Epigenetic Skin Aging and Its Reversal to Improve Skin Longevity across Ethnicities and Phototypes Using a Dihydromyricetin-Containing Serum: Results from a Prospective, Single-Cohort Study.

Gestational Epigenetics and Risk of Childhood Leukemia

BackgroundWork-related stress is a well-established contributor to mental health decline, particularly in the context of burnout, a state of prolonged exhaustion. Epigenetic clocks, which estimate biological age based on DNA methylation (DNAm) patterns, have been proposed as potential biomarkers of chronic stress and its impact on biological aging and health. However, their role in mediating the relationship between work-related stress, physiological stress markers, and burnout remains unclear.MethodsHere, we analyzed DNAm data from 296 employed individuals (nfemale = 202; Mage = 45.4; SDage = 11.3; rangeage = 19.5–67.1) from the longitudinally assessed cohort of the Dresden Burnout Study to investigate whether epigenetic aging mediates the relationship between work-related stress (effort–reward imbalance), hair glucocorticoids (cortisol, cortisone), and burnout symptoms. We examined four epigenetic clocks (DNAm Skin&Blood Age, DNAm PhenoAge, DNAm GrimAge, and DNAm GrimAge2) at baseline and follow-up (one year later). Additional mediation analyses were conducted for depressive symptoms to distinguish their potential effects from those specifically associated with burnout symptoms.ResultsAs expected, work-related stress at baseline significantly predicted burnout (β = .47, p < .001) and depressive symptoms (β = .32, p < .001) at follow-up. However, epigenetic aging did not mediate these relationships, neither cross-sectionally (indirect effects of epigenetic age acceleration [EAA]: ßburnout = [−.0008, −.00001]) nor longitudinally (indirect effects of changes in raw clock estimates: ßburnout = [−.002, .007]). Furthermore, work-related stress and hair glucocorticoids were not significantly associated with any epigenetic age markers (all p values > .117), and both EAA and changes in epigenetic aging over time were unrelated to burnout or depressive symptoms (all p values > .190). Sensitivity analyses adjusting for blood cell composition and technical variance confirmed these findings.ConclusionsConsequently, our results do not support the hypothesis that epigenetic aging serves as a biological mechanism linking work-related stress or biological stress markers to burnout symptoms. While work-related stress significantly predicts burnout and depressive symptoms, its association does not appear to be driven by epigenetic aging pathways in a low to moderately burdened population. These findings underscore the need for longer follow-up studies to explore alternative biological and psychosocial pathways that shape the long-term consequences of work-related stress on mental health.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13148-025-01968-z.

Chronic arsenic exposure is a global health hazard significantly associated with the development of deleterious cutaneous changes and increased keratinocyte cancer risk. Although arsenic exposure is associated with broad-scale cellular and molecular changes, gaps exist in understanding how these changes impact the skin and facilitate malignant transformation. Recently developed epigenetic "clocks" can accurately predict chronological, biological and mitotic age, as well as telomere length, on the basis of tissue DNA methylation state. Deviations of predicted from expected age (epigenetic age dysregulation) have been associated with numerous complex diseases, increased all-cause mortality and higher cancer risk. We investigated the ability of these algorithms to detect molecular changes associated with chronic arsenic exposure in the context of associated skin lesions. To accomplish this, we utilized a multi-algorithmic approach incorporating seven "clocks" (Horvath, Skin&Blood, PhenoAge, PCPhenoAge, GrimAge, DNAmTL and epiTOC2) to analyze peripheral blood of pediatric and adult cohorts of arsenic-exposed (n = 84) and arsenic-naïve (n = 33) individuals, among whom n = 18 were affected by skin lesions. Arsenic-exposed adults with skin lesions exhibited accelerated epigenetic (Skin&Blood: + 7.0years [95% CI 3.7; 10.2], q = 6.8 × 10-4), biological (PhenoAge: + 5.8years [95% CI 0.7; 11.0], q = 7.4 × 10-2, p = 2.8 × 10-2) and mitotic age (epiTOC2: + 19.7 annual cell divisions [95% CI 1.8; 37.7], q = 7.4 × 10-2, p = 3.2 × 10-2) compared to healthy arsenic-naïve individuals; and accelerated epigenetic age (Skin&Blood: + 2.8years [95% CI 0.2; 5.3], q = 2.4 × 10-1, p = 3.4 × 10-2) compared to lesion-free arsenic-exposed individuals. Moreover, lesion-free exposed adults exhibited accelerated Skin&Blood age (+ 4.2 [95% CI 1.3; 7.1], q = 3.8 × 10-2) compared to their arsenic-naïve counterparts. Compared to the pediatric group, arsenic-exposed adults exhibited accelerated epigenetic (+ 3.1 to 4.4years (95% CI 1.2; 6.4], q = 2.4 × 10-4-3.1 × 10-3), biological (+ 7.4 to 7.8years [95% CI 3.0; 12.1] q = 1.6 × 10-3-2.8 × 10-3) and mitotic age (+ 50.0 annual cell divisions [95% CI 15.6; 84.5], q = 7.8 × 10-3), as well as shortened telomere length (- 0.23 kilobases [95% CI - 0.13; - 0.33], q = 2.4 × 10-4), across all seven algorithms. We demonstrate that lifetime arsenic exposure and presence of arsenic-associated skin lesions are associated with accelerated epigenetic, biological and mitotic age, and shortened telomere length, reflecting altered immune signaling and genomic regulation. Our findings highlight the usefulness of DNA methylation-based algorithms in identifying deleterious molecular changes associated with chronic exposure to the heavy metal, serving as potential prognosticators of arsenic-induced cutaneous malignancy.

Background Facial appearance is regarded as a typical index of aging. However, people of the same age do not necessarily show the same aging in terms of their facial appearance. There is thus a need for an easy-to-understand indicator representing visible facial skin aging in comparison with that of individuals of a similar age. Objectives The purpose of this study was to develop a simple and accurate index of skin to understand the degree of facial skin aging. Methods Facial skin images were taken with two simple and convenient facial imaging devices (Magic Scan, Magic Ring) in 110 Asian women aged 20 - 60 years, and texture, pores, wrinkles, and dullness (skin unevenness) were quantified as parameters of visual skin aging. Regression analysis was performed on each skin aging parameter and age, and the variation of change in skin aging parameters over time for each subject was calculated. The ratio of each measured skin aging parameter to the mean variation of that same parameter among individuals of the same age as the subject and that ratio was converted into a delta (Δ) age value. Skin age for each skin aging parameter was then calculated by adding or subtracting the Δ skin age to the subject’s chronological age. The average skin age for all four parameters was defined as the overall facial skin age (Skin Age Index). The Skin Age Index was then compared to the results of visual grading of facial skin aging. We also determined the correlation between Skin Age Indexes determined using Magic Scan or Magic Ring. Furthermore, Galactomyces Ferment Filtrate (GFF, Pitera) containing anti-aging skin care products’ treatment efficacy was performed on 21 healthy Asian women to determine the change in skin age. Results Determined Skin Age Index, together with all visible skin aging parameters of texture, pores, wrinkles, and dullness, were highly correlated with actual age. Notably, a high correlation was also observed between visually evaluated comprehensive facial skin aging and Skin Age Index (r = 0.6801 with Magic Scan, r = 0.5668 with Magic Ring). This showed that the degree of skin aging and the apparent skin aging were approximate. The Skin Age Indexes obtained using the two different facial skin imaging devices showed a high correlation (r = 0.8295), suggesting the possibility of calibrating skin age using different image measurement devices. The three GFF-formulated anti-aging skin care products achieved improvements in texture, pores, and wrinkles, and resulted in a skin age that was 5.92 years younger after 1 week of treatment. Conclusions From this study, a method for measuring facial skin age was developed. This Skin Age Index showed an excellent correlation with the subjectively evaluated visible facial skin aging. Furthermore, this Skin Age Index has been shown to be a useful indicator of the effectiveness of applying anti-aging skin care products.

DNA methylation patterns change with age and can be used to derive an estimate of “epigenetic age,” an indicator of biological age. Several studies have shown associations of posttraumatic stress disorder (PTSD) with worse somatic health and early mortality, raising the possibility of accelerated biological aging. This study examined associations between estimated epigenetic age and various variables in 160 male combat-exposed war veterans with (n = 79) and without PTSD (n = 81). DNA methylation was assessed in leukocyte genomic DNA using the Illumina 450K DNA methylation arrays. Epigenetic age was estimated using Horvath’s epigenetic clock algorithm and Δage (epigenetic age-chronological age) was calculated. In veterans with PTSD (Δage = 3.2), Δage was on average lower compared to those without PTSD (Δage = 5.0; p = 0.02; Cohen’s d = 0.42). This between-group difference was not explained by race/ethnicity, lifestyle factors or childhood trauma. Antidepressant use, however, explained part of the association. In the PTSD positive group, telomerase activity was negatively related to Δage (β = –0.35; p = 0.007). In conclusion, veterans with PTSD had significantly lower epigenetic age profiles than those without PTSD. Further, current antidepressant use and higher telomerase activity were related to relatively less epigenetic aging in veterans with PTSD, speculative of a mechanistic pathway that might attenuate biological aging-related processes in the context of PTSD.

Background and Aims Chronic kidney disease (CKD) shares important features of a dysregulated ageing process with other common “burden of lifestyle” diseases, which aggregates into the diseasome of ageing. Typically, this is hallmarked by an acceleration of epigenetic (DNA methylation-based) clocks. It remains to be determined if current therapeutic interventions, such as renal transplantation or dialysis, can slow this clock, and thus the rate of biological ageing, in CKD. We therefore assessed the rate of biological ageing in CKD patients and whether these therapies impact on it, by measuring epigenetic age before and 1 year after treatment. Methods Whole blood samples were taken from CKD 5 patients at baseline and 1 year after renal transplantation (n=12) or dialysis (n=11; peritoneal dialysis n=7, haemodialysis n=4) as well as from age and sex-matched population-based controls (n=24). DNA methylation was measured using the Illumina Infinium Human Methylation 450K BeadChip and epigenetic age was calculated using three independent DNA methylation clocks: the Horvath, Hannum, and PhenoAge clocks. Additionally, a novel composite clock incorporating these three clocks was evaluated. We then calculated the age acceleration (difference between epigenetic and chronological age) for each clock and compared average age acceleration between groups and across time points. Results Incident dialysis patients displayed accelerated ageing versus chronologically age-matched controls (p&amp;lt;0.001). We observed a PhenoAge age acceleration difference in both the transplant (8.5 years, p=0.001) and dialysis (9.7 years, p&amp;lt;0.001) groups at baseline compared to control. After 1 year, we also observed a decrease of the age acceleration in the transplant group (mean reduced by 4.4 years, p=0.016), but not in the dialysis group (mean reduced by 0.7 years, p=0.668). Conclusion CKD 5 patients display an increased biological (i.e. epigenetic) age. This age acceleration is mitigated one year after renal transplantation, but not in patients undergoing dialysis. Neither therapy reverses high biological age.

Objective: Atherosclerosis, an aging-related disease, may begin developing in childhood. Epigenetic age is known to predict biological aging accurately, and epigenetic gestational age can predict biological maturity at birth. However, the association of biological aging at birth with atherosclerosis in later life remains unknown. We aim to examine the association of epigenetic gestational age with subclinical measures of atherosclerosis at ages 11 to 24 and their changes over time. Methods: In the Southern California Children’s Health Study, DNA methylation from newborn bloodspots of 242 participants was analyzed using the Infinium 450K array. We calculated epigenetic gestational ages with the Knight and Bohlin algorithms. Intrinsic Epigenetic Gestational Age Deceleration (IEGAD), indicating developmental immaturity at birth, was derived by regressing epigenetic age on clinical gestational age, adjusted for cell composition. Subclinical measures of atherosclerosis, including carotid intima-media thickness (CIMT) and carotid distensibility, were obtained from ultrasound images from all participants in childhood (mean age: 11.3 years, SD: 0.6) in 2007, and repeatedly obtained from a subset of 54 participants again in adulthood (mean age: 24.2 years, SD: 1.6) between 2019 and 2022. Associations between each IEGAD and subclinical atherosclerosis measures, including their changes over time, were evaluated using linear regression, adjusting for sex, race, birthweight, age and body mass index at time of ultrasound, maternal age at delivery, and maternal pregnancy complications. Results: Knight IEGAD (mean: -0.05, SD = 1.1) and Bohlin IEGAD (mean: -0.03, SD=0.78) was moderately correlated (Pearson r = 0.67, P&lt;0.001). Each week increase in Bohlin EEGAD was associated with higher adult CIMT (β = 34.9 µm, 95% CI: 1.63, 68.2) and with more CIMT thickening from childhood to adulthood (β = 2.2 µm/year, 95% CI: 0.05, 4.36). Similarly, each week increase in Knight IEGAD was associated with reduced arterial elasticity, as measured by lower carotid distensibility, in both childhood (β = -3.22, 95% CI: -0.78, -5.67) units (10 −6 ×m 2 /Newtons) and adulthood (β = -1.99, 95% CI: -0.36, 4.34), and an annual reduction of 0.40 (-0.14, 0.94) unit/year from childhood to adulthood. Conclusion: Developmental immaturity at birth, as indicated by epigenetic gestational age, is associated with adverse subclinical atherosclerosis markers from childhood to adulthood.

DNA methylation (DNAm) plays a pivotal role in regulating gene expression and tissue function in the skin, which exhibits a high degree of responsiveness to environmental and lifestyle factors. These factors are believed to contribute to epigenetic drift, a hallmark of aging marked by increased methylation variability and changes in regulatory regions. While epigenetic clocks have advanced our understanding of skin aging, the effects of many modifiable factors on the skin methylome remain largely unknown. We analyzed DNAm data from 851 participants in a population-based cohort and comprehensive phenotyping of 326 lifestyle, physiological, and pharmacological factors. The DNAm age was estimated using a published skin-specific epigenetic clock, and associations with individual factors were tested using regression models. Epigenome-wide association studies have identified differentially methylated positions linked to significant factors, with further analyses examining their genomic context. The broader relevance of these findings was assessed using other established non-skin-specific epigenetic clocks and phenotypic skin aging measures. Our analysis identified 20 factors associated with decelerated and 17 with accelerated DNAm age in human skin, reflecting both positive and negative associations with epigenetic aging. We observed that factors associated with DNAm age acceleration tended to coincide with reduced methylome variance, a feature of epigenetic drift, while factors associated with DNAm age deceleration were mapped to methylation differences in transcription elongation regions, supporting transcriptional integrity. Intervention analyses showed that compounds, such as dihydromyricetin and aspirin, are associated with methylation patterns consistent with decelerated epigenetic aging. Several associations were validated in an independent cohort and were consistent across both skin-specific and general epigenetic clocks, suggesting broader relevance of these findings. These findings suggest that both environmental exposures and certain interventions are associated with variations in the epigenetic trajectory of skin aging. The identified modifiable factors associated with DNAm age and skin phenotypes generate testable hypotheses regarding potential determinants of skin longevity. Longitudinal studies and interventional study designs will be needed to evaluate causality.

Chronological age is a common and non-modifiable factor for chronic disease, but does not fully explain age-related changes. Biological clocks have been developed to explore biological aging mechanisms. They could help identify protective factors against accelerated aging and associated diseases. We aim to assess the association between reduced epigenetic or inflammatory aging and ideal cardiovascular health or cardiovascular risk. We conducted a cross-sectional analysis of participants from the INSPIRE-T cohort. Cardiovascular health (CVH) was assessed using the Life's Essential 8 score. Cardiovascular risk was assessed using the American Framingham risk score (FRS) and the European Systematic Coronary Risk Evaluation (SCORE2) score. Epigenetic and inflammatory aging was calculated from the residuals from linear regression of biological age (based on five epigenetic clocks and one inflammatory clock) and chronological age. Linear and logistic regression models were used. Better CVH has been associated with slower epigenetic aging, particularly in younger subjects and men. Accelerated epigenetic aging measured by GrimAge was associated with an increase cardiovascular risk (for SCORE2: OR = 1.10 95%CI [1.04; 1.16]). No persistent association was found with the inflammatory clock. Our study reported an association between ideal global CVH with reduced epigenetic aging after adjustment for chronological age and gender. This suggests that epigenetic aging may be modifiable through healthy lifestyle and cardiovascular risk management, although a potential underlying causal relationship remains to be established. Moreover, accelerated epigenetic aging is linked to worsening cardiovascular risk, and could be a new risk factor alongside chronological age.

In this research, we delve into the association between epigenetic aging and idiopathic pulmonary fibrosis (IPF), a debilitating lung disease that progresses over time. Utilizing the Illumina MethylationEPIC array, we assessed DNA methylation levels in donated human lung tissue from patients with IPF, categorizing the disease into mild, moderate, and severe stages based on clinical assessments. We used seven epigenetic clocks to determine age acceleration, which is the discrepancy between biological (epigenetic) and chronological age. Our findings revealed a notable acceleration of biological aging in IPF tissues compared with healthy controls, with four clocks-Horvath's, Hannum's, PhenoAge, and DunedinPACE-showing significant correlations. DunedinPACE, in particular, indicated a more rapid aging process in the more severe regions within the lungs of IPF cases. These results suggest that the biological aging process in IPF is expedited and closely tied to the severity of the disease. The study underscores the potential of DNA methylation as a biomarker for IPF, providing valuable insights into the underlying methylation patterns and the dynamics of epigenetic aging in affected lung tissue. This research supports the broader application of epigenetic clocks in clinical prognosis and highlights the critical role of biological age in the context of medical research and healthcare.NEW & NOTEWORTHY Using epigenetic clocks, we found a notable acceleration of biological aging in IPF tissues, particularly in DunedinPACE, suggesting that the biological aging process in IPF is accelerated and closely related to the severity of the disease. The study also underscores DNA methylation's potential as a biomarker for IPF, as well as the dynamics of epigenetic aging and the need to consider biological age in medical research and healthcare.

Epigenetic clocks assess DNA aging based on DNA methylation. We aimed to study the utility of methylation clocks in understanding the distinct characteristics of sporadic and hereditary neuroendocrine neoplasms (NEN). Epigenetic age and acceleration were calculated based on Horvath multi-tissue, Levine, and Hannum clocks, and compared by genetic predisposition and NEN grading (WHO-defined G1, G2 and G3). Following quality assessment and filtering of the data, 93/96 samples were analyzed. Of them, 41/93, 42/93, and 10/93 were sporadic, multiple endocrine neoplasia 1 (MEN1) and von Hippel-Lindau (VHL)-related NEN, respectively. Forty-eight (48/93) were pancreatic NEN (PanNEN). mDNA age positively correlated with chronological age based on three different clock algorithms, but stronger correlations were found in the hereditary NEN subgroups (Horvath clock, r = 0.65, p < 0.001 for MEN1-relatd NEN, and r = 0.86, p = 0.002 in VHL-related NEN). Epigenetic age acceleration was higher in sporadic NEN compared to hereditary NEN, both based on chronological age-adjusted epigenetic age (Hannum clock, sporadic vs. MEN, p = 0.03; sporadic vs. VHL, p = 0.0002), and based on the difference between epigenetic age and chronological age (Hannum clock, sporadic vs. MEN1, p = 0.009; sporadic vs. VHL, p = 0.0005). Finally, epigenetic age (p = 0.04) and age acceleration (p = 0.03) were higher among adult patients with NEN (G2/3 vs. G1). Epigenetic age and age acceleration analysis demonstrate distinct patterns in sporadic and hereditary NEN, suggesting lower impact of epigenetic alteration or DNA aging in the pathogenesis of hereditary NEN.

BackgroundEstablishing biological aging markers that predict cognitive performance may aid early identification of individuals at risk for accelerated cognitive decline and promote the development of interventions to preserve optimal cognitive function across the lifespan. We investigated two distinct classes of biological aging markers, 1) epigenetic aging, an emerging class of blood‐derived DNA methylation markers that aggregate aging‐related DNA methylation information; and 2) Spatial Patterns of Abnormality for Recognition of Brain Aging (SPARE‐BA), a composite magnetic resonance imaging (MRI) index of brain aging.MethodWe evaluated the cross‐sectional and prospective associations between both classes of aging markers and cognitive performance across a 15‐year follow‐up in the biracial CARDIA cohort of approximately 1,000 middle‐aged adults, using multiple linear regression and logistic regression. We compared the diagnostic performance of both aging markers using receiver operating characteristic (ROC) curve analysis.ResultWe found that accelerated epigenetic aging and brain aging were both cross‐sectionally and prospectively associated with worse cognitive outcomes. Specifically, every 5‐year faster epigenetic/brain aging is on average associated with 9.7% standard deviation (SD) higher in Stroop Test score, 7.7% SD lower in Rey Auditory Verbal Learning Test score, and 10.3% SD lower in Digital Symbol Substitution Test (all false‐discovery‐rate‐adjusted p &lt;0.05). ROC analysis showed that a combined model with both epigenetic aging and brain aging markers optimized discriminability of individuals with lower cognitive performance 5 to 10 years later (area under the ROC curve: 0.70; 95% confident interval: 0.63‐0.77, Figure). Epigenetic and brain aging markers were weakly correlated with one another (Person’s r =0.17) and not statistically significant.ConclusionOur results showcase the significance of novel biological aging markers for cognitive health. Accelerated epigenetic aging and brain aging may capture distinct facets of biological aging and may jointly serve as early indicators of future cognitive decline and inform early interventions to prevent or delay cognitive impairment.

An increase in systemic inflammation (inflammaging) is one of the hallmarks of aging. Epigenetic (DNA methylation) clocks can quantify the degree of biological aging and this can be reversed by lifestyle and pharmacological intervention. We aimed to investigate whether a multi-component nutritional supplement could reduce systemic inflammation and epigenetic age in healthy older adults.We recruited 80 healthy older participants (mean age ± SD: 71.85 ± 6.23; males = 31, females = 49). Blood and saliva were obtained pre and post a 12-week course of a multi-component supplement, containing: Vitamin B3, Vitamin C, Vitamin D, Omega 3 fish oils, Resveratrol, Olive fruit phenols and Astaxanthin. Plasma GDF-15 and C-reactive protein (CRP) concentrations were quantified as markers of biological aging and inflammation respectively. DNA methylation was assessed in whole blood and saliva and used to derive epigenetic age using various clock algorithms.No difference between the epigenetic and chronological ages of participants was observed pre- and post-treatment by the blood-based Horvath or Hannum clocks, or the saliva-based InflammAge clock. However, in those with epigenetic age acceleration of ≥ 2 years at baseline, a significant reduction in epigenetic age (p = 0.015) and epigenetic age acceleration (p = 0.0058) was observed post-treatment using the saliva-based InflammAge clock. No differences were observed pre- and post-treatment in plasma GDF-15 and CRP, though participants with CRP indicative of an elevated cardiovascular disease risk (hsCRP ≥ 3µg/ml), had a reduction in CRP post-supplementation (p = 0.0195).Our data suggest a possible benefit of combined nutritional supplementation in individuals with an accelerated epigenetic age and inflammaging.

Epigenetic age captures both genetic and environmental influences across time on cellular functions and is an indicator of biological aging. Epigenetic age may deviate from chronological age substantially in individuals. Epigenetic age is also tissue-specific. Emerging evidence suggests that female breast tissue ages faster than other parts of the body according to epigenetic age estimation using the "Horvath Clock" model. The Horvath method is based on the DNA methylation of 353 CpG loci on the outdated Illumina microarray platforms. The increasing availability of next-generation sequencing data calls for method development that uses DNA methylation sequencing data to estimate tissue-specific epigenetic age. We developed a new method to estimate breast tissue-specific epigenetic aging using next-generation methylation sequencing data and assessed the difference between epigenetic and chronological ages, known as epigenetic age acceleration (EAA), in different breast tissue types. The Illumina TruSeq Methyl Capture EPIC Sequencing technology was used to obtain DNA methylation profiles of approximately 3.3 million CpG sites in 111 tumor, 48 matched adjacent normal, and 462 normal breast tissue samples. A total of approximately 1.4 million CpG sites remained after quality control. Following the Horvath approach, we used an elastic net penalized regression model to regress chronological age on CpG sites in normal breast tissue and defined a new set of 247 clock CpGs specific to breast tissue with randomly divided training (n = 370) and testing (n = 92) data sets. We estimated breast tissue-specific epigenetic age and EAA in tumor, adjacent, and normal breast tissue. We found that breast tissue-specific epigenetic age was positively correlated with chronological age (r=0.87; P&amp;lt;2.2X10-16). Neither normal nor adjacent normal breast tissue showed a significant EAA. However, tumor breast tissue had a significant and increased EAA (median = 8.0 years; P=6.9X10-9). While triple-negative breast tumors showed no significant EAA, hormone receptive-positive and Her2-positive breast tumors had a significant and increased EAA (median=9.5 and 13.1 years; P=1X10-5 and 0.02, respectively). Results of this new model were compared to similar results using the Horvath Clock model and were found to be qualitatively consistent. Further research is needed to determine whether epigenetic age acceleration in normal breast tissue is predictive of breast cancer risk and how breast cancer risk factors influence the rate of acceleration. Citation Format: James R. Castle, Nan Lin, Jingpeng Liu, Chi Wang, Yunlong Liu, Chunyan He. Estimating breast tissue-specific epigenetic age using next-generation methylation sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 827.

Epigenetic studies, which can reflect biological aging, have shown that measuring DNA methylation (DNAm) levels provides new insights into the biological effects of social environment and socioeconomic position (SEP). This study explores how race, family structure, and SEP (income to poverty ratio) at birth influence youth epigenetic aging at age 15. Data were obtained from the Future of Families and Child Wellbeing Study (FFCWS) cohort, with GrimAge used as a measure of DNAm levels and epigenetic aging. Our analysis included 854 racially and ethnically diverse participants followed from birth to age 15. Structural equation modeling (SEM) examined the relationships among race, SEP at birth, and epigenetic aging at age 15, controlling for sex, ethnicity, and family structure at birth. Findings indicate that race was associated with lower SEP at birth and faster epigenetic aging. Specifically, income to poverty ratio at birth partially mediated the effects of race on accelerated aging by age 15. The effect of income to poverty ratio at birth on DNAm was observed in male but not female youth at age 15. Thus, SEP partially mediated the effect of race on epigenetic aging in male but not female youth. These results suggest that income to poverty ratio at birth partially mediates the effects of race on biological aging into adolescence. These findings highlight the long-term biological impact of early-life poverty in explaining racial disparities in epigenetic aging and underscore the importance of addressing economic inequalities to mitigate these disparities. Policymakers should focus on poverty prevention in Black communities to prevent accelerated biological aging and associated health risks later in life. Interventions aimed at eliminating poverty and addressing racial inequities could have significant long-term benefits for public health. Future research should explore additional factors contributing to epigenetic aging and investigate potential interventions to slow down the aging process. Further studies are needed to understand the mechanisms underlying these associations and to identify effective strategies for mitigating the impact of SEP and racial disparities on biological aging.