Epigenetic age acceleration and mortality risk prediction in U.S. adults.

Background: Epigenetic clocks have emerged as novel measures of biological age and potential predictors of mortality. We aimed to test whether epigenetic age acceleration (EAA) estimated using different epigenetic clocks predict long-term overall, cardiovascular or cancer mortality. Methods: We analyzed data from 2,105 participants to the 1999-2002 National Health and Nutrition Examination Survey aged ≥50 years old who were followed for mortality through 2019. EAAs was calculated from the residuals of Horvath, Hannum, SkinBlood, Pheno, Zhang, Lin, Weidner, Vidal-Bralo and Grim epigenetic clocks regressed on chronological age. Using cox proportional hazards regression, we estimated the hazard ratio (HR) and 95% confidence interval (CI) for the association of EAA (per 5-year) and the DunedinPoAm pace of aging (per 10% increase) with overall, cardiovascular and cancer mortality, adjusting for covariates and white blood cell composition. Results: During a median follow-up of 17.5 years, 998 deaths occurred, including 272 from cardiovascular disease and 209 from cancer. Overall mortality was most significantly predicted by Grim EAA (P < 0.0001; HR: 1.50, 95% CI: 1.32-1.71) followed by Hannum (P = 0.001; HR: 1.16, 95% CI: 1.07-1.27), Pheno (P = 0.001; HR: 1.13, 95% CI: 1.05-1.21), Horvath (P = 0.007; HR: 1.13, 95% CI: 1.04-1.22) and Vidal-Bralo (P = 0.008; HR: 1.13, 95% CI: 1.03-1.23) EAAs. Grim EAA predicted cardiovascular mortality (P < 0.0001; HR: 1.55, 95% CI: 1.29-1.86), whereas Hannum (P = 0.006; HR: 1.24, 95% CI: 1.07-1.44), Horvath (P = 0.02; HR: 1.18, 95% CI: 1.02-1.35) and Grim (P = 0.049; HR: 1.37, 95% CI: 1.00-1.87) EAAs predicted cancer mortality. DunedinPoAm pace of aging was associated with overall (P = 0.003; HR: 1.23, 95% CI: 1.08-1.38) and cardiovascular (P = 0.04; HR: 1.25, 95% CI: 1.01-1.55) mortality. Conclusions: In a U.S. representative sample, Horvath, Hannum, Pheno, Vidal-Bralo and Grim EAA all predicted overall mortality but only Grim EAA predicted cardiovascular mortality and Horvath, Hannum or Grim EAA predicted cancer mortality. Pace of aging predicted overall and cardiovascular mortality.

Parental Divorce in Childhood and the Accelerated Epigenetic Aging for Earlier and Later Cohorts: Role of Mediators of Chronic Depressive Symptoms, Education, Smoking, Obesity, and Own Marital Disruption.

We examine effects of parental divorce on epigenetic aging in later adulthood for two birth cohorts: one born in the early 20th century and the other born in the later 20th century. Using data from the Health and Retirement Study (n = 1,545), we examine the relationship between parental divorce in childhood and accelerated epigenetic aging in older adulthood as indicated by the Dunedin methylation Pace of Aging score. We assess how this relationship is mediated by chronic depressive symptoms, education, lifetime smoking, body mass index (BMI), and an older adult's own divorce. The mean age of the earlier cohort is 85.8 (SD = 3.9) and that of the later cohort is 60.2 (SD = 2.8). We find that parental divorce was related to faster aging in the later-born cohort, and that 56% of this relationship (b = 0.060) was mediated by chronic depressive symptoms (b = 0.013), lower education levels (b = 0.005), and smoking (b = 0.019). For the earlier cohort, there was no effect of parental divorce on epigenetic aging. Parental divorce in childhood may have lasting effects on later-life health, as reflected in the rate of epigenetic aging. However, the effects and mechanisms of this relationship differ across cohorts living in different social environments.

Childhood trauma is linked to epigenetic age deceleration in young adults with previous youth residential care placements.

Background: Early adversity increases the risk for mental and physical disorders as well as premature death. Epigenetic processes, and altered epigenetic aging in particular, might mediate these effects. While the literature that examined links between early adversity and epigenetic aging is growing, results have been heterogeneous.Objective: In the current work, we explored the link between early adversity and epigenetic aging in a sample of formerly out-of-home placed young adults.Method: A total of N = 117 young adults (32% women, age mean = 26.3 years, SD = 3.6 years) with previous youth residential care placements completed the Childhood Trauma Questionnaire (CTQ) and the Life Events Checklist (LEC-R) and provided blood samples for the analysis of DNA methylation using the Illumina Infinium MethylationEPIC BeadChip Microarray. Epigenetic age was estimated using Hovarth's and Hannum's epigenetic clocks. Furthermore, Hovarth's and Hannum's epigenetic age residuals were calculated as a proxy of epigenetic aging by regressing epigenetic age on chronological age. The statistical analysis plan was preregistered (https://osf.io/b9ev8).Results: Childhood trauma (CTQ) was negatively associated with Hannum's epigenetic age residuals, ß = -.23, p = .004 when controlling for sex, BMI, smoking status and proportional white blood cell type estimates. This association was driven by experiences of physical neglect, ß = -.25, p = .001. Lifetime trauma exposure (LEC-R) was not a significant predictor of epigenetic age residuals.Conclusion: Childhood trauma, and physical neglect in particular, was associated with decelerated epigenetic aging in our sample. More studies focusing on formerly institutionalized at-risk populations are needed to better understand which factors affect stress-related adaptations following traumatic experiences.

Growing literature links early adversity to altered epigenetic aging, yet results have been heterogeneous.We assessed childhood and lifetime trauma exposure using the Childhood Trauma Questionnaire and the Life Events Checklist and estimated epigenetic aging by obtaining Horvath's and Hannum's epigenetic age residuals in a sample of formerly out-of-home placed young adults.In this high-risk sample, childhood trauma, physical neglect in particular, but not lifetime trauma was negatively related to epigenetic aging.

Epigenetic Aging Helps Explain Differential Resilience in Older Adults.

Past research suggests that resilience to health hazards increases with age, potentially because less resilient individuals die at earlier ages, leaving behind their more resilient peers. Using lifetime cigarette smoking as a model health hazard, we examined whether accelerated epigenetic aging (indicating differences in the speed of individuals' underlying aging process) helps explain age-related resilience in a nationally representative sample of 3,783 older U.S. adults from the Health and Retirement Study. Results of mediation moderation analyses indicated that participants aged 86 or older showed a weaker association between lifetime cigarette smoking and mortality relative to participants aged 76-85 and a weaker association between smoking and multimorbidity relative to all younger cohorts. This moderation effect was mediated by a reduced association between smoking pack-years and epigenetic aging. This research helps identify subpopulations of particularly resilient individuals and identifies epigenetic aging as a potential mechanism explaining this process. Interventions in younger adults could utilize epigenetic aging estimates to identify the most vulnerable individuals and intervene before adverse health outcomes, such as chronic disease morbidity or mortality, manifest.

Objective Assessments of Smoking and Drinking Outperform Clinical Phenotypes in Predicting Variance in Epigenetic Aging.

The reliability of the associations of the acceleration of epigenetic aging (EA) indices with clinical phenotypes other than for smoking and drinking is poorly understood. Furthermore, the majority of clinical phenotyping studies have been conducted using data from subjects of European ancestry. In order to address these limitations, we conducted clinical, physiologic, and epigenetic assessments of a cohort of 278 middle-aged African American adults and analyzed the associations with the recently described principal-components-trained version of GrimAge (i.e., PC-GrimAge) and with the DunedinPACE (PACE) index using regression analyses. We found that 74% of PC-GrimAge accelerated aging could be predicted by a simple baseline model consisting of age, sex, and methylation-sensitive digital PCR (MSdPCR) assessments of smoking and drinking. The addition of other serological, demographic, and medical history variables or PACE values did not meaningfully improve the prediction, although some variables did significantly improve the model fit. In contrast, clinical variables mapping to cardiometabolic syndrome did independently contribute to the prediction of PACE values beyond the baseline model. The PACE values were poorly correlated with the GrimAge values (r = 0.2), with little overlap in variance explained other than that conveyed by smoking and drinking. The results suggest that EA indices may differ in the clinical information that they provide and may have significant limitations as screening tools to guide patient care.

Current evidence supporting associations of DNA methylation measurements with survivorship burdens in cancer survivors: A scoping review.

INTRODUCTION: Identifying reliable biomarkers that reflect cancer survivorship symptoms remains a challenge for researchers. DNA methylation (DNAm) measurements reflecting epigenetic changes caused by anti-cancer therapy may provide needed insights. Given lack of consensus describing utilization of DNAm data to predict survivorship issues, a review evaluating the current landscape is warranted. OBJECTIVE: Provide an overview of current studies examining associations of DNAm with survivorship burdens in cancer survivors. METHODS: A literature review was conducted including studies if they focused on cohorts of cancer survivors, utilized peripheral blood cell DNAm data, and evaluated the associations of DNAm and survivorship issues. RESULTS: A total of 22 studies were identified, with majority focused on breast (n = 7) or childhood cancer (n = 9) survivors, and half studies included less than 100 patients (n = 11). Survivorship issues evaluated included those related to neurocognition (n = 5), psychiatric health (n = 3), general wellness (n = 9), chronic conditions (n = 5), and treatment specific toxicities (n = 4). Studies evaluated epigenetic age metrics (n = 10) and DNAm levels at individual CpG sites or regions (n = 12) for their associations with survivorship issues in cancer survivors along with relevant confounding factors. Significant associations of measured DNAm in the peripheral blood samples of cancer survivors and survivorship issues were identified. DISCUSSION/CONCLUSION: Studies utilizing epigenetic age metrics and differential methylation analysis demonstrated significant associations of DNAm measurements with survivorship burdens. Associations were observed encompassing diverse survivorship outcomes and timeframes relative to anti-cancer therapy initiation. These findings underscore the potential of these measurements as useful biomarkers in survivorship care and research.

Improvement in Epigenetic Aging Clock Induced by BioBran Containing Rice Kefiran in Relation to Various Biomarkers: A Pilot Study.

Many lifestyle-related diseases such as cancer, dementia, myocardial infarction, and stroke are known to be caused by aging, and the WHO's ICD-11 (International Classification of Diseases, 11th edition) created the code "aging-related" in 2022. In other words, aging is irreversible but aging-related diseases are reversible, so taking measures to treat them is important for health longevity and preventing other diseases. Therefore, in this study, we used BioBran containing rice kefiran as an approach to improve aging. Rice kefiran has been reported to improve the intestinal microflora, regulate the intestines, and have anti-aging effects. BioBran has also been reported to have antioxidant effects and improve liver function, and human studies have shown that it affects the diversity of the intestinal microbiota. Quantitative measures of aging that correlate with disease risk are now available through the epigenetic clock test, which examines the entire gene sequence and determines biological age based on the methylation level. Horvath's Clock is the best known of many epigenetic clock tests and was published by Steve Horvath in 2013. In this study, we examine the effect of using Horvath's Clock to improve aging and report on the results, which show a certain effect.

Epigenetic and biological age acceleration in children with atopic dermatitis.

Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease resulting from the complex interplay of genetic and environmental factors, meriting exploration using temporally dynamic biomarkers. DNA methylation-based algorithms have been trained to accurately estimate biological age, and deviation of predicted age from true age (epigenetic age acceleration) has been implicated in several inflammatory diseases, including asthma. Objective: We sought to determine the role of epigenetic and biological aging, telomere length, and epigenetically inferred abundance of 7 inflammatory biomarkers in AD. Methods: We performed DNA methylation-based analyses in a pediatric AD cohort (n = 24, mean ± standard deviation [SD] age 2.56 ± 0.28 years) and age-matched healthy subjects (n = 24, age 2.09 [0.15] years) derived from blood using 5 validated algorithms that assess epigenetic age (Horvath, Skin&Blood) and biological age (PhenoAge, GrimAge), telomere length (TelomereLength), and inflammatory biomarker levels. Results: Epigenetic and biological age, but not telomere length, were accelerated in AD patients for 4 algorithms: Horvath (+0.88 years; 95% confidence interval [CI], 0.33 to 1.4; P = 2.3 × 10-3), Skin&Blood (+0.95 years; 95% CI, 0.67 to 1.2; P = 1.8 × 10-8), PhenoAge (+8.2 years; 95% CI, 3.4 to 13.0; P = 1.3 × 10-3), and GrimAge (+1.8 years 95% CI, 0.22 to 3.3; P = .026). Moreover, patients had increased levels of ß2 microglobulin (+47,584.4 ng/mL; P = .029), plasminogen activation inhibitor 1 (+3,432.9 ng/mL; P = 1.1 × 10-5), and cystatin C (+31,691 ng/mL; P = 4.0 × 10-5), while levels of tissue inhibitor metalloproteinase 1 (-370.7 ng/mL; P = 7.5 × 10-4) were decreased compared to healthy subjects. Conclusion: DNA methylation changes associated with epigenetic and biological aging, and inflammatory proteins appear early in life in pediatric AD and may be relevant clinical biomarkers of pathophysiology.

Characterization of the genetic determinants of context-specific DNA methylation in primary monocytes.

To better understand inter-individual variation in sensitivity of DNA methylation (DNAm) to immune activity, we characterized effects of inflammatory stimuli on primary monocyte DNAm (n = 190). We find that monocyte DNAm is site-dependently sensitive to lipopolysaccharide (LPS), with LPS-induced demethylation occurring following hydroxymethylation. We identify 7,359 high-confidence immune-modulated CpGs (imCpGs) that differ in genomic localization and transcription factor usage according to whether they represent a gain or loss in DNAm. Demethylated imCpGs are profoundly enriched for enhancers and colocalize to genes enriched for disease associations, especially cancer. DNAm is age associated, and we find that 24-h LPS exposure triggers approximately 6 months of gain in epigenetic age, directly linking epigenetic aging with innate immune activity. By integrating LPS-induced changes in DNAm with genetic variation, we identify 234 imCpGs under local genetic control. Exploring shared causal loci between LPS-induced DNAm responses and human disease traits highlights examples of disease-associated loci that modulate imCpG formation.

Diet Quality and Epigenetic Aging in the Women's Health Initiative.

BACKGROUND: Higher diet quality scores are associated with a lower risk for many chronic diseases and all-cause mortality; however, it is unclear if diet quality is associated with aging biology. OBJECTIVE: This study aimed to examine the association between diet quality and a measure of biological aging known as epigenetic aging. DESIGN: A cross-sectional data analysis was used to examine the association between three diet quality scores based on self-reported food frequency questionnaire data and five measures of epigenetic aging based on DNA methylation (DNAm) data from peripheral blood. PARTICIPANTS/SETTING: This study included 4,500 postmenopausal women recruited from multiple sites across the United States (1993-98), aged 50 to 79 years, with food frequency questionnaire and DNAm data available from the Women's Health Initiative baseline visit. MAIN OUTCOME MEASURES: Five established epigenetic aging measures were generated from HumanMethylation450 Beadchip DNAm data, including AgeAccelHannum, AgeAccelHorvath, AgeAccelPheno, AgeAccelGrim, and DunedinPACE. STATISTICAL ANALYSES PERFORMED: Linear mixed models were used to test for associations between three diet quality scores (Healthy Eating Index, Dietary Approaches to Stop Hypertension, and alternate Mediterranean diet scores) and epigenetic aging measures, adjusted for age, race and ethnicity, education, tobacco smoking, physical activity, Women's Health Initiative substudy from which DNAm data were obtained, and DNAm-based estimates of leukocyte proportions. RESULTS: Healthy Eating Index, Dietary Approaches to Stop Hypertension, and alternate Mediterranean diet scores were all inversely associated with AgeAccelPheno, AgeAccelGrim, and DunedinPACE (P < 0.05), with the largest effects with DunedinPACE. A one standard deviation increment in diet quality scores was associated with a decrement (ß ± SE) in DunedinPACE z score of -0.097 ± 0.014 (P = 9.70 x 10-13) for Healthy Eating Index, -0.107 ± 0.014 (P = 1.53 x 10-14) for Dietary Approaches to Stop Hypertension, and -0.068 ± 0.013 (P = 2.31 x 10-07) for the alternate Mediterranean diet. CONCLUSIONS: In postmenopausal women, diet quality scores were inversely associated with DNAm-based measures of biological aging, particularly DunedinPACE.

Accelerated epigenetic age, inflammation, and gene expression in lung: comparisons of smokers and vapers with non-smokers.

BACKGROUND: Cigarette smoking and aging are the main risk factors for pulmonary diseases, including cancer. Epigenetic aging may explain the relationship between smoking, electronic cigarette vaping, and pulmonary health. No study has examined smoking and vaping-related epigenetic aging in relation to lung biomarkers. METHODS: Lung epigenetic aging measured by DNA methylation (mAge) and its acceleration (mAA) was assessed in young (age 21-30) electronic cigarette vapers (EC, n = 14, including 3 never-smoking EC), smokers (SM, n = 16), and non-EC/non-SM (NS, n = 39). We investigated relationships of mAge estimates with chronological age (Horvath-mAge), lifespan/mortality (Grim-mAge), telomere length (TL-mAge), smoking/EC history, urinary biomarkers, lung cytokines, and transcriptome. RESULTS: Compared to NS, EC and SM had significantly older Grim-mAge, shorter TL-mAge, significantly accelerated Grim-mAge and decelerated TL-mAge. Among SM, Grim-mAA was associated with nicotine intake and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL). For EC, Horvath-mAA was significantly correlated with puffs per day. Overall, cytokines (IL-1ß, IL-6, and IL-8) and 759 transcripts (651 unique genes) were significantly associated with Grim-mAA. Grim-mAA-associated genes were highly enriched in immune-related pathways and genes that play a role in the morphology and structures of cells/tissues. CONCLUSIONS: Faster lung mAge for SM is consistent with prior studies of blood. Faster lung mAge for EC compared to NS indicates possible adverse pulmonary effects of EC on biological aging. Our findings support further research, particularly on epigenetic markers, on effects of smoking and vaping on pulmonary health. Given that most EC are former smokers, further study is needed to understand unique effects of electronic cigarettes on biological aging.

Bloom syndrome patients and mice display accelerated epigenetic aging.

Bloom syndrome (BSyn) is an autosomal recessive disorder caused by variants in the BLM gene, which is involved in genome stability. Patients with BSyn present with poor growth, sun sensitivity, mild immunodeficiency, diabetes, and increased risk of cancer, most commonly leukemias. Interestingly, patients with BSyn do not have other signs of premature aging such as early, progressive hair loss and cataracts. We set out to determine epigenetic age in BSyn, which can be a better predictor of health and disease over chronological age. Our results show for the first time that patients with BSyn have evidence of accelerated epigenetic aging across several measures in blood lymphocytes, as compared to carriers. Additionally, homozygous Blm mice exhibit accelerated methylation age in multiple tissues, including brain, blood, kidney, heart, and skin, according to the brain methylation clock. Overall, we find that Bloom syndrome is associated with accelerated epigenetic aging effects in multiple tissues and more generally a strong effect on CpG methylation levels.

Biological age is increased by stress and restored upon recovery.

Aging is classically conceptualized as an ever-increasing trajectory of damage accumulation and loss of function, leading to increases in morbidity and mortality. However, recent in vitro studies have raised the possibility of age reversal. Here, we report that biological age is fluid and exhibits rapid changes in both directions. At epigenetic, transcriptomic, and metabolomic levels, we find that the biological age of young mice is increased by heterochronic parabiosis and restored following surgical detachment. We also identify transient changes in biological age during major surgery, pregnancy, and severe COVID-19 in humans and/or mice. Together, these data show that biological age undergoes a rapid increase in response to diverse forms of stress, which is reversed following recovery from stress. Our study uncovers a new layer of aging dynamics that should be considered in future studies. The elevation of biological age by stress may be a quantifiable and actionable target for future interventions.

Genetic Evidence for Causal Effects of Socioeconomic, Lifestyle, and Cardiometabolic Factors on Epigenetic-Age Acceleration.

GrimAge acceleration (GrimAgeAccel) and PhenoAge acceleration (PhenoAgeAccel) are DNA methylation-based markers of accelerated biological aging, standing out in predicting mortality and age-related cardiometabolic morbidities. Causal risk factors for GrimAgeAccel and PhenoAgeAccel are unclear. In this study, we performed 2-sample univariable and multivariable Mendelian randomization (MR) to investigate causal associations of 19 modifiable socioeconomic, lifestyle, and cardiometabolic factors with GrimAgeAccel and PhenoAgeAccel. Instrument variants representing 19 modifiable factors were extracted from genome-wide association studies (GWASs) with up to 1 million Europeans. Summary statistics for GrimAgeAccel and PhenoAgeAccel were derived from a GWAS of 34 710 Europeans. We identified 12 and 8 factors causally associated with GrimAgeAccel and PhenoAgeAccel, respectively. Smoking was the strongest risk factor (ß [standard error {SE}]: 1.299 [0.107] year) for GrimAgeAccel, followed by higher alcohol intake, higher waist circumference, daytime napping, higher body fat percentage, higher body mass index, higher C-reactive protein, higher triglycerides, childhood obesity, and type 2 diabetes; whereas education was the strongest protective factor (ß [SE]: -1.143 [0.121] year), followed by household income. Furthermore, higher waist circumference (ß [SE]: 0.850 [0.269] year) and education (ß [SE]: -0.718 [0.151] year) were the leading causal risk and protective factors for PhenoAgeAccel, respectively. Sensitivity analyses strengthened the robustness of these causal associations. Multivariable MR analyses further demonstrated independent effects of the strongest risk and protective factors on GrimAgeAccel and PhenoAgeAccel, respectively. In conclusion, our findings provide novel quantitative evidence on modifiable causal risk factors for accelerated epigenetic aging, suggesting promising intervention targets against age-related morbidity and improving healthy longevity.

Mother's childhood adversity is associated with accelerated epigenetic aging in pregnancy and in male newborns.

Background: Adverse childhood experiences (ACEs) are correlated with accelerated epigenetic aging, but it is not clear whether altered epigenetic aging from childhood adversities persists into adulthood and can be transmitted to the next generation. Thus, we tested whether mothers' childhood adversity is associated with accelerated epigenetic aging during pregnancy and in their newborn offspring. Methods: Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC) sub-study, Accessible Resource for Integrated Epigenomic Studies (ARIES). Women provided retrospective self-reports during pregnancy of ACE exposure. DNA methylation was measured in mothers during pregnancy and cord blood at birth. Estimates of epigenetic age acceleration were calculated using Principal Components of Horvath, Hannum skin & blood, GrimAge, PhenoAge, and DunedinPACE epigenetic clocks for mothers; and the Knight and Bohlin cord blood clocks for newborns. Associations between a cumulative maternal ACE score and epigenetic age acceleration were estimated using linear regression models, adjusting for maternal age at pregnancy, smoking during pregnancy, education, and pre-pregnancy BMI. Models for offspring were stratified by sex and additionally adjusted for gestation age. Results: Mothers' total ACE score was positively associated with accelerated maternal PhenoAge and GrimAge. In newborn offspring, mothers' total ACE score was positively associated with accelerated epigenetic aging in males using the Bohlin clock, but not in females using either epigenetic clock. We found male offsprings' epigenetic age was accelerated in those born to mothers exposed to neglect using the Knight clock; and parental substance abuse using the Bohlin clock. Conclusion: Our results show that mothers' ACE exposure is associated with DNAm age acceleration in male offspring, supporting the notion that DNAm age could be a marker of intergenerational biological embedding of mothers' childhood adversity. This is consistent with findings on vulnerability of male fetuses to environmental insults.

Impact of age, antiretroviral therapy, and cancer on epigenetic aging in people living with HIV.

BACKGROUND: Premature aging has been identified as a global risk factor for cancer. Causes of premature aging are multifactorial, including inflammation, infection, chronic stress, and lifestyle factors. METHOD: We evaluated whether premature aging in people living with HIV (PLWH) was associated with antiretroviral therapy (ART) or the diagnosis of cancer. We used well-established DNA methylation patterns to assess premature aging, using Horvath et al., in individuals with HIV located in Cleveland, Ohio and compared these to standardized datasets of US historical blood samples. Some of the PLWH developed cancer over time. RESULTS: We found that DNA methylation analysis identified accelerated aging in PLWH whereas ART therapy mitigated the advancement of DNA methylation age. A variety of cancers were observed in this population, but a cancer diagnosis was not significantly associated with more advanced DNA methylation age. CONCLUSION: We find that the age acceleration detected in PLWH is mitigated by ART therapy and is not further accelerated by a diagnosis of cancer.

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

BACKGROUND: Few studies have examined epigenetic age acceleration (AA), the difference between DNA methylation (DNAm) predicted age and chronological age, in relation to somatic genomic features in paired cancer and normal tissue, with less work done in non-European populations. In this study, we aimed to examine DNAm age and its associations with breast cancer risk factors, subtypes, somatic genomic profiles including mutation and copy number alterations and other aging markers in breast tissue of Chinese breast cancer (BC) patients from Hong Kong. METHODS: We performed genome-wide DNA methylation profiling of 196 tumor and 188 paired adjacent normal tissue collected from Chinese BC patients in Hong Kong (HKBC) using Illumina MethylationEPIC array. The DNAm age was calculated using Horvath's pan-tissue clock model. Somatic genomic features were based on data from RNA sequencing (RNASeq), whole-exome sequencing (WES), and whole-genome sequencing (WGS). Pearson's correlation (r), Kruskal-Wallis test, and regression models were used to estimate associations of DNAm AA with somatic features and breast cancer risk factors. RESULTS: DNAm age showed a stronger correlation with chronological age in normal (Pearson r = 0.78, P < 2.2e-16) than in tumor tissue (Pearson r = 0.31, P = 7.8e-06). Although overall DNAm age or AA did not vary significantly by tissue within the same individual, luminal A tumors exhibited increased DNAm AA (P = 0.004) while HER2-enriched/basal-like tumors exhibited markedly lower DNAm AA (P = < .0001) compared with paired normal tissue. Consistent with the subtype association, tumor DNAm AA was positively correlated with ESR1 (Pearson r = 0.39, P = 6.3e-06) and PGR (Pearson r = 0.36, P = 2.4e-05) gene expression. In line with this, we found that increasing DNAm AA was associated with higher body mass index (P = 0.039) and earlier age at menarche (P = 0.035), factors that are related to cumulative exposure to estrogen. In contrast, variables indicating extensive genomic instability, such as TP53 somatic mutations, high tumor mutation/copy number alteration burden, and homologous repair deficiency were associated with lower DNAm AA. CONCLUSIONS: Our findings provide additional insights into the complexity of breast tissue aging that is associated with the interaction of hormonal, genomic, and epigenetic mechanisms in an East Asian population.

Epigenetic age acceleration correlates with BMI in young adults.

INTRODUCTION: Obesity increases the risk of Type 2 diabetes, cardiovascular disease, several types of cancer, and other age-related disorders. Among older adults, obesity is also related to epigenetic age, typically measured with DNA methylation (DNAm). Because less is known about obesity and epigenetic aging earlier in the lifespan, this study examined the relationship between obesity and DNAm in young adulthood and whether these relationships vary by sex. METHODS: A cross-sectional community sample of 290 healthy young adults (mean age 27.39 years, 60% female; 80% African American, 18% White) had their BMI and waist circumference measured. Four epigenetic age estimators were derived from salivary DNA: Hannum DNAm, Horvath DNAm, Phenoage DNAm, and GrimAge DNAm. Sociodemographic covariates included age, sex, race, parental education, and income-to-needs ratio. RESULTS: After adjusting for covariates, higher BMI and waist were associated with higher DNAm PhenoAge in both sexes, with a stronger effect on BMI in males (ß = 0.35, p < .001) compared to females (ß = 0.13, p = .002). Higher waist, but not BMI, was associated with higher Horvath DNA methylation age. Both BMI and waist circumference were associated with higher Hannum DNAm age in men but not in women. Neither BMI nor waist circumference were related to GrimAge. DISCUSSION: This study extends prior research by linking obesity with accelerated epigenetic aging in young adulthood, replicating the associations across two measures of obesity and four indices of salivary epigenetic aging. The results add to evidence that higher BMI accelerates aging early in the lifespan.

Adolescent peer struggles predict accelerated epigenetic aging in midlife.

This study examined struggles to establish autonomy and relatedness with peers in adolescence and early adulthood as predictors of advanced epigenetic aging assessed at age 30. Participants (N = 154; 67 male and 87 female) were observed repeatedly, along with close friends and romantic partners, from ages 13 through 29. Observed difficulty establishing close friendships characterized by mutual autonomy and relatedness from ages 13 to 18, an interview-assessed attachment state of mind lacking autonomy and valuing of attachment at 24, and self-reported difficulties in social integration across adolescence and adulthood were all linked to greater epigenetic age at 30, after accounting for chronological age, gender, race, and income. Analyses assessing the unique and combined effects of these factors, along with lifetime history of cigarette smoking, indicated that each of these factors, except for adult social integration, contributed uniquely to explaining epigenetic age acceleration. Results are interpreted as evidence that the adolescent preoccupation with peer relationships may be highly functional given the relevance of such relationships to long-term physical outcomes.

The role of adolescent lifestyle habits in biological aging: A prospective twin study.

Background: Adolescence is a stage of fast growth and development. Exposures during puberty can have long-term effects on health in later life. This study aims to investigate the role of adolescent lifestyle in biological aging. Methods: The study participants originated from the longitudinal FinnTwin12 study (n = 5114). Adolescent lifestyle-related factors, including body mass index (BMI), leisure-time physical activity, smoking, and alcohol use, were based on self-reports and measured at ages 12, 14, and 17 years. For a subsample, blood-based DNA methylation (DNAm) was used to assess biological aging with six epigenetic aging measures in young adulthood (21-25 years, n = 824). A latent class analysis was conducted to identify patterns of lifestyle behaviors in adolescence, and differences between the subgroups in later biological aging were studied. Genetic and environmental influences on biological aging shared with lifestyle behavior patterns were estimated using quantitative genetic modeling. Results: We identified five subgroups of participants with different adolescent lifestyle behavior patterns. When DNAm GrimAge, DunedinPoAm, and DunedinPACE estimators were used, the class with the unhealthiest lifestyle and the class of participants with high BMI were biologically older than the classes with healthier lifestyle habits. The differences in lifestyle-related factors were maintained into young adulthood. Most of the variation in biological aging shared with adolescent lifestyle was explained by common genetic factors. Conclusions: These findings suggest that an unhealthy lifestyle during pubertal years is associated with accelerated biological aging in young adulthood. Genetic pleiotropy may largely explain the observed associations. Funding: This work was supported by the Academy of Finland (213506, 265240, 263278, 312073 to J.K., 297908 to M.O. and 341750, 346509 to E.S.), EC FP5 GenomEUtwin (J.K.), National Institutes of Health/National Heart, Lung, and Blood Institute (grant HL104125), EC MC ITN Project EPITRAIN (J.K. and M.O.), the University of Helsinki Research Funds (M.O.), Sigrid Juselius Foundation (J.K. and M.O.), Yrjö Jahnsson Foundation (6868), Juho Vainio Foundation (E.S.) and Päivikki and Sakari Sohlberg foundation (E.S.).

For most animals, events that occur early in life can have a lasting impact on individuals' health. In humans, adolescence is a particularly vulnerable time when rapid growth and development collide with growing independence and experimentation. An unhealthy lifestyle during this period of rapid cell growth can contribute to later health problems like heart disease, lung disease, and premature death. This is due partly to accelerated biological aging, where the body deteriorates faster than what would be expected for an individual's chronological age. One way to track the effects of lifestyle on biological aging is by measuring epigenetic changes. Epigenetic changes consist on adding or removing chemical 'tags' on genes. These tags can switch the genes on or off without changing their sequences. Scientists can measure certain epigenetic changes by measuring the levels of methylated DNA ­ DNA with a chemical 'tag' known as a methyl group ­ in blood samples. Several algorithms ­ known as 'epigenetic clocks' ­ are available that estimate how fast an individual is aging biologically based on DNA methylation. Kankaanpää et al. show that unhealthy lifestyles during adolescence may lead to accelerated aging in early adulthood. For their analysis, Kankaanpää et al. used data on the levels of DNA methylation in blood samples from 824 twins between 21 and 25 years old. The twins were participants in the FinnTwin12 study and had completed a survey about their lifestyles at ages 12, 14, and 17. Kankaanpää et al. classified individuals into five groups depending on their lifestyles. The first three groups, which included most of the twins, contained individuals that led relatively healthy lives. The fourth group contained individuals with a higher body mass index based on their height and weight. Finally, the last group included individuals with unhealthy lifestyles who binge drank, smoked and did not exercise. After estimating the biological ages for all of the participants, Kankaanpää et al. found that both the individuals with higher body mass indices and those in the group with unhealthy lifestyles aged faster than those who reported healthier lifestyles. However, the results varied depending on which epigenetic clock Kankaanpää et al. used to measure biological aging: clocks that had been developed earlier showed fewer differences in aging between groups; while newer clocks consistently found that individuals in the higher body mass index and unhealthy groups were older. Kankaanpää et al. also showed that shared genetic factors explained both unhealthy lifestyles and accelerated biological aging. The experiments performed by Kankaanpää et al. provide new insights into the vital role of an individual's genetics in unhealthy lifestyles and cellular aging. These insights might help scientists identify at risk individuals early in life and try to prevent accelerated aging.