Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels

The association of prenatal ambient air pollution with placental epigenetic gestational age at birth

Background

Prenatal air pollutants have been associated with adverse birth outcomes, and DNA methylation (DNAm) changes in placenta may contribute to these associations. DNAm-based epigenetic gestational age (GA) estimators are emerging biomarkers for aging/biological age that can reflect early-life exposures and predict long-term health outcomes. We leveraged 103 mother-offspring pairs from the Early Autism Risk Longitudinal Investigation cohort to assess associations between prenatal air pollution and placental epigenetic GA at birth.

Methods

Prenatal air pollution concentrations (NO2, O3, PM2.5, and PM10) were estimated from weekly data from monitoring stations near maternal residence and calculated for preconception and pregnancy periods. DNAm from fetal-side placenta samples was measured on Illumina HumanMethylation450 BeadChip. Epigenetic GA was computed using Lee's robust placenta clock algorithm. GA acceleration/deceleration was the residual of predicted epigenetic GA on chronologic GA, adjusted (intrinsic) or unadjusted (extrinsic) for cell type proportions. We used linear regressions to examine associations between average air pollution levels in each period and GA acceleration/deceleration, and weekly distributed lag models to examine critical exposure windows.

Results

Higher pregnancy average O3 and PM10 exposures were associated with decelerated intrinsic (β = -0.65 and -0.79) and extrinsic GA (β = -0.69 and -0.74) at birth (per 10-unit increment). Trimester-specific analyses revealed higher O3 and PM10 exposures in trimesters 2 to 3 associated with decelerated GA at birth. Weekly distributed lag models suggested pregnancy weeks 21 to 31 and 21 to 29 were critical windows of O3 and PM10 exposures, respectively.

Conclusions

Prenatal air pollution exposures, especially during mid- to late-pregnancy, were associated with lower biological maturity at birth.

Chemical and climatic environmental exposures and epigenetic aging: A systematic review

Epigenetic aging biomarkers are used for evaluating morbidity and mortality, monitoring therapies, and direct-to-consumer testing. However, the influence of environmental exposures on epigenetic age acceleration (EAA), also known as epigenetic age deviation, has not been systematically evaluated. In this systematic review, we synthesized findings from human epidemiologic studies on chemical and climatic environmental exposures, particularly air pollution, chemicals, metals, climate, and cigarette smoke, and EAA. A total of 102 studies analyzing epigenetic data from over 180,000 subjects were evaluated. Overall, studies in each exposure category frequently included adult participants, used a variety of epigenetic clocks, analyzed whole blood samples, and had a low risk of bias. Exposure to air pollution (15/19 of studies; 79%), cigarette smoke (53/66; 80%), and synthetic and occupational chemicals (5/8; 63%) were notably associated with increased EAA. Results for essential and non-essential metal exposure were more equivocal: 7/13 studies (54%) reported increased EAA. One study reported increased EAA with greater temperature exposure. In summary, we identified environmental exposures, such as air pollution and cigarette smoke, that were strongly associated with increased EAA. Further research is needed with larger and more diverse samples and high-quality exposure assessment.

Placental epigenetic age and adolescent blood pressure: the Extremely Low Gestational Age Newborn cohort

BACKGROUND

We examined the association between placental epigenetic gestational age (eGA) acceleration and adolescent systolic blood pressure (SBP) in a cohort born extremely preterm.

METHODS

Study participants were a subset of the Extremely Low Gestational Age Newborn cohort (born <28 weeks' gestation) who had placental DNA methylation quantified and had SBP measured during adolescent follow-up. eGA acceleration was calculated as the residual from the regression of predicted placental eGA (using the Robust Placental Clock) onto chronological gestational age. Unadjusted and adjusted mixed effects models were used to test the association between eGA acceleration and adolescent SBP. We also tested the interaction of eGA acceleration and sex on SBP.

RESULTS

In the overall sample (N = 193), we found no association between placental eGA acceleration and adolescent SBP. When interaction between eGA acceleration and sex was tested, males had a 3.6 mmHg increase in SBP (95% CI 0.9, 6.4; p = 0.01) for every 1-week acceleration in eGA after adjusting for confounders.

CONCLUSION

Placental eGA acceleration is associated with SBP increase in adolescent males but not females born extremely preterm, supporting the hypothesis that placental eGA could be evaluated as a risk biomarker for childhood cardiovascular outcomes.

IMPACT

This study examines the association between placental epigenetic gestational age (eGA) and adolescent blood pressure. For every 1-week acceleration in placental eGA, adolescent males born extremely preterm had a 3.6 mmHg increase in systolic blood pressure (95% CI 0.9, 6.4; p = 0.01) after adjusting for confounders. The same association was not seen in females or the overall cohort. Our sex-specific finding supports the hypothesis that differences in placental eGA are associated with childhood health. Placental eGA estimation as a tool for identifying children who are at risk for developing elevated blood pressure should be further evaluated in other cohorts.

Sex-specific effects of in utero exposure to per- and polyfluoroalkyl substances on placental development

BACKGROUND

Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants that may impact placental function, and potentially gestational age acceleration (GAA), a deviation from reported and predicted gestational age. GAA potentially represents differences in cell maturation in response to a challenging environment.

OBJECTIVE

This study aimed to characterize the effects of individual and mixtures of PFAS on GAA, cell composition, birth length, and birthweight.

METHODS

Pregnant peoples were recruited from around Little Rock, Arkansas, United States between 2011 and 2014. We utilized placental DNA methylation profiles of 153 healthy pregnancies to calculate GAA and estimate the proportions of six placental cell types. PFAS were quantified in homogenized placental tissue using high-performance liquid chromatography-tandem mass spectrometry. Five PFAS were detected in over 70% of samples. We studied these five PFAS individually using multiple linear regression and as a mixture using quantile g-computation, while adjusting for confounders. The dependent variables in our models included GAA, cell proportions, birthweight, and birth length.

RESULTS

We did not observe associations between PFAS and any of our outcomes in our primary models. While GAA in male placentas were not significantly affected by PFAS, the PFAS mixture associated with decreased syncytiotrophoblast proportion (Ψ = -0.018, 95% CI [-0.032, -0.004]). PFAS mixture did not alter cell proportions in female placentas but was associated with increased GAA (Ψ = 0.269, 95% CI [0.026, 0.513]). Similarly, for females, greater GAA was associated with PFOA (β = 0.141, 95% CI [-0.016,0.040]) and PFOS (β = 0.205, 95% CI [-0.020,0.0416]).

DISCUSSION

We illustrate that PFAS may influence placental development in a sex specific manner. Suggested by decrease in syncytotrophoblast, male placenta may experience a more stunted development due to PFAS exposure. Alternatively, female placentas exhibited increased GAA, a plausible marker of elevated developmental maturation in the face of environmental adversity.

Quantification of Epigenetic Aging in Public Health

Estimators of biological age hold promise for use in preventive medicine, for early detection of chronic conditions, and for monitoring the effectiveness of interventions aimed at improving population health. Among the promising biomarkers in this field are DNA methylation-based biomarkers, commonly referred to as epigenetic clocks. This review provides a survey of these clocks, with an emphasis on second-generation clocks that predict human morbidity and mortality. It explores the validity of epigenetic clocks when considering factors such as race, sex differences, lifestyle, and environmental influences. Furthermore, the review addresses the current challenges and limitations in this research area.

Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders

Increasing evidence supports the role of the placenta in neurodevelopment and in the onset of neuropsychiatric disorders. Recently, mQTL and iQTL maps have proven useful in understanding relationships between SNPs and GWAS that are not captured by eQTL. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation. We construct a public placental cis-mQTL database including 214,830 CpG sites calculated in 368 fetal placenta DNA samples from the INMA project, and run cell type-, gestational age- and sex-imQTL models. We combine these data with summary statistics of GWAS on ten neuropsychiatric disorders using summary-based Mendelian randomization and colocalization. We also evaluate the influence of identified DNA methylation sites on placental gene expression in the RICHS cohort. We find that placental cis-mQTLs are enriched in placenta-specific active chromatin regions, and establish that part of the genetic burden for schizophrenia, bipolar disorder, and major depressive disorder confers risk through placental DNA methylation. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, the involvement of cell type-imQTLs, and the correlation of identified DNA methylation sites with the expression levels of relevant genes in the placenta.

Breaking rules: the complex relationship between DNA methylation and X-chromosome inactivation in the human placenta

BACKGROUND

The human placenta is distinct from most organs due to its uniquely low-methylated genome. DNA methylation (DNAme) is particularly depleted in the placenta at partially methylated domains and on the inactive X chromosome (Xi) in XX samples. While Xi DNAme is known to be critical for X-chromosome inactivation (XCI) in other tissues, its role in the placenta remains unclear. Understanding X-linked DNAme variation in the placenta may provide insights into XCI and have implications for prenatal development and phenotypic sex differences.

METHODS

DNAme data were analyzed from over 350 human placental (chorionic villus) samples, along with samples from cord blood, amnion and chorion placental membranes, and fetal somatic tissues. We characterized X chromosome DNAme variation in the placenta relative to sample variables including cell composition, ancestry, maternal age, placental weight, and fetal birth weight, and compared these patterns to other tissues. We also evaluated the relationship between X-linked DNAme and previously reported XCI gene expression status in placenta.

RESULTS

Our findings confirm that the placenta exhibits significant depletion of DNAme on the Xi compared to other tissues. Additionally, we observe that X chromosome DNAme profiles in the placenta are influenced by cell composition, particularly trophoblast proportion, with minimal DNAme variation across gestation. Notably, low promoter DNAme is observed at most genes on the Xi regardless of XCI status, challenging known associations in somatic tissues between low promoter DNAme and escape from XCI.

CONCLUSIONS

This study provides evidence that the human placenta has a distinct Xi DNAme landscape, which may inform our understanding of sex differences during prenatal development. Future research should explore the mechanisms underlying the placenta's unique X-linked DNAme profile, and the factors involved in placental XCI maintenance.

Genome-wide methylation profiling of maternal cell-free DNA using methylated DNA sequencing (MeD-seq) indicates a placental and immune-cell signature

BACKGROUND

Placental-originated cell-free DNA (cfDNA) provides unique opportunities to study (epi)genetic placental programming remotely, but studies investigating the cfDNA methylome are scarce and usually technologically challenging. Methylated DNA sequencing (MeD-seq) is well compatible with low cfDNA concentrations and has a high genome-wide coverage. We therefore aim to investigate the feasibility of genome-wide methylation profiling of first trimester maternal cfDNA using MeD-seq, by identifying placental-specific methylation marks in cfDNA.

METHODS

We collected cfDNA from nonpregnant controls (female n = 6, male n = 12) and pregnant women (n = 10), first trimester placentas (n = 10), and paired preconceptional and first trimester buffy coats (total n = 20). Differentially methylated regions (DMRs) were identified between pregnant and nonpregnant women. We investigated placental-specific markers in maternal cfDNA, including RASSF1 promoter and Y-chromosomal methylation, and studied overlap with placental and buffy coat DNA methylation.

RESULTS

We identified 436 DMRs between cfDNA from pregnant and nonpregnant women, which were validated using male cfDNA. RASSF1 promoter methylation was higher in maternal cfDNA (fold change 2.87, unpaired t-test p < .0001). Differential methylation of Y-chromosomal sequences could determine fetal sex. DMRs in maternal cfDNA showed large overlap with DNA methylation of these regions in placentas and buffy coats. Sixteen DMRs in maternal cfDNA were specifically found only in placentas. These novel potential placental-specific DMRs were more prominent than RASSF1.

CONCLUSIONS

MeD-seq can detect (novel) genome-wide placental DNA methylation marks and determine fetal sex in maternal cfDNA. Our results indicate a placental and immune-cell contribution to the pregnancy-specific cfDNA methylation signature. This study supports future research into maternal cfDNA methylation.

DNA methylation biomarkers of intellectual/developmental disability across the lifespan

Epigenetic mechanisms, including DNA methylation, act at the interface of genes and environment by allowing a static genome to respond and adapt to a dynamic environment during the lifespan of an individual. Genome-wide DNA methylation analyses on a wide range of human biospecimens are beginning to identify epigenetic biomarkers that can predict risk of intellectual/developmental disabilities (IDD). DNA methylation-based epigenetic signatures are becoming clinically useful in categorizing benign from pathogenic genetic variants following exome sequencing. While DNA methylation marks differ by tissue source, recent studies have shown that accessible perinatal tissues, such as placenta, cord blood, newborn blood spots, and cell free DNA may serve as accessible surrogate tissues for testing epigenetic biomarkers relevant to understanding genetic, environmental, and gene by environment interactions on the developing brain. These DNA methylation signatures may also provide important information about the biological pathways that become dysregulated prior to disease progression that could be used to develop early pharmacological interventions. Future applications could involve preventative screenings using DNA methylation biomarkers during pregnancy or the newborn period for IDDs and other neurodevelopmental disorders. DNA methylation biomarkers in adolescence and adulthood are also likely to be clinically useful for tracking biological aging or co-occurring health conditions that develop across the lifespan. In conclusion, DNA methylation biomarkers are expected to become more common in clinical diagnoses of IDD, to improve understanding of complex IDD etiologies, to improve endpoints for clinical trials, and to monitor potential health concerns for individuals with IDD as they age.

Prenatal Exposure to Metals Is Associated with Placental Decelerated Epigenetic Gestational Age in a Sex-Dependent Manner in Infants Born Extremely Preterm

Prenatal exposure to metals can influence fetal programming via DNA methylation and has been linked to adverse birth outcomes and long-term consequences. Epigenetic clocks estimate the biological age of a given tissue based on DNA methylation and are potential health biomarkers. This study leveraged the Extremely Low Gestational Age Newborn (ELGAN) study (n = 265) to evaluate associations between umbilical cord tissue concentrations of 11 metals as single exposures as well as mixtures in relation to (1) placental epigenetic gestational age acceleration (eGAA) and the (2) methylation status of the Robust Placental Clock (RPC) CpGs. Linear mixed effect regression models were stratified by infant sex. Both copper (Cu) and manganese (Mn) were significantly associated with a decelerated placental eGA of -0.98 (95% confidence interval (CI): -1.89, -0.07) and -0.90 weeks (95% CI: -1.78, -0.01), respectively, in male infants. Cu and Mn levels were also associated with methylation at RPC CpGs within genes related to processes including energy homeostasis and inflammatory response in placenta. Overall, these findings suggest that prenatal exposures to Cu and Mn impact placental eGAA in a sex-dependent manner in ELGANs, and future work could examine eGAA as a potential mechanism mediating in utero metal exposures and later life consequences.

Longitudinal maternal glycemia during pregnancy and placental epigenetic age acceleration

BACKGROUND

Dysregulation of maternal glucose homeostasis has been related to an increased risk of morbidity and mortality in mothers and fetuses, yet the mechanism remains unclear. This study investigated the association between maternal glycemic levels and placental epigenetic age acceleration (PAA) in a multiethnic cohort.

METHODS

In a sample of 301 pregnant women (102 Hispanic, 77 White, 72 Black, and 50 Asian/Pacific Islander), the association of glycemic markers cumulative exposure with PAA was tested using linear regression adjusting for fetal sex, maternal age, educational status, and health insurance status. Models were applied in the full cohort and stratified by race/ethnicity. Further, sensitivity analyses were performed after excluding women with GDM or preeclampsia.

RESULTS

Among Black women, high glucose, HbA1c, and insulin cumulative exposure levels were associated with lower PAA compared to low cumulative exposure levels (β = - 0.75 weeks, 95% CI = - 1.41 to - 0.08); β = - 0.86, 95% CI = - 1.51 to - 0.21; and β = - 0.76, 95% CI = - 1.49 to - 0.03, respectively). Among Asian/Pacific Islander women, medium insulin cumulative exposure level was associated with lower PAA (β = - 0.94 weeks, 95% CI = - 1.74 to - 0.14). No significant association was observed among White and Hispanic women as well as in the full cohort.

CONCLUSIONS

Elevated glucose, HbA1c, and insulin cumulative levels throughout pregnancy were associated with lower PAA in Black and Asian/Pacific Islander women. Placental epigenetic aging may be altered by maternal elevated glycemia and may in part underlie early programming of health outcomes in pregnancy and childhood health outcomes.

Methylome profiling of cell-free DNA during the early life course in (un)complicated pregnancies using MeD-seq: Protocol for a cohort study embedded in the prospective Rotterdam periconception cohort

INTRODUCTION

Placental DNA methylation differences have been associated with timing in gestation and pregnancy complications. Maternal cell-free DNA (cfDNA) partly originates from the placenta and could enable the minimally invasive study of placental DNA methylation dynamics. We will for the first time longitudinally investigate cfDNA methylation during pregnancy by using Methylated DNA Sequencing (MeD-seq), which is compatible with low cfDNA levels and has an extensive genome-wide coverage. We aim to investigate DNA methylation in placental tissues and cfDNA during different trimesters in uncomplicated pregnancies, and in pregnancies with placental-related complications, including preeclampsia and fetal growth restriction. Identified gestational-age and disease-specific differentially methylated regions (DMRs) could lead to numerous applications including biomarker development.

METHODS AND ANALYSIS

Our study design involves three sub-studies. Sub-study 1 is a single-centre prospective, observational subcohort embedded within the Rotterdam Periconception cohort (Predict study). We will longitudinally collect maternal plasma in each trimester and during delivery, and sample postpartum placentas (n = 300). In sub-study 2, we will prospectively collect first and second trimester placental tissues (n = 10 per trimester). In sub-study 3 we will retrospectively collect plasma after non-invasive prenatal testing (NIPT) in an independent validation case-control cohort (n = 30-60). A methylation-dependent restriction enzyme (LpnPI) will be used to generate DNA fragments followed by sequencing on the Illumina NextSeq2000 platform. DMRs will be identified in placental tissues and cell types, and in cfDNA related to gestational-age or placental-related complications. (Paired) placental methylation profiles will be correlated to DMRs in cfDNA to aid tissue-of-origin analysis. We will establish a methylation score to predict associated diseases.

DISCUSSION

This study will provide insights in placental DNA methylation dynamics in health and disease, and could lead to clinical relevant biomarkers.

Prenatal chemical exposures and the methylome: current evidence and opportunities for environmental epigenetics

Exposure to pollutants and chemicals during critical developmental periods in early life can impact health and disease risk across the life course. Research in environmental epigenetics has provided increasing evidence that prenatal exposures affect epigenetic markers, particularly DNA methylation. In this article, we discuss the role of DNA methylation in early life programming and review evidence linking the intrauterine environment to epigenetic modifications, with a focus on exposure to tobacco smoke, metals, and endocrine-disrupting chemicals. We also discuss challenges and novel approaches in environmental epigenetic research and explore the potential of epigenetic biomarkers in studies of pediatric populations as indicators of exposure and disease risk. Overall, we aim to highlight how advancements in environmental epigenetics may transform our understanding of early-life exposures and inform new approaches for supporting long-term health.

Deciphering DNA Methylation in Gestational Diabetes Mellitus: Epigenetic Regulation and Potential Clinical Applications

Gestational diabetes mellitus (GDM) represents a prevalent complication during pregnancy, exerting both short-term and long-term impacts on maternal and offspring health. This review offers a comprehensive outline of DNA methylation modifications observed in various maternal and offspring tissues affected by GDM, emphasizing the intricate interplay between DNA methylation dynamics, gene expression, and the pathogenesis of GDM. Furthermore, it explores the influence of environmental pollutants, maternal nutritional supplementation, and prenatal gut microbiota on GDM development through alterations in DNA methylation profiles. Additionally, this review summarizes recent advancements in DNA methylation-based diagnostics and predictive models in early GDM detection and risk assessment for subsequent type 2 diabetes. These insights contribute significantly to our understanding of the epigenetic mechanisms underlying GDM development, thereby enhancing maternal and fetal health outcomes and advocating further efforts in this field.

Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology

Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.

Consistent cord blood DNA methylation signatures of gestational age between South Asian and white European cohorts

BACKGROUND

Epigenetic modifications, particularly DNA methylation (DNAm) in cord blood, are an important biological marker of how external exposures during gestation can influence the in-utero environment and subsequent offspring development. Despite the recognized importance of DNAm during gestation, comparative studies to determine the consistency of these epigenetic signals across different ethnic groups are largely absent. To address this gap, we first performed epigenome-wide association studies (EWAS) of gestational age (GA) using newborn cord blood DNAm comparatively in a white European (n = 342) and a South Asian (n = 490) birth cohort living in Canada. Then, we capitalized on established cord blood epigenetic GA clocks to examine the associations between maternal exposures, offspring characteristics and epigenetic GA, as well as GA acceleration, defined as the residual difference between epigenetic and chronological GA at birth.

RESULTS

Individual EWASs confirmed 1,211 and 1,543 differentially methylated CpGs previously reported to be associated with GA, in white European and South Asian cohorts, respectively, with a similar distribution of effects. We confirmed that Bohlin's cord blood GA clock was robustly correlated with GA in white Europeans (r = 0.71; p = 6.0 × 10-54) and South Asians (r = 0.66; p = 6.9 × 10-64). In both cohorts, Bohlin's clock was positively associated with newborn weight and length and negatively associated with parity, newborn female sex, and gestational diabetes. Exclusive to South Asians, the GA clock was positively associated with the newborn ponderal index, while pre-pregnancy weight and gestational weight gain were strongly predictive of increased epigenetic GA in white Europeans. Important predictors of GA acceleration included gestational diabetes mellitus, newborn sex, and parity in both cohorts.

CONCLUSIONS

These results demonstrate the consistent DNAm signatures of GA and the utility of Bohlin's GA clock across the two populations. Although the overall pattern of DNAm is similar, its connections with the mother's environment and the baby's anthropometrics can differ between the two groups. Further research is needed to understand these unique relationships.

methscore: a comprehensive R function for DNA methylation-based health predictors

MOTIVATION

DNA methylation-based predictors of various biological metrics have been widely published and are becoming valuable tools in epidemiologic studies of epigenetics and personalized medicine. However, generating these predictors from original source software and web servers is complex and time consuming. Furthermore, different predictors were often derived based on data from different types of arrays, where array differences and batch effects can make predictors difficult to compare across studies.

RESULTS

We integrate these published methods into a single R function to produce 158 previously published predictors for chronological age, biological age, exposures, lifestyle traits and serum protein levels using both classical and principal component-based methods. To mitigate batch and array differences, we also provide a modified RCP method (ref-RCP) that normalize input DNA methylation data to reference data prior to estimation. Evaluations in real datasets show that this approach improves estimate precision and comparability across studies.

AVAILABILITY AND IMPLEMENTATION

The function was included in software package ENmix, and is freely available from Bioconductor website (https://www.bioconductor.org/packages/release/bioc/html/ENmix.html).

pyaging: a Python-based compendium of GPU-optimized aging clocks

MOTIVATION

Aging is intricately linked to diseases and mortality. It is reflected in molecular changes across various tissues which can be leveraged for the development of biomarkers of aging using machine learning models, known as aging clocks. Despite advancements in the field, a significant challenge remains: the lack of robust, Python-based software tools for integrating and comparing these diverse models. This gap highlights the need for comprehensive solutions that can handle the complexity and variety of data in aging research.

RESULTS

To address this gap, I introduce pyaging, a comprehensive open-source Python package designed to facilitate aging research. pyaging harmonizes dozens of aging clocks, covering a range of molecular data types such as DNA methylation, transcriptomics, histone mark ChIP-Seq, and ATAC-Seq. The package is not limited to traditional model types; it features a diverse array, from linear and principal component models to neural networks and automatic relevance determination models. Thanks to a PyTorch-based backend that enables GPU acceleration, pyaging is capable of rapid inference, even when dealing with large datasets and complex models. In addition, the package's support for multi-species analysis extends its utility across various organisms, including humans, various mammals, and Caenorhabditis elegans.

AVAILABILITY AND IMPLEMENTATION

pyaging is accessible on GitHub, at https://github.com/rsinghlab/pyaging, and the distribution is available on PyPi, at https://pypi.org/project/pyaging/. The software is also archived on Zenodo, at https://zenodo.org/doi/10.5281/zenodo.10335011.

Evidence of reduced gestational age in response to in utero arsenic exposure and implications for aging trajectories of the newborn

Arsenic exposure is associated with a plethora of age-related health outcomes of disparate etiology. However, evidence of the impact of arsenic on aging remains limited. Here, we investigated the utility of epigenetic clocks in two different populations and the impact of maternal arsenic exposure during pregnancy on epigenetic gestational age at birth. To do this, we examined publicly available DNA methylation data and estimated gestational age across five gestational clocks in two unrelated human populations. These populations also differ in the extent of arsenic exposure and the targeted tissue of analysis (cord blood and placental tissue). Our results indicate that same-tissue clocks produce gestational age estimates that are more highly correlated with clinical gestational age. Interestingly, our results also indicate that arsenic exposure is associated with gestational age, with higher arsenic exposures associated with decreased gestational age. We also applied two pediatric clocks to evaluate infant biological age in the same samples. The data is suggestive of higher pediatric age in infants exposed to higher arsenic levels during gestation. Taken altogether, our findings are consistent with past work indicating that that in utero arsenic exposure is associated with decreased gestational maturity as characterized by infant outcomes such as low birthweight and lung underdevelopment and dysfunction in arsenic exposed infants. The findings are also consistent with arsenic exposure setting infants on a trajectory of accelerated epigenetic aging that starts at birth.

DNA methylation as a window into female reproductive aging

People with ovaries experience reproductive aging as their reproductive function and system declines. This has significant implications for both fertility and long-term health, with people experiencing an increased risk of cardiometabolic disorders after menopause. Reproductive aging can be assessed through markers of ovarian reserve, response to fertility treatment or molecular biomarkers, including DNA methylation. Changes in DNA methylation with age associate with poorer reproductive outcomes, and epigenome-wide studies can provide insight into genes and pathways involved. DNA methylation-based epigenetic clocks can quantify biological age in reproductive tissues and systemically. This review provides an overview of hallmarks and theories of aging in the context of the reproductive system, and then focuses on studies of DNA methylation in reproductive tissues.

Placental accelerated aging in antenatal depression

BACKGROUND

Antenatal maternal depression is associated with poor pregnancy outcomes and long-term effects on the offspring. Previous studies have identified links between antenatal depression and placental DNA methylation and between placental epigenetic aging and poor pregnancy outcomes, such as preterm labor and preeclampsia. The relationship between antenatal depression and poor pregnancy outcomes may be partly mediated via placental aging.

OBJECTIVE

This study aimed to investigate whether antenatal depressive symptoms are associated with placental epigenetic age acceleration, an epigenetic aging clock measure derived from the difference between methylation age and gestational age at delivery.

STUDY DESIGN

The study included 301 women who provided placenta samples at delivery as part of the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies - Singletons that recruited participants from diverse race and ethnic groups at 12 US clinical sites (2009-2013). Women underwent depression screening using the Edinburgh Postnatal Depression Scale up to 6 times across the 3 trimesters of pregnancy. Depressive symptoms status was determined for each pregnancy trimester using an Edinburgh Postnatal Depression Scale score, in which a score of ≥10 was defined as having depressive symptoms and a score of <10 was defined as not having depressive symptoms. Placental DNA methylation was profiled from placenta samples. Placental epigenetic age was estimated using a methylation-based age estimator (placental "epigenetic clock") that has previously been found to have high placental gestational age prediction accuracy for uncomplicated term pregnancies. Placental age acceleration was defined to be the residual upon regressing the estimated epigenetic age on gestational age at delivery. Associations between an Edinburgh Postnatal Depression Scale score of ≥10 and an Edinburgh Postnatal Depression Scale score of <10 in the first, second, and third trimesters of pregnancy (ie, depressive symptoms vs none in each trimester) and placental age acceleration were tested using multivariable linear regression adjusting for maternal age, parity, race and ethnicity, and employment.

RESULTS

There were 31 (10.3%), 48 (16%), and 49 (16.4%) women with depressive symptoms (ie, Edinburgh Postnatal Depression Scale score of ≥10) in the first, second, and third trimesters of pregnancy, respectively. Of these women, 21 (7.2%) had sustained first- and second-trimester depressive symptoms, 19 (7%) had sustained second- and third-trimester depressive symptoms, and 12 (4.8%) had sustained depressive symptoms throughout pregnancy. Women with depressive symptoms in the second trimester of pregnancy had 0.41 weeks higher placental age acceleration than women without depressive symptoms during the second trimester of pregnancy (β=0.21 weeks [95% confidence interval, -0.17 to 0.58; P=.28] during the first trimester of pregnancy; β=0.41 weeks [95% confidence interval, 0.10-0.71; P=.009] during the second trimester of pregnancy; β=0.17 weeks [95% confidence interval, -0.14 to 0.47; P=.29] during the third trimester of pregnancy). Sustained first- and second-trimester depressive symptoms were associated with 0.72 weeks higher placental age acceleration (95% confidence interval, 0.29-1.15; P=.001) than no depressive symptom in the 2 trimesters. The association between second-trimester depressive symptoms and higher placental epigenetic age acceleration strengthened in the analysis of pregnancies with male fetuses (β=0.53 weeks; 95% confidence interval, 0.06-1.08; P=.03) but was not significant in pregnancies with female fetuses.

CONCLUSION

Antenatal depressive symptoms during the second trimester of pregnancy were associated with an average of 0.41 weeks of increased placental age acceleration. Accelerated placental aging may play an important role in the underlying mechanism linking antenatal depression to pregnancy complications related to placental dysfunction.

Biological Aging Acceleration Due to Environmental Exposures: An Exciting New Direction in Toxicogenomics Research

Biological clock technologies are designed to assess the acceleration of biological age (B-age) in diverse cell types, offering a distinctive opportunity in toxicogenomic research to explore the impact of environmental stressors, social challenges, and unhealthy lifestyles on health impairment. These clocks also play a role in identifying factors that can hinder aging and promote a healthy lifestyle. Over the past decade, researchers in epigenetics have developed testing methods that predict the chronological and biological age of organisms. These methods rely on assessing DNA methylation (DNAm) levels at specific CpG sites, RNA levels, and various biomolecules across multiple cell types, tissues, and entire organisms. Commonly known as 'biological clocks' (B-clocks), these estimators hold promise for gaining deeper insights into the pathways contributing to the development of age-related disorders. They also provide a foundation for devising biomedical or social interventions to prevent, reverse, or mitigate these disorders. This review article provides a concise overview of various epigenetic clocks and explores their susceptibility to environmental stressors.

Does DNA methylation in the fetal brain leave an epigenetic memory in the blood?

Epigenetic memory is an emerging concept that refers to the process in which epigenetic changes occurring early-in life can lead to long-term programs of gene regulation in time and space. By leveraging neural network regression modeling of DNA methylation data in pigs, we show that specific methylations in the adult blood can reliably predict methylation changes that occurred in the fetal brain. Genes associated with these methylations represented known markers of specific cell types of blood including bone marrow hematopoietic progenitor cells, and ependymal and oligodendrocyte cells of brain. This suggested that methylation changes that occurred in the developing brain were maintained as an epigenetic memory in the blood through the adult life.

Accelerated epigenetic age at birth and child emotional and behavioura development in early childhood: a meta-analysis of four prospective cohort studies in ECHO

Background: 'Epigenetic clocks' have been developed to accurately predict chronologic gestational age and have been associated with child health outcomes in prior work.Methods: We meta-analysed results from four prospective U.S cohorts investigating the association between epigenetic age acceleration estimated using blood DNA methylation collected at birth and preschool age Childhood Behavior Checklist (CBCL) scores.Results: Epigenetic ageing was not significantly associated with CBCL total problem scores (β = 0.33, 95% CI: -0.95, 0.28) and DSM-oriented pervasive development problem scores (β = -0.23, 95% CI: -0.61, 0.15). No associations were observed for other DSM-oriented subscales.Conclusions: The meta-analysis results suggest that epigenetic gestational age acceleration is not associated with child emotional and behavioural functioning for preschool age group. These findings may relate to our study population, which includes two cohorts enriched for ASD and one preterm birth cohort.; future work should address the role of epigenetic age in child health in other study populations.Abbreviations: DNAm: DNA methylation; CBCL: Child Behavioral Checklist; ECHO: Environmental Influences on Child Health Outcomes; EARLI: Early Autism Risk Longitudinal Investigation; MARBLES: Markers of Autism Risk in Babies - Learning Early Signs; ELGAN: Extremely Low Gestational Age Newborns; ASD: autism spectrum disorder; BMI: body mass index; DSM: Diagnostic and Statistical Manual of Mental Disorders.

Sex-based differences in placental DNA methylation profiles related to gestational age: an NIH ECHO meta-analysis

The placenta undergoes many changes throughout gestation to support the evolving needs of the foetus. There is also a growing appreciation that male and female foetuses develop differently in utero, with unique epigenetic changes in placental tissue. Here, we report meta-analysed sex-specific associations between gestational age and placental DNA methylation from four cohorts in the National Institutes of Health (NIH) Environmental influences on Child Health Outcomes (ECHO) Programme (355 females/419 males, gestational ages 23-42 weeks). We identified 407 cytosine-guanine dinucleotides (CpGs) in females and 794 in males where placental methylation levels were associated with gestational age. After cell-type adjustment, 55 CpGs in females and 826 in males were significant. These were enriched for biological processes critical to the immune system in females and transmembrane transport in males. Our findings are distinct between the sexes: in females, associations with gestational age are largely explained by differences in placental cellular composition, whereas in males, gestational age is directly associated with numerous alterations in methylation levels.

Cumulative stress, PTSD, and emotion dysregulation during pregnancy and epigenetic age acceleration in Hispanic mothers and their newborn infants

Pregnancy can exacerbate or prompt the onset of stress-related disorders, such as post-traumatic stress disorder (PTSD). PTSD is associated with heightened stress responsivity and emotional dysregulation, as well as increased risk of chronic disorders and mortality. Further, maternal PTSD is associated with gestational epigenetic age acceleration in newborns, implicating the prenatal period as a developmental time period for the transmission of effects across generations. Here, we evaluated the associations between PTSD symptoms, maternal epigenetic age acceleration, and infant gestational epigenetic age acceleration in 89 maternal-neonatal dyads. Trauma-related experiences and PTSD symptoms in mothers were assessed during the third trimester of pregnancy. The MethylationEPIC array was used to generate DNA methylation data from maternal and neonatal saliva samples collected within 24 h of infant birth. Maternal epigenetic age acceleration was calculated using Horvath's multi-tissue clock, PhenoAge and GrimAge. Gestational epigenetic age was estimated using the Haftorn clock. Maternal cumulative past-year stress (GrimAge: p = 3.23e-04, PhenoAge: p = 9.92e-03), PTSD symptoms (GrimAge: p = 0.019), and difficulties in emotion regulation (GrimAge: p = 0.028) were associated with accelerated epigenetic age in mothers. Maternal PTSD symptoms were associated with lower gestational epigenetic age acceleration in neonates (p = 0.032). Overall, our results suggest that maternal cumulative past-year stress exposure and trauma-related symptoms may increase the risk for age-related problems in mothers and developmental problems in their newborns.

Accelerated Aging and the Life Course of Individuals Born Preterm

Individuals born preterm have shorter lifespans and elevated rates of chronic illness that contribute to mortality risk when compared to individuals born at term. Emerging evidence suggests that individuals born preterm or of low birthweight also exhibit physiologic and cellular biomarkers of accelerated aging. It is unclear whether, and to what extent, accelerated aging contributes to a higher risk of chronic illness and mortality among individuals born preterm. Here, we review accelerated aging phenotypes in adults born preterm and biological pathways that appear to contribute to accelerated aging. We highlight biomarkers of accelerated aging and various resiliency factors, including both pharmacologic and non-pharmacologic factors, that might buffer the propensity for accelerated aging among individuals born preterm.

The application of epiphenotyping approaches to DNA methylation array studies of the human placenta

BACKGROUND

Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied.

RESULTS

Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry-informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, as well as over very long placental processing times. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component.

CONCLUSIONS

This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. We further demonstrate the specific utility of epiphenotyping tools developed for use with placental DNAme data, and show that these variables (i) provide an independent check of clinically obtained data and (ii) provide a robust approach to compare variables across different datasets. Finally, we present a general framework for the processing and analysis of placental DNAme data, integrating the epiphenotype variables discussed here.

eoPred: predicting the placental phenotype of early-onset preeclampsia using public DNA methylation data

Background: A growing body of literature has reported molecular and histological changes in the human placenta in association with preeclampsia (PE). Placental DNA methylation (DNAme) and transcriptomic patterns have revealed molecular subgroups of PE that are associated with placental histopathology and clinical phenotypes of the disease. However, the clinical and molecular heterogeneity of PE both across and within subtypes complicates the study of this disease. PE is most strongly associated with placental pathology and adverse fetal and maternal outcomes when it develops early in pregnancy. We focused on placentae from pregnancies affected by preeclampsia that were delivered before 34 weeks of gestation to develop eoPred, a predictor of the DNAme signature associated with the placental phenotype of early-onset preeclampsia (EOPE). Results: Public data from 83 placental samples (HM450K), consisting of 42 EOPE and 41 normotensive preterm birth (nPTB) cases, was used to develop eoPred-a supervised model that relies on a highly discriminative 45 CpG DNAme signature of EOPE in the placenta. The performance of eoPred was assessed using cross-validation (AUC = 0.95) and tested in an independent validation cohort (n = 49, AUC = 0.725). A subset of fetal growth restriction (FGR) and late-PE cases showed a similar DNAme profile at the 45 predictive CpGs, consistent with the overlap in placental pathology between these conditions. The relationship between the EOPE probability generated by eoPred and various phenotypic variables was also assessed, revealing that it is associated with gestational age, and it is not driven by cell composition differences. Conclusion: eoPred relies on a 45-CpG DNAme signature to predict a homogeneous placental phenotype of EOPE in a discrete or continuous manner. Using this classifier should 1) aid in the study of placental insufficiency and improve the consistency of future placental DNAme studies of PE, 2) facilitate identifying the placental phenotype of EOPE in public data sets and 3) importantly, standardize the placental diagnosis of EOPE to allow better cross-cohort comparisons. Lastly, classification of cases with eoPred will be useful for investigating the relationship between placental pathology and genetic or environmental variables.

Evaluation of pediatric epigenetic clocks across multiple tissues

BACKGROUND

Epigenetic clocks are promising tools for assessing biological age. We assessed the accuracy of pediatric epigenetic clocks in gestational and chronological age determination.

RESULTS

Our study used data from seven tissue types on three DNA methylation profiling microarrays and found that the Knight and Bohlin clocks performed similarly for blood cells, while the Lee clock was superior for placental samples. The pediatric-buccal-epigenetic clock performed the best for pediatric buccal samples, while the Horvath clock is recommended for children's blood cell samples. The NeoAge clock stands out for its unique ability to predict post-menstrual age with high correlation with the observed age in infant buccal cell samples.

CONCLUSIONS

Our findings provide valuable guidance for future research and development of epigenetic clocks in pediatric samples, enabling more accurate assessments of biological age.

Sexually dimorphic methylation patterns characterize the placenta and blood from extremely preterm newborns

BACKGROUND

Health outcomes among children born prematurely are known to be sexually dimorphic, with male infants often more affected, yet the mechanism behind this observation is not clear. CpG methylation levels in the placenta and blood also differ by sex and are associated with adverse health outcomes. We contrasted CpG methylation levels in the placenta and neonatal blood (n = 358) from the Extremely Low Gestational Age Newborn (ELGAN) cohort based on the EPIC array, which assays over 850,000 CpG sites across the epigenome. Sex-specific epigenome-wide association analyses were conducted for the placenta and neonatal blood samples independently, and the results were compared to determine tissue-specific differences between the methylation patterns in males and females. All models were adjusted for cell type heterogeneity. Enrichment pathway analysis was performed to identify the biological functions of genes related to the sexually dimorphic CpG sites.

RESULTS

Approximately 11,500 CpG sites were differentially methylated in relation to sex. Of these, 5949 were placenta-specific and 5361 were blood-specific, with only 233 CpG sites overlapping in both tissues. For placenta-specific CpG sites, 90% were hypermethylated in males. For blood-specific CpG sites, 95% were hypermethylated in females. In the placenta, keratinocyte differentiation biological pathways were enriched among the differentially methylated genes. No enrichment pathways were observed for blood.

CONCLUSIONS

Distinct methylation patterns were observed between male and female children born extremely premature, and keratinocyte differentiation pathways were enriched in the placenta. These findings provide new insights into the epigenetic mechanisms underlying sexually dimorphic health outcomes among extremely premature infants.

Stability selection enhances feature selection and enables accurate prediction of gestational age using only five DNA methylation sites

BACKGROUND

DNA methylation (DNAm) is robustly associated with chronological age in children and adults, and gestational age (GA) in newborns. This property has enabled the development of several epigenetic clocks that can accurately predict chronological age and GA. However, the lack of overlap in predictive CpGs across different epigenetic clocks remains elusive. Our main aim was therefore to identify and characterize CpGs that are stably predictive of GA.

RESULTS

We applied a statistical approach called 'stability selection' to DNAm data from 2138 newborns in the Norwegian Mother, Father, and Child Cohort study. Stability selection combines subsampling with variable selection to restrict the number of false discoveries in the set of selected variables. Twenty-four CpGs were identified as being stably predictive of GA. Intriguingly, only up to 10% of the CpGs in previous GA clocks were found to be stably selected. Based on these results, we used generalized additive model regression to develop a new GA clock consisting of only five CpGs, which showed a similar predictive performance as previous GA clocks (R2 = 0.674, median absolute deviation = 4.4 days). These CpGs were in or near genes and regulatory regions involved in immune responses, metabolism, and developmental processes. Furthermore, accounting for nonlinear associations improved prediction performance in preterm newborns.

CONCLUSION

We present a methodological framework for feature selection that is broadly applicable to any trait that can be predicted from DNAm data. We demonstrate its utility by identifying CpGs that are highly predictive of GA and present a new and highly performant GA clock based on only five CpGs that is more amenable to a clinical setting.

The influence of early environment and micronutrient availability on developmental epigenetic programming: lessons from the placenta

DNA methylation is the most commonly studied epigenetic mark in humans, as it is well recognised as a stable, heritable mark that can affect genome function and influence gene expression. Somatic DNA methylation patterns that can persist throughout life are established shortly after fertilisation when the majority of epigenetic marks, including DNA methylation, are erased from the pre-implantation embryo. Therefore, the period around conception is potentially critical for influencing DNA methylation, including methylation at imprinted alleles and metastable epialleles (MEs), loci where methylation varies between individuals but is correlated across tissues. Exposures before and during conception can affect pregnancy outcomes and health throughout life. Retrospective studies of the survivors of famines, such as those exposed to the Dutch Hunger Winter of 1944-45, have linked exposures around conception to later disease outcomes, some of which correlate with DNA methylation changes at certain genes. Animal models have shown more directly that DNA methylation can be affected by dietary supplements that act as cofactors in one-carbon metabolism, and in humans, methylation at birth has been associated with peri-conceptional micronutrient supplementation. However, directly showing a role of micronutrients in shaping the epigenome has proven difficult. Recently, the placenta, a tissue with a unique hypomethylated methylome, has been shown to possess great inter-individual variability, which we highlight as a promising target tissue for studying MEs and mixed environmental exposures. The placenta has a critical role shaping the health of the fetus. Placenta-associated pregnancy complications, such as preeclampsia and intrauterine growth restriction, are all associated with aberrant patterns of DNA methylation and expression which are only now being linked to disease risk later in life.

The application of epiphenotyping approaches to DNA methylation array studies of the human placenta

Background : Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied. Results : Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, but reassuringly were robust to placental processing time. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component. Conclusions : This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. Further, we demonstrate that estimating epiphenotype variables from the DNAme data itself, when possible, provides both an independent check of clinically-obtained data and can provide a robust approach to compare variables across different datasets.

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.

Associations of stress and stress-related psychiatric disorders with GrimAge acceleration: review and suggestions for future work

The notion of "biological aging" as distinct from chronological aging has been of increasing interest in psychiatry, and many studies have explored associations of stress and psychiatric illness with accelerated biological aging. The "epigenetic clocks" are one avenue of this research, wherein "biological age" is estimated using DNA methylation data from specific CpG dinucleotide sites within the human genome. Many iterations of the epigenetic clocks have been developed, but the GrimAge clock continues to stand out for its ability to predict morbidity and mortality. Several studies have now explored associations of stress, PTSD, and MDD with GrimAge acceleration (GrimAA). While stress, PTSD, and MDD are distinct psychiatric entities, they may share common mechanisms underlying accelerated biological aging. Yet, no one has offered a review of the evidence on associations of stress and stress-related psychopathology with GrimAA. In this review, we identify nine publications on associations of stress, PTSD, and MDD with GrimAA. We find that results are mixed both within and across each of these exposures. However, we also find that analytic methods - and specifically, the choice of covariates - vary widely between studies. To address this, we draw upon popular methods from the field of clinical epidemiology to offer (1) a systematic framework for covariate selection, and (2) an approach to results reporting that facilitates analytic consensus. Although covariate selection will differ by the research question, we encourage researchers to consider adjustment for tobacco, alcohol use, physical activity, race, sex, adult socioeconomic status, medical comorbidity, and blood cell composition.

Epigenetic gestational age and the relationship with developmental milestones in early childhood

Shorter gestational age (GA) is a risk factor of developmental delay. GA is usually estimated clinically from last menstrual period and ultrasound. DNA methylation (DNAm) estimates GA using sets of cytosine-guanine-sites coupled with a clock algorithm. Therefore, DNAm-estimated GA may better reflect biological maturation. A DNAm GA greater than clinical GA, known as gestational age acceleration (GAA), may indicate epigenetic maturity and holds potential as an early biomarker for developmental delay risk. We used data from the Upstate KIDS Study to examine associations of DNAm GA and developmental delay within the first 3 years based on the Ages & Stages Questionnaire® (n = 1010). We estimated DNAm GA using two clocks specific to the Illumina Methylation EPIC 850K, the Haftorn clock and one developed from the Effects of Aspirin in Gestation and Reproduction study, in which women were followed to detect pregnancy at the earliest time possible. Among singletons, each week increase in DNAm GA was protective for overall delay (odds ratio:0.74; 95% confidence interval:0.61-0.90) and delay in all domains except for problem-solving skills. Among twins, we observed similar point estimates but lower precision. Results were similar for clinical GA. GAA was largely not associated with developmental delays. In summary, either DNAm GA or clinical GA at birth, but not epigenetic maturity (i.e. GAA), was associated with decreased odds of developmental delay in early childhood. Our study does not support using DNAm GA or GAA as separate risk factors for future risk of developmental delay within the first 3 years of age.

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.

Characterization of methylation profiles in spontaneous preterm birth placental villous tissue

Preterm birth is a global public health crisis which results in significant neonatal and maternal mortality. Yet little is known regarding the molecular mechanisms of idiopathic spontaneous preterm birth, and we have few diagnostic markers for adequate assessment of placental development and function. Previous studies of placental pathology and our transcriptomics studies suggest a role for placental maturity in idiopathic spontaneous preterm birth. It is known that placental DNA methylation changes over gestation. We hypothesized that if placental hypermaturity is present in our samples, we would observe a unique idiopathic spontaneous preterm birth DNA methylation profile potentially driving the gene expression differences we previously identified in our placental samples. Our results indicate the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern suggesting hypermaturity. Only seven significant differentially methylated regions fitting the idiopathic spontaneous preterm birth specific (relative to the controls) profile were identified, indicating unusually high similarity in DNA methylation between idiopathic spontaneous preterm birth and term birth samples. We identified an additional 1,718 significantly methylated regions in our gestational age matched controls where the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern, again indicating a striking level of similarity between the idiopathic spontaneous preterm birth and term birth samples. Pathway analysis of these regions revealed differences in genes within the WNT and Cadherin signaling pathways, both of which are essential in placental development and maturation. Taken together, these data demonstrate that the idiopathic spontaneous preterm birth samples display a hypermature methylation signature than expected given their respective gestational age which likely impacts birth timing.

Epigenetic clocks and female fertility timeline: A new approach to an old issue?

Worldwide increase in life expectancy has boosted research on aging. Overcoming the concept of chronological age, higher attention has been addressed to biological age, which reflects a person's real health state, and which may be the resulting combination of both intrinsic and environmental factors. As epigenetics may exert a pivotal role in the biological aging, epigenetic clocks were developed. They are based on mathematical models aimed at identifying DNA methylation patterns that can define the biological age and that can be adopted for different clinical scopes (i.e., estimation of the risks of developing age-related disorders or predicting lifespan). Recently, epigenetic clocks have gained a peculiar attention in the fertility research field, in particular in the female counterpart. The insight into the possible relations between epigenetic aging and women's infertility might glean additional information about certain conditions that are still not completely understood. Moreover, they could disclose significant implications for health promotion programs in infertile women. Of relevance here is that the impact of biological age and epigenetics may not be limited to fertility status but could translate into pregnancy issues. Indeed, epigenetic alterations of the mother may transfer into the offspring, and pregnancy itself as well as related complications could contribute to epigenetic modifications in both the mother and newborn. However, even if the growing interest has culminated in the conspicuous production of studies on these topics, a global overview and the availability of validated instruments for diagnosis is still missing. The present narrative review aims to explore the possible bonds between epigenetic aging and fertility timeline. In the "infertility" section, we will discuss the advances on epigenetic clocks focusing on the different tissues examined (endometrium, peripheral blood, ovaries). In the "pregnancy" section, we will discuss the results obtained from placenta, umbilical cord and peripheral blood. The possible role of epigenetic aging on infertility mechanisms and pregnancy outcomes represents a question that may configure epigenetic clock as a bond between two apparently opposite worlds: infertility and pregnancy.

Select Early-Life Environmental Exposures and DNA Methylation in the Placenta

PURPOSE OF REVIEW

To summarize recent literature relating early-life environmental exposures on DNA methylation in the placenta, to identify how variation in placental methylation is regulated in an exposure-specific manner, and to encourage additional work in this area.

RECENT FINDINGS

Multiple studies have evaluated associations between prenatal environmental exposures and placental methylation in both gene-specific and epigenome-wide frameworks. Specific exposures lead to unique variability in methylation, and cross-exposure assessments have uncovered certain genes that demonstrate consistency in differential placental methylation. Exposure studies that assess methylation effects in a trimester-specific approach tend to find larger effects during the 1st trimester exposure. Earlier studies have more targeted gene-specific approaches to methylation, while later studies have shifted towards epigenome-wide, array-based approaches. Studies focusing on exposures such as air pollution, maternal smoking, environmental contaminants, and trace metals appear to be more abundant, while studies of socioeconomic adversity and circadian disruption are scarce but demonstrate remarkable effects. Understanding the impacts of early-life environmental exposures on placental methylation is critical to establishing the link between the maternal environment, epigenetic variation, and long-term health. Future studies into this field should incorporate repeated measures of exposure throughout pregnancy, in order to determine the critical windows in which placental methylation is most heavily affected. Additionally, the use of methylation-based scores and sequencing technology could provide important insights into epigenetic gestational age and uncovering more genomic regions where methylation is affected. Studies examining the impact of other exposures on methylation, including pesticides, alcohol, and other chemicals are also warranted.

A human stem cell-derived neuronal model of morphine exposure reflects brain dysregulation in opioid use disorder: Transcriptomic and epigenetic characterization of postmortem-derived iPSC neurons

Introduction

Human-derived induced pluripotent stem cell (iPSC) models of brain promise to advance our understanding of neurotoxic consequences of drug use. However, how well these models recapitulate the actual genomic landscape and cell function, as well as the drug-induced alterations, remains to be established. New in vitro models of drug exposure are needed to advance our understanding of how to protect or reverse molecular changes related to substance use disorders.

Methods

We engineered a novel induced pluripotent stem cell-derived model of neural progenitor cells and neurons from cultured postmortem human skin fibroblasts, and directly compared these to isogenic brain tissue from the donor source. We assessed the maturity of the cell models across differentiation from stem cells to neurons using RNA cell type and maturity deconvolution analyses as well as DNA methylation epigenetic clocks trained on adult and fetal human tissue. As proof-of-concept of this model's utility for substance use disorder studies, we compared morphine- and cocaine-treated neurons to gene expression signatures in postmortem Opioid Use Disorder (OUD) and Cocaine Use Disorder (CUD) brains, respectively.

Results

Within each human subject (N = 2, 2 clones each), brain frontal cortex epigenetic age parallels that of skin fibroblasts and closely approximates the donor's chronological age; stem cell induction from fibroblast cells effectively sets the epigenetic clock to an embryonic age; and differentiation of stem cells to neural progenitor cells and then to neurons progressively matures the cells via DNA methylation and RNA gene expression readouts. In neurons derived from an individual who died of opioid overdose, morphine treatment induced alterations in gene expression similar to those previously observed in OUD ex-vivo brain tissue, including differential expression of the immediate early gene EGR1, which is known to be dysregulated by opioid use.

Discussion

In summary, we introduce an iPSC model generated from human postmortem fibroblasts that can be directly compared to corresponding isogenic brain tissue and can be used to model perturbagen exposure such as that seen in opioid use disorder. Future studies with this and other postmortem-derived brain cellular models, including cerebral organoids, can be an invaluable tool for understanding mechanisms of drug-induced brain alterations.

DNA methylation in peripheral blood leukocytes for the association with glucose metabolism and invasive breast cancer

BACKGROUND

Insulin resistance (IR) is a well-established factor for breast cancer (BC) risk in postmenopausal women, but the interrelated molecular pathways on the methylome are not explicitly described. We conducted a population-level epigenome-wide association (EWA) study for DNA methylation (DNAm) probes that are associated with IR and prospectively correlated with BC development, both overall and in BC subtypes among postmenopausal women.

METHODS

We used data from Women's Health Initiative (WHI) ancillary studies for our EWA analyses and evaluated the associations of site-specific DNAm across the genome with IR phenotypes by multiple regressions adjusting for age and leukocyte heterogeneities. For our analysis of the top 20 IR-CpGs with BC risk, we used the WHI and the Cancer Genomic Atlas (TCGA), using multiple Cox proportional hazards and logit regressions, respectively, accounting for age, diabetes, obesity, leukocyte heterogeneities, and tumor purity (for TCGA). We further conducted a Gene Set Enrichment Analysis.

RESULTS

We detected several EWA-CpGs in TXNIP, CPT1A, PHGDH, and ABCG1. In particular, cg19693031 in TXNIP was replicated in all IR phenotypes, measured by fasting levels of glucose, insulin, and homeostatic model assessment-IR. Of those replicated IR-genes, 3 genes (CPT1A, PHGDH, and ABCG1) were further correlated with BC risk; and 1 individual CpG (cg01676795 in POR) was commonly detected across the 2 cohorts.

CONCLUSIONS

Our study contributes to better understanding of the interconnected molecular pathways on the methylome between IR and BC carcinogenesis and suggests potential use of DNAm markers in the peripheral blood cells as preventive targets to detect an at-risk group for IR and BC in postmenopausal women.

Cadmium inhibits differentiation of human trophoblast stem cells into extravillous trophoblasts and disrupts epigenetic changes within the promoter region of the HLA-G gene

Cadmium (Cd) is a toxic heavy metal widely distributed in the environment. Maternal whole-blood Cd levels during pregnancy are positively associated with the risk of early preterm birth. We hypothesized that Cd inhibits trophoblast differentiation, resulting in the development of hypertensive disorders of pregnancy and a high risk of early preterm birth. Using the CT27 human trophoblast stem cell line, we found that exposing these cells to 0.1-0.4 µM Cd inhibited their differentiation into extravillous cytotrophoblasts (EVTs). Supporting this finding, we found that expression of the metal-binding protein metallothionein, which suppresses the toxicity of Cd, is low in EVTs. We also found that Cd exposure changes the methylation status of the promoter region of the HLA-G gene, which is specifically expressed in EVTs. Together, these results suggest that Cd inhibits placental formation by suppressing trophoblast differentiation into EVTs. This suppression may underlie the increased risk of gestational hypertension in women with high whole-blood Cd levels.

Profiling placental DNA methylation associated with maternal SSRI treatment during pregnancy

Selective serotonin reuptake inhibitors (SSRIs) for treatment of prenatal maternal depression have been associated with neonatal neurobehavioral disturbances, though the molecular mechanisms remain poorly understood.  In utero exposure to SSRIs may affect DNA methylation (DNAme) in the human placenta, an epigenetic mark that is established during development and is associated with gene expression. Chorionic villus samples from 64 human placentas were profiled with the Illumina MethylationEPIC BeadChip; clinical assessments of maternal mood and SSRI treatment records were collected at multiple time points during pregnancy. Case distribution was 20 SSRI-exposed cases and 44 SSRI non-exposed cases. Maternal depression was defined using a mean maternal Hamilton Depression score > 8 to indicate symptomatic depressed mood ("maternally-depressed"), and we further classified cases into SSRI-exposed, maternally-depressed (n = 14); SSRI-exposed, not maternally-depressed (n = 6); SSRI non-exposed, maternally-depressed (n = 20); and SSRI non-exposed, not maternally-depressed (n = 24). For replication, Illumina 450K DNAme profiles were obtained from 34 additional cases from an independent cohort (n = 17 SSRI-exposed, n = 17 SSRI non-exposed). No CpGs were differentially methylated at FDR < 0.05 comparing SSRI-exposed to non-exposed placentas, in a model adjusted for mean maternal Hamilton Depression score, or in a model restricted to maternally-depressed cases with and without SSRI exposure. However, at a relaxed threshold of FDR < 0.25, five CpGs were differentially methylated (|Δβ| > 0.03) by SSRI exposure status. Four were covered by the replication cohort measured by the 450K array, but none replicated. No CpGs were differentially methylated (FDR < 0.25) comparing maternally depressed to not depressed cases. In sex-stratified analyses for SSRI-exposed versus non-exposed cases (females n = 31; males n = 33), three additional CpGs in females, but none in males, were differentially methylated at the relaxed FDR < 0.25 cut-off. We did not observe large-scale alterations of DNAme in placentas exposed to maternal SSRI treatment, as compared to placentas with no SSRI exposure. We also found no evidence for altered DNAme in maternal depression-exposed versus depression non-exposed placentas. This novel work in a prospectively-recruited cohort with clinician-ascertained SSRI exposure and mood assessments would benefit from future replication.

Placental epigenetic gestational aging in relation to maternal sociodemographic factors and smoking among infants born extremely preterm: a descriptive study

Social determinants of health (SDoH) are defined as the conditions in which people are born, grow, live, work, and age. The distribution of these conditions is influenced by underlying structural factors and may be linked to adverse pregnancy outcomes through epigenetic modifications of gestational tissues. A promising modification is epigenetic gestational age (eGA), which captures 'biological' age at birth. Measuring eGA in placenta, an organ critical for foetal development, may provide information about how SDoH 'get under the skin' during pregnancy to influence birth outcomes and ethnic/racial disparities. We examined relationships of placental eGA with sociodemographic factors, smoking, and two key clinical outcomes: Apgar scores and NICU length of stay. Using the Robust Placental Clock, we estimated eGA for placental samples from the Extremely Low Gestational Age Newborns cohort (N = 408). Regression modelling revealed smoking during pregnancy was associated with placental eGA acceleration (i.e., eGA higher than chronologic gestational age). This association differed by maternal race: among infants born to mothers racialized as Black, we observed greater eGA acceleration (+0.89 week, 95% CI: 0.38, 1.40) as compared to those racialized as white (+0.27 week, 95% CI: -0.06, 0.59). Placental eGA acceleration was also correlated with shorter NICU lengths of stay, but only among infants born to mothers racialized as Black (-0.08 d/week-eGA, 95% CI: -0.12, -0.05). Together, these observed associations suggest that interpretations of epigenetic gestational aging may be tissue-specific.

Evaluation of different computational methods for DNA methylation-based biological age

In recent years there has been a widespread interest in researching biomarkers of aging that could predict physiological vulnerability better than chronological age. Aging, in fact, is one of the most relevant risk factors for a wide range of maladies, and molecular surrogates of this phenotype could enable better patients stratification. Among the most promising of such biomarkers is DNA methylation-based biological age. Given the potential and variety of computational implementations (epigenetic clocks), we here present a systematic review of such clocks. Furthermore, we provide a large-scale performance comparison across different tissues and diseases in terms of age prediction accuracy and age acceleration, a measure of deviance from physiology. Our analysis offers both a state-of-the-art overview of the computational techniques developed so far and a heterogeneous picture of performances, which can be helpful in orienting future research.

Prenatal Exposure to Ambient Air Pollution and Epigenetic Aging at Birth in Newborns

In utero air pollution exposure has been associated with adverse birth outcomes, yet effects of air pollutants on regulatory mechanisms in fetal growth and critical windows of vulnerability during pregnancy are not well understood. There is evidence that epigenetic alterations may contribute to these effects. DNA methylation (DNAm) based age estimators have been developed and studied extensively with health outcomes in recent years. Growing literature suggests environmental factors, such as air pollution and smoking, can influence epigenetic aging. However, little is known about the effect of prenatal air pollution exposure on epigenetic aging. In this study, we leveraged existing data on prenatal air pollution exposure and cord blood DNAm from 332 mother-child pairs in the Early Autism Risk Longitudinal Investigation (EARLI) and Markers of Autism Risk in Babies-Learning Early Signs (MARBLES), two pregnancy cohorts enrolling women who had a previous child diagnosed with autism spectrum disorder, to assess the relationship of prenatal exposure to air pollution and epigenetic aging at birth. DNAm age was computed using existing epigenetic clock algorithms for cord blood tissue-Knight and Bohlin. Epigenetic age acceleration was defined as the residual of regressing chronological gestational age on DNAm age, accounting for cell type proportions. Multivariable linear regression models and distributed lag models (DLMs), adjusting for child sex, maternal race/ethnicity, study sites, year of birth, maternal education, were completed. In the single-pollutant analysis, we observed exposure to PM2.5, PM10, and O3 during preconception period and pregnancy period were associated with decelerated epigenetic aging at birth. For example, pregnancy average PM10 exposure (per 10 unit increase) was associated with epigenetic age deceleration at birth (weeks) for both Knight and Bohlin clocks (β = -0.62, 95% CI: -1.17, -0.06; β = -0.32, 95% CI: -0.63, -0.01, respectively). Weekly DLMs revealed that increasing PM2.5 during the first trimester and second trimester were associated with decelerated epigenetic aging and that increasing PM10 during the preconception period was associated with decelerated epigenetic aging, using the Bohlin clock estimate. Prenatal ambient air pollution exposure, particularly in early and mid-pregnancy, was associated with decelerated epigenetic aging at birth.

Large-scale placenta DNA methylation integrated analysis reveals fetal sex-specific differentially methylated CpG sites and regions

Although male–female differences in placental structure and function have been observed, little is understood about their molecular underpinnings. Here, we present a mega-analysis of 14 publicly available placenta DNA methylation (DNAm) microarray datasets to identify individual CpGs and regions associated with fetal sex. In the discovery dataset of placentas from full term pregnancies (N = 532 samples), 5212 CpGs met genome-wide significance (p < 1E−8) and were enriched in pathways such as keratinization (FDR p-value = 7.37E−14), chemokine activity (FDR p-value = 1.56E−2), and eosinophil migration (FDR p-value = 1.83E−2). Nine differentially methylated regions were identified (fwerArea < 0.1) including a region in the promoter of ZNF300 that showed consistent differential DNAm in samples from earlier timepoints in pregnancy and appeared to be driven predominately by effects in the trophoblast cell type. We describe the largest study of fetal sex differences in placenta DNAm performed to date, revealing genes and pathways characterizing sex-specific placenta function and health outcomes later in life.

DNA Methylation, Aging, and Cancer Risk: A Mini-Review

Accumulation of somatic mutations and genomic instability are hallmarks of both aging and cancer. Epigenetic alterations occur across cell types and tissues with advancing age. DNA methylation-based estimates of biologic age can predict important age-related outcomes, including risk of frailty and mortality, and most recently have been shown to be associated with risk of developing cancer. In this mini-review, we examine pathways known to exhibit altered methylation in aging tissues, pre-malignant lesions, and tumors and review methodologies of epigenetic clocks that reliably predict cancer risk, including those derived from methylation studies of peripheral blood, as well as those methylation levels from within the tissues at high risk of cancer.