Interferon-related inflammaging links epigenetic age acceleration to multimorbidity.

Associations between Epigenetic Age Acceleration and Psychoneurological Symptoms in Sickle Cell Disease

Gestational Epigenetics and Risk of Childhood Leukemia

Background: Obesity is associated with increased risk of cardiovascular and other age-related diseases that may represent accelerated aging. As methylation levels in DNA change with aging, epigenetic age (EA), which integrates whole-genome methylation has emerged as a novel biomarker of aging and has been associated with mortality and age-related morbidity. Epigenetic age acceleration (EAA), is based on the residual value of 353 previously defined methylation markers regressed on chronologic age (CA), and is thus independent of CA. Therefore, we sought to examine the association of obesity and EAA in midlife. Methods: A subset of participants in the CARDIA cohort (n=1200) randomly selected (balanced on race and sex) underwent genome-wide DNA methylation profiling with the Illumina EPIC array from exam year 15 (2000-01 [age 33-45 years]) and 20 (2005-06 [38-50 years] for calculation of EAA. Body mass index (BMI) was measured at Y15 and Y20, respectively. We used linear regression to examine the association of obesity (independent variable) with EAA after adjusting for CA, race, sex, education, study center, smoking status, physical activity, and alcohol intake. Results: Participants were 52% female and 41% black and had mean BMI 28.5±6.2 kg/m 2 at Y15 and 29.2±6.4 kg/m 2 at Y20. At Y15, participants who were obese had 1.04 (0.38) years higher EAA compared to normal BMI participants (p<0.01, Figure) . Similar results were observed at Y20. Results were similar when evaluating the association of BMI continuously with EAA (p<0.05). Conclusions: EAA is a promising molecular biomarker of aging associated with obesity. Changes in DNA methylation may serve as an intermediate phenotype prior to the onset of age-associated pathologies related to obesity.

The DNA methylation of neonatal cord blood can be used to accurately estimate gestational age. This is known as epigenetic gestational age. The greater the difference between epigenetic and chronological gestational age, the greater the association with an inappropriate perinatal fetal environment and development. Maternal vitamin D deficiency is common in Japan. The aim of this study was to investigate the associations between maternal serum vitamin D levels and epigenetic gestational age acceleration at birth in Japan. The data were obtained from the hospital-based birth cohort study conducted at the National Center for Child Health and Development in Tokyo, Japan. Maternal blood was collected in the second trimester to measure the serum vitamin D concentration. Cord blood was collected at birth to measure serum vitamin D and to extract DNA. DNA methylation was assessed using an Illumina methylation EPIC array. Epigenetic gestational age was calculated using the "methylclock" R package. Linear regression analysis was performed to see associations. Maternal serum vitamin D levels in the second trimester were negatively associated with epigenetic gestational age acceleration at birth when calculated by Bohlin's method (regression coefficient [95% CI]: -0.022 [-0.039, -0.005], n = 157), which was still significant after considering infants' sex (-0.022 [-0.039, -0.005]). Cord blood serum vitamin D levels were not associated with epigenetic age acceleration. Maternal age at delivery and birth height were associated in positive and negative ways with epigenetic gestational age acceleration, respectively (0.048 [0.012, 0.085] and -0.075 [-0.146, -0.003]). Maternal vitamin D deficiency was related to an infant's epigenetic gestational age acceleration at birth. These findings suggest that the association between fetal development and maternal vitamin D levels may involve the fetal epigenetic regulation of the fetus.

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.

Background: Epigenetic age, captured by DNA methylation changes, is thought to be more informative with respect to disease risk and progression, than chronological age. A few studies have associated epigenetic age acceleration (EAA), the difference between DNA methylation age (DNAm age) and chronological age, with BC risk and subtypes. However, most of these studies were conducted in Western populations. In this study, we examined EAA in an Asian population, in which BC incidence rate is lower and age at BC onset is younger compared to most Western populations. Methods: We performed genome-wide DNA methylation profiling of 97 tumor and 89 paired distant normal tissue samples collected from BC patients in Hong Kong (HK) using an Illumina MethylationEPIC array. Two independent datasets were used to compare results: The Cancer Genome Atlas (TCGA, n=525 tumor and n=88 adjacent normal) and healthy women from the Komen tissue bank (n=59). DNAm age was calculated using Horvath's model based on 353 CpGs. The significance of EAA was tested using a simple linear regression model. We also used a multivariate regression model to test for equality of slopes (EAA rates) among different BC subtypes or datasets, considering interaction terms between age and subtype/dataset. Results: The average age at BC diagnosis was 58 years old (range: 33-81) and the distribution of the molecular subtype based on PAM50 was 43.0%, 29.1%, and 27.9% for luminal A, luminal B, and HER2-enriched/basal tumors, respectively. As expected, DNAm age showed a stronger correlation with chronological age in normal tissue (r=0.78, p&amp;lt;.0001) than in tumor tissue (r=0.27, p=0.0075). The average EAAs in normal and tumor samples were 9.43 and 6.02 years, respectively. Among different BC subtypes, EAA in normal tissue did not vary by subtypes. However, in tumor samples, luminal patients showed positive EAA (average 10/13 years in luminal A/B, respectively), while HER2-enriched/basal patients showed a negative EAA (average -8 years), although the rate of EAA did not vary significantly by subtype. Analyses on TCGA data produced consistent results. When comparing the rate of DNAm acceleration in normal tissue of HK, TCGA, and Komen, HK patients had a significantly different rate (βHK=0.46) compared to TCGA (βTCGA=0.65, p=0.001) and Komen (βKomen=0.80, p&amp;lt;.0001). Conclusion: Consistent with previous studies, we found that EAA in tumor samples varied across tumor subtypes. We also found that HK BC patients' epigenetic age accelerated at a different rate compared to predominantly white TCGA and Komen women, suggesting a potential racial biological difference. Large studies in other Asian populations are warranted to confirm our findings, which may provide biological insight into racial heterogeneity of BC, especially with regard to age at onset. Citation Format: Hela Koka, Bin Zhu, Shelly Lap Ah Tse, Difei Wang, Maeve Kiely, Jennifer Lyn Guida, Priscilla Lee, Feng Wang, Cherry Wu, Koon Ho Tsang, Wing-cheong Chan, Sze Hong Law, Eric Karlins, Bin Zhu, Amy Hutchinson, Belynda Hicks, Xiaohong R. Yang. DNA methylation age of paired tumor-normal breast tissue in Chinese women with breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 146.

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.

Chronic lymphocytic leukemia (CLL) is a mature B cell neoplasm with a predilection for older individuals. While previous studies have identified epigenetic signatures associated with CLL, whether age-related DNA methylation changes modulate CLL relapse remains elusive. In this study, we examined the association between epigenetic age acceleration and time to CLL relapse in a publicly available dataset. DNA methylation profiling of 35 CLL patients prior to initiating chemoimmunotherapy was performed using the Infinium HumanMethylation450 BeadChip. Four epigenetic age acceleration metrics (intrinsic epigenetic age acceleration [IEAA], extrinsic epigenetic age acceleration [EEAA], PhenoAge acceleration [PhenoAA], and GrimAge acceleration [GrimAA]) were estimated from blood DNA methylation levels. Linear, quantile, and logistic regression and receiver operating characteristic curve analyses were conducted to assess the association between each epigenetic age metric and time to CLL relapse. EEAA (p = 0.011) and PhenoAA (p = 0.046) were negatively and GrimAA (p = 0.040) was positively associated with time to CLL relapse. Simultaneous assessment of EEAA and GrimAA in male patients distinguished patients who relapsed early from patients who relapsed later (p = 0.039). No associations were observed with IEAA. These findings suggest epigenetic age acceleration prior to chemoimmunotherapy initiation is associated with time to CLL relapse. Our results provide novel insight into the association between age-related DNA methylation changes and CLL relapse and may serve has biomarkers for treatment relapse, and potentially, treatment selection.

Physical activity has been extensively associated with epigenetic modifications. However, the potential contribution of DNA methylation patterns to sports injury susceptibility remains largely unexplored, particularly among high-performance athletes. Since methylation regulates genes involved in inflammation, tissue repair, and musculoskeletal function, altered methylation profiles may influence injury risk. Moreover, epigenetic clocks are increasingly used to assess vulnerability to clinical phenotypes, as accelerated epigenetic aging has been linked to various diseases. Here, we studied the DNA methylome of peripheral blood cells in 74 elite female and male soccer players with extensive non-contact injury follow-up. We aimed to explore alterations associated with increased injury risk and to describe the dynamics of epigenetic age acceleration in this group. Although DNA methylomes between players with higher and lower injury risk were overall similar, we identified 1081 differentially methylated CpGs sites that partly affected genes involved in skeletal muscle functions. We also estimated epigenetic age using eight clocks but found no association with injuries. However, male athletes displayed higher epigenetic age acceleration than females. Comparing the methylome of age-accelerated versus decelerated individuals revealed widespread changes across five clocks, strongly biased towards hypomethylation in age-accelerated players. Differential CpGs targeted genes enriched in extracellular matrix, cytoskeletal and collagen-related functions. Overall, this study suggests a link between DNA methylation and non-contact injuries in elite soccer players and shows that epigenetic age acceleration, although unrelated to injuries, is associated with widespread hypomethylation.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-25784-w.

Introduction: Aging has become a global issue and in consequence, the prevalence of many chronic diseases has increased, especially metabolic syndrome (MS) and colorectal cancer (CRC). CRC was the top cancer prevalence in Changhua in the last decade, and the prevalence of MS also increased annually. Diethyl phthalate (DEP) is a common plasticizer frequently used in daily life. DEP may enter human body through inhalation, ingestion, and dermal contact. DEP has a weak estrogen effect. The hazard associated with DEP including skin sensitivity, reproductive hazard, metabolic disease, and cancer. Several studies indicated that DEP can cause MS and cancer through DNA methylation changes. DNA methylation may be able to explain the link between DEP exposure and the related health effects. In addition, epigenetic age can better access human aging. We investigated the effects of DEP on DNA methylation levels and epigenetic age acceleration in relation to MS and the development of CRC in Changhua. Materials and methods: Our study participants were from the participants of Changhua community-integrated screening (CIS), including 61 participants from 2006 to 2014. We used blood cell samples to measured DNA methylation levels by using Illumina Infinium® MethylationEPIC BeadChip. The qualitative and quantitative DEP exposure analyses were measured in serum by UHPLC Q-TOF MS and UPLC-MS/MS, respectively. The health screening results were collected in Changhua CIS. ChAMP package were used for DNA methylation related analyses. Both univariable and multivariable models were used. Epigenetic age was calculated in five methods, including Hannum, Horvath, ELOVL2, FHL2, and Weidner’s equation. The associations between DEP exposure and epigenetic age acceleration were estimated. Differential methylation analysis used two significant thresholds, false discovery rate (FDR) adjusted p-value < 0.05 and p-value < 5×10-5. The two-tailed test significant threshold was type I error < 0.05. Results: The mean age of our study participant was 59.27 years old, mean BMI was 26.38 kg/m2, and mean DEP exposure concentration was 7.71 ng/mL. When exposed to the higher concentrations of DEP, most of the MS-related indicators values changes had negative effects on health, particularly increased waistline, fasting blood glucose, and the risk of MS. Although we found the concentration of DEP exposure was higher in adenoma and CRC than control, but not statistically significant. We also observed that the genes affected by DEP exposure were mainly in the metabolic and carcinogenesis pathways. In addition, comparing to participants exposure to low concentrations of DEP, we found that DEP was associated with a decrease in CD8T cells, MS effector genes (POR, CNPY1, FTO, SH3RF3, and KRT32) and cancer-related effector genes (KNDC1, STK25, NFATC3, CCDC183, WDR74, SLC15A3, MPRIP, SNORA10B, and PLCL2) were hypomethylated among participants exposure high concentration of DEP. The hypomethylation of MS effector genes was related to BMI, waistline, blood pressure, fasting blood glucose, triglyceride, and high density lipoprotein. We did not find DEP exposure significantly related to accelerated aging of epigenetic age. Discussion and conclusion: In our results, higher concentration of DEP exposure was related to the increase of waistline and fasting blood glucose, which was the same as the results of previous studies. Additionally, DEP concentration was related to the decrease of CD8T cells, which may promote the development of cancer. POR, CNPY1, and FTO have been defined as MS-related genes in previous studies, while SH3RF3 and KRT32 were first to be discovered to have functions in the metabolic pathway. Previous studies showed that the methylation levels of KNDC1 and PLCL2 were related to cancer, while CCDC183 was the first time to link to cancer in our research. Although the half-life of DEP is short and DEP concentration of our participants was lower than other countries, we still found a positive relation between DEP exposure and MS and the development of CRC. Therefore, we must pay attention to chronic disease risks and hazards caused by DEP exposure and formulate relevant regulations. The further replications regarding the DEP exposure related effects in a larger sample size are still required.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease worldwide, but its pathophysiological mechanisms remain elusive. It is a progressive disease, encompassing hepatic steatosis, steatohepatitis with (out) fibrosis, and ultimately cirrhosis and hepatocellular carcinoma. DNA methylation (DNAm) is dysregulated in MASLD and may play a central role in its pathogenesis. Additionally, aging is associated with MASLD and shares common processes of chronic inflammation and oxidative stress. Therefore, this study focuses on DNAm changes in relation to MASLD progression and epigenetic age acceleration (EAA). Liver biopsies from 22 individuals with varying MASLD status were analyzed using Infinium MethylationEPIC BeadChip arrays. Strikingly, progression of MASLD was characterized by gradual DNAm changes, revealing multiple associated KEGG pathways. Additionally, Horvath's EAA significantly correlated with MASLD stage and individual histological MASLD parameters while LiverClock's EAA correlated only with MASLD stage. In contrast, both Horvath's intrinsic EAA and HepClock's EAA showed no significant correlations. Integrative analyses, leveraging both gradual MASLD and Horvath's EAA DNAm signatures, gene expression (n = 118), and a MASLD-specific transcriptional regulatory network, identified (regulon-specific) transcription factors implicated in MASLD and EAA progression, representing a transcription factor-network of redox (ferroptosis), immune, and metabolic/endocrine related epigenetic processes. Gradual DNAm changes were found to align with progression of MASLD and EAA, with EAA a potential nonbiased quantitative biomarker for MASLD. Integrative analysis highlighted potential new therapeutic transcription factor targets, with special emphasis on AEBP1 and emerging nuclear receptors including CAR(NR1I3), MR(NR3C2), GR(NR3C1), and ESRRG, underscoring the potential of epigenetic redox-metabolic therapies for MASLD.

A known association exists between exposure to gestational diabetes mellitus (GDM) and epigenetic age acceleration (EAA) in GDM-exposed offspring compared to those without GDM exposure. This association has not been assessed previously in mothers with pregnancies complicated by GDM. A total of 137 mother-child dyads with an index pregnancy 4–10 years before study enrollment were included. Clinical data and whole blood samples were collected and quantified to obtain DNA methylation (DNAm) estimates using the Illumina MethylEPIC 850K array in mothers and offspring. DNAm age and age acceleration were evaluated using the Horvath and Hannum clocks. Multivariable linear regression models were performed to determine the association between EAA and leptin, high-density lipoprotein cholesterol (HDL-C), fasting glucose, fasting insulin, and HOMA-IR. Mothers with a GDM and non-GDM pregnancy had strong correlations between chronological age and DNAm age (r > 0.70). Offspring of GDM mothers had moderate to strong correlations, whereas offspring of non-GDM mothers had moderate correlations between chronological age and DNAm age. Association analyses revealed a significant association between EAA and fasting insulin in offspring (FDR < 0.05), while HDL-C was the only metabolic marker significantly associated with EAA in mothers (FDR < 0.05). Mothers in the GDM group had a higher predicted epigenetic age and age acceleration than mothers in the non-GDM group. The association between EAA with elevated fasting insulin in offspring and elevated HDL-C in mothers suggests possible biomarkers that can better elucidate the effects of exposure to a GDM pregnancy and future cardiometabolic outcomes.

BackgroundEpigenetic age acceleration (EAA) and epigenetic gestational age acceleration (EGAA) are biomarkers of physiological development and may be affected by the perinatal environment. The aim of this study was to evaluate performance of epigenetic clocks and to identify biological and sociodemographic correlates of EGAA and EAA at birth and in childhood. In the Project Viva pre-birth cohort, DNA methylation was measured in nucleated cells in cord blood (leukocytes and nucleated red blood cells, N = 485) and leukocytes in early (N = 120, median age = 3.2 years) and mid-childhood (N = 460, median age = 7.7 years). We calculated epigenetic gestational age (EGA; Bohlin and Knight clocks) and epigenetic age (EA; Horvath and skin & blood clocks), and respective measures of EGAA and EAA. We evaluated the performance of clocks relative to chronological age using correlations and median absolute error. We tested for associations of maternal-child characteristics with EGAA and EAA using mutually adjusted linear models controlling for estimated cell type proportions. We also tested associations of Horvath EA at birth with childhood EAA.ResultsBohlin EGA was strongly correlated with chronological gestational age (Bohlin EGA r = 0.82, p < 0.001). Horvath and skin & blood EA were weakly correlated with gestational age, but moderately correlated with chronological age in childhood (r = 0.45–0.65). Maternal smoking during pregnancy was associated with higher skin & blood EAA at birth [B (95% CI) = 1.17 weeks (− 0.09, 2.42)] and in early childhood [0.34 years (0.03, 0.64)]. Female newborns and children had lower Bohlin EGAA [− 0.17 weeks (− 0.30, − 0.04)] and Horvath EAA at birth [B (95% CI) = − 2.88 weeks (− 4.41, − 1.35)] and in childhood [early childhood: − 0.3 years (− 0.60, 0.01); mid-childhood: − 0.48 years (− 0.77, − 0.18)] than males. When comparing self-reported Asian, Black, Hispanic, and more than one race or other racial/ethnic groups to White, we identified significant differences in EGAA and EAA at birth and in mid-childhood, but associations varied across clocks. Horvath EA at birth was positively associated with childhood Horvath and skin & blood EAA.ConclusionsMaternal smoking during pregnancy and child sex were associated with EGAA and EAA at multiple timepoints. Further research may provide insight into the relationship between perinatal factors, pediatric epigenetic aging, and health and development across the lifespan.

Rationale: Up to 70% of intensive care unit (ICU) patients experience delirium, a syndrome associated with accelerated cognitive and physical aging. Epigenetic clocks (EC) are biomarkers that estimate epigenetic age based on DNA methylation (DNAm) data, while epigenetic age acceleration (EAA) represents the difference between epigenetic and chronological age. The relationship between EC, EAA, and ICU delirium has not been well quantified. We aimed to explore the relationships between epigenetic age and ICU delirium duration and severity. Methods: This is a hypothesis-generating pilot study utilizing blood samples and data from participants enrolled in Pharmacological Management of Delirium (PMD), a previously published negative randomized controlled trial. Serum samples were collected upon study enrollment (within 48 hours of ICU admission). DNA was isolated from serum clots and analyzed in triplicate on Illumina MethylationEPIC arrays to quantify DNAm. Epigenetic age and EAA were computed for the Horvath, Hannum, PhenoAge, HorvathSkin, Telomere Length (TL), Best Linear Unbiased Predictor (BLUP), Elastic Network (EN), and DunedinPACE epigenetic clocks from DNAm data. The severity of illness at ICU admission was measured using the Acute Physiology and Chronic Health Evaluation (APACHE) II score. Coma, delirium, and delirium severity were assessed twice daily until day 30 or discharge using Richmond Agitation-Sedation Scale (RASS), Confusion Assessment Method for ICU (CAM-ICU), and CAM-ICU-7, respectively. Spearman correlations were computed for relationships between EC/EAA and delirium outcomes of interest using SAS. Results: A convenience sample of 20 ICU patients with delirium was included. The cohort's mean age was 66.7 years (SD=11.3), 12% were female, and 50% were Black. The median Charlson Comorbidity Index was 1 (IQR 1 – 4), and the median APACHE-II was 18 (IQR 13 – 22). The median delirium/coma-free days (DCFD) by day 8 were 3 (IQR 0 – 6.5). EN EAA was moderately correlated with mean CAM-ICU-7 scores by day 8 (Spearman r= -0.54, p&amp;lt;0.05) and by hospital discharge (r= -0.48, p&amp;lt;0.05). There were no significant correlations between other EC/EAAs and delirium. Conclusion: In this exploratory study, we observed a negative correlation between EAA and delirium severity via one EC. Larger studies are needed to confirm the correlations among epigenetic age, delirium, and long-term outcomes among ICU delirium survivors.

Because DNA methylation changes reliably with age, machine learning models called epigenetic clocks can estimate an individual's age based on their DNA methylation profile. This epigenetic measure of age can deviate from one's true age, and the difference between the epigenetic age and true age, known as epigenetic age acceleration (EAA), has been found to directly correlate with morbidity and mortality in adults. Emerging evidence suggests that EAA is also associated with aberrant health outcomes in children, making epigenetic clocks useful tools for studying aging and development. We developed two highly accurate epigenetic clocks for the rhesus macaque, utilizing 1,008 blood samples from 690 macaques between 2 days and 23.4 years of age with diverse genetic backgrounds and exposure to environmental conditions. The first clock, which is trained on all samples, achieves a Pearson correlation between true age and predicted age of 0.983 and median absolute error of 0.210 years. To study phenotypes during development, the second clock is optimized for macaques younger than 6 years and achieves a Pearson correlation of 0.974 and a median absolute error of 0.148 years. Using the latter clock, we investigated whether epigenetic aging is affected by early life adversity in the form of infant maltreatment. Our data suggests that maltreatment and increased hair cortisol levels are associated with epigenetic age acceleration right after the period of maltreatment.