Age-associated DNA methylation in pediatric populations

Longitudinal Changes in Epigenetic Age Acceleration Across Childhood and Adolescence

Importance

Individuals exposed to discrimination may exhibit greater epigenetic age acceleration (ie, cellular indicators of premature aging) over time, but few studies have examined longitudinal changes in epigenetic age acceleration, the heterogeneity in these changes for diverse groups of youths, and contextual explanations (ie, discrimination) for differences by ethnicity or race.

Objective

To provide a descriptive illustration of changes in epigenetic age acceleration across childhood and adolescence among an ethnically and racially diverse sample of youths.

Design, Setting, and Participants

This cohort study leveraged longitudinal data on a large sample of youths from low-income households in 20 large urban US cities who provided repeated assessments of saliva tissue samples at ages 9 and 15 years for DNA methylation analysis. Of 4898 youths from the Future of Families and Child Well-Being study, an ongoing study that oversampled children born to unmarried parents from 1998 to 2000, 2039 were included in the present analysis, as these youths had salivary DNA methylation data assayed and publicly available. Analyses were conducted from March 2023 to June 2024.

Exposures

Racialized intrusive encounters with police (eg, stop and frisk and racial slurs).

Main Outcomes and Measures

Analyses were conducted to examine longitudinal changes in salivary epigenetic age acceleration over time, whether such changes varied across ethnically and racially diverse groups of youths, and whether police intrusion was associated with variation across ethnic and racial groups.

Results

Among 2039 youths (mean [SD] age at baseline, 9.27 [0.38] years; 1023 [50%] male and 1016 [50%] female; 917 [45%] Black, 430 [21%] Hispanic or Latino, 351 [17%] White, and 341 [17%] other, including multiple races and self-identified other) with salivary epigenetic clocks at 9 and 15 years of age, longitudinal results showed that White youths exhibited less accelerated epigenetic aging over time than did Black and Hispanic or Latino youths and those reporting other or multiple races or ethnicities from ages 9 to 15 years, particularly in the Hannum (B, 1.54; 95% CI, 0.36-2.18), GrimAge (B, 1.31; 95% CI, 0.68-1.97), and DunedinPACE epigenetic clocks (B, 0.27; 95% CI, 0.11-0.44). Across these clocks and the PhenoAge clock, police intrusion was associated with Black youths' more accelerated epigenetic aging (Hannum: B, 0.11; 95% CI, 0.03-0.23; GrimAge: B, 0.09; 95% CI, 0.03-0.18; PhenoAge: B, 0.08; 95% CI, 0.02-0.18; DunedinPACE: B, 0.01; 95% CI, 0.01-0.03).

Conclusions and Relevance

The transition from childhood to adolescence may represent a sensitive developmental period when racism can have long-term deleterious impacts on healthy human development across the life span. Future research should build on the present study and interrogate which social regularities and policies may be perpetuating discrimination against ethnically and racially minoritized adolescents.

DNA methylation changes in the genome of patients with hypogonadotropic hypogonadism

Although some Mendelian neurodevelopmental disorders have been shown to entail specific DNA methylation changes designated as epi-signatures, it remains unknown whether epi-signatures are consistent features of other genetic disorders. Here, we analyzed DNA methylation profiles of patients with hypogonadotropic hypogonadism (HH), a rare neuroendocrine disorder typically caused by monogenic or oligogenic mutations. First, we performed microarray-based genome-wide methylation analyses of nine patients with HH due to ANOS1, SOX2, or SOX10 variants and 12 control individuals. The results showed that 1118 probes were differentially methylated in one or more patients. The differentially methylated probes were highly variable among patients. No significant methylation changes were observed in genes functionally associated with ANOS1, SOX2, or SOX10. Then, we performed pyrosequencing of six selected CpG sites in the nine patients and 35 additional HH patients. The results of the patients were compared with those of 48 fertile men. There were no common methylation changes among these patients, with the exception of hypermethylation of two CpG sites in the ZNF245 promoter of three patients. Hypermethylation of the promoter has previously been reported as a very rare epigenetic polymorphism in the general population. These results indicate that genomes of HH patients have considerable DNA methylation changes; however, these changes are more likely to be physiological epigenetic variations than disease-specific epi-signatures. Our data suggest a possible association between hypermethylation of the ZNF254 promoter and HH, which needs to be examined in future studies.

Uncertainty quantification in epigenetic clocks via conformalized quantile regression

DNA methylation (DNAm) is a chemical modification of DNA that can be influenced by various factors, including age, environment, and lifestyle. An epigenetic clock is a predictive tool that measures biological age based on DNAm levels. It can provide insights into an individual's biological age, which may differ from their chronological age. This difference, known as the epigenetic age acceleration, may indicate the state of one's health and risk for age-related diseases. Moreover, epigenetic clocks are used in studies of aging to assess the effectiveness of anti-aging interventions and to understand the underlying mechanisms of aging and disease. Various epigenetic clocks have been developed using samples from different populations, tissues, and cell types, typically by training high-dimensional linear regression models with an elastic net penalty. While these models can predict mean biological age with high precision, there is a lack of uncertainty quantification which is important for interpreting the precision of age estimations and for clinical decision-making. To understand the distribution of a biological age clock beyond its mean, we propose a general pipeline for training epigenetic clocks, based on an integration of high-dimensional quantile regression and conformal prediction, to effectively reveal population heterogeneity and construct prediction intervals. Our approach produces adaptive prediction intervals not only achieving nominal coverage but also accounting for the inherent variability across individuals. By using the data collected from 728 blood samples in 11 DNAm datasets from children, we find that our quantile regression-based prediction intervals are narrower than those derived from conventional mean regression-based epigenetic clocks. This observation demonstrates an improved statistical efficiency over the existing pipeline for training epigenetic clocks. In addition, the resulting intervals have a synchronized varying pattern to age acceleration, effectively revealing cellular evolutionary heterogeneity in age patterns in different developmental stages during individual childhoods and adolescent cohort. Our findings suggest that conformalized high-dimensional quantile regression can produce valid prediction intervals and uncover underlying population heterogeneity. Although our methodology focuses on the distribution of aging in children, it is applicable to a broader range of populations to improve understanding of epigenetic age beyond the mean. This inference-based toolbox could provide valuable insights for future applications of epigenetic interventions for age-related diseases.

Epigenetic biomarkers in aging and longevity: Current and future application

The aging process has been one of the most necessary research fields in the current century, and knowing different theories of aging and the role of different genetic, epigenetic, molecular, and environmental modulating factors in increasing the knowledge of aging mechanisms and developing appropriate diagnostic, therapeutic, and preventive ways would be helpful. One of the most conserved signs of aging is epigenetic changes, including DNA methylation, histone modifications, chromatin remodeling, noncoding RNAs, and extracellular RNAs. Numerous biological processes and hallmarks are vital in aging development, but epigenomic alterations are especially notable because of their importance in gene regulation and cellular identity. The mounting evidence points to a possible interaction between age-related epigenomic alterations and other aging hallmarks, like genome instability. To extend a healthy lifespan and possibly reverse some facets of aging and aging-related diseases, it will be crucial to comprehend global and locus-specific epigenomic modifications and recognize corresponding regulators of health and longevity. In the current study, we will aim to discuss the role of epigenomic mechanisms in aging and the most recent developments in epigenetic diagnostic biomarkers, which have the potential to focus efforts on reversing the destructive signs of aging and extending the lifespan.

ELOVL2, PRKG2, and EDARADD DNA Methylation Strongly Estimate Indonesian Adolescents

Recently, there has been a growing interest in using DNA methylation analysis for age estimation. Despite this growing interest, there is a scarcity of research on the potential of DNA methylation as a biomarker for age estimation in Indonesia. This study aims to investigate the applicability of ELOVL2, PRKG2, and EDARADD genes for forensic identification in the 11-20 age group among Indonesians. This research utilizes 43 archived blood samples from healthy individuals who underwent blood tests at the Gatot Soebroto Army Hospital (RSPAD) in Central Jakarta, Indonesia. The methylation-specific PCR (MSP) technique assessed the DNA methylation level. The key findings of this study include (1) a strong positive correlation between methylation levels in the ELOVL2 gene and age; (2) a strong negative correlation between methylation levels in PRKG2 and EDARADD genes with age; (3) the development of three linear regression formulas for age prediction; and (4) mean absolute error (MAE) values derived from this research, which are ±0.48 for ELOVL2 gene regression formula, ±0.58 for PRKG2 gene regression formula, and ±0.72 for EDARADD gene regression formula. In summary, this study explores the potential of DNA methylation analysis for age estimation in Indonesia, focusing on ELOVL2, PRKG2, and EDARADD genes in the 11-20 age group. The findings underscore the applicability of DNA methylation analysis in forensic identification and age estimation, paving the way for future research in this field.

Sex-Specific Associations between Prenatal Exposure to Bisphenols and Phthalates and Infant Epigenetic Age Acceleration

We examined whether prenatal exposure to two classes of endocrine-disrupting chemicals (EDCs) was associated with infant epigenetic age acceleration (EAA), a DNA methylation biomarker of aging. Participants included 224 maternal-infant pairs from a Canadian pregnancy cohort study. Two bisphenols and 12 phthalate metabolites were measured in maternal second trimester urines. Buccal epithelial cell cheek swabs were collected from 3 month old infants and DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The Pediatric-Buccal-Epigenetic tool was used to estimate EAA. Sex-stratified robust regressions examined individual chemical associations with EAA, and Bayesian kernel machine regression (BKMR) examined chemical mixture effects. Adjusted robust models showed that in female infants, prenatal exposure to total bisphenol A (BPA) was positively associated with EAA (B = 0.72, 95% CI: 0.21, 1.24), and multiple phthalate metabolites were inversely associated with EAA (Bs from -0.36 to -0.66, 95% CIs from -1.28 to -0.02). BKMR showed that prenatal BPA was the most important chemical in the mixture and was positively associated with EAA in both sexes. No overall chemical mixture effects or male-specific associations were noted. These findings indicate that prenatal EDC exposures are associated with sex-specific deviations in biological aging, which may have lasting implications for child health and development.

Individual longitudinal changes in DNA-methylome identify signatures of early-life adversity and correlate with later outcome

Adverse early-life experiences (ELA) affect a majority of the world's children. Whereas the enduring impact of ELA on cognitive and emotional health is established, there are no tools to predict vulnerability to ELA consequences in an individual child. Epigenetic markers including peripheral-cell DNA-methylation profiles may encode ELA and provide predictive outcome markers, yet the interindividual variance of the human genome and rapid changes in DNA methylation in childhood pose significant challenges. Hoping to mitigate these challenges we examined the relation of several ELA dimensions to DNA methylation changes and outcome using a within-subject longitudinal design and a high methylation-change threshold. DNA methylation was analyzed in buccal swab/saliva samples collected twice (neonatally and at 12 months) in 110 infants. We identified CpGs differentially methylated across time for each child and determined whether they associated with ELA indicators and executive function at age 5. We assessed sex differences and derived a sex-dependent 'impact score' based on sites that most contributed to methylation changes. Changes in methylation between two samples of an individual child reflected age-related trends and correlated with executive function years later. Among tested ELA dimensions and life factors including income to needs ratios, maternal sensitivity, body mass index and infant sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, high early-life unpredictability interacted with methylation changes to presage executive function. Thus, longitudinal, within-subject changes in methylation profiles may provide a signature of ELA and a potential predictive marker of individual outcome.

DNA methylation of the Lamin A/C gene is associated with congenital heart disease

BACKGROUND

Prior studies report associations of maternal serum Lamin A, encoded by the LMNA gene, with fetal congenital heart disease (CHD). It is unknown whether DNA methylation (DNAm) of cytosine-phosphate-guanine (CpG) sites in LMNA impacts the CHD susceptibility.

METHODS

We investigated the associations of LMNA DNAm with CHD using publicly available data of CHD cases (n = 197) and controls (n = 134) from the Gene Expression Omnibus repository. Peripheral blood DNAm was measured using Illumina 850 K BeadChip for cases and 450 K BeadChip for controls. We tested 31 LMNA CpGs to identify differences in DNAm between cases and controls using linear regression correcting for multiple testing with false discovery rate (FDR). In a case-only analysis, we tested the variations in LMNA DNAm between CHD subtypes. To identify the consistency of DNAm across tissue types we compared peripheral blood (n = 197) and heart tissue DNAm (n = 20) in CHD cases.

RESULTS

After adjusting for age, sex, and cell types there were significant differences in 17 of the 31 LMNA CpGs between CHD cases and controls (FDR p ≤ .05). We identified lower DNAm of cg09820673 at 3' UTR for hypoplastic left heart syndrome compared to other CHD subtypes. Three CpGs exhibited uniform DNAm in blood and heart tissues in cases. Eleven CpGs showed changes in the same direction in blood and heart tissues in cases compared to controls.

CONCLUSION

We identify statistically significant differences in LMNA DNAm between CHD cases and controls. Future studies should investigate the role of maternal LMNA DNAm in CHD development.

Epigenetic signature of very low birth weight in young adult life

BACKGROUND

Globally, one in ten babies is born preterm (<37 weeks), and 1-2% preterm at very low birth weight (VLBW, <1500 g). As adults, they are at increased risk for a plethora of health conditions, e.g., cardiometabolic disease, which may partly be mediated by epigenetic regulation. We compared blood DNA methylation between young adults born at VLBW and controls.

METHODS

157 subjects born at VLBW and 161 controls born at term, from the Helsinki Study of Very Low Birth Weight Adults, were assessed for peripheral venous blood DNA methylation levels at mean age of 22 years. Significant CpG-sites (5'-C-phosphate-G-3') were meta-analyzed against continuous birth weight in four independent cohorts (pooled n = 2235) with cohort mean ages varying from 0 to 31 years.

RESULTS

In the discovery cohort, 66 CpG-sites were differentially methylated between VLBW adults and controls. Top hits were located in HIF3A, EBF4, and an intergenic region nearest to GLI2 (distance 57,533 bp). Five CpG-sites, all in proximity to GLI2, were hypermethylated in VLBW and associated with lower birth weight in the meta-analysis.

CONCLUSION

We identified differentially methylated CpG-sites suggesting an epigenetic signature of preterm birth at VLBW present in adult life.

IMPACT

Being born preterm at very low birth weight has major implications for later health and chronic disease risk factors. The mechanism linking preterm birth to later outcomes remains unknown. Our cohort study of 157 very low birth weight adults and 161 controls found 66 differentially methylated sites at mean age of 22 years. Our findings suggest an epigenetic mark of preterm birth present in adulthood, which opens up opportunities for mechanistic studies.

Sex-Specific Deflection of Age-Related DNA Methylation and Gene Expression in Mouse Heart by Perinatal Toxicant Exposures

Background

Global and site-specific changes in DNA methylation and gene expression are associated with cardiovascular aging and disease, but how toxicant exposures during early development influence the normal trajectory of these age-related molecular changes, and whether there are sex differences, has not yet been investigated.

Objectives

We used an established mouse model of developmental exposures to investigate the effects of perinatal exposure to either lead (Pb) or diethylhexyl phthalate (DEHP), two ubiquitous environmental contaminants strongly associated with CVD, on age-related cardiac DNA methylation and gene expression.

Methods

Dams were randomly assigned to receive human physiologically relevant levels of Pb (32 ppm in water), DEHP (25 mg/kg chow), or control water and chow. Exposures started two weeks prior to mating and continued until weaning at postnatal day 21 (3 weeks of age). Approximately one male and one female offspring per litter were followed to 3 weeks, 5 months, or 10 months of age, at which time whole hearts were collected (n ≥ 5 per sex per exposure). Enhanced reduced representation bisulfite sequencing (ERRBS) was used to assess the cardiac DNA methylome at 3 weeks and 10 months, and RNA-seq was conducted at all 3 time points. MethylSig and edgeR were used to identify age-related differentially methylated regions (DMRs) and differentially expressed genes (DEGs), respectively, within each sex and exposure group. Cell type deconvolution of bulk RNA-seq data was conducted using the MuSiC algorithm and publicly available single cell RNA-seq data.

Results

Thousands of DMRs and hundreds of DEGs were identified in control, DEHP, and Pb-exposed hearts across time between 3 weeks and 10 months of age. A closer look at the genes and pathways showing differential DNA methylation revealed that the majority were unique to each sex and exposure group. Overall, pathways governing development and differentiation were most frequently altered with age in all conditions. A small number of genes in each group showed significant changes in DNA methylation and gene expression with age, including several that were altered by both toxicants but were unchanged in control. We also observed subtle, but significant changes in the proportion of several cell types due to age, sex, and developmental exposure.

Discussion

Together these data show that perinatal Pb or DEHP exposures deflect normal age-related gene expression, DNA methylation programs, and cellular composition across the life course, long after cessation of exposure, and highlight potential biomarkers of developmental toxicant exposures. Further studies are needed to investigate how these epigenetic and transcriptional changes impact cardiovascular health across the life course.

The peripheral epigenome predicts white matter volume contingent on developmental stage: An ECHO study

Epigenetic processes, including DNA methylation, are emerging as key areas of interest for their potential roles as biomarkers and contributors to the risk of neurodevelopmental, psychiatric, and other brain-based disorders. Despite this growing focus, there remains a notable gap in our understanding of how DNA methylation correlates with individual variations in brain function and structure. Additionally, the dynamics of these relationships during developmental periods, which are critical windows during which many disorders first appear, are still largely unexplored. The current study extends the field by examining if peripheral DNA methylation of myelination-related genes predicts white matter volume in a healthy pediatric population [N = 250; females = 113; age range 2 months-14 years; Mage = 5.14, SDage = 3.60]. We assessed if DNA methylation of 17 myelin-related genes predict white matter volume and if age moderates these relationships. Results highlight low variability in myelin-related epigenetic variance at birth, which rapidly increases non-linearly with age, and that DNA methylation, measured at both the level of a CpG site or gene, is highly predictive of white matter volume, in early childhood but not late childhood. These novel findings propel the field forward by establishing that DNA methylation of myelin-related genes from a peripheral tissue is a predictive marker of white matter volume in children and is influenced by developmental stage. The research underscores the significance of peripheral epigenetic patterns as a proxy for investigating the effects of environmental factors, behaviors, and disorders associated with white matter.

Insights into ageing rates comparison across tissues from recalibrating cerebellum DNA methylation clock

DNA methylation (DNAm)-based age clocks have been studied extensively as a biomarker of human ageing and a risk factor for age-related diseases. Despite different tissues having vastly different rates of proliferation, it is still largely unknown whether they age at different rates. It was previously reported that the cerebellum ages slowly; however, this claim was drawn from a single clock using a relatively small sample size and so warrants further investigation. We collected the largest cerebellum DNAm dataset (N = 752) to date. We found the respective epigenetic ages are all severely underestimated by six representative DNAm age clocks, with the underestimation effects more pronounced in the four clocks whose training datasets do not include brain-related tissues. We identified 613 age-associated CpGs in the cerebellum, which accounts for only 14.5% of the number found in the middle temporal gyrus from the same population (N = 404). From the 613 cerebellum age-associated CpGs, we built a highly accurate age prediction model for the cerebellum named CerebellumClockspecific (Pearson correlation=0.941, MAD=3.18 years). Ageing rate comparisons based on the two tissue-specific clocks constructed on the 201 overlapping age-associated CpGs support the cerebellum has younger DNAm age. Nevertheless, we built BrainCortexClock to prove a single DNAm clock is able to unbiasedly estimate DNAm ages of both cerebellum and cerebral cortex, when they are adequately and equally represented in the training dataset. Comparing ageing rates across tissues using DNA methylation multi-tissue clocks is flawed. The large underestimation of age prediction for cerebellums by previous clocks mainly reflects the improper usage of these age clocks. There exist strong and consistent ageing effects on the cerebellar methylome, and we suggest the smaller number of age-associated CpG sites in cerebellum is largely attributed to its extremely low average cell replication rates.

ResnetAge: A Resnet-Based DNA Methylation Age Prediction Method

Aging is a significant contributing factor to degenerative diseases such as cancer. The extent of DNA methylation in human cells indicates the aging process and screening for age-related methylation sites can be used to construct epigenetic clocks. Thereby, it can be a new aging-detecting marker for clinical diagnosis and treatments. Predicting the biological age of human individuals is conducive to the study of physical aging problems. Although many researchers have developed epigenetic clock prediction methods based on traditional machine learning and even deep learning, higher prediction accuracy is still required to match the clinical applications. Here, we proposed an epigenetic clock prediction method based on a Resnet neuro networks model named ResnetAge. The model accepts 22,278 CpG sites as a sample input, supporting both the Illumina 27K and 450K identification frameworks. It was trained using 32 public datasets containing multiple tissues such as whole blood, saliva, and mouth. The Mean Absolute Error (MAE) of the training set is 1.29 years, and the Median Absolute Deviation (MAD) is 0.98 years. The Mean Absolute Error (MAE) of the validation set is 3.24 years, and the Median Absolute Deviation (MAD) is 2.3 years. Our method has higher accuracy in age prediction in comparison with other methylation-based age prediction methods.

Within-subject changes in methylome profile identify individual signatures of early-life adversity, with a potential to predict neuropsychiatric outcome

Background

Adverse early-life experiences (ELA), including poverty, trauma and neglect, affect a majority of the world's children. Whereas the impact of ELA on cognitive and emotional health throughout the lifespan is well-established, it is not clear how distinct types of ELA influence child development, and there are no tools to predict for an individual child their vulnerability or resilience to the consequences of ELAs. Epigenetic markers including DNA-methylation profiles of peripheral cells may encode ELA and provide a predictive outcome marker. However, the rapid dynamic changes in DNA methylation in childhood and the inter-individual variance of the human genome pose barriers to identifying profiles predicting outcomes of ELA exposure. Here, we examined the relation of several dimensions of ELA to changes of DNA methylation, using a longitudinal within-subject design and a high threshold for methylation changes in the hope of mitigating the above challenges.

Methods

We analyzed DNA methylation in buccal swab samples collected twice for each of 110 infants: neonatally and at 12 months. We identified CpGs differentially methylated across time, calculated methylation changes for each child, and determined whether several indicators of ELA associated with changes of DNA methylation for individual infants. We then correlated select dimensions of ELA with methylation changes as well as with measures of executive function at age 5 years. We examined for sex differences, and derived a sex-dependent 'impact score' based on sites that most contributed to the methylation changes.

Findings

Setting a high threshold for methylation changes, we discovered that changes in methylation between two samples of an individual child reflected age-related trends towards augmented methylation, and also correlated with executive function years later. Among the tested factors and ELA dimensions, including income to needs ratios, maternal sensitivity, body mass index and sex, unpredictability of parental and household signals was the strongest predictor of executive function. In girls, an interaction was observed between a measure of high early-life unpredictability and methylation changes, in presaging executive function.

Interpretation

These findings establish longitudinal, within-subject changes in methylation profiles as a signature of some types of ELA in an individual child. Notably, such changes are detectable beyond the age-associated DNA methylation dynamics. Future studies are required to determine if the methylation profile changes identified here provide a predictive marker of vulnerabilities to poorer cognitive and emotional outcomes.

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

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

Getting the chronological age out of DNA: using insights of age-dependent DNA methylation for forensic DNA applications

BACKGROUND

DNA analysis for forensic investigations has a long tradition with important developments and optimizations since its first application. Traditionally, short tandem repeats analysis has been the most powerful method for the identification of individuals. However, in addition, epigenetic changes, i.e., DNA methylation, came into focus of forensic DNA research. Chronological age prediction is one promising application to allow for narrowing the pool of possible individuals who caused a trace, as well as to support the identification of unknown bodies and for age verification of living individuals.

OBJECTIVE

This review aims to provide an overview of the current knowledge, possibilities, and (current) limitations about DNA methylation-based chronological age prediction with emphasis on forensic application.

METHODS

The development, implementation and application of age prediction tools requires a deep understanding about the biological background, the analysis methods, the age-dependent DNA methylation markers, as well as the mathematical models for age prediction and their evaluation. Furthermore, additional influences can have an impact. Therefore, the literature was evaluated in respect to these diverse topics.

CONCLUSION

The numerous research efforts in recent years have led to a rapid change in our understanding of the application of DNA methylation for chronological age prediction, which is now on the way to implementation and validation. Knowledge of the various aspects leads to a better understanding and allows a more informed interpretation of DNAm quantification results, as well as the obtained results by the age prediction tools.

The role of DNA methylation in personalized medicine for immune-related diseases

Epigenetics functions as a bridge between host genetic & environmental factors, aiding in human health and diseases. Many immune-related diseases, including infectious and allergic diseases, have been linked to epigenetic mechanisms, particularly DNA methylation. In this review, we summarized an updated overview of DNA methylation and its importance in personalized medicine, and demonstrated that DNA methylation has excellent potential for disease prevention, diagnosis, and treatment in a personalized manner. The future implications and limitations of the DNA methylation study have also been well-discussed.

Accurate age prediction from blood using a small set of DNA methylation sites and a cohort-based machine learning algorithm

Chronological age prediction from DNA methylation sheds light on human aging, health, and lifespan. Current clocks are mostly based on linear models and rely upon hundreds of sites across the genome. Here, we present GP-age, an epigenetic non-linear cohort-based clock for blood, based upon 11,910 methylomes. Using 30 CpG sites alone, GP-age outperforms state-of-the-art models, with a median accuracy of ∼2 years on held-out blood samples, for both array and sequencing-based data. We show that aging-related changes occur at multiple neighboring CpGs, with implications for using fragment-level analysis of sequencing data in aging research. By training three independent clocks, we show enrichment of donors with consistent deviation between predicted and actual age, suggesting individual rates of biological aging. Overall, we provide a compact yet accurate alternative to array-based clocks for blood, with applications in longitudinal aging research, forensic profiling, and monitoring epigenetic processes in transplantation medicine and cancer.

The association of epigenetic age acceleration and depressive and anxiety symptom severity among children recently exposed to substantiated maltreatment

Child maltreatment is a major risk factor for both depressive and anxiety disorders. However, many children exposed to maltreatment never meet diagnostic threshold for either disorder while experiencing only transitory symptoms post-exposure. Recent research suggests DNA methylation adds predictive value in explaining variation in the onset and course of multiple psychiatric disorders following exposure to child maltreatment. Epigenetic age acceleration (EAA), the biological aging of cells not attributable to chronological aging, is a stress-sensitive biomarker capturing genome-wide variation in DNA methylation with the potential to identify children who have been maltreated at greatest risk for depressive and anxiety disorders. The current study examined two EAA clocks appropriate for the pediatric population, the Horvath and Pediatric Buccal Epigenetic (PedBE) clocks, and their associations with depressive and anxiety symptom severity following child maltreatment. Children (N = 71) 8-15 years of age, all of whom were exposed to substantiated child maltreatment in the 12 months prior to study entry, were enrolled. Risk modeling adjusting for several confounders revealed that EAA estimated via the Horvath clock was significantly associated with more severe depressive and anxiety symptoms. The PedBE clock was not associated with either depressive or anxiety symptom severity. Sensitivity analyses demonstrated that EAA via the Horvath clock robustly predicted depressive and anxiety symptom severity across multiple modeling scenarios. Our findings advance existing research suggesting EAA, as estimated with the Horvath clock, may be a promising biomarker for identifying children at greatest risk for more severe depressive and anxiety symptoms following maltreatment.

A Review of the Epigenetic Clock: Emerging Biomarkers for Asthma and Allergic Disease

DNA methylation (DNAm) is a dynamic, age-dependent epigenetic modification that can be used to study interactions between genetic and environmental factors. Environmental exposures during critical periods of growth and development may alter DNAm patterns, leading to increased susceptibility to diseases such as asthma and allergies. One method to study the role of DNAm is the epigenetic clock-an algorithm that uses DNAm levels at select age-informative Cytosine-phosphate-Guanine (CpG) dinucleotides to predict epigenetic age (EA). The difference between EA and calendar age (CA) is termed epigenetic age acceleration (EAA) and reveals information about the biological capacity of an individual. Associations between EAA and disease susceptibility have been demonstrated for a variety of age-related conditions and, more recently, phenotypes such as asthma and allergic diseases, which often begin in childhood and progress throughout the lifespan. In this review, we explore different epigenetic clocks and how they have been applied, particularly as related to childhood asthma. We delve into how in utero and early life exposures (e.g., smoking, air pollution, maternal BMI) result in methylation changes. Furthermore, we explore the potential for EAA to be used as a biomarker for asthma and allergic diseases and identify areas for further study.

Methylation across the central dogma in health and diseases: new therapeutic strategies

The proper transfer of genetic information from DNA to RNA to protein is essential for cell-fate control, development, and health. Methylation of DNA, RNAs, histones, and non-histone proteins is a reversible post-synthesis modification that finetunes gene expression and function in diverse physiological processes. Aberrant methylation caused by genetic mutations or environmental stimuli promotes various diseases and accelerates aging, necessitating the development of therapies to correct the disease-driver methylation imbalance. In this Review, we summarize the operating system of methylation across the central dogma, which includes writers, erasers, readers, and reader-independent outputs. We then discuss how dysregulation of the system contributes to neurological disorders, cancer, and aging. Current small-molecule compounds that target the modifiers show modest success in certain cancers. The methylome-wide action and lack of specificity lead to undesirable biological effects and cytotoxicity, limiting their therapeutic application, especially for diseases with a monogenic cause or different directions of methylation changes. Emerging tools capable of site-specific methylation manipulation hold great promise to solve this dilemma. With the refinement of delivery vehicles, these new tools are well positioned to advance the basic research and clinical translation of the methylation field.

The methylation profile of IL4, IL5, IL10, IFNG and FOXP3 associated with environmental exposures differed between Polish infants with the food allergy and/or atopic dermatitis and without the disease

Objectives

Epigenetic dynamics has been indicated to play a role in allergy development. The environmental stimuli have been shown to influence the methylation processes. This study investigated the differences in CpGs methylation rate of immune-attached genes between healthy and allergic infants. The research was aimed at finding evidence for the impact of environmental factors on methylation-based regulation of immunological processes in early childhood.

Methods

The analysis of methylation level of CpGs in the IL4, IL5, IL10, IFNG and FOXP3 genes was performed using high resolution melt real time PCR technology. DNA was isolated from whole blood of Polish healthy and allergic infants, with food allergy and/or atopic dermatitis, aged under six months.

Results

The significantly lower methylation level of FOXP3 among allergic infants compared to healthy ones was reported. Additional differences in methylation rates were found, when combining with environmental factors. In different studied groups, negative correlations between age and the IL10 and FOXP3 methylation were detected, and positive - in the case of IL4. Among infants with different allergy symptoms, the decrease in methylation level of IFNG, IL10, IL4 and FOXP3 associated with passive smoke exposure was observed. Complications during pregnancy were linked to different pattern of the IFNG, IL5, IL4 and IL10 methylation depending on allergy status. The IFNG and IL5 methylation rates were higher among exclusively breastfed infants with atopic dermatitis compared to the non-breastfed. A decrease in the IFNG methylation was noted among allergic patients fed exclusively with milk formula. In different study groups, a negative correlation between IFNG, IL5 methylation and maternal BMI or IL5 methylation and weight was noted. Some positive correlations between methylation rate of IL10 and child's weight were found. A higher methylation of IL4 was positively correlated with the number of family members with allergy.

Conclusion

The FOXP3 methylation in allergic infants was lower than in the healthy ones. The methylation profile of IL4, IL5, IL10, IFNG and FOXP3 associated with environmental exposures differed between the studied groups. The results offer insights into epigenetic regulation of immunological response in early childhood.

Identification of a novel epigenetic marker for typical and mosaic presentations of Fragile X syndrome

BACKGROUND

Fragile X syndrome (FXS) is primarily due to CGG repeat expansions in the FMR1 gene. FMR1 alleles are classified as normal (N), intermediate (I), premutation (PM), and full mutation (FM). FXS patients often carry an FM, but size mosaicism can occur. Additionally, loss of methylation boundary upstream of repeats results in de novo methylation spreading to FMR1 promoter in FXS patients.

RESEARCH DESIGN AND METHODS

This pilot study investigated the methylation boundary and adjacent regions in 66 males with typical and atypical FXS aged 1 to 30 years (10.86 ± 6.48 years). AmplideX FMR1 mPCR kit was used to discriminate allele profiles and methylation levels. CpG sites were assessed by pyrosequencing.

RESULTS

40 out of 66 FXS patients (60.6%) showed an exclusive FM (n = 40), whereas the remaining (n = 26) exhibited size mosaicism [10 PM_FM (15.15%); 10 N_FM (15.15%); 2 N_PM_FM (3%)]. Four patients (6.1%) had deletions near repeats. Noteworthy, a CpG within FMR1 intron 2 displayed hypomethylation in FXS patients and hypermethylation in controls, demonstrating remarkable specificity, sensitivity, and accuracy when a methylation threshold of 69.5% was applied.

CONCLUSIONS

Since intragenic methylation is pivotal in gene regulation, the intronic CpG might be a novel epigenetic biomarker for FXS diagnosis.

An epigenetic clock for gestational age based on human umbilical vein endothelial cells from a diverse population of newborns

Background

Epigenetic clocks are emerging as a useful tool in many areas of research. Many epigenetic clocks have been developed for adults; however, there are fewer clocks focused on newborns and most are trained using blood from European ancestry populations. In this study, we built an epigenetic clock based on primary human umbilical vein endothelial cells from a racially and ethnically diverse population.

Results

Using human umbilical vein endothelial cell [HUVEC]-derived DNA, we calculated epigenetic gestational age using 83 CpG sites selected through elastic net regression. In this study with newborns from different racial/ethnic identities, epigenetic gestational age and clinical gestational age were more highly correlated (r = 0.85), than epigenetic clocks built from adult and other pediatric populations. The correlation was also higher than clocks based on blood samples from newborns with European ancestry. We also found that birth weight was positively associated with epigenetic gestational age acceleration (EGAA), while NICU admission was associated with lower EGAA. Newborns self-identified as Hispanic or non-Hispanic Black had lower EGAA than self-identified as non-Hispanic White.

Conclusions

Epigenetic gestational age can be used to estimate clinical gestational age and may help index neonatal development. Caution should be exercised when using epigenetic clocks built from adults with children, especially newborns. We highlight the importance of cell type-specific epigenetic clocks and general pan tissue epigenetic clocks derived from a large racially and ethnically diverse population.

Biomarkers of aging through the life course: A Recent Literature Update

Purpose of review

The development of biomarkers of aging has greatly advanced epidemiological studies of aging processes. However, much debate remains on the timing of aging onset and the causal relevance of these biomarkers. In this review, we discuss the most recent biomarkers of aging that have been applied across the life course.

Recent findings

The most recently developed aging biomarkers that have been applied across the life course can be designated into three categories: epigenetic clocks, epigenetic markers of chronic inflammation, and mitochondrial DNA copy number. While these have been applied at different life stages, the development, validation, and application of these markers has been largely centered on populations of older adults. Few studies have examined trajectories of aging biomarkers across the life course. As the wealth of molecular and biochemical data increases, emerging biomarkers may be able to capture complex and system-specific aging processes. Recently developed biomarkers include novel epigenetic clocks; clocks based on ribosomal DNA, transcriptomic profiles, proteomics, metabolomics, and inflammatory markers; clonal hematopoiesis of indeterminate potential gene mutations; and multi-omics approaches.

Summary

Attention should be placed on aging at early and middle life stages to better understand trajectories of aging biomarkers across the life course. Additionally, novel biomarkers will provide greater insight into aging processes. The specific mechanisms of aging reflected by these biomarkers should be considered when interpreting results.

Stressful life events and accelerated biological aging over time in youths

Experiencing adversity in childhood and adolescence, including stressful life events (SLEs), may accelerate the pace of development, leading to adverse mental and physical health. However, most research on adverse early experiences and biological aging (BA) in youths relies on cross-sectional designs. In 171 youths followed for approximately 2 years, we examined if SLEs over follow-up predicted rate of change in two BA metrics: epigenetic age and Tanner stage. We also investigated if rate of change in BA was associated with changes in depressive symptoms over time. Youths aged 8-16 years at baseline self-reported Tanner stage and depressive symptoms at baseline and follow-up and provided saliva samples for DNA at both assessments. Horvath epigenetic age estimates were derived from DNA methylation data measured with the Illumina EPIC array. At follow-up, contextual threat interviews were administered to youths and caregivers to assess youths' experiences of past-year SLEs. Interviews were objectively coded by an independent rating team to generate a SLE impact score, reflecting the severity of all SLEs occurring over the prior year. Rate of change in BA metrics was operationalized as change in epigenetic age or Tanner stage as a function of time between assessments. Higher objective SLE impact scores over follow-up were related to a greater rate of change in epigenetic age (β = 0.21, p = .043). Additionally, among youths with lower-but not higher-Tanner stage at baseline, there was a positive association of SLE impact scores with rate of change in Tanner stage (Baseline Tanner Stage × SLE Impact Score interaction: β = - 0.21, p = .011). A greater rate of change in epigenetic age was also associated with higher depressive symptom levels at follow-up, adjusting for baseline symptoms (β = 0.15, p = .043). Associations with epigenetic age were similar, although slightly attenuated, when adjusting for epithelial (buccal) cell proportions. Whereas much research in youths has focused on severe experiences of early adversity, we demonstrate that more commonly experienced SLEs during adolescence may also contribute to accelerated BA. Further research is needed to understand the long-term consequences of changes in BA metrics for health.

Down Syndrome Altered Cell Composition in Blood, Brain, and Buccal Swab Samples Profiled by DNA-Methylation-Based Cell-Type Deconvolution

Down syndrome (DS) is a genetic disorder caused by an extra copy of chromosome 21 that presents developmental dysfunction and intellectual disability. To better understand the cellular changes associated with DS, we investigated the cell composition in blood, brain, and buccal swab samples from DS patients and controls using DNA methylation-based cell-type deconvolution. We used genome-scale DNA methylation data from Illumina HumanMethylation450k and HumanMethylationEPIC arrays to profile cell composition and trace fetal lineage cells in blood samples (DS N = 46; control N = 1469), brain samples from various regions (DS N = 71; control N = 101), and buccal swab samples (DS N = 10; control N = 10). In early development, the number of cells from the fetal lineage in the blood is drastically lower in DS patients (Δ = 17.5%), indicating an epigenetically dysregulated maturation process for DS patients. Across sample types, we observed significant alterations in relative cell-type proportions for DS subjects compared with the controls. Cell-type proportion alterations were present in samples from early development and adulthood. Our findings provide insight into DS cellular biology and suggest potential cellular interventional targets for DS.

DNA methylation age at birth and childhood: performance of epigenetic clocks and characteristics associated with epigenetic age acceleration in the Project Viva cohort

BACKGROUND

Epigenetic 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.

RESULTS

Bohlin 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.

CONCLUSIONS

Maternal 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.

Maternal and Paternal Dietary Quality and Dietary Inflammation Associations with Offspring DNA Methylation and Epigenetic Biomarkers of Aging in the Lifeways Cross-Generation Study

BACKGROUND

Early-life nutritional exposures may contribute to offspring epigenetic modifications. However, few studies have evaluated parental dietary quality effects on offspring DNA methylation (DNAm).

OBJECTIVES

We aim to fill this gap by elucidating the influence of maternal and paternal whole-diet quality and inflammatory potential on offspring DNAm in the Lifeways Cross-generation cohort.

METHODS

Families (n = 1124) were recruited around 16 weeks of gestation in the Republic of Ireland between 2001 and 2003. Maternal dietary intake during the first trimester and paternal diet during the 12 previous months were assessed with an FFQ. Parental dietary inflammatory potential and quality were determined using the energy-adjusted Dietary Inflammatory Index (E-DII), the Healthy Eating Index-2015 (HEI-2015), and the maternal DASH score. DNAm in the saliva of 246 children at age nine was measured using the Illumina Infinium HumanMethylationEPIC array. DNAm-derived biomarkers of aging, the Pediatric-Buccal-Epigenetic clock and DNAm estimator of telomere length, were calculated. Parental diet associations with the DNAm concentrations of 850K Cytosine-phosphate-guanine sites (CpG sites) and with DNAm-derived biomarkers of aging were examined using an epigenome-wide association study and linear regressions, respectively.

RESULTS

Maternal HEI-2015 scores were inversely associated with DNAm at CpG site (cg21840035) located near the PLEKHM1 gene, whose functions involve regulation of bone development (β = -0.0036, per 1 point increase in the score; P = 5.6 × 10-8). Higher paternal HEI-2015 score was related to lower methylation at CpG site (cg22431767), located near cell signaling gene LUZP1 (β = -0.0022, per 1 point increase in the score, P = 4.1 × 10-8). There were no associations with parental E-DII and DASH scores, and no evidence of major effects on biomarkers of aging.

CONCLUSIONS

Parental dietary quality in the prenatal period, evaluated by the HEI-2015, may influence offspring DNAm during childhood. Further research to improve our understanding of parental nutritional programming is warranted.

Refining epigenetic prediction of chronological and biological age

BACKGROUND

Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture.

METHODS

First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women's Health Initiative study).

RESULTS

Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10-52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10-60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations.

CONCLUSIONS

The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age.

DNA methylation-based age estimation for adults and minors: considering sex-specific differences and non-linear correlations

DNA methylation patterns change during human lifetime; thus, they can be used to estimate an individual's age. It is known, however, that correlation between DNA methylation and aging might not be linear and that the sex might influence the methylation status. In this study, we conducted a comparative evaluation of linear and several non-linear regressions, as well as sex-specific versus unisex models. Buccal swab samples from 230 donors aged 1 to 88 years were analyzed using a minisequencing multiplex array. Samples were divided into a training set (n = 161) and a validation set (n = 69). The training set was used for a sequential replacement regression and a simultaneous 10-fold cross-validation. The resulting model was improved by including a cut-off of 20 years, dividing the younger individuals with non-linear from the older individuals with linear dependence between age and methylation status. Sex-specific models were developed and improved prediction accuracy in females but not in males, which might be explained by a small sample set. We finally established a non-linear, unisex model combining the markers EDARADD, KLF14, ELOVL2, FHL2, C1orf132, and TRIM59. While age- and sex-adjustments did not generally improve the performance of our model, we discuss how other models and large cohorts might benefit from such adjustments. Our model showed a cross-validated MAD and RMSE of 4.680 and 6.436 years in the training set and of 4.695 and 6.602 years in the validation set, respectively. We briefly explain how to apply the model for age prediction.

Integrative Approaches of DNA Methylation Patterns According to Age, Sex and Longitudinal Changes

Background

In humans, age-related DNA methylation has been studied in blood, tissues, buccal swabs, and fibroblasts, and changes in DNA methylation patterns according to age and sex have been detected. To date, approximately 137,000 samples have been analyzed from 14,000 studies, and the information has been uploaded to the NCBI GEO database.

Methods

A correlation between age and methylation level and longitudinal changes in methylation levels was revealed in both sexes. Here, 20 public datasets derived from whole blood were analyzed using the Illumina BeadChip. Batch effects with respect to the time differences were correlated. The overall change in the pattern was provided as the inverse of the coefficient of variation (COV).

Results

Of the 20 datasets, nine were from a longitudinal study. All data had age and sex as common variables. Comprehensive details of age-, sex-, and longitudinal change-based DNA methylation levels in the whole blood sample were elucidated in this study. ELOVL2 and FHL2 showed the maximum correlation between age and DNA methylation. The methylation patterns of genes related to mental health differed according to age. Age-correlated genes have been associated with malformations (anteverted nostril, craniofacial abnormalities, and depressed nasal bridge) and drug addiction (drug habituation and smoking).

Conclusion

Based on 20 public DNA methylation datasets, methylation levels according to age and longitudinal changes by sex were identified and visualized using an integrated approach. The results highlight the molecular mechanisms underlying the association of sex and biological age with changes in DNA methylation, and the importance of optimal genomic information management.

Long-term impact of paediatric critical illness on the difference between epigenetic and chronological age in relation to physical growth

BACKGROUND

Altered DNA-methylation affects biological ageing in adults and developmental processes in children. DNA-methylation is altered by environmental factors, trauma and illnesses. We hypothesised that paediatric critical illness, and the nutritional management in the paediatric intensive care unit (PICU), affects DNA-methylation changes that underly the developmental processes of childhood ageing.

RESULTS

We studied the impact of critical illness, and of the early use of parenteral nutrition (early-PN) versus late-PN, on "epigenetic age-deviation" in buccal mucosa of 818 former PICU-patients (406 early-PN, 412 late-PN) who participated in the 2-year follow-up of the multicentre PEPaNIC-RCT (ClinicalTrials.gov-NCT01536275), as compared with 392 matched healthy children, and assessed whether this relates to their impaired growth. The epigenetic age-deviation (difference between PedBE clock-estimated epigenetic age and chronological age) was calculated. Using bootstrapped multivariable linear regression models, we assessed the impact hereon of critical illness, and of early-PN versus late-PN. As compared with healthy children, epigenetic age of patients assessed 2 years after PICU-admission deviated negatively from chronological age (p < 0.05 in 51% of bootstrapped replicates), similarly in early-PN and late-PN groups. Next, we identified vulnerable subgroups for epigenetic age-deviation using interaction analysis. We revealed that DNA-methylation age-deceleration in former PICU-patients was dependent on age at time of illness (p < 0.05 for 83% of bootstrapped replicates), with vulnerability starting from 6 years onwards. Finally, we assessed whether vulnerability to epigenetic age-deviation could be related to impaired growth from PICU-admission to follow-up at 2 and 4 years. Multivariable repeated measures ANOVA showed that former PICU-patients, as compared with healthy children, grew less in height (p = 0.0002) and transiently gained weight (p = 0.0003) over the 4-year time course. Growth in height was more stunted in former PICU-patients aged ≥ 6-years at time of critical illness (p = 0.002) than in the younger patients.

CONCLUSIONS

As compared with healthy children, former PICU-patients, in particular those aged ≥ 6-years at time of illness, revealed epigenetic age-deceleration, with a physical correlate revealing stunted growth in height. Whether this vulnerability around the age of 6 years for epigenetic age-deceleration and stunted growth years later relates to altered endocrine pathways activated at the time of adrenarche requires further investigation.

Maternal Periconceptional Folic Acid Supplementation and DNA Methylation Patterns in Adolescent Offspring

BACKGROUND

Folate, including the folic acid form, is a key component of the one-carbon metabolic pathway used for DNA methylation. Changes in DNA methylation patterns during critical development periods are associated with disease outcomes and are associated with changes in nutritional status in pregnancy. The long-term impact of periconceptional folic acid supplementation on DNA methylation patterns is unknown.

OBJECTIVES

To determine the long-term impact of periconceptional folic acid supplementation on DNA methylation patterns, we examined the association of the recommended dosage (400 μg/d) and time period (periconceptional before pregnancy through first trimester) of folic acid supplementation with the DNA methylation patterns in the offspring at age 14-17 y compared with offspring with no supplementation.

METHODS

Two geographic sites in China from the 1993-1995 Community Intervention Program of folic acid supplementation were selected for the follow-up study. DNA methylation at 402,730 CpG sites was assessed using saliva samples from 89 mothers and 179 adolescents (89 male). The mean age at saliva collection was 40 y among mothers (range: 35-54 y) and 15 y among adolescents (range: 14-17 y). Epigenome-wide analyses were conducted to assess the interactions of periconceptional folic acid exposure, the 5,10-methylenetetrahydrofolate reductase (MTHFR)-C677T genotype, and epigenome-wide DNA methylation controlling for offspring sex, geographic region, and background cell composition in the saliva.

RESULTS

In the primary outcome, no significant differences were observed in epigenome-wide methylation patterns between adolescents exposed and those non-exposed to maternal periconceptional folic acid supplementation after adjustment for potential confounders [false discovery rate (FDR) P values < 0.05]. The MTHFR-C677T genotype did not modify this lack of association (FDR P values < 0.05).

CONCLUSIONS

Overall, there were no differences in DNA methylation between adolescents who were exposed during the critical developmental window and those not exposed to the recommended periconceptional/first-trimester dosage of folic acid.

Associations between accelerated parental biologic age, autism spectrum disorder, social traits, and developmental and cognitive outcomes in their children

Parental age is a known risk factor for autism spectrum disorder (ASD), however, studies to identify the biologic changes underpinning this association are limited. In recent years, "epigenetic clock" algorithms have been developed to estimate biologic age and to evaluate how the epigenetic aging impacts health and disease. In this study, we examined the relationship between parental epigenetic aging and their child's prospective risk of ASD and autism related quantitative traits in the Early Autism Risk Longitudinal Investigation study. Estimates of epigenetic age were computed using three robust clock algorithms and DNA methylation measures from the Infinium HumanMethylation450k platform for maternal blood and paternal blood specimens collected during pregnancy. Epigenetic age acceleration was defined as the residual of regressing chronological age on epigenetic age while accounting for cell type proportions. Multinomial logistic regression and linear regression models were completed adjusting for potential confounders for both maternal epigenetic age acceleration (n = 163) and paternal epigenetic age acceleration (n = 80). We found accelerated epigenetic aging in mothers estimated by Hannum's clock was significantly associated with lower cognitive ability and function in offspring at 12 months, as measured by Mullen Scales of Early Learning scores (β = -1.66, 95% CI: -3.28, -0.04 for a one-unit increase). We also observed a marginal association between accelerated maternal epigenetic aging by Horvath's clock and increased odds of ASD in offspring at 36 months of age (aOR = 1.12, 95% CI: 0.99, 1.26). By contrast, fathers accelerated aging was marginally associated with decreased ASD risk in their offspring (aOR = 0.83, 95% CI: 0.68, 1.01). Our findings suggest epigenetic aging could play a role in parental age risks on child brain development.

Childhood Trauma and Epigenetics: State of the Science and Future

PURPOSE OF REVIEW

There is a great deal of interest regarding the biological embedding of childhood trauma and social exposures through epigenetic mechanisms, including DNA methylation (DNAm), but a comprehensive understanding has been hindered by issues of limited reproducibility between studies. This review presents a summary of the literature on childhood trauma and DNAm, highlights issues in the field, and proposes some potential solutions.

RECENT FINDINGS

Investigations of the associations between DNAm and childhood trauma are commonly performed using candidate gene approaches, specifically involving genes related to neurological and stress pathways. Childhood trauma is defined in a wide range of ways in several societal contexts. However, although variations in DNAm are frequently found in stress-related genes, unsupervised epigenome-wide association studies (EWAS) have shown limited reproducibility both between studies and in relating these changes to exposures. The reproducibility of childhood trauma DNAm studies, and the field of social epigenetics in general, may be improved by increasing sample sizes, standardizing variables, making use of effect size thresholds, collecting longitudinal and intervention samples, appropriately accounting for known confounding factors, and applying causal analysis wherever possible, such as "two-step epigenetic Mendelian randomization."

Association of Pediatric Buccal Epigenetic Age Acceleration With Adverse Neonatal Brain Growth and Neurodevelopmental Outcomes Among Children Born Very Preterm With a Neonatal Infection

IMPORTANCE

Very preterm neonates (24-32 weeks' gestation) remain at a higher risk of morbidity and neurodevelopmental adversity throughout their lifespan. Because the extent of prematurity alone does not fully explain the risk of adverse neonatal brain growth or neurodevelopmental outcomes, there is a need for neonatal biomarkers to help estimate these risks in this population.

OBJECTIVES

To characterize the pediatric buccal epigenetic (PedBE) clock-a recently developed tool to measure biological aging-among very preterm neonates and to assess its association with the extent of prematurity, neonatal comorbidities, neonatal brain growth, and neurodevelopmental outcomes at 18 months of age.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study was conducted in 2 neonatal intensive care units of 2 hospitals in Toronto, Ontario, Canada. A total of 35 very preterm neonates (24-32 weeks' gestation) were recruited in 2017 and 2018, and neuroimaging was performed and buccal swab samples were acquired at 2 time points: the first in early life (median postmenstrual age, 32.9 weeks [IQR, 32.0-35.0 weeks]) and the second at term-equivalent age (TEA) at a median postmenstrual age of 43.0 weeks (IQR, 41.0-46.0 weeks). Follow-ups for neurodevelopmental assessments were completed in 2019 and 2020. All neonates in this cohort had at least 1 infection because they were originally enrolled to assess the association of neonatal infection with neurodevelopment. Neonates with congenital malformations, genetic syndromes, or congenital TORCH (toxoplasmosis, rubella, cytomegalovirus, herpes and other agents) infection were excluded.

EXPOSURES

The extent of prematurity was measured by gestational age at birth and PedBE age difference. PedBE age was computed using DNA methylation obtained from 94 age-informative CpG (cytosine-phosphate-guanosine) sites. PedBE age difference (weeks) was calculated by subtracting PedBE age at each time point from the corresponding postmenstrual age.

MAIN OUTCOMES AND MEASURES

Total cerebral volumes and cerebral growth during the neonatal intensive care unit period were obtained from magnetic resonance imaging scans at 2 time points: approximately the first 2 weeks of life and at TEA. Bayley Scales of Infant and Toddler Development, Third Edition, were used to assess neurodevelopmental outcomes at 18 months.

RESULTS

Among 35 very preterm neonates (21 boys [60.0%]; median gestational age, 27.0 weeks [IQR, 25.9-29.9 weeks]; 23 [65.7%] born extremely preterm [<28 weeks' gestation]), extremely preterm neonates had an accelerated PedBE age compared with neonates born at a later gestational age (β = 9.0; 95% CI, 2.7-15.3; P = .01). An accelerated PedBE age was also associated with smaller cerebral volumes (β = -5356.8; 95% CI, -6899.3 to -2961.7; P = .01) and slower cerebral growth (β = -2651.5; 95% CI, -5301.2 to -1164.1; P = .04); these associations remained significant after adjusting for clinical neonatal factors. These findings were significant at TEA but not earlier in life. Similarly, an accelerated PedBE age at TEA was associated with lower cognitive (β = -0.4; 95% CI, -0.8 to -0.03; P = .04) and language (β = -0.6; 95% CI, -1.1 to -0.06; P = .02) scores at 18 months.

CONCLUSIONS AND RELEVANCE

This cohort study of very preterm neonates suggests that biological aging may be associated with impaired brain growth and neurodevelopmental outcomes. The associations between epigenetic aging and adverse neonatal brain health warrant further attention.

Epigenetic clock: A promising biomarker and practical tool in aging

As a complicated process, aging is characterized by various changes at the cellular, subcellular and nuclear levels, one of which is epigenetic aging. With increasing awareness of the critical role that epigenetic alternations play in aging, DNA methylation patterns have been employed as a measure of biological age, currently referred to as the epigenetic clock. This review provides a comprehensive overview of the epigenetic clock as a biomarker of aging and a useful tool to manage healthy aging. In this burgeoning scientific field, various kinds of epigenetic clocks continue to emerge, including Horvath's clock, Hannum's clock, DNA PhenoAge, and DNA GrimAge. We hereby present the most classic epigenetic clocks, as well as their differences. Correlations of epigenetic age with morbidity, mortality and other factors suggest the potential of epigenetic clocks for risk prediction and identification in the context of aging. In particular, we summarize studies on promising age-reversing interventions, with epigenetic clocks employed as a practical tool in the efficacy evaluation. We also discuss how the lack of higher-quality information poses a major challenge, and offer some suggestions to address existing obstacles. Hopefully, our review will help provide an appropriate understanding of the epigenetic clocks, thereby enabling novel insights into the aging process and how it can be manipulated to promote healthy aging.

Persistent blood DNA methylation changes one year after SARS-CoV-2 infection

We recently reported the COVID-19-induced circulating leukocytes DNA methylation profile. Here, we hypothesized that some of these genes would persist differentially methylated after disease resolution. Fifteen participants previously hospitalized for SARS-CoV-2 infection were epityped one year after discharge. Of the 1505 acute illness-induced differentially methylated regions (DMRs) previously identified, we found 71 regions with persisted differentially methylated, with an average of 7 serial CpG positions per DMR. Sixty-four DMRs persisted hypermethylated, and 7 DMR persisted hypomethylated. These data are the first reported evidence that DNA methylation changes in circulating leukocytes endure long after recovery from acute illness.

Immunosenescence: A Critical Factor Associated With Organ Injury After Sepsis

Progressive immune dysfunction associated with aging is known as immunosenescence. The age-related deterioration of immune function is accompanied by chronic inflammation and microenvironment changes. Immunosenescence can affect both innate and acquired immunity. Sepsis is a systemic inflammatory response that affects parenchymal organs, such as the respiratory system, cardiovascular system, liver, urinary system, and central nervous system, according to the sequential organ failure assessment (SOFA). The initial immune response is characterized by an excess release of inflammatory factors, followed by persistent immune paralysis. Moreover, immunosenescence was found to complement the severity of the immune disorder following sepsis. Furthermore, the immune characteristics associated with sepsis include lymphocytopenia, thymus degeneration, and immunosuppressive cell proliferation, which are very similar to the characteristics of immunosenescence. Therefore, an in-depth understanding of immunosenescence after sepsis and its subsequent effects on the organs may contribute to the development of promising therapeutic strategies. This paper focuses on the characteristics of immunosenescence after sepsis and rigorously analyzes the possible underlying mechanism of action. Based on several recent studies, we summarized the relationship between immunosenescence and sepsis-related organs. We believe that the association between immunosenescence and parenchymal organs might be able to explain the delayed consequences associated with sepsis.

DNA Methylation Episignatures in Neurodevelopmental Disorders Associated with Large Structural Copy Number Variants: Clinical Implications

Large structural chromosomal deletions and duplications, referred to as copy number variants (CNVs), play a role in the pathogenesis of neurodevelopmental disorders (NDDs) through effects on gene dosage. This review focuses on our current understanding of genomic disorders that arise from large structural chromosome rearrangements in patients with NDDs, as well as difficulties in overlap of clinical presentation and molecular diagnosis. We discuss the implications of epigenetics, specifically DNA methylation (DNAm), in NDDs and genomic disorders, and consider the implications and clinical impact of copy number and genomic DNAm testing in patients with suspected genetic NDDs. We summarize evidence of global methylation episignatures in CNV-associated disorders that can be used in the diagnostic pathway and may provide insights into the molecular pathogenesis of genomic disorders. Finally, we discuss the potential for combining CNV and DNAm assessment into a single diagnostic assay.

Altered DNA methylation at age-associated CpG sites in children with growth disorders: impact on age estimation?

Age estimation based on DNA methylation (DNAm) can be applied to children, adolescents and adults, but many CG dinucleotides (CpGs) exhibit different kinetics of age-associated DNAm across these age ranges. Furthermore, it is still unclear how growth disorders impact epigenetic age predictions, and this may be particularly relevant for a forensic application. In this study, we analyzed buccal mucosa samples from 95 healthy children and 104 children with different growth disorders. DNAm was analysed by pyrosequencing for 22 CpGs in the genes PDE4C, ELOVL2, RPA2, EDARADD and DDO. The relationship between DNAm and age in healthy children was tested by Spearman's rank correlation. Differences in DNAm between the groups "healthy children" and the (sub-)groups of children with growth disorders were tested by ANCOVA. Models for age estimation were trained (1) based on the data from 11 CpGs with a close correlation between DNAm and age (R ≥ 0.75) and (2) on five CpGs that also did not present significant differences in DNAm between healthy and diseased children. Statistical analysis revealed significant differences between the healthy group and the group with growth disorders (11 CpGs), the subgroup with a short stature (12 CpGs) and the non-short stature subgroup (three CpGs). The results are in line with the assumption of an epigenetic regulation of height-influencing genes. Age predictors trained on 11 CpGs with high correlations between DNAm and age revealed higher mean absolute errors (MAEs) in the group of growth disorders (mean MAE 2.21 years versus MAE 1.79 in the healthy group) as well as in the short stature (sub-)groups; furthermore, there was a clear tendency for overestimation of ages in all growth disorder groups (mean age deviations: total growth disorder group 1.85 years, short stature group 1.99 years). Age estimates on samples from children with growth disorders were more precise when using a model containing only the five CpGs that did not present significant differences in DNAm between healthy and diseased children (mean age deviations: total growth disorder group 1.45 years, short stature group 1.66 years). The results suggest that CpGs in genes involved in processes relevant for growth and development should be avoided in age prediction models for children since they may be sensitive for alterations in the DNAm pattern in cases of growth disorders.

Prenatal exposure to phthalates and peripheral blood and buccal epithelial DNA methylation in infants: An epigenome-wide association study

BACKGROUND

Prenatal exposure to phthalates has been associated with adverse health and neurodevelopmental outcomes. DNA methylation (DNAm) alterations may be a mechanism underlying these effects, but prior investigations of prenatal exposure to phthalates and neonatal DNAm profiles are limited to placental tissue and umbilical cord blood.

OBJECTIVE

Conduct an epigenome-wide association study (EWAS) of the associations between prenatal exposure to phthalates and DNAm in two accessible infant tissues, venous buffy coat blood and buccal epithelial cells (BECs).

METHODS

Participants included 152 maternal-infant pairs from the Alberta Pregnancy Outcomes and Nutrition (APrON) study. Maternal second trimester urine samples were analyzed for nine phthalate metabolites. Blood (n = 74) or BECs (n = 78) were collected from 3-month-old infants and profiled for DNAm using the Infinium HumanMethylation450 (450K) BeadChip. Robust linear regressions were used to investigate the associations between high (HMWPs) and low molecular weight phthalates (LMWPs) and change in methylation levels at variable Cytosine-phosphate-Guanine (CpG) sites in infant tissues, as well as the sensitivity of associations to potential confounders.

RESULTS

One candidate CpG in gene RNF39 reported by a previous study examining prenatal exposure to phthalates and cord blood DNAm was replicated. The EWAS identified 12 high-confidence CpGs in blood and another 12 in BECs associated with HMWPs and/or LMWPs. Prenatal exposure to bisphenol A (BPA) associated with two of the CpGs associated with HMWPs in BECs.

DISCUSSION

Prenatal exposure to phthalates was associated with DNAm variation at CpGs annotated to genes associated with endocrine hormone activity (i.e., SLCO4A1, TPO), immune pathways and DNA damage (i.e., RASGEF1B, KAZN, HLA-A, MYO18A, DIP2C, C1or109), and neurodevelopment (i.e., AMPH, NOTCH3, DNAJC5). Future studies that characterize the stability of these associations in larger samples, multiple cohorts, across tissues, and investigate the potential associations between these biomarkers and relevant health and neurodevelopmental outcomes are needed.

Pseudotime Analysis Reveals Exponential Trends in DNA Methylation Aging with Mortality Associated Timescales

The epigenetic trajectory of DNA methylation profiles has a nonlinear relationship with time, reflecting rapid changes in DNA methylation early in life that progressively slow with age. In this study, we use pseudotime analysis to determine the functional form of these trajectories. Unlike epigenetic clocks that constrain the functional form of methylation changes with time, pseudotime analysis orders samples along a path, based on similarities in a latent dimension, to provide an unbiased trajectory. We show that pseudotime analysis can be applied to DNA methylation in human blood and brain tissue and find that it is highly correlated with the epigenetic states described by the Epigenetic Pacemaker. Moreover, we show that the pseudotime trajectory can be modeled with respect to time, using a sum of two exponentials, with coefficients that are close to the timescales of human age-associated mortality. Thus, for the first time, we can identify age-associated molecular changes that appear to track the exponential dynamics of mortality risk.

Epigenetic regulation of pediatric and neonatal immune responses

Epigenetic regulation of transcription is a collective term that refers to mechanisms known to regulate gene transcription without changing the underlying DNA sequence. These mechanisms include DNA methylation and histone tail modifications which influence chromatin accessibility, and microRNAs that act through post-transcriptional gene silencing. Epigenetics is known to regulate a variety of biological processes, and the role of epigtenetics in immunity and immune-mediated diseases is becoming increasingly recognized. While DNA methylation is the most widely studied, each of these systems play an important role in the development and maintenance of appropriate immune responses. There is clear evidence that epigenetic mechanisms contribute to developmental stage-specific immune responses in a cell-specific manner. There is also mounting evidence that prenatal exposures alter epigenetic profiles and subsequent immune function in exposed offspring. Early life exposures that are associated with poor long-term health outcomes also appear to impact immune specific epigenetic patterning. Finally, each of these epigenetic mechanisms contribute to the pathogenesis of a wide variety of diseases that manifest during childhood. This review will discuss each of these areas in detail. IMPACT: Epigenetics, including DNA methylation, histone tail modifications, and microRNA expression, dictate immune cell phenotypes. Epigenetics influence immune development and subsequent immune health. Prenatal, perinatal, and postnatal exposures alter immune cell epigenetic profiles and subsequent immune function. Numerous pediatric-onset diseases have an epigenetic component. Several successful strategies for childhood diseases target epigenetic mechanisms.

Perspectives and challenges of epigenetic determinants of childhood obesity: A systematic review

The tremendous increase in childhood obesity prevalence over the last few decades cannot merely be explained by genetics and evolutionary changes in the genome, implying that gene-environment interactions, such as epigenetic modifications, likely play a major role. This systematic review aims to summarize the evidence of the association between epigenetics and childhood obesity. A literature search was performed via PubMed and Scopus engines using a combination of terms related to epigenetics and pediatric obesity. Articles studying the association between epigenetic mechanisms (including DNA methylation and hydroxymethylation, non-coding RNAs, and chromatin and histones modification) and obesity and/or overweight (or any related anthropometric parameters) in children (0-18 years) were included. The risk of bias was assessed with a modified Newcastle-Ottawa scale for non-randomized studies. One hundred twenty-one studies explored epigenetic changes related to childhood obesity. DNA methylation was the most widely investigated mechanism (N = 101 studies), followed by non-coding RNAs (N = 19 studies) with evidence suggestive of an association with childhood obesity for DNA methylation of specific genes and microRNAs (miRNAs). One study, focusing on histones modification, was identified. Heterogeneity of findings may have hindered more insights into the epigenetic changes related to childhood obesity. Gaps and challenges that future research should face are herein described.

Exploring the Contribution of Proximal Family Risk Factors on SLC6A4 DNA Methylation in Children with a History of Maltreatment: A Preliminary Study

The cumulative effects of proximal family risk factors have been associated with a high number of adverse outcomes in childhood maltreatment, and DNA methylation of the serotonin transporter gene (SLC6A4) has been associated with child maltreatment. However, the relationships between proximal family risk factors and SLC6A4 methylation remains unexplored. We examined the association among cumulative family risk factors, maltreatment experiences and DNA methylation in the SLC6A4 gene in a sample of 33 child victims of maltreatment. We computed a cumulative family risk (CFR) index that included proximal family risk factors, such as drug or alcohol abuse, psychopathology, parents’ experiences of maltreatment/abuse in childhood, criminal history, and domestic violence. The majority of children (90.9%) experienced more than one type of maltreatment. Hierarchical regression models suggested that the higher the CFR index score and the number of maltreatment experiences, and the older the children, the higher the SLC6A4 DNA methylation levels. Although preliminary, our findings suggest that, along with childhood maltreatment experiences per se, cumulative proximal family risk factors are seemingly critically associated with DNA methylation at the SLC6A4 gene.