between German and Japanese donors aged between 10 and 65 years (N = 287 and N = 83, respectively). ANCOVA was performed by testing the Japanese samples against age- and sex-matched German subsamples (N = 83 each; extracted 500 times from the German total sample). The median p values suggest a strong evidence for significant differences (p < 0.05) at least for two CpGs (EDARADD, CpG 2, and PDE4C, CpG 2) and no differences for 11 CpGs (p > 0.3).Age prediction models based on DNAm data from all 20 CpGs from German training data did not reveal relevant differences between the Japanese test samples and German subsamples. Obviously, the high number of included "robust CpGs" prevented relevant effects of differences in DNAm at two CpGs.Nevertheless, the presented data demonstrates the need for further research regarding the impact of confounding factors on DNAm in the context of ethnicity/ancestry to ensure a high quality of age estimation. One approach may be the search for "robust" CpG markers-which requires the targeted investigation of different populations, at best by collaborative research with coordinated research strategies.

The accelerated aging phenotype: The role of race and social determinants of health on aging

The pursuit to discover the fundamental biology and mechanisms of aging within the context of the physical and social environment is critical to designing interventions to prevent and treat its complex phenotypes. Aging research is critically linked to understanding health disparities because these inequities shape minority aging, which may proceed on a different trajectory than the overall population. Health disparities are characteristically seen in commonly occurring age-associated diseases such as cardiovascular and cerebrovascular disease as well as diabetes mellitus and cancer. The early appearance and increased severity of age-associated disease among African American and low socioeconomic status (SES) individuals suggests that the factors contributing to the emergence of health disparities may also induce a phenotype of 'premature aging' or 'accelerated aging' or 'weathering'. In marginalized and low SES populations with high rates of early onset age-associated disease the interaction of biologic, psychosocial, socioeconomic and environmental factors may result in a phenotype of accelerated aging biologically similar to premature aging syndromes with increased susceptibility to oxidative stress, premature accumulation of oxidative DNA damage, defects in DNA repair and higher levels of biomarkers of oxidative stress and inflammation. Health disparities, therefore, may be the end product of this complex interaction in populations at high risk. This review will examine the factors that drive both health disparities and the accelerated aging phenotype that ultimately contributes to premature mortality.

Epigenetic Aging Biomarkers Associated With Cognitive Impairment in Older African American Adults With Human Immunodeficiency Virus (HIV)

BACKGROUND

Accelerated epigenetic aging using DNA methylation (DNAm)-based biomarkers has been reported in people with human immunodeficiency virus (HIV, PWH), but limited data are available among African Americans (AA), women, and older PWH.

METHODS

DNAm was measured using Illumina EPIC Arrays for 107 (69 PWH and 38 HIV-seronegative controls) AA adults ≥60 years in New York City. Six DNAm-based biomarkers of aging were estimated: (1) epigenetic age acceleration (EAA), (2) extrinsic epigenetic age acceleration (EEAA), (3) intrinsic epigenetic age acceleration (IEAA), (4) GrimAge, (5) PhenoAge, and (6) DNAm-estimated telomere length (DNAm-TL). The National Institutes of Health (NIH) Toolbox Cognition Battery (domains: executive function, attention, working memory, processing speed, and language) and Montreal Cognitive Assessment (MoCA) were administered. Participants were assessed for frailty by the Fried criteria.

RESULTS

The PWH and control groups did not differ by sex, chronological age, or ethnicity. In total, 83% of PWH had a viral load <50 copies/mL, and 94% had a recent CD4 ≥200 cells/µL. The PWH group had a higher EAA, EEAA, GrimAge, and PhenoAge, and a lower DNAm-TL compared to the controls. IEAA was not different between groups. For PWH, there were significant negative correlations between IEAA and executive function, attention, and working memory and PhenoAge and attention. No associations between biomarkers and frailty were detected.

CONCLUSIONS

Evidence of epigenetic age acceleration was observed in AA older PWH using DNAm-based biomarkers of aging. There was no evidence of age acceleration independent of cell type National Institutes of Health composition (IEAA) associated with HIV, but this measure was associated with decreased cognitive function among PWH.

Development and inter-laboratory validation of the VISAGE enhanced tool for age estimation from semen using quantitative DNA methylation analysis

The analysis of DNA methylation has become an established method for chronological age estimation. This has triggered interest in the forensic community to develop new methods for age estimation from biological crime scene material. Various assays are available for age estimation from somatic tissues, the majority from blood. Age prediction from semen requires different DNA methylation markers and the only assays currently developed for forensic analysis are based on SNaPshot or pyrosequencing. Here, we describe a new assay using massively parallel sequencing to analyse 13 candidate CpG sites targeted in two multiplex PCRs. The assay has been validated by five consortium laboratories of the VISible Attributes through GEnomics (VISAGE) project within a collaborative exercise and was tested for reproducible quantification of DNA methylation levels and sensitivity with DNA methylation controls. Furthermore, DNA extracts and stains on Whatman FTA cards from two semen samples were used to evaluate concordance and mimic casework samples. Overall, the assay yielded high read depths (> 1000 reads) at all 13 marker positions. The methylation values obtained indicated robust quantification with an average standard deviation of 2.8% at the expected methylation level of 50% across the 13 markers and a good performance with 50 ng DNA input into bisulfite conversion. The absolute difference of quantifications from one participating laboratory to the mean quantifications of concordance and semen stains of remaining laboratories was approximately 1%. These results demonstrated the assay to be robust and suitable for age estimation from semen in forensic investigations. In addition to the 13-marker assay, a more streamlined protocol combining only five age markers in one multiplex PCR was developed. Preliminary results showed no substantial differences in DNA methylation quantification between the two assays, indicating its applicability with the VISAGE age model for semen developed with data from the complete 13-marker tool.

[The presence of a psychiatric diagnosis could alter the epigenetic clock in monozygotic twins]

BACKGROUND

The acceleration of the epigenetic clock has been associated with a reduction in life expectancy. Individuals diagnosed with a psychiatric disorder have a reduction in life expectancy, and some studies have correlated it with accelerated aging.

OBJECTIVE

The present study aims to explore whether the presence of any psychiatric disorder could accelerate the epigenetic clock in monozygotic twins.

METHODS

A total of 15 pairs of monozygotic twins were included. Epigenetic age in peripheral blood cells was estimated by previously published algorithms, using the 450K Beadchip microarray.

RESULTS

We found that in twins with a diagnosis of a psychiatric disorder, the epigenetic clock could increase compared to their twin without a psychiatric disorder.

DISCUSSION AND CONCLUSION

The presence of some psychiatric disorder could accelerate the epigenetic clock in homozygous twins, but studies with larger samples are required to clarify this relationship.

Impact of paternal education on epigenetic ageing in adolescence and mid-adulthood: a multi-cohort study in the USA and Mexico

BACKGROUND

Both parental and neighbourhood socio-economic status (SES) are linked to poorer health independently of personal SES measures, but the biological mechanisms are unclear. Our objective was to examine these influences via epigenetic age acceleration (EAA)-the discrepancy between chronological and epigenetic ages.

METHODS

We examined three USA-based [Coronary Artery Risk Disease in Adults (CARDIA) study, Fragile Families and Child Wellbeing Study (FFCWS) and Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS)] and one Mexico-based (Project Viva) cohort. DNA methylation was measured using Illumina arrays, personal/parental SES by questionnaire and neighbourhood disadvantage from geocoded address. In CARDIA, we examined the most strongly associated personal, parental and neighbourhood SES measures with EAA (Hannum's method) at study years 15 and 20 separately and combined using a generalized estimating equation (GEE) and compared with other EAA measures (Horvath's EAA, PhenoAge and GrimAge calculators, and DunedinPoAm).

RESULTS

EAA was associated with paternal education in CARDIA [GEEs: βsome college = -1.01 years (-1.91, -0.11) and β<high school = 1.05 (0.09, 2.01) vs college graduates] and FFCWS [GEEs: β<high school = 0.62 (0.00, 1.24)]. We found stronger associations for some paternal education categories among White adults (for GEE, βsome college = -1.39 (-2.41, -0.38)], men (βsome college = -1.76 (-3.16, -0.35)] and women [β<high school = 1.77 (0.42, 3.11)].

CONCLUSIONS

These findings suggest that EAA captures epigenetic impacts of paternal education independently of personal SES later in life. Longitudinal studies should explore these associations at different life stages and link them to health outcomes. EAA could be a useful biomarker of SES-associated health and provide important insight into the pathogenesis and prevention of chronic disease.

Aging of the progenitor cells that initiate prostate cancer

Many organs experience a loss of tissue mass and a decline in regenerative capacity during aging. In contrast, the prostate continues to grow in volume. In fact, age is the most important risk factor for prostate cancer. However, the age-related factors that influence the composition, morphology and molecular features of prostate epithelial progenitor cells, the cells-of-origin for prostate cancer, are poorly understood. Here, we review the evidence that prostate luminal progenitor cells are expanded with age. We explore the age-related changes to the microenvironment that may influence prostate epithelial cells and risk of transformation. Finally, we raise a series of questions about models of aging and regulators of prostate aging which need to be addressed. A fundamental understanding of aging in the prostate will yield critical insights into mechanisms that promote the development of age-related prostatic disease.

Epigenetic Age Acceleration Reflects Long-Term Cardiovascular Health

[Figure: see text].

Epigenetic Age in Young African American Adults With Perinatally Acquired HIV

BACKGROUND

Prior studies have measured accelerated aging in people with HIV using a DNA methylation (DNAm)-based biomarker of aging, "epigenetic age," but data are limited in African American (AA) young adults with perinatally acquired HIV infection (PHIV).

METHODS

We performed a cross-sectional study of AA young adults aged 20-35 years with PHIV (N = 31) and seronegative controls (N = 30) using DNAm measured in whole blood and cognitive function measured by the NIH Toolbox. Illumina EPIC array was used to measure DNAm age and accelerated aging markers including epigenetic age acceleration (EAA), as well as extrinsic (EEAA) and intrinsic (IEAA) EAA.

RESULTS

PHIV and controls did not differ by sex (45 vs. 43% male), chronological age (26.2 vs. 28.0 years), or ethnicity. Chronological age and DNAm age were correlated (r = 0.56, P < 0.01). PHIV had a higher mean EAA (2.86 ± 6.5 vs. -2.96 ± 3.9, P < 0.01) and EEAA (4.57 ± 13.0 vs. -4.72 ± 6.0, P < 0.01) than controls; however, IEAA was not different between groups. Among PHIV, EAA and EEAA were higher in those with HIV viral load ≥50 copies/mL than <50 copies/mL (EEA: 8.1 ± 5.2 vs. 0.11 ± 5.5, P = 0 < 0.01 and EEAA: 16.1 ± 10.6 vs. -1.83 ± 9.7, P < 0.01). We observed negative correlations (r = -0.36 to -0.31) between EEAA and executive function, attention, and language scores.

CONCLUSIONS

In conclusion, EAA in blood was observed in AA young adults with PHIV on ART using 2 measures, including EEAA which upweights the contribution of immunosenescent cell types. However, there was no evidence of age acceleration with a measure independent of cell type composition.

DNA methylation of decedent blood samples to estimate the chronological age of human remains

Chronological age estimation may offer valuable investigative leads in human identification cases. Bisulfite pyrosequencing analysis of single CpG sites on five genes (KLF14, ELOVL2, C1orf132, TRIM59, and FHL2) was performed on 264 postmortem blood samples from individuals aged 3 months to 93 years. The goals were to develop age prediction models based on the correlation between the methylation profile and chronological age and to assess the accuracy of the prediction. Linear regression between methylation levels and age at each CpG site revealed that the five markers show a statistically significant correlation with age. The methylation data from a training set of 160 postmortem blood samples were used to develop an age prediction model with a correlation coefficient of 0.65, explaining 73.1% of age variation, with a mean absolute deviation from the chronological age of 7.60 years. The accuracy of the model was evaluated with a test set of 72 samples producing a mean absolute deviation of 7.42 years. The training and test sets were also categorized by specific age groups to assess accuracy and deviation from chronological age. The data for both sets revealed a lower prediction potential as an individual increases in age, particularly for the age categories above 50 years.

Genome-wide identification of age-related CpG sites for age estimation from blood DNA of Han Chinese individuals

Age-related CpG (AR-CpG) sites are currently the most promising molecular markers for forensic age estimation. However, the AR-CpG sites of Han Chinese population remains to be systematically characterized. In this study, we performed genome-wide methylation analyses on 42 whole blood DNA from healthy Han Chinese volunteers (aged from 18 to 62 years) using the Illumina MethylationEPIC BeadChip microarray. As expected, both known and novel AR-CpG sites were identified. Considering the sex difference in aging rate, we then separately selected AR-CpG candidates and built pyrosequencing-based multiple linear regression models for age estimation of males and females. The model constructed from the male sample group (n = 167, aged from 1.50 to 85.71 years) explained 95.22% of variation in age using five AR-CpG sites (chr6:11044864 ELOVL2, chr1:207997068 C1orf132, cg19283806 CCDC102B, cg17740900, and chr10:73740306 CHST3) and yielded a mean absolute error (MAE) of 2.79 years. The model constructed from the female sample group (n = 141, aged from 3.33 to 80.38 years) explained 94.90% of variation in age with six AR-CpG sites (chr6:11044867 ELOVL2, chr1:207997060 C1orf132, chr2:106015757 FHL2, cg26947034, chr16: 67184108 B3GNT9, and chr20:44658203 SLC12A5) and yielded an MAE of 2.53 years. Besides, the estimated age was highly correlated with the actual age (R > 0.97). The robustness of these AR-CpG markers was demonstrated by 10-fold cross-validations. In conclusion, we updated the AR-CpG sites of Han Chinese population and provided two sets of AR-CpG sites for accurate age estimation.

Epigenetics and pulmonary diseases in the horizon of precision medicine: a review

Epigenetic mechanisms represent potential molecular routes which could bridge the gap between genetic background and environmental risk factors contributing to the pathogenesis of pulmonary diseases. In patients with COPD, asthma and pulmonary arterial hypertension (PAH), there is emerging evidence of aberrant epigenetic marks, mainly including DNA methylation and histone modifications which directly mediate reversible modifications to the DNA without affecting the genomic sequence. Post-translational events and microRNAs can be also regulated epigenetically and potentially participate in disease pathogenesis. Thus, novel pathogenic mechanisms and putative biomarkers may be detectable in peripheral blood, sputum, nasal and buccal swabs or lung tissue. Besides, DNA methylation plays an important role during the early phases of fetal development and may be impacted by environmental exposures, ultimately influencing an individual's susceptibility to COPD, asthma and PAH later in life. With the advances in omics platforms and the application of computational biology tools, modelling the epigenetic variability in a network framework, rather than as single molecular defects, provides insights into the possible molecular pathways underlying the pathogenesis of COPD, asthma and PAH. Epigenetic modifications may have clinical applications as noninvasive biomarkers of pulmonary diseases. Moreover, combining molecular assays with network analysis of epigenomic data may aid in clarifying the multistage transition from a "pre-disease" to "disease" state, with the goal of improving primary prevention of lung diseases and its subsequent clinical management.We describe epigenetic mechanisms known to be associated with pulmonary diseases and discuss how network analysis could improve our understanding of lung diseases.

Young women with poor ovarian response exhibit epigenetic age acceleration based on evaluation of white blood cells using a DNA methylation-derived age prediction model

STUDY QUESTION

Is poor ovarian response associated with a change in predicted age based on a DNA methylation-derived age prediction model (the Horvath algorithm) in white blood cells (WBCs) or cumulus cells (CCs)?

SUMMARY ANSWER

In young women, poor ovarian response is associated with epigenetic age acceleration within WBC samples but is not associated with age-related changes in CC.

WHAT IS KNOWN ALREADY

The majority of human tissues follow predictable patterns of methylation which can be assessed throughout a person's lifetime. DNA methylation patterns may serve as informative biomarkers of aging within various tissues. Horvath's 'epigenetic clock', which is a DNA methylation-derived age prediction model, accurately predicts a subject's true chronologic age when applied to WBC but not to CC.

STUDY DESIGN, SIZE, DURATION

A prospective cohort study was carried out involving 175 women undergoing ovarian stimulation between February 2017 and December 2018. Women were grouped according to a poor (≤5 oocytes retrieved) or good (>5 oocytes) response to ovarian stimulation. Those with polycystic ovary syndrome (PCOS) (n = 35) were placed in the good responder group.

PARTICIPANTS/MATERIALS, SETTING, METHODS

DNA methylation patterns from WBC and CC were assessed for infertile patients undergoing ovarian stimulation at a university-affiliated private practice. DNA was isolated from peripheral blood samples and CC. Bisulfite conversion was then performed and a DNA methylation array was utilized to measure DNA methylation levels throughout the genome. Likelihood ratio tests were utilized to assess the relationship between predicted age, chronologic age and ovarian response.

MAIN RESULTS AND THE ROLE OF CHANCE

The Horvath-predicted age for WBC samples was consistent with patients' chronologic age. However, predicted age from analysis of CC was younger than chronologic age. In subgroup analysis of women less than 38 years of age, poor ovarian response was associated with an accelerated predicted age in WBC (P = 0.017). Poor ovarian response did not affect the Horvath-predicted age based on CC samples (P = 0.502). No alternative methylation-based calculation was identified to be predictive of age for CC.

LIMITATIONS, REASONS FOR CAUTION

To date, analyses of CC have failed to identify epigenetic changes that are predictive of the aging process within the ovary. Despite the poor predictive nature of both the Horvath model and the novel methylation-based age prediction model described here, it is possible that our efforts failed to identify appropriate sites which would result in a successful age-prediction model derived from the CC epigenome. Additionally, lower DNA input for CC samples compared to WBC samples was a methodological limitation. We acknowledge that a universally accepted definition of poor ovarian response is lacking. Furthermore, women with PCOS were included and therefore the group of good responders in the current study may not represent a population with entirely normal methylation profiles.

WIDER IMPLICATIONS OF THE FINDINGS

The process of ovarian and CC aging continues to be poorly understood. Women who demonstrate poor ovarian response to stimulation represent a common clinical challenge, so clarifying the exact biological changes that occur within the ovary over time is a worthwhile endeavor. The data from CC support a view that hormonally responsive tissues may possess distinct epigenetic aging patterns when compared with other tissue types. Future studies may be able to determine whether alternative DNA methylation sites can accurately predict chronologic age or ovarian response to stimulation from CC samples. Going forward, associations between epigenetic age acceleration and reproductive and general health consequences must also be clearly defined.

STUDY FUNDING/COMPETING INTEREST(S)

No external funding was obtained for the study and there are no conflicts of interest.

TRIAL REGISTRATION NUMBER

N/A.

Adopting a "Compound" Exposome Approach in Environmental Aging Biomarker Research: A Call to Action for Advancing Racial Health Equity

BACKGROUND

In June 2020, the National Academies of Sciences, Engineering, and Medicine hosted a virtual workshop focused on integrating the science of aging and environmental health research. The concurrent COVID-19 pandemic and national attention on racism exposed shortcomings in the environmental research field's conceptualization and methodological use of race, which have subsequently hindered the ability of research to address racial health disparities. By the workshop's conclusion, the authors deduced that the utility of environmental aging biomarkers-aging biomarkers shown to be specifically influenced by environmental exposures-would be greatly diminished if these biomarkers are developed absent of considerations of broader societal factors-like structural racism-that impinge on racial health equity.

OBJECTIVES

The authors reached a post-workshop consensus recommendation: To advance racial health equity, a "compound" exposome approach should be widely adopted in environmental aging biomarker research. We present this recommendation here.

DISCUSSION

The authors believe that without explicit considerations of racial health equity, people in most need of the benefits afforded by a better understanding of the relationships between exposures and aging will be the least likely to receive them because biomarkers may not encompass cumulative impacts from their unique social and environmental stressors. Employing an exposome approach that allows for more comprehensive exposure-disease pathway characterization across broad domains, including the social exposome and neighborhood factors, is the first step. Exposome-centered study designs must then be supported with efforts aimed at increasing the recruitment and retention of racially diverse study populations and researchers and further "compounded" with strategies directed at improving the use and interpretation of race throughout the publication and dissemination process. This compound exposome approach maximizes the ability of our science to identify environmental aging biomarkers that explicate racial disparities in health and best positions the environmental research community to contribute to the elimination of racial health disparities. https://doi.org/10.1289/EHP8392.

A Meta-Analysis of Brain DNA Methylation Across Sex, Age, and Alzheimer's Disease Points for Accelerated Epigenetic Aging in Neurodegeneration

Alzheimer's disease (AD) is characterized by specific alterations of brain DNA methylation (DNAm) patterns. Age and sex, two major risk factors for AD, are also known to largely affect the epigenetic profiles in brain, but their contribution to AD-associated DNAm changes has been poorly investigated. In this study we considered publicly available DNAm datasets of four brain regions (temporal, frontal, entorhinal cortex, and cerebellum) from healthy adult subjects and AD patients, and performed a meta-analysis to identify sex-, age-, and AD-associated epigenetic profiles. In one of these datasets it was also possible to distinguish 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) profiles. We showed that DNAm differences between males and females tend to be shared between the four brain regions, while aging differently affects cortical regions compared to cerebellum. We found that the proportion of sex-dependent probes whose methylation is modified also during aging is higher than expected, but that differences between males and females tend to be maintained, with only a few probes showing age-by-sex interaction. We did not find significant overlaps between AD- and sex-associated probes, nor disease-by-sex interaction effects. On the contrary, we found that AD-related epigenetic modifications are significantly enriched in probes whose DNAm varies with age and that there is a high concordance between the direction of changes (hyper or hypo-methylation) in aging and AD, supporting accelerated epigenetic aging in the disease. In summary, our results suggest that age-associated DNAm patterns concur to the epigenetic deregulation observed in AD, providing new insights on how advanced age enables neurodegeneration.